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47. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in collecting the first activity information, and the no personally identifiable information of the sender is collected comprises not collecting an e-mail address of the sender; storing the first activity information at a storage server; receiving second activity information when a 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 recipient collected in collecting the second activity information; using at least one processor, attempting to identify a first node representative of the sender in a social graph; when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph; and based on at least information associated with the second node in the social graph, selecting a personalized digital content for delivery to the sender.

47. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in collecting the first activity information, and the no personally identifiable information of the sender is collected comprises not collecting an e-mail address of the sender; storing the first activity information at a storage server; receiving second activity information when a 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 recipient collected in collecting the second activity information; using at least one processor, attempting to identify a first node representative of the sender in a social graph; when a first node representative of the sender in a social graph is not identified and after receiving the second activity information, creating a second node to represent the sender in the social graph; and based on at least information associated with the second node in the social graph, selecting a personalized digital content for delivery to the sender. 59. The method of claim 47 wherein each edge between nodes in the social graph represents a sharing category.

1. A method of providing services in a network, the method comprising: sending a service request from a service requesting network element to a service matching network element, the service matching network element storing structured service documents defining available services in a database and the service request comprising a structured request document containing a plurality of nodes; at the service matching network element: receiving the service request; forming a Path and Parent Associated Node (PPAN) element for each node in the structured request document, each PPAN element being a data structure containing a path level of a current node in the structured request document, a name and value pair associated with the current element, and a name and value pair of a parent element of the current element, the PPAN element not containing additional information about structure of the structured request document other than the path level of the current node and the parent-child relationship of the current node and its parent node; using the PPAN elements from the structured request document to identify a subset of the stored structured service documents that contain data and structure that match the PPAN elements; and sending to the service requesting network element, at least part of a structured service document in the identified subset of structured service documents; at the service requesting network element: receiving the at least part of the structured service document; and using the at least part of the structured service document to access a service defined by the at least part of the structured service document.

1. A method of providing services in a network, the method comprising: sending a service request from a service requesting network element to a service matching network element, the service matching network element storing structured service documents defining available services in a database and the service request comprising a structured request document containing a plurality of nodes; at the service matching network element: receiving the service request; forming a Path and Parent Associated Node (PPAN) element for each node in the structured request document, each PPAN element being a data structure containing a path level of a current node in the structured request document, a name and value pair associated with the current element, and a name and value pair of a parent element of the current element, the PPAN element not containing additional information about structure of the structured request document other than the path level of the current node and the parent-child relationship of the current node and its parent node; using the PPAN elements from the structured request document to identify a subset of the stored structured service documents that contain data and structure that match the PPAN elements; and sending to the service requesting network element, at least part of a structured service document in the identified subset of structured service documents; at the service requesting network element: receiving the at least part of the structured service document; and using the at least part of the structured service document to access a service defined by the at least part of the structured service document. 20. The method of claim 1 , wherein the structured request document is a Standard Generalized Markup Language (SGML) request) document.

8. A computer-implemented system for electronically signing an electronically stored document that includes document content and is accessible by the system, the system comprising: one or more processors; and one or more memory devices for storing program instructions, wherein the program instructions, when executed by the one or more processors, cause the one or more processors to: provide at least a first user and a second user remote access to the electronically stored document; apply a first electronic signature to the electronically stored document to produce an initial signed version of the electronically stored document, wherein the first electronic signature includes information that associates the first electronic signature with the initial signed version of the electronically stored document, the first electronic signature verifies integrity of the document content of the initial signed version of the electronically stored document, and the first electronic signature includes a first cryptographic component; subsequent to application of the first electronic signature to the electronically stored document, modify the document content of the initial signed version of the electronically stored document thereby producing a first revision of the electronically stored document; subsequent to modification of the document content of the initial signed version of the electronically stored document, apply a second electronic signature to the first revision of the electronically stored document, wherein the second electronic signature includes information that associates the second electronic signature with the first revision of the electronically stored document, the second electronic signature verifies integrity of the document content of the first revision of the electronically stored document, and the second electronic signature includes a second cryptographic component; and generate a revision history of the electronically stored document, wherein the revision history associates the first electronic signature with the initial signed version of the electronically stored document and associates at least the second electronic signature with the first revision of the first electronically stored document.

8. A computer-implemented system for electronically signing an electronically stored document that includes document content and is accessible by the system, the system comprising: one or more processors; and one or more memory devices for storing program instructions, wherein the program instructions, when executed by the one or more processors, cause the one or more processors to: provide at least a first user and a second user remote access to the electronically stored document; apply a first electronic signature to the electronically stored document to produce an initial signed version of the electronically stored document, wherein the first electronic signature includes information that associates the first electronic signature with the initial signed version of the electronically stored document, the first electronic signature verifies integrity of the document content of the initial signed version of the electronically stored document, and the first electronic signature includes a first cryptographic component; subsequent to application of the first electronic signature to the electronically stored document, modify the document content of the initial signed version of the electronically stored document thereby producing a first revision of the electronically stored document; subsequent to modification of the document content of the initial signed version of the electronically stored document, apply a second electronic signature to the first revision of the electronically stored document, wherein the second electronic signature includes information that associates the second electronic signature with the first revision of the electronically stored document, the second electronic signature verifies integrity of the document content of the first revision of the electronically stored document, and the second electronic signature includes a second cryptographic component; and generate a revision history of the electronically stored document, wherein the revision history associates the first electronic signature with the initial signed version of the electronically stored document and associates at least the second electronic signature with the first revision of the first electronically stored document. 10. The computer-implemented system of claim 8 , wherein the first revision of the electronically stored document includes both the first electronic signature and the second electronic signature.

1. A method comprising: detecting a location of a text selection icon on a display of an electronic device; detecting a touch input representing a selection of text displayed on the display using the text selection icon; determining a movement of the text selection icon while the touch input is maintained during the movement, wherein the movement is continuous and drags the text selection icon into a zone adjacent an edge of the display; in response to the determination, enabling a row by row selection mode; and during the movement of the text selection icon while the touch input is maintained and the row by row selection mode is enabled, dynamically increasing a width of said zone based on at least one of a number of rows of displayed text selected by the continuous movement of the text selection icon or a speed of the movement; wherein: if the detected location of the text selection icon is maintained within said zone during the movement while the touch input is maintained, the displayed text is selected on a row by row basis; and, if the detected location of the text selection icon moves outside said zone and moves into the displayed text during the movement while the touch input is maintained, the row by row selection mode is switched to a letter by letter selection mode, wherein in the letter by letter selection mode the displayed text is selected on a letter by letter basis.

1. A method comprising: detecting a location of a text selection icon on a display of an electronic device; detecting a touch input representing a selection of text displayed on the display using the text selection icon; determining a movement of the text selection icon while the touch input is maintained during the movement, wherein the movement is continuous and drags the text selection icon into a zone adjacent an edge of the display; in response to the determination, enabling a row by row selection mode; and during the movement of the text selection icon while the touch input is maintained and the row by row selection mode is enabled, dynamically increasing a width of said zone based on at least one of a number of rows of displayed text selected by the continuous movement of the text selection icon or a speed of the movement; wherein: if the detected location of the text selection icon is maintained within said zone during the movement while the touch input is maintained, the displayed text is selected on a row by row basis; and, if the detected location of the text selection icon moves outside said zone and moves into the displayed text during the movement while the touch input is maintained, the row by row selection mode is switched to a letter by letter selection mode, wherein in the letter by letter selection mode the displayed text is selected on a letter by letter basis. 9. A method according to claim 1 , wherein the displayed text selected after the text selection icon moves outside said zone is selected on a letter by letter basis while the text selected on the row by row basis remains selected after the text selection icon moves outside said zone.

1. A character input device comprising a display unit having a display screen simultaneously displaying, when characters of hiragana 50-character Japanese language phonetic syllabary or alphanumeric characters are divided into a plurality of groups comprising columns and rows, characters of at least two columns spanning from at least two lines on a character input region provided on said display screen, a first group of two input keys and a second group of two input keys, and a display control unit displaying, in an identifiable manner, at least one selected character among the characters displayed on the character input region, said display control unit sequentially changing at least one character which is to be focused so as to be identifiable by scrolling at least two lines of characters in accordance with an operation of said first group of two input keys, said at least two lines of characters being displayed simultaneously; and changing the character, which is being focused so as to be identifiable, with another character belonging to the same row as that character in accordance with operation of said second group of two input keys.

1. A character input device comprising a display unit having a display screen simultaneously displaying, when characters of hiragana 50-character Japanese language phonetic syllabary or alphanumeric characters are divided into a plurality of groups comprising columns and rows, characters of at least two columns spanning from at least two lines on a character input region provided on said display screen, a first group of two input keys and a second group of two input keys, and a display control unit displaying, in an identifiable manner, at least one selected character among the characters displayed on the character input region, said display control unit sequentially changing at least one character which is to be focused so as to be identifiable by scrolling at least two lines of characters in accordance with an operation of said first group of two input keys, said at least two lines of characters being displayed simultaneously; and changing the character, which is being focused so as to be identifiable, with another character belonging to the same row as that character in accordance with operation of said second group of two input keys. 9. A character input device as set forth in claim 1 , which displays characters displayed in said character input region three-dimensionally by one of a block shape and cylindrical shape.

12. A computer-implemented system for document searching, the system comprising: (a) a computing system that comprises one or more computing devices coupled to a computer network said computing system operable to receive queries; (b) a data store coupled to the computing system operable to store document data in a form suitable for computerized searching; and (c) a software search component running on the computing system that, in response to the computing system receiving a query that includes first and second lists of query terms: (i) logically combines the first and second lists of query terms to form sub-queries, each sub-query comprising at least one term from the first list and at least one term from the second list; (ii) searches the data store by executing the sub-queries such that at least two of the sub-queries are executed in parallel; (iii) obtains results from each sub-query execution, the results including information that identifies the locations of the terms from the first and second lists in the document data stored in the data store; (iv) combines the results from all sub-queries to create a single query result; (v) removes duplicate results from the single query result; and (vi) returns the single query result.

12. A computer-implemented system for document searching, the system comprising: (a) a computing system that comprises one or more computing devices coupled to a computer network said computing system operable to receive queries; (b) a data store coupled to the computing system operable to store document data in a form suitable for computerized searching; and (c) a software search component running on the computing system that, in response to the computing system receiving a query that includes first and second lists of query terms: (i) logically combines the first and second lists of query terms to form sub-queries, each sub-query comprising at least one term from the first list and at least one term from the second list; (ii) searches the data store by executing the sub-queries such that at least two of the sub-queries are executed in parallel; (iii) obtains results from each sub-query execution, the results including information that identifies the locations of the terms from the first and second lists in the document data stored in the data store; (iv) combines the results from all sub-queries to create a single query result; (v) removes duplicate results from the single query result; and (vi) returns the single query result. 16. The system of claim 12 , further including a search engine running on the computing system.

14. An apparatus for processing text data, the apparatus comprising: a text data loading unit configured to load text data including a story; an emotion information reading unit configured to read emotion information corresponding to development of a situation of the story; a speech setting information generating unit configured to generate speech setting information to perform a text-to-speech (TTS) transformation based on the emotion information; and a TTS transforming unit configured to transform the text data to speech based on the speech setting information, wherein the emotion information corresponding to a character profile with respect to a character in the story, a narrator profile with respect to a narrator in the story, emotion change information of a character in the story, tension information of the story, and conversation background information in the story; wherein the character profile includes a character name, a characteristic of the character, a speech style being changed based on a function of a text-to-speech (TTS) system, a relationship with another character, a speed of speech, an intensity of speech, and a pitch of speech, and wherein the narrator profile includes a narrator name, a speech style being changed based on a function of a text-to-speech (TTS) system, a degree of applying a tension of the story, a speed of speech, an intensity of speech, and a pitch of speech.

14. An apparatus for processing text data, the apparatus comprising: a text data loading unit configured to load text data including a story; an emotion information reading unit configured to read emotion information corresponding to development of a situation of the story; a speech setting information generating unit configured to generate speech setting information to perform a text-to-speech (TTS) transformation based on the emotion information; and a TTS transforming unit configured to transform the text data to speech based on the speech setting information, wherein the emotion information corresponding to a character profile with respect to a character in the story, a narrator profile with respect to a narrator in the story, emotion change information of a character in the story, tension information of the story, and conversation background information in the story; wherein the character profile includes a character name, a characteristic of the character, a speech style being changed based on a function of a text-to-speech (TTS) system, a relationship with another character, a speed of speech, an intensity of speech, and a pitch of speech, and wherein the narrator profile includes a narrator name, a speech style being changed based on a function of a text-to-speech (TTS) system, a degree of applying a tension of the story, a speed of speech, an intensity of speech, and a pitch of speech. 18. The apparatus of claim 14 , wherein the speech setting information generating unit generates speech setting information of a current point in time from emotion change information of the character.

13. A system for using user preferences to customize answer output comprising: a computing platform having a processor; a computer readable, tangible storage device; and program instructions stored by the computer readable, tangible storage device, which, when executed by the processor, cause a computing platform to: for a first user and a first question: extract by a natural language processor from the question one or more user preferences and one or more sentiment levels; perform a semantic search on of the first question; receive a plurality of candidate answers from the semantic search; select one or more of the received candidate answers, wherein the selection is performed both according to the one or more sentiment levels and according to the one or more user preferences; and produce a first user output including the selected one or more candidate answers; for a second question and a second user, repeat the step of extracting preferences from the second question; accumulate the preferences and sentiments extracted from the second question with the preferences and sentiments extracted from the first question; and for the second question, repeat the steps of performing a semantic search, receiving candidate answers, selecting candidate answers according to the accumulated preferences and sentiments, and producing a second output.

13. A system for using user preferences to customize answer output comprising: a computing platform having a processor; a computer readable, tangible storage device; and program instructions stored by the computer readable, tangible storage device, which, when executed by the processor, cause a computing platform to: for a first user and a first question: extract by a natural language processor from the question one or more user preferences and one or more sentiment levels; perform a semantic search on of the first question; receive a plurality of candidate answers from the semantic search; select one or more of the received candidate answers, wherein the selection is performed both according to the one or more sentiment levels and according to the one or more user preferences; and produce a first user output including the selected one or more candidate answers; for a second question and a second user, repeat the step of extracting preferences from the second question; accumulate the preferences and sentiments extracted from the second question with the preferences and sentiments extracted from the first question; and for the second question, repeat the steps of performing a semantic search, receiving candidate answers, selecting candidate answers according to the accumulated preferences and sentiments, and producing a second output. 14. The system as set forth in claim 13 further comprising program instructions stored by the computer readable, tangible storage device, which, when executed by a processor, cause a computing platform to: for the first user and a third question, extract by a natural language processor one or more user preferences and one or more sentiment levels, wherein each user preference and each sentiment level is associated with the third question, or associated with the first user, or associated with both the third question and the first user; search semantically on the third question; receive a plurality of candidate answers from the semantic search on the third question; selecting by a computer one or more of the received candidate answers from the search on the third question, wherein the selection is performed according to a combination of the one or more sentiment levels and according to the one or more user preferences associated with the first and second users and with the first, second and third questions; and produce a third user output including the selected one or more candidate answers selected from the search on the third question.

12. The system of claim 10 , wherein determining the respective a convergence status of each of the plurality of processes comprises: determining a difference between two or more training iterations and comparing the difference to a predetermined threshold value; and determining that the process is unlikely to converge if the difference exceeds the threshold value, and otherwise, determining that the process is likely to converge if the difference is less than the threshold value.

12. The system of claim 10 , wherein determining the respective a convergence status of each of the plurality of processes comprises: determining a difference between two or more training iterations and comparing the difference to a predetermined threshold value; and determining that the process is unlikely to converge if the difference exceeds the threshold value, and otherwise, determining that the process is likely to converge if the difference is less than the threshold value. 14. The system of claim 12 , wherein the difference is an absolute numerical value change between two iterations and the predetermined threshold value is expressed as a numerical value.

16. The system of claim 14 , wherein the instructions cause the one or more data processing apparatus to perform operations comprising creating an interaction histogram based on the interaction rankings and the numbers of user interactions with the responsive images.

16. The system of claim 14 , wherein the instructions cause the one or more data processing apparatus to perform operations comprising creating an interaction histogram based on the interaction rankings and the numbers of user interactions with the responsive images. 17. The system of claim 16 , wherein the instructions cause the one or more data processing apparatus to perform operations comprising creating a sub-query histogram based on the sub-query model rankings and the number of user interactions with the responsive images.

6. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, obtaining a plurality of sequences of item identifiers indicating a history of items accessed; randomizing an order of item identifiers included in at least a portion of the plurality of sequences of item identifiers to generate a randomized plurality of sequences of item identifiers; generating a language model using the randomized plurality of sequences of item identifiers as the words of the language modeled by the language model, the language model configured to provide one or more candidate predictions for items of a processing target; receiving a request from an access device of a processing target, the request including information indicative of items for the processing target; generating a candidate prediction for the processing target using the language model and the items for the processing target; and providing a prediction for the processing target using the candidate prediction.

6. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, obtaining a plurality of sequences of item identifiers indicating a history of items accessed; randomizing an order of item identifiers included in at least a portion of the plurality of sequences of item identifiers to generate a randomized plurality of sequences of item identifiers; generating a language model using the randomized plurality of sequences of item identifiers as the words of the language modeled by the language model, the language model configured to provide one or more candidate predictions for items of a processing target; receiving a request from an access device of a processing target, the request including information indicative of items for the processing target; generating a candidate prediction for the processing target using the language model and the items for the processing target; and providing a prediction for the processing target using the candidate prediction. 15. The computer-implemented method of claim 6 , further comprising instructions for generating a randomized list of item identifiers by randomizing the order of item identifiers included in at least a portion of item identifiers for the items for the processing target, wherein generating the candidate prediction for the processing target uses the randomized list of item identifiers for the processing target.

1. A system for providing television advertisements based on a telephone conversation between two or more persons comprising: a speech recognition system for a telephone service configured to monitor a telephone conversation between two or more persons and to recognize key words and phrases spoken by one or more of the persons during the conversation; a database having one or more advertisements indexed by words and phrases; a search engine for querying the database based on key words and phrases recognized during the conversation; a television broadcast for a television service configured to integrate at least one advertisement from the database into the video feed to the television of at least one of the persons based on key words and phrases recognized during the conversation, wherein the television broadcast including the at least one advertisement is received during the telephone conversation.

1. A system for providing television advertisements based on a telephone conversation between two or more persons comprising: a speech recognition system for a telephone service configured to monitor a telephone conversation between two or more persons and to recognize key words and phrases spoken by one or more of the persons during the conversation; a database having one or more advertisements indexed by words and phrases; a search engine for querying the database based on key words and phrases recognized during the conversation; a television broadcast for a television service configured to integrate at least one advertisement from the database into the video feed to the television of at least one of the persons based on key words and phrases recognized during the conversation, wherein the television broadcast including the at least one advertisement is received during the telephone conversation. 4. The system according to claim 1 , wherein the device used for the telephone conversation by at least one of the two or more persons is a VoIP phone, VoIP softphone, POTS phone, cellular phone, wireless device, VoIP-enabled phone, or an Analog Terminal Adaptor (ATA) connected to an analog phone.

16. A system comprising: a policy comprising change implementations based on at least one of a plurality of contexts; an execution system configured to execute a first application in said plurality of contexts; a change monitoring system configured to: determine that a change has been made to said first application; determine at least one context for said change; store said change such that said change may be implemented when said at least one context is a current context.

16. A system comprising: a policy comprising change implementations based on at least one of a plurality of contexts; an execution system configured to execute a first application in said plurality of contexts; a change monitoring system configured to: determine that a change has been made to said first application; determine at least one context for said change; store said change such that said change may be implemented when said at least one context is a current context. 17. The system of claim 16 , said plurality of contexts comprising at least one of a group composed of: a session specific context; a session type specific context; a cross machine context; and a dual application context.

6. The method according to claim 5 , wherein the cross-document structure priority information includes a retrieval count of a structure that is taken of, at every time specified in the query condition, and the processing unit extracts data from the documents to be retrieved which are stored on the second storage unit in a descending order of the retrieval count of the structure, and stores the extracted data onto the first storage unit.

6. The method according to claim 5 , wherein the cross-document structure priority information includes a retrieval count of a structure that is taken of, at every time specified in the query condition, and the processing unit extracts data from the documents to be retrieved which are stored on the second storage unit in a descending order of the retrieval count of the structure, and stores the extracted data onto the first storage unit. 8. The method according to claim 6 , wherein the cross-document structure priority information includes at least one of information regarding registered data structures, which are those to be preferentially stored on the first storage unit, and information regarding excluded data structures which are those not to be stored on the fist storage unit, wherein the information regarding the registered data structures and the information regarding the excluded data structures are both received through the input unit, and the processing unit extracts data from the documents to be retrieved which are stored on the second storage unit, based on one of the information regarding registered data structures and the information regarding excluded data structures, and stores the extracted data onto the first storage unit as the partial documents of the documents to be retrieved.

12. A system comprising: one or more processors; and a non-transitory computer-readable medium including one or more sequences of instructions that, when executed by one or more processors, causes: displaying, via a display interface, text using a first display size; receiving, from an input device, an input requesting an increase in the first display size; responsive to the input, determining that the increase in the display size requested is beyond a maximum display size; and responsive to the determination that the requested display size is beyond the maximum display size, providing an audio output corresponding to the text, wherein the audio output includes an audio rendition of the text displayed in a display region.

12. A system comprising: one or more processors; and a non-transitory computer-readable medium including one or more sequences of instructions that, when executed by one or more processors, causes: displaying, via a display interface, text using a first display size; receiving, from an input device, an input requesting an increase in the first display size; responsive to the input, determining that the increase in the display size requested is beyond a maximum display size; and responsive to the determination that the requested display size is beyond the maximum display size, providing an audio output corresponding to the text, wherein the audio output includes an audio rendition of the text displayed in a display region. 19. The system of claim 12 , further comprising: determining, from the prior instruction, the first display size.

12. A method, for contact information handling, implemented by running a document editing program in a computer, the method comprising: allowing a user to enter textual information into a document using the document editing program; displaying the textual information in the document electronically using the document editing program; allowing, in the document editing program, the user to select in the document at least a portion of the textual information while the textual information is displayed; following user selection of textual information in the document, analyzing, by the document editing program, the selected textual information to determine if the selected textual information is regarded by the document editing program as contact information and what type or types of contact information the selected textual information is; providing an input device configured by the document editing program to allow the user to initiate an operation, such operation being of a type depending at least in part on the type or types of contact information of the selected textual information, the operation comprising identifying at least part of the selected textual information to use as a search term in order to find second information, of a specific type or types, associated with the search term in an information source external to the document; after identifying at least part of the selected information to use as a search term, and in consequence of receipt by the document editing program of an execute command from the input device, performing the operation, wherein the operation further comprises: causing an electronic search in the information source, by an information management program external to the document editing program, for the search term in order to find whether the search term is included in the information source; and performing an action having a type, wherein the type of action depends at least in part on whether the search term is included in the information source, and if the search term is so included, and if the information source includes the second information, the action comprises causing insertion of at least part of the second information into the document.

12. A method, for contact information handling, implemented by running a document editing program in a computer, the method comprising: allowing a user to enter textual information into a document using the document editing program; displaying the textual information in the document electronically using the document editing program; allowing, in the document editing program, the user to select in the document at least a portion of the textual information while the textual information is displayed; following user selection of textual information in the document, analyzing, by the document editing program, the selected textual information to determine if the selected textual information is regarded by the document editing program as contact information and what type or types of contact information the selected textual information is; providing an input device configured by the document editing program to allow the user to initiate an operation, such operation being of a type depending at least in part on the type or types of contact information of the selected textual information, the operation comprising identifying at least part of the selected textual information to use as a search term in order to find second information, of a specific type or types, associated with the search term in an information source external to the document; after identifying at least part of the selected information to use as a search term, and in consequence of receipt by the document editing program of an execute command from the input device, performing the operation, wherein the operation further comprises: causing an electronic search in the information source, by an information management program external to the document editing program, for the search term in order to find whether the search term is included in the information source; and performing an action having a type, wherein the type of action depends at least in part on whether the search term is included in the information source, and if the search term is so included, and if the information source includes the second information, the action comprises causing insertion of at least part of the second information into the document. 16. A method according to claim 12 , wherein the information source is available over a network.

8. A computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising: identifying a web page of interest to form an identified page; loading the identified page a first time to form a first load, wherein the second load is based, at least in part, upon the use of a proxy; responsive to a determination that a delta has not been computed for the identified web page, loading the identified page a second time to form a second load; determining whether portions of the first load differ from portions of the second load; responsive to a determination portions of the first load differ from portions of the second load, identifying the portions that differ to form a delta; storing the delta to form a stored delta; excluding the delta from a document object model associated with the identified page to form a modified document object model; excluding the stored delta from a document object model comparison process, wherein the document object model comparison process from which the stored delta is excluded is a document object model equivalence function, wherein the excluded stored delta includes one or more page sections ignored by crawlers; and if the identified page is part of a rich Internet application, adding the identified page to a rich Internet application model.

8. A computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising: identifying a web page of interest to form an identified page; loading the identified page a first time to form a first load, wherein the second load is based, at least in part, upon the use of a proxy; responsive to a determination that a delta has not been computed for the identified web page, loading the identified page a second time to form a second load; determining whether portions of the first load differ from portions of the second load; responsive to a determination portions of the first load differ from portions of the second load, identifying the portions that differ to form a delta; storing the delta to form a stored delta; excluding the delta from a document object model associated with the identified page to form a modified document object model; excluding the stored delta from a document object model comparison process, wherein the document object model comparison process from which the stored delta is excluded is a document object model equivalence function, wherein the excluded stored delta includes one or more page sections ignored by crawlers; and if the identified page is part of a rich Internet application, adding the identified page to a rich Internet application model. 13. The computer program product of claim 8 wherein the operation of excluding the stored delta from a document object model associated with the identified page to form a modified document object model comprises: tracking parts in a document object model that do not change in time; and using the parts with a document object model comparison process wherein common parts of the document object model functions as a mask to a current document object model.

19. The article of claim 18 , wherein the instructions for generating the translation for the noun phrase and the prepositional phrase comprise instructions operative to cause the machine to generate the translation using the first model; and wherein the instructions for generating the translation of the input string comprise instructions operative to cause the machine to generate the translation using a second model.

19. The article of claim 18 , wherein the instructions for generating the translation for the noun phrase and the prepositional phrase comprise instructions operative to cause the machine to generate the translation using the first model; and wherein the instructions for generating the translation of the input string comprise instructions operative to cause the machine to generate the translation using a second model. 20. The article of claim 19 , wherein the first model comprises a model trained using a corpus consisting of noun phrases and prepositional phrases.

25. A method for updating aspects of an interactive television program guide implemented on a user television equipment, the method comprising: receiving a markup language document at the interactive television program guide implemented on the user television equipment; updating an aspect of the interactive television program guide based on the received markup language document using the interactive television program guide; and generating and displaying a program guide display screen on the user television equipment having aspects of the interactive television program guide as updated based on the markup language document.

25. A method for updating aspects of an interactive television program guide implemented on a user television equipment, the method comprising: receiving a markup language document at the interactive television program guide implemented on the user television equipment; updating an aspect of the interactive television program guide based on the received markup language document using the interactive television program guide; and generating and displaying a program guide display screen on the user television equipment having aspects of the interactive television program guide as updated based on the markup language document. 26. The method of claim 25 wherein the receiving comprises: allowing an operator to remotely supply the markup language document; and the markup language document being received without intervention by the user.

1. A computer system comprising: a test identifier configured to identify runs of test scenarios run by users belonging to different organizations on software systems associated with the different organizations; at least one processor and memory; the at least one processor and the memory cooperating to function as: a route analyzer configured to receive a run of a test scenario; wherein the run is instantiated from a first test scenario template and the first test scenario template defines a first template route that instantiations of the first test scenario template are supposed to follow; the route analyzer is further configured to determine whether the run follows a certain divergent route that diverges from the first template route in at least one of the following ways: the certain divergent route diverges from the first template route and later on converges back to the first template route, the certain divergent route diverges from the first template route and does not converge back to the first tem late route, and the certain divergent route merges with the first template route, a database configured to store the certain divergent route; a route counter configured to receive a second template route belonging to a second test scenario template; wherein the second test scenario template is associated with an organization that does not belong to the different organizations; and wherein each organization of the different organizations has a different composition of shareholders; the route counter is further configured to count number of divergent routes in the database that are essentially the same as the second template route; and a template manipulator configured to determine the number reaches a predetermined threshold (greater than one) and to manipulate the second test scenario template according to the divergent routes in the database that are similar to the second template route.

1. A computer system comprising: a test identifier configured to identify runs of test scenarios run by users belonging to different organizations on software systems associated with the different organizations; at least one processor and memory; the at least one processor and the memory cooperating to function as: a route analyzer configured to receive a run of a test scenario; wherein the run is instantiated from a first test scenario template and the first test scenario template defines a first template route that instantiations of the first test scenario template are supposed to follow; the route analyzer is further configured to determine whether the run follows a certain divergent route that diverges from the first template route in at least one of the following ways: the certain divergent route diverges from the first template route and later on converges back to the first template route, the certain divergent route diverges from the first template route and does not converge back to the first tem late route, and the certain divergent route merges with the first template route, a database configured to store the certain divergent route; a route counter configured to receive a second template route belonging to a second test scenario template; wherein the second test scenario template is associated with an organization that does not belong to the different organizations; and wherein each organization of the different organizations has a different composition of shareholders; the route counter is further configured to count number of divergent routes in the database that are essentially the same as the second template route; and a template manipulator configured to determine the number reaches a predetermined threshold (greater than one) and to manipulate the second test scenario template according to the divergent routes in the database that are similar to the second template route. 13. The computer system of claim 1 , wherein the at least one processor and the memory further cooperate to function as a ranking module configured to rank the manipulated second test scenario template according to the number of the divergent routes.

13. The system of claim 10 , wherein the new API call address is generated by providing the API call name as input to a lookup table.

13. The system of claim 10 , wherein the new API call address is generated by providing the API call name as input to a lookup table. 14. The system of claim 13 , wherein an API call name for the generated new API call is the same as the API call name.

1. A tangible, non-transitory computer-readable medium storing instructions for controlling a computing device to detect morphemes using lattices in an automated task classification system which operates on one or more task objectives of a user, the instructions comprising: recognizing a lattice of phone strings in user input, the lattice representing a distribution over the phone strings; detecting morphemes in the user input using the recognized lattice; and making task-type classification decisions based on the detected morphemes in the user input.

1. A tangible, non-transitory computer-readable medium storing instructions for controlling a computing device to detect morphemes using lattices in an automated task classification system which operates on one or more task objectives of a user, the instructions comprising: recognizing a lattice of phone strings in user input, the lattice representing a distribution over the phone strings; detecting morphemes in the user input using the recognized lattice; and making task-type classification decisions based on the detected morphemes in the user input. 8. The tangible, non-transitory computer-readable medium of claim 1 , wherein the instructions further comprise prompting the user to provide a feedback response including additional information with respect to an initial user input.

10. A system for providing characters and character groups from a roundel image comprising: a region analyzer for vertically-aligning electronically represented text in said roundel image; determining a point at which said roundel image starts; segmenting the vertically-aligned text into characters and character groups; and dividing said roundel image into sections according to said point; a pattern locater marking each of said character groups as flipped if said character group meets pre-determined criteria; and marking said character groups in one of said sections as unflipped if none of said character groups in said one section is flipped, or if said one section includes predetermined text that is unflipped; and an image analyzer creating an image by rearranging the underlying representation of said character groups if there are said character groups that are marked as flipped; and segmenting said image into new characters; and a provider for providing the new characters to an electronic sink according to the segmented image.

10. A system for providing characters and character groups from a roundel image comprising: a region analyzer for vertically-aligning electronically represented text in said roundel image; determining a point at which said roundel image starts; segmenting the vertically-aligned text into characters and character groups; and dividing said roundel image into sections according to said point; a pattern locater marking each of said character groups as flipped if said character group meets pre-determined criteria; and marking said character groups in one of said sections as unflipped if none of said character groups in said one section is flipped, or if said one section includes predetermined text that is unflipped; and an image analyzer creating an image by rearranging the underlying representation of said character groups if there are said character groups that are marked as flipped; and segmenting said image into new characters; and a provider for providing the new characters to an electronic sink according to the segmented image. 11. The system as in claim 10 further comprising: a character processor for determining unflipped characters and unflipped character confidences for each character in the vertically-aligned electronically represented text; flipping the characters; determining flipped characters and flipped character confidences for the flipped characters; selecting a set of character confidences from the unflipped confidences and the flipped confidences according to predetermined criteria; summing the set of character confidences for each of the characters to compile a set of unflipped character group confidences; and summing the set of flipped character confidences for each of the flipped characters to compile a set of flipped character group confidences.

2. The method according to claim 1 , the method further comprising the step of: specifying in advance, at least one of said plurality of model elements corresponding to a root block table, wherein said root block table is a center table of said multi-dimensional data model structure.

2. The method according to claim 1 , the method further comprising the step of: specifying in advance, at least one of said plurality of model elements corresponding to a root block table, wherein said root block table is a center table of said multi-dimensional data model structure. 3. The method according to claim 2 , wherein said step of generating a hierarchical multi-dimensional data model further comprises the step of: generating said hierarchical multi-dimensional data model from said plurality of model elements, wherein said plurality of model elements are extracted by said extraction queries that apply a first block table associated with said specified root block table and a second block table associated with said first block table.

1. In a computer system including a display screen comprising a result display area of a graphical user interface, a computer-implemented method of receiving user input for changing the amount of data displayed in the result display area of the graphical user interface, the method comprising: retrieving data from a data source, the data comprising a plurality of text elements; displaying, in the result display area, a plurality of text display blocks each comprising at least a portion of the text of each of the plurality of text elements, each text display block having a size individually determined based on the amount of data to be displayed in the block; displaying in a control area of the graphical user interface distinguished from the result display area, a single control for adjusting the sizes of the displayed plurality of text display blocks; and in response to user input moving the control in the control area: adjusting the size of each of the displayed plurality of text display blocks, wherein at least two of the text display blocks have different amounts of data and are displayed having different sizes, and wherein the adjusting is dynamic, visible and concurrent with moving the control.

1. In a computer system including a display screen comprising a result display area of a graphical user interface, a computer-implemented method of receiving user input for changing the amount of data displayed in the result display area of the graphical user interface, the method comprising: retrieving data from a data source, the data comprising a plurality of text elements; displaying, in the result display area, a plurality of text display blocks each comprising at least a portion of the text of each of the plurality of text elements, each text display block having a size individually determined based on the amount of data to be displayed in the block; displaying in a control area of the graphical user interface distinguished from the result display area, a single control for adjusting the sizes of the displayed plurality of text display blocks; and in response to user input moving the control in the control area: adjusting the size of each of the displayed plurality of text display blocks, wherein at least two of the text display blocks have different amounts of data and are displayed having different sizes, and wherein the adjusting is dynamic, visible and concurrent with moving the control. 11. The method of claim 1 , further comprising: storing the sizes of each of the displayed plurality of text display blocks comprising the portions of the text displayed by user.

1. A computer-assisted method for automatically discovering topics in a document collection comprising one or more documents that comprise sentences and terms, comprising: automatically dividing each of the sentences into the grammatical components of a subject and a predicate by a computer system, wherein the predicate is defined as the portion of a sentence other than the subject; assigning a first weighting coefficient to subjects in the sentences; assigning a second weighting coefficient to predicates in the sentences; tokenizing the sentences to produce a plurality of tokens, wherein each of the terms is associated with one or more of the plurality of tokens; for each one of the terms, calculating a first token count in the plurality of tokens in which the one of the terms matches a subject in the sentences; multiplying the first weighting coefficient with the first token count to produce a first weighted token count; calculating a second token count in the plurality of tokens in which the one of the terms matches a predicate in the sentences; multiplying the second weighting coefficient with the second token count to produce a second weighted token count; producing a first score value for the one of the terms based on the first weighted token count and the second weighted token count, wherein the first score can be referred to as an internal term prominence (ITP) value in comparison to a second value, wherein the second value can be referred to as an external term prominence (ETP) value, wherein the ETP value represents the prominence of the term outside the document collection; selecting one or more terms from the terms at least in part based on the first score values of the terms; and outputting the one or more terms representing one or more topics associated with the document collection.

1. A computer-assisted method for automatically discovering topics in a document collection comprising one or more documents that comprise sentences and terms, comprising: automatically dividing each of the sentences into the grammatical components of a subject and a predicate by a computer system, wherein the predicate is defined as the portion of a sentence other than the subject; assigning a first weighting coefficient to subjects in the sentences; assigning a second weighting coefficient to predicates in the sentences; tokenizing the sentences to produce a plurality of tokens, wherein each of the terms is associated with one or more of the plurality of tokens; for each one of the terms, calculating a first token count in the plurality of tokens in which the one of the terms matches a subject in the sentences; multiplying the first weighting coefficient with the first token count to produce a first weighted token count; calculating a second token count in the plurality of tokens in which the one of the terms matches a predicate in the sentences; multiplying the second weighting coefficient with the second token count to produce a second weighted token count; producing a first score value for the one of the terms based on the first weighted token count and the second weighted token count, wherein the first score can be referred to as an internal term prominence (ITP) value in comparison to a second value, wherein the second value can be referred to as an external term prominence (ETP) value, wherein the ETP value represents the prominence of the term outside the document collection; selecting one or more terms from the terms at least in part based on the first score values of the terms; and outputting the one or more terms representing one or more topics associated with the document collection. 3. The computer-assisted method of claim 1 , further comprising: obtaining a data set comprising a plurality of ETP values each associated with one of the terms, and producing a third score value for each of the terms using its associated ITP and ETP value, wherein the third score value can be referred to as the collection-specific term prominence (CSTP) value, wherein the one or more terms are selected from the terms using the CSTP values of the respective terms as representing one or more topics associated with the document collection.

11. A computer program product for annotating an unindexed document for shared use, the computer program product comprising: a non-transitory computer-readable storage medium; and computer program code, stored on the non-transitory computer-readable storage medium, when executed by one or more processors, for: receiving, by a computing device from a portable capture device, a first digital image depicting at least a first portion of the unindexed document, wherein the unindexed document is unknown to an index of stored documents; receiving, by the computing device, an annotation associated with the unindexed document from a first user of the portable capture device; extracting, by the computing device, features from the first digital image; storing, by the computing device, the first digital image, the extracted features, and the annotation as an annotated digital image; recognizing, by the computing device, a second user from the features of the first digital image, wherein the first digital image depicts at least the first portion of the unindexed document and the unindexed document is associated with the annotation from the first user; responsive to recognizing the second user from the features of the first digital image depicting at least the first portion of the unindexed document, creating a new tie between the first user and the second user in a network of users who have captured documents with similar features; and responsive to creating the new tie, making the annotated digital image available to the second user and sharing an identity of the second user with the first user; determining a first group of users, including the first user, who have operated on the unindexed document from users who have ties with the second user in the network; determining a second group of users who have not operated on the unindexed document from the users who have ties with the second user in the network; and weakening, by the computing device, the ties between the second user and the second group of users of the network based on the first group being larger than the second group.

11. A computer program product for annotating an unindexed document for shared use, the computer program product comprising: a non-transitory computer-readable storage medium; and computer program code, stored on the non-transitory computer-readable storage medium, when executed by one or more processors, for: receiving, by a computing device from a portable capture device, a first digital image depicting at least a first portion of the unindexed document, wherein the unindexed document is unknown to an index of stored documents; receiving, by the computing device, an annotation associated with the unindexed document from a first user of the portable capture device; extracting, by the computing device, features from the first digital image; storing, by the computing device, the first digital image, the extracted features, and the annotation as an annotated digital image; recognizing, by the computing device, a second user from the features of the first digital image, wherein the first digital image depicts at least the first portion of the unindexed document and the unindexed document is associated with the annotation from the first user; responsive to recognizing the second user from the features of the first digital image depicting at least the first portion of the unindexed document, creating a new tie between the first user and the second user in a network of users who have captured documents with similar features; and responsive to creating the new tie, making the annotated digital image available to the second user and sharing an identity of the second user with the first user; determining a first group of users, including the first user, who have operated on the unindexed document from users who have ties with the second user in the network; determining a second group of users who have not operated on the unindexed document from the users who have ties with the second user in the network; and weakening, by the computing device, the ties between the second user and the second group of users of the network based on the first group being larger than the second group. 13. The computer program product of claim 11 , wherein the annotation is text.

1. A system that ranks search results, comprising a processor executing the following components: a ranking component that determines relevance of respective search results generated from a search associated with one or more of a Usenet, a discussion thread, a blog, an archived community discussion, or a chat room via multiple feature-based relevance functions, wherein features of the relevance functions are based at least on one or more global thread properties comprising at least a thread depth defined over a thread comprising one or more messages that include at least a message core and a message body, one or more posting-specific thread properties and attributes of a person posting the messages, and wherein the attributes comprise at least a number of posting per time duration, a number of newsgroups posted to and a number of postings that have no responses; a function generator component that generates the relevance functions such that ordered search results are ordered based on their respective relevancies; wherein the search is selectively scoped based at least on a structure of the thread comprising the one or more messages, wherein further at least one of the features is based on inferred labels on edges between an existing message in the thread and one or more of a parent or child of the message, and wherein the labels determine a nature of a respective message in the thread and are automatically inferred from content of the one or more messages within the thread; a thresholding component that defines a threshold for an acceptable relevance level for at least one of the multiple relevance functions to mitigate providing non-relevant search results to a user, wherein the threshold is dynamically adjustable to adapt to the user's response to returned results by raising the threshold when the user rejects at least part of the returned results with a relevance above the threshold; and wherein the threshold limits the returned results based on system level constraints.

1. A system that ranks search results, comprising a processor executing the following components: a ranking component that determines relevance of respective search results generated from a search associated with one or more of a Usenet, a discussion thread, a blog, an archived community discussion, or a chat room via multiple feature-based relevance functions, wherein features of the relevance functions are based at least on one or more global thread properties comprising at least a thread depth defined over a thread comprising one or more messages that include at least a message core and a message body, one or more posting-specific thread properties and attributes of a person posting the messages, and wherein the attributes comprise at least a number of posting per time duration, a number of newsgroups posted to and a number of postings that have no responses; a function generator component that generates the relevance functions such that ordered search results are ordered based on their respective relevancies; wherein the search is selectively scoped based at least on a structure of the thread comprising the one or more messages, wherein further at least one of the features is based on inferred labels on edges between an existing message in the thread and one or more of a parent or child of the message, and wherein the labels determine a nature of a respective message in the thread and are automatically inferred from content of the one or more messages within the thread; a thresholding component that defines a threshold for an acceptable relevance level for at least one of the multiple relevance functions to mitigate providing non-relevant search results to a user, wherein the threshold is dynamically adjustable to adapt to the user's response to returned results by raising the threshold when the user rejects at least part of the returned results with a relevance above the threshold; and wherein the threshold limits the returned results based on system level constraints. 4. The system of claim 1 , wherein the search results are further associated with searches over data associated with one or more of, a mailing list, a wiky, a web page, a database or a list.

1. One or more computer-readable storage devices that store executable instructions to provide search results, the executable instructions, when executed by a computer, causing the computer to perform acts comprising: receiving a query from a user; determining that the query is one to be asked to a person in addition to, or instead of, a search engine; comparing said query to a corpus of information to obtain objective results; comparing said query to a social graph to identify one or more people whose relationship to said user meets a closeness condition and who have an aspect of relevance to said query; creating person results that comprise said one or more people and, for each of said one or more people, an explanation of each person's relevance to said query, said social graph indicating attributes for people in said social graph, said explanation of a given person's relevance comprising an attribute that is indicated in said social graph for said given person, said attribute matching a term in said query; and providing, to said user, a set of results that comprise said objective results and said person results.

1. One or more computer-readable storage devices that store executable instructions to provide search results, the executable instructions, when executed by a computer, causing the computer to perform acts comprising: receiving a query from a user; determining that the query is one to be asked to a person in addition to, or instead of, a search engine; comparing said query to a corpus of information to obtain objective results; comparing said query to a social graph to identify one or more people whose relationship to said user meets a closeness condition and who have an aspect of relevance to said query; creating person results that comprise said one or more people and, for each of said one or more people, an explanation of each person's relevance to said query, said social graph indicating attributes for people in said social graph, said explanation of a given person's relevance comprising an attribute that is indicated in said social graph for said given person, said attribute matching a term in said query; and providing, to said user, a set of results that comprise said objective results and said person results. 5. The one or more computer-readable storage devices of claim 1 , said aspect of relevance being based on a comparison of words in said query with a characteristic that is derived from likes or text posts of a person in said social graph, said query being found to match said person based on words in said query matching said characteristic.

14. One or more computer-readable storage media having computer-executable instructions embodied thereon that, when executed, perform a method of presenting prediction candidates based on a recognized handwriting input, the method comprising: receiving a handwriting input from a handwriting input device coupled to a computing device having a processor and a memory; executing, by the computing device, a recognition engine to identify a recognition candidate based on the handwriting input; determining a prediction candidate associated with the recognition candidate; and presenting the recognition candidate and the prediction candidate, the recognition candidate being presented singularly and as a combination candidate that includes the recognition candidate followed by the prediction candidate.

14. One or more computer-readable storage media having computer-executable instructions embodied thereon that, when executed, perform a method of presenting prediction candidates based on a recognized handwriting input, the method comprising: receiving a handwriting input from a handwriting input device coupled to a computing device having a processor and a memory; executing, by the computing device, a recognition engine to identify a recognition candidate based on the handwriting input; determining a prediction candidate associated with the recognition candidate; and presenting the recognition candidate and the prediction candidate, the recognition candidate being presented singularly and as a combination candidate that includes the recognition candidate followed by the prediction candidate. 20. The computer-readable storage media of claim 14 , wherein the prediction candidate includes more than one words, phrases, or symbols.

11. A method as claim 9 recites, wherein the candidate segment masks overlap the ground-truth bounding box at least in part as a degree of overlap.

11. A method as claim 9 recites, wherein the candidate segment masks overlap the ground-truth bounding box at least in part as a degree of overlap. 12. A method as claim 11 recites, wherein the ranked candidate segment masks are ranked based at least in part on the degree of overlap with the ground-truth bounding box.

1. A computer-implemented, knowledge reasoning process for understanding, in natural language format, at least a portion of the contents of a document, comprising using a computer processor to perform the steps of: (a) receiving a document in electronic form, the document stored on a computer readable medium; (b) determining and extracting facts and goals, which consist of definitions, information, and data in natural language format, the facts and goals representative of local characteristics and context of the document; (c) providing the facts and goals to a computer-implemented reasoning management unit; (d) receiving formatted knowledge corresponding to human document understanding in natural language format from a computer-implemented rule verification, validation and management unit; (e) using the formatted knowledge to prepare a computer-implemented expert system having an inference engine; (f) reasoning the facts and goals against formatted knowledge using the inference engine of the computer-implemented expert system and determining a set of applicable rules regarding understanding of the content and context of the at least a portion of the document; (g) providing the computer-implemented reasoning management unit with the applicable rules and information concerning the understanding of at least a portion of the document; (h) sending a summary of abstract meaning concerning content understanding to a results and reports processing unit; and (i) performing at least one function on the document in electronic form selected from document classification, document sorting, information redaction, information capturing and data extraction wherein the rule verification, validation and management unit performs the following steps: (1) determining whether conflicting rules exist; (2) determining whether conflicting facts exist; and (3) determining whether cyclic data locks, recursive loops and indefinite execution of rules are present.

1. A computer-implemented, knowledge reasoning process for understanding, in natural language format, at least a portion of the contents of a document, comprising using a computer processor to perform the steps of: (a) receiving a document in electronic form, the document stored on a computer readable medium; (b) determining and extracting facts and goals, which consist of definitions, information, and data in natural language format, the facts and goals representative of local characteristics and context of the document; (c) providing the facts and goals to a computer-implemented reasoning management unit; (d) receiving formatted knowledge corresponding to human document understanding in natural language format from a computer-implemented rule verification, validation and management unit; (e) using the formatted knowledge to prepare a computer-implemented expert system having an inference engine; (f) reasoning the facts and goals against formatted knowledge using the inference engine of the computer-implemented expert system and determining a set of applicable rules regarding understanding of the content and context of the at least a portion of the document; (g) providing the computer-implemented reasoning management unit with the applicable rules and information concerning the understanding of at least a portion of the document; (h) sending a summary of abstract meaning concerning content understanding to a results and reports processing unit; and (i) performing at least one function on the document in electronic form selected from document classification, document sorting, information redaction, information capturing and data extraction wherein the rule verification, validation and management unit performs the following steps: (1) determining whether conflicting rules exist; (2) determining whether conflicting facts exist; and (3) determining whether cyclic data locks, recursive loops and indefinite execution of rules are present. 2. The process of claim 1 , wherein the facts and goals are generated using a facts generator using at least one tool selected from the group consisting of a pattern generator, an optical character recognition program, natural handwriting recognition program and an intelligent character recognition program.

2. The method of claim 1 , further comprising selecting a location at the center of the map as the geographic location.

2. The method of claim 1 , further comprising selecting a location at the center of the map as the geographic location. 3. The method of claim 2 , further comprising selecting the geographic location based on a zoom level of the map.

2. The method of claim 1 , further comprising: performing an action on behalf of the user with respect to at least one entity of the one or more entities identified as being described by the profile parameter.

2. The method of claim 1 , further comprising: performing an action on behalf of the user with respect to at least one entity of the one or more entities identified as being described by the profile parameter. 3. The method of claim 2 , wherein the action includes at least one of: submitting a public contribution to a webpage of the at least one entity, sending a private message to the at least one entity via a social network service of the one or more social network services, indicating that the user endorses an interaction published by the at least one entity, submitting a comment on the interaction published by the at least one entity, submitting a descriptor for the interaction published by the at least one entity, requesting removal of the descriptor for the interaction published by the at least one entity, accessing a public portion of a profile of the at least one entity, accessing a restricted portion of the profile of the at least one entity, accessing a private portion of the profile of the at least one entity, and accessing a further profile for a further entity that is referenced by the profile of the at least one entity.

13. For use with a system allowing a user to select a particular menu option from a plurality of menu options, the particular menu option associated with a particular region, the system including: (1) a display area; and (2) a computer coupled to the display area for receiving a movement related signal responsive to user movement of the user, the user movement capable of indicating a potential user selection, the user movement capable of indicating: (i) a first starting location intersecting the particular region; (ii) at a time at or after the time the first starting location occurs, a second starting location intersecting the particular region; (iii) at a time after the time the second starting location occurs, a second intermediate location intersecting the particular region at a time after the time the second intermediate location occurs, a second ending location intersecting the particular region; and (iv) at a time after the time the second ending location occurs, a first ending location intersecting the particular region; wherein a first period of intersection starts in response to the first starting location intersecting the particular region and ends in response to the first ending location intersecting the particular region; wherein a second period of intersection starts in response to the second starting location intersecting the particular region and ends in response to the second ending location intersecting the particular region; and wherein the duration of the second period of intersection increases between the time the second intermediate location occurs and the time the second ending location occurs an apparatus for indicating dwell time comprising: (a) a carrier readable by the computer; and (b) a first program, stored on or transmitted via the carrier and executable by the computer, for: (1) at least partially delimiting the particular region with respect to the display area; (2) selecting the particular menu option responsive to a first quantity equalling or exceeding a first predetermined quantity, the first quantity being a function of the duration of the first period of intersection; and (3) providing a continuous or apparently continuous indication to the user prior to the first program selecting the particular menu option, the indication responsive to a second quantity, the second quantity being a function of the increasing duration of the second period of intersection.

13. For use with a system allowing a user to select a particular menu option from a plurality of menu options, the particular menu option associated with a particular region, the system including: (1) a display area; and (2) a computer coupled to the display area for receiving a movement related signal responsive to user movement of the user, the user movement capable of indicating a potential user selection, the user movement capable of indicating: (i) a first starting location intersecting the particular region; (ii) at a time at or after the time the first starting location occurs, a second starting location intersecting the particular region; (iii) at a time after the time the second starting location occurs, a second intermediate location intersecting the particular region at a time after the time the second intermediate location occurs, a second ending location intersecting the particular region; and (iv) at a time after the time the second ending location occurs, a first ending location intersecting the particular region; wherein a first period of intersection starts in response to the first starting location intersecting the particular region and ends in response to the first ending location intersecting the particular region; wherein a second period of intersection starts in response to the second starting location intersecting the particular region and ends in response to the second ending location intersecting the particular region; and wherein the duration of the second period of intersection increases between the time the second intermediate location occurs and the time the second ending location occurs an apparatus for indicating dwell time comprising: (a) a carrier readable by the computer; and (b) a first program, stored on or transmitted via the carrier and executable by the computer, for: (1) at least partially delimiting the particular region with respect to the display area; (2) selecting the particular menu option responsive to a first quantity equalling or exceeding a first predetermined quantity, the first quantity being a function of the duration of the first period of intersection; and (3) providing a continuous or apparently continuous indication to the user prior to the first program selecting the particular menu option, the indication responsive to a second quantity, the second quantity being a function of the increasing duration of the second period of intersection. 19. The apparatus of claim 13 wherein the continuous or apparently continuous indication includes any one of: (1) a visible signal, including any one of: (a) a size; (b) a shape; (c) a hue; (d) a brightness; (e) a contrast; (f) a tone; (g) a dithering; (f) a fill; (h) a font; (i) a blinking; (j) a hatching; and (k) a pattern; (2) an audible signal; and (3) a tactile signal.

1. A method in a networked computer system for searching for encrypted documents, the method comprising: for each of a plurality of values of an attribute of documents, the values having an ordering, determining a number of different encrypted instances of the value to generate, wherein the number of different encrypted instances determined for at least one of the plurality of values is greater than one, generating the determined number of different encrypted instances of the value so that the value serves as a basis for generating each of the determined number of different encrypted instances of the value, wherein more than one encrypted instance of the at least one of the plurality of values is generated, and storing the generated encrypted instances of the value, wherein each encrypted instance of the value can be decrypted into the value; generating a mapping of the values of the attribute to each document having that value for the attribute, wherein the mapping maps different encrypted instances of a value to different documents; providing the generated mapping to a document storage service; and identifying an encrypted document that matches a query that specified a value for the attribute by, determining a lower bound on encrypted instances associated with the value specified by the query, determining an upper bound on encrypted instances associated with the value specified by the query, sending the determined lower and upper bounds to a document storage service, and receiving from the document storage service an indication of at least one document associated with an encrypted instance between the lower and upper bounds.

1. A method in a networked computer system for searching for encrypted documents, the method comprising: for each of a plurality of values of an attribute of documents, the values having an ordering, determining a number of different encrypted instances of the value to generate, wherein the number of different encrypted instances determined for at least one of the plurality of values is greater than one, generating the determined number of different encrypted instances of the value so that the value serves as a basis for generating each of the determined number of different encrypted instances of the value, wherein more than one encrypted instance of the at least one of the plurality of values is generated, and storing the generated encrypted instances of the value, wherein each encrypted instance of the value can be decrypted into the value; generating a mapping of the values of the attribute to each document having that value for the attribute, wherein the mapping maps different encrypted instances of a value to different documents; providing the generated mapping to a document storage service; and identifying an encrypted document that matches a query that specified a value for the attribute by, determining a lower bound on encrypted instances associated with the value specified by the query, determining an upper bound on encrypted instances associated with the value specified by the query, sending the determined lower and upper bounds to a document storage service, and receiving from the document storage service an indication of at least one document associated with an encrypted instance between the lower and upper bounds. 4. The method of claim 1 wherein the encrypted instances are stored in a first table and wherein a second table stores, for each value in a sequence, the index from the first table of the smallest encrypted instance of that value.

11. A method, implemented by a computing device, comprising: providing a chunking specification; providing one or more part-of-speech-tagged corpora; chunking the one or more corpora, with a processor, in accordance with the chunking specification, the chunking comprising: chunking nouns, noun-verbs, pronouns, noun-adjectives, noun morphemes, and named entities, either single or as the head in a modifier-head structure with a modifier comprising a noun, a numerical phrase, or an adjective phrase, as noun chunks; chunking verbs, verb-particle structures in which the particle comprises an oriented verb or an auxiliary, and modifier-verb structures in which the modifier comprises an adverbial phrase or an auxiliary verb, in verb chunks; refining the chunking specification through iterative chunking consistency feedback with a training corpus, wherein one or more groups of identical or similar sections of text from different parts of the training corpus that have been chunked differently from each other are compared, and for one or more of the groups, the chunking of one of the identical or similar sections of text is selected to replace the chunking of the other identical or similar sections of text within the group; automatically calculating, with a processor, a consistency ratio for the chunking of the training corpus; comparing the calculated consistency ratio with a chunk consistency threshold, wherein refining the chunking specification is continued at least until the calculated consistency ratio meets the chunk consistency threshold; incorporating the refined chunking specification in a chunking utility that also comprises a plurality of definitions of chunk types and a set of chunking rules; receiving an input; assigning chunk types to portions of the input based at least in part on the chunking utility comprising the refined chunking specification; and providing an output comprising the portions of the input with the assigned chunk types.

11. A method, implemented by a computing device, comprising: providing a chunking specification; providing one or more part-of-speech-tagged corpora; chunking the one or more corpora, with a processor, in accordance with the chunking specification, the chunking comprising: chunking nouns, noun-verbs, pronouns, noun-adjectives, noun morphemes, and named entities, either single or as the head in a modifier-head structure with a modifier comprising a noun, a numerical phrase, or an adjective phrase, as noun chunks; chunking verbs, verb-particle structures in which the particle comprises an oriented verb or an auxiliary, and modifier-verb structures in which the modifier comprises an adverbial phrase or an auxiliary verb, in verb chunks; refining the chunking specification through iterative chunking consistency feedback with a training corpus, wherein one or more groups of identical or similar sections of text from different parts of the training corpus that have been chunked differently from each other are compared, and for one or more of the groups, the chunking of one of the identical or similar sections of text is selected to replace the chunking of the other identical or similar sections of text within the group; automatically calculating, with a processor, a consistency ratio for the chunking of the training corpus; comparing the calculated consistency ratio with a chunk consistency threshold, wherein refining the chunking specification is continued at least until the calculated consistency ratio meets the chunk consistency threshold; incorporating the refined chunking specification in a chunking utility that also comprises a plurality of definitions of chunk types and a set of chunking rules; receiving an input; assigning chunk types to portions of the input based at least in part on the chunking utility comprising the refined chunking specification; and providing an output comprising the portions of the input with the assigned chunk types. 13. The method of claim 11 , wherein the input is received in a format other than text, and the method further comprises converting the input into a text format, prior to the assigning the chunk types to the portions of the input.

1. A method for searching key words, comprising: obtaining, by a terminal device, a key word typed in a search box; sending, by the terminal device, a search request based on the obtained key word; obtaining, by the terminal device, a first set of directly associated words of the key word from a keyword database based on a matching between the search request and the keyword database, and obtaining a summary extracted from search results queried using the first set of directly associated words; obtaining, by the terminal device, a second set of indirectly associated words of the key word; displaying, by the terminal device as a list, the first set of directly associated words and the second set of indirectly associated words along with but below the first set of directly associated words in the search box; upon displaying the list, triggering a time measurement by the terminal device to acquire a user dwell time on the displayed first set of associated words; monitoring and determining that the user dwell time on the displayed directly associated words has reached a predetermined threshold user dwell time; and displaying, by the terminal device upon determining that the user dwell time has reached the predetermined threshold user dwell time, the summary extracted from the search results along with the displayed first set of associated words.

1. A method for searching key words, comprising: obtaining, by a terminal device, a key word typed in a search box; sending, by the terminal device, a search request based on the obtained key word; obtaining, by the terminal device, a first set of directly associated words of the key word from a keyword database based on a matching between the search request and the keyword database, and obtaining a summary extracted from search results queried using the first set of directly associated words; obtaining, by the terminal device, a second set of indirectly associated words of the key word; displaying, by the terminal device as a list, the first set of directly associated words and the second set of indirectly associated words along with but below the first set of directly associated words in the search box; upon displaying the list, triggering a time measurement by the terminal device to acquire a user dwell time on the displayed first set of associated words; monitoring and determining that the user dwell time on the displayed directly associated words has reached a predetermined threshold user dwell time; and displaying, by the terminal device upon determining that the user dwell time has reached the predetermined threshold user dwell time, the summary extracted from the search results along with the displayed first set of associated words. 3. The method of claim 1 , wherein the second set of indirectly associated words of the key word comprise words from the keyword database that are associated with but not direct match of the key word.

6. Apparatus according to claim 5, wherein the information generated by the memory means is input to a code converter to generate a code word.

6. Apparatus according to claim 5, wherein the information generated by the memory means is input to a code converter to generate a code word. 7. Apparatus according to claim 6, wherein a series of groups of latches are connected to outputs of the meory device to generate the code words.

1. A method for providing an XML integration grammar (XG) for mapping multiple XML sources into a single XML target, the method comprising: for each production based on a Document Type Definition (DTD) of the target, the production being associated with a parent type, automatically defining a set of rules, the defining comprising: for each child type of the production, defining a first rule for computing an inherited attribute for the child type by extracting data, via a query, from one or more DTDs corresponding to the multiple XML sources, the query being adapted to take an inherited attribute defined for the parent type as a query parameter; and for the parent type, defining a second rule for computing a synthesized attribute for the parent type by grouping synthesized attributes for all child types of the production; and storing the XIG, wherein the XIG comprises defined sets of rules.

1. A method for providing an XML integration grammar (XG) for mapping multiple XML sources into a single XML target, the method comprising: for each production based on a Document Type Definition (DTD) of the target, the production being associated with a parent type, automatically defining a set of rules, the defining comprising: for each child type of the production, defining a first rule for computing an inherited attribute for the child type by extracting data, via a query, from one or more DTDs corresponding to the multiple XML sources, the query being adapted to take an inherited attribute defined for the parent type as a query parameter; and for the parent type, defining a second rule for computing a synthesized attribute for the parent type by grouping synthesized attributes for all child types of the production; and storing the XIG, wherein the XIG comprises defined sets of rules. 4. The method of claim 1 wherein, when the production is p=A→B 1 , . . . , B n , the first rule is defined as Inh ( B i )= Q i ( Inh ( A )), for each iε[ 1 ,n] and the second rule is defined as Syn ( A )=< A>{Syn ( B 1 ) . . . Syn ( B n )}</ A> where: Inh (A) is the inherited attribute for the parent type A, Syn (A) is the synthesized attribute for the parent type A, Inh (B) is the inherited attribute for the child type B, Syn (B) is the synthesized attribute for the child type B, and for each iε[1, n], Q i is an XQ e query that returns a single element (subtree).

32. The system according to claim 29 including means for using Real-time Transport Protocol (RTP) or Secure RTP (SRTP) for the real-time IP media transport session.

32. The system according to claim 29 including means for using Real-time Transport Protocol (RTP) or Secure RTP (SRTP) for the real-time IP media transport session. 33. The system according to claim 32 including means for identifying the text packets by using a RTP or SRTP payload type identifier in an RTP or SRTP packet header.

5. An apparatus for configuring a speech engine for a multimodal application based on location, the multimodal application operating on a multimodal device supporting multiple modes of user interaction with the multimodal application, the modes of user interaction including a voice mode and one or more non-voice modes, the multimodal application operatively coupled to a speech engine, the apparatus comprising a computer processor and a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions that, when executed by the computer processor, perform a method of: receiving a location change notification in a location change monitor from a device location manager, the device location manager operatively coupled to a position detection component of the multimodal device, the location change notification specifying a current location of the multimodal device; identifying in a configuration parameter repository, location-based configuration parameters for the speech engine in dependence upon the current location of the multimodal device, the location-based configuration parameters specifying a configuration for the speech engine at the current location, wherein the location-based configuration include an identifier for an acoustic model from among a plurality of acoustic models including a first acoustic model and a second acoustic model, an identifier for a lexicon from among a plurality of lexicons including a first lexicon and a second lexicon, speech transition times, silence detection times, speech timeouts, gain maps, and a configuration for use by a text-to-speech (‘TTS’) engine including a voice used in synthesizing speech from text, wherein each of the first acoustic model and the second acoustic model associates acoustic features with phonemes, wherein the first lexicon and the second lexicon specify a different phoneme representation for a same word; and updating, by the location change monitor, a current configuration for the speech engine according to the identified location-based configuration parameters.

5. An apparatus for configuring a speech engine for a multimodal application based on location, the multimodal application operating on a multimodal device supporting multiple modes of user interaction with the multimodal application, the modes of user interaction including a voice mode and one or more non-voice modes, the multimodal application operatively coupled to a speech engine, the apparatus comprising a computer processor and a computer memory operatively coupled to the computer processor, the computer memory having disposed within it computer program instructions that, when executed by the computer processor, perform a method of: receiving a location change notification in a location change monitor from a device location manager, the device location manager operatively coupled to a position detection component of the multimodal device, the location change notification specifying a current location of the multimodal device; identifying in a configuration parameter repository, location-based configuration parameters for the speech engine in dependence upon the current location of the multimodal device, the location-based configuration parameters specifying a configuration for the speech engine at the current location, wherein the location-based configuration include an identifier for an acoustic model from among a plurality of acoustic models including a first acoustic model and a second acoustic model, an identifier for a lexicon from among a plurality of lexicons including a first lexicon and a second lexicon, speech transition times, silence detection times, speech timeouts, gain maps, and a configuration for use by a text-to-speech (‘TTS’) engine including a voice used in synthesizing speech from text, wherein each of the first acoustic model and the second acoustic model associates acoustic features with phonemes, wherein the first lexicon and the second lexicon specify a different phoneme representation for a same word; and updating, by the location change monitor, a current configuration for the speech engine according to the identified location-based configuration parameters. 7. The apparatus of claim 5 , wherein the first acoustic model and the second acoustic model associate different audio input with a same phoneme.

24. The device control method of claim 19 for controlling a navigation device mounted on a vehicle, wherein the process execution step specifies a content of a navigation process to be performed based on the specified content of the uttered speech, and performs the specified navigation process.

24. The device control method of claim 19 for controlling a navigation device mounted on a vehicle, wherein the process execution step specifies a content of a navigation process to be performed based on the specified content of the uttered speech, and performs the specified navigation process. 25. The device control method according to claim 24 , further comprising: an information acquisition step of acquiring information via a predetermined communication device; and a speech output step of outputting a speech based on the information acquired in the information acquisition step, whereby when the navigation process specified in the process execution step is to output the information acquired in the information acquisition step, a speech is output based on the information in the speech output step.

24. A tangible computer readable storage medium including computer instructions for defining a service monitor for a web service, the computer instructions comprising instructions for: accepting a functional web service that operates as one of a plurality of functional web services all operating on a single server; including in the functional web service at least one monitor data collection function that records at least one monitor data element, the at least one monitor data element characterizing at least one operation of the functional web service, and the at least one monitor data element being made available to the monitoring service; defining at least one functional web service description language (WSDL) document for the functional web service; defining a monitor web service, separate from the functional web service, the monitor web service providing access to the at least one monitor data element recorded by the at least one data collection function included within the functional web service; and including, in the at least one functional web service description language document (WSDL), a reference to a monitoring web service description language (WSDL) document defining the monitoring service, wherein the monitoring web service description language (WSDL) document is separate from the functional web service description language (WSDL) document.

24. A tangible computer readable storage medium including computer instructions for defining a service monitor for a web service, the computer instructions comprising instructions for: accepting a functional web service that operates as one of a plurality of functional web services all operating on a single server; including in the functional web service at least one monitor data collection function that records at least one monitor data element, the at least one monitor data element characterizing at least one operation of the functional web service, and the at least one monitor data element being made available to the monitoring service; defining at least one functional web service description language (WSDL) document for the functional web service; defining a monitor web service, separate from the functional web service, the monitor web service providing access to the at least one monitor data element recorded by the at least one data collection function included within the functional web service; and including, in the at least one functional web service description language document (WSDL), a reference to a monitoring web service description language (WSDL) document defining the monitoring service, wherein the monitoring web service description language (WSDL) document is separate from the functional web service description language (WSDL) document. 28. The tangible computer readable storage medium according to claim 24 , wherein the monitoring service is developed after the functional web service.

7. One or more computer-storage media embodying computer-useable instructions for performing a method comprising: receiving handwriting input corresponding with a handheld writing device being moved relative to a display surface; displaying digital ink at a location on a display corresponding with a location of the display surface at which the handwriting input is received; analyzing the handwriting input using a recognizer to identify one or more words of text corresponding with the handwriting input; replacing display of the digital ink with the text as the user continues to provide additional handwriting input using the handheld writing device, wherein the text is displayed inline with additional digital ink corresponding with the additional handwriting input; saving the digital ink after the text has been displayed in place of the digital ink; and using the digital ink with new digital ink for recognition purposes, wherein the digital ink is no longer used for recognition purposes when the one or more words of text corresponding with the digital ink are more than a predetermined number of words prior to the new digital ink; receiving input to present a word of the text in a character correction interface, the character correction interface providing an enlarged display of the word in place of an original display of the word to facilitate receiving further handwriting input to correct the word, wherein the character correction interface allows correction of the word on an individual character basis; displaying the word in the character correction interface by replacing the original display of the word with the enlarged display of the word; and adjusting display of other words within the text to provide space for the enlarged display of the word.

7. One or more computer-storage media embodying computer-useable instructions for performing a method comprising: receiving handwriting input corresponding with a handheld writing device being moved relative to a display surface; displaying digital ink at a location on a display corresponding with a location of the display surface at which the handwriting input is received; analyzing the handwriting input using a recognizer to identify one or more words of text corresponding with the handwriting input; replacing display of the digital ink with the text as the user continues to provide additional handwriting input using the handheld writing device, wherein the text is displayed inline with additional digital ink corresponding with the additional handwriting input; saving the digital ink after the text has been displayed in place of the digital ink; and using the digital ink with new digital ink for recognition purposes, wherein the digital ink is no longer used for recognition purposes when the one or more words of text corresponding with the digital ink are more than a predetermined number of words prior to the new digital ink; receiving input to present a word of the text in a character correction interface, the character correction interface providing an enlarged display of the word in place of an original display of the word to facilitate receiving further handwriting input to correct the word, wherein the character correction interface allows correction of the word on an individual character basis; displaying the word in the character correction interface by replacing the original display of the word with the enlarged display of the word; and adjusting display of other words within the text to provide space for the enlarged display of the word. 10. The one or more computer-storage media of claim 7 , wherein the method further comprises: receiving further handwriting input at a location corresponding with a character of the word within the character correction user interface; displaying further digital ink corresponding with the further handwriting input; analyzing at least the further handwriting input using a recognizer to identify an alternate word for the word; and automatically replacing display of the word with display of the alternate word.

1. A learning device comprising: a feature-quantity extraction circuit that extracts a feature quantity from a feature point of each learning image of a plurality of learning images, the plurality of learning images including a first learning image including a detection target and a second learning image not including the detection target; an acquisition circuit that acquires, from an external device, a transfer classifier for detecting the detection target; a weak-classification calculation circuit that calculates a classification result of the detection target according to a weak classifier for each learning image by substituting the feature quantity extracted by the feature-quantity extraction unit that corresponds to the weak classifier into the weak classifier with respect to each of a plurality of weak classifiers constituting the transfer classifier; and a classifier generation circuit that generates a classifier using the transfer classifier and the weak classifier selected from the plurality of weak classifiers based on the classification result of each of the plurality of weak classifiers.

1. A learning device comprising: a feature-quantity extraction circuit that extracts a feature quantity from a feature point of each learning image of a plurality of learning images, the plurality of learning images including a first learning image including a detection target and a second learning image not including the detection target; an acquisition circuit that acquires, from an external device, a transfer classifier for detecting the detection target; a weak-classification calculation circuit that calculates a classification result of the detection target according to a weak classifier for each learning image by substituting the feature quantity extracted by the feature-quantity extraction unit that corresponds to the weak classifier into the weak classifier with respect to each of a plurality of weak classifiers constituting the transfer classifier; and a classifier generation circuit that generates a classifier using the transfer classifier and the weak classifier selected from the plurality of weak classifiers based on the classification result of each of the plurality of weak classifiers. 5. The learning device according to claim 1 , wherein the transfer classifier detects the detection target when the detection target is in a first state, and wherein the generated classifier detects the detection target when the detection target is in a second state different from the first state.

4. A method for configuring a computer, comprising: configuring the computer to create a user interface page, wherein the user interface page when interpreted displays a search graph, wherein the search graph comprises a plurality of axes, and the plurality of axes represent a plurality of respective search criteria; configuring the computer to create the user interface page, wherein the user interface page when interpreted displays a plurality of icons representing a plurality of respective search terms at a plurality of respective positions on the search graph, wherein the plurality of respective positions specify a plurality of respective values of the search criteria for the search term, wherein each of the plurality of respective values represents a relative importance of all of the plurality of search criteria for each of the plurality of respective search terms, wherein the plurality of respective search terms are entered by a user, wherein a first axis of the plurality of axes represents the relative importance of how close the plurality of search terms must be in a web page for the web page to be a match for the plurality of search terms, and wherein a second axis of the plurality of axes represents the relative importance of phrase density, wherein phrase density comprises a frequency of the plurality of respective search terms in the web page divided by a number of words in the web page; configuring the computer to submit the search term and the value of the search criteria to a search engine, wherein the search engine searches for the web page; configuring the computer to display search results from the search engine; and configuring the computer to adjust the plurality of values of the respective search criteria for the plurality of search terms in response to a user requesting a change to the plurality of respective positions of the plurality of icons representing the plurality of respective search terms on the search graph; configuring the computer to move one of the plurality of icons off of the search graph; and configuring the computer to update the search results in response to the change in the position on the search graph.

4. A method for configuring a computer, comprising: configuring the computer to create a user interface page, wherein the user interface page when interpreted displays a search graph, wherein the search graph comprises a plurality of axes, and the plurality of axes represent a plurality of respective search criteria; configuring the computer to create the user interface page, wherein the user interface page when interpreted displays a plurality of icons representing a plurality of respective search terms at a plurality of respective positions on the search graph, wherein the plurality of respective positions specify a plurality of respective values of the search criteria for the search term, wherein each of the plurality of respective values represents a relative importance of all of the plurality of search criteria for each of the plurality of respective search terms, wherein the plurality of respective search terms are entered by a user, wherein a first axis of the plurality of axes represents the relative importance of how close the plurality of search terms must be in a web page for the web page to be a match for the plurality of search terms, and wherein a second axis of the plurality of axes represents the relative importance of phrase density, wherein phrase density comprises a frequency of the plurality of respective search terms in the web page divided by a number of words in the web page; configuring the computer to submit the search term and the value of the search criteria to a search engine, wherein the search engine searches for the web page; configuring the computer to display search results from the search engine; and configuring the computer to adjust the plurality of values of the respective search criteria for the plurality of search terms in response to a user requesting a change to the plurality of respective positions of the plurality of icons representing the plurality of respective search terms on the search graph; configuring the computer to move one of the plurality of icons off of the search graph; and configuring the computer to update the search results in response to the change in the position on the search graph. 7. The method of claim 4 , further comprising: configuring the computer to display the search results in a results pane, wherein the results pane is concurrently visible with the search graph.

1. A distributed machine learning system, comprising: a plurality of distributed learning environments in communication over a network, wherein each environment comprises: a computing device having a memory and a processor coupled to the memory, the processor adapted to implement a learning environment via one or more agents in a rules-based system, wherein the agents learn to perform tasks in their respective learning environment to develop knowledge; a storage in which knowledge comprising a plurality of rule sets developed by the agents for performing the tasks are stored, wherein the knowledge is tagged to facilitate identification, storage and retrieval; an ontology that is weighted to provide, in response to at least one request by the one or more agents, classification of at least a close choice of knowledge to share rule sets developed by the agents in the plurality of distributed learning environments for implementing tasks which are related, but not necessarily the same so that matched parts from the at least close choice of the knowledge provided from at least one sending agent is included with an unmatched part of the rule sets of at least one requesting agent, wherein the at least close choice of knowledge comprising a highest score indicating a level of match of the capabilities between a desired and an available rules lists and providing classification comprises tagging the knowledge with words that define what it does using an ontology-based tagging system; an interface for sharing at least one of the tagged knowledge and the at least close choice of knowledge with other agents throughout the plurality of distributed learning environments when the at least one requesting agent requests at least one of the tagged knowledge and the close choice of knowledge.

1. A distributed machine learning system, comprising: a plurality of distributed learning environments in communication over a network, wherein each environment comprises: a computing device having a memory and a processor coupled to the memory, the processor adapted to implement a learning environment via one or more agents in a rules-based system, wherein the agents learn to perform tasks in their respective learning environment to develop knowledge; a storage in which knowledge comprising a plurality of rule sets developed by the agents for performing the tasks are stored, wherein the knowledge is tagged to facilitate identification, storage and retrieval; an ontology that is weighted to provide, in response to at least one request by the one or more agents, classification of at least a close choice of knowledge to share rule sets developed by the agents in the plurality of distributed learning environments for implementing tasks which are related, but not necessarily the same so that matched parts from the at least close choice of the knowledge provided from at least one sending agent is included with an unmatched part of the rule sets of at least one requesting agent, wherein the at least close choice of knowledge comprising a highest score indicating a level of match of the capabilities between a desired and an available rules lists and providing classification comprises tagging the knowledge with words that define what it does using an ontology-based tagging system; an interface for sharing at least one of the tagged knowledge and the at least close choice of knowledge with other agents throughout the plurality of distributed learning environments when the at least one requesting agent requests at least one of the tagged knowledge and the close choice of knowledge. 8. The distributed machine learning system of claim 1 wherein the processor is adapted to provide an ontological abstraction of the classifications of the knowledge encoded in the rules that is at least a close choice of the knowledge sought.

11. The computer implemented method of claim 10 , wherein the requested electronic document comprises one of the plurality of electronic documents identified in the list of document identifiers previous to a previously transmitted electronic document.

11. The computer implemented method of claim 10 , wherein the requested electronic document comprises one of the plurality of electronic documents identified in the list of document identifiers previous to a previously transmitted electronic document. 14. The computer implemented method of claim 11 , further comprising, prior to utilizing the unique numeric category identifier, the pointer, and the list of document identifiers embodied in the first hyperlink to provide the second hyperlink: incrementing the pointer; generating the second hyperlink comprising the incremented pointer and the list of document identifiers; and transmitting the second hyperlink for provision.

1. A method comprising: determining, using a processor, text subgroups within an electronic text; determining, using the processor, a relevance score for each of one or more words within each of the text subgroups; selecting, using the processor, one of the text subgroups to select a text seed; selecting, using the processor, the text seed within the selected text subgroup based on the relevance scores for the one or more words within the selected text subgroup; determining, using the processor, a similarity relationship between the selected text seed and one or more text subgroups adjacent to the selected text subgroup that do not include the selected text seed; creating, using the processor, a text cluster by associating the selected text seed with the one or more adjacent text subgroups based on the determined similarity relationship to the selected text subgroup; determining an activity indication of times when a user has user read other text subgroups within the electronic text; determining, using the processor, a similarity relationship between the text cluster and the other text subgroups; linking, using the processor, the text cluster to one of the other text subgroups based on the determined similarity relationship to the other text subgroups; and presenting at least one navigational link that links the text cluster to the one of other the text subgroups based on the times when the user read the other text subgroups.

1. A method comprising: determining, using a processor, text subgroups within an electronic text; determining, using the processor, a relevance score for each of one or more words within each of the text subgroups; selecting, using the processor, one of the text subgroups to select a text seed; selecting, using the processor, the text seed within the selected text subgroup based on the relevance scores for the one or more words within the selected text subgroup; determining, using the processor, a similarity relationship between the selected text seed and one or more text subgroups adjacent to the selected text subgroup that do not include the selected text seed; creating, using the processor, a text cluster by associating the selected text seed with the one or more adjacent text subgroups based on the determined similarity relationship to the selected text subgroup; determining an activity indication of times when a user has user read other text subgroups within the electronic text; determining, using the processor, a similarity relationship between the text cluster and the other text subgroups; linking, using the processor, the text cluster to one of the other text subgroups based on the determined similarity relationship to the other text subgroups; and presenting at least one navigational link that links the text cluster to the one of other the text subgroups based on the times when the user read the other text subgroups. 5. The method of claim 1 , wherein selecting the text seed comprises selecting the text seed based on user input.

8. A device for dynamic adjustment of text input system components, the device comprising: one or more processors; and a text input system; a machine-readable medium comprising instructions stored therein, which when executed by the processors, cause the device to perform operations comprising: receiving an indication of user activity with respect to the text input system; determining one or more activity indicators based on at least the user activity, the one or more activity indicators corresponding to typing habits of a user, including at least one of variance of exact touch position within one or more keys and drift of a recorded touch position for the one or more keys; identifying one or more components of the text input system, each component providing a typing assistance functionality to the user and being associated with a set of parameters, the one or more components including a key target resizing component associated with a set of parameters comprising an amount of inactive space around each key and a size of an active area for each key; and for each of the one or more components: determining, by the one or more processors, whether the component should be adjusted based on the one or more activity indicators; and dynamically adjusting the component when it is determined that the component should be adjusted based on the one or more activity indicators, wherein dynamically adjusting the component comprises adjusting the set of parameters associated with the component.

8. A device for dynamic adjustment of text input system components, the device comprising: one or more processors; and a text input system; a machine-readable medium comprising instructions stored therein, which when executed by the processors, cause the device to perform operations comprising: receiving an indication of user activity with respect to the text input system; determining one or more activity indicators based on at least the user activity, the one or more activity indicators corresponding to typing habits of a user, including at least one of variance of exact touch position within one or more keys and drift of a recorded touch position for the one or more keys; identifying one or more components of the text input system, each component providing a typing assistance functionality to the user and being associated with a set of parameters, the one or more components including a key target resizing component associated with a set of parameters comprising an amount of inactive space around each key and a size of an active area for each key; and for each of the one or more components: determining, by the one or more processors, whether the component should be adjusted based on the one or more activity indicators; and dynamically adjusting the component when it is determined that the component should be adjusted based on the one or more activity indicators, wherein dynamically adjusting the component comprises adjusting the set of parameters associated with the component. 13. The system of claim 8 , wherein the one or more components comprise a dictionary component for providing a dictionary in association with the text input system, and wherein the set of parameters associated with the dictionary component comprises at least one of a parameter for a language of the dictionary or a priority for each of multiple language dictionaries.

13. A computer program product embedded in a computer-readable storage medium for providing user-subscribed sources for secure search, comprising: program code for providing to a user a template for crawling a source, the template defining a location of and crawl settings for a target data repository source, the template not having specified security credentials for the source; program code for allowing a user to subscribe to the source using the template; program code for receiving user-specified security credentials from the user and applying the user-specified security credentials to an instance of the template to create a user-subscribed source; program code for authenticating a crawler as the user on the source; program code for crawling the source as the user template with user-specified security credentials; program code for indexing documents for the user during the crawling in an index; and program code for stamping identification information for the user with each entry in the index such that the associated documents are only available for search in the index by the user.

13. A computer program product embedded in a computer-readable storage medium for providing user-subscribed sources for secure search, comprising: program code for providing to a user a template for crawling a source, the template defining a location of and crawl settings for a target data repository source, the template not having specified security credentials for the source; program code for allowing a user to subscribe to the source using the template; program code for receiving user-specified security credentials from the user and applying the user-specified security credentials to an instance of the template to create a user-subscribed source; program code for authenticating a crawler as the user on the source; program code for crawling the source as the user template with user-specified security credentials; program code for indexing documents for the user during the crawling in an index; and program code for stamping identification information for the user with each entry in the index such that the associated documents are only available for search in the index by the user. 19. A computer program product according to claim 13 , further comprising: program code for associating the template with a predetermined group of secure data.

1. A computer translation system comprising A language input device that detects a first language signal and a device location; and An interpretation engine coupled with the language input device and configured to: obtain the first language signal and the device location; activate a language model, including a mobile interference model, based on the first language signal and at least in part based on the device location; update utterance probabilities of the language model based the device location; extract a conceptual interlingua result set from the first language signal according to the updated language model and by applying the mobile interference model; map the conceptual interlingua result set to a second language representation of a second language; and cause an output device to present an output interpretation according to the second language derived from the second language representation.

1. A computer translation system comprising A language input device that detects a first language signal and a device location; and An interpretation engine coupled with the language input device and configured to: obtain the first language signal and the device location; activate a language model, including a mobile interference model, based on the first language signal and at least in part based on the device location; update utterance probabilities of the language model based the device location; extract a conceptual interlingua result set from the first language signal according to the updated language model and by applying the mobile interference model; map the conceptual interlingua result set to a second language representation of a second language; and cause an output device to present an output interpretation according to the second language derived from the second language representation. 6. The system of claim 1 , wherein the device location corresponds to a user position.

5. The speech-enabled system as recited in claim 1 , wherein the question control is further configured to provide a list of possible answers to the question after the custom prompt is played.

5. The speech-enabled system as recited in claim 1 , wherein the question control is further configured to provide a list of possible answers to the question after the custom prompt is played. 8. The speech-enabled system as recited in claim 5 , wherein the list of possible answers is provided by the speech-enabled application that incorporates the question control.

5. A text filtering system comprising: one or more processors; memory; a keyword storage unit stored in the memory and executable by the one or more processors that stores a plurality of semantic keywords; a basic finding unit stored in the memory and executable by the one or more processors that finds a basic keyword of a semantic keyword in an input text; a semantic matching unit stored in the memory and executable by the one or more processors that, in an event that a text content matching the basic keyword in the input text is found, conducts a semantic match in the found text content, the semantic match comprising matching the found text content with the semantic keyword according to the logical operator included in the semantic keyword; and a filter processing unit stored in the memory and executable by the one or more processors that, in an event that the semantic match is successful, filters a matched text context, wherein the basic finding unit comprises: a text obtaining sub-unit that obtains a character c 1 in the input text; a character matching sub-unit that: uses c 1 as a current character and a root node of a tree-type structure as a current node, the root node corresponding to one of a first character or a last character of the basic keyword, determines whether the current character matches the current node, in an event that the current character matches the current node and the current node has a child node, sets a next character following or preceding the current character to be the current character, sets the child node to be the current node and repeats the determining of whether the current character matches the current node, in an event that the current character does not match the current node and the current node has a sibling node, sets the sibling node to be the current node and repeats the determining of whether the current character matches the current node, and in an event that the current character matches the current node and the current node does not have a child node or the current character does not match with the current node and the current node does not have a sibling node; and a determination sub-unit that: connects the last matched current node to the root node to obtain a matching route, and determines whether the basic keyword is found in the input text based at least in part on whether the matching route includes a successfully matched leaf node of the tree-type structure.

5. A text filtering system comprising: one or more processors; memory; a keyword storage unit stored in the memory and executable by the one or more processors that stores a plurality of semantic keywords; a basic finding unit stored in the memory and executable by the one or more processors that finds a basic keyword of a semantic keyword in an input text; a semantic matching unit stored in the memory and executable by the one or more processors that, in an event that a text content matching the basic keyword in the input text is found, conducts a semantic match in the found text content, the semantic match comprising matching the found text content with the semantic keyword according to the logical operator included in the semantic keyword; and a filter processing unit stored in the memory and executable by the one or more processors that, in an event that the semantic match is successful, filters a matched text context, wherein the basic finding unit comprises: a text obtaining sub-unit that obtains a character c 1 in the input text; a character matching sub-unit that: uses c 1 as a current character and a root node of a tree-type structure as a current node, the root node corresponding to one of a first character or a last character of the basic keyword, determines whether the current character matches the current node, in an event that the current character matches the current node and the current node has a child node, sets a next character following or preceding the current character to be the current character, sets the child node to be the current node and repeats the determining of whether the current character matches the current node, in an event that the current character does not match the current node and the current node has a sibling node, sets the sibling node to be the current node and repeats the determining of whether the current character matches the current node, and in an event that the current character matches the current node and the current node does not have a child node or the current character does not match with the current node and the current node does not have a sibling node; and a determination sub-unit that: connects the last matched current node to the root node to obtain a matching route, and determines whether the basic keyword is found in the input text based at least in part on whether the matching route includes a successfully matched leaf node of the tree-type structure. 7. The system as recited in claim 5 , wherein: the semantic keyword comprises a filtering condition; and the semantic matching unit comprises a category matching sub-unit that matches an attribute of the input text with the filtering condition.

1. An apparatus, comprising least one processor and at least one memory including computer program code, the memory and the computer program code configured to, working with the processor, cause the apparatus to perform at least the following: receive a multiple touch input comprising a first touch input having a first text position within a first word such that the first text position is a text position between a first character of the first word and a last letter of the first word, and a second touch input having a second text position such that the second text position is a text position between a first character of a second word and a last letter of the second word; determine a first text selection point positioned outside of the first word based at least in part on the first text position being within the first word, such that the first text selection point is at least one of a text position preceding a first character of the first word, or a text position following a last letter of the first word; determine a second text selection point positioned outside of the second word based at least in part on the second text position, such that the second text selection point is at least one of a text position preceding a first character of the second word, or a text position following a last letter of the second word; and select text information between the first text selection point and the second text selection point.

1. An apparatus, comprising least one processor and at least one memory including computer program code, the memory and the computer program code configured to, working with the processor, cause the apparatus to perform at least the following: receive a multiple touch input comprising a first touch input having a first text position within a first word such that the first text position is a text position between a first character of the first word and a last letter of the first word, and a second touch input having a second text position such that the second text position is a text position between a first character of a second word and a last letter of the second word; determine a first text selection point positioned outside of the first word based at least in part on the first text position being within the first word, such that the first text selection point is at least one of a text position preceding a first character of the first word, or a text position following a last letter of the first word; determine a second text selection point positioned outside of the second word based at least in part on the second text position, such that the second text selection point is at least one of a text position preceding a first character of the second word, or a text position following a last letter of the second word; and select text information between the first text selection point and the second text selection point. 13. The apparatus of claim 1 , wherein the second text selection point is a text position associated with an end of a word preceding the second word.

8. A system comprising: one or more computer systems, each computer system having at least one processor and one memory device; the one or more computer systems configured to provide; a reputation scorer operating on at least one of the computer systems, the reputation scorer, using the at least one computer system, searches for a first category to identify persons related to said first category and determines a reputation rating for said persons relating to said first category; and an influencer analyzer operating on at least one of the computer systems, the influence analyzer, using the computer system, configured to: search a social network for persons having said reputation rating for said first category; determine a strength of a relationship between a first user and the identified persons, wherein the strength of the relationship is a variable strength of the relationship based upon an analysis of various relationships between the first user and the identified persons; determine an influence score for said persons based at least in part on the determined strength of the relationship; and rank said persons based in part on said influence score; and an application operating on at least one of the computer systems, the application, using the computer system, configured to: filter or rank the results of a query based on the ranked said persons to generate a customized set of search results; and present the customized set of search results in response to the query.

8. A system comprising: one or more computer systems, each computer system having at least one processor and one memory device; the one or more computer systems configured to provide; a reputation scorer operating on at least one of the computer systems, the reputation scorer, using the at least one computer system, searches for a first category to identify persons related to said first category and determines a reputation rating for said persons relating to said first category; and an influencer analyzer operating on at least one of the computer systems, the influence analyzer, using the computer system, configured to: search a social network for persons having said reputation rating for said first category; determine a strength of a relationship between a first user and the identified persons, wherein the strength of the relationship is a variable strength of the relationship based upon an analysis of various relationships between the first user and the identified persons; determine an influence score for said persons based at least in part on the determined strength of the relationship; and rank said persons based in part on said influence score; and an application operating on at least one of the computer systems, the application, using the computer system, configured to: filter or rank the results of a query based on the ranked said persons to generate a customized set of search results; and present the customized set of search results in response to the query. 16. The system of claim 8 , said social network aggregator that searches a maximum number of nodes away from said user.

1. A computer-implemented method comprising: receiving, at a computer system, a request to determine whether to assign a classification to a first query; selecting, by the computer system, a plurality of search entities that are associated with the first query based on respective user behavior data for the first query associated with each of the search entities; determining a first measure of how many of the plurality of search entities have been assigned the classification; determining that the first measure of how many of the plurality of search entities have been assigned the classification satisfies a classification threshold; in response to determining that the first measure of how many of the plurality of search entities have been assigned the classification satisfies the classification threshold, determining a second measure of how many of a top group of search entities from the plurality of search entities have been assigned the classification, each search entity in the top group of search entities being in a subset of the plurality of search entities having highest respective measures of relevance to the query based on the user behavior data; determining, by the computer system that the first measure of how many of the plurality of search entities have been assigned the classification is consistent with the second measure of how many of the top group of search entities have been assigned the classification; and in response to determining that the first measure of how many of the plurality of search entities have been assigned the classification is consistent with the second measure of how many of the top group of search entities have been assigned the classification, assigning the classification to the first query.

1. A computer-implemented method comprising: receiving, at a computer system, a request to determine whether to assign a classification to a first query; selecting, by the computer system, a plurality of search entities that are associated with the first query based on respective user behavior data for the first query associated with each of the search entities; determining a first measure of how many of the plurality of search entities have been assigned the classification; determining that the first measure of how many of the plurality of search entities have been assigned the classification satisfies a classification threshold; in response to determining that the first measure of how many of the plurality of search entities have been assigned the classification satisfies the classification threshold, determining a second measure of how many of a top group of search entities from the plurality of search entities have been assigned the classification, each search entity in the top group of search entities being in a subset of the plurality of search entities having highest respective measures of relevance to the query based on the user behavior data; determining, by the computer system that the first measure of how many of the plurality of search entities have been assigned the classification is consistent with the second measure of how many of the top group of search entities have been assigned the classification; and in response to determining that the first measure of how many of the plurality of search entities have been assigned the classification is consistent with the second measure of how many of the top group of search entities have been assigned the classification, assigning the classification to the first query. 8. The method of claim 1 , wherein determining the first measure of how many of the plurality of search entities have been assigned the classification comprises: determining the first measure of how many of the plurality of search entities have been assigned the classification according to respective weights for the classification assigned to each of the plurality of search entities, the weights being based on the user behavior data associated with each of the plurality of search entities.

31. The computer implemented method of claim 23 , further comprising the step of receiving user performance data and an updated learning objective from a software application, and then translating said performance data and said updated learning objective back into a user profile.

31. The computer implemented method of claim 23 , further comprising the step of receiving user performance data and an updated learning objective from a software application, and then translating said performance data and said updated learning objective back into a user profile. 32. The computer implemented method of claim 31 , wherein the step of translating said performance data back into a user profile comprises the use of a weighting factor which is the inverse of a weighting factor used for adapting the software application.

28. The method of claim 24 , wherein the input string comprises an HTTP request message, and the method further comprises: examining the input string, using the parser, to identify a Universal Resource Identifier (URI) field of the request message.

28. The method of claim 24 , wherein the input string comprises an HTTP request message, and the method further comprises: examining the input string, using the parser, to identify a Universal Resource Identifier (URI) field of the request message. 29. The method of claim 28 , further comprising: comparing characters of the input string, using the parser, with the regular expression “[ASCII]+[whitespace]HTTP” to identify the URI field of the request message.

27. An apparatus comprising: a processor configured to: define a communication goal data structure, wherein the communication goal data structure is associated with a communication goal and comprises (1) first data that is indicative of a content block data structure associated with the communication goal data structure, the associated content block data structure comprising a parameterized model for a plurality of data components that need to be analyzed to generate a narrative and a parameterized model for a plurality of computational components for analyzing the data components to generate a narrative, and (2) second data that is indicative of a plurality of communication goal parameters whose values are variable, wherein the plurality of communication goal parameters are for use by the parameterized models of the associated content block data structure; store the defined communication goal data structure in a memory such that the defined communication goal data structure is accessible for use by a processor when automatically generating a narrative about data based on input about a communication goal to be satisfied by the automatically generated narrative; receive input through an interface, the input defining a plurality of values for the communication goal parameters; instantiate the content block data structure associated with the communication goal data structure based on the defined parameter values; and automatically generate a narrative about the data using the instantiated content block data structure, wherein the narrative targets the communication goal associated with the communication goal data structure.

27. An apparatus comprising: a processor configured to: define a communication goal data structure, wherein the communication goal data structure is associated with a communication goal and comprises (1) first data that is indicative of a content block data structure associated with the communication goal data structure, the associated content block data structure comprising a parameterized model for a plurality of data components that need to be analyzed to generate a narrative and a parameterized model for a plurality of computational components for analyzing the data components to generate a narrative, and (2) second data that is indicative of a plurality of communication goal parameters whose values are variable, wherein the plurality of communication goal parameters are for use by the parameterized models of the associated content block data structure; store the defined communication goal data structure in a memory such that the defined communication goal data structure is accessible for use by a processor when automatically generating a narrative about data based on input about a communication goal to be satisfied by the automatically generated narrative; receive input through an interface, the input defining a plurality of values for the communication goal parameters; instantiate the content block data structure associated with the communication goal data structure based on the defined parameter values; and automatically generate a narrative about the data using the instantiated content block data structure, wherein the narrative targets the communication goal associated with the communication goal data structure. 28. The apparatus of claim 27 wherein the interface comprises a user interface, and wherein the received input comprises user input.

29. The method of claim 20 , wherein determining personalization information including the first search phrase and the second search phrase further comprises identifying a search phrase explicitly defined by the at least one community.

29. The method of claim 20 , wherein determining personalization information including the first search phrase and the second search phrase further comprises identifying a search phrase explicitly defined by the at least one community. 30. The method of claim 29 , wherein the search phrase explicitly defined by the at least one community is defined by an owner of the at least one community.

22. A text entry system, comprising: (a) a reduced user input device comprising an auto-correcting keyboard region comprising a plurality of character set members, wherein locations having known coordinates in the auto-correcting keyboard region are associated with corresponding character set members, each location having associated therewith a plurality of said character set members of said alphabet such that contact with one of said locations is ambiguous as to which character set member associated with the location is intended, wherein each time a user contacts the user input device within the auto-correcting keyboard region, a location associated with the user contact is determined and the determined contact location is added to a current input sequence of contact locations; (b) a memory containing a plurality of objects, wherein each object is a string of one or a plurality of character set members; (c) an output device with a text display area; and (d) a processor coupled to the user input device, memory, and output device, said processor comprising: (i) a distance value calculation component which, for each determined contact location in the input sequence of contacts, calculates a set of distance values between the contact locations and the known coordinate locations corresponding to one or a plurality of character set members within the auto-correcting keyboard region; (ii) an object evaluation component which, for each generated input sequence, identifies at least one candidate object in memory, and for each of the at least one identified candidate objects, evaluates each identified candidate object by calculating a matching metric based on the calculated distance values associated with the object, and ranks evaluated candidate objects based on the calculated matching metric values; and (iii) a selection component for identifying at least one candidate object according to an evaluated ranking, presenting the at least one identified object to the user, and enabling the user to select one of the at least one presented objects for output to the text display area on the output device.

22. A text entry system, comprising: (a) a reduced user input device comprising an auto-correcting keyboard region comprising a plurality of character set members, wherein locations having known coordinates in the auto-correcting keyboard region are associated with corresponding character set members, each location having associated therewith a plurality of said character set members of said alphabet such that contact with one of said locations is ambiguous as to which character set member associated with the location is intended, wherein each time a user contacts the user input device within the auto-correcting keyboard region, a location associated with the user contact is determined and the determined contact location is added to a current input sequence of contact locations; (b) a memory containing a plurality of objects, wherein each object is a string of one or a plurality of character set members; (c) an output device with a text display area; and (d) a processor coupled to the user input device, memory, and output device, said processor comprising: (i) a distance value calculation component which, for each determined contact location in the input sequence of contacts, calculates a set of distance values between the contact locations and the known coordinate locations corresponding to one or a plurality of character set members within the auto-correcting keyboard region; (ii) an object evaluation component which, for each generated input sequence, identifies at least one candidate object in memory, and for each of the at least one identified candidate objects, evaluates each identified candidate object by calculating a matching metric based on the calculated distance values associated with the object, and ranks evaluated candidate objects based on the calculated matching metric values; and (iii) a selection component for identifying at least one candidate object according to an evaluated ranking, presenting the at least one identified object to the user, and enabling the user to select one of the at least one presented objects for output to the text display area on the output device. 58. The system of claim 22 , wherein said auto-correcting keyboard region is displayed or printed on the surface of the user input device without defined key boundaries.

15. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: performing automatic speech recognition using a bootstrap model on utterance data not having a corresponding manual transcription, to produce automatically transcribed utterances, wherein the bootstrap model is based on text data mined from a website relevant to a specific domain; selecting a predetermined number of utterances not having a corresponding manual transcription based on a geometrically computed n-tuple confidence score; receiving transcriptions of the predetermined number of utterances, wherein the transcriptions are made by a human being; and generating a language model based on the automatically transcribed utterances, the predetermined number of utterances, and the transcriptions.

15. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: performing automatic speech recognition using a bootstrap model on utterance data not having a corresponding manual transcription, to produce automatically transcribed utterances, wherein the bootstrap model is based on text data mined from a website relevant to a specific domain; selecting a predetermined number of utterances not having a corresponding manual transcription based on a geometrically computed n-tuple confidence score; receiving transcriptions of the predetermined number of utterances, wherein the transcriptions are made by a human being; and generating a language model based on the automatically transcribed utterances, the predetermined number of utterances, and the transcriptions. 19. The computer-readable storage device of claim 15 , wherein the predetermined number of utterances used in generating the language model are equal in number to the automatically transcribed utterances.

24. The apparatus of claim 1 , wherein the computerized apparatus comprises an interface compliant with an IEEE 802.11 standard.

24. The apparatus of claim 1 , wherein the computerized apparatus comprises an interface compliant with an IEEE 802.11 standard. 25. The apparatus of claim 24 , wherein the interface compliant with an IEEE 802.11 standard is configured to permit communication between the computerized apparatus and one or more remote networked servers.

1. A method, comprising: tagging an input text string; examining, via a processor, the input text string for at least one first set of substitutions based on content of the input text string; and if the input text string is a substring of a previously tagged input text string: determining whether the input text string and at least one additional input text string share a common pre-assigned tag identifier stored in a memory location, and if the input text string and the at least one additional input text string share the common pre-assigned tag identifier stored in the memory location: eliminating at least one of the input text string and the at least one additional input text string from a natural language grammar.

1. A method, comprising: tagging an input text string; examining, via a processor, the input text string for at least one first set of substitutions based on content of the input text string; and if the input text string is a substring of a previously tagged input text string: determining whether the input text string and at least one additional input text string share a common pre-assigned tag identifier stored in a memory location, and if the input text string and the at least one additional input text string share the common pre-assigned tag identifier stored in the memory location: eliminating at least one of the input text string and the at least one additional input text string from a natural language grammar. 4. The method of claim 1 , wherein eliminating at least one of the input text string and the at least one additional input text string from the natural language grammar comprises determining which comprises a longer input text string and eliminating that which is a longer input text string among the input text string and the at least one additional input text string.

6. The method of claim 1 , wherein creating the domain-specific sentiment lexicon based at least in part on the set of high-sentiment documents comprises: identifying n-grams occurring within the documents in the set of high-sentiment documents; filtering the identified n-grams to remove n-grams unlikely to express sentiment in the specific domain; and storing the filtered n-grams as the domain-specific sentiment lexicon.

6. The method of claim 1 , wherein creating the domain-specific sentiment lexicon based at least in part on the set of high-sentiment documents comprises: identifying n-grams occurring within the documents in the set of high-sentiment documents; filtering the identified n-grams to remove n-grams unlikely to express sentiment in the specific domain; and storing the filtered n-grams as the domain-specific sentiment lexicon. 7. The method of claim 6 , wherein filtering the identified n-grams comprises: removing extremely common n-grams.

1. A method, comprising: at an electronic device having a touch-sensitive surface and configured to execute a software application: displaying views of the software application, wherein the displayed views are associated with a plurality of gesture recognizers, the plurality of gesture recognizers including: at least one discrete gesture recognizer, the discrete gesture recognizer configured to recognize a respective discrete gesture in accordance with a discrete gesture definition and send to the software application only a single action message that indicates recognition of the respective discrete gesture in response to the respective discrete gesture; and at least one continuous gesture recognizer, the continuous gesture recognizer configured to recognize a respective continuous gesture in accordance with a continuous gesture definition that is distinct from the discrete gesture definition and send to the software application action messages for successive recognized sub-events of the respective continuous gesture, wherein: each discrete gesture recognizer is configured to send only a single action message for each gesture recognized by the discrete gesture recognizer, and each continuous gesture recognizer is configured to send a sequence of action messages for each gesture recognized by the continuous gesture recognizer; detecting one or more touches; processing the one or more touches using one or more of the gesture recognizers, the processing of a respective touch of the one or more touches including: processing the respective touch at a respective gesture recognizer in accordance with a respective gesture definition corresponding to the respective gesture recognizer, and conditionally sending one or more respective action messages from the respective gesture recognizer to the software application in accordance with an outcome of the processing of the respective touch at the respective gesture recognizer; and executing the software application in accordance with one or more action messages received from one or more of the gesture recognizers corresponding to one or more of the touches.

1. A method, comprising: at an electronic device having a touch-sensitive surface and configured to execute a software application: displaying views of the software application, wherein the displayed views are associated with a plurality of gesture recognizers, the plurality of gesture recognizers including: at least one discrete gesture recognizer, the discrete gesture recognizer configured to recognize a respective discrete gesture in accordance with a discrete gesture definition and send to the software application only a single action message that indicates recognition of the respective discrete gesture in response to the respective discrete gesture; and at least one continuous gesture recognizer, the continuous gesture recognizer configured to recognize a respective continuous gesture in accordance with a continuous gesture definition that is distinct from the discrete gesture definition and send to the software application action messages for successive recognized sub-events of the respective continuous gesture, wherein: each discrete gesture recognizer is configured to send only a single action message for each gesture recognized by the discrete gesture recognizer, and each continuous gesture recognizer is configured to send a sequence of action messages for each gesture recognized by the continuous gesture recognizer; detecting one or more touches; processing the one or more touches using one or more of the gesture recognizers, the processing of a respective touch of the one or more touches including: processing the respective touch at a respective gesture recognizer in accordance with a respective gesture definition corresponding to the respective gesture recognizer, and conditionally sending one or more respective action messages from the respective gesture recognizer to the software application in accordance with an outcome of the processing of the respective touch at the respective gesture recognizer; and executing the software application in accordance with one or more action messages received from one or more of the gesture recognizers corresponding to one or more of the touches. 2. The method of claim 1 , wherein each gesture recognizer has a set of gesture recognizer states.

16. A mobile device comprising: a user interface configured to receive a user request to create an image-based reminder, the user request including a time period; a camera for capturing one or more images in conjunction with receiving the user request; and a processing subsystem configured to: extract one or more identifying data items from the one or more images, wherein the one or more identifying data items include location information; cross-reference the location information with a database that stores one or more locations each associated with at least one of a corresponding keyword or a corresponding message, to identify a first message stored in the database and associated with the location information; use the first message to form a reminder message; store, in a memory, the reminder message with an association to the time period; monitor time to detect when the time period is reached; and when the time period is reached: access the memory to obtain the reminder message; and provide the reminder message to the user.

16. A mobile device comprising: a user interface configured to receive a user request to create an image-based reminder, the user request including a time period; a camera for capturing one or more images in conjunction with receiving the user request; and a processing subsystem configured to: extract one or more identifying data items from the one or more images, wherein the one or more identifying data items include location information; cross-reference the location information with a database that stores one or more locations each associated with at least one of a corresponding keyword or a corresponding message, to identify a first message stored in the database and associated with the location information; use the first message to form a reminder message; store, in a memory, the reminder message with an association to the time period; monitor time to detect when the time period is reached; and when the time period is reached: access the memory to obtain the reminder message; and provide the reminder message to the user. 18. The mobile device of claim 16 , wherein the processing subsystem is further configured to: cross-reference the location information with the database to identify a first keyword associated with the location information; identify the first message using the first keyword, wherein the first message is associated with the first keyword.

1. A computer-implemented method comprising: (A) using an automatic speech recognizer to produce a document based on an audio signal; (B) receiving input text; (C) determining whether the input text contains at least one non-alphanumeric character; (D) if, during (C), it is determined that the input text does not contain at least one non-alphanumeric character, then: (D)(1) identifying the input text as first anchor text; (D)(2) determining whether the document contains an instance of the first anchor text; (D)(3) if it is determined that the document contains an instance of the first anchor text, then identifying the instance of the first anchor text in the document; (E) if, during (C), it is determined that the input text contains solely a first non-alphanumeric character, then: (E)(1) identifying a portion of the input text appearing before the first non-alphanumeric character as the first anchor text; (E)(2) determining whether the document contains an instance of the first anchor text; (E)(3) identifying, in the document, a portion of the input text appearing after the first anchor text as replacement text; (F) if, during (C), it is determined that the input text contains a plurality non-alphanumeric characters, then: (F)(1) identifying the portion of the input text appearing before a first one of the plurality of non-alphanumeric characters as first anchor text, identifying the portion of the input text appearing after a last one of the non-alphanumeric characters as second anchor text, and identifying a portion of the input text in between the first anchor text and the second anchor text as replacement text; (F)(2) determining whether the document contains an instance of the first anchor text and an instance of the second anchor text at a position in the document after the instance of the first anchor text; (F)(3) if it is determined that the document contains an instance of the first anchor text and an instance of the second anchor text at a position in the document after the instance of the first anchor text, then: (F)(3)(a) identifying text in the document between the instance of the first anchor text and the instance of the second anchor text; (F)(3)(b) replacing the text between the instance of the first anchor text and the instance of the second anchor text with the replacement text, without replacing the instance of the first anchor text and without replacing the instance of the second anchor text; and (F)(3)(c) moving, automatically after (D)(2), a text cursor to a position in the document corresponding to a current audio cursor position representing a location in the audio signal that is being played back.

1. A computer-implemented method comprising: (A) using an automatic speech recognizer to produce a document based on an audio signal; (B) receiving input text; (C) determining whether the input text contains at least one non-alphanumeric character; (D) if, during (C), it is determined that the input text does not contain at least one non-alphanumeric character, then: (D)(1) identifying the input text as first anchor text; (D)(2) determining whether the document contains an instance of the first anchor text; (D)(3) if it is determined that the document contains an instance of the first anchor text, then identifying the instance of the first anchor text in the document; (E) if, during (C), it is determined that the input text contains solely a first non-alphanumeric character, then: (E)(1) identifying a portion of the input text appearing before the first non-alphanumeric character as the first anchor text; (E)(2) determining whether the document contains an instance of the first anchor text; (E)(3) identifying, in the document, a portion of the input text appearing after the first anchor text as replacement text; (F) if, during (C), it is determined that the input text contains a plurality non-alphanumeric characters, then: (F)(1) identifying the portion of the input text appearing before a first one of the plurality of non-alphanumeric characters as first anchor text, identifying the portion of the input text appearing after a last one of the non-alphanumeric characters as second anchor text, and identifying a portion of the input text in between the first anchor text and the second anchor text as replacement text; (F)(2) determining whether the document contains an instance of the first anchor text and an instance of the second anchor text at a position in the document after the instance of the first anchor text; (F)(3) if it is determined that the document contains an instance of the first anchor text and an instance of the second anchor text at a position in the document after the instance of the first anchor text, then: (F)(3)(a) identifying text in the document between the instance of the first anchor text and the instance of the second anchor text; (F)(3)(b) replacing the text between the instance of the first anchor text and the instance of the second anchor text with the replacement text, without replacing the instance of the first anchor text and without replacing the instance of the second anchor text; and (F)(3)(c) moving, automatically after (D)(2), a text cursor to a position in the document corresponding to a current audio cursor position representing a location in the audio signal that is being played back. 8. The method of claim 1 , wherein (F)(1) and (F)(2) are performed without receiving text cursor navigation commands from the user.

22. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving search results in response to a query, the query including one or more keywords, the search results including a first search result and a second search result; generating a set of final search results from the received search results with one or more processors, including: adding the first search result to the set of final search results; determining that a first document corresponding to the first search result and a second document corresponding to the second search result are query-specific duplicate documents from a comparison of one or more first query-relevant parts of the first document and one or more second query-relevant parts of the second document, where each query-relevant part includes at least one of the one or more keywords; and in response to the determination, not adding the second search result to the set of final search results; and providing the set of final search results.

22. A computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving search results in response to a query, the query including one or more keywords, the search results including a first search result and a second search result; generating a set of final search results from the received search results with one or more processors, including: adding the first search result to the set of final search results; determining that a first document corresponding to the first search result and a second document corresponding to the second search result are query-specific duplicate documents from a comparison of one or more first query-relevant parts of the first document and one or more second query-relevant parts of the second document, where each query-relevant part includes at least one of the one or more keywords; and in response to the determination, not adding the second search result to the set of final search results; and providing the set of final search results. 27. The computer storage medium of claim 22 , wherein the query-relevant parts include a predetermined number of words.

6. The method of claim 1 , wherein the decomposing step applies the supported presentation technology features to resolve inconsistencies among a plurality of browser applications.

6. The method of claim 1 , wherein the decomposing step applies the supported presentation technology features to resolve inconsistencies among a plurality of browser applications. 9. The method of claim 6 , wherein the updating step is repeated for each iterated animation portion.

1. An interactive device of that recognizes input voice of a user and thereby contents of utterance of the user and performs a predetermined response action corresponding to the recognized contents, the interactive device comprising: a recognition section setting means that sets a recognition starting point to an utterance starting end frame serving as a starting end of the user's utterance in the input voice and sets a recognition terminal point to a frame which is a predetermined length of time ahead of the recognition starting point to thereby set a recognition section throughout which voice recognition is performed, a voice recognition means that performs voice recognition for the recognition section, a response action determining means that, if a recognition result by the voice recognition means includes a key phrase, determines a response action associated with the key phrase, and a response action executing means that executes the response action determined by the response action determining means, the recognition section setting means repeatedly updating the frame set as the recognition terminal point to a frame which is the predetermined length of time ahead of the recognition terminal point, to thereby set a plurality of recognition sections having different recognition terminal points, and the voice recognition means performing voice recognition on each of the plurality of recognition sections having different recognition terminal points, wherein the recognition section setting means comprises: a recognition starting point setting unit that detects the utterance starting end frame and sets the recognition starting point at the detected utterance starting end frame, a recognition terminal point setting unit that sets the recognition terminal point at a frame which is the predetermined length of time ahead of the recognition starting point set by the recognition starting point setting unit; and a recognition terminal point updating unit that updates repeatedly the recognition terminal point set by the recognition terminal point setting unit to a frame which is the predetermined length of time ahead of the recognition terminal point, the recognition terminal point updating unit detects an utterance terminal end frame serving as a terminal end of the user's utterance in the input voice and updates the recognition terminal point to the detected utterance terminal end frame, said recognition terminal point being either one of the recognition terminal point set by the recognition terminal point setting unit and the recognition terminal point updated by the recognition terminal point updating unit, the voice recognition means comprises: a first-path searching unit that searches word candidates in the user's utterance in a direction from the utterance starting end frame to the utterance terminal end frame, and a second-path search unit that searches the word candidates in each of the plurality of recognition sections having different recognition terminal points in a direction from the recognition terminal point to the recognition starting point according to a search result produced by the first-path searching unit, and the response action determining means determines, when a search result produced by the second-path search unit includes the key phase, the response action corresponding to the key phrase.

1. An interactive device of that recognizes input voice of a user and thereby contents of utterance of the user and performs a predetermined response action corresponding to the recognized contents, the interactive device comprising: a recognition section setting means that sets a recognition starting point to an utterance starting end frame serving as a starting end of the user's utterance in the input voice and sets a recognition terminal point to a frame which is a predetermined length of time ahead of the recognition starting point to thereby set a recognition section throughout which voice recognition is performed, a voice recognition means that performs voice recognition for the recognition section, a response action determining means that, if a recognition result by the voice recognition means includes a key phrase, determines a response action associated with the key phrase, and a response action executing means that executes the response action determined by the response action determining means, the recognition section setting means repeatedly updating the frame set as the recognition terminal point to a frame which is the predetermined length of time ahead of the recognition terminal point, to thereby set a plurality of recognition sections having different recognition terminal points, and the voice recognition means performing voice recognition on each of the plurality of recognition sections having different recognition terminal points, wherein the recognition section setting means comprises: a recognition starting point setting unit that detects the utterance starting end frame and sets the recognition starting point at the detected utterance starting end frame, a recognition terminal point setting unit that sets the recognition terminal point at a frame which is the predetermined length of time ahead of the recognition starting point set by the recognition starting point setting unit; and a recognition terminal point updating unit that updates repeatedly the recognition terminal point set by the recognition terminal point setting unit to a frame which is the predetermined length of time ahead of the recognition terminal point, the recognition terminal point updating unit detects an utterance terminal end frame serving as a terminal end of the user's utterance in the input voice and updates the recognition terminal point to the detected utterance terminal end frame, said recognition terminal point being either one of the recognition terminal point set by the recognition terminal point setting unit and the recognition terminal point updated by the recognition terminal point updating unit, the voice recognition means comprises: a first-path searching unit that searches word candidates in the user's utterance in a direction from the utterance starting end frame to the utterance terminal end frame, and a second-path search unit that searches the word candidates in each of the plurality of recognition sections having different recognition terminal points in a direction from the recognition terminal point to the recognition starting point according to a search result produced by the first-path searching unit, and the response action determining means determines, when a search result produced by the second-path search unit includes the key phase, the response action corresponding to the key phrase. 5. The interactive device of claim 1 , wherein it further comprises: a response action storing means that stores, in relation with each other, the key phrase, the response action corresponding to the key phrase, and a response action category serving as a category of the response action, and a response action history storing means that stores a history of response actions already determined by the response action determining means, wherein, when the search result by the second-path search unit includes the key phase, the response action determining means judges, by referring to the response action storing means and the response action history storing means, whether or not a response action category of a response action determined currently by the response action determining means and a response action category of a response action determined previously by the response action determining means are the same, and determines, when the both categories are the same, the response action corresponding to the key phrase.

1. A computer-implemented process for enabling multidimensional search capabilities on a computing device, other than a desktop personal computer or a laptop computer, being utilized by a user, comprising: using said computing device to perform the following process actions: receiving an original query submitted by the user via the computing device; accessing a structured data repository to extract structured data that is available for the original query, wherein the extracted structured data represents attributes of the original query; providing the extracted structured data to the user in the form of a hierarchical menu which allows the user to interactively modify the original query by selecting at least one item from the hierarchical menu, such modification resulting in a revised query; submitting the revised query to a search service; receiving search results for the revised query from the search service; and providing the search results to the user via the computing device.

1. A computer-implemented process for enabling multidimensional search capabilities on a computing device, other than a desktop personal computer or a laptop computer, being utilized by a user, comprising: using said computing device to perform the following process actions: receiving an original query submitted by the user via the computing device; accessing a structured data repository to extract structured data that is available for the original query, wherein the extracted structured data represents attributes of the original query; providing the extracted structured data to the user in the form of a hierarchical menu which allows the user to interactively modify the original query by selecting at least one item from the hierarchical menu, such modification resulting in a revised query; submitting the revised query to a search service; receiving search results for the revised query from the search service; and providing the search results to the user via the computing device. 15. The process of claim 1 , wherein the computing device comprises a display device and a three-dimensional gesture-sensing device, and the process action of providing the extracted structured data to the user in the form of a hierarchical menu which allows the user to interactively modify the original query comprises the actions of: displaying a plurality of graphical elements on the display device, wherein each graphical element represents a different item of extracted structured data and is labeled to identify said item; and whenever the user gestures with his hand to virtually grab one or more of the graphical elements, using the item of extracted structured data represented by each grabbed graphical element to generate the revised query.

15. A computer readable medium storing a computer program for execution by at least one processor, the computer program comprising: a set of instructions for defining a set of objects to be included in a menu theme template for producing a multimedia menu comprising a plurality of user-selectable menu controls for navigating a multimedia presentation, said set of objects comprising a drop zone area object for receiving and displaying content selected by a user while the multimedia menu is being authored, wherein said set of instructions for defining the set of object comprises a set of instructions for defining properties for the set of objects in a menu theme description file; a set of instructions for defining a set of modules for rendering the set of objects, each module providing a particular functionality for rendering a particular object in the set of objects; a set of instructions for defining a set of paths to said set of modules; and a set of instructions for defining a rendering engine for compositing a user-editable version of the menu theme template based on the properties defined in the menu theme description file and the set of objects rendered according to the set of modules, said rendering engine using the set of paths to identify the set of modules, said menu theme template for allowing the user to author the multimedia menu.

15. A computer readable medium storing a computer program for execution by at least one processor, the computer program comprising: a set of instructions for defining a set of objects to be included in a menu theme template for producing a multimedia menu comprising a plurality of user-selectable menu controls for navigating a multimedia presentation, said set of objects comprising a drop zone area object for receiving and displaying content selected by a user while the multimedia menu is being authored, wherein said set of instructions for defining the set of object comprises a set of instructions for defining properties for the set of objects in a menu theme description file; a set of instructions for defining a set of modules for rendering the set of objects, each module providing a particular functionality for rendering a particular object in the set of objects; a set of instructions for defining a set of paths to said set of modules; and a set of instructions for defining a rendering engine for compositing a user-editable version of the menu theme template based on the properties defined in the menu theme description file and the set of objects rendered according to the set of modules, said rendering engine using the set of paths to identify the set of modules, said menu theme template for allowing the user to author the multimedia menu. 20. The computer readable medium of claim 15 , wherein the set of modules comprises a special effect module, wherein the drop zone is further for displaying the content by using the special effect module to apply a visual effect to the content.

1. A computer implemented method for automatically generating a data repository abstraction component describing, and used to access, data in a data repository, the method comprising: monitoring queries issued against the data repository by an application; collecting, from the monitored queries, information regarding usage of the fields of the data repository; identifying, from the collected usage information, a limited subset of one or more fields of the data repository accessed by the application; and generating, by operation of one or more computer processors and for use in the data repository abstraction component, abstract representations for the limited subset of fields, wherein the abstract representations logically model the respective limited subset of fields, whereby the data repository abstraction component is customized on the basis of usage of the fields of the data repository, and whereby the data repository abstraction component excludes at least one field of the data repository, based on the collected usage information.

1. A computer implemented method for automatically generating a data repository abstraction component describing, and used to access, data in a data repository, the method comprising: monitoring queries issued against the data repository by an application; collecting, from the monitored queries, information regarding usage of the fields of the data repository; identifying, from the collected usage information, a limited subset of one or more fields of the data repository accessed by the application; and generating, by operation of one or more computer processors and for use in the data repository abstraction component, abstract representations for the limited subset of fields, wherein the abstract representations logically model the respective limited subset of fields, whereby the data repository abstraction component is customized on the basis of usage of the fields of the data repository, and whereby the data repository abstraction component excludes at least one field of the data repository, based on the collected usage information. 2. The method of claim 1 , wherein identifying the limited subset of fields comprises extracting, from the monitored queries, a list of one or more referenced fields.

1. A method for producing and organizing electronically stored information, the method comprising: identifying, with one or more processors associated with one or more computer systems, a plurality of documents from the electronically stored information as satisfying similarity criteria; identifying, with the one or more processors associated with one or more computer systems, a first document in the plurality of documents as a pivot document for the plurality of documents that satisfy the similarity criteria, the pivot document being representative of the plurality of documents that satisfy the similarity criteria; generating, with the one or more processors associated with one or more computer systems, information configured to display a graphical user interface that enables users of the graphical user interface to associate review content with each pivot document in a collection of pivot documents visually represented in the graphical user interface; receiving, at the one or more computer systems, the review content that is indicative of textual information or one or more annotations provided by a user of the graphical user interface; associating, with the one or more processors associated with one or more computer systems, the review content indicative of the textual information or the one or more annotations with the pivot document; and propagating, with the one or more processors associated with one or more computer systems, the review content indicative of the textual information or the one or more annotations from the pivot document to one or more documents in the plurality of documents that satisfy the similarity criteria.

1. A method for producing and organizing electronically stored information, the method comprising: identifying, with one or more processors associated with one or more computer systems, a plurality of documents from the electronically stored information as satisfying similarity criteria; identifying, with the one or more processors associated with one or more computer systems, a first document in the plurality of documents as a pivot document for the plurality of documents that satisfy the similarity criteria, the pivot document being representative of the plurality of documents that satisfy the similarity criteria; generating, with the one or more processors associated with one or more computer systems, information configured to display a graphical user interface that enables users of the graphical user interface to associate review content with each pivot document in a collection of pivot documents visually represented in the graphical user interface; receiving, at the one or more computer systems, the review content that is indicative of textual information or one or more annotations provided by a user of the graphical user interface; associating, with the one or more processors associated with one or more computer systems, the review content indicative of the textual information or the one or more annotations with the pivot document; and propagating, with the one or more processors associated with one or more computer systems, the review content indicative of the textual information or the one or more annotations from the pivot document to one or more documents in the plurality of documents that satisfy the similarity criteria. 2. The method of claim 1 , wherein propagating the review content indicative of the textual information or the one or more annotations from the pivot document to the one or more documents in the plurality of documents that satisfy the similarity criteria comprises associating the review content indicative of the textual information or the one or more annotations with the one or more documents in the plurality of documents that satisfy the similarity criteria.

9. One or more non-transitory machine-readable storage media storing instructions that are executable by one or more processing devices to perform operations comprising: receiving an input query from a computing device; comparing words in the input query to keywords, the keywords being associated with content items that can be provided to computing devices; generating, based on the comparing, matching scores indicating how well the input query matches keywords for different content items; obtaining geographies associated with the computing device and associated with the content items that can be provided to computing devices; identifying geographic matches between the computing device and at least some of the content items; including, in an auction, content items having matching scores that exceed a threshold and that match a geography of the computing device, the auction for receiving bids from content providers to determine which of the content items in the auction to output in response to the input query; determining, based at least in part on bids provided in the auction, candidate content items for output in response to the input query; obtaining geographic areas associated with the candidate content items; selecting a candidate content item having a smallest geographic area; and outputting the selected candidate content item in response to the input query.

9. One or more non-transitory machine-readable storage media storing instructions that are executable by one or more processing devices to perform operations comprising: receiving an input query from a computing device; comparing words in the input query to keywords, the keywords being associated with content items that can be provided to computing devices; generating, based on the comparing, matching scores indicating how well the input query matches keywords for different content items; obtaining geographies associated with the computing device and associated with the content items that can be provided to computing devices; identifying geographic matches between the computing device and at least some of the content items; including, in an auction, content items having matching scores that exceed a threshold and that match a geography of the computing device, the auction for receiving bids from content providers to determine which of the content items in the auction to output in response to the input query; determining, based at least in part on bids provided in the auction, candidate content items for output in response to the input query; obtaining geographic areas associated with the candidate content items; selecting a candidate content item having a smallest geographic area; and outputting the selected candidate content item in response to the input query. 10. The one or more non-transitory machine-readable storage media of claim 9 , wherein matching scores of the candidate content items are within a predefined tolerance of each other, and bids associated with the candidate content items are within a predefined tolerance of each other.

8. A computer program product having stored thereon computer-executable instructions that, when executed by a processor, cause a computer system to perform a method including the following: detect a change to an application executing on a device, the executing application having a configuration and a first state, the executing application integrated with a second application, the change affecting a resource included in the application and defining a second state; determine a context for the second state; and disposition the change based on the context.

8. A computer program product having stored thereon computer-executable instructions that, when executed by a processor, cause a computer system to perform a method including the following: detect a change to an application executing on a device, the executing application having a configuration and a first state, the executing application integrated with a second application, the change affecting a resource included in the application and defining a second state; determine a context for the second state; and disposition the change based on the context. 13. The computer program product of claim 8 , wherein computer-executable instructions that, when executed, cause the computer system to determine a context for the second state comprise computer-executable instructions that, when executed, cause the computer system to determine a context that includes parameters of an operating system.

14. A method for designing an integrated circuit using a high-level synthesis (HLS) tool, the method comprising: defining, by a synthesis tool module, a library component based on a first register-transfer level (RTL) configured to define an element of the integrated circuit, replacing, by the synthesis tool module, a portion of a source code corresponding to a first program model with the library component, the source code defining the integrated circuit, and generating, by the synthesis tool module, a second RTL description representing the integrated circuit based on the source code, wherein during the generating of the second RTL description, an output is written to a first memory location in a same clock cycle as reading an input from a second memory location.

14. A method for designing an integrated circuit using a high-level synthesis (HLS) tool, the method comprising: defining, by a synthesis tool module, a library component based on a first register-transfer level (RTL) configured to define an element of the integrated circuit, replacing, by the synthesis tool module, a portion of a source code corresponding to a first program model with the library component, the source code defining the integrated circuit, and generating, by the synthesis tool module, a second RTL description representing the integrated circuit based on the source code, wherein during the generating of the second RTL description, an output is written to a first memory location in a same clock cycle as reading an input from a second memory location. 18. The method of claim 14 , wherein the generating of the second RTL description includes writing an output to a first memory location in a same clock cycle as reading an input from a second memory location when interfacing with the library component.

34. A computer implemented method, comprising: using at least one computer system configured for: receiving a SQL statement for a database for compilation, at an auto tuning optimizer and performance information related to the SQL statement; and determining whether one or more statistics relating to the SQL statement are available or accurate in the performance information; determining a hint for a missing or an inaccurate statistic in the performance information; creating or improving an estimate of a value determined by the auto-tuning optimizer for generating an execution plan by sampling an adjustable portion of data of the database without requiring performance of a full table scan and by using a hint based at least in part upon a recursive determination of a relationship between a predicate selectivity and a threshold or a determination of whether an index for the SQL statement exists; and verifying the estimate by executing the SQL statement to perform at least the full table scan based at least in part upon the predicate selectivity, wherein the act of verifying the estimate performs a sample of a result of the full table scan to adjust the estimate.

34. A computer implemented method, comprising: using at least one computer system configured for: receiving a SQL statement for a database for compilation, at an auto tuning optimizer and performance information related to the SQL statement; and determining whether one or more statistics relating to the SQL statement are available or accurate in the performance information; determining a hint for a missing or an inaccurate statistic in the performance information; creating or improving an estimate of a value determined by the auto-tuning optimizer for generating an execution plan by sampling an adjustable portion of data of the database without requiring performance of a full table scan and by using a hint based at least in part upon a recursive determination of a relationship between a predicate selectivity and a threshold or a determination of whether an index for the SQL statement exists; and verifying the estimate by executing the SQL statement to perform at least the full table scan based at least in part upon the predicate selectivity, wherein the act of verifying the estimate performs a sample of a result of the full table scan to adjust the estimate. 41. The method of claim 34 , further comprising: using the self-corrected information to build auto tuning hints to correct optimizer settings.

11. A computer system for generating at least one multidimensional tag to analyze tagged content, the computer system comprising: at least one processor; and one or more memory devices communicative with the at least one processor, wherein the one or more memory devices store instructions to: define at least one tag core corresponding to web content, wherein the at least one tag core comprises an effective semantic label identifying the web content; record a plurality of predetermined tag dimensions and one or more predetermined measures associated with the web content, wherein the plurality of predetermined tag dimensions comprise parameters of metrics describing evolution of the web content and the one or more predetermined measures comprise parameters of metrics describing consumption of the web content; assemble the at least one tag core with the corresponding recorded plurality of predetermined tag dimensions and the one or more predetermined measures to generate at least one multidimensional tag; and update the at least one multidimensional tag by recording latest at least one predetermined tag dimension and latest predetermined measure when the web content associated with the at least one multidimensional tag is consumed.

11. A computer system for generating at least one multidimensional tag to analyze tagged content, the computer system comprising: at least one processor; and one or more memory devices communicative with the at least one processor, wherein the one or more memory devices store instructions to: define at least one tag core corresponding to web content, wherein the at least one tag core comprises an effective semantic label identifying the web content; record a plurality of predetermined tag dimensions and one or more predetermined measures associated with the web content, wherein the plurality of predetermined tag dimensions comprise parameters of metrics describing evolution of the web content and the one or more predetermined measures comprise parameters of metrics describing consumption of the web content; assemble the at least one tag core with the corresponding recorded plurality of predetermined tag dimensions and the one or more predetermined measures to generate at least one multidimensional tag; and update the at least one multidimensional tag by recording latest at least one predetermined tag dimension and latest predetermined measure when the web content associated with the at least one multidimensional tag is consumed. 12. The computerized system of claim 11 , wherein updating the at least one multidimensional tag comprises: receiving at least one search query; responding to the at least one search query with the web content associated with the at least one multidimensional tag; recording the latest at least one predetermined tag dimension and the corresponding predetermined measure associated with the displayed web content; and updating the at least one multidimensional tag with the latest recorded at least one predetermined tag dimension and the latest predetermined measure.

1. A method of conforming an audio input to a musical key, the method comprising: receiving an audio input; determining a musical key of the audio input; sequentially for each consecutive note of the audio input, determining a pitch value for a preceding note and a subsequent note and an interval between the preceding note and the subsequent note of the audio input, selecting a plurality of alternative subsequent notes for each subsequent note based on the determined musical key and the determined pitch value of the subsequent note, scoring each interval between each alternative subsequent note and each respective note of a selected plurality of alternative subsequent notes corresponding to the preceding note based on the interval between the preceding note and the subsequent note of the audio input, selecting a best interval for each alternative subsequent note based on the scored intervals, and selecting a best-match note for each note of the audio input based on the best intervals of all of the plurality of notes of the audio input; and conforming each note of the audio input to a frequency of each respective best-match note.

1. A method of conforming an audio input to a musical key, the method comprising: receiving an audio input; determining a musical key of the audio input; sequentially for each consecutive note of the audio input, determining a pitch value for a preceding note and a subsequent note and an interval between the preceding note and the subsequent note of the audio input, selecting a plurality of alternative subsequent notes for each subsequent note based on the determined musical key and the determined pitch value of the subsequent note, scoring each interval between each alternative subsequent note and each respective note of a selected plurality of alternative subsequent notes corresponding to the preceding note based on the interval between the preceding note and the subsequent note of the audio input, selecting a best interval for each alternative subsequent note based on the scored intervals, and selecting a best-match note for each note of the audio input based on the best intervals of all of the plurality of notes of the audio input; and conforming each note of the audio input to a frequency of each respective best-match note. 5. The method of claim 1 , wherein each interval is determined based on midi pitch range.

46. The system according to claim 1 wherein said system further comprises a rule-based fact acquisition routine for determining a truth value for a hypothesis fact.

46. The system according to claim 1 wherein said system further comprises a rule-based fact acquisition routine for determining a truth value for a hypothesis fact. 48. The system according to claim 46 wherein said rule-based fact acquisition routine further comprises: a perform test function comprising at least one set of optional input parameters comprising a first set of configurations for a performance test, and at least three output parameters; a first Boolean value comprising a general success value, a general failure value; a second Boolean value comprising a test success value, a test failure value, a third parameter comprising a quality attribute value.

13. The method of claim 12 , further comprising: determining that a first query application module includes at least one event having a validity start time previous to or equal to a timestamp of the punctuation event; and transmitting the punctuation event to the first query application module.

13. The method of claim 12 , further comprising: determining that a first query application module includes at least one event having a validity start time previous to or equal to a timestamp of the punctuation event; and transmitting the punctuation event to the first query application module. 14. The method of claim 13 , further comprising: determining that a second query application module does not include at least one event having a validity start time previous to or equal to the timestamp of the punctuation event; and not transmitting the punctuation event to the second query application module.

3. The method of claim 1 , wherein adjusting the initial language model comprises: accessing a database including one or more follow-up query mappings, each follow-up query mapping specifying a list of candidate follow-up queries for (i) prior transcriptions of utterances of the user, (ii) prior search results associated with the user, and (iii) data associated with the prior search results associated the user; determining that one or more terms of the transcription of the initial utterance of the user are included within the one or more follow-up query mappings; and adjusting the initial language model to increase the respective probability associated with the list of candidate follow-up queries that correspond to the one or more terms of the transcription of the initial utterance of the user that are included within the one or more follow-up query mappings.

3. The method of claim 1 , wherein adjusting the initial language model comprises: accessing a database including one or more follow-up query mappings, each follow-up query mapping specifying a list of candidate follow-up queries for (i) prior transcriptions of utterances of the user, (ii) prior search results associated with the user, and (iii) data associated with the prior search results associated the user; determining that one or more terms of the transcription of the initial utterance of the user are included within the one or more follow-up query mappings; and adjusting the initial language model to increase the respective probability associated with the list of candidate follow-up queries that correspond to the one or more terms of the transcription of the initial utterance of the user that are included within the one or more follow-up query mappings. 4. The method of claim 3 , wherein the list of candidate follow-up queries that are included within the one or more follow-up query mappings is based at least on a user location associated with the initial utterance of the user.

20. The pen input processing apparatus of claim 1, further comprising: informing means for generating a sound to confirm that the editing instruction has been recognized by said recognizing means.

20. The pen input processing apparatus of claim 1, further comprising: informing means for generating a sound to confirm that the editing instruction has been recognized by said recognizing means. 21. The pen input processing apparatus as set forth in claim 20, wherein sad informing means includes: a first sound source for informing by a first sound that the editing instruction is recognized by said recognizing means; and a second sound source for informing by a second sound that the editing instruction is not recognized by said recognizing means, the first and second sounds being different from each other.

11. Computer apparatus locating expertise, comprising: a user interface executable by a computer and enabling users to associate experts with respective certain objects, each object inheriting from classes in a mutable ontology-based hierarchy, the user interface resulting in respective correspondences between experts and the certain objects, wherein the mutable ontology-based hierarchy is extendable on demand such that said associating includes adding objects or classes, on demand, to the ontology-based hierarchy; a processor executable ontology-based location tool coupled to utilize the correspondences and to, based on ontology, find a candidate expert about a particular subject area, the candidate expert being in one of the correspondences associating the candidate expert with one of the certain objects as user defined through the user interface, the tool allowing the certain object associated with the candidate expert to be found from the particular subject area whether the particular subject area is a relatively specific topic or a more general area of expertise than the certain object; and an output member displaying an indication of the candidate expert.

11. Computer apparatus locating expertise, comprising: a user interface executable by a computer and enabling users to associate experts with respective certain objects, each object inheriting from classes in a mutable ontology-based hierarchy, the user interface resulting in respective correspondences between experts and the certain objects, wherein the mutable ontology-based hierarchy is extendable on demand such that said associating includes adding objects or classes, on demand, to the ontology-based hierarchy; a processor executable ontology-based location tool coupled to utilize the correspondences and to, based on ontology, find a candidate expert about a particular subject area, the candidate expert being in one of the correspondences associating the candidate expert with one of the certain objects as user defined through the user interface, the tool allowing the certain object associated with the candidate expert to be found from the particular subject area whether the particular subject area is a relatively specific topic or a more general area of expertise than the certain object; and an output member displaying an indication of the candidate expert. 17. Computer apparatus as claimed in claim 11 wherein the location tool further finds multiple experts per certain object, and the output member displays a listing of the multiple experts.

17. The method of claim 11 , wherein the user interface includes a presentation of a plurality of filter values for the third filter, wherein the plurality of filter values for the third filter is presented in a sequence that is ordered based on the filter context.

17. The method of claim 11 , wherein the user interface includes a presentation of a plurality of filter values for the third filter, wherein the plurality of filter values for the third filter is presented in a sequence that is ordered based on the filter context. 18. The method of claim 17 , wherein the sequence is from a highest to lowest probability of the first filter co-occurring with the third filter in a listing that is randomly identified in the first plurality of listings.

1. A method of managing data, comprising: generating a model file on a non-transitory computer readable medium containing descriptions of the data, wherein the descriptions of the data in the model file are formatted as a collection of dictionaries, wherein the descriptions of the data are divided into multiple groups that are associated with multiple hierarchical pages, wherein the multiple groups associated with the multiple hierarchical pages are listed in the model file in a flat structure, and wherein a first entry in a first of the multiple hierarchical pages shares an identifier with a second entry in a second of the multiple hierarchical pages; and generating a controller file on the non-transitory computer readable medium that, when executed by a processor, causes the processor to interpret the model file and present the data in the multiple hierarchical pages to a user, wherein the controller file refers to one of the multiple groups in the model file, wherein the controller file is re-used to interpret the multiple groups in the descriptions of the data and present the data in the multiple hierarchical pages, and wherein the controller file is configured to retrieve data associated with the second entry and display at least a portion of the data associated with the second entry on the first of the multiple hierarchical pages.

1. A method of managing data, comprising: generating a model file on a non-transitory computer readable medium containing descriptions of the data, wherein the descriptions of the data in the model file are formatted as a collection of dictionaries, wherein the descriptions of the data are divided into multiple groups that are associated with multiple hierarchical pages, wherein the multiple groups associated with the multiple hierarchical pages are listed in the model file in a flat structure, and wherein a first entry in a first of the multiple hierarchical pages shares an identifier with a second entry in a second of the multiple hierarchical pages; and generating a controller file on the non-transitory computer readable medium that, when executed by a processor, causes the processor to interpret the model file and present the data in the multiple hierarchical pages to a user, wherein the controller file refers to one of the multiple groups in the model file, wherein the controller file is re-used to interpret the multiple groups in the descriptions of the data and present the data in the multiple hierarchical pages, and wherein the controller file is configured to retrieve data associated with the second entry and display at least a portion of the data associated with the second entry on the first of the multiple hierarchical pages. 3. The method of claim 1 , wherein the controller file, when executed by the processor, further causes the processor to handle loading of the data from a storage medium and storing of the data to the storage medium.

54. A system comprising one or more processors: an input/output system; an auto-fill engine providing proposed values and corresponding likelihood assessments generated based on values entered in observed form fields using the input/output system, the likelihood assessments indicating relative probability of the proposed values being entered in one or more current form field objects in a current form instance; and a form presentation component displaying the current form instance using the input/output system such that one or more predicted values are displayed in connection with the one or more current form field objects, the one or more predicted values being selected from the proposed values based on the likelihood assessments, wherein the auto-fill engine provides the proposed values and the corresponding likelihood assessments based on a determination of semantic similarity among the one or more current form field objects and the observed form fields.

54. A system comprising one or more processors: an input/output system; an auto-fill engine providing proposed values and corresponding likelihood assessments generated based on values entered in observed form fields using the input/output system, the likelihood assessments indicating relative probability of the proposed values being entered in one or more current form field objects in a current form instance; and a form presentation component displaying the current form instance using the input/output system such that one or more predicted values are displayed in connection with the one or more current form field objects, the one or more predicted values being selected from the proposed values based on the likelihood assessments, wherein the auto-fill engine provides the proposed values and the corresponding likelihood assessments based on a determination of semantic similarity among the one or more current form field objects and the observed form fields. 83. The system of claim 54 , wherein the form presentation component displays a predicted value in one of the one or more current form field objects in response to user activation of the one of the one or more current form field objects when a likelihood assessment for the predicted value is a highest of likelihood assessments corresponding to the one of the one or more current form field objects.

1. A system for providing extensible controls for a content data repository, the system comprising: a content repository, residing on a server with one or more processors, including a plurality of nodes to maintain data associated with a plurality of specific data types, wherein each of the plurality of nodes contains data in one of the plurality of specific data types; an extensible control residing on a server with one or more processors, said extensible control including an invoke method and a set of create, read, update and delete (CRUD) methods for performing specific operations within the content repository; and a plurality of extended control interfaces, wherein each extended control interface is extended from an extensible control interface and is associated with one of the plurality of nodes in the content repository that contains data in one of the plurality of specific data types, said extended control interface including one or more annotations to specify properties of said node in the content repository, wherein the extensible control interface contains logic to map the one or more annotations in the extended control interface into the specific data type and perform one or more operations on a node in the content repository that contains data in the specific data type, said one or more operations being mapped to the CRUD methods on the extensible control such that for every annotated method call on the extended control interface, a corresponding CRUD method is invoked on the extensible control in order to perform an appropriate operation in the content repository, wherein one operation is to programmatically create or modify a specific data type within the content repository instead of changing a configuration file.

1. A system for providing extensible controls for a content data repository, the system comprising: a content repository, residing on a server with one or more processors, including a plurality of nodes to maintain data associated with a plurality of specific data types, wherein each of the plurality of nodes contains data in one of the plurality of specific data types; an extensible control residing on a server with one or more processors, said extensible control including an invoke method and a set of create, read, update and delete (CRUD) methods for performing specific operations within the content repository; and a plurality of extended control interfaces, wherein each extended control interface is extended from an extensible control interface and is associated with one of the plurality of nodes in the content repository that contains data in one of the plurality of specific data types, said extended control interface including one or more annotations to specify properties of said node in the content repository, wherein the extensible control interface contains logic to map the one or more annotations in the extended control interface into the specific data type and perform one or more operations on a node in the content repository that contains data in the specific data type, said one or more operations being mapped to the CRUD methods on the extensible control such that for every annotated method call on the extended control interface, a corresponding CRUD method is invoked on the extensible control in order to perform an appropriate operation in the content repository, wherein one operation is to programmatically create or modify a specific data type within the content repository instead of changing a configuration file. 2. The system of claim 1 wherein the content repository further includes: a type manager associated with the extensible control interface to perform operations associated with the content repository.

5. The method of claim 4 , further comprising: converting all of the plurality of speech signals to words using the specific one of the multiple secondary vocabulary applications.

5. The method of claim 4 , further comprising: converting all of the plurality of speech signals to words using the specific one of the multiple secondary vocabulary applications. 6. The method of claim 5 , further comprising: using a natural language understanding process for recognizing the converted words.

15. A non-transitory computer-readable storage medium storing instructions that when executed by a processor cause actions to be performed, comprising: receiving a plurality of candidate pieces of content; receiving a plurality of aggregated user activity streams, each aggregated user activity stream containing a record of at least one social activity performed by a user on a web page; extracting a plurality of topics from the plurality of aggregated user activity streams; calculating a velocity of each extracted topic based on a difference between a metric of the topic over a first period of time and a metric of the topic over a second period of time, wherein the second period of time came before the first period of time; calculating a trending score for each of the plurality of candidate pieces of content based on a measure of the velocities of one or more extracted topics contained in the candidate piece of content; ranking the plurality of candidate pieces of content based on the trending score; and publishing one or more of the plurality of candidate pieces of content based on the ranking.

15. A non-transitory computer-readable storage medium storing instructions that when executed by a processor cause actions to be performed, comprising: receiving a plurality of candidate pieces of content; receiving a plurality of aggregated user activity streams, each aggregated user activity stream containing a record of at least one social activity performed by a user on a web page; extracting a plurality of topics from the plurality of aggregated user activity streams; calculating a velocity of each extracted topic based on a difference between a metric of the topic over a first period of time and a metric of the topic over a second period of time, wherein the second period of time came before the first period of time; calculating a trending score for each of the plurality of candidate pieces of content based on a measure of the velocities of one or more extracted topics contained in the candidate piece of content; ranking the plurality of candidate pieces of content based on the trending score; and publishing one or more of the plurality of candidate pieces of content based on the ranking. 18. The computer-readable storage medium of claim 15 , wherein the velocity of each topic is calculated based on an average of historical metrics taken over a plurality of related periods of time including particular hours of the day over one or more days, particular days of the week over one or more weeks, particular weeks of the year over one or more years, particular months of the year over one or more years, particular seasons of the year over one or more years, or particular holidays over one or more years.

9. The medical decision making support apparatus according to claim 4 , further comprising an evaluation unit configured to calculate an evaluation value for a highest posteriori probability of a plurality of posteriori probabilities calculated in association with the plurality of inference results, based on the plurality of posteriori probabilities, wherein the presentation unit presents a warning associated with reliability of an inference result when the evaluation value does not satisfy a predetermined condition.

9. The medical decision making support apparatus according to claim 4 , further comprising an evaluation unit configured to calculate an evaluation value for a highest posteriori probability of a plurality of posteriori probabilities calculated in association with the plurality of inference results, based on the plurality of posteriori probabilities, wherein the presentation unit presents a warning associated with reliability of an inference result when the evaluation value does not satisfy a predetermined condition. 11. The medical decision making support apparatus according to claim 9 , wherein the evaluation unit sets, as the evaluation value, a difference between a highest posteriori probability of the plurality of posteriori probabilities and a reciprocal of the number of the plurality of posteriori probabilities.

5. A computer-implemented method comprising: under control of one or more computer systems configured with executable instructions, obtaining image information using a camera of a computing device; identifying an event associated with the image information; analyzing text associated with the event using at least one of a computer vision algorithm or an optical character recognition algorithm to identify the text in the image information; determining at least one action available to a user, the action being related to the event; and causing the computing device to perform the at least one action related to the event.

5. A computer-implemented method comprising: under control of one or more computer systems configured with executable instructions, obtaining image information using a camera of a computing device; identifying an event associated with the image information; analyzing text associated with the event using at least one of a computer vision algorithm or an optical character recognition algorithm to identify the text in the image information; determining at least one action available to a user, the action being related to the event; and causing the computing device to perform the at least one action related to the event. 14. The computer-implemented method of claim 5 , further comprising: prompting a user to confirm intent to perform the at least one function.

14. A non-transitory computer readable medium comprising instructions encoded thereon for calculating a trust score, the instructions comprising: instructions for retrieving, from a first database using processing circuitry, first data associated with a first entity in a computer network; instructions for calculating a first component score based on the first data; instructions for retrieving, from a second database using the processing circuitry, second data associated with the first entity; instructions for calculating a second component score based on the second data; instructions for calculating a weighted combination of the first component score and the second component score to produce a trust score for the first entity; instructions for receiving, from a user device of a second entity in the computer network, data indicating an attribute associated with the first entity; instructions for recalculating the first component score based on the first data and the received data indicating the attribute associated with the first entity, wherein the instructions for recalculating the first component score comprise instructions for receiving improving the first component score by a predetermined amount; and instructions for updating the trust score for the first entity by calculating a weighted combination of the recalculated first component score and the second component score; instructions for receiving a request for the trust score for the first entity from a user device of a third entity in the computer network; instructions for retrieving, using the processing circuitry, data indicating paths in the computer network; and instructions for identifying, based on the retrieved data indicating paths in the computer network, a path connecting the third entity to the second entity in the computer network, the path comprising a number of links that is less than a threshold number of links.

14. A non-transitory computer readable medium comprising instructions encoded thereon for calculating a trust score, the instructions comprising: instructions for retrieving, from a first database using processing circuitry, first data associated with a first entity in a computer network; instructions for calculating a first component score based on the first data; instructions for retrieving, from a second database using the processing circuitry, second data associated with the first entity; instructions for calculating a second component score based on the second data; instructions for calculating a weighted combination of the first component score and the second component score to produce a trust score for the first entity; instructions for receiving, from a user device of a second entity in the computer network, data indicating an attribute associated with the first entity; instructions for recalculating the first component score based on the first data and the received data indicating the attribute associated with the first entity, wherein the instructions for recalculating the first component score comprise instructions for receiving improving the first component score by a predetermined amount; and instructions for updating the trust score for the first entity by calculating a weighted combination of the recalculated first component score and the second component score; instructions for receiving a request for the trust score for the first entity from a user device of a third entity in the computer network; instructions for retrieving, using the processing circuitry, data indicating paths in the computer network; and instructions for identifying, based on the retrieved data indicating paths in the computer network, a path connecting the third entity to the second entity in the computer network, the path comprising a number of links that is less than a threshold number of links. 15. The non-transitory computer readable medium of claim 14 , wherein the instructions for receiving, from the user device of the second entity, the data indicating an attribute associated with the first entity comprise instructions for receiving an indication of a user input from the second entity that validates the first data.

16. The system of claim 14 , comprising an action component operable to cause at least one action to be taken.

16. The system of claim 14 , comprising an action component operable to cause at least one action to be taken. 18. The system of claim 16 , wherein the at least one action is at least one signal transmitted to the at least one agent.

1. A method comprising: A processor examining graphic user interface (GUI) logic; identifying flaws in the logic that expose security damage; mapping a visual invariant to a program invariant; discovering inputs to the GUI logic that include a user action and an execution context to cause the program invariant to be violated; and uncovering browser address bar spoofing by examining for logic correctness as to navigation functionality that includes loading a new page, travelling back in the history log, and opening a new window.

1. A method comprising: A processor examining graphic user interface (GUI) logic; identifying flaws in the logic that expose security damage; mapping a visual invariant to a program invariant; discovering inputs to the GUI logic that include a user action and an execution context to cause the program invariant to be violated; and uncovering browser address bar spoofing by examining for logic correctness as to navigation functionality that includes loading a new page, travelling back in the history log, and opening a new window. 6. The method of claim 1 , wherein the flaws are directed to non browser applications.

7. A computer program product comprising a computer readable storage device having a computer program recorded therein, said computer program adapted to be executed on a processor of a computer system to perform a method for processing a user input character string entered by a user into the computer system, said computer system comprising a browser, said method comprising: receiving the user input character string, said user input character string conforming to a native character set and encoding of the browser for a language selected by the user; converting the user input character string to a converted character string consisting of characters of a Universal Character Set (UCS) which are independent of platform and language, wherein the converted character string comprises a plurality of leading whitespace characters, a plurality of trailing whitespace characters, and a middle character string comprising remaining whitespace characters that include at least one grouping of at least two consecutive whitespace characters, wherein the middle character string is disposed between the leading whitespace characters and the trailing whitespace characters, and wherein the leftmost character and the rightmost character of the middle character string are not whitespace characters; transforming the converted character string to a transformed character string by a first transformation or a second transformation, wherein said transforming the converted character string to the transformed character string by the first transformation comprises removing the leading whitespace characters and the trailing whitespace characters in the converted character string such that the transformed character string does not comprise any leading whitespace character, does not comprise any trailing whitespace character, and comprises the remaining whitespace characters; and wherein said transforming the converted character string to the transformed character string by the second transformation comprises removing the trailing whitespace characters in the converted character string such that the transformed character string does not comprise any trailing whitespace character and comprises both the leading whitespace characters and the remaining whitespace characters; and after said transforming, converting each grouping of the at least one grouping of at least two consecutive whitespace characters in the middle character string of the transformed character string to a single whitespace character, resulting in the transformed character string being converted to a resultant character string; wherein the method comprises modifying the user input character string to generate the resultant character string; wherein if said transforming consists of transforming the converted character string to the transformed character string by the first transformation, then said modifying consists of said converting the user input character string, said transforming the converted character string, and said converting each grouping; wherein if said transforming consists of transforming the converted character string to the transformed character string by the second transformation, then said modifying comprises said converting the user input character string, said transforming the converted character string, and said converting each grouping.

7. A computer program product comprising a computer readable storage device having a computer program recorded therein, said computer program adapted to be executed on a processor of a computer system to perform a method for processing a user input character string entered by a user into the computer system, said computer system comprising a browser, said method comprising: receiving the user input character string, said user input character string conforming to a native character set and encoding of the browser for a language selected by the user; converting the user input character string to a converted character string consisting of characters of a Universal Character Set (UCS) which are independent of platform and language, wherein the converted character string comprises a plurality of leading whitespace characters, a plurality of trailing whitespace characters, and a middle character string comprising remaining whitespace characters that include at least one grouping of at least two consecutive whitespace characters, wherein the middle character string is disposed between the leading whitespace characters and the trailing whitespace characters, and wherein the leftmost character and the rightmost character of the middle character string are not whitespace characters; transforming the converted character string to a transformed character string by a first transformation or a second transformation, wherein said transforming the converted character string to the transformed character string by the first transformation comprises removing the leading whitespace characters and the trailing whitespace characters in the converted character string such that the transformed character string does not comprise any leading whitespace character, does not comprise any trailing whitespace character, and comprises the remaining whitespace characters; and wherein said transforming the converted character string to the transformed character string by the second transformation comprises removing the trailing whitespace characters in the converted character string such that the transformed character string does not comprise any trailing whitespace character and comprises both the leading whitespace characters and the remaining whitespace characters; and after said transforming, converting each grouping of the at least one grouping of at least two consecutive whitespace characters in the middle character string of the transformed character string to a single whitespace character, resulting in the transformed character string being converted to a resultant character string; wherein the method comprises modifying the user input character string to generate the resultant character string; wherein if said transforming consists of transforming the converted character string to the transformed character string by the first transformation, then said modifying consists of said converting the user input character string, said transforming the converted character string, and said converting each grouping; wherein if said transforming consists of transforming the converted character string to the transformed character string by the second transformation, then said modifying comprises said converting the user input character string, said transforming the converted character string, and said converting each grouping. 10. The computer program product of claim 7 , wherein the user input character string is a null character string.