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1. A method for transmitting interactive television information over a television broadcast, comprising: compiling business data into a binary form, the business data comprising descriptions of products, wherein said business data is compiled for use by a set-top box; generating a script using a script authoring tool, wherein said compiled business data is processed according to said generated script independent from a further user interaction; and transmitting a stream, comprising the compiled business data and the script, to a receiver for generating video information for a user's television, wherein the receiver uses the script to access the compiled business data and generate a presentation of the products for the user.

1. A method for transmitting interactive television information over a television broadcast, comprising: compiling business data into a binary form, the business data comprising descriptions of products, wherein said business data is compiled for use by a set-top box; generating a script using a script authoring tool, wherein said compiled business data is processed according to said generated script independent from a further user interaction; and transmitting a stream, comprising the compiled business data and the script, to a receiver for generating video information for a user's television, wherein the receiver uses the script to access the compiled business data and generate a presentation of the products for the user. 28. The method as described in claim 1 , wherein the compiled business data transmitted are updated as data changes by recompiling the business data into the television broadcast, eliminating the need to generate said script.

1. A method for providing multi-media conferencing, the method comprising: receiving textual information for display during a conference session among a plurality of participants; retrieving configuration information specifying language assistance for the textual information, wherein the configuration information is associated with one of the participants; augmenting the textual information according to the configuration information for comprehension of the textual information by the one participant, wherein the augmenting of the textual information includes determining whether the textual information is contained in a predetermined list of terms and associated supplemental information, wherein the supplemental information includes definitions of the corresponding terms, and marking the textual information to notify the one participant that the supplemental information is available for selective display if the textual information is in the list; and forwarding the textual information having the marking to the one participant for display during the conference session without replacement of the textual information.

1. A method for providing multi-media conferencing, the method comprising: receiving textual information for display during a conference session among a plurality of participants; retrieving configuration information specifying language assistance for the textual information, wherein the configuration information is associated with one of the participants; augmenting the textual information according to the configuration information for comprehension of the textual information by the one participant, wherein the augmenting of the textual information includes determining whether the textual information is contained in a predetermined list of terms and associated supplemental information, wherein the supplemental information includes definitions of the corresponding terms, and marking the textual information to notify the one participant that the supplemental information is available for selective display if the textual information is in the list; and forwarding the textual information having the marking to the one participant for display during the conference session without replacement of the textual information. 3. A method according to claim 1 , wherein one of the terms is an acronym.

19. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for: defining a query, the query posing a question having an answer formed of terms from the electronic documents; creating one or more hypothetical facts in response to the query and the electronic documents, each hypothetical fact representing a possible answer to the query, wherein creating one or more hypothetical facts in response to the query comprises: parsing the query to filter out noise words and produce filtered terms; searching a repository of facts comprising attributes and values to identify attributes corresponding to the filtered terms; searching the electronic documents to identify terms that frequently appear near the filtered terms; and forming one or more hypothetical facts responsive to the attributes corresponding to the filtered terms and the terms that frequently appear near the filtered terms in the electronic documents; corroborating the one or more hypothetical facts using the electronic documents to identify a likely correct fact; and presenting the identified likely correct fact as the answer to the query.

19. A non-transitory computer readable storage medium storing one or more programs configured for execution by a computer, the one or more programs comprising instructions for: defining a query, the query posing a question having an answer formed of terms from the electronic documents; creating one or more hypothetical facts in response to the query and the electronic documents, each hypothetical fact representing a possible answer to the query, wherein creating one or more hypothetical facts in response to the query comprises: parsing the query to filter out noise words and produce filtered terms; searching a repository of facts comprising attributes and values to identify attributes corresponding to the filtered terms; searching the electronic documents to identify terms that frequently appear near the filtered terms; and forming one or more hypothetical facts responsive to the attributes corresponding to the filtered terms and the terms that frequently appear near the filtered terms in the electronic documents; corroborating the one or more hypothetical facts using the electronic documents to identify a likely correct fact; and presenting the identified likely correct fact as the answer to the query. 22. The computer readable storage medium of claim 19 , further comprising instructions for: determining how many of the electronic documents support the hypothetical fact; identifying the hypothetical fact as likely correct if an amount of support for the hypothetical fact surpasses a threshold.

1. A method of processing a flow description document, the method comprising steps of: extracting, from a first flow description document, a first description which specifies services to be invoked by the first flow description document, and extracting, from a second flow description document, a second description which specifies services to be invoked by the second flow description document; detecting a common part between the first description of the first flow description document and the second description of the second flow description document, wherein services specified by the first description extracted from the first flow description document include one or more services among services specified by the second description extracted from the second flow description document; and rewriting the common part in the second flow description document into a reference to the common part in the first flow description document, wherein the reference includes identification information of the first flow description document, and information which specifies a start tag and end tag of the common part.

1. A method of processing a flow description document, the method comprising steps of: extracting, from a first flow description document, a first description which specifies services to be invoked by the first flow description document, and extracting, from a second flow description document, a second description which specifies services to be invoked by the second flow description document; detecting a common part between the first description of the first flow description document and the second description of the second flow description document, wherein services specified by the first description extracted from the first flow description document include one or more services among services specified by the second description extracted from the second flow description document; and rewriting the common part in the second flow description document into a reference to the common part in the first flow description document, wherein the reference includes identification information of the first flow description document, and information which specifies a start tag and end tag of the common part. 3. The method according to claim 1 , wherein in the detecting step, whether a WEB service interface document identical to an input WEB service interface document has already been registered is further determined, and if the identical WEB service interface document has not been registered, the input WEB service interface document is registered.

17. A computer-based system for recognizing handwriting, the computer comprising an input device, a memory module, a preprocessor unit, a front end unit and a modeling component, the system comprising: (a) means for receiving character signals into the preprocessor unit from the input device representing training observation sequences of sample characters; (b) means for sorting said character signals in the preprocessor unit according to lexemes which represent different writing styles for a given character, by mapping said sample characters in lexographic space, said lexographic space being a location in the memory module which contains one or more character-level feature vectors, to find high-level variations in said character signals; (c) means for generating sequences of feature vector signals in the front end unit representing feature vectors for said character signals by mapping in chirographic space, said chirographic space being a location in the memory module which contains one or more frame-level feature vectors; (d) means for generating Markov model signals in the modeling component representing hidden Markov models for said lexemes, each of said hidden Markov models having model parameter signals and one or more states, each of said states having emission transitions and non-emission transitions, wherein said generating means comprises: (i) means for initializing said model parameter signals in each of said hidden Markov models, said initializing means comprising: means for setting a length for said hidden Markov model; means for initializing state transition probabilities of said hidden Markov model to be uniform; means for tying one or more output probability distributions for said emission transitions for each of said states; means for assigning a Gaussian density distribution for each of one or more codebooks for each of said states; and means for alternatively initializing one or more mixture coefficients to be values-obtained from a statistical mixture model; and (ii) means for updating said model parameter signals in each of said hidden Markov models.

17. A computer-based system for recognizing handwriting, the computer comprising an input device, a memory module, a preprocessor unit, a front end unit and a modeling component, the system comprising: (a) means for receiving character signals into the preprocessor unit from the input device representing training observation sequences of sample characters; (b) means for sorting said character signals in the preprocessor unit according to lexemes which represent different writing styles for a given character, by mapping said sample characters in lexographic space, said lexographic space being a location in the memory module which contains one or more character-level feature vectors, to find high-level variations in said character signals; (c) means for generating sequences of feature vector signals in the front end unit representing feature vectors for said character signals by mapping in chirographic space, said chirographic space being a location in the memory module which contains one or more frame-level feature vectors; (d) means for generating Markov model signals in the modeling component representing hidden Markov models for said lexemes, each of said hidden Markov models having model parameter signals and one or more states, each of said states having emission transitions and non-emission transitions, wherein said generating means comprises: (i) means for initializing said model parameter signals in each of said hidden Markov models, said initializing means comprising: means for setting a length for said hidden Markov model; means for initializing state transition probabilities of said hidden Markov model to be uniform; means for tying one or more output probability distributions for said emission transitions for each of said states; means for assigning a Gaussian density distribution for each of one or more codebooks for each of said states; and means for alternatively initializing one or more mixture coefficients to be values-obtained from a statistical mixture model; and (ii) means for updating said model parameter signals in each of said hidden Markov models. 18. The system of claim 17, further comprising: (e) means for receiving test characters; (f) means for generating sequences of feature vectors for said test characters by mapping in chirographic space; (g) means for computing probabilities that said test characters can be generated by said hidden Markov models; and (h) means for decoding said test characters as recognized characters associated with said selected hidden Markov models having greatest probabilities.

1. A system operable for anchoring of and into at least one corpus disposed distally in a conduit, the system including a handling and manipulation shaft and a stranded tube having a plurality of wound coiled threads and a longitudinal axis, the system comprising: a tube tool associated with the stranded tube and navigated together therewith by the handling and manipulation shaft into engagement with the corpus, the tube tool being configured to unwind at least one wound coiled thread out of the plurality of wound threads as an unwound helically coiled thread by relative rotation against the stranded tube, and the unwound helically coiled thread(s) of the stranded tube being configured for anchoring of and into the corpus with rotational corkscrew-like translation and rotation, wherein the stranded tube has a direction of winding and when rotated in the direction of winding to unwind wound coiled threads, each unwound thread rotates about a respective unwound thread longitudinal axis, and the tube tool is configured to unwind the unwound threads in rotation along an unwound thread longitudinal axis which is disposed at an angle relative to the longitudinal axis of the stranded tube, and having a plurality of tube tool thread ducts oriented at a duct angle relative to the longitudinal axis for control of the angle.

1. A system operable for anchoring of and into at least one corpus disposed distally in a conduit, the system including a handling and manipulation shaft and a stranded tube having a plurality of wound coiled threads and a longitudinal axis, the system comprising: a tube tool associated with the stranded tube and navigated together therewith by the handling and manipulation shaft into engagement with the corpus, the tube tool being configured to unwind at least one wound coiled thread out of the plurality of wound threads as an unwound helically coiled thread by relative rotation against the stranded tube, and the unwound helically coiled thread(s) of the stranded tube being configured for anchoring of and into the corpus with rotational corkscrew-like translation and rotation, wherein the stranded tube has a direction of winding and when rotated in the direction of winding to unwind wound coiled threads, each unwound thread rotates about a respective unwound thread longitudinal axis, and the tube tool is configured to unwind the unwound threads in rotation along an unwound thread longitudinal axis which is disposed at an angle relative to the longitudinal axis of the stranded tube, and having a plurality of tube tool thread ducts oriented at a duct angle relative to the longitudinal axis for control of the angle. 7. The system of claim 1 , wherein the unwound stranded tube is configured to anchor a physical body.

6. The video tagging method of claim 5 , further comprising: receiving the incident-specific dictionary at the at least one video camera or the back-end server communicatively coupled to the at least one video camera; capturing video by the at least one video camera; tagging the captured video with the keywords from the incident-specific dictionary; and uploading the captured video with the tagged keywords.

6. The video tagging method of claim 5 , further comprising: receiving the incident-specific dictionary at the at least one video camera or the back-end server communicatively coupled to the at least one video camera; capturing video by the at least one video camera; tagging the captured video with the keywords from the incident-specific dictionary; and uploading the captured video with the tagged keywords. 7. The video tagging method of claim 6 , further comprising: searching a plurality of videos using the tagged keywords as search terms.

17. A text-to-imagery conversion system comprising: a processor; a memory coupled to the processor, the memory storing a text sentence that includes a verb phrase, wherein the text sentence is associated with a plurality of semantic roles; a text/image comparison module that is stored in the memory, the text/image comparison module comprising means for making a determination that no single image stored in a designated image database captures each of the plurality of semantic roles associated with the text sentence; and a text sentence analyzer that is stored in the memory, the text sentence analyzer comprising means for breaking the received text sentence into multiple sentence fragments, each of which is associated with a respective fragmented semantic role, wherein the received text sentence is broken into the multiple sentence fragments in response to making the determination, wherein the text/image comparison module further comprises means for identifying, amongst images stored in the designated image database, an image that captures one of the fragmented semantic roles.

17. A text-to-imagery conversion system comprising: a processor; a memory coupled to the processor, the memory storing a text sentence that includes a verb phrase, wherein the text sentence is associated with a plurality of semantic roles; a text/image comparison module that is stored in the memory, the text/image comparison module comprising means for making a determination that no single image stored in a designated image database captures each of the plurality of semantic roles associated with the text sentence; and a text sentence analyzer that is stored in the memory, the text sentence analyzer comprising means for breaking the received text sentence into multiple sentence fragments, each of which is associated with a respective fragmented semantic role, wherein the received text sentence is broken into the multiple sentence fragments in response to making the determination, wherein the text/image comparison module further comprises means for identifying, amongst images stored in the designated image database, an image that captures one of the fragmented semantic roles. 19. The text-to-imagery conversion system of claim 17 , further comprising a web server configured to receive the text sentence from a client device and submit a query to the designated image database, wherein the determination is made as a result of submitting the query to the designated image database.

13. The method of claim 8 , further comprising performing a negative model-based comment classification in the event that the context sentiment type is determined to be negative sentiment-entailing.

13. The method of claim 8 , further comprising performing a negative model-based comment classification in the event that the context sentiment type is determined to be negative sentiment-entailing. 14. The method of claim 13 , further comprising training a negative model-based classifier using training data comprising sample comment data known to be associated with negative sentiment-entailing contexts.

2. The method of claim 1 , wherein the processing further comprises: correlating the first and second roads with stored information to identify first and second route links associated with corresponding ones of the first and second roads; determining whether the first road intersects the second road; and constructing a portion of the routing graph that includes the identified route links when the first and second roads intersect, the identified route links being connected within the routing graph by a corresponding one of the nodes.

2. The method of claim 1 , wherein the processing further comprises: correlating the first and second roads with stored information to identify first and second route links associated with corresponding ones of the first and second roads; determining whether the first road intersects the second road; and constructing a portion of the routing graph that includes the identified route links when the first and second roads intersect, the identified route links being connected within the routing graph by a corresponding one of the nodes. 3. The method of claim 2 , wherein the correlating comprises: accessing the link information associated with the identified route links, the link information comprising connectivity information.

16. A method of detecting text in real-world images comprising: dividing an image representing a real-world scene into one or more regions; calculating a cascade of classifiers, the cascade comprising a plurality of stages, each stage including one or more weak classifiers, the plurality of stages organized to start out with classifiers that are most useful for ruling out non-text regions of the image; receiving training images; feeding the training images into the cascade; comparing classifier results to known training image results; and adapting one or more of an order of stages in the cascade, an order of classifiers in the stages, one or more classifier confidence level thresholds, and the classifiers by selecting features for each classifier that reduce a number of false positive and false negative detections by a reduced number of tests; feeding the one or more regions into the cascade; and removing regions of the image classified as the non-text regions from the cascade prior to completion of the cascade to avoid subsequent processing of the removed regions; and displaying a result.

16. A method of detecting text in real-world images comprising: dividing an image representing a real-world scene into one or more regions; calculating a cascade of classifiers, the cascade comprising a plurality of stages, each stage including one or more weak classifiers, the plurality of stages organized to start out with classifiers that are most useful for ruling out non-text regions of the image; receiving training images; feeding the training images into the cascade; comparing classifier results to known training image results; and adapting one or more of an order of stages in the cascade, an order of classifiers in the stages, one or more classifier confidence level thresholds, and the classifiers by selecting features for each classifier that reduce a number of false positive and false negative detections by a reduced number of tests; feeding the one or more regions into the cascade; and removing regions of the image classified as the non-text regions from the cascade prior to completion of the cascade to avoid subsequent processing of the removed regions; and displaying a result. 18. The method of claim 16 , further comprising utilizing two neighborhood thresholds: TLight=μ+kσ and TDark=μ−kσ where and μ and σ are the mean and variance within the selected neighborhood respectively, and k is a constant.

2. Apparatus according to claim 1, wherein said pattern recognition means includes classification means for providing distance values between the unknown pattern and at least one known pattern.

2. Apparatus according to claim 1, wherein said pattern recognition means includes classification means for providing distance values between the unknown pattern and at least one known pattern. 3. Apparatus according to claim 2, further comprising confidence level determining means for determining confidence level of said plural candidates based on the distance values from said classification means.

20. An electronic device for providing an audio menu to a user, comprising: a single sensing element for detecting user inputs; an audio output; and a processor operative to: direct the audio output to play back a first audio clip in a first manner; during the playback of the first audio clip in the first manner, receive from the single sensing element a first user input that is detected by the single sensing element; in response to the receiving the first user input, direct the audio output to alter the playback from the first manner to a second manner; during the playback of the first audio clip in the second manner, direct the audio output to play back a second audio clip to announce the first audio clip; and after the playback of the second audio clip, direct the audio output to play back a first menu audio clip that is associated with the audio menu.

20. An electronic device for providing an audio menu to a user, comprising: a single sensing element for detecting user inputs; an audio output; and a processor operative to: direct the audio output to play back a first audio clip in a first manner; during the playback of the first audio clip in the first manner, receive from the single sensing element a first user input that is detected by the single sensing element; in response to the receiving the first user input, direct the audio output to alter the playback from the first manner to a second manner; during the playback of the first audio clip in the second manner, direct the audio output to play back a second audio clip to announce the first audio clip; and after the playback of the second audio clip, direct the audio output to play back a first menu audio clip that is associated with the audio menu. 31. The electronic device of claim 20 , wherein the processor is further operative to, after the directing the audio output to play back the second audio clip, but before the directing the audio output to play back the first menu audio clip: direct the audio output to play back a third audio clip to indicate an end of the announcing of the first audio clip.

8. A computer-implemented method, comprising: determining, by one or more computing systems, a plurality of social interactions associated with a plurality of people, each social interaction comprising a particular person interacting with a particular social object of a plurality of social objects; generating, by the one or more computing systems, a social object matrix using the determined social interactions; generating, by the one or more computing systems, a social brain by performing Singular Value Decomposition (SVD) on the social object matrix, the social brain comprising a singular value representation of the social object matrix; determining, by the one or more computing systems, text from the social objects of the determined social interactions; generating, by the one or more computing systems, a term-document matrix (TDM) using the determined text; generating, by the one or more computing systems, a semantic brain by performing SVD on the TDM, the semantic brain comprising a singular value representation of the TDM; generating, by the one or more computing systems, an index using the determined text; and performing, by the one or more computing systems, a query using the social brain, the semantic brain, and the index.

8. A computer-implemented method, comprising: determining, by one or more computing systems, a plurality of social interactions associated with a plurality of people, each social interaction comprising a particular person interacting with a particular social object of a plurality of social objects; generating, by the one or more computing systems, a social object matrix using the determined social interactions; generating, by the one or more computing systems, a social brain by performing Singular Value Decomposition (SVD) on the social object matrix, the social brain comprising a singular value representation of the social object matrix; determining, by the one or more computing systems, text from the social objects of the determined social interactions; generating, by the one or more computing systems, a term-document matrix (TDM) using the determined text; generating, by the one or more computing systems, a semantic brain by performing SVD on the TDM, the semantic brain comprising a singular value representation of the TDM; generating, by the one or more computing systems, an index using the determined text; and performing, by the one or more computing systems, a query using the social brain, the semantic brain, and the index. 9. The computer-implemented method of claim 8 , wherein determining text from the social objects of the determined social interactions comprises: capturing text from the plurality of social objects that are textual social objects; and determining proxies for the plurality of social objects that are non-textual social objects and capturing text from the determined proxies.

11. The method of claim 10 , further comprising determining the category for the visit within the at least one block according to the random number.

11. The method of claim 10 , further comprising determining the category for the visit within the at least one block according to the random number. 12. The method of claim 11 , wherein the category corresponds to a keyword of the at least one keyword.

34. A search engine apparatus, comprising: a first database containing records relating to a content of a plurality of information resources; a second database of records relating to commercial messages; a memory storing: a persistent identifier and instructions for execution by an automated processor system; the automated processor system, configured to execute the instructions causing the automated processor system to: receive a search query and automatically define in dependence thereon a query of said first database to retrieve hyperlinked identifiers of records of said first database corresponding to said search query, and a selection of records from said second database to define hyperlinked identifiers of records of said second database relating to commercial messages associated with at least one of said search query and said persistent identifier, automatically organize said identifiers of records from said first database together with said identifiers of records from said second database in a common output, in further dependence on said persistent identifier, define a hierarchy from the hyperlinked identifiers of records of said first database corresponding to said search query according to content of or linkage among the hyperlinked identifiers of records of said first database, insert the hyperlinked identifiers of records of said second database relating to commercial messages associated with at least one of said search query and said persistent identifier into the hierarchy according to content of or linkage between the hyperlinked identifiers of records of said second database and the hyperlinked identifiers of records of said first database; and an accounting database, for recording accounting information for at least one of a presentation and a selection of an identifier of a record from said second database with respect to an account maintained by an entity relating to a corresponding commercial message.

34. A search engine apparatus, comprising: a first database containing records relating to a content of a plurality of information resources; a second database of records relating to commercial messages; a memory storing: a persistent identifier and instructions for execution by an automated processor system; the automated processor system, configured to execute the instructions causing the automated processor system to: receive a search query and automatically define in dependence thereon a query of said first database to retrieve hyperlinked identifiers of records of said first database corresponding to said search query, and a selection of records from said second database to define hyperlinked identifiers of records of said second database relating to commercial messages associated with at least one of said search query and said persistent identifier, automatically organize said identifiers of records from said first database together with said identifiers of records from said second database in a common output, in further dependence on said persistent identifier, define a hierarchy from the hyperlinked identifiers of records of said first database corresponding to said search query according to content of or linkage among the hyperlinked identifiers of records of said first database, insert the hyperlinked identifiers of records of said second database relating to commercial messages associated with at least one of said search query and said persistent identifier into the hierarchy according to content of or linkage between the hyperlinked identifiers of records of said second database and the hyperlinked identifiers of records of said first database; and an accounting database, for recording accounting information for at least one of a presentation and a selection of an identifier of a record from said second database with respect to an account maintained by an entity relating to a corresponding commercial message. 41. The search engine apparatus according to claim 34 , wherein said records of at least one of said first database and said second database are selected in dependence on a collaborative filter.

10. The electronic device of claim 9 , wherein the time-independent axis orders the at least some of the plurality of search results based, at least in part, on the media content associated with the at least some of the plurality of search results.

10. The electronic device of claim 9 , wherein the time-independent axis orders the at least some of the plurality of search results based, at least in part, on the media content associated with the at least some of the plurality of search results. 11. The electronic device of claim 10 , wherein the time-independent axis orders the at least some of the plurality of search results based, at least in part, on the type of media content associated with the at least some of the plurality of search results.

1. A method comprising, by a computing device: receiving, from a client system of a user, an indication of the user accessing a query field of a currently accessed interface of an online social network at the client device of the user, wherein the query field is in a null state; generating a plurality of structured queries that each comprise one or more unique query tokens referencing one or more unique objects associated with the online social network; calculating a score for each structured query based on one or more user-engagement factors, the score for each structured query representing a probability that the user will engage with the structured query; and sending, to the client system responsive to the indication of the user accessing the query field, instructions for displaying one or more suggested queries on the interface, wherein the one or more suggested queries correspond to one or more structured queries, respectively, having respective scores greater than a threshold score, and wherein each suggested query that is displayed is selectable by the user to retrieve search results corresponding to the selected query.

1. A method comprising, by a computing device: receiving, from a client system of a user, an indication of the user accessing a query field of a currently accessed interface of an online social network at the client device of the user, wherein the query field is in a null state; generating a plurality of structured queries that each comprise one or more unique query tokens referencing one or more unique objects associated with the online social network; calculating a score for each structured query based on one or more user-engagement factors, the score for each structured query representing a probability that the user will engage with the structured query; and sending, to the client system responsive to the indication of the user accessing the query field, instructions for displaying one or more suggested queries on the interface, wherein the one or more suggested queries correspond to one or more structured queries, respectively, having respective scores greater than a threshold score, and wherein each suggested query that is displayed is selectable by the user to retrieve search results corresponding to the selected query. 9. The method of claim 1 , wherein calculating the score for each structured query based on the one or more user-engagement factors comprises calculating the score based at least in part on whether the structured query is a sponsored query.

17. A computer program product comprising: a computer-readable, tangible storage device; and computer-readable program instructions stored in the computer-readable, tangible storage device, the computer-readable program instructions, when carried out by a central processing unit (CPU) of a computer system, implement a method of generating a log parser, the method comprising the steps of: the computer system receiving a sample log whose parts are delimited by one or more occurrences of a delimiter in the sample log; the computer system retrieving a plurality of tokens; the computer system generating a tokenized log by delimiting the received sample log based on a token included in the retrieved plurality of tokens, the tokenized log comprising a plurality of elements, each element delimited in the tokenized log by the token; the computer system determining one or more matches between respective one or more elements in the plurality of elements and respective one or more attributes, each attribute being an attribute of a field included in one or more fields of the sample log; based on the one or more matches and based on the token, the computer system determining one or more positions of the respective one or more elements within the tokenized log; based on the one or more matches, the computer system determining a ranking of the token, the ranking indicating a first likelihood that the token is the delimiter that delimits the parts of the sample log; the computer system determining a second ranking of another token included in the retrieved plurality of tokens, the second ranking indicating a second likelihood that the other token is the delimiter; the computer system determining the first likelihood is greater than the second likelihood; based on the one or more positions, the one or more matches, and the token, the computer system generating a first parser by generating one or more parser patterns for the one or more matches, respectively; the computer system generating a second parser based in part on the other token; the computer system parsing the sample log based on the generated first parser; and based on the first likelihood being greater than the second likelihood, the computer system presenting a result of the step of parsing the sample log and the computer system receiving a validation of the presented result without the computer system presenting another result of parsing the sample log based on the second parser.

17. A computer program product comprising: a computer-readable, tangible storage device; and computer-readable program instructions stored in the computer-readable, tangible storage device, the computer-readable program instructions, when carried out by a central processing unit (CPU) of a computer system, implement a method of generating a log parser, the method comprising the steps of: the computer system receiving a sample log whose parts are delimited by one or more occurrences of a delimiter in the sample log; the computer system retrieving a plurality of tokens; the computer system generating a tokenized log by delimiting the received sample log based on a token included in the retrieved plurality of tokens, the tokenized log comprising a plurality of elements, each element delimited in the tokenized log by the token; the computer system determining one or more matches between respective one or more elements in the plurality of elements and respective one or more attributes, each attribute being an attribute of a field included in one or more fields of the sample log; based on the one or more matches and based on the token, the computer system determining one or more positions of the respective one or more elements within the tokenized log; based on the one or more matches, the computer system determining a ranking of the token, the ranking indicating a first likelihood that the token is the delimiter that delimits the parts of the sample log; the computer system determining a second ranking of another token included in the retrieved plurality of tokens, the second ranking indicating a second likelihood that the other token is the delimiter; the computer system determining the first likelihood is greater than the second likelihood; based on the one or more positions, the one or more matches, and the token, the computer system generating a first parser by generating one or more parser patterns for the one or more matches, respectively; the computer system generating a second parser based in part on the other token; the computer system parsing the sample log based on the generated first parser; and based on the first likelihood being greater than the second likelihood, the computer system presenting a result of the step of parsing the sample log and the computer system receiving a validation of the presented result without the computer system presenting another result of parsing the sample log based on the second parser. 18. The program product of claim 17 , wherein the method further comprises the steps of: the computer system selecting a format of a timestamp in the sample log from a plurality of potential formats of the timestamp, the selected format of the timestamp being an attribute included in the one or more attributes; the computer system determining a match between an element in the plurality of elements included in the tokenized log and the selected format of the timestamp; and based on the match between the element and the selected format of the timestamp and based on the token, the computer system determining a position of the element within the tokenized log, wherein the step of determining the ranking of the token is further based on the match between the element and the selected format of the timestamp, and wherein the step of generating the first parser includes a step of generating a parser pattern for the timestamp based on the token, the position and the selected format of the timestamp.

18. The non-transitory computer-readable storage medium of claim 17 , the method further comprising determining that the output block of incorrectly translated text was erroneously not translated during an automated translation process based on the confirmation.

18. The non-transitory computer-readable storage medium of claim 17 , the method further comprising determining that the output block of incorrectly translated text was erroneously not translated during an automated translation process based on the confirmation. 19. The non-transitory computer-readable storage, medium of claim 18 , wherein the method further comprises: determining a base language from which the translated document was translated; and using a spell-checker for the base language to confirm that the block of incorrectly translated text is in the base language.

1. A method comprising: transcribing audio data comprising audio of one or more clinical personnel speaking while performing a surgical procedure, the audio data comprising audio of a first clinician speaking to one or more other clinical personnel while performing the surgical procedure; analyzing the transcribed audio data, including the transcribed audio of the first clinician speaking to the one or more other clinical personnel while performing the surgical procedure, at least in part by automatically extracting one or more clinical facts from the transcribed audio data using a fact extraction component implemented via at least one processor, to identify relevant information for documenting the surgical procedure, wherein analyzing the transcribed audio data comprises identifying within the transcribed audio data a present-tense narration by the first clinician stating to the other clinical personnel that the first clinician is currently performing a particular step of the surgical procedure; automatically generating a text report including the relevant information documenting the surgical procedure, wherein automatically generating the text report comprises automatically transforming the present-tense narration into a non-present-tense text portion in the report, stating that the particular step of the surgical procedure was performed; and outputting the automatically generated text report for review via a user interface on an audio and/or visual display device.

1. A method comprising: transcribing audio data comprising audio of one or more clinical personnel speaking while performing a surgical procedure, the audio data comprising audio of a first clinician speaking to one or more other clinical personnel while performing the surgical procedure; analyzing the transcribed audio data, including the transcribed audio of the first clinician speaking to the one or more other clinical personnel while performing the surgical procedure, at least in part by automatically extracting one or more clinical facts from the transcribed audio data using a fact extraction component implemented via at least one processor, to identify relevant information for documenting the surgical procedure, wherein analyzing the transcribed audio data comprises identifying within the transcribed audio data a present-tense narration by the first clinician stating to the other clinical personnel that the first clinician is currently performing a particular step of the surgical procedure; automatically generating a text report including the relevant information documenting the surgical procedure, wherein automatically generating the text report comprises automatically transforming the present-tense narration into a non-present-tense text portion in the report, stating that the particular step of the surgical procedure was performed; and outputting the automatically generated text report for review via a user interface on an audio and/or visual display device. 4. The method of claim 1 , wherein the audio data comprises audio of the one or more clinical personnel orally identifying one or more complications occurring during the surgical procedure.

7. A non-transitory computer readable storage medium storing an application, which, when executed on a processor, performs an operation for integrating a physical query statement in a data abstraction model comprising a first plurality of logical fields used to expose an underlying physical database, the operation comprising: parsing the physical query statement to identify a plurality of output fields specified by the physical query statement; upon determining that a first output field of the identified plurality of output fields has a corresponding logical field, of the first plurality of logical fields, mapping the first output field of the physical query statement to the corresponding logical field provided by the data abstraction model; upon determining that a second output field of the identified plurality of output fields does not have any corresponding logical field, generating a second logical field mapping to the second output field, wherein the second logical field includes an access method mapping the second logical field to the second output field; upon determining that a naming conflict exists between the second output field and one of the plurality of logical fields: determining a second name to assign to the second logical field to resolve the determined naming conflict, wherein the second name is different from a first name; and adding the second logical field having the second name to the plurality of logical fields, wherein the naming conflict is resolved without having to replace any logical field in the data abstraction model; and upon determining that no naming conflict exists between the second output field and one of the plurality of logical fields: determining a first name to assign to the second logical field; and adding the second logical field having the first name to the plurality of logical fields.

7. A non-transitory computer readable storage medium storing an application, which, when executed on a processor, performs an operation for integrating a physical query statement in a data abstraction model comprising a first plurality of logical fields used to expose an underlying physical database, the operation comprising: parsing the physical query statement to identify a plurality of output fields specified by the physical query statement; upon determining that a first output field of the identified plurality of output fields has a corresponding logical field, of the first plurality of logical fields, mapping the first output field of the physical query statement to the corresponding logical field provided by the data abstraction model; upon determining that a second output field of the identified plurality of output fields does not have any corresponding logical field, generating a second logical field mapping to the second output field, wherein the second logical field includes an access method mapping the second logical field to the second output field; upon determining that a naming conflict exists between the second output field and one of the plurality of logical fields: determining a second name to assign to the second logical field to resolve the determined naming conflict, wherein the second name is different from a first name; and adding the second logical field having the second name to the plurality of logical fields, wherein the naming conflict is resolved without having to replace any logical field in the data abstraction model; and upon determining that no naming conflict exists between the second output field and one of the plurality of logical fields: determining a first name to assign to the second logical field; and adding the second logical field having the first name to the plurality of logical fields. 9. The non-transitory computer readable storage medium of claim 7 , wherein the second output field provides data values not exposed by any of the plurality of logical fields.

1. A method comprising: receiving a selection of a business intelligence report element of a first business intelligence report specification, the first business intelligence report specification in a first file format; creating a serialized description of the business intelligence report element in a second file format based on a business intelligence report element data model; receiving an instruction to add the business intelligence report element to a second business intelligence report specification, the second business intelligence report specification in a third file format; and adding the business intelligence report element to the second business intelligence report specification in the third file format based on the serialized description of the business intelligence report element.

1. A method comprising: receiving a selection of a business intelligence report element of a first business intelligence report specification, the first business intelligence report specification in a first file format; creating a serialized description of the business intelligence report element in a second file format based on a business intelligence report element data model; receiving an instruction to add the business intelligence report element to a second business intelligence report specification, the second business intelligence report specification in a third file format; and adding the business intelligence report element to the second business intelligence report specification in the third file format based on the serialized description of the business intelligence report element. 7. A method according to claim 1 , wherein the first file format is different from the second file format.

43. The method of claim 41 wherein at least one of said records is a folder type record, said folder type record including at least one cell that contains data and a plurality of pointers to a plurality of other records included within said folder.

43. The method of claim 41 wherein at least one of said records is a folder type record, said folder type record including at least one cell that contains data and a plurality of pointers to a plurality of other records included within said folder. 44. The method of claim 43 wherein said plurality of other records included within said folder each includes a cell that contains a pointer to said folder type record.

1. A supervisory process control and manufacturing information application development and execution system supporting the execution of application object scripts derived from multiple different scripting languages, the system comprising: a script editor interface facilitating specifying scripts for application objects, and wherein the script editor interface supports multiple distinct user-side script languages; a script translation component including routines for rendering execution-side script of a single execution-side scripting language from source script rendered by the script editor and written according to any of a set of user-side script languages, the set of user-side script languages including at least: a first scripting language, and a second scripting language; and a scripting engine for executing the execution-side script of the single execution-side scripting language generated by the script translation component for the first scripting language and the second scripting language.

1. A supervisory process control and manufacturing information application development and execution system supporting the execution of application object scripts derived from multiple different scripting languages, the system comprising: a script editor interface facilitating specifying scripts for application objects, and wherein the script editor interface supports multiple distinct user-side script languages; a script translation component including routines for rendering execution-side script of a single execution-side scripting language from source script rendered by the script editor and written according to any of a set of user-side script languages, the set of user-side script languages including at least: a first scripting language, and a second scripting language; and a scripting engine for executing the execution-side script of the single execution-side scripting language generated by the script translation component for the first scripting language and the second scripting language. 7. The application development and execution system of claim 1 wherein the first script language comprises a text-based scripting language and the second scripting language comprises a graphical object-based scripting language.

7. The method of claim 5 wherein said machine readable symbol also has encoded therein an encryption key associated with said source identifier data string, said encryption key is transposed by said computer input device, said transposed encryption key is used by said client computer to encrypt information specific to a user associated with said client computer, and said encrypted user information is assembled within said computer file transfer request word and transmitted to said target server computer.

7. The method of claim 5 wherein said machine readable symbol also has encoded therein an encryption key associated with said source identifier data string, said encryption key is transposed by said computer input device, said transposed encryption key is used by said client computer to encrypt information specific to a user associated with said client computer, and said encrypted user information is assembled within said computer file transfer request word and transmitted to said target server computer. 10. The method of claim 7 wherein said target server computer utilizes said source identifier data string to access a lookup table to determine a decryption key associated with said encryption key, and said target server decrypts said encrypted user information received from said client computer.

1. A translation method adapted to a domain of interest comprising: receiving a source text string comprising a sequence of source words in a source language; generating a set of candidate translations of the source text string, each candidate translation comprising a sequence of target words in a target language; and with a processor, identifying an optimal translation from the set of candidate translations as a function of at least one domain-adapted feature, the at least one domain-adapted feature being computed based on: bilingual probabilities, each bilingual probability being for a source text fragment and a target text fragment of the source text string and candidate translation respectively, the bilingual probabilities being estimated on an out-of-domain parallel corpus comprising source and target strings; and monolingual probabilities for text fragments of one of the source text string and candidate translation, the monolingual probabilities being estimated on an in-domain monolingual corpus, wherein the domain-adapted feature comprises at least one of: a) a forward domain-adapted lexical feature which is a function of ∑ ( i , j ) ∈ a ⁢ ⁢ w in ⁡ ( s i ❘ t j ) where w in (s i |t j ) is an adapted word probability and is a function of a product of w out (t j |s i ) and w in (s i ); b) a reverse domain-adapted lexical feature which is a function of ∑ ( i , j ) ∈ a ⁢ ⁢ w in ⁡ ( t j ❘ s i ) where w in (t j |s i ) is an adapted word probability and is a function of a product of w out (t j |s i ) and w in (t j ); c) a forward domain-adapted phrasal feature which is a function of: ∑ ( i , j ) ∈ a ⁢ phr in ⁡ ( s _ i ❘ t _ j ) , where phr in ( s i | t j ) is an adapted phrase probability and is a function of a product of phr out ( t j | s i ) and p in ( s i ); d) a reverse domain-adapted phrasal feature which is a function of: ∑ ( i , j ) ∈ a ⁢ phr in ⁡ ( t _ j ❘ s _ i ) , where phr in ( t j | s i ) is an adapted phrase probability and is a function of a product of phr out ( s i | t j ) and p in ( t j ); where s i and t j represent words of the source string and candidate translation respectively which are aligned in an alignment α of the source string and candidate translation, w out (t j |s i ) represents the bilingual probability, which is a word probability for target word t j in the presence of source word s i , derived from the parallel corpus, and w in (s i ) represents the monolingual probability, which is the word probability for source word s i derived from the in-domain monolingual corpus; s i and t j represent phrases of the source string and candidate translation respectively which are aligned in the alignment α of the source string and candidate translation, phr out ( t j | s i )represents the bilingual probability, which is a phrasal probability for target phrase t j in the presence of source phrase s i , derived from the parallel corpus, p in ( s i ) represents the monolingual probability, which is the phrasal probability for source phrase s i derived from the in-domain monolingual corpus, and p in ( t j ) represents the monolingual probability, which is the phrasal probability for target phrase t j derived from the in-domain monolingual corpus.

1. A translation method adapted to a domain of interest comprising: receiving a source text string comprising a sequence of source words in a source language; generating a set of candidate translations of the source text string, each candidate translation comprising a sequence of target words in a target language; and with a processor, identifying an optimal translation from the set of candidate translations as a function of at least one domain-adapted feature, the at least one domain-adapted feature being computed based on: bilingual probabilities, each bilingual probability being for a source text fragment and a target text fragment of the source text string and candidate translation respectively, the bilingual probabilities being estimated on an out-of-domain parallel corpus comprising source and target strings; and monolingual probabilities for text fragments of one of the source text string and candidate translation, the monolingual probabilities being estimated on an in-domain monolingual corpus, wherein the domain-adapted feature comprises at least one of: a) a forward domain-adapted lexical feature which is a function of ∑ ( i , j ) ∈ a ⁢ ⁢ w in ⁡ ( s i ❘ t j ) where w in (s i |t j ) is an adapted word probability and is a function of a product of w out (t j |s i ) and w in (s i ); b) a reverse domain-adapted lexical feature which is a function of ∑ ( i , j ) ∈ a ⁢ ⁢ w in ⁡ ( t j ❘ s i ) where w in (t j |s i ) is an adapted word probability and is a function of a product of w out (t j |s i ) and w in (t j ); c) a forward domain-adapted phrasal feature which is a function of: ∑ ( i , j ) ∈ a ⁢ phr in ⁡ ( s _ i ❘ t _ j ) , where phr in ( s i | t j ) is an adapted phrase probability and is a function of a product of phr out ( t j | s i ) and p in ( s i ); d) a reverse domain-adapted phrasal feature which is a function of: ∑ ( i , j ) ∈ a ⁢ phr in ⁡ ( t _ j ❘ s _ i ) , where phr in ( t j | s i ) is an adapted phrase probability and is a function of a product of phr out ( s i | t j ) and p in ( t j ); where s i and t j represent words of the source string and candidate translation respectively which are aligned in an alignment α of the source string and candidate translation, w out (t j |s i ) represents the bilingual probability, which is a word probability for target word t j in the presence of source word s i , derived from the parallel corpus, and w in (s i ) represents the monolingual probability, which is the word probability for source word s i derived from the in-domain monolingual corpus; s i and t j represent phrases of the source string and candidate translation respectively which are aligned in the alignment α of the source string and candidate translation, phr out ( t j | s i )represents the bilingual probability, which is a phrasal probability for target phrase t j in the presence of source phrase s i , derived from the parallel corpus, p in ( s i ) represents the monolingual probability, which is the phrasal probability for source phrase s i derived from the in-domain monolingual corpus, and p in ( t j ) represents the monolingual probability, which is the phrasal probability for target phrase t j derived from the in-domain monolingual corpus. 17. The method of claim 1 , further comprising outputting the optimal translation as the translation of the source string.

8. A non-transitory computer readable medium encoded with a plurality of instructions that, when executed by a computer, perform a method comprising: receiving, from a speech recognition component, one or more words corresponding to a voice input; searching a product information management (PIM) component to identify at least one matching item and/or category in a product catalog based, at least in part, on the one or more received words and at least one item attribute associated with at least one item and/or at least one category attribute associated with at least one category in the PIM component; and outputting coded results to a voice synthesis component in response to the search, wherein the coded results indicate whether the search resulted in the identification of at least one matching item and/or category in the PIM component.

8. A non-transitory computer readable medium encoded with a plurality of instructions that, when executed by a computer, perform a method comprising: receiving, from a speech recognition component, one or more words corresponding to a voice input; searching a product information management (PIM) component to identify at least one matching item and/or category in a product catalog based, at least in part, on the one or more received words and at least one item attribute associated with at least one item and/or at least one category attribute associated with at least one category in the PIM component; and outputting coded results to a voice synthesis component in response to the search, wherein the coded results indicate whether the search resulted in the identification of at least one matching item and/or category in the PIM component. 14. The computer-readable medium of claim 8 , wherein the coded results indicate multiple matching items were identified, wherein the method further comprises: determining if there are one or more matching categories corresponding to the matching items; instructing the voice synthesis component to generate a request for additional voice input from the user in response to determining there are no matching categories corresponding to the matching items; instructing the voice synthesis component to generate a request for subcategory and/or item attributes in response to determining that there is a single matching category corresponding to the matching items; and instructing the voice synthesis component to generate a request for confirmation of a suitable category in response to determining that there are multiple categories corresponding to the matching items.

1. A computer system implemented method for deploying data science transformations from a development computing environment into a production computing environment, comprising: receiving, with one or more first computing systems, first transformation data representing one or more first transformations defined in a first programming language, the one or more first transformations operable on one or more operands to generate one or more results, wherein the one or more first computing systems are a development computing environment; receiving second transformation data representing one or more second transformations defined in a second programming language, the one or more second transformations operable on the one or more operands to generate the one or more results, wherein each of the one or more second transformations defined in the second programming language mirrors a corresponding one of the one or more first transformations defined in the first programming language, further wherein the second transformation data includes one or more configuration parameters for configuring physical and/or virtual resources to execute one or more transformations; associating the first transformation data with the second transformation data in a transformations data structure to associate the one or more first transformations with the one or more second transformations; storing the transformations data structure to one or more sections of memory associated with the one or more computing systems; receiving macro-transformation data representing a macro-transformation in the first programming language, the macro-transformation being a combination of multiple ones of the one or more first transformations that are logically connected to receive operand data for the macro-transformation and are logically connected to provide output data from the macro-transformation; compiling the first programming language macro-transformation data to generate executable code for the macro-transformation in the second programming language to enable deployment of the macro-transformation into one or more second computing systems while preserving a relational complexity of the combination of multiple ones of the one or more first transformations of the macro-transformation, wherein compiling the macro-transformation data at least partially includes accessing contents of the transformations data structure that is stored in the one or more sections of memory; and deploying the executable code to the one or more second computing systems to enable the one or more second computing systems to interpret and execute the macro-transformation in the second programming language to provide services to a plurality of users that is at least partially based on a functionality of the macro-transformation, wherein the one or more second computing systems are the production environment.

1. A computer system implemented method for deploying data science transformations from a development computing environment into a production computing environment, comprising: receiving, with one or more first computing systems, first transformation data representing one or more first transformations defined in a first programming language, the one or more first transformations operable on one or more operands to generate one or more results, wherein the one or more first computing systems are a development computing environment; receiving second transformation data representing one or more second transformations defined in a second programming language, the one or more second transformations operable on the one or more operands to generate the one or more results, wherein each of the one or more second transformations defined in the second programming language mirrors a corresponding one of the one or more first transformations defined in the first programming language, further wherein the second transformation data includes one or more configuration parameters for configuring physical and/or virtual resources to execute one or more transformations; associating the first transformation data with the second transformation data in a transformations data structure to associate the one or more first transformations with the one or more second transformations; storing the transformations data structure to one or more sections of memory associated with the one or more computing systems; receiving macro-transformation data representing a macro-transformation in the first programming language, the macro-transformation being a combination of multiple ones of the one or more first transformations that are logically connected to receive operand data for the macro-transformation and are logically connected to provide output data from the macro-transformation; compiling the first programming language macro-transformation data to generate executable code for the macro-transformation in the second programming language to enable deployment of the macro-transformation into one or more second computing systems while preserving a relational complexity of the combination of multiple ones of the one or more first transformations of the macro-transformation, wherein compiling the macro-transformation data at least partially includes accessing contents of the transformations data structure that is stored in the one or more sections of memory; and deploying the executable code to the one or more second computing systems to enable the one or more second computing systems to interpret and execute the macro-transformation in the second programming language to provide services to a plurality of users that is at least partially based on a functionality of the macro-transformation, wherein the one or more second computing systems are the production environment. 8. The computer system implemented method of claim 1 , wherein the relational complexity of the combination of multiple ones of the one or more first transformations of the macro-transformation includes scalability and extensibility of the combination of multiple ones of the one or more first transformations of the macro-transformation.

1. A computer implemented method comprising: partitioning a plurality of queries into a plurality of clusters, each cluster containing a plurality of queries; (a) for each query of the plurality of queries, generating a plurality of suggested rewrites, wherein each suggested rewrite of said plurality of suggested rewrites is the result of applying a query rewrite policy, the query rewrite policy being an ordered set of one or more query rewrite techniques, each query rewrite technique of said one or more query rewrite techniques being provided by a query rewrite provider of a plurality of query rewrite providers; (b) for each query, generating a set of rewrite scores, wherein each rewrite score of said set of rewrite scores reflects the quality of a particular suggested query rewrite generated for the query by a respective query rewrite policy; (c) for each cluster, generating aggregate rewrite scores by aggregating the rewrite scores of the same query rewrite policy for the same cluster; (d) based on the aggregate rewrite scores generated, query features of each query of said plurality of queries, and the rewrite scores generated for each query of the plurality of queries, generating a partitioning function by which to partition said plurality of queries into clusters; (e) based on the partitioning function, repartitioning said plurality of queries into a new set of clusters; repeating steps (a), (b), (c), (d) and (e) one or more times; and wherein the steps are performed by one or more computers.

1. A computer implemented method comprising: partitioning a plurality of queries into a plurality of clusters, each cluster containing a plurality of queries; (a) for each query of the plurality of queries, generating a plurality of suggested rewrites, wherein each suggested rewrite of said plurality of suggested rewrites is the result of applying a query rewrite policy, the query rewrite policy being an ordered set of one or more query rewrite techniques, each query rewrite technique of said one or more query rewrite techniques being provided by a query rewrite provider of a plurality of query rewrite providers; (b) for each query, generating a set of rewrite scores, wherein each rewrite score of said set of rewrite scores reflects the quality of a particular suggested query rewrite generated for the query by a respective query rewrite policy; (c) for each cluster, generating aggregate rewrite scores by aggregating the rewrite scores of the same query rewrite policy for the same cluster; (d) based on the aggregate rewrite scores generated, query features of each query of said plurality of queries, and the rewrite scores generated for each query of the plurality of queries, generating a partitioning function by which to partition said plurality of queries into clusters; (e) based on the partitioning function, repartitioning said plurality of queries into a new set of clusters; repeating steps (a), (b), (c), (d) and (e) one or more times; and wherein the steps are performed by one or more computers. 5. The method of claim 1 , wherein a given rewrite policy involves multiple applications of the same query rewrite technique.

15. A computer-implemented people matching system, comprising one or more processor-based devices configured to execute: a computer-implemented tagging function that enables a user of a computer implemented system to tag a plurality of computer-implemented objects for future reference; a people matching function that generates a match comprising a first person and a second person, wherein the match is generated based, at least in part, on an inference from a plurality of usage behaviors, wherein one of the plurality of usage behaviors is not a tagging behavior and a second of the plurality of usage behaviors is the user using the computer-implemented tagging function to tag a first computer-implemented object of the plurality of computer-implemented objects for future reference; and a computer implemented explanatory function that delivers a reason for the match to the first person, wherein the reason comprises the inference, wherein the inference is of a common interest.

15. A computer-implemented people matching system, comprising one or more processor-based devices configured to execute: a computer-implemented tagging function that enables a user of a computer implemented system to tag a plurality of computer-implemented objects for future reference; a people matching function that generates a match comprising a first person and a second person, wherein the match is generated based, at least in part, on an inference from a plurality of usage behaviors, wherein one of the plurality of usage behaviors is not a tagging behavior and a second of the plurality of usage behaviors is the user using the computer-implemented tagging function to tag a first computer-implemented object of the plurality of computer-implemented objects for future reference; and a computer implemented explanatory function that delivers a reason for the match to the first person, wherein the reason comprises the inference, wherein the inference is of a common interest. 17. The system of claim 15 , further comprising: the plurality of usage behaviors, wherein one of the plurality of usage behaviors is a subscription by the first person to a computer-implemented object that delivers information in accordance with the subscription, wherein the delivered information comprises content authored by the second person.

24. A computer program product embedded in a non-transitory computer readable medium for enabling a user to provide criterion-specific feedback for an item, comprising: program code for providing for display a representation of the item and information regarding the item; and program code for providing a user with the ability to provide feedback for the item, including: enabling the user to select an existing response to an existing question or statement regarding at least one criterion for the item; enabling the user to specify a new response to an existing question or statement regarding at least one criterion for the item; enabling the user to select an add feedback element when the at least one existing criterion does not substantially represent the feedback the user wishes to provide for the item; and in response to receiving a selection of the add feedback element, enabling the user to input a new criterion that represents the feedback the user wishes to provide for the item and one or more new values for the new criterion, by enabling the user to input a new question corresponding the new criterion and one or more new responses to the new question, the one or more new responses corresponding to the one or more new values; and program code for aggregating feedback provided by the user with existing feedback for the item, the aggregated feedback able to be subsequently provided for display with the representation of the item and information regarding the item.

24. A computer program product embedded in a non-transitory computer readable medium for enabling a user to provide criterion-specific feedback for an item, comprising: program code for providing for display a representation of the item and information regarding the item; and program code for providing a user with the ability to provide feedback for the item, including: enabling the user to select an existing response to an existing question or statement regarding at least one criterion for the item; enabling the user to specify a new response to an existing question or statement regarding at least one criterion for the item; enabling the user to select an add feedback element when the at least one existing criterion does not substantially represent the feedback the user wishes to provide for the item; and in response to receiving a selection of the add feedback element, enabling the user to input a new criterion that represents the feedback the user wishes to provide for the item and one or more new values for the new criterion, by enabling the user to input a new question corresponding the new criterion and one or more new responses to the new question, the one or more new responses corresponding to the one or more new values; and program code for aggregating feedback provided by the user with existing feedback for the item, the aggregated feedback able to be subsequently provided for display with the representation of the item and information regarding the item. 25. A computer program product according to claim 24 , further comprising: code for providing an ability for the user to specify an affirmative feedback statement corresponding to a new question to be displayed with the representation of the item when feedback received from the user includes the new question.

10. The device defined in claim 6 further comprising: a clock/calendar chip connected to said control means for generating at least one time parameter; and said control means being capable of transferring said at least one time parameter to said display means for displaying said time parameter.

10. The device defined in claim 6 further comprising: a clock/calendar chip connected to said control means for generating at least one time parameter; and said control means being capable of transferring said at least one time parameter to said display means for displaying said time parameter. 12. The device defined in claim 10 wherein said at least one time parameter is the current time in hours and minutes.

1. A computer-implemented method of reviewing prior art, the method comprising using one or more processors to perform the following operations: identifying at least a first patent concept related to an area of technology in the prior art, the first patent concept automatically provided from an ontology of patent concepts stored in a database; receiving a search query including the first patent concept; conducting an initial search as a function of the search query; generating a first set of search results, wherein the first set of search results includes information relating to two or more of the following: most-cited prior art owners in the area of technology, the most-cited prior art owners determined by comparing an owner citation frequency of each prior art owner of a set of prior art owners cited within the area of technology; most-cited prior art references in the area of technology, the most-cited prior art references determined by comparing a reference citation frequency of each prior art reference of a set of prior art references cited within the area of technology; and keywords differentiating the first patent concept from the prior art; storing the first set of search results in a database; automatically conducting a subsequent search as a function of the search query, the subsequent search conducted at a predetermined interval after the initial search; generating a second set of search results corresponding to the first set of search results; comparing the first and second sets of search results to identify differences between the first set of search results and the second set of search results; communicating the differences in the search results to a user; and generating a patent activity profile for one or more entities based at least in part on the differences in the search results, wherein the patent activity profile monitors, and flags deviances from, at least of the one or more of the entity's patterns of: type of applications filed; location of applications filed; subject matter abandoned during prosecution; and instances or circumstances of annuity fee non-payment.

1. A computer-implemented method of reviewing prior art, the method comprising using one or more processors to perform the following operations: identifying at least a first patent concept related to an area of technology in the prior art, the first patent concept automatically provided from an ontology of patent concepts stored in a database; receiving a search query including the first patent concept; conducting an initial search as a function of the search query; generating a first set of search results, wherein the first set of search results includes information relating to two or more of the following: most-cited prior art owners in the area of technology, the most-cited prior art owners determined by comparing an owner citation frequency of each prior art owner of a set of prior art owners cited within the area of technology; most-cited prior art references in the area of technology, the most-cited prior art references determined by comparing a reference citation frequency of each prior art reference of a set of prior art references cited within the area of technology; and keywords differentiating the first patent concept from the prior art; storing the first set of search results in a database; automatically conducting a subsequent search as a function of the search query, the subsequent search conducted at a predetermined interval after the initial search; generating a second set of search results corresponding to the first set of search results; comparing the first and second sets of search results to identify differences between the first set of search results and the second set of search results; communicating the differences in the search results to a user; and generating a patent activity profile for one or more entities based at least in part on the differences in the search results, wherein the patent activity profile monitors, and flags deviances from, at least of the one or more of the entity's patterns of: type of applications filed; location of applications filed; subject matter abandoned during prosecution; and instances or circumstances of annuity fee non-payment. 2. The computer-implemented method of claim 1 further comprising: maintaining a patent matter database, wherein the patent matter database includes data about patent matters, the data including a claim set for at least one patent matter, and wherein the first patent concept relates to at least one feature of the claim set.

25. A computer-implemented method for implementing an event centric social networking platform, said method comprising the following steps: storing, in a first repository, at least user related information including at least registration information; storing, in a second repository, at least the information corresponding to catalog offerings; storing, in a third repository, at least event-related information corresponding to said users, information corresponding to resources uploaded onto a social networking platform by said users, information corresponding to access privileges and action permissions granted to user roles with respect to event-related information; receiving a request from a user towards organizing an event based on at least one of catalog offerings/catalog offering related activities, said request including at least event related information; searching said second repository for catalog offerings related to said event related information, and generating a list of catalog offerings related to event specified by a user based on user related information; enabling selection of at least one vendor offering from said list of catalog offerings and updating the event-related information stored in said third repository to reflect the vendor offering selected by said user; searching friend list for users, based on a pre-defined criteria, and categorizing users in search result into pre-determined invitee categories; generating an invitee list for an event including user names selected from at least one of said pre-determined invitee categories and non-registered invitees, and selectively transmitting an invitation inviting users included in said invitee list to attend said event, enabling said registered/non-registered invitees to respond to the event invitation, and tracking the responses of invited users; and displaying a list of event invitations including past events and the events planned for future dates, controlling users' access to said list of event invitations, providing users with selective access to contents of the event invitations, enabling said users to view the listed event invitation, edit the listed event invitation, comment on the listed event invitation and add image/social media files on to the listed event invitation; generating notifications corresponding to at least the activities performed by said users on said social networking platform, and transmitting said notifications to at least one other user whose name is included in the friend list associated with the users.

25. A computer-implemented method for implementing an event centric social networking platform, said method comprising the following steps: storing, in a first repository, at least user related information including at least registration information; storing, in a second repository, at least the information corresponding to catalog offerings; storing, in a third repository, at least event-related information corresponding to said users, information corresponding to resources uploaded onto a social networking platform by said users, information corresponding to access privileges and action permissions granted to user roles with respect to event-related information; receiving a request from a user towards organizing an event based on at least one of catalog offerings/catalog offering related activities, said request including at least event related information; searching said second repository for catalog offerings related to said event related information, and generating a list of catalog offerings related to event specified by a user based on user related information; enabling selection of at least one vendor offering from said list of catalog offerings and updating the event-related information stored in said third repository to reflect the vendor offering selected by said user; searching friend list for users, based on a pre-defined criteria, and categorizing users in search result into pre-determined invitee categories; generating an invitee list for an event including user names selected from at least one of said pre-determined invitee categories and non-registered invitees, and selectively transmitting an invitation inviting users included in said invitee list to attend said event, enabling said registered/non-registered invitees to respond to the event invitation, and tracking the responses of invited users; and displaying a list of event invitations including past events and the events planned for future dates, controlling users' access to said list of event invitations, providing users with selective access to contents of the event invitations, enabling said users to view the listed event invitation, edit the listed event invitation, comment on the listed event invitation and add image/social media files on to the listed event invitation; generating notifications corresponding to at least the activities performed by said users on said social networking platform, and transmitting said notifications to at least one other user whose name is included in the friend list associated with the users. 40. The method as claimed in claim 25 , wherein the method further includes the following steps: enabling said users to announce their availability for event participation during a specific time period, their interest towards attending an event based on specific catalog offerings, one or more activity types associated with said catalog offerings, and their preference of friends from whom said user wishes to receive event invitations in response to their announcement; and notifying other users present in said user's friend list of the announcement should a notified user wish to invite announcing user and other users to a planned event.

67. The non-transitory computer-readable medium of claim 60 , wherein the operations further comprise: receiving, from the server, one or more server sound models similar to the input sound model; and updating the client database based on the second label and the one or more server sound models.

67. The non-transitory computer-readable medium of claim 60 , wherein the operations further comprise: receiving, from the server, one or more server sound models similar to the input sound model; and updating the client database based on the second label and the one or more server sound models. 69. The non-transitory computer-readable medium of claim 67 , wherein updating the client database comprises: outputting the second label; receiving an input indicating whether the second label matches the input environmental sound; and updating the client database based on the input.

13. A system, comprising: a video input source; a processor; and a memory storing a machine learning engine, wherein the machine learning engine is configured to perform an operation for processing video image data, the operation comprising: detecting a plurality of objects in the video image data; and for each object: generating a primitive event symbol stream identifying one or more primitive events engaged in by the object, wherein each primitive event represents a behavior engaged in by the object, generating a phase-space symbol stream representing quantitative characteristics of the object, wherein the phase-space symbol stream for the object indicates a trajectory of that object in the video image data over time, and combining the primitive event symbol stream and the phase-space symbol stream to generate a vector representation of the behavior engaged in by the object as depicted in the video image data.

13. A system, comprising: a video input source; a processor; and a memory storing a machine learning engine, wherein the machine learning engine is configured to perform an operation for processing video image data, the operation comprising: detecting a plurality of objects in the video image data; and for each object: generating a primitive event symbol stream identifying one or more primitive events engaged in by the object, wherein each primitive event represents a behavior engaged in by the object, generating a phase-space symbol stream representing quantitative characteristics of the object, wherein the phase-space symbol stream for the object indicates a trajectory of that object in the video image data over time, and combining the primitive event symbol stream and the phase-space symbol stream to generate a vector representation of the behavior engaged in by the object as depicted in the video image data. 14. The system of claim 13 , wherein the operation further comprises, identifying, by a machine learning engine, at least one pattern of behavior for one or more of the objects based on the vector representations of the plurality of objects.

1. A method of identifying phishing websites, the method comprising, at a computer system: receiving website information from a first server computer corresponding to a website; rendering a document object model (DOM) object of the website using the website information; extracting a plurality of features from the DOM object; identifying a subset of features in the plurality of features; applying a phishing model to the subset of features to determine an indication of whether the website is performing phishing, wherein the phishing model includes a hierarchical decision logic defined by a plurality of nodes, each of the plurality of nodes having a different one of a plurality of phishing rules, wherein each of the plurality of phishing rules is a conditional statement for assessing one or more of the subset of features, and wherein applying the phishing model to the subset of features includes: identifying a subset of nodes in the plurality of nodes, the subset of nodes defining a decision path in the hierarchical decision logic, wherein the subset of nodes are identified by traversing the hierarchical decision logic based on an outcome of assessing a phishing rule of each of the subset of nodes, wherein the subset of nodes includes an initial node and a final node, and wherein after the initial node is identified, each subsequent node of the subset of nodes is identified based on the outcome of assessing a phishing rule of a node that is a parent of the subsequent node in the decision path; and determining a final phishing rule of the final node of the subset of nodes of the decision path, the final phishing rule being one of the plurality of phishing rules, wherein the indication of whether the website is performing phishing is determined based on an outcome of assessing the final phishing rule; determining a classification about whether the website is performing phishing based on the indication determined by the applying of the phishing model to the subset of features; and reporting a phishing occurrence based on determining that the classification specifies the website is performing phishing.

1. A method of identifying phishing websites, the method comprising, at a computer system: receiving website information from a first server computer corresponding to a website; rendering a document object model (DOM) object of the website using the website information; extracting a plurality of features from the DOM object; identifying a subset of features in the plurality of features; applying a phishing model to the subset of features to determine an indication of whether the website is performing phishing, wherein the phishing model includes a hierarchical decision logic defined by a plurality of nodes, each of the plurality of nodes having a different one of a plurality of phishing rules, wherein each of the plurality of phishing rules is a conditional statement for assessing one or more of the subset of features, and wherein applying the phishing model to the subset of features includes: identifying a subset of nodes in the plurality of nodes, the subset of nodes defining a decision path in the hierarchical decision logic, wherein the subset of nodes are identified by traversing the hierarchical decision logic based on an outcome of assessing a phishing rule of each of the subset of nodes, wherein the subset of nodes includes an initial node and a final node, and wherein after the initial node is identified, each subsequent node of the subset of nodes is identified based on the outcome of assessing a phishing rule of a node that is a parent of the subsequent node in the decision path; and determining a final phishing rule of the final node of the subset of nodes of the decision path, the final phishing rule being one of the plurality of phishing rules, wherein the indication of whether the website is performing phishing is determined based on an outcome of assessing the final phishing rule; determining a classification about whether the website is performing phishing based on the indication determined by the applying of the phishing model to the subset of features; and reporting a phishing occurrence based on determining that the classification specifies the website is performing phishing. 13. The method of claim 1 , further comprising: classifying the website associated with the first server computer as performing phishing; requesting updated website information from the first server computer; determining an operating status of the website associated with the first server computer; and reporting the operating status of the website to a monitoring system.

31. A computer-implemented method, comprising: receiving, at an information-capturing system, a text capture indication corresponding to a text capture operation performed on a rendered document that captured less than a whole page of text; the information-capturing system generating a text entry based upon said text capture indication, wherein the text entry specifies a number of documents matching text of the text capture operation; and the information-capturing system publishing the text entry.

31. A computer-implemented method, comprising: receiving, at an information-capturing system, a text capture indication corresponding to a text capture operation performed on a rendered document that captured less than a whole page of text; the information-capturing system generating a text entry based upon said text capture indication, wherein the text entry specifies a number of documents matching text of the text capture operation; and the information-capturing system publishing the text entry. 44. A non-transitory computer-readable medium having stored thereon instructions that, when executed, implement the method of claim 31 .

1. A method for monitoring changes to data comprising: receiving an indication that a data bearing object expects to undergo a change, wherein the data bearing object includes a programmatic grouping of data and the change includes a modification, an addition, or a removal of associated data; taking, at least in part in response to receiving said indication, a snapshot of said data bearing object, wherein the snapshot includes a copy of a state of at least a portion of the data of the data bearing object; and identifying said change to said data bearing object by comparing (1) said data bearing object after said change has been made to (2) said snapshot of said object.

1. A method for monitoring changes to data comprising: receiving an indication that a data bearing object expects to undergo a change, wherein the data bearing object includes a programmatic grouping of data and the change includes a modification, an addition, or a removal of associated data; taking, at least in part in response to receiving said indication, a snapshot of said data bearing object, wherein the snapshot includes a copy of a state of at least a portion of the data of the data bearing object; and identifying said change to said data bearing object by comparing (1) said data bearing object after said change has been made to (2) said snapshot of said object. 5. A method as recited in claim 1 , wherein said indication is received from said data bearing object.

1. A computer implemented method for inferring a probability of a first inference, wherein the probability of the first inference comprises an identification of a dangerous individual, wherein the dangerous individual comprises any individual, individuals, or group of individuals that are disturbed, distressed, or mentally ill and that have a likely predisposition to violent behavior, according to a likely determination of a professional of ordinary skill in the art of mental health, assuming that the professional had possession of at least one fact that would be relevant to the professional in making the determination, wherein likely comprises more probable than not, wherein relevant comprises relevance according to accepted standards of those of ordinary skill in the art of mental health, and wherein the computer implemented method comprises: receiving a query at a database regarding a fact, wherein the first inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the plurality of divergent data in the database is conformed to the dimensions of the database, wherein each datum of the plurality of divergent data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; applying a first set of rules to the query, wherein the first set of rules are determined for the query according to a second set of rules, wherein the frame of reference serves as an anchor for generating associations among the plurality of cohort data and is used to determine rules for limiting the plurality of divergent data that is searched, wherein the first set of rules determine how the plurality of divergent data are to be compared to the fact, and wherein the first set of rules determine a search space for the query; executing the query to create the first inference and the probability of the first inference, wherein the probability of the first inference is determined from comparing the plurality of divergent data according to the first set of rules; performing security filtering based on at least one of a significant level of the probability of the first inference, a probability of the first inference exceeding a pre-selected value, and a security level possessed by a user; storing the probability of the first inference; presenting the probability of the first inference to the user based on whether the user is authorized to receive a set of medical information under the standards of one of a law and an institutional review board; and presenting the probability of the first inference to the user even if the user is not authorized to receive the set of medical information under standards of one of the law and the institutional review board, but only responsive to a) restricting the user from accessing the medical information and b) a probability of the first inference exceeding a pre-defined value.

1. A computer implemented method for inferring a probability of a first inference, wherein the probability of the first inference comprises an identification of a dangerous individual, wherein the dangerous individual comprises any individual, individuals, or group of individuals that are disturbed, distressed, or mentally ill and that have a likely predisposition to violent behavior, according to a likely determination of a professional of ordinary skill in the art of mental health, assuming that the professional had possession of at least one fact that would be relevant to the professional in making the determination, wherein likely comprises more probable than not, wherein relevant comprises relevance according to accepted standards of those of ordinary skill in the art of mental health, and wherein the computer implemented method comprises: receiving a query at a database regarding a fact, wherein the first inference is absent from the database, wherein the database comprises a plurality of divergent data, wherein the plurality of divergent data includes a plurality of cohort data, wherein each datum of the plurality of divergent data in the database is conformed to the dimensions of the database, wherein each datum of the plurality of divergent data has associated metadata and an associated key, wherein the associated metadata comprises data regarding cohorts associated with the corresponding datum, data regarding hierarchies associated with the corresponding datum, data regarding a corresponding source of the datum, and data regarding probabilities associated with integrity, reliability, and importance of each associated datum; establishing the fact as a frame of reference for the query; applying a first set of rules to the query, wherein the first set of rules are determined for the query according to a second set of rules, wherein the frame of reference serves as an anchor for generating associations among the plurality of cohort data and is used to determine rules for limiting the plurality of divergent data that is searched, wherein the first set of rules determine how the plurality of divergent data are to be compared to the fact, and wherein the first set of rules determine a search space for the query; executing the query to create the first inference and the probability of the first inference, wherein the probability of the first inference is determined from comparing the plurality of divergent data according to the first set of rules; performing security filtering based on at least one of a significant level of the probability of the first inference, a probability of the first inference exceeding a pre-selected value, and a security level possessed by a user; storing the probability of the first inference; presenting the probability of the first inference to the user based on whether the user is authorized to receive a set of medical information under the standards of one of a law and an institutional review board; and presenting the probability of the first inference to the user even if the user is not authorized to receive the set of medical information under standards of one of the law and the institutional review board, but only responsive to a) restricting the user from accessing the medical information and b) a probability of the first inference exceeding a pre-defined value. 8. The computer implemented method of claim 1 further comprising: presenting the probability of the first inference to the user only if the security level possessed by the user exceeds a pre-determined value.

13. A computer program product available as a download or on a computer readable medium having executable instructions for undertaking dictionary-based compression or decompression, comprising: receiving an indication for compressing content; parsing the content into discrete constructions; passing the discrete constructions to a searching engine to locate network information at a plurality of uniform resource identifiers that corresponds to the discrete constructions; upon the locating the network information corresponding to the discrete constructions, creating a dictionary of entries corresponding to the content; and encoding the content from the dictionary of entries by indicating offsets to the network information corresponding to the discrete constructions per each of the uniform resource identifiers.

13. A computer program product available as a download or on a computer readable medium having executable instructions for undertaking dictionary-based compression or decompression, comprising: receiving an indication for compressing content; parsing the content into discrete constructions; passing the discrete constructions to a searching engine to locate network information at a plurality of uniform resource identifiers that corresponds to the discrete constructions; upon the locating the network information corresponding to the discrete constructions, creating a dictionary of entries corresponding to the content; and encoding the content from the dictionary of entries by indicating offsets to the network information corresponding to the discrete constructions per each of the uniform resource identifiers. 14. The computer program product of claim 13 , further including downloading the network information.

18. A system for conducting a compliance audit, the system comprising: at least one first processor and at least one first memory operably coupleable to the at least one first processor, the first processor and the first memory operable to access a database, wherein the database includes a knowledge base, the knowledge base including a rule set, the rule set including rules formulated from at least one requirement; an interface operable to accept input regarding circumstance data, the interface for accepting input regarding circumstance data operably coupleable to the at least one first processor and to the at least one first memory, the circumstance data regarding a subject of the at least one requirement; at least one second processor and at least one second memory, the at least one second processor operably coupleable to the interface for accepting input regarding circumstance data, the at least one second processor and the at least one second memory operable to apply the rule set to the input regarding circumstance data; and at least one third processor and at least one third memory, the at least one third processor and at least one third memory operable to generate a compliance audit, the at least one third processor and the at least one third memory operably coupleable to the at least one second processor for applying the rule set to the input regarding circumstance data, the compliance audit based on an application of the rule set to the input regarding circumstance data; wherein the circumstance data comprises: product class data to identify a general class of products for an item of manufacture; and at least one item from the group consisting of: product type data to identify a more specific type of product, within the general class of products, for the item of manufacture; product attribute data to identify a property of the item of manufacture; and customer data to identify a type of customer for the item of manufacture.

18. A system for conducting a compliance audit, the system comprising: at least one first processor and at least one first memory operably coupleable to the at least one first processor, the first processor and the first memory operable to access a database, wherein the database includes a knowledge base, the knowledge base including a rule set, the rule set including rules formulated from at least one requirement; an interface operable to accept input regarding circumstance data, the interface for accepting input regarding circumstance data operably coupleable to the at least one first processor and to the at least one first memory, the circumstance data regarding a subject of the at least one requirement; at least one second processor and at least one second memory, the at least one second processor operably coupleable to the interface for accepting input regarding circumstance data, the at least one second processor and the at least one second memory operable to apply the rule set to the input regarding circumstance data; and at least one third processor and at least one third memory, the at least one third processor and at least one third memory operable to generate a compliance audit, the at least one third processor and the at least one third memory operably coupleable to the at least one second processor for applying the rule set to the input regarding circumstance data, the compliance audit based on an application of the rule set to the input regarding circumstance data; wherein the circumstance data comprises: product class data to identify a general class of products for an item of manufacture; and at least one item from the group consisting of: product type data to identify a more specific type of product, within the general class of products, for the item of manufacture; product attribute data to identify a property of the item of manufacture; and customer data to identify a type of customer for the item of manufacture. 23. The system of claim 18 , wherein the accepting input regarding circumstance data, the circumstance data regarding a subject of the at least one requirement, further comprises: the accepting input regarding circumstance data, the circumstance data regarding a subject of the at least one requirement, wherein the at least one requirement includes a standard provision.

11. A method as recited in claim 1 further comprising associating respective metadata with each of the audio text files.

11. A method as recited in claim 1 further comprising associating respective metadata with each of the audio text files. 12. A method as recited in claim 11 further comprising at least one of naming each audio text file in response to the respective metadata, and naming each audio text file of the audio text files in response to the respective metadata and wherein searching comprises searching content of each audio text file of the audio text files and the respective metadata.

15. A method of air traffic management, the method comprising: predicting, by a processor, trajectories of at least two aircraft, comprising for each prediction: reading data providing a description of aircraft intent expressed using a formal language, the data provided by: receiving information defining how the at least two aircraft are to be flown during an operation interval, and storing the information in an information database; deriving a set of instructions from the information stored, wherein the set of instructions comprise configuration instructions that describe an aerodynamic configuration of the at least two aircraft and motion instructions that control motions of the at least two aircraft, wherein the aerodynamic configuration comprises a physical configuration of at least one of a high lift device, a landing gear, and a speed brake of each of the at least two aircrafts; confirming, by the processor, that the set of instructions comply with a set of rules stored in a rules database, that the configuration instructions define the aerodynamic configuration of the at least two aircraft and that the motion instructions close degrees of freedom of equations of motion used to describe the aircraft motion of the at least two aircraft during the operation interval; and expressing the set of instructions using the formal language; solving, by the processor, equations of motion defining the aircraft motion using the data and with reference to an aircraft performance model and an Earth model; comparing, by the processor, the at least two predicted trajectories to identify potential conflicts; and managing, by the processor, air traffic, including the at least two aircraft, using the at least two predicted trajectories.

15. A method of air traffic management, the method comprising: predicting, by a processor, trajectories of at least two aircraft, comprising for each prediction: reading data providing a description of aircraft intent expressed using a formal language, the data provided by: receiving information defining how the at least two aircraft are to be flown during an operation interval, and storing the information in an information database; deriving a set of instructions from the information stored, wherein the set of instructions comprise configuration instructions that describe an aerodynamic configuration of the at least two aircraft and motion instructions that control motions of the at least two aircraft, wherein the aerodynamic configuration comprises a physical configuration of at least one of a high lift device, a landing gear, and a speed brake of each of the at least two aircrafts; confirming, by the processor, that the set of instructions comply with a set of rules stored in a rules database, that the configuration instructions define the aerodynamic configuration of the at least two aircraft and that the motion instructions close degrees of freedom of equations of motion used to describe the aircraft motion of the at least two aircraft during the operation interval; and expressing the set of instructions using the formal language; solving, by the processor, equations of motion defining the aircraft motion using the data and with reference to an aircraft performance model and an Earth model; comparing, by the processor, the at least two predicted trajectories to identify potential conflicts; and managing, by the processor, air traffic, including the at least two aircraft, using the at least two predicted trajectories. 16. The method of claim 15 , further comprising resolving conflicts by advising aircraft of necessary changes to their aircraft intent.

30. The computer program product of claim 23 , where the instructions operable to cause the processor to select the one web site address include instructions to cause the processor to: ignore a particular web site address of the plurality of web site addresses based on a quantity of web pages on a web site, associated with the particular web site address.

30. The computer program product of claim 23 , where the instructions operable to cause the processor to select the one web site address include instructions to cause the processor to: ignore a particular web site address of the plurality of web site addresses based on a quantity of web pages on a web site, associated with the particular web site address. 31. The computer program product of claim 30 , where the instructions operable to cause the processor to ignore the particular web site address include one or more instructions operable to cause the processor to: compare the quantity of web pages to a threshold.

13. A computer system comprising the following: one or more processors; system memory; one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by the one or more processors, cause the computing system to execute a method for establishing a schema graph that allows queries to be answered by traversing graph nodes, the method comprising the following: an act of accessing a relational database comprising one or more database tables in a first data storage area that stores relational data; an act of extracting a schema graph from the accessed relational database, the schema graph comprising graph nodes representing the accessed database tables, the schema graph further comprising edges, which are displayed as corresponding lines and that visually represent relationships between the graph nodes, wherein at least two edges are represented as separate lines with different display attributes, the different display attributes corresponding to different relationship attributes between different nodes, the schema graph being stored in a second, different storage area; an act of associating one or more relational tables with the graph nodes of the schema graph, such that both the relational tables and the relational tables' corresponding relationships are accessible via the schema graph; an act of receiving a query at the computer system, the query specifying one or more relational tables and their relationships that are to be retrieved from the relational database; and an act of traversing the edges connecting the graph nodes of the schema graph to execute the received query.

13. A computer system comprising the following: one or more processors; system memory; one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by the one or more processors, cause the computing system to execute a method for establishing a schema graph that allows queries to be answered by traversing graph nodes, the method comprising the following: an act of accessing a relational database comprising one or more database tables in a first data storage area that stores relational data; an act of extracting a schema graph from the accessed relational database, the schema graph comprising graph nodes representing the accessed database tables, the schema graph further comprising edges, which are displayed as corresponding lines and that visually represent relationships between the graph nodes, wherein at least two edges are represented as separate lines with different display attributes, the different display attributes corresponding to different relationship attributes between different nodes, the schema graph being stored in a second, different storage area; an act of associating one or more relational tables with the graph nodes of the schema graph, such that both the relational tables and the relational tables' corresponding relationships are accessible via the schema graph; an act of receiving a query at the computer system, the query specifying one or more relational tables and their relationships that are to be retrieved from the relational database; and an act of traversing the edges connecting the graph nodes of the schema graph to execute the received query. 23. The computer system of claim 13 , wherein different relationship attributes comprise different quantities of relationships existing between different nodes.

1. A method comprising the steps of: monitoring a communication being conducted by a particular agent of a contact center and a contact party in real-time by an analytics processing system; detecting an occurrence of a particular keyphrase during the monitoring by the analytics processing system; and in response to detecting the occurrence of the particular keyphrase: querying memory based on the particular keyphrase to identify a particular information resource, wherein the particular keyphrase had been previously identified in at least two prior communications conducted between agents at the contact center and contact parties by performing at least one of speech analytics and text analytics on the prior communications and the particular information resource had been previously associated with the particular keyphrase by determining a pattern of utilization of one or more information resources used by the agents during the prior communications conducted with the contact parties in which the one or more information resources provided different information that may have been helpful to the agents during the prior communications and selecting the particular information resource based on the pattern of utilization; and making the particular information resource available to the particular agent during the communication.

1. A method comprising the steps of: monitoring a communication being conducted by a particular agent of a contact center and a contact party in real-time by an analytics processing system; detecting an occurrence of a particular keyphrase during the monitoring by the analytics processing system; and in response to detecting the occurrence of the particular keyphrase: querying memory based on the particular keyphrase to identify a particular information resource, wherein the particular keyphrase had been previously identified in at least two prior communications conducted between agents at the contact center and contact parties by performing at least one of speech analytics and text analytics on the prior communications and the particular information resource had been previously associated with the particular keyphrase by determining a pattern of utilization of one or more information resources used by the agents during the prior communications conducted with the contact parties in which the one or more information resources provided different information that may have been helpful to the agents during the prior communications and selecting the particular information resource based on the pattern of utilization; and making the particular information resource available to the particular agent during the communication. 7. The method of claim 1 further comprising the steps of: querying the memory based on the particular keyphrase to identify a second particular information resource; and making the second particular information resource available to the particular agent during the communication after making the particular information resource available to the particular agent, wherein the second particular information resource is made available after the particular information resource is made available to the particular agent because the particular information resource has a higher priority than the second particular information resource.

1. A bulletin board messaging system service, comprising: enabling a caller to indicate a selected bulletin board from a plurality of bulletin boards associated with a subscriber telephone number; enabling the caller to indicate a selected public message option from a group consisting of a recording public message option and a listening to public messages option; enabling the caller to indicate, upon providing an applicable personal identification number, a selected private message option from a group consisting of a recording private message option and a listening to private messages option; and responsive to the caller successfully indicating the selected public message option: recording a voice message of the caller; storing the voice message in a tangible storage medium; and associating the voice message stored in the tangible storage medium with the selected bulletin board.

1. A bulletin board messaging system service, comprising: enabling a caller to indicate a selected bulletin board from a plurality of bulletin boards associated with a subscriber telephone number; enabling the caller to indicate a selected public message option from a group consisting of a recording public message option and a listening to public messages option; enabling the caller to indicate, upon providing an applicable personal identification number, a selected private message option from a group consisting of a recording private message option and a listening to private messages option; and responsive to the caller successfully indicating the selected public message option: recording a voice message of the caller; storing the voice message in a tangible storage medium; and associating the voice message stored in the tangible storage medium with the selected bulletin board. 3. The service of claim 1 , further comprising: enabling the caller to indicate, responsive to the storing of the voice message, a selected public comment option from a group consisting of a recording public comment option and a listening to public comments option; and enabling the caller to indicate, in response to the storing of the voice message and upon providing the applicable personal identification number, a selected private comment option from a group consisting of a recording private comment option and a listening to private comments option; and responsive to the caller successfully indicating either the recording public comment or the recording private comment option: recording a voice comment of the caller; storing the voice comment as recorded to a tangible storage medium; and associating the voice comment as recorded with the selected bulletin board wherein the voice comment is responsive to the voice message.

9. An advertising server network for finding predictive cross-category search queries for behavioral targeting, comprising: a module for aggregating, using a computer, at least one training model dataset formed by a particular configuration of a data structure, the training model dataset comprising multiple configured data structures each representing an advertisement impression and including at least a history of clicks corresponding to historical advertisement information, a plurality of page features including a position of an advertisement within the page as shown to a particular user, and a plurality of internet property features, and the training model dataset comprising a plurality of targeting categories derived from the historical advertisement information; a module for training a baseline training model dataset with an initial feature set including page information features and advertisement information features, wherein the initial feature set is used to model a prior distribution of clicks and absence of clicks in a training set; a module for determining historical query and targeting category pairs such that the user historical query of the pair is predictive of clicks on display ads with the targeting category of the pair; a module for selecting, using a computer, a plurality of features from the at least one training model dataset, wherein the selected plurality of features include initial features and at least one candidate feature, wherein the candidate feature varies to fit training data and provides measuring likelihood gain of the candidate feature when added to the baseline training model dataset; a module for calculating a click probability for a subject advertisement to be clicked by a user from a page, said calculating using at least the selected plurality of features, wherein the initial features include features of the page, and wherein the at least one candidate feature is different from the initial features of the at least one training model dataset, and said calculating being normalized for queries that have a high click propensity and no relation to any user interest in a behavioral targeting taxonomy; and serving the subject advertisement to the user, when the click probability of the subject advertisement is predictive of clicks on display ads based on the determined historical query and targeting category pairs.

9. An advertising server network for finding predictive cross-category search queries for behavioral targeting, comprising: a module for aggregating, using a computer, at least one training model dataset formed by a particular configuration of a data structure, the training model dataset comprising multiple configured data structures each representing an advertisement impression and including at least a history of clicks corresponding to historical advertisement information, a plurality of page features including a position of an advertisement within the page as shown to a particular user, and a plurality of internet property features, and the training model dataset comprising a plurality of targeting categories derived from the historical advertisement information; a module for training a baseline training model dataset with an initial feature set including page information features and advertisement information features, wherein the initial feature set is used to model a prior distribution of clicks and absence of clicks in a training set; a module for determining historical query and targeting category pairs such that the user historical query of the pair is predictive of clicks on display ads with the targeting category of the pair; a module for selecting, using a computer, a plurality of features from the at least one training model dataset, wherein the selected plurality of features include initial features and at least one candidate feature, wherein the candidate feature varies to fit training data and provides measuring likelihood gain of the candidate feature when added to the baseline training model dataset; a module for calculating a click probability for a subject advertisement to be clicked by a user from a page, said calculating using at least the selected plurality of features, wherein the initial features include features of the page, and wherein the at least one candidate feature is different from the initial features of the at least one training model dataset, and said calculating being normalized for queries that have a high click propensity and no relation to any user interest in a behavioral targeting taxonomy; and serving the subject advertisement to the user, when the click probability of the subject advertisement is predictive of clicks on display ads based on the determined historical query and targeting category pairs. 13. The advertising server network of claim 9 , wherein aggregating the training model dataset includes aggregating a data structure including at least one of, a user cookie, a timestamp, a targeting category, a position, a property.

9. A computing apparatus, comprising: a processor; and a memory that is configured with components that are executable by the processor, the components comprising: a receiver component that receives: a first electronic document that comprises a first set of word sequences; and a second electronic document that comprises a second set of word sequences and a hyperlink to the first electronic document, wherein the first electronic document is automatically correlated with the second electronic document based at least in part upon the hyperlink to the first electronic document in the second electronic document; a feature extractor component that extracts a plurality of features based on the first electronic document and the second electronic document, the plurality of features comprising: a first distortion feature that is indicative of a difference between a position of a previously aligned word sequence and a currently aligned word sequence with respect to at least one word sequence in the first set of word sequences and the respective word sequences in the second set of word sequences or an empty word sequence; and a second distortion feature that is indicative of a difference between: an actual position of the currently aligned word sequence in the second electronic document relative to the previously aligned word sequence in the second electronic document; and an expected position of the currently aligned word sequence in the second electronic document, the expected position being adjacent to the previously aligned word sequence; and a ranker component that outputs a ranked list of word sequence pairs, wherein the word sequence pairs comprise a word sequence in the first set of word sequences and a word sequence in the second set of word sequences, wherein the ranked list of word sequence pairs are ranked in an order based at least in part upon the first distortion feature and the second distortion feature and that is indicative of an amount of parallelism between word sequences in the word sequence pairs.

9. A computing apparatus, comprising: a processor; and a memory that is configured with components that are executable by the processor, the components comprising: a receiver component that receives: a first electronic document that comprises a first set of word sequences; and a second electronic document that comprises a second set of word sequences and a hyperlink to the first electronic document, wherein the first electronic document is automatically correlated with the second electronic document based at least in part upon the hyperlink to the first electronic document in the second electronic document; a feature extractor component that extracts a plurality of features based on the first electronic document and the second electronic document, the plurality of features comprising: a first distortion feature that is indicative of a difference between a position of a previously aligned word sequence and a currently aligned word sequence with respect to at least one word sequence in the first set of word sequences and the respective word sequences in the second set of word sequences or an empty word sequence; and a second distortion feature that is indicative of a difference between: an actual position of the currently aligned word sequence in the second electronic document relative to the previously aligned word sequence in the second electronic document; and an expected position of the currently aligned word sequence in the second electronic document, the expected position being adjacent to the previously aligned word sequence; and a ranker component that outputs a ranked list of word sequence pairs, wherein the word sequence pairs comprise a word sequence in the first set of word sequences and a word sequence in the second set of word sequences, wherein the ranked list of word sequence pairs are ranked in an order based at least in part upon the first distortion feature and the second distortion feature and that is indicative of an amount of parallelism between word sequences in the word sequence pairs. 11. The computing apparatus of claim 9 , wherein the ranker component outputs the ranked list of word sequence pairs based at least in part upon word sequence alignment between the first electronic document and the second electronic document.

14. A server comprising: at least one tangible memory that stores processor-executable instructions for facilitating a search for content via the Internet; and at least one hardware computer processor, coupled to the at least one tangible memory, that executes the processor-executable instructions to: receive a first search query from a client device; identify at least one search engine to be queried; generate at least one second search query, wherein the at least one second search query is generated based, at least in part, on the content of the first search query, and wherein the at least one second search query comprises at least one formatted search query that is formatted for the at least one search engine; and send, to the client device, the at least one second search query, including the at least one formatted search query, and information specifying the identified at least one search engine to be used in performing an Internet search using the at least one second search query and the information specifying the identified at least one search engine; wherein the first search query is in audio form, and wherein the at least one hardware computer processor generates the at least one second search query by generating the at least one second search query, at least in part, by performing speech recognition on the first search query using a first language model associated with the identified at least one search engine; and wherein the identified at least one search engine is a site-specific search engine.

14. A server comprising: at least one tangible memory that stores processor-executable instructions for facilitating a search for content via the Internet; and at least one hardware computer processor, coupled to the at least one tangible memory, that executes the processor-executable instructions to: receive a first search query from a client device; identify at least one search engine to be queried; generate at least one second search query, wherein the at least one second search query is generated based, at least in part, on the content of the first search query, and wherein the at least one second search query comprises at least one formatted search query that is formatted for the at least one search engine; and send, to the client device, the at least one second search query, including the at least one formatted search query, and information specifying the identified at least one search engine to be used in performing an Internet search using the at least one second search query and the information specifying the identified at least one search engine; wherein the first search query is in audio form, and wherein the at least one hardware computer processor generates the at least one second search query by generating the at least one second search query, at least in part, by performing speech recognition on the first search query using a first language model associated with the identified at least one search engine; and wherein the identified at least one search engine is a site-specific search engine. 19. The server of claim 14 , wherein the at least one hardware computer processor, executes the processor-executable instructions to identify the at least one search engine to be queried based on the content of the first search query.

8. A system, comprising: a document converter that, when operating, receives a textual data set comprising a plurality of character codes, each respective character code comprising a code value indicating at least one respective text character to be visually rendered; and a graphical encoder that, when operating, determines, based on the textual data set, a drawing instruction set comprising, for each respective code value within the plurality of character codes, a respective at least one drawing instruction in a rendering language to draw at least part of a glyph of the respective code value, wherein each respective at least one drawing instruction excludes an indication of a correspondence with the respective character code, wherein each respective at least one drawing instruction for a specified text character excludes instructions to repeat drawing instructions specified for other instances of the specified text character.

8. A system, comprising: a document converter that, when operating, receives a textual data set comprising a plurality of character codes, each respective character code comprising a code value indicating at least one respective text character to be visually rendered; and a graphical encoder that, when operating, determines, based on the textual data set, a drawing instruction set comprising, for each respective code value within the plurality of character codes, a respective at least one drawing instruction in a rendering language to draw at least part of a glyph of the respective code value, wherein each respective at least one drawing instruction excludes an indication of a correspondence with the respective character code, wherein each respective at least one drawing instruction for a specified text character excludes instructions to repeat drawing instructions specified for other instances of the specified text character. 12. The system of claim 8 , wherein the textual data set comprises: a first character code indicating a first presentation of a specified text character at a first location; and a second character code indicating a second presentation of the specified text character at a second location different from the first location, wherein a presentation of the specified text character comprises a particular drawing segment that has a particular length and a particular shape, and wherein a respective at least one drawing instruction for the first presentation specifies a respective first drawing segment corresponding to the particular drawing segment that has a first length and a first shape, and a respective at least one drawing instruction for the second presentation specifies a respective second drawing segment corresponding to the particular drawing segment that has a second length and a second shape, wherein at least one of the second length is a perturbation of the first length or the second shape is a perturbation of the first shape.

1. A method for managing an information storage infrastructure and a flexible development environment for data storage using a computer system, comprising: managing system resources including a relational database; authenticating and selectively providing access to users through predetermined user roles; creating a metadata model for organizing instance data having metadata elements and relationships among the elements, wherein the metadata model is represented using trees and graphs in a table driven infrastructure; running processes and generating said instance data; storing the instance data, using said metadata model, in a plurality of tables having said table driven infrastructure within said relational database; performing transforms of the instance data, comprising rendering said instance data into at least one view; and keeping an audit trail of changes to said instance data.

1. A method for managing an information storage infrastructure and a flexible development environment for data storage using a computer system, comprising: managing system resources including a relational database; authenticating and selectively providing access to users through predetermined user roles; creating a metadata model for organizing instance data having metadata elements and relationships among the elements, wherein the metadata model is represented using trees and graphs in a table driven infrastructure; running processes and generating said instance data; storing the instance data, using said metadata model, in a plurality of tables having said table driven infrastructure within said relational database; performing transforms of the instance data, comprising rendering said instance data into at least one view; and keeping an audit trail of changes to said instance data. 12. A method in accordance with claim 1 , wherein said step of storing the instance data comprises storing the instance data in XML format within said relational database.

76. The computer program product of claim 75 , and further comprising computer code for displaying, in response to a first user interaction, the first additional information associated with the first message, utilizing the at least one window.

76. The computer program product of claim 75 , and further comprising computer code for displaying, in response to a first user interaction, the first additional information associated with the first message, utilizing the at least one window. 91. The computer program product of claim 76 , wherein the computer program product is configured such that the first additional information includes more information with respect to the first information.

13. The cluster computing system as recited in claim 12 , wherein the first compute node executes a database engine for accessing the database of the job state object, wherein the database engine comprises a runtime library.

13. The cluster computing system as recited in claim 12 , wherein the first compute node executes a database engine for accessing the database of the job state object, wherein the database engine comprises a runtime library. 14. The cluster computing system as recited in claim 13 , wherein the database engine is a single file relational database technology database engine.

1. A computerized method for evaluating a patent document, comprising: in a computer having a processor configured for: (a) introducing one or more patent indices, characterizing different aspects of the patent document, and a Patent Quality (PQ) index, depending on said one or more patent indices; a monetary value of the patent document being a function of said PQ index; (b) the Patent Quality index having a single numerical value, and being varied on a bounded interval for said PQ index having respective PQ min and PQ max values; each patent index having a single numerical value and being defined on a bounded interval for each said patent index having respective minimal and maximal values; and (c) transforming said one or more patent indices into said Patent Quality index according to a deterministic non-linear transformation; said non-linear transformation being continuous, monotonous with respect to each of said patent indices, said non-linear transformation being non-linear with respect to at least one of said patent indices; wherein said patent indices and said non-linear transformation are chosen so as to satisfy the following: tending of any one of said patent indices substantially to a respective minimal value, results in said Patent Quality index tending substantially to one of the following, independent of values of other patent indices: the PQ min ; the PQ max ; and wherein said non-linear transformation has a parameter of non-linearity expressed as a real number, and wherein said non-linear transformation is a single-valued transformation providing a single numerical value for said PQ index for any parameter of non-linearity.

1. A computerized method for evaluating a patent document, comprising: in a computer having a processor configured for: (a) introducing one or more patent indices, characterizing different aspects of the patent document, and a Patent Quality (PQ) index, depending on said one or more patent indices; a monetary value of the patent document being a function of said PQ index; (b) the Patent Quality index having a single numerical value, and being varied on a bounded interval for said PQ index having respective PQ min and PQ max values; each patent index having a single numerical value and being defined on a bounded interval for each said patent index having respective minimal and maximal values; and (c) transforming said one or more patent indices into said Patent Quality index according to a deterministic non-linear transformation; said non-linear transformation being continuous, monotonous with respect to each of said patent indices, said non-linear transformation being non-linear with respect to at least one of said patent indices; wherein said patent indices and said non-linear transformation are chosen so as to satisfy the following: tending of any one of said patent indices substantially to a respective minimal value, results in said Patent Quality index tending substantially to one of the following, independent of values of other patent indices: the PQ min ; the PQ max ; and wherein said non-linear transformation has a parameter of non-linearity expressed as a real number, and wherein said non-linear transformation is a single-valued transformation providing a single numerical value for said PQ index for any parameter of non-linearity. 11. The method as described in claim 1 , the step (c) comprising selecting the non-linear transformation as follows: PQ = 1 1 - b + b · ( K 1 x 1 + K 2 x 2 + … + K n x n ) , wherein b is the parameter of non-linearity, x 1 , x 2 , . . . , x n are patent indices, and K i , i=1, . . . n is a coefficient indicating relative contribution of the i-th patent index into the PQ, where K 1 +K 2 + . . . +K n =1.

13. A non-transitory machine readable storage device tangibly storing a program of machine-readable instructions executable by a computer-based machine, which instructions, when performed by the computer-based machine, cause the computer-based machine to perform operations comprising: receiving, over a network, via a network interface, a digital location identifier for navigation to a shared reading location with an associated annotation, said digital location identifier specifying the shared reading location within a version of the electronic reference document and does not include the version of the electronic reference document; upon receipt of a selection to navigate to the shared reading location, determining if a user has sufficient rights to use a copy of the electronic reference document referenced by the digital location identifier, and, if the user does not have sufficient rights, (i) providing a prompt with an option for the user to purchase said rights, (ii) responsive to confirmation of the purchase of the rights to use the copy of the electronic reference document, receiving the copy of the electronic reference document, and (iii) storing the copy of the electronic reference document in the digital memory; and upon successful confirmation of the user's rights to use the copy of the electronic reference document and responsive to the selection to navigate to the shared reading location (i) determining that the content referenced by the digital location identifier exists in the copy of the reference document, (ii) displaying at least a portion of the copy of the electronic reference document at the shared reading location and the associated annotation within the copy of the electronic reference document at the shared reading location.

13. A non-transitory machine readable storage device tangibly storing a program of machine-readable instructions executable by a computer-based machine, which instructions, when performed by the computer-based machine, cause the computer-based machine to perform operations comprising: receiving, over a network, via a network interface, a digital location identifier for navigation to a shared reading location with an associated annotation, said digital location identifier specifying the shared reading location within a version of the electronic reference document and does not include the version of the electronic reference document; upon receipt of a selection to navigate to the shared reading location, determining if a user has sufficient rights to use a copy of the electronic reference document referenced by the digital location identifier, and, if the user does not have sufficient rights, (i) providing a prompt with an option for the user to purchase said rights, (ii) responsive to confirmation of the purchase of the rights to use the copy of the electronic reference document, receiving the copy of the electronic reference document, and (iii) storing the copy of the electronic reference document in the digital memory; and upon successful confirmation of the user's rights to use the copy of the electronic reference document and responsive to the selection to navigate to the shared reading location (i) determining that the content referenced by the digital location identifier exists in the copy of the reference document, (ii) displaying at least a portion of the copy of the electronic reference document at the shared reading location and the associated annotation within the copy of the electronic reference document at the shared reading location. 17. The non-transitory machine-readable storage device of claim 13 , wherein the instructions further comprise instructions, which when performed by the machine, cause the machine to perform the operations comprising: displaying a plurality of annotations received from one or more electronic devices, each associated with a corresponding reading location within the electronic reference document.

15. The method of claim 12 , further comprising displaying an interactive graphical object simultaneously with the subset of messages, wherein interaction with the interactive graphical object causes messages presented to the user to alter.

15. The method of claim 12 , further comprising displaying an interactive graphical object simultaneously with the subset of messages, wherein interaction with the interactive graphical object causes messages presented to the user to alter. 17. The method of claim 15 , wherein the interactive graphical object comprises a selectable map that indicates message volume by geographic location, wherein selection of a portion of the map causes the messages to be filtered based upon a geographic location corresponding to the portion of the map.

9. The method of claim 2 , further comprising: recognizing, by the processing device, an identity of the customer premise equipment user; and verifying, by the processing device, the identity of the customer premise equipment user.

9. The method of claim 2 , further comprising: recognizing, by the processing device, an identity of the customer premise equipment user; and verifying, by the processing device, the identity of the customer premise equipment user. 11. The method of claim 9 , further comprising: utilizing, by the processing device, biometrics to recognize and verify the identity of the customer premise equipment user.

1. A method performed on at least one processor of speech recognition wherein the speech recognition system replaces a generic language model with a user specific language model, comprising: receiving analog audio from a specific speaker; digitizing the analog audio to generate a corpus of material associated with the specific speaker; receiving a user specific language model that is formed from the corpus of material associated with the specific speaker; determining whether a continuous speech recognition system should use a generic language model or the user specific language model, wherein the step of determining comprises: estimating an asymptotic size of the user specific language model; calculating a number of user specific n-grams missing from the generic language model; calculating a number of user specific n-grams missing from the user specific language model; and determining whether the number of user specific n-grams missing from the user specific language model is less than a parameterization factor times the number of user specific n-grams missing from the generic language model; and if it is determined that the continuous speech recognition system should use the generic language model, repeating the receiving step and the determining step until it is determined that the continuous speech recognition system should use the user specific language model; and if it is determined that the continuous speech recognition system should use the user specific language model, causing the continuous speech recognition system to replace the generic language model with the user specific language model.

1. A method performed on at least one processor of speech recognition wherein the speech recognition system replaces a generic language model with a user specific language model, comprising: receiving analog audio from a specific speaker; digitizing the analog audio to generate a corpus of material associated with the specific speaker; receiving a user specific language model that is formed from the corpus of material associated with the specific speaker; determining whether a continuous speech recognition system should use a generic language model or the user specific language model, wherein the step of determining comprises: estimating an asymptotic size of the user specific language model; calculating a number of user specific n-grams missing from the generic language model; calculating a number of user specific n-grams missing from the user specific language model; and determining whether the number of user specific n-grams missing from the user specific language model is less than a parameterization factor times the number of user specific n-grams missing from the generic language model; and if it is determined that the continuous speech recognition system should use the generic language model, repeating the receiving step and the determining step until it is determined that the continuous speech recognition system should use the user specific language model; and if it is determined that the continuous speech recognition system should use the user specific language model, causing the continuous speech recognition system to replace the generic language model with the user specific language model. 2. The method of claim 1 further comprising the step of updating the user specific language model.

1. A computer-implemented method for extracting pixel-level micro-features from image data captured by a video camera, the method comprising: receiving the image data; identifying a set of pixels in the image data associated with a foreground patch that depicts a foreground object; evaluating appearance values of the pixels included in the set of pixels to compute a plurality of micro-feature values representing the foreground object, each based on at least one pixel-level characteristic of the foreground patch, wherein the micro-feature values are computed independent of training data that defines a plurality of object types; generating a micro-feature vector that includes the plurality of micro-feature values; classifying the foreground object as depicting an object type as based on the micro-feature vector, wherein the object type is determined by mapping the micro-feature vector to a cluster in a self-organizing map (SOM) adaptive resonance theory (ART) network generated from a plurality of micro-feature vectors; and updating one or more cluster properties associated with the cluster based on the plurality of micro-feature values in the generated micro-feature vector.

1. A computer-implemented method for extracting pixel-level micro-features from image data captured by a video camera, the method comprising: receiving the image data; identifying a set of pixels in the image data associated with a foreground patch that depicts a foreground object; evaluating appearance values of the pixels included in the set of pixels to compute a plurality of micro-feature values representing the foreground object, each based on at least one pixel-level characteristic of the foreground patch, wherein the micro-feature values are computed independent of training data that defines a plurality of object types; generating a micro-feature vector that includes the plurality of micro-feature values; classifying the foreground object as depicting an object type as based on the micro-feature vector, wherein the object type is determined by mapping the micro-feature vector to a cluster in a self-organizing map (SOM) adaptive resonance theory (ART) network generated from a plurality of micro-feature vectors; and updating one or more cluster properties associated with the cluster based on the plurality of micro-feature values in the generated micro-feature vector. 7. The computer-implemented method of claim 1 , wherein one of the computed micro-feature values is an absolute value of a cosine of an angle of alignment between a major axis and an orientation line of the foreground patch and the pixel-level characteristic is the orientation line of the foreground patch.

1. A visualization system that generates a customized visualization in an industrial automation environment, comprising: a processor, communicatively coupled to a memory, and configured to execute computer-executable components, the computer-executable components comprising: a context component configured to capture context information regarding a first data visualization, wherein the first data visualization presents data received from at least one device of the industrial automation environment and the captured context information relates to interaction with the first data visualization during presentment of the received data by the first data visualization; and a visualization component configured to: determine, based upon the captured context information, an inability of the first data visualization to present the received data in accord with the captured context information; and a second data visualization, wherein the second data visualization facilitates presentation of the received data in accord with the captured context information; and dynamically replace, in response to the second data visualization being determined, the first visualization with the second visualization.

1. A visualization system that generates a customized visualization in an industrial automation environment, comprising: a processor, communicatively coupled to a memory, and configured to execute computer-executable components, the computer-executable components comprising: a context component configured to capture context information regarding a first data visualization, wherein the first data visualization presents data received from at least one device of the industrial automation environment and the captured context information relates to interaction with the first data visualization during presentment of the received data by the first data visualization; and a visualization component configured to: determine, based upon the captured context information, an inability of the first data visualization to present the received data in accord with the captured context information; and a second data visualization, wherein the second data visualization facilitates presentation of the received data in accord with the captured context information; and dynamically replace, in response to the second data visualization being determined, the first visualization with the second visualization. 2. The visualization system of claim 1 , wherein the first data visualization comprises a first display object.

1. A computer-implemented method comprising: receiving a request to identify trending search queries in a search system; grouping a plurality of search queries into a plurality of clusters of search queries; associating each cluster of search queries with a respective representative category; determining, by one or more computers and for each cluster of search queries, a cluster score based on a cluster performance score or a category popularity score, wherein the category popularity score of a particular category is a score whose value correlates with the number of clusters associated with the particular category, and wherein the cluster performance score of a particular cluster is a score whose value correlates with a respective rank of one or more pages that are identified for one or more of search queries that are grouped into the particular cluster; generating a ranking of the clusters of search queries based on the cluster scores; and presenting, as a representation of the trending search queries in the search system, information identifying a subset of the clusters of search queries as ranked according to the ranking.

1. A computer-implemented method comprising: receiving a request to identify trending search queries in a search system; grouping a plurality of search queries into a plurality of clusters of search queries; associating each cluster of search queries with a respective representative category; determining, by one or more computers and for each cluster of search queries, a cluster score based on a cluster performance score or a category popularity score, wherein the category popularity score of a particular category is a score whose value correlates with the number of clusters associated with the particular category, and wherein the cluster performance score of a particular cluster is a score whose value correlates with a respective rank of one or more pages that are identified for one or more of search queries that are grouped into the particular cluster; generating a ranking of the clusters of search queries based on the cluster scores; and presenting, as a representation of the trending search queries in the search system, information identifying a subset of the clusters of search queries as ranked according to the ranking. 8. The method of claim 1 , wherein associating each cluster of search queries with a respective representative category further comprises: for each cluster: associating each search query in the cluster with one or more categories based on a respective set of result documents responsive to the search query; and associating the cluster with a respective representative category based on the category associations of the cluster's search queries.

18. The electronic device of claim 17 , wherein the upper sublayer data manager is configured to: maintain an internal model for the data; provide access to data based on a set of predefined paths established by a profile definition; track changes to the data; and resolve conflicts that may arise between multiple updaters of the data set.

18. The electronic device of claim 17 , wherein the upper sublayer data manager is configured to: maintain an internal model for the data; provide access to data based on a set of predefined paths established by a profile definition; track changes to the data; and resolve conflicts that may arise between multiple updaters of the data set. 19. The electronic device of claim 18 , wherein the lower sublayer protocol engine is configured to: bind requests to a particular node or remote service endpoint; maintain transactions for the data management entity to local smart data management entities of connected devices in the fabric; encode communications a predefined format; and interact with a fabric exchange manager to facilitate communication with the local smart data management entities of the connected devices.

1. A method of computer implemented sorting of a plurality of documents relevant to one or more of a plurality of specialties, said method being employed to construct or maintain a computer accessible database to be accessed by a plurality of readers or groups of readers, said method comprising the steps of developing a list of said plurality of specialties in a field of interest to said plurality of readers or groups of readers, identifying documents relevant to respective ones of said one or more specialties, wherein said step of identifying is carried out by at least one expert in said one or more specialties, said expert being a person, selecting a limited number of documents for inclusion in said plurality of documents, wherein said step of selecting is carried out by at least one expert in said one or more specialties, said expert being a person, developing a hierarchical master index of subject matter referred to in said plurality of documents, each entry in said hierarchical master index having at least one of an index term and an associated code, wherein said step of developing a hierarchical master index is carried out by at least one expert in said one or more specialties, said expert being a person, assigning a limited number of index terms and associated codes of said hierarchical master index to each document of said plurality of documents, wherein said step of assigning a limited number of index terms and associated codes is carried out by at least one expert in said one or more specialties, said expert being a person, and wherein said step of assigning a limited number of index terms or codes is based on primary relevance of material described as determined by said expert, assigning at least one of said one or more specialties of said list of specialties developed in said developing step to each document of said plurality of documents, wherein said step of assigning at least one of said one or more specialties is carried out separately from said step of assigning a limited number of index terms by at least one expert in said one or more specialties, said expert being a person, assembling, using a computer, a plurality of hierarchical specialty indices of subject matter for respective ones of said plurality of specialties from index terms and associated codes assigned to respective documents in each of said ones of said plurality of specialties, wherein results of said step of assigning a limited number of index terms and results of said step of assigning at least one of said plurality of specialties as applied to respective ones of said documents identified in said step of identifying documents relevant to respective ones of said one or more specialities are merged by said computer, and sorting, using said computer, respective documents of said plurality of documents in accordance with a respective one of said plurality of hierarchical speciality indices for a respective one or more specialties, wherein said method results in construction or maintenance of a database from which documents, limited in number in accordance with said selecting step and relevant to each respective speciality, are retrieved with improved accuracy and reduction of false positives, and wherein the creation of empty folders in said hierarchical speciality indices is prevented.

1. A method of computer implemented sorting of a plurality of documents relevant to one or more of a plurality of specialties, said method being employed to construct or maintain a computer accessible database to be accessed by a plurality of readers or groups of readers, said method comprising the steps of developing a list of said plurality of specialties in a field of interest to said plurality of readers or groups of readers, identifying documents relevant to respective ones of said one or more specialties, wherein said step of identifying is carried out by at least one expert in said one or more specialties, said expert being a person, selecting a limited number of documents for inclusion in said plurality of documents, wherein said step of selecting is carried out by at least one expert in said one or more specialties, said expert being a person, developing a hierarchical master index of subject matter referred to in said plurality of documents, each entry in said hierarchical master index having at least one of an index term and an associated code, wherein said step of developing a hierarchical master index is carried out by at least one expert in said one or more specialties, said expert being a person, assigning a limited number of index terms and associated codes of said hierarchical master index to each document of said plurality of documents, wherein said step of assigning a limited number of index terms and associated codes is carried out by at least one expert in said one or more specialties, said expert being a person, and wherein said step of assigning a limited number of index terms or codes is based on primary relevance of material described as determined by said expert, assigning at least one of said one or more specialties of said list of specialties developed in said developing step to each document of said plurality of documents, wherein said step of assigning at least one of said one or more specialties is carried out separately from said step of assigning a limited number of index terms by at least one expert in said one or more specialties, said expert being a person, assembling, using a computer, a plurality of hierarchical specialty indices of subject matter for respective ones of said plurality of specialties from index terms and associated codes assigned to respective documents in each of said ones of said plurality of specialties, wherein results of said step of assigning a limited number of index terms and results of said step of assigning at least one of said plurality of specialties as applied to respective ones of said documents identified in said step of identifying documents relevant to respective ones of said one or more specialities are merged by said computer, and sorting, using said computer, respective documents of said plurality of documents in accordance with a respective one of said plurality of hierarchical speciality indices for a respective one or more specialties, wherein said method results in construction or maintenance of a database from which documents, limited in number in accordance with said selecting step and relevant to each respective speciality, are retrieved with improved accuracy and reduction of false positives, and wherein the creation of empty folders in said hierarchical speciality indices is prevented. 5. The method as recited in claim 1 , wherein codes are applied to entries in said hierarchical master index, said codes relating to subject matter of respective entries.

29. A design tool comprising: a processor configured to: determine a user selected construct within the design tool; receive a selection of a computing environment within the design tool, the computing environment being selected from at least one textual computing environment and at least one graphical computing environment; identify the selected computing environment into which the selected construct is placed; determine a position of the user selected construct placed in the selected computing environment; select a template based on the selected computing environment and the user selected construct; and insert the selected template into the selected computing environment at the determined position in the selected computing environment.

29. A design tool comprising: a processor configured to: determine a user selected construct within the design tool; receive a selection of a computing environment within the design tool, the computing environment being selected from at least one textual computing environment and at least one graphical computing environment; identify the selected computing environment into which the selected construct is placed; determine a position of the user selected construct placed in the selected computing environment; select a template based on the selected computing environment and the user selected construct; and insert the selected template into the selected computing environment at the determined position in the selected computing environment. 32. The design tool according to claim 29 , wherein the design tool comprises a standalone graphical application.

3. The system of claim 2 , wherein the particular template further comprises query specification data that is used by a query formulator to generate a structured query comprising a first clause that specifies how the corresponding particular input is compared to the one or more data structures when conducting a search.

3. The system of claim 2 , wherein the particular template further comprises query specification data that is used by a query formulator to generate a structured query comprising a first clause that specifies how the corresponding particular input is compared to the one or more data structures when conducting a search. 5. The system of claim 3 , wherein the structured query further comprises: a particular search filter with a required value indicated by the query specification data.

7. The text classifier of claim 1 wherein the feature vector is based only on words in a vocabulary supported by the natural language interface.

7. The text classifier of claim 1 wherein the feature vector is based only on words in a vocabulary supported by the natural language interface. 8. The text classifier of claim 7 wherein the feature vector is based on n-grams of the words in the vocabulary.

12. A system for voice transformation comprising: a processor; a voice transformation component for transforming a source speech of a person using transformation parameters, wherein the transforming comprises modifying the source speech to sound as if the source speech were spoken by a different person; and a steganography component for encoding information on the transformation parameters in an output speech using steganography; wherein the source speech can be reconstructed using the output speech and the information on the transformation parameters.

12. A system for voice transformation comprising: a processor; a voice transformation component for transforming a source speech of a person using transformation parameters, wherein the transforming comprises modifying the source speech to sound as if the source speech were spoken by a different person; and a steganography component for encoding information on the transformation parameters in an output speech using steganography; wherein the source speech can be reconstructed using the output speech and the information on the transformation parameters. 16. The system as claimed in claim 12 , including a compiling component for compiling the information on the transformation parameters including: a quantizing component for quantizing the transformation parameters; and a binary stream component for converting the quantized transformation parameters to a binary stream.

4. The method of claim 2 , wherein the scheme further includes a group number.

4. The method of claim 2 , wherein the scheme further includes a group number. 5. The method of claim 4 , further comprising adding a separator to at least a first document in each group before printing the documents from the sorted document stream.

1. A method for computerized batching of huge populations of electronic documents, including computerized assignment of electronic documents into at least one sequence of electronic document batches such that each document is assigned to a batch in the sequence of batches and such that absent conflict between batching requirements, the following batching requirements being maintained by a suitably programmed processor: a. pre-defined subsets of documents are always kept together in the same batch b. batches are equal in size c. the population is partitioned into clusters and all documents in any given batch belong to a single cluster rather than to two or more clusters, the method also comprising filling batches, separately for each of several clusters, including first using large keep-together sets as batches and then combining keep-together sets other than the large sets into batches and finally ordering the resulting batches into a sequence according to urgency.

1. A method for computerized batching of huge populations of electronic documents, including computerized assignment of electronic documents into at least one sequence of electronic document batches such that each document is assigned to a batch in the sequence of batches and such that absent conflict between batching requirements, the following batching requirements being maintained by a suitably programmed processor: a. pre-defined subsets of documents are always kept together in the same batch b. batches are equal in size c. the population is partitioned into clusters and all documents in any given batch belong to a single cluster rather than to two or more clusters, the method also comprising filling batches, separately for each of several clusters, including first using large keep-together sets as batches and then combining keep-together sets other than the large sets into batches and finally ordering the resulting batches into a sequence according to urgency. 2. The method according to claim 1 wherein absent conflict between batching requirements, the following batching requirement is also maintained: positions of documents within the sequence of batches are determined by the document's pre-known urgency for review such that highly urgent documents appear in early batches and less urgent documents appear in later batches.

9. A computer program product residing on a non-transitory computer readable storage medium having a plurality of instructions stored thereon, which when executed by a processor, cause the processor to perform operations comprising: receiving, using one or more computing devices, an image having a character string that includes one or more characters; receiving, using the one or more computing devices, a character string identifying each of the one or more characters; automatically generating, using the one or more computing devices, at least one segmentation parameter; performing segmentation, using the one or more computing devices, on the image having the character string using the at least one segmentation parameter, wherein segmentation is configured to separate each character of the character string; determining, using the one or more computing devices, if a resultant segmentation satisfies an ASCII uniformity criteria; and if the resultant segmentation satisfies the A criteria, selecting the at least one segmentation parameter.

9. A computer program product residing on a non-transitory computer readable storage medium having a plurality of instructions stored thereon, which when executed by a processor, cause the processor to perform operations comprising: receiving, using one or more computing devices, an image having a character string that includes one or more characters; receiving, using the one or more computing devices, a character string identifying each of the one or more characters; automatically generating, using the one or more computing devices, at least one segmentation parameter; performing segmentation, using the one or more computing devices, on the image having the character string using the at least one segmentation parameter, wherein segmentation is configured to separate each character of the character string; determining, using the one or more computing devices, if a resultant segmentation satisfies an ASCII uniformity criteria; and if the resultant segmentation satisfies the A criteria, selecting the at least one segmentation parameter. 16. The computer program product of claim 9 , wherein the at least one segmentation parameter includes one or more polarity, line refinement, angle search range, skew search range, normalization mode, stroke width, binarization threshold, border fragments, pixel count, fragment contrast threshold, character height, character width, intercharacter gap, intracharacter gap, fragment distance to main line, fragment merge mode, minimum character aspect, character width type, analysis mode, pitch metric, pitch type, minimum pitch, space insertion, width of space character.

8. A system for extracting content from input markup language text comprising: at least one computer that: (a) classifies the input markup language text into a classification; (b) after classifying the input markup language text, parses the input markup language text into a first hierarchical data model; (c) generates a second hierarchical data model based on the first hierarchical data model using one or more filters to remove content from the first hierarchical data model, wherein at least one setting of the one or more filters controls the removal of content from two or more portions of the first hierarchical data model, and wherein the at least on setting is selected based on the classification of the input markup language text; and (d) generates output markup language text from the second hierarchical data model, wherein one of the one or more filters removes at least one of tables, programming script, styles and image links from the first hierarchical data model based on one or more predetermined rules, wherein one of the one or more predetermined rules is removing tables containing less than a threshold number of characters, and wherein one of the one or more predetermined rules is removing image links that have a source equivalent to any source within a set of blocked sources.

8. A system for extracting content from input markup language text comprising: at least one computer that: (a) classifies the input markup language text into a classification; (b) after classifying the input markup language text, parses the input markup language text into a first hierarchical data model; (c) generates a second hierarchical data model based on the first hierarchical data model using one or more filters to remove content from the first hierarchical data model, wherein at least one setting of the one or more filters controls the removal of content from two or more portions of the first hierarchical data model, and wherein the at least on setting is selected based on the classification of the input markup language text; and (d) generates output markup language text from the second hierarchical data model, wherein one of the one or more filters removes at least one of tables, programming script, styles and image links from the first hierarchical data model based on one or more predetermined rules, wherein one of the one or more predetermined rules is removing tables containing less than a threshold number of characters, and wherein one of the one or more predetermined rules is removing image links that have a source equivalent to any source within a set of blocked sources. 14. The system of claim 8 , wherein the output markup language text generated from the second hierarchical data model is in a different markup language than the input markup language text.

1. A method for translating electronic messages sent from a first party to a second different party, comprising: receiving at a destination location of the second different party an electronic message from the first party in a source language; determining whether the source language of the electronic message that has been received is similar to a preferred destination language; translating the electronic message that has been received into the preferred destination language when the source language is not similar to the preferred destination language, wherein translating includes determining the preferred destination language, wherein determining the preferred destination language includes determining a preferred operating system language of a computing device of the second different party; providing an option to the second different party to translate the electronic message that has been received from the preferred destination language into a different language, the different language being different than the source language and the preferred destination language, and sending at the destination location a reply electronic message in the preferred destination language to the first party; wherein at the destination location of the second different party, the electronic message from the first party received at the destination location is translated and; further comprising: including an indication that the received message has been translated; wherein the indication is one of a label, a symbol, a color of text, and a background of the message.

1. A method for translating electronic messages sent from a first party to a second different party, comprising: receiving at a destination location of the second different party an electronic message from the first party in a source language; determining whether the source language of the electronic message that has been received is similar to a preferred destination language; translating the electronic message that has been received into the preferred destination language when the source language is not similar to the preferred destination language, wherein translating includes determining the preferred destination language, wherein determining the preferred destination language includes determining a preferred operating system language of a computing device of the second different party; providing an option to the second different party to translate the electronic message that has been received from the preferred destination language into a different language, the different language being different than the source language and the preferred destination language, and sending at the destination location a reply electronic message in the preferred destination language to the first party; wherein at the destination location of the second different party, the electronic message from the first party received at the destination location is translated and; further comprising: including an indication that the received message has been translated; wherein the indication is one of a label, a symbol, a color of text, and a background of the message. 14. The method of claim 1 , further comprising transmitting the electronic message in the preferred destination language for display.

17. The system of claim 16 , wherein the first custom video is accessed by the first user with the first computer and by the second user with the second computer, and wherein the first user and the second user independently of each other produce through the distribution server a first distribution of the first custom video to a first set of potential buyers and a second distribution of the second custom video to a second set of potential buyers, respectively.

17. The system of claim 16 , wherein the first custom video is accessed by the first user with the first computer and by the second user with the second computer, and wherein the first user and the second user independently of each other produce through the distribution server a first distribution of the first custom video to a first set of potential buyers and a second distribution of the second custom video to a second set of potential buyers, respectively. 18. The system of claim 17 , further comprising a third custom soundtrack produced on the second computer and added to a selected one of the first videos for the first item through the single multimedia dashboard to form a third custom video tailored for an individual client in the second set of buyers, and a third distribution of the third custom video to the individual client.

25. The recording medium according to claim 1 , wherein said multidimensional space includes a time axis.

25. The recording medium according to claim 1 , wherein said multidimensional space includes a time axis. 27. The recording medium according to claim 25 , wherein the time axis has the capability of representing intervals of time during which no version of the predefined portion is valid.

1. A method implemented by processor-executable instructions located in a storage media, the method comprising: determining a mobile-friendliness indication that is associated with a uniform resource locator (URL), wherein the mobile-friendliness indication indicates a compatibility of a page associated with the URL with one or more display characteristics of a mobile device; determining the mobile-friendliness indication based on a site comparator, a markup language comparator, a mobile-specific response examiner, and a site content analyzer to identify multiple mobile friendliness scores; identifying the multiple mobile friendliness scores based on a first weight mobile friendliness score from the site comparator, a second weight mobile friendliness score from the markup language comparator, a third weight mobile friendliness score from the mobile-specific response examiner, and a fourth weight mobile friendliness score from the site content analyzer; producing a weighted average mobile friendliness score from the multiple mobile friendliness scores; in response to the weighted average mobile friendliness score, determining the mobile friendliness indication; and storing the determined mobile-friendliness indication.

1. A method implemented by processor-executable instructions located in a storage media, the method comprising: determining a mobile-friendliness indication that is associated with a uniform resource locator (URL), wherein the mobile-friendliness indication indicates a compatibility of a page associated with the URL with one or more display characteristics of a mobile device; determining the mobile-friendliness indication based on a site comparator, a markup language comparator, a mobile-specific response examiner, and a site content analyzer to identify multiple mobile friendliness scores; identifying the multiple mobile friendliness scores based on a first weight mobile friendliness score from the site comparator, a second weight mobile friendliness score from the markup language comparator, a third weight mobile friendliness score from the mobile-specific response examiner, and a fourth weight mobile friendliness score from the site content analyzer; producing a weighted average mobile friendliness score from the multiple mobile friendliness scores; in response to the weighted average mobile friendliness score, determining the mobile friendliness indication; and storing the determined mobile-friendliness indication. 6. The method as recited in claim 1 , wherein the determining comprises: requesting a response from the URL while impersonating a mobile-friendly user agent type; ascertaining a markup language type of the response; comparing the markup language type of the response to the mobile-friendly user agent type; and determining the mobile-friendliness indication based on the comparing.

10. A computer implemented method comprising: searching, based in part on a term identifier associated with a term, a first portion of a user-term index comprising time-ordered database shards of records for post identifiers of posts that include the term and that are associated with connections of a user, where the user-term index comprises shards of records that are searched from newest to oldest, the searching comprising: matching the term identifier to corresponding term identifiers in shards of records within the selected portion, the selected portion including user identifiers associated with connections of the user, and wherein the matching identifies post identifiers for posts that include the term and are associated with a connection of the user; and retrieving posts from an index using the identified post identifiers, the retrieved posts for presentation to the user.

10. A computer implemented method comprising: searching, based in part on a term identifier associated with a term, a first portion of a user-term index comprising time-ordered database shards of records for post identifiers of posts that include the term and that are associated with connections of a user, where the user-term index comprises shards of records that are searched from newest to oldest, the searching comprising: matching the term identifier to corresponding term identifiers in shards of records within the selected portion, the selected portion including user identifiers associated with connections of the user, and wherein the matching identifies post identifiers for posts that include the term and are associated with a connection of the user; and retrieving posts from an index using the identified post identifiers, the retrieved posts for presentation to the user. 17. The computer implemented method of claim 10 , further comprising: deleting the oldest shard, of the time-ordered database shards of records; and deleting an object store associated with the oldest shard.

25. The computer implemented method of claim 12 , wherein the graphical objects includes objects indicative of one or more nodes and one or more edges of a graph.

25. The computer implemented method of claim 12 , wherein the graphical objects includes objects indicative of one or more nodes and one or more edges of a graph. 27. The computer implemented method of claim 25 , wherein the graphical distance between the nodes is determined by a function of the association strength of the nodes that are connected to each other.

1. In a health care enterprise, a computerized provider order entry system for receiving one or more search terms from a health care provider and finding an order for providing a medication or medical service related to the one or more search terms, comprising: a repository including a plurality of records identifying a corresponding plurality of medications or medical services available for order, a record of an individual medication or medical service available for order including a plurality of related text terms describing order related parameters, including terms identifying a treatment and at least one of: (a) a diagnosis code associated with the medication or medical service available for order, (b) a medical condition associated with the medication or medical service available for order, and (c) a medical problem associated with the medication or medical service available for order; a search processor for searching said plurality of records to find candidate medications or medical services available for order corresponding to the one or more health care provider entered search terms by: determining a relative frequency of occurrence of respective ones of the one or more search terms in the related text terms of corresponding records of candidate medications or medical services available for order; summing data representing the relative frequency of occurrence of the respective ones of the one or more search terms to provide data representing a summed relative frequency of the one or more search terms in corresponding records of candidate medications or medical services available for order; identifying and prioritizing candidate medications or medical services available for order in response to the summed relative frequency of occurrence of said health care provider entered search terms in corresponding records of said candidate medications or medical services available for order; and ranking said identified and prioritized candidate medications or medical services available for order in response to a relative frequency of ordering of said identified and prioritized candidate medications or medical services available for use by health care providers; wherein said search processor alters search result ranking based on voting mechanisms for said medications or medical services available for order, said voting achieved by at least one of (a) selection of an item for order in normal use and (b) manual adjustment of priority weighting of that item for order; and an output processor for providing search result data representing said ranked, identified and prioritized candidate medications or medical services.

1. In a health care enterprise, a computerized provider order entry system for receiving one or more search terms from a health care provider and finding an order for providing a medication or medical service related to the one or more search terms, comprising: a repository including a plurality of records identifying a corresponding plurality of medications or medical services available for order, a record of an individual medication or medical service available for order including a plurality of related text terms describing order related parameters, including terms identifying a treatment and at least one of: (a) a diagnosis code associated with the medication or medical service available for order, (b) a medical condition associated with the medication or medical service available for order, and (c) a medical problem associated with the medication or medical service available for order; a search processor for searching said plurality of records to find candidate medications or medical services available for order corresponding to the one or more health care provider entered search terms by: determining a relative frequency of occurrence of respective ones of the one or more search terms in the related text terms of corresponding records of candidate medications or medical services available for order; summing data representing the relative frequency of occurrence of the respective ones of the one or more search terms to provide data representing a summed relative frequency of the one or more search terms in corresponding records of candidate medications or medical services available for order; identifying and prioritizing candidate medications or medical services available for order in response to the summed relative frequency of occurrence of said health care provider entered search terms in corresponding records of said candidate medications or medical services available for order; and ranking said identified and prioritized candidate medications or medical services available for order in response to a relative frequency of ordering of said identified and prioritized candidate medications or medical services available for use by health care providers; wherein said search processor alters search result ranking based on voting mechanisms for said medications or medical services available for order, said voting achieved by at least one of (a) selection of an item for order in normal use and (b) manual adjustment of priority weighting of that item for order; and an output processor for providing search result data representing said ranked, identified and prioritized candidate medications or medical services. 8. A system according to claim 1 , further comprising: a repository of mapping information associating an individual term with a plurality of corresponding synonyms; wherein said search processor parses said healthcare provider entered search terms and, if a search term in the one or more search terms is in the repository of mapping information, expands said healthcare provider entered search term to a corresponding plurality of search terms using said mapping information.

6. A computing system comprising: one or more processors; and computer storage storing machine-executable instructions including one or more modules configured for execution by the one or more processors in order to cause the computing system to at least: receive, by the one or more processors, a first set of information identifying an input set of documents, said input set comprising a plurality of documents; identify, by the one or more processors, an additional document that is not a member of the input set, but which is citationally related to at least some of the documents in the input set; calculate, by the one or more processors, a data value that represents a degree to which said document is citationally related to at least some of the documents in the input set, said data value dependent upon at least (a) how many citational relationships exist at generations higher than a first generation between the input set of documents and said additional document, and (b) generation levels of said citational relationships, wherein calculating said data value comprises assigning different amounts of weight to citational relationships of different generation levels, said amounts of weight being based at least in part on a generational citation count determined for each of the different generation levels and an analysis in which multi-generation citational relationships between documents are used to predict existences of first generation citational relationships between documents, said analysis performed over a document population; and store the data value in computer storage in association with identifiers of the input set of documents.

6. A computing system comprising: one or more processors; and computer storage storing machine-executable instructions including one or more modules configured for execution by the one or more processors in order to cause the computing system to at least: receive, by the one or more processors, a first set of information identifying an input set of documents, said input set comprising a plurality of documents; identify, by the one or more processors, an additional document that is not a member of the input set, but which is citationally related to at least some of the documents in the input set; calculate, by the one or more processors, a data value that represents a degree to which said document is citationally related to at least some of the documents in the input set, said data value dependent upon at least (a) how many citational relationships exist at generations higher than a first generation between the input set of documents and said additional document, and (b) generation levels of said citational relationships, wherein calculating said data value comprises assigning different amounts of weight to citational relationships of different generation levels, said amounts of weight being based at least in part on a generational citation count determined for each of the different generation levels and an analysis in which multi-generation citational relationships between documents are used to predict existences of first generation citational relationships between documents, said analysis performed over a document population; and store the data value in computer storage in association with identifiers of the input set of documents. 8. The computing system of claim 6 , wherein the analysis performed over the document population comprises a statistical analysis.

16. A computer program product comprising a computer usable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform steps comprising: generating an interface for receiving a copybook selection and REDEFINE criteria; importing a copybook from a database, the copybook corresponding with a set of COBOL data stored in the database that includes a dynamic COBOL construct; creating an object model for the copybook; receiving the set of COBOL data; identifying, based at least in part on the received set of COBOL data, an instance of a REDEFINE clause and automatically forming the REDEFINE clause as an object instance; and forming the object instance that is equivalent to the set of COBOL data, the object instance including one or more representations for a complete set of one or more properties included in the dynamic COBOL construct without requiring custom coding for the forming of the object instance.

16. A computer program product comprising a computer usable medium including a computer readable program, wherein the computer readable program when executed on a computer causes the computer to perform steps comprising: generating an interface for receiving a copybook selection and REDEFINE criteria; importing a copybook from a database, the copybook corresponding with a set of COBOL data stored in the database that includes a dynamic COBOL construct; creating an object model for the copybook; receiving the set of COBOL data; identifying, based at least in part on the received set of COBOL data, an instance of a REDEFINE clause and automatically forming the REDEFINE clause as an object instance; and forming the object instance that is equivalent to the set of COBOL data, the object instance including one or more representations for a complete set of one or more properties included in the dynamic COBOL construct without requiring custom coding for the forming of the object instance. 20. The computer program product of claim 16 , wherein the computer readable program when executed on the computer causes the computer further to receive input specifying a data source and to receive the set of COBOL data from the specified data source.

9. A computer-implemented method for providing management of a virtualization infrastructure, the method comprising: receiving a query related to the virtualization infrastructure, wherein the virtualization infrastructure is mapped into a social network comprising human members and non-human members, wherein the human members of the social network comprise users corresponding to entities of the virtualization infrastructure and groups of users, wherein the non-human members of the social network comprise components of the virtualization infrastructure, and wherein the components of the virtualization infrastructure comprise a host computing system and a virtual machine hosted by the host computing system, wherein the query is sent through the social network of the virtualization infrastructure, wherein the query is received at a user of the social network associated with a graph database, and wherein the query identifies at least one of: a type of member of the virtualization infrastructure; and a type of relationship of the virtualization infrastructure; accessing the graph database populated with members and relationships of the social network of the virtualization infrastructure, the graph database comprising nodes associated with the members of the virtualization infrastructure and edges associated with the relationships of the members of the virtualization infrastructure, wherein the relationships of the members are in accordance with an inventory structure of the virtualization infrastructure, wherein the members of the virtualization infrastructure comprises at least one host computing system, and at least one virtual machine hosted by the at least one host computing system, and wherein the nodes comprise types of members and the relationships comprise types of relationships; retrieving an answer to the query from the graph database; and transmitting the answer over the social network from the user of the social network associated with the graph database to a user of the social network associated with a source of the query.

9. A computer-implemented method for providing management of a virtualization infrastructure, the method comprising: receiving a query related to the virtualization infrastructure, wherein the virtualization infrastructure is mapped into a social network comprising human members and non-human members, wherein the human members of the social network comprise users corresponding to entities of the virtualization infrastructure and groups of users, wherein the non-human members of the social network comprise components of the virtualization infrastructure, and wherein the components of the virtualization infrastructure comprise a host computing system and a virtual machine hosted by the host computing system, wherein the query is sent through the social network of the virtualization infrastructure, wherein the query is received at a user of the social network associated with a graph database, and wherein the query identifies at least one of: a type of member of the virtualization infrastructure; and a type of relationship of the virtualization infrastructure; accessing the graph database populated with members and relationships of the social network of the virtualization infrastructure, the graph database comprising nodes associated with the members of the virtualization infrastructure and edges associated with the relationships of the members of the virtualization infrastructure, wherein the relationships of the members are in accordance with an inventory structure of the virtualization infrastructure, wherein the members of the virtualization infrastructure comprises at least one host computing system, and at least one virtual machine hosted by the at least one host computing system, and wherein the nodes comprise types of members and the relationships comprise types of relationships; retrieving an answer to the query from the graph database; and transmitting the answer over the social network from the user of the social network associated with the graph database to a user of the social network associated with a source of the query. 10. The computer-implemented method of claim 9 , wherein the query is communicated via a private message to the user of the social network associated with the graph database.

8. The method recited in claim 7 in which each said transferred data set directory is recorded on said destination diskette immediately preceding said programming modules assigned to said data set.

8. The method recited in claim 7 in which each said transferred data set directory is recorded on said destination diskette immediately preceding said programming modules assigned to said data set. 9. The method recited in claim 8 in which said step of transferring data set directories only transfers a said directory from said program source diskette if there is at least one programming module assigned to said corresponding data set.

1. A computer program product for performing operations via a spreadsheet, the computer program product comprising: one or more computer-readable, tangible storage devices; program instructions, stored on at least one of the one or more storage devices, to create in the spreadsheet a multidimensional array object, wherein: at least one element of the multidimensional array object constitutes an array with a plurality of elements, wherein the multidimensional array object comprise a set of elements, one element for each distinct list of coordinates of the multidimensional array object, the list of coordinates comprising a coordinate for each dimension of the multidimensional array object; program instructions, stored on at least one of the one or more storage devices, to access the elements of the multidimensional array object, the accessing comprising displaying the elements of the multidimensional array object as cells of the spreadsheet; and program instructions, stored on at least one of the one or more storage devices, to modify the elements of the multidimensional array object via modifying the contents of the cells of the spreadsheet.

1. A computer program product for performing operations via a spreadsheet, the computer program product comprising: one or more computer-readable, tangible storage devices; program instructions, stored on at least one of the one or more storage devices, to create in the spreadsheet a multidimensional array object, wherein: at least one element of the multidimensional array object constitutes an array with a plurality of elements, wherein the multidimensional array object comprise a set of elements, one element for each distinct list of coordinates of the multidimensional array object, the list of coordinates comprising a coordinate for each dimension of the multidimensional array object; program instructions, stored on at least one of the one or more storage devices, to access the elements of the multidimensional array object, the accessing comprising displaying the elements of the multidimensional array object as cells of the spreadsheet; and program instructions, stored on at least one of the one or more storage devices, to modify the elements of the multidimensional array object via modifying the contents of the cells of the spreadsheet. 2. The computer program product of claim 1 , wherein: the computer program product further comprises: program instructions, stored on at least one of the one or more storage devices, to provide by the spreadsheet a dimension type, an object of the type comprising a list of elements; and program instructions, stored on at least one of the one or more storage devices, to create in the spreadsheet a plurality of dimension objects; and the program instructions to create the multidimensional array object comprise program instructions, stored on at least one of the one or more storage devices, to assign a dimension object to each dimension of the multidimensional array object, wherein the elements of the dimension object constitute the coordinates of the array along the dimension.

10. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a client system, cause the client system to perform a method comprising: displaying a spreadsheet; receiving a request to add a cell value to the spreadsheet, the request containing a reference to an object and an attribute; generating a query corresponding to the request; sending the query to a fact repository; receiving the requested cell value from the fact repository, wherein the cell value correspond to a value of a fact, the fact being associated with an object in the fact repository, wherein a respective fact includes an attribute field indicating an attribute and a value field describing the indicated attributes, wherein objects in the fact repository are created by: extracting facts from web documents; determining entities with which the extracted facts are associated; storing the extracted facts in the fact repository; and associating the stored extracted facts with objects corresponding to the determined entities; inserting the received cell value into the spreadsheet.

10. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a client system, cause the client system to perform a method comprising: displaying a spreadsheet; receiving a request to add a cell value to the spreadsheet, the request containing a reference to an object and an attribute; generating a query corresponding to the request; sending the query to a fact repository; receiving the requested cell value from the fact repository, wherein the cell value correspond to a value of a fact, the fact being associated with an object in the fact repository, wherein a respective fact includes an attribute field indicating an attribute and a value field describing the indicated attributes, wherein objects in the fact repository are created by: extracting facts from web documents; determining entities with which the extracted facts are associated; storing the extracted facts in the fact repository; and associating the stored extracted facts with objects corresponding to the determined entities; inserting the received cell value into the spreadsheet. 11. The non-transitory computer readable storage medium of claim 10 , wherein the spreadsheet is a web spreadsheet page.

2. The system of claim 1 , wherein the query database further comprises a set of STI (special technology information) queries addressing the differences among a number of mask layers for the manufacturing processes.

2. The system of claim 1 , wherein the query database further comprises a set of STI (special technology information) queries addressing the differences among a number of mask layers for the manufacturing processes. 3. The system of claim 2 , wherein the query database further comprises a set of LOP (logic operation) queries addressing the differences among logic operations for the manufacturing processes.

22. A method for controlling a wager-based game played at a gaming system, the method comprising: detecting one or more identification gestures by a first player participating in a first game session at the gaming system; identifying the first player based on the detected one or more identification gestures; automatically detecting a first gesture by the first player; interpreting the first gesture with respect to a first set of criteria; generating gesture interpretation information relating to the interpretation of the first gesture; advancing a state of the first game session using at least a portion of the gesture interpretation information; and communicating the advancement of the state of the first game session to the first player via a mobile, handheld device.

22. A method for controlling a wager-based game played at a gaming system, the method comprising: detecting one or more identification gestures by a first player participating in a first game session at the gaming system; identifying the first player based on the detected one or more identification gestures; automatically detecting a first gesture by the first player; interpreting the first gesture with respect to a first set of criteria; generating gesture interpretation information relating to the interpretation of the first gesture; advancing a state of the first game session using at least a portion of the gesture interpretation information; and communicating the advancement of the state of the first game session to the first player via a mobile, handheld device. 31. The method of claim 22 further comprising: determining an active game type of the first game session at the gaming system; and interpreting the first gesture based at least in part upon the active game type of the first game session at the gaming system.

10. In a document processing system including system memory means for storing and providing said documents and routines for controlling operation of said system workstation means including memory and processor means for storing and operating upon said documents, keyboard means for entering document data and document manipulation commands and means for displaying said documents, and bus means for transferring said documents and routines between said system memory means and said workstation means, means for controlling operations of said system, comprising: in said system memory means, bus control means responsive to operation of said system for controlling said transferring of said documents and routines between said system memory means and said workstation means, means responsive to operation of said bus control means for storing and providing to said workstation means supervisory routines for controlling supervisory operations of said workstation means, means responsive to operation of said bus control means for storing a master copy of each of said documents and providing active segments of said documents to be operated upon to said workstation means, and means responsive to operation of said bus control means for storing and providing to said workstation means currently active overlays of routines for operating upon said currently active document segments, in said workstation means, document memory means for storing currently active segments of a said document being operated upon, document control means, including buffer means for transferring said document data between said document memory means and other portions of said system, document access means for storing and providing information identifying the locations in said document memory means of said currently active segments of said document currently being operated upon, and information identifying the locations in said buffer means of said document data to be transferred between said document memory means and said other portions of said system, document manipulation means, including memory means for storing said currently active overlays of said currently active document operation routines supervisory control means, including supervisory operation memory means for storing and providing a copy of said workstation supervisory operation routines for controlling supervisory operations of said workstation, and means responsive to operation of said keyboard means for providing operation vectors identifying document operations to be performed upon said document data and said document segments and supervisory operations to be performed by said system, said processor means being responsive to said operation vectors for reading and performing corresponding said document operation and supervisory operation routines, and responsive to said document operation routines for reading said location information from said document access means for locating said document segments and data to be operated upon in said document memory means and said buffer means, wherein, the only routines which perform operations upon said document segments residing in said document memory means are said document operation routines, said document operation routines access said document segments and data residing in said document memory means and said buffer means only through said location information residing in said document access means, and said document segments and data transferred between said document memory means and said keyboard and display means only through said buffer means.

10. In a document processing system including system memory means for storing and providing said documents and routines for controlling operation of said system workstation means including memory and processor means for storing and operating upon said documents, keyboard means for entering document data and document manipulation commands and means for displaying said documents, and bus means for transferring said documents and routines between said system memory means and said workstation means, means for controlling operations of said system, comprising: in said system memory means, bus control means responsive to operation of said system for controlling said transferring of said documents and routines between said system memory means and said workstation means, means responsive to operation of said bus control means for storing and providing to said workstation means supervisory routines for controlling supervisory operations of said workstation means, means responsive to operation of said bus control means for storing a master copy of each of said documents and providing active segments of said documents to be operated upon to said workstation means, and means responsive to operation of said bus control means for storing and providing to said workstation means currently active overlays of routines for operating upon said currently active document segments, in said workstation means, document memory means for storing currently active segments of a said document being operated upon, document control means, including buffer means for transferring said document data between said document memory means and other portions of said system, document access means for storing and providing information identifying the locations in said document memory means of said currently active segments of said document currently being operated upon, and information identifying the locations in said buffer means of said document data to be transferred between said document memory means and said other portions of said system, document manipulation means, including memory means for storing said currently active overlays of said currently active document operation routines supervisory control means, including supervisory operation memory means for storing and providing a copy of said workstation supervisory operation routines for controlling supervisory operations of said workstation, and means responsive to operation of said keyboard means for providing operation vectors identifying document operations to be performed upon said document data and said document segments and supervisory operations to be performed by said system, said processor means being responsive to said operation vectors for reading and performing corresponding said document operation and supervisory operation routines, and responsive to said document operation routines for reading said location information from said document access means for locating said document segments and data to be operated upon in said document memory means and said buffer means, wherein, the only routines which perform operations upon said document segments residing in said document memory means are said document operation routines, said document operation routines access said document segments and data residing in said document memory means and said buffer means only through said location information residing in said document access means, and said document segments and data transferred between said document memory means and said keyboard and display means only through said buffer means. 11. The document processing system of claim 10, wherein said operation vectors selected in response to said operation of said keyboard means are dependent upon current state of operation of said system and said system further comprises: means for storing current state of operation of said system, said processor means being responsive to a said routine presently being executed for writing said current state of said system into said means for storing said current state of operation, wherein said current state of operation is determined by said routine presently being executed, and said supervisory control means for providing operation vectors is further responsive to said current state of operation for providing said corresponding operation vectors

24. The system of claim 18 , wherein the grammar rule item includes output control instructions.

24. The system of claim 18 , wherein the grammar rule item includes output control instructions. 28. The system of claim 24 , wherein the output control instructions are implicit in the grammar rule item.

1. A method for identifying one or more queries related to a given query, the method comprising: receiving a query written according to one or more writing systems of a language with multiple writing systems; identifying a candidate set of queries written according to one or more writing systems of the language with multiple writing systems; calculating a number of common characters in a given candidate query before disagreement with the query received; calculating a number of total common characters between the given candidate query and the query received; calculating a quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs; and calculating a similarity score on the basis of the number of characters before disagreements, the number of total common characters and the quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs, wherein the similarity score indicates the similarity of the one or more queries with respect to the query received.

1. A method for identifying one or more queries related to a given query, the method comprising: receiving a query written according to one or more writing systems of a language with multiple writing systems; identifying a candidate set of queries written according to one or more writing systems of the language with multiple writing systems; calculating a number of common characters in a given candidate query before disagreement with the query received; calculating a number of total common characters between the given candidate query and the query received; calculating a quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs; and calculating a similarity score on the basis of the number of characters before disagreements, the number of total common characters and the quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs, wherein the similarity score indicates the similarity of the one or more queries with respect to the query received. 17. The method of claim 1 wherein calculating a score comprises: identifying a number of co-occurring Japanese Kanji characters in the received query and a selected query from the candidate set; identifying a total number of unique Japanese Kanji characters in the received query and the selected query from the candidate set; calculating a quotient of the number of co-occurring Japanese Kanji characters and the total number of unique Japanese Kanji characters; and calculating a difference between the numerical value one (“1”) and the calculated quotient.

22. A computer program product, embodied on a non-transitory computer-readable medium, operable on a data processing apparatus to perform operations comprising: receiving a target vector; determining a total number of dimensions associated with the received target vector; processing at least one of the target vector dimensions to determine a total number of magnitudes assigned to the processed target vector dimension; receiving a source vector; determining a total number of dimensions associated with the received source vector; processing at least one of the source vector dimensions to determine a total number of magnitudes assigned to the processed source vector dimension; and selecting one of the assigned magnitudes for the processed target vector dimension based on the determined total number of magnitudes assigned to the processed source vector dimension.

22. A computer program product, embodied on a non-transitory computer-readable medium, operable on a data processing apparatus to perform operations comprising: receiving a target vector; determining a total number of dimensions associated with the received target vector; processing at least one of the target vector dimensions to determine a total number of magnitudes assigned to the processed target vector dimension; receiving a source vector; determining a total number of dimensions associated with the received source vector; processing at least one of the source vector dimensions to determine a total number of magnitudes assigned to the processed source vector dimension; and selecting one of the assigned magnitudes for the processed target vector dimension based on the determined total number of magnitudes assigned to the processed source vector dimension. 23. The computer program product of claim 22 , further operable to cause a data processing apparatus to compare the target vector with the source vector to obtain a similarity measure.

31. A method comprising: receiving first activity information for a sender of a message sent to at least one recipient by a collection resource at a Web site, wherein the message comprises text associated with the Web site, the collection resource adds a first link to the message, and no personally identifiable information of the sender is collected in collecting the first activity information; storing the first activity information at a storage server; receiving second activity information when a first recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the first recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender; using the second activity information to identify a second node in the social graph as being representative of the first recipient; determining a category for the first link as a first category type; identifying a first edge between the first and second nodes is representative of the first category type; and in the social graph, updating a value of the first edge between the first and second nodes, wherein the using the first activity information to identify a first node in a social graph as being representative of the sender comprises: extracting a user identifier from the first activity data; and if a match for the user identifier is not found in the social graph, attempting to match a nonmobile Web browser identifier to a mobile Web browser identifier.

31. A method comprising: receiving first activity information for a sender of a message sent to at least one recipient by a collection resource at a Web site, wherein the message comprises text associated with the Web site, the collection resource adds a first link to the message, and no personally identifiable information of the sender is collected in collecting the first activity information; storing the first activity information at a storage server; receiving second activity information when a first recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the first recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender; using the second activity information to identify a second node in the social graph as being representative of the first recipient; determining a category for the first link as a first category type; identifying a first edge between the first and second nodes is representative of the first category type; and in the social graph, updating a value of the first edge between the first and second nodes, wherein the using the first activity information to identify a first node in a social graph as being representative of the sender comprises: extracting a user identifier from the first activity data; and if a match for the user identifier is not found in the social graph, attempting to match a nonmobile Web browser identifier to a mobile Web browser identifier. 34. The method of claim 31 comprising: when the sender sends the message to the first recipient and a second recipient, and the first recipient accesses the first link, updating the value of the first edge between the first and second nodes by a first amount; and when the sender sends the message to only the first recipient and no other recipients, and the first recipient accesses the first link, updating the value of the first edge between the first and second nodes by a second amount, wherein the second amount is greater than the first amount.

25. A system for testing a voice enabled application on a target device, the system comprising: the target device; a speaker configured to send sound to the target device; a noise source configured to send a noise signal to the target device; wherein the noise source comprises an acoustic noise source configured to generate the noise signal to produce the acoustic environment, the acoustic noise source replicating one or more noises of a real environment; a computer configured to conduct one or more interactions with the target device, including selecting one of a plurality of input modes for sending input to the target device and determining one of a plurality of response modes for responding to an output of the target device, at least some of the interactions comprising: sending commands to the target device using the selected input mode and receiving communications from the target device using the determined response mode; presenting an acoustic utterance in an acoustic environment to the target device; receiving an output of the target device in response to the acoustic utterance; comparing the output to an output expected from the acoustic utterance wherein the selected input mode and the determined response mode depend on input/output capabilities of the target device; wherein presenting the acoustic utterance further comprises generating the acoustic utterance using the speaker; wherein the speaker is an artificial human mouth.

25. A system for testing a voice enabled application on a target device, the system comprising: the target device; a speaker configured to send sound to the target device; a noise source configured to send a noise signal to the target device; wherein the noise source comprises an acoustic noise source configured to generate the noise signal to produce the acoustic environment, the acoustic noise source replicating one or more noises of a real environment; a computer configured to conduct one or more interactions with the target device, including selecting one of a plurality of input modes for sending input to the target device and determining one of a plurality of response modes for responding to an output of the target device, at least some of the interactions comprising: sending commands to the target device using the selected input mode and receiving communications from the target device using the determined response mode; presenting an acoustic utterance in an acoustic environment to the target device; receiving an output of the target device in response to the acoustic utterance; comparing the output to an output expected from the acoustic utterance wherein the selected input mode and the determined response mode depend on input/output capabilities of the target device; wherein presenting the acoustic utterance further comprises generating the acoustic utterance using the speaker; wherein the speaker is an artificial human mouth. 34. The system of claim 25 , wherein receiving the output further comprises receiving an image of alphanumeric characters from the target device.

1. A method comprising: adding a first attribute to a first data object in a standard repository of data objects, wherein the first data object is identified by a first name; in response to the adding the first attribute to the first data object, adding the first attribute to each data object identified by the first name in a customized repository of data objects; identifying each object, in the customized repository, that comprises an upgrade ancestor field that includes a value of the first name; and in response to the adding the first attribute to the first data object, and in response to the identifying, adding, using a processor, the first attribute to the each data object that comprises an upgrade ancestor field that includes a value of the first name.

1. A method comprising: adding a first attribute to a first data object in a standard repository of data objects, wherein the first data object is identified by a first name; in response to the adding the first attribute to the first data object, adding the first attribute to each data object identified by the first name in a customized repository of data objects; identifying each object, in the customized repository, that comprises an upgrade ancestor field that includes a value of the first name; and in response to the adding the first attribute to the first data object, and in response to the identifying, adding, using a processor, the first attribute to the each data object that comprises an upgrade ancestor field that includes a value of the first name. 3. The method of claim 1 further comprising: adding second and third attributes to a second data object in the standard repository, wherein the second data object is identified by a second name, and wherein the first and second names are distinct from each other; in response to the adding the second and third attributes to the second data object, adding the second and third attributes to each data object identified by the second name in the customized repository; and in response to the adding the second and third attributes to the second data object, adding the second and third attributes to each data object, in the customized repository, that comprises an upgrade ancestor field that includes a value of the second name.

9. A non-transitory computer-readable storage medium storing sets of instructions which, when executed by a computer, cause the computer to: define a template source for crawling a target data repository; identifying the target data repository in the template source without including in the template source security credentials required to crawl the target data repository; allow a first user to subscribe to the template source; receive first user credentials for the first user; creating a user-subscribed source based at least on the template source and the first user credentials; generate an access control list that controls access to the user-subscribed source; receive a crawl request from a second user of one or more users to crawl the target data repository; and based on user credentials of the second user and the access control list that controls access to the user-subscribed source, determine to allow the second user to initiate a crawl using the user-subscribed source; and crawl the target data repository, using the first user credentials, to index only documents which are accessible with the first user credentials.

9. A non-transitory computer-readable storage medium storing sets of instructions which, when executed by a computer, cause the computer to: define a template source for crawling a target data repository; identifying the target data repository in the template source without including in the template source security credentials required to crawl the target data repository; allow a first user to subscribe to the template source; receive first user credentials for the first user; creating a user-subscribed source based at least on the template source and the first user credentials; generate an access control list that controls access to the user-subscribed source; receive a crawl request from a second user of one or more users to crawl the target data repository; and based on user credentials of the second user and the access control list that controls access to the user-subscribed source, determine to allow the second user to initiate a crawl using the user-subscribed source; and crawl the target data repository, using the first user credentials, to index only documents which are accessible with the first user credentials. 10. The non-transitory computer-readable storage medium according to claim 9 , wherein the sets of instructions further comprise instructions which when executed by the computer cause the computer to dynamically inherit changes from the template source to the user-described source for each subsequent crawl.

1. A method for collecting information, enriching the information, and binding the information to services, said method comprising: (a) providing a note taking function to allow a user to create a note on a user device, wherein said created note is stored, wherein said note is a shared note, wherein said shared note is accessible by multiple users, wherein said shared note comprises a conversation between said multiple users, and wherein said shared note comprises a chronological list of comments of said conversation; (b) providing a categorizing function to label said note with one or more categories, wherein one or more of said categories of said note is changeable; (c) generating a code to label a physical object, wherein said code is associated with said note; (d) imaging said code, wherein said code is placed on or near said physical object; and (e) linking said physical object with said note based on said imaged code.

1. A method for collecting information, enriching the information, and binding the information to services, said method comprising: (a) providing a note taking function to allow a user to create a note on a user device, wherein said created note is stored, wherein said note is a shared note, wherein said shared note is accessible by multiple users, wherein said shared note comprises a conversation between said multiple users, and wherein said shared note comprises a chronological list of comments of said conversation; (b) providing a categorizing function to label said note with one or more categories, wherein one or more of said categories of said note is changeable; (c) generating a code to label a physical object, wherein said code is associated with said note; (d) imaging said code, wherein said code is placed on or near said physical object; and (e) linking said physical object with said note based on said imaged code. 7. The method as set forth in claim 1 , further comprising encrypting said code.

4. An apparatus to form Chinese prosodic words, comprising: an input part to input Chinese text; a word segmentation and part of speech annotating part to perform a process of word segmentation and part of speech annotation for the input Chinese text to generate an initial prosodic word sequence; a prosodic word grid insert part to insert grids representing prosodic word boundaries for all the words in the initial prosodic word sequence to generate a grid prosodic word sequence including inserting at least one eliminable indicator in the grid prosodic word sequence; a prosodic word grid delete part to annotate grids ready to be deleted in the grid prosodic word sequence based on a prosodic word forming means, the plurality of prosodic word forming means including a prosodic word forming based on a binary prosodic tree, a prosodic word forming based on statistical probability, and a prosodic word forming based on rules; a grid deletion trust degree evaluation part to comprehensively to judge grids which actually need to be deleted in the grids ready to be deleted based on a plurality of prosodic word forming means and to provide a trust degree for the grids ready to be deleted; a grid deletion part to judge whether the grids ready to be deleted actually need to be deleted based on said trust degree and to delete the grids which actually need to be deleted in the grid prosodic word sequence in accordance with a result from the grid deletion part by checking whether a current grid has been marked with the at least one eliminable indicator; and a prosodic word generating part to form the words between every two grids in the remaining grids to generate prosodic words.

4. An apparatus to form Chinese prosodic words, comprising: an input part to input Chinese text; a word segmentation and part of speech annotating part to perform a process of word segmentation and part of speech annotation for the input Chinese text to generate an initial prosodic word sequence; a prosodic word grid insert part to insert grids representing prosodic word boundaries for all the words in the initial prosodic word sequence to generate a grid prosodic word sequence including inserting at least one eliminable indicator in the grid prosodic word sequence; a prosodic word grid delete part to annotate grids ready to be deleted in the grid prosodic word sequence based on a prosodic word forming means, the plurality of prosodic word forming means including a prosodic word forming based on a binary prosodic tree, a prosodic word forming based on statistical probability, and a prosodic word forming based on rules; a grid deletion trust degree evaluation part to comprehensively to judge grids which actually need to be deleted in the grids ready to be deleted based on a plurality of prosodic word forming means and to provide a trust degree for the grids ready to be deleted; a grid deletion part to judge whether the grids ready to be deleted actually need to be deleted based on said trust degree and to delete the grids which actually need to be deleted in the grid prosodic word sequence in accordance with a result from the grid deletion part by checking whether a current grid has been marked with the at least one eliminable indicator; and a prosodic word generating part to form the words between every two grids in the remaining grids to generate prosodic words. 5. The apparatus according to claim 4 , comprising: a word dividing result storage part for storing the word dividing result after the process of word dividing and part of speech annotating the input Chinese text to generate an initial prosodic word sequence based on said word segmentation result.

19. The method of claim 18 , including the further step of providing text related to a document.

19. The method of claim 18 , including the further step of providing text related to a document. 20. The method of claim 19 , including the further step of providing continuing professional education material related to said document.