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5. The method of claim 4 further including controlling the device combinations to perform the selected user task suggestion.

5. The method of claim 4 further including controlling the device combinations to perform the selected user task suggestion. 6. The method of claim 5 , wherein a task suggestion is represented using a language structure organized as a set of terms to describe user tasks as abstractions of the obtained device function descriptions and task descriptions.

1. A data storage system comprising: a computing system comprising one or more hardware processors programmed to: detect a file interaction event with respect to a file on a storage device; responsive to detecting the file interaction event with respect to the file, access an encryption rule, the encryption rule including a set of rules for determining whether to encrypt files based on a set of context conditions, the set of context conditions including a geographic context; determine a set of data tokens for the file, each of the data tokens comprising a portion of content of the file; apply the encryption rule to the set of data tokens to determine whether the file includes content designated for protection, wherein application of the encryption rule includes: determining whether one or more data tokens from the set of data tokens satisfy the encryption rule; and ceasing said determining whether the one or more data tokens from the set of data tokens satisfy the encryption rule upon identification of a threshold number of data tokens satisfying the encryption rule regardless of whether each data token from the set of data tokens has been processed to determine whether it satisfies the encryption rule; responsive to determining that the file includes content designated for protection: determine a geographic location of the storage device; determine whether the geographic location of the storage device satisfies the geographic context for encrypting the file; and responsive to the geographic location of the storage device satisfying the geographic context, encrypting the file; and responsive to an indication that the file does not include content designated for protection: include the file with a set of training files used to generate one or more encryption rules; and modify the encryption rule based at least in part on the set of training files and the file.

1. A data storage system comprising: a computing system comprising one or more hardware processors programmed to: detect a file interaction event with respect to a file on a storage device; responsive to detecting the file interaction event with respect to the file, access an encryption rule, the encryption rule including a set of rules for determining whether to encrypt files based on a set of context conditions, the set of context conditions including a geographic context; determine a set of data tokens for the file, each of the data tokens comprising a portion of content of the file; apply the encryption rule to the set of data tokens to determine whether the file includes content designated for protection, wherein application of the encryption rule includes: determining whether one or more data tokens from the set of data tokens satisfy the encryption rule; and ceasing said determining whether the one or more data tokens from the set of data tokens satisfy the encryption rule upon identification of a threshold number of data tokens satisfying the encryption rule regardless of whether each data token from the set of data tokens has been processed to determine whether it satisfies the encryption rule; responsive to determining that the file includes content designated for protection: determine a geographic location of the storage device; determine whether the geographic location of the storage device satisfies the geographic context for encrypting the file; and responsive to the geographic location of the storage device satisfying the geographic context, encrypting the file; and responsive to an indication that the file does not include content designated for protection: include the file with a set of training files used to generate one or more encryption rules; and modify the encryption rule based at least in part on the set of training files and the file. 5. The data storage system of claim 1 , wherein determining whether the geographic location of the storage device satisfies the geographic context comprises determining whether the storage device is external to a particular geographic area.

51. A system for managing active fonts on a computer system, comprising: an input for receiving input data requesting activation of a first font for rendering a first portion of an electronic document and a second font for rendering a second portion of the electronic document; and a processor system programmed and adapted to: (a) determine that the first font and the second font do not exist in a font management vault, (b) upon determining that the first font does not exist in the font management vault: (i) identify the first font in a first multi-font suitcase file of a first plurality of multi-font suitcase files, each multi-font suitcase file of the first plurality including a similarly named version of the first font, (ii) separate the first font from the first multi-font suitcase file, and (iii) save the separated first font in the font management vault, and (c) upon determining that the second font does not exist in the font management vault: (i) identify the second font in a second multi-font suitcase file, (ii) separate the second font from the second multi-font suitcase file, and (iii) save the separated second font in the font management vault.

51. A system for managing active fonts on a computer system, comprising: an input for receiving input data requesting activation of a first font for rendering a first portion of an electronic document and a second font for rendering a second portion of the electronic document; and a processor system programmed and adapted to: (a) determine that the first font and the second font do not exist in a font management vault, (b) upon determining that the first font does not exist in the font management vault: (i) identify the first font in a first multi-font suitcase file of a first plurality of multi-font suitcase files, each multi-font suitcase file of the first plurality including a similarly named version of the first font, (ii) separate the first font from the first multi-font suitcase file, and (iii) save the separated first font in the font management vault, and (c) upon determining that the second font does not exist in the font management vault: (i) identify the second font in a second multi-font suitcase file, (ii) separate the second font from the second multi-font suitcase file, and (iii) save the separated second font in the font management vault. 52. A system according to claim 51 , wherein the processor system is further programmed and adapted to activate the first font and the second font from the font management vault.

7. A method for handling a free text search query, comprising: enabling a particular grid component within a grid environment, wherein the grid environment comprises a plurality of computing systems each comprising at least one resource communicatively connected over a network to share each said at least one resource through a plurality of web services implemented within a web services layer extended by an open grid services infrastructure atop a grid service layer comprising at least one grid service implemented within the open grid services architecture enabling interfacing with each at least one resource, wherein the particular grid component comprises at least one of said at least one resource; specifying, using a processor, the particular grid component to interpret a meaning of a particular aspect of at least one of a plurality of specifications within at least one search query distributed by at least one search service from among the at least one grid service; responsive to receiving a free text string with a particular plurality of specifications for a particular search query from the at least one search service, interpreting, using the processor, by the particular component the meaning of the particular aspect of at least one specification within the particular plurality of specifications within the free text string; and returning, using the processor, from the particular grid component the interpreted meaning to the search service to synthesize with other interpreted meanings for other aspects of the free text string returned to the search service by other grid components from among the plurality of grid components.

7. A method for handling a free text search query, comprising: enabling a particular grid component within a grid environment, wherein the grid environment comprises a plurality of computing systems each comprising at least one resource communicatively connected over a network to share each said at least one resource through a plurality of web services implemented within a web services layer extended by an open grid services infrastructure atop a grid service layer comprising at least one grid service implemented within the open grid services architecture enabling interfacing with each at least one resource, wherein the particular grid component comprises at least one of said at least one resource; specifying, using a processor, the particular grid component to interpret a meaning of a particular aspect of at least one of a plurality of specifications within at least one search query distributed by at least one search service from among the at least one grid service; responsive to receiving a free text string with a particular plurality of specifications for a particular search query from the at least one search service, interpreting, using the processor, by the particular component the meaning of the particular aspect of at least one specification within the particular plurality of specifications within the free text string; and returning, using the processor, from the particular grid component the interpreted meaning to the search service to synthesize with other interpreted meanings for other aspects of the free text string returned to the search service by other grid components from among the plurality of grid components. 11. The method according to claim 7 , wherein interpreting by the particular component the meaning of the particular aspect of at least one specification within the particular plurality of specifications within the free text string further comprises receiving at the particular grid component the free text string of the particular search query comprising a plurality of specifications which are interpretable for a plurality of separate aspects, wherein one of the plurality of specifications is interpretable according to the particular aspect of the particular grid component.

15. A computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for constructing a model that generates text, the method comprising: representing a concept as a cluster node; representing a word as a terminal node; assigning a weight to a link between two nodes; and training the model based on a set of documents, comprising: for each cluster node, computing a probabilistic cost of a corresponding concept existing in a document but not triggering any words.

15. A computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for constructing a model that generates text, the method comprising: representing a concept as a cluster node; representing a word as a terminal node; assigning a weight to a link between two nodes; and training the model based on a set of documents, comprising: for each cluster node, computing a probabilistic cost of a corresponding concept existing in a document but not triggering any words. 26. The computer-readable storage medium of claim 15 , wherein the concept represents conceptually related words.

1. A system for an autonomous vehicle comprising: two or more microphones mounted to the autonomous vehicle; a controller executing a pre-processor programmed to detect audio features in two or more audio streams from the two or more microphones; a collision avoidance module programmed to classify the audio features and a direction to a source thereof, and, if the class for the sound source is a vehicle, invoke obstacle avoidance with respect to the direction; wherein the collision avoidance module is further programmed to: classify the audio features by inputting the audio features into a machine learning model; and wherein the machine-learning model outputs a confidence value indicating a probability that the audio features correspond to a vehicle.

1. A system for an autonomous vehicle comprising: two or more microphones mounted to the autonomous vehicle; a controller executing a pre-processor programmed to detect audio features in two or more audio streams from the two or more microphones; a collision avoidance module programmed to classify the audio features and a direction to a source thereof, and, if the class for the sound source is a vehicle, invoke obstacle avoidance with respect to the direction; wherein the collision avoidance module is further programmed to: classify the audio features by inputting the audio features into a machine learning model; and wherein the machine-learning model outputs a confidence value indicating a probability that the audio features correspond to a vehicle. 5. The system of claim 1 , wherein the collision avoidance module is further programmed to identify the audio features by filtering the two or more audio streams to obtain two or more filtered signals each including one or more of the audible features.

18. The computer-readable storage medium of claim 14 , wherein the plurality of predicates includes a derivation predicate that analyzes inheritance relationships between classes.

18. The computer-readable storage medium of claim 14 , wherein the plurality of predicates includes a derivation predicate that analyzes inheritance relationships between classes. 19. The computer-readable storage medium of claim 18 , wherein the derivation predicate determines whether given nodes of the input AST correspond to a first class that inherits from a second class supplied as an argument to the derivation predicate.

1. A computer-implemented method for dynamically adapting metadata for use with a native data encoding, the computer-implemented method being performed by one or more processors executing computer executable instructions for the computer-implemented method, and the computer-implemented method comprising acts of: accessing one or more portions of metadata in a file containing an object model description of an object model, the metadata comprising metadata represented in an encoding that is expected by a metadata reader configured to read native metadata; determining that at least some of the one or more portions of the accessed metadata are encoded in a non-native encoding; determining one or more metadata modifications required to transform the non-native encoding into native encoding for the at least some of the one or more portions of the accessed metadata; and adapting the accessed portions of metadata from non-native encoding to native encoding according to the determined one or more modifications, such that the native and non-native encodings of the accessed portions of the metadata are contained in the file containing the object model descriptions for the object model, and such that the object model is readable by a native runtime.

1. A computer-implemented method for dynamically adapting metadata for use with a native data encoding, the computer-implemented method being performed by one or more processors executing computer executable instructions for the computer-implemented method, and the computer-implemented method comprising acts of: accessing one or more portions of metadata in a file containing an object model description of an object model, the metadata comprising metadata represented in an encoding that is expected by a metadata reader configured to read native metadata; determining that at least some of the one or more portions of the accessed metadata are encoded in a non-native encoding; determining one or more metadata modifications required to transform the non-native encoding into native encoding for the at least some of the one or more portions of the accessed metadata; and adapting the accessed portions of metadata from non-native encoding to native encoding according to the determined one or more modifications, such that the native and non-native encodings of the accessed portions of the metadata are contained in the file containing the object model descriptions for the object model, and such that the object model is readable by a native runtime. 12. The computer-implemented method of claim 1 , wherein adapting the accessed portions of metadata from non-native encoding to native encoding comprises modifying types referenced by the non-native encoding to be types used by the native encoding.

9. The apparatus of claim 8 , wherein the determining a preferred language comprises accessing a client processing device associated with the second user.

9. The apparatus of claim 8 , wherein the determining a preferred language comprises accessing a client processing device associated with the second user. 10. The apparatus of claim 9 , further comprising: outputting the electronic message in the preferred language for display in a transcript window associated with the second user.

1. A computer-implemented method of managing perspective data associated with a common feature in items, the method comprising: identifying, by a processor and via a scan of stored data, a common feature in a first item and a second item, the first item having a set of perspective data, the common feature relating a component of the first item with a component of the second item, and wherein the identifying includes: parsing, using a natural language processing technique configured to analyze semantic and syntactic content, a set of description data associated with the first and second items; determining, in response to parsing the set of description data, a set of shared characteristics in the set of description data; and selecting, from the set of shared characteristics, at least one feature as the common feature; establishing a subset of perspective data associated with the common feature; and associating the subset of perspective data with the second item.

1. A computer-implemented method of managing perspective data associated with a common feature in items, the method comprising: identifying, by a processor and via a scan of stored data, a common feature in a first item and a second item, the first item having a set of perspective data, the common feature relating a component of the first item with a component of the second item, and wherein the identifying includes: parsing, using a natural language processing technique configured to analyze semantic and syntactic content, a set of description data associated with the first and second items; determining, in response to parsing the set of description data, a set of shared characteristics in the set of description data; and selecting, from the set of shared characteristics, at least one feature as the common feature; establishing a subset of perspective data associated with the common feature; and associating the subset of perspective data with the second item. 2. The method of claim 1 , further comprising: determining a set of relevancy scores for the subset of perspective data associated with the common feature; establishing a set of relevant perspective data from the subset of perspective data, the set of relevant perspective data having relevancy scores outside of a relevancy threshold; and associating the set of relevant perspective data with the second item.

1. A computer-readable memory containing therein instructions that, when executed, generate on a display device a graphical user interface (GUI) for creating or revising a rule that contains multiple conditions and an action to be taken when the conditions are satisfied, the GUI comprising: first and second user-selectable elements; a rule-editing area that is configured to: (i) display, upon user selection of the first element, a condition input field set for accepting a first user specification of: (a) an attribute name for each of the conditions, (b) an attribute value for each of the conditions, and (c) a choice between an “and” logical operator and an “or” logical operator for logically connecting two or more of the conditions, wherein the condition input field set accepts user selection of the attribute name for each of the conditions from a list of options for the attribute name for each of the conditions and further accepts user input of text for the attribute value for each of the conditions, wherein, after the first user specification, the rule-editing area displays a user-specified attribute name and attribute value for each of the conditions while the condition input field set is displayed, and (ii) display, upon user selection of the second element, an action input field set for accepting a second user specification of: (d) an action name identifying the action, and (e) an action value for the action, wherein the action input field accepts user selection of the action name from a list of options for the action name and further accepts user input of text for the action value, wherein, after the second user specification, the rule-editing area displays a user-specified action name and action value while the action input field set is displayed, and wherein the condition input field set and the action input field set are not displayed concurrently with each other; and a rule preview area configured to provide, after the first and second user specifications, a display of a user-understandable representation of the rule comprising both the conditions and the action, the rule preview area being displayed both while the condition input field set is displayed and while the action input field set is displayed, the user-understandable representation including at least the user-specified attribute name and attribute value for each of the conditions after the first user specification, and including at least the user-specified action name and action value for the action after the second user specification.

1. A computer-readable memory containing therein instructions that, when executed, generate on a display device a graphical user interface (GUI) for creating or revising a rule that contains multiple conditions and an action to be taken when the conditions are satisfied, the GUI comprising: first and second user-selectable elements; a rule-editing area that is configured to: (i) display, upon user selection of the first element, a condition input field set for accepting a first user specification of: (a) an attribute name for each of the conditions, (b) an attribute value for each of the conditions, and (c) a choice between an “and” logical operator and an “or” logical operator for logically connecting two or more of the conditions, wherein the condition input field set accepts user selection of the attribute name for each of the conditions from a list of options for the attribute name for each of the conditions and further accepts user input of text for the attribute value for each of the conditions, wherein, after the first user specification, the rule-editing area displays a user-specified attribute name and attribute value for each of the conditions while the condition input field set is displayed, and (ii) display, upon user selection of the second element, an action input field set for accepting a second user specification of: (d) an action name identifying the action, and (e) an action value for the action, wherein the action input field accepts user selection of the action name from a list of options for the action name and further accepts user input of text for the action value, wherein, after the second user specification, the rule-editing area displays a user-specified action name and action value while the action input field set is displayed, and wherein the condition input field set and the action input field set are not displayed concurrently with each other; and a rule preview area configured to provide, after the first and second user specifications, a display of a user-understandable representation of the rule comprising both the conditions and the action, the rule preview area being displayed both while the condition input field set is displayed and while the action input field set is displayed, the user-understandable representation including at least the user-specified attribute name and attribute value for each of the conditions after the first user specification, and including at least the user-specified action name and action value for the action after the second user specification. 5. The computer-readable memory of claim 1 , wherein the rule-editing area contains, for each particular condition of the multiple conditions: a first menu having a set of user-selectable options for determining the attribute name of the particular condition; a second menu having a set of user-selectable options for determining the operator of the particular condition; and a text-entry field to accept user input for determining the attribute value of the particular condition.

15. A system comprising: a processor coupled to a memory, the processor being configured to: generate a first address string based on a set of attributes of a first object included in a database of the memory and a set of attributes of a second object included in the database, the set of attributes of the first object containing the second object and the set of attributes of the second object referencing a third object, the first address string indicating, based on the set of attributes of the first object containing the second object, a first relationship that deletion of the first object from the database requires also deleting the second object, the first address string also indicating, based on the set of attributes of the second object referencing the third object, a second relationship that deletion of the second object from the database does not require deleting the third object; store the first object in a first location in an object storage area associated with the database; store the second object in a second location in the object storage area, the second location being based on the first relationship indicated by the first address string; store the third object in a third location in the object storage area, the third location being based on the second relationship indicated by the first address string; and store the first address string in an address string storage area associated with the database in association with the first object, the first address string including a first indicator of the first location, a second indicator of the second location, and a third indicator of the third location.

15. A system comprising: a processor coupled to a memory, the processor being configured to: generate a first address string based on a set of attributes of a first object included in a database of the memory and a set of attributes of a second object included in the database, the set of attributes of the first object containing the second object and the set of attributes of the second object referencing a third object, the first address string indicating, based on the set of attributes of the first object containing the second object, a first relationship that deletion of the first object from the database requires also deleting the second object, the first address string also indicating, based on the set of attributes of the second object referencing the third object, a second relationship that deletion of the second object from the database does not require deleting the third object; store the first object in a first location in an object storage area associated with the database; store the second object in a second location in the object storage area, the second location being based on the first relationship indicated by the first address string; store the third object in a third location in the object storage area, the third location being based on the second relationship indicated by the first address string; and store the first address string in an address string storage area associated with the database in association with the first object, the first address string including a first indicator of the first location, a second indicator of the second location, and a third indicator of the third location. 17. The system of claim 15 wherein the processor is configured to parse the first address string to determine a first relational path between the first object, the second object, and the third object.

6. The method of claim 1 , wherein: the selecting content further comprises using demographic data associated with the determined first one of the geographic features, and the corresponding keyword mapping for the determined first one of the geographic features is based on demographic data of the user.

6. The method of claim 1 , wherein: the selecting content further comprises using demographic data associated with the determined first one of the geographic features, and the corresponding keyword mapping for the determined first one of the geographic features is based on demographic data of the user. 7. The method of claim 6 , wherein greater weight is assigned to location keywords in the corresponding keyword mapping that are associated with demographic data similar to the demographic data of the user.

14. The method of claim 1 wherein computing the anatomical similarity scores between the subject image and the exemplar images based on the first and second landmarks comprises: calculating distances between corresponding first landmarks in the subject image and second landmarks in each exemplar image; and calculating the anatomic similarity score of each exemplar image based on the distances.

14. The method of claim 1 wherein computing the anatomical similarity scores between the subject image and the exemplar images based on the first and second landmarks comprises: calculating distances between corresponding first landmarks in the subject image and second landmarks in each exemplar image; and calculating the anatomic similarity score of each exemplar image based on the distances. 16. The method of claim 14 further comprising removing outlier distances from computation prior to calculating the anatomical similarity score of each exemplar image.

5. The user device of claim 1 , further comprising an input guide coupled over a portion of the touch screen having first physical portions corresponding to the location of the input regions and second physical portions corresponding to the location of the input region boundaries, and wherein the first and second physical portions have different physical characteristics.

5. The user device of claim 1 , further comprising an input guide coupled over a portion of the touch screen having first physical portions corresponding to the location of the input regions and second physical portions corresponding to the location of the input region boundaries, and wherein the first and second physical portions have different physical characteristics. 6. The user device of claim 5 , wherein the input guide is a planar sheet of transparent material.

23. The system of claim 15 , said program code further comprising: program code for monitoring user behavior to determine at least one use pattern; and program code for adjusting a time remaining of said content item idle timers responsive, at least in part, to said at least one use pattern.

23. The system of claim 15 , said program code further comprising: program code for monitoring user behavior to determine at least one use pattern; and program code for adjusting a time remaining of said content item idle timers responsive, at least in part, to said at least one use pattern. 24. The system of claim 23 , wherein said at least one use pattern comprises an average time between user operations.

10. The computationally-implemented method of claim 1 , wherein said facilitating acquisition of adaptation result data that is based on at least one aspect of the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data comprises: generating adaptation result data that is based on at least one aspect of the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data.

10. The computationally-implemented method of claim 1 , wherein said facilitating acquisition of adaptation result data that is based on at least one aspect of the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data comprises: generating adaptation result data that is based on at least one aspect of the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data. 11. The computationally-implemented method of claim 10 , wherein said generating adaptation result data that is based on at least one aspect of the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data comprises: generating adaptation result data that is based on a result of the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data.

1. A computer network implementable method for synthesizing relevant messaging from one or more domains of information, underpinned by non-promoted content, using a consumer-generated context, the method comprising: obtaining non-promoted content and linking the non-promoted content to at least one promoter; receiving advertising material from the at least one promoter; receiving a consumer-generated context; and semantically analyzing and synthesizing, or facilitating the semantic analysis and synthesis of, by one or more computer processors, relevant messaging based on the non-promoted content and the consumer-generated context, wherein the relevant messaging is traceable to the at least one promoter, the synthesizing comprising: deconstructing the advertising material received from the at least one promoter into a plurality of messaging leads; and selecting at least some of the plurality of messaging leads and assembling the selected messaging leads into a message based on the consumer-generated context, the message having relevant non-promoted content interspersed between the selected messaging leads from the received advertising material.

1. A computer network implementable method for synthesizing relevant messaging from one or more domains of information, underpinned by non-promoted content, using a consumer-generated context, the method comprising: obtaining non-promoted content and linking the non-promoted content to at least one promoter; receiving advertising material from the at least one promoter; receiving a consumer-generated context; and semantically analyzing and synthesizing, or facilitating the semantic analysis and synthesis of, by one or more computer processors, relevant messaging based on the non-promoted content and the consumer-generated context, wherein the relevant messaging is traceable to the at least one promoter, the synthesizing comprising: deconstructing the advertising material received from the at least one promoter into a plurality of messaging leads; and selecting at least some of the plurality of messaging leads and assembling the selected messaging leads into a message based on the consumer-generated context, the message having relevant non-promoted content interspersed between the selected messaging leads from the received advertising material. 5. The method of claim 1 , wherein the messaging is synthesized from a randomly selected subset of the selected domains.

5. A non-transitory computer readable medium having stored thereon a set of data operable to configure a computer to perform a set of tasks comprising: a) receiving an input string, the input string comprising a plurality of words; b) determining a division for the input string, wherein the division comprises a set of word groups, wherein each word from the plurality of words is a member of exactly one word group from the set of word groups; and c) determining a set of parts of speech, wherein: 1) cardinality for the set of parts of speech and the set of word groups is identical; 2) each part of speech from the set of parts of speech is associated with a single word group from the set of word groups; 3) each part of speech from the set of parts of speech is selected from a plurality of parts of speech, the plurality of parts of speech comprising an invented part of speech; 4) the task of determining the set of parts of speech is performed based on: i) a set of probabilities, the set of probabilities comprising, for each part of speech from the plurality of parts of speech, a probability that the part of speech is followed by a second part of speech; ii) a first rule varying likelihood of the invented part of speech based on string position; iii) a second rule decreasing likelihood of a plurality of instances of the invented part of speech in the set of parts of speech.

5. A non-transitory computer readable medium having stored thereon a set of data operable to configure a computer to perform a set of tasks comprising: a) receiving an input string, the input string comprising a plurality of words; b) determining a division for the input string, wherein the division comprises a set of word groups, wherein each word from the plurality of words is a member of exactly one word group from the set of word groups; and c) determining a set of parts of speech, wherein: 1) cardinality for the set of parts of speech and the set of word groups is identical; 2) each part of speech from the set of parts of speech is associated with a single word group from the set of word groups; 3) each part of speech from the set of parts of speech is selected from a plurality of parts of speech, the plurality of parts of speech comprising an invented part of speech; 4) the task of determining the set of parts of speech is performed based on: i) a set of probabilities, the set of probabilities comprising, for each part of speech from the plurality of parts of speech, a probability that the part of speech is followed by a second part of speech; ii) a first rule varying likelihood of the invented part of speech based on string position; iii) a second rule decreasing likelihood of a plurality of instances of the invented part of speech in the set of parts of speech. 8. The non-transitory computer readable medium of claim 5 , wherein the second rule increases the likelihood of there being only one instance of the invented part of speech in the set of parts of speech.

1. An auditory prosthesis system, comprising: an implantable auditory prostheses configured to deliver stimulation signals to a recipient; and an external device comprising: an interface configured to communicate with the implantable auditory prostheses; a display screen, and at least one processor configured to: provide received speech signals to the implantable auditory prostheses for use in delivering stimulation signals representative of the received speech signals to the recipient, display, at the display screen, a graphical representation comprising a humanoid avatar that includes at least head, neck, and shoulder features, wherein the humanoid avatar is configured to enable the recipient to compensate for reduced tonal perception associated with delivery to the recipient of the stimulation signals representative of the received speech signals, analyze the received speech signals to detect an emotion of a speaker of the received speech signals, and animate one or more features of the avatar based on the received speech signals to convey the emotion to the recipient.

1. An auditory prosthesis system, comprising: an implantable auditory prostheses configured to deliver stimulation signals to a recipient; and an external device comprising: an interface configured to communicate with the implantable auditory prostheses; a display screen, and at least one processor configured to: provide received speech signals to the implantable auditory prostheses for use in delivering stimulation signals representative of the received speech signals to the recipient, display, at the display screen, a graphical representation comprising a humanoid avatar that includes at least head, neck, and shoulder features, wherein the humanoid avatar is configured to enable the recipient to compensate for reduced tonal perception associated with delivery to the recipient of the stimulation signals representative of the received speech signals, analyze the received speech signals to detect an emotion of a speaker of the received speech signals, and animate one or more features of the avatar based on the received speech signals to convey the emotion to the recipient. 3. The auditory prosthesis system of claim 1 , wherein the avatar includes a mouth region and wherein the processor is configured to generate movement of the mouth region of the avatar that emulates vocal articulator movements of a speaker of the received speech signals.

13. The method of claim 1 , wherein each respective entity tuple in the output list is accompanied by a listing of a subset of the plurality of documents, from which that entity tuple is identified.

13. The method of claim 1 , wherein each respective entity tuple in the output list is accompanied by a listing of a subset of the plurality of documents, from which that entity tuple is identified. 15. The method of claim 13 , wherein: the plurality of documents are stored in a plurality of computers accessed by way of a network using uniform resource identifiers, and for each respective entity tuple, the list includes the respective uniform resource identifiers for each respective document in the subset of the plurality of documents.

1. A computer-implemented system for displaying clusters via a dynamic user interface, comprising: a cluster spine module to display cluster spines, each comprising two or more clusters of documents; a compass framing at least a portion of one or more of the cluster spines in the display; a label generation module to generate at least one label to identify a concept of one of the framed cluster spines; a label display module to display the label circumferentially around the compass; and a concept module to change the concept as the compass moves over others of the cluster spines.

1. A computer-implemented system for displaying clusters via a dynamic user interface, comprising: a cluster spine module to display cluster spines, each comprising two or more clusters of documents; a compass framing at least a portion of one or more of the cluster spines in the display; a label generation module to generate at least one label to identify a concept of one of the framed cluster spines; a label display module to display the label circumferentially around the compass; and a concept module to change the concept as the compass moves over others of the cluster spines. 10. A system according to claim 1 , further comprising: a placement module to place at least a portion of the cluster spines circumferentially around a circle in a display.

31. One or more non-transitory computer-readable storage media, storing software instructions, which when executed by one or more processors cause performance of: creating two or more sets of field searchable, time stamped event records from raw data stored in at least one data store, wherein each set of field searchable, time stamped event records among the two or more sets of field searchable, time stamped event records comprises field searchable, time stamped event records having time stamps that fall within a time range, the time range different than time ranges associated with other sets of field searchable, time stamped event records among the two or more sets of field searchable, time stamped event records, wherein each field searchable, time stamped event record in the two or more sets of field searchable, time stamped event records includes a portion of the raw data and is associated with a time stamp derived from the raw data, wherein the raw data reflects activity in an information technology environment; generating a summarization table for each set of field searchable, time stamped event records in the two or more sets of field searchable, time stamped event records that: identifies one or more field values, wherein a field value comprises a value that appears in an associated field in one or more field searchable, time stamped event records in the set of field searchable, time stamped event records; and for each field value, includes a posting value to the one or more field searchable, time stamped event records in the set of field searchable, time stamped event records that contain the field value for the associated field; storing the summarization table for each set of field searchable, time stamped event records among the two or more sets of time stamped field searchable event records; selecting a stored summarization table based on a received query that includes search criteria for evaluating field values for one or more fields; using the search criteria to evaluate field values for one or more fields in the selected summarization table to generate a query result; and wherein the query result reflects an aspect of activity in the information technology environment.

31. One or more non-transitory computer-readable storage media, storing software instructions, which when executed by one or more processors cause performance of: creating two or more sets of field searchable, time stamped event records from raw data stored in at least one data store, wherein each set of field searchable, time stamped event records among the two or more sets of field searchable, time stamped event records comprises field searchable, time stamped event records having time stamps that fall within a time range, the time range different than time ranges associated with other sets of field searchable, time stamped event records among the two or more sets of field searchable, time stamped event records, wherein each field searchable, time stamped event record in the two or more sets of field searchable, time stamped event records includes a portion of the raw data and is associated with a time stamp derived from the raw data, wherein the raw data reflects activity in an information technology environment; generating a summarization table for each set of field searchable, time stamped event records in the two or more sets of field searchable, time stamped event records that: identifies one or more field values, wherein a field value comprises a value that appears in an associated field in one or more field searchable, time stamped event records in the set of field searchable, time stamped event records; and for each field value, includes a posting value to the one or more field searchable, time stamped event records in the set of field searchable, time stamped event records that contain the field value for the associated field; storing the summarization table for each set of field searchable, time stamped event records among the two or more sets of time stamped field searchable event records; selecting a stored summarization table based on a received query that includes search criteria for evaluating field values for one or more fields; using the search criteria to evaluate field values for one or more fields in the selected summarization table to generate a query result; and wherein the query result reflects an aspect of activity in the information technology environment. 45. The one or more non-transitory computer-readable storage media of claim 31 , wherein the summarization table for each set of field searchable, time stamped event records in the one or more sets of field searchable, time stamped event records includes two or more table portions, and wherein each of the two or more table portions is stored in a location associated with a subset of the event records to which a respective table portion pertains.

3. The system of claim 1 , wherein the snippets include metadata associated with their respective source electronic documents.

3. The system of claim 1 , wherein the snippets include metadata associated with their respective source electronic documents. 6. The system of claim 3 , wherein the metadata included in the snippets includes document numbers associated with the source electronic documents.

1. An information processing apparatus comprising: a processor configured to function as: an acquiring unit that acquires, for a plurality of documents, candidates for elements representing characteristics of each of the plurality of documents; an extraction unit that extracts, from the candidates acquired by the acquiring unit, common elements common to two or more of the plurality of documents; a selection unit that extracts, from the plurality of documents, a document including two or more common elements among the common elements, and determines the two or more common elements included in the extracted document to be elements representing characteristics of the document; a first acquiring unit that acquires, for each of the plurality of documents, a first group of elements included in a first image generated by reading the document; an addition unit that generates a plurality of second images by adding noises that differ from each other to the first image; a second acquiring unit that acquires second groups of elements included in the plurality of respective second images; and a first extraction unit that extracts, from the first group of elements, candidates for elements representing characteristics of the document in accordance with degrees of similarity between elements included in the first group of elements and elements included in the second groups of elements.

1. An information processing apparatus comprising: a processor configured to function as: an acquiring unit that acquires, for a plurality of documents, candidates for elements representing characteristics of each of the plurality of documents; an extraction unit that extracts, from the candidates acquired by the acquiring unit, common elements common to two or more of the plurality of documents; a selection unit that extracts, from the plurality of documents, a document including two or more common elements among the common elements, and determines the two or more common elements included in the extracted document to be elements representing characteristics of the document; a first acquiring unit that acquires, for each of the plurality of documents, a first group of elements included in a first image generated by reading the document; an addition unit that generates a plurality of second images by adding noises that differ from each other to the first image; a second acquiring unit that acquires second groups of elements included in the plurality of respective second images; and a first extraction unit that extracts, from the first group of elements, candidates for elements representing characteristics of the document in accordance with degrees of similarity between elements included in the first group of elements and elements included in the second groups of elements. 2. The information processing apparatus according to claim 1 , wherein the acquiring unit acquires the candidates extracted by the first extraction unit.

1. A method for enabling social network interaction via a graphical user interface comprising search results, the graphical user interface being physically generated on a hardware display device by a computing device, the method comprising the steps of: generating, in the graphical user interface, a presentation of multiple document search results identifying a first set of documents responsive to a user's search; generating, in the graphical user interface, a presentation of an identification of a first individual responsive to the user's search, the first individual being associated with the user via an external social networking service; receiving, via the graphical user interface, user-authored content to be directed to the social networking service; including, as part of the user-authored content, a search context utilizable by recipients of the search context to subsequently perform, after receiving the search context, an equivalent search to the user's search and receive identical document search results to the multiple document search results presented to the user; including, as part of the user-authored content, a further search context comprising at least one of the multiple document search results; submitting the user-authored content to the social networking service to be included in a social networking context of the user; and generating, for at least some of the multiple document search results, individual selection elements by which the user can specify the inclusion of individual ones of the multiple document search results in the user-authored content.

1. A method for enabling social network interaction via a graphical user interface comprising search results, the graphical user interface being physically generated on a hardware display device by a computing device, the method comprising the steps of: generating, in the graphical user interface, a presentation of multiple document search results identifying a first set of documents responsive to a user's search; generating, in the graphical user interface, a presentation of an identification of a first individual responsive to the user's search, the first individual being associated with the user via an external social networking service; receiving, via the graphical user interface, user-authored content to be directed to the social networking service; including, as part of the user-authored content, a search context utilizable by recipients of the search context to subsequently perform, after receiving the search context, an equivalent search to the user's search and receive identical document search results to the multiple document search results presented to the user; including, as part of the user-authored content, a further search context comprising at least one of the multiple document search results; submitting the user-authored content to the social networking service to be included in a social networking context of the user; and generating, for at least some of the multiple document search results, individual selection elements by which the user can specify the inclusion of individual ones of the multiple document search results in the user-authored content. 3. The method of claim 1 , further comprising the steps of: removing the generated individual selection elements if a user action causes a user-authored content entry area to no longer be displayed.

8. A computer-implemented method comprising: rendering one or more pages; presenting a user interface for a search tool that enables a user to select to perform a syntactically similar search on the one or more rendered pages for a search term that the user enters, the user interface for the search tool having multiple selectable options to selectively designate performance of one or both of the synonym search or a syntactically similar search according to the search term; receiving, via the user interface, a search term entered by the user; exposing an option via the user interface to select one or more contextual choices associated with the search term entered by the user; ascertaining at least syntactically similar words relative to the search term entered by the user in accordance with a selection made via the multiple selectable options; conducting a local search by traversing the one or more rendered pages looking for exact matches for the search term and for syntactically similar words for the search term in accordance with one or more contextual choices made via the exposed option; and for words that constitute an exact match or a syntactically similar word, displaying said words for the user in context within the one or more rendered pages.

8. A computer-implemented method comprising: rendering one or more pages; presenting a user interface for a search tool that enables a user to select to perform a syntactically similar search on the one or more rendered pages for a search term that the user enters, the user interface for the search tool having multiple selectable options to selectively designate performance of one or both of the synonym search or a syntactically similar search according to the search term; receiving, via the user interface, a search term entered by the user; exposing an option via the user interface to select one or more contextual choices associated with the search term entered by the user; ascertaining at least syntactically similar words relative to the search term entered by the user in accordance with a selection made via the multiple selectable options; conducting a local search by traversing the one or more rendered pages looking for exact matches for the search term and for syntactically similar words for the search term in accordance with one or more contextual choices made via the exposed option; and for words that constitute an exact match or a syntactically similar word, displaying said words for the user in context within the one or more rendered pages. 14. The method of claim 8 , wherein syntactically similar words comprise words that are spelled differently.

1. A method for building a rule that specifies an action that may occur during execution of an application, the method comprising: storing in a computer memory an expression editor tool; reading, with a processor, an action point definition from a database, the action point definition comprising an action point identifier that specifies an action point located in application program code; determining from the action point definition, with the processor, a dataset that is in-context at the action point in the application program code; executing from the computer memory, with the processor, the expression editor tool, where the expression editor tool is operable to: display an expression definition interface comprising: data source selectors for obtaining selected data fields from among the dataset; and an operator selector for obtaining a selected logical operator to connect the selected data fields; construct a new expression from the selected data fields and the selected logical operator; display an outcome selection interface comprising: an outcome selector for obtaining a selected outcome for the new expression; create a rule comprising the new expression and the selected outcome; store the rule in the database linked to the action point definition; and display an expression combination interface comprising: an expression ordering section operable to display multiple defined expressions, including the new expression; an operator selector for obtaining a selected logical operator to connect the multiple defined expressions; and an expression grouping element operable to combine a first and a second defined expression among the multiple defined expressions into an individually selectable unitary expression for combination within the expression combination interface.

1. A method for building a rule that specifies an action that may occur during execution of an application, the method comprising: storing in a computer memory an expression editor tool; reading, with a processor, an action point definition from a database, the action point definition comprising an action point identifier that specifies an action point located in application program code; determining from the action point definition, with the processor, a dataset that is in-context at the action point in the application program code; executing from the computer memory, with the processor, the expression editor tool, where the expression editor tool is operable to: display an expression definition interface comprising: data source selectors for obtaining selected data fields from among the dataset; and an operator selector for obtaining a selected logical operator to connect the selected data fields; construct a new expression from the selected data fields and the selected logical operator; display an outcome selection interface comprising: an outcome selector for obtaining a selected outcome for the new expression; create a rule comprising the new expression and the selected outcome; store the rule in the database linked to the action point definition; and display an expression combination interface comprising: an expression ordering section operable to display multiple defined expressions, including the new expression; an operator selector for obtaining a selected logical operator to connect the multiple defined expressions; and an expression grouping element operable to combine a first and a second defined expression among the multiple defined expressions into an individually selectable unitary expression for combination within the expression combination interface. 3. The method of claim 1 , further comprising executing the expression editor tool to: construct a new expression combination from the multiple defined expressions and the selected logical operator; and create the rule from the new expression combination and the selected outcome.

1. A non-transitory computer-readable medium encoded with a computer program product for computing a correction rate predictor for medical record dictations, the computer program product comprising computer-readable instructions for causing a computer to: initiate automatic speech recognition processing of a dictation to initiate producing a draft medical transcription of at least a portion of the dictation; determine features of at least a portion of the dictation to produce a feature set comprising a combination of features of the dictation, the features being relevant to a quantity of expected transcription errors in the transcription of the at least a portion of the dictation; analyze the feature set to compute a predicted correction rate associated with the at least a portion of the dictation; use the predicted correction rate to determine whether to abandon the automatic speech recognition processing prior to automatic speech recognition processing of all of the dictation; use the predicted correction rate to determine whether to provide at least a portion of the draft medical transcription of the at least a portion of the dictation to a transcriptionist; and provide the at least a portion of the draft medical transcription to the transcriptionist if the predicted correction rate is below a threshold.

1. A non-transitory computer-readable medium encoded with a computer program product for computing a correction rate predictor for medical record dictations, the computer program product comprising computer-readable instructions for causing a computer to: initiate automatic speech recognition processing of a dictation to initiate producing a draft medical transcription of at least a portion of the dictation; determine features of at least a portion of the dictation to produce a feature set comprising a combination of features of the dictation, the features being relevant to a quantity of expected transcription errors in the transcription of the at least a portion of the dictation; analyze the feature set to compute a predicted correction rate associated with the at least a portion of the dictation; use the predicted correction rate to determine whether to abandon the automatic speech recognition processing prior to automatic speech recognition processing of all of the dictation; use the predicted correction rate to determine whether to provide at least a portion of the draft medical transcription of the at least a portion of the dictation to a transcriptionist; and provide the at least a portion of the draft medical transcription to the transcriptionist if the predicted correction rate is below a threshold. 13. The computer-readable medium of claim 1 , wherein at least one feature is specific to a selected word in a raw word recognition output.

8. The computer-implemented method of claim 1 , wherein receiving the first set of digital audio signals comprises receiving the first set of digital audio signals from another electronic device via radio frequency signaling.

8. The computer-implemented method of claim 1 , wherein receiving the first set of digital audio signals comprises receiving the first set of digital audio signals from another electronic device via radio frequency signaling. 9. The computer-implemented method of claim 8 , further comprising: receiving, at the computing device, a second set of digital audio signals from a microphone associated with the computing device; obtaining, at the computing device, a third translation of the second set of digital audio signals from speech of the second language into translated speech of the first language; and outputting, at the computing device, the third translation by transmitting a third set of digital audio signals representing the third translation to the other electronic device via radio frequency signaling, wherein the third set of digital audio signals are output via a speaker of the other electronic device.

3. A machine-implemented method for retrieving multimedia information, comprising: providing a textual search entry path configured to enable entry of one or more terms to search for in at least a portion of textual information stored on a computer-readable storage medium, wherein the textual search entry path is operable to access a stem index including a plurality of stems that are each associated with textual information and one or more related stems, the stems being concatenated in order to map each stem to other stems and to textual information that express a similar idea; and searching the textual information using the stem index for textual information that closely resembles a search inquiry comprising one or more terms entered in the textual search entry path.

3. A machine-implemented method for retrieving multimedia information, comprising: providing a textual search entry path configured to enable entry of one or more terms to search for in at least a portion of textual information stored on a computer-readable storage medium, wherein the textual search entry path is operable to access a stem index including a plurality of stems that are each associated with textual information and one or more related stems, the stems being concatenated in order to map each stem to other stems and to textual information that express a similar idea; and searching the textual information using the stem index for textual information that closely resembles a search inquiry comprising one or more terms entered in the textual search entry path. 6. The method of claim 3 , further comprising automatically checking the spelling of terms in the search inquiry and providing alternate versions of misspelled words.

15. A computer system comprising: a processor, a computer readable memory, and a computer readable storage medium; first program instructions to receive a data stream of non-contextual data objects, wherein each of the non-contextual data objects ambiguously relates to multiple subject-matters; second program instructions to associate one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; third program instructions to parse the synthetic context-based object into an n-tuple, wherein the n-tuple comprises a pointer to said one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object; fourth program instructions to calculate a virtual mass of a parsed synthetic context-based object, wherein the virtual mass of the parsed synthetic context-based object is derived from a formula of: P ( C )× Wt ( S ), where P(C) is the probability that the non-contextual data object has been associated with the correct context object, and where Wt(S) is the weighting factor of importance of the synthetic context-based object; fifth program instructions to create multiple context-based data gravity well frameworks on a context-based data gravity wells membrane, wherein the context-based data gravity wells membrane is a mathematical framework for a data structure, wherein each of the multiple context-based data gravity well frameworks comprises at least one non-contextual data object and at least one context object, and wherein the context-based data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based data gravity wells; sixth program instructions to transmit multiple parsed synthetic context-based objects to the context-based data gravity wells membrane; and seventh program instructions to define multiple context-based data gravity wells according to the mass of multiple parsed synthetic context-based objects that are pulled into each of the context-based data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects is pulled into a particular context-based data gravity well in response to values from its n-tuple matching said at least one non-contextual data object and said at least one context object in said particular context-based data gravity well; and wherein the first, second, third, fourth, fifth, sixth, and seventh program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory.

15. A computer system comprising: a processor, a computer readable memory, and a computer readable storage medium; first program instructions to receive a data stream of non-contextual data objects, wherein each of the non-contextual data objects ambiguously relates to multiple subject-matters; second program instructions to associate one of the non-contextual data objects with a context object to define a synthetic context-based object, wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of said one of the non-contextual data objects; third program instructions to parse the synthetic context-based object into an n-tuple, wherein the n-tuple comprises a pointer to said one of the non-contextual data objects, a probability that a non-contextual data object has been associated with a correct context object, and a weighting factor of importance of the synthetic context-based object; fourth program instructions to calculate a virtual mass of a parsed synthetic context-based object, wherein the virtual mass of the parsed synthetic context-based object is derived from a formula of: P ( C )× Wt ( S ), where P(C) is the probability that the non-contextual data object has been associated with the correct context object, and where Wt(S) is the weighting factor of importance of the synthetic context-based object; fifth program instructions to create multiple context-based data gravity well frameworks on a context-based data gravity wells membrane, wherein the context-based data gravity wells membrane is a mathematical framework for a data structure, wherein each of the multiple context-based data gravity well frameworks comprises at least one non-contextual data object and at least one context object, and wherein the context-based data gravity wells membrane is a virtual mathematical membrane that is capable of supporting multiple context-based data gravity wells; sixth program instructions to transmit multiple parsed synthetic context-based objects to the context-based data gravity wells membrane; and seventh program instructions to define multiple context-based data gravity wells according to the mass of multiple parsed synthetic context-based objects that are pulled into each of the context-based data gravity well frameworks, wherein each of the multiple parsed synthetic context-based objects is pulled into a particular context-based data gravity well in response to values from its n-tuple matching said at least one non-contextual data object and said at least one context object in said particular context-based data gravity well; and wherein the first, second, third, fourth, fifth, sixth, and seventh program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. 16. The computer system of claim 15 , further comprising: eighth program instructions to graphically display the multiple context-based data gravity wells according to a combined mass of the multiple parsed synthetic context-based objects, wherein a first context-based data gravity well holds a more massive combination of parsed synthetic context-based objects than a second context-based data gravity well, and wherein the first context-based data gravity well extends farther away from the context-based data gravity wells membrane than the second context-based data gravity well; and wherein the eighth program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory.

14. The apparatus of claim 13 , wherein content of the second document is indented relative to content of the first document.

14. The apparatus of claim 13 , wherein content of the second document is indented relative to content of the first document. 15. The apparatus of claim 14 , further comprising displaying the third document in a sub-screen area of the second document, wherein content of the third document is indented relative to content of the second document.

8. A computer system, comprising: a processor that is configured to execute machine-readable instructions; and a memory device that stores Web activity data generated by a plurality of users at a plurality of Webpages associated with a plurality of unaffiliated Websites, wherein the Web activity data comprises a plurality of query Uniform Resource Locators (URLs) that represent searches performed by users; and instructions that are executable by the processor, the instructions comprising: a search term extractor configured to obtain a plurality of search terms from the plurality of query URLs and associate each of the search terms with a corresponding Webpage, wherein the search term extractor is a classifier, which is generated by a training system and configured to identify a portion of the query URLs that include the search terms; and a data generator to generate statistical data from the Web activity data based, at least in part, on the search terms, wherein the statistical data comprises a first statistical data for a target search term associated with a target Website and a second statistical data for the target search term associated with another Website.

8. A computer system, comprising: a processor that is configured to execute machine-readable instructions; and a memory device that stores Web activity data generated by a plurality of users at a plurality of Webpages associated with a plurality of unaffiliated Websites, wherein the Web activity data comprises a plurality of query Uniform Resource Locators (URLs) that represent searches performed by users; and instructions that are executable by the processor, the instructions comprising: a search term extractor configured to obtain a plurality of search terms from the plurality of query URLs and associate each of the search terms with a corresponding Webpage, wherein the search term extractor is a classifier, which is generated by a training system and configured to identify a portion of the query URLs that include the search terms; and a data generator to generate statistical data from the Web activity data based, at least in part, on the search terms, wherein the statistical data comprises a first statistical data for a target search term associated with a target Website and a second statistical data for the target search term associated with another Website. 13. The computer-implemented method of claim 8 , wherein the data generator is configured to group the Webpages into clusters based, at least in part, on a similarity of the search terms that occur at to the Webpages.

12. An apparatus, comprising: at least one processor configured to identify a first network comprising one or more indexed classes of artificial neurons and determine one or more tags for the one or more indexed classes of artificial neurons regardless of their indexing, wherein the at least one processor is configured to determine the one or more tags for the one or more indexed classes of artificial neurons by: augmenting the first network with a second network comprising one or more artificial neurons, wherein each neuron in the second network corresponds to a tag; connecting each of the one or more indexed classes of artificial neurons to all the neurons in the second network with one or more plastic connections; and providing supervisory bias signals to the one or more indexed classes of artificial neurons via the plastic connections, such that the supervisory signal imposes a desired mapping between classes and output layer neurons; and a memory coupled with the at least one processor.

12. An apparatus, comprising: at least one processor configured to identify a first network comprising one or more indexed classes of artificial neurons and determine one or more tags for the one or more indexed classes of artificial neurons regardless of their indexing, wherein the at least one processor is configured to determine the one or more tags for the one or more indexed classes of artificial neurons by: augmenting the first network with a second network comprising one or more artificial neurons, wherein each neuron in the second network corresponds to a tag; connecting each of the one or more indexed classes of artificial neurons to all the neurons in the second network with one or more plastic connections; and providing supervisory bias signals to the one or more indexed classes of artificial neurons via the plastic connections, such that the supervisory signal imposes a desired mapping between classes and output layer neurons; and a memory coupled with the at least one processor. 20. The apparatus of claim 12 , wherein the at least one processor configured to provide supervisory bias signals is configured to: provide positive supervisory signals below a firing threshold to create a bias for firing on a desired output layer neuron.

3. A method of processing a query directed to a database, said method comprising the steps of: obtaining said query from a user; disambiguating said query using a knowledge base to obtain a set of identifiable interpretations associated with words in said query; selecting one interpretation from said set as a best interpretation based on a likelihood of intended meaning; selectively processing remaining interpretations of said set of interpretations by: re-disambiguating said query by excluding results associated with said best interpretation; and selecting at least a next best interpretation from said remaining interpretations to form set of re-disambiguated remaining interpretations; for said best interpretation and each member of said second set of re-disambiguated remaining interpretations: expanding and paraphrasing its associated interpretation to obtain semantically related interpretations to produce an expanded interpretation of the query; comparing the expanded interpretation of the query to an index associated with said database; and obtaining results from said database based on said expanded interpretation; obtaining from said user an indication of which result from all results returned from said database corresponds to the intended interpretation of said query; and further disambiguating said query based on said indication.

3. A method of processing a query directed to a database, said method comprising the steps of: obtaining said query from a user; disambiguating said query using a knowledge base to obtain a set of identifiable interpretations associated with words in said query; selecting one interpretation from said set as a best interpretation based on a likelihood of intended meaning; selectively processing remaining interpretations of said set of interpretations by: re-disambiguating said query by excluding results associated with said best interpretation; and selecting at least a next best interpretation from said remaining interpretations to form set of re-disambiguated remaining interpretations; for said best interpretation and each member of said second set of re-disambiguated remaining interpretations: expanding and paraphrasing its associated interpretation to obtain semantically related interpretations to produce an expanded interpretation of the query; comparing the expanded interpretation of the query to an index associated with said database; and obtaining results from said database based on said expanded interpretation; obtaining from said user an indication of which result from all results returned from said database corresponds to the intended interpretation of said query; and further disambiguating said query based on said indication. 5. The method of claim 3 further comprising updating said knowledge base with data regarding the user identified intended interpretation.

1. A transformation rule generation supporting apparatus configured to support generation of a transformation rule for transforming a transformation-source structured document having a hierarchical structure based on physical disposition of data in the document into a transformation-target structured document having a hierarchical structure based on a logical structure of data content, the apparatus comprising: a memory having computer readable instructions; and one or more processors for executing the computer readable instructions, the computer readable instructions comprising: reading a graphical representation of the transformation rule from a storage device, the graphical representation of the transformation rule including a reduced rule of at least one of a one-to-many transformation rule and a many-to-one transformation rule, the one-to-many transformation rule being indicated by a plurality of links mapping one node representing an input element that is an element in the transformation-source structured document to a plurality of nodes each representing an output element that is an element in the transformation-target structured document, the many-to-one transformation rule being indicated by a plurality of links mapping a plurality of nodes each representing an input element in the transformation-source structured document to one node representing an output element in the transformation-target structured document; and in response to that the read graphical representation of the transformation rule is the one-to-many transformation rule, determining, according to an output sort order, an output order in which each of the output elements represented by the plurality of nodes is output for the input element represented by the one node, the output sort order being a depth-first order in the hierarchical structure of the transformation-target structured document, and in response to that the read graphical representation of the transformation rule is the many-to-one transformation rule, determining an output target to which the output element represented by the one node is output for each of the input elements represented by the plurality of nodes with reference to an output target of an input element located immediately before each of the input elements in a list in an input sort order of one or more input elements mapped to an output element that is a parent of the output element, the input sort order being a depth-first order in the hierarchical structure of the transformation-source structured document.

1. A transformation rule generation supporting apparatus configured to support generation of a transformation rule for transforming a transformation-source structured document having a hierarchical structure based on physical disposition of data in the document into a transformation-target structured document having a hierarchical structure based on a logical structure of data content, the apparatus comprising: a memory having computer readable instructions; and one or more processors for executing the computer readable instructions, the computer readable instructions comprising: reading a graphical representation of the transformation rule from a storage device, the graphical representation of the transformation rule including a reduced rule of at least one of a one-to-many transformation rule and a many-to-one transformation rule, the one-to-many transformation rule being indicated by a plurality of links mapping one node representing an input element that is an element in the transformation-source structured document to a plurality of nodes each representing an output element that is an element in the transformation-target structured document, the many-to-one transformation rule being indicated by a plurality of links mapping a plurality of nodes each representing an input element in the transformation-source structured document to one node representing an output element in the transformation-target structured document; and in response to that the read graphical representation of the transformation rule is the one-to-many transformation rule, determining, according to an output sort order, an output order in which each of the output elements represented by the plurality of nodes is output for the input element represented by the one node, the output sort order being a depth-first order in the hierarchical structure of the transformation-target structured document, and in response to that the read graphical representation of the transformation rule is the many-to-one transformation rule, determining an output target to which the output element represented by the one node is output for each of the input elements represented by the plurality of nodes with reference to an output target of an input element located immediately before each of the input elements in a list in an input sort order of one or more input elements mapped to an output element that is a parent of the output element, the input sort order being a depth-first order in the hierarchical structure of the transformation-source structured document. 2. The transformation rule generation supporting apparatus according to claim 1 , wherein: the graphical representation of the transformation rule includes a set of nodes representing input elements, a set of links each representing a hierarchical relationship between two different nodes in the set of the nodes representing the input elements, the set of nodes representing output elements, a set of links each representing a hierarchical relationship between two different nodes in the set of the nodes representing the output elements, and a set of links representing correspondence between the nodes representing the input elements and the nodes representing the output elements; each node and each link have associated therewith at least one of a pattern for use in matching performed for each element in a structured document to be transformed and an output-related parameter; and the computer readable instructions further comprise: generating a transformation rule in text form for a processing-target node taken from the set of the nodes representing the input elements in the input sort order, the transformation rule instructing, on condition that matching using the pattern associated with the processing-target node succeeds for an element in the structured document to be transformed, to output an output element represented by a node mapped by a link to the processing-target node, on the basis of the output-related parameter associated with the link and the output-related parameter associated with the node representing the output element.

33. An article of manufacture comprising: a computer-readable storage medium comprising programming configured to cause processing circuitry to: select a cluster label for a cluster comprising a subset of a plurality of documents of a document set at least in part by co-occurrence of the cluster label and a plurality of terms of the documents of the cluster which are indicative of subject matter content of the documents of the cluster, wherein the subset comprises a plurality of the documents and wherein the cluster label comprises one of a plurality of terms common to at least one of the documents of the cluster and the cluster label comprises a plurality of word senses; determine, for individual ones of the word senses, a plurality of semantic similarity values for respective ones of the terms, wherein the semantic similarity values are individually indicative of a degree of semantic similarity between one of the word senses and one of the terms; analyze the semantic similarity values determined for respective ones of the word senses; and select one of the word senses using the analysis, wherein the one of the word senses has an increased relevancy with respect to the terms of the documents of the cluster compared with the relevancies of others of the word senses.

33. An article of manufacture comprising: a computer-readable storage medium comprising programming configured to cause processing circuitry to: select a cluster label for a cluster comprising a subset of a plurality of documents of a document set at least in part by co-occurrence of the cluster label and a plurality of terms of the documents of the cluster which are indicative of subject matter content of the documents of the cluster, wherein the subset comprises a plurality of the documents and wherein the cluster label comprises one of a plurality of terms common to at least one of the documents of the cluster and the cluster label comprises a plurality of word senses; determine, for individual ones of the word senses, a plurality of semantic similarity values for respective ones of the terms, wherein the semantic similarity values are individually indicative of a degree of semantic similarity between one of the word senses and one of the terms; analyze the semantic similarity values determined for respective ones of the word senses; and select one of the word senses using the analysis, wherein the one of the word senses has an increased relevancy with respect to the terms of the documents of the cluster compared with the relevancies of others of the word senses. 36. The article of claim 33 wherein the programming is configured to cause the processing circuitry to, for individual ones of the terms, select the greatest semantic similarity values for individual ones of the word senses and, for individual ones of the word senses, to sum the selected greatest semantic similarity values for the respective word sense providing a cumulative value for the word sense to analyze the semantic similarity values, and to select the one of the word senses having the greatest cumulative value.

11. A method for interacting with a person, the method comprising: receiving a user textual input; matching a structured representation of the user textual input against expected user statement fields of knowledge database entries; wherein a knowledge database entry comprises an expected user statement field and at least one action field; wherein multiple entries of the knowledge database form a data structure that comprises multiple expected user statements fields that match an expected sequence of user textual inputs.

11. A method for interacting with a person, the method comprising: receiving a user textual input; matching a structured representation of the user textual input against expected user statement fields of knowledge database entries; wherein a knowledge database entry comprises an expected user statement field and at least one action field; wherein multiple entries of the knowledge database form a data structure that comprises multiple expected user statements fields that match an expected sequence of user textual inputs. 12. The method according to claim 11 wherein at least one action field comprises a link to another knowledge database entry that comprises another expected user statement field and at least one other action field.

1. A computer-implemented speech recognition method for selecting a combination of list elements via a speech input having a first portion and a second portion, wherein a first list element of the combination is part of a first set of list elements and a second list element of the combination is part of a second set of list elements, the method comprising: receiving at a processor the speech input; comparing within the processor each list element of the first set of list elements with the first portion of the speech input to obtain a first candidate list of best matching list elements; processing the second set of list elements using the first candidate list to obtain a subset of the second set of list elements; comparing each list element of the subset of the second set of list elements with the second portion of the speech input to obtain a second candidate list of best matching list elements; and selecting a combination of list elements using the first and the second candidate lists wherein selecting a combination of list elements comprises: determining combinations of a list element of the first candidate list with a related list element of the second candidate list; scoring each determined combination by combining the score of the list element of the first candidate list and the score of the related list element of the second candidate list; determining a result list wherein the result list comprises best matching combinations of a list element of the first set of list elements and a list element of the second set of list elements; and comparing each combination of the result list with the speech input to determine a score for each combination, thereby obtaining a pruned result list, wherein the first candidate list, the second candidate list, the result list and the pruned result list comprise a maximum number of list elements, in particular wherein the maximum number of list elements of the first candidate list, the second candidate list, the result list and the pruned result list are determined based on the length of the speech input.

1. A computer-implemented speech recognition method for selecting a combination of list elements via a speech input having a first portion and a second portion, wherein a first list element of the combination is part of a first set of list elements and a second list element of the combination is part of a second set of list elements, the method comprising: receiving at a processor the speech input; comparing within the processor each list element of the first set of list elements with the first portion of the speech input to obtain a first candidate list of best matching list elements; processing the second set of list elements using the first candidate list to obtain a subset of the second set of list elements; comparing each list element of the subset of the second set of list elements with the second portion of the speech input to obtain a second candidate list of best matching list elements; and selecting a combination of list elements using the first and the second candidate lists wherein selecting a combination of list elements comprises: determining combinations of a list element of the first candidate list with a related list element of the second candidate list; scoring each determined combination by combining the score of the list element of the first candidate list and the score of the related list element of the second candidate list; determining a result list wherein the result list comprises best matching combinations of a list element of the first set of list elements and a list element of the second set of list elements; and comparing each combination of the result list with the speech input to determine a score for each combination, thereby obtaining a pruned result list, wherein the first candidate list, the second candidate list, the result list and the pruned result list comprise a maximum number of list elements, in particular wherein the maximum number of list elements of the first candidate list, the second candidate list, the result list and the pruned result list are determined based on the length of the speech input. 7. The method according to claim 1 , wherein comparing the list elements of the first set and/or the list elements of the subset of the second set with the speech input comprises determining for each list element of the first set and/or of the subset of the second set a score.

27. A memory media which stores program instructions for automatically generating graphical code for a graphical program, wherein the graphical program performs a man/machine interface function for monitoring and/or controlling a process, wherein the method operates in a computer system including a display screen, wherein the program instructions are executable to implement: configuring a front panel interface on the display screen in response to user input, wherein the front panel interface is useable for monitoring and/or controlling the process, wherein said configuring includes selecting at least one front panel object which represents input to or output from the graphical program; associating the at least one front panel object with at least one data value in the process; configuring one or more parameter values in response to user input, wherein said one or more parameter values indicate a desired functionality of the graphical program; automatically selecting a graphical code portion in response to the at least one front panel object, wherein said selected graphical code portion corresponds to said at least one front panel object; automatically configuring said graphical code portion with said one or more parameter values to produce a configured graphical code portion, wherein said configured graphical code portion comprises at least a portion of the graphical program.

27. A memory media which stores program instructions for automatically generating graphical code for a graphical program, wherein the graphical program performs a man/machine interface function for monitoring and/or controlling a process, wherein the method operates in a computer system including a display screen, wherein the program instructions are executable to implement: configuring a front panel interface on the display screen in response to user input, wherein the front panel interface is useable for monitoring and/or controlling the process, wherein said configuring includes selecting at least one front panel object which represents input to or output from the graphical program; associating the at least one front panel object with at least one data value in the process; configuring one or more parameter values in response to user input, wherein said one or more parameter values indicate a desired functionality of the graphical program; automatically selecting a graphical code portion in response to the at least one front panel object, wherein said selected graphical code portion corresponds to said at least one front panel object; automatically configuring said graphical code portion with said one or more parameter values to produce a configured graphical code portion, wherein said configured graphical code portion comprises at least a portion of the graphical program. 52. The memory media of claim 27, wherein said at least one front panel object is selected from the group comprising numeric indicators, numeric controls, Boolean indicators, Boolean controls, Table indicators, Waveform chart indicators, and XY Graph.

1. A method for graphically characterizing statements about an object, comprising: applying, as a result of computing hardware and programmable memory, frame extraction, to a first corpus, in order to attempt to identify, for each statement of the corpus, an object and a sentiment expressed about the object; identifying, as a result of computing hardware and programmable memory, a first object-specific corpus, that is a subset of the first corpus, where all the statements of the first object-specific corpus are about a same first object; categorizing, as a result of computing hardware and programmable memory, a sentiment of each statement, of the first object-specific corpus; categorizing a polarity of each statement, of the first object-specific corpus; categorizing an intensity of each statement, of the first object-specific corpus; determining, as a result of computing hardware and programmable memory, a net polarity measure as a function of the polarity categorization and a net intensity measure as a function of the intensity categorization; producing, as a result of computing hardware and programmable memory, a first graphical representation, of the first object-specific corpus; placing the first graphical representation, relative to a first axis, in accordance with the net polarity measure; and placing the first graphical representation, relative to a second axis, in accordance with the net intensity measure.

1. A method for graphically characterizing statements about an object, comprising: applying, as a result of computing hardware and programmable memory, frame extraction, to a first corpus, in order to attempt to identify, for each statement of the corpus, an object and a sentiment expressed about the object; identifying, as a result of computing hardware and programmable memory, a first object-specific corpus, that is a subset of the first corpus, where all the statements of the first object-specific corpus are about a same first object; categorizing, as a result of computing hardware and programmable memory, a sentiment of each statement, of the first object-specific corpus; categorizing a polarity of each statement, of the first object-specific corpus; categorizing an intensity of each statement, of the first object-specific corpus; determining, as a result of computing hardware and programmable memory, a net polarity measure as a function of the polarity categorization and a net intensity measure as a function of the intensity categorization; producing, as a result of computing hardware and programmable memory, a first graphical representation, of the first object-specific corpus; placing the first graphical representation, relative to a first axis, in accordance with the net polarity measure; and placing the first graphical representation, relative to a second axis, in accordance with the net intensity measure. 11. The method of claim 1 , wherein the first object represents a brand.

20. A computer readable storage medium comprising one or more sequences of instructions, which when executed by one or more processors cause: presenting, at a local client machine, a first webpage that includes a first plurality of search results based on a user-provided search criteria, wherein a copy of the first webpage is locally cached; receiving a first user selection of a search result of the first plurality of search results included on the first webpage, wherein selection of the search result causes a document corresponding to the first user selection to be displayed; modifying, at the local client machine, the locally cached copy of the first webpage to include metadata associated with the first user selection of the search result; in response to receiving a request to re-display the first-webpage: inspecting the locally cached copy of the first webpage for any metadata, added to the locally cached copy subsequent to presenting the first webpage, associated with user interaction on the first web page; detecting that the locally cached copy of the first webpage has been modified to include the metadata associated with the first user selection of the search result; in response to the detecting step, obtaining content based on the metadata; responding to the request to re-display the first webpage by displaying a modified search results webpage, wherein the modified search results webpage has been changed relative to the first web page based, at least in part, on the content that was obtained based on the metadata.

20. A computer readable storage medium comprising one or more sequences of instructions, which when executed by one or more processors cause: presenting, at a local client machine, a first webpage that includes a first plurality of search results based on a user-provided search criteria, wherein a copy of the first webpage is locally cached; receiving a first user selection of a search result of the first plurality of search results included on the first webpage, wherein selection of the search result causes a document corresponding to the first user selection to be displayed; modifying, at the local client machine, the locally cached copy of the first webpage to include metadata associated with the first user selection of the search result; in response to receiving a request to re-display the first-webpage: inspecting the locally cached copy of the first webpage for any metadata, added to the locally cached copy subsequent to presenting the first webpage, associated with user interaction on the first web page; detecting that the locally cached copy of the first webpage has been modified to include the metadata associated with the first user selection of the search result; in response to the detecting step, obtaining content based on the metadata; responding to the request to re-display the first webpage by displaying a modified search results webpage, wherein the modified search results webpage has been changed relative to the first web page based, at least in part, on the content that was obtained based on the metadata. 30. The computer readable storage medium of claim 20 , wherein the metadata includes at least one of: a web address associated with the first user selection, the document corresponding to the first user selection, or a time the first user selection was made.

1. A non-transitory computer-readable medium storing computer-executable instructions implementing a parser that has multiple parse states, wherein, when the instructions are executed by a computer, the instructions cause the computer to perform a process comprising: receiving a portion of a software program in an original linguistic form in a high level language, wherein the portion of the software program includes a nonlinear program element having a body; tokenizing the portion of the software program to generate an input stream of tokens representing the portion of the software program; and while retaining the original linguistic form, using a set of one or more production rules to control a parser to directly execute the nonlinear program element by manipulating a parse state and the input stream of tokens, wherein the one or more production rules enable the parser to perform type conversion and the one or more production rules enable the parser to insert an expression into the input stream of tokens to skip tokens in the input stream of tokens during execution of the nonlinear program element, and wherein directly executing comprises executing tokens until the dynamic end of the nonlinear program element is reached, and wherein manipulating the input stream of tokens comprises using the one or more production rules to perform type conversion on at least one token of the input stream of tokens and using the one or more production rules to insert expressions into the input stream of tokens to skip tokens during execution of the nonlinear program element.

1. A non-transitory computer-readable medium storing computer-executable instructions implementing a parser that has multiple parse states, wherein, when the instructions are executed by a computer, the instructions cause the computer to perform a process comprising: receiving a portion of a software program in an original linguistic form in a high level language, wherein the portion of the software program includes a nonlinear program element having a body; tokenizing the portion of the software program to generate an input stream of tokens representing the portion of the software program; and while retaining the original linguistic form, using a set of one or more production rules to control a parser to directly execute the nonlinear program element by manipulating a parse state and the input stream of tokens, wherein the one or more production rules enable the parser to perform type conversion and the one or more production rules enable the parser to insert an expression into the input stream of tokens to skip tokens in the input stream of tokens during execution of the nonlinear program element, and wherein directly executing comprises executing tokens until the dynamic end of the nonlinear program element is reached, and wherein manipulating the input stream of tokens comprises using the one or more production rules to perform type conversion on at least one token of the input stream of tokens and using the one or more production rules to insert expressions into the input stream of tokens to skip tokens during execution of the nonlinear program element. 13. The non-transitory computer-readable medium as recited in claim 1 , further comprising injecting a token in the input token stream in a parser to facilitate runtime program flow control.

1. A method comprising: receiving at least two sets of attributes and values for a product through a communications network, each set of attributes representing quantifiable properties of the product and each set of values representing numerical quantities of the respective properties, wherein there is at least one difference between each of the sets of attributes and values; forming a collaborative component taxonomy instantiation, the taxonomy instantiation comprising a union of distinct attributes and values obtained from the at least two sets of attributes and values; associating a unique identifier with the formed collaborative component taxonomy instantiation; comparing the union of product attributes and values in the collaborative component taxonomy instantiation to product catalog information received from different computing systems through a communications network; associating the unique identifier with those matching products included in the received product catalog information based on the comparing; and distributing the unique identifier and the association with a corresponding matching product to each computing system having product catalog information containing the corresponding matching product through the communications network, wherein the unique identifier is associated with each matching product at each computing system through the distributing.

1. A method comprising: receiving at least two sets of attributes and values for a product through a communications network, each set of attributes representing quantifiable properties of the product and each set of values representing numerical quantities of the respective properties, wherein there is at least one difference between each of the sets of attributes and values; forming a collaborative component taxonomy instantiation, the taxonomy instantiation comprising a union of distinct attributes and values obtained from the at least two sets of attributes and values; associating a unique identifier with the formed collaborative component taxonomy instantiation; comparing the union of product attributes and values in the collaborative component taxonomy instantiation to product catalog information received from different computing systems through a communications network; associating the unique identifier with those matching products included in the received product catalog information based on the comparing; and distributing the unique identifier and the association with a corresponding matching product to each computing system having product catalog information containing the corresponding matching product through the communications network, wherein the unique identifier is associated with each matching product at each computing system through the distributing. 5. The method of claim 1 , further comprising selecting a taxonomy.

43. The apparatus of 28 , wherein the method further comprises: (D) before (C), identifying a default playback rate of the spoken audio stream; and (E) identifying an emphasized playback rate of the spoken audio stream as a quotient of the default playback rate and the emphasis factor.

43. The apparatus of 28 , wherein the method further comprises: (D) before (C), identifying a default playback rate of the spoken audio stream; and (E) identifying an emphasized playback rate of the spoken audio stream as a quotient of the default playback rate and the emphasis factor. 44. The apparatus of claim 43 , wherein the method further comprises: (E) playing the spoken audio stream at the emphasized playback rate.

16. A system for recording media for a contact center comprising: a processor; a memory, wherein the first memory has stored thereon instructions that, when executed by the processor, cause the processor to: receive a request for a telephony call from a first communication device; invoke a rule based on an attribute of the telephony call, wherein the rule identifies a condition for recording the call; determine whether the condition for recording the call is satisfied; in response to determining that the condition for recording the call is satisfied, establish a first call path with a recording system instead of a second call path, wherein the recording system is configured to receive media transmitted by the first communication device via the first call path instead of the second call path, bridge a media path between the first communication and a second communication device, and record the media in a storage device; and in response to determining that the condition for recording the call is not satisfied, establish the second call path with the second communication device without establishing the first call path, wherein the media transmitted by the first communication device is for being received via the second call path instead of the first call path.

16. A system for recording media for a contact center comprising: a processor; a memory, wherein the first memory has stored thereon instructions that, when executed by the processor, cause the processor to: receive a request for a telephony call from a first communication device; invoke a rule based on an attribute of the telephony call, wherein the rule identifies a condition for recording the call; determine whether the condition for recording the call is satisfied; in response to determining that the condition for recording the call is satisfied, establish a first call path with a recording system instead of a second call path, wherein the recording system is configured to receive media transmitted by the first communication device via the first call path instead of the second call path, bridge a media path between the first communication and a second communication device, and record the media in a storage device; and in response to determining that the condition for recording the call is not satisfied, establish the second call path with the second communication device without establishing the first call path, wherein the media transmitted by the first communication device is for being received via the second call path instead of the first call path. 27. The system of claim 16 , wherein the metadata includes a link to a recording of media exchanged during the telephony call, wherein the recording system is further configured to: receive a call event associated with the telephony call, the call event including a timestamp of when the event occurred during the telephony call; store the call event in a database record; retrieve the database record for displaying the call event on a display device; receive a user command identifying the call event in response to the display on the display device; and retrieve a portion of the recording associated with the call event in response to the user command for providing an audible rendering of the retrieved portion of the recording.

1. A computer implemented method for evaluating a correlation between (i) a gene, a SNP, a SNP pattern, a portion of gene, a region of a genome, or a compound, and (ii) a disease or a genotype, the method comprising: providing a taxonomy of categories of diseases and/or phenotypes arranged in a hierarchical structure comprising at least one top-level category; providing, a plurality of feature sets, each feature set comprising (a) two or more features, (b) associated experimentally-derived statistical information indicating one or more of: differential expression of said features, abundance of said features, responses of said features to a treatment or stimulus, and effects of said features on biological systems, and (c) a feature rank indicating the importance of the feature in an experiment from which the statistical information was derived, wherein the features are genes, SNPs, SNP patterns, portions of genes, regions of a genome, or compounds, at least some of the features have different names but correspond to a same gene, SNP, SNP pattern, portion of gene, region of a genome, or compound, the plurality of feature sets is obtained from across different experiments, platforms, and/or organisms, and at least some of said feature sets are associated with one or more categories in the taxonomy; providing a plurality of globally unique mapping identifiers; identifying, for each globally unique mapping identifier, one or more features associated with the globally unique mapping identifier; mapping, for each globally unique mapping identifier, the identified one or more features to the globally unique mapping identifier, thereby providing mapping data indicating mapping between a plurality of features and the plurality of globally unique mapping identifiers, wherein at least some features having different names but corresponding to a same gene, SNP, SNP pattern, portion of gene, region of a genome, or compound are mapped to a same globally unique mapping identifier; storing the mapping data in an index set; identifying, for each of a plurality of the categories in the taxonomy, contributing feature sets that contribute to scoring a category under consideration by identifying all feature sets among the provided feature sets that are associated with the category under consideration and its child categories in the taxonomy; combining the feature ranks of all features in the contributing feature sets that can be mapped to a globally unique mapping identifier under consideration based on the mapping data in the index set to obtain an overall score; and evaluating a correlation between (i) a gene, a SNP, a SNP pattern, a portion of gene, a region of a genome, or a compound corresponding to the globally unique mapping identifier under consideration, and (ii) a disease or a genotype corresponding to the category under consideration based on the obtained overall score.

1. A computer implemented method for evaluating a correlation between (i) a gene, a SNP, a SNP pattern, a portion of gene, a region of a genome, or a compound, and (ii) a disease or a genotype, the method comprising: providing a taxonomy of categories of diseases and/or phenotypes arranged in a hierarchical structure comprising at least one top-level category; providing, a plurality of feature sets, each feature set comprising (a) two or more features, (b) associated experimentally-derived statistical information indicating one or more of: differential expression of said features, abundance of said features, responses of said features to a treatment or stimulus, and effects of said features on biological systems, and (c) a feature rank indicating the importance of the feature in an experiment from which the statistical information was derived, wherein the features are genes, SNPs, SNP patterns, portions of genes, regions of a genome, or compounds, at least some of the features have different names but correspond to a same gene, SNP, SNP pattern, portion of gene, region of a genome, or compound, the plurality of feature sets is obtained from across different experiments, platforms, and/or organisms, and at least some of said feature sets are associated with one or more categories in the taxonomy; providing a plurality of globally unique mapping identifiers; identifying, for each globally unique mapping identifier, one or more features associated with the globally unique mapping identifier; mapping, for each globally unique mapping identifier, the identified one or more features to the globally unique mapping identifier, thereby providing mapping data indicating mapping between a plurality of features and the plurality of globally unique mapping identifiers, wherein at least some features having different names but corresponding to a same gene, SNP, SNP pattern, portion of gene, region of a genome, or compound are mapped to a same globally unique mapping identifier; storing the mapping data in an index set; identifying, for each of a plurality of the categories in the taxonomy, contributing feature sets that contribute to scoring a category under consideration by identifying all feature sets among the provided feature sets that are associated with the category under consideration and its child categories in the taxonomy; combining the feature ranks of all features in the contributing feature sets that can be mapped to a globally unique mapping identifier under consideration based on the mapping data in the index set to obtain an overall score; and evaluating a correlation between (i) a gene, a SNP, a SNP pattern, a portion of gene, a region of a genome, or a compound corresponding to the globally unique mapping identifier under consideration, and (ii) a disease or a genotype corresponding to the category under consideration based on the obtained overall score. 3. The computer-implemented method of claim 1 , further comprising: for each of a plurality of categories in the taxonomy, receiving, feature set-feature set correlation scores between the contributing feature sets and a feature set obtained from a person; and combining the feature set-feature set correlation scores to obtain a category-feature set score indicating the relevance of the category under consideration to the feature set obtained from the person; and determining whether the person is likely to have the disease or the phenotype by comparing the category-feature set score to a criterion.

10. The system as recited in claim 9 , wherein the selected search term is to be selected from closed captioning text of one of a television program, broadcast program, streaming media and recorded media.

10. The system as recited in claim 9 , wherein the selected search term is to be selected from closed captioning text of one of a television program, broadcast program, streaming media and recorded media. 13. The system as recited in claim 10 , wherein the natural language processor module is configured to use proximity based statistical analysis in identifying the keyword results to be provided to the context search engine.

14. A method for security analysis, comprising: training a classifier, comprising: running an initial security analysis on a training codebase to generate a set of vulnerabilities associated with the training codebase; analyzing a program with a feature set that limits a number of detected vulnerabilities to generate a limited set of vulnerabilities associated with the feature set; comparing the limited set of vulnerabilities to a known vulnerability distribution to generate an accuracy score using a processor; iterating said steps of analyzing and comparing using different feature sets to find a feature set having a highest accuracy score; and generating a classifier based on the feature set having the highest accuracy score; and scanning code using the classifier to locate potential vulnerabilities.

14. A method for security analysis, comprising: training a classifier, comprising: running an initial security analysis on a training codebase to generate a set of vulnerabilities associated with the training codebase; analyzing a program with a feature set that limits a number of detected vulnerabilities to generate a limited set of vulnerabilities associated with the feature set; comparing the limited set of vulnerabilities to a known vulnerability distribution to generate an accuracy score using a processor; iterating said steps of analyzing and comparing using different feature sets to find a feature set having a highest accuracy score; and generating a classifier based on the feature set having the highest accuracy score; and scanning code using the classifier to locate potential vulnerabilities. 16. The method of claim 14 , wherein the feature set includes one or more blocked code locations.

1. A computer-implemented method that facilitates utilizing rule-based technology with a radio frequency identification (RFID) network, comprising: receiving a dynamic update in real time of a declarative event policy, the declarative event policy comprising one or more logical rules that are grouped together to perform in memory filtering, alerting, deduction and inferences based upon events and data associated with RFID events; creating a logical source associated with the RFID network, the logical source providing tag data comprising an identification (ID), a type, a source, a time, and a device name, the logical source comprising each of a device collection, a filter policy, an alert policy, and an event handler, the filter policy comprising removal of duplicate reads and allowing at least one combination of items, the alert policy comprising raising an alert when an RFID tag in a given range is collected, raising an alert when a first given RFID tag is collected in a first given time period, and raising an alert when a second given RFID tag is read repeatedly in a second given time period, the alert policy also comprising raising an alert when a first device within the RFID network is down, raising an alert when a second device within the RFID network comes up, raising an alert when a new device within the RFID network is discovered, wherein each alert raised comprises the ID, type, source, time, data, and device name associated with the particular RFID tag or device; receiving RFID information from the logical source associated with the RFID network; asserting at least a portion of the tag data to be used in the filter policy into a rules engine (RE), the RE utilizing a rule component that applies rules that are contained within rule sets that adhere to a fixed format comprising event, condition, and action rules, the RE supporting predicates and conditions, wherein the rules are expressed at least in part using a domain specific nomenclature and wherein the rules are interpreted at least in part by a vocabulary component which maps one or more domain specific terms in the domain specific nomenclature to one or more underlying implementing technologies; the RE inferring states and generating a probability distribution over the states based upon a captured set of RFID observations, the inferred states identifying a specific context and action; the RE accepting and deploying an updated rule set in real-time, wherein deploying the updated rule set is accomplished without a restart of the RE; executing the filter policy based at least in part upon the tag data provided by the logical source; and executing the alert policy based at least in part upon the tag data provided by the logical source, wherein a set of alert actions associated with the alert policy comprises one or more of sending email, sending SMS, sending a page, and creating a log.

1. A computer-implemented method that facilitates utilizing rule-based technology with a radio frequency identification (RFID) network, comprising: receiving a dynamic update in real time of a declarative event policy, the declarative event policy comprising one or more logical rules that are grouped together to perform in memory filtering, alerting, deduction and inferences based upon events and data associated with RFID events; creating a logical source associated with the RFID network, the logical source providing tag data comprising an identification (ID), a type, a source, a time, and a device name, the logical source comprising each of a device collection, a filter policy, an alert policy, and an event handler, the filter policy comprising removal of duplicate reads and allowing at least one combination of items, the alert policy comprising raising an alert when an RFID tag in a given range is collected, raising an alert when a first given RFID tag is collected in a first given time period, and raising an alert when a second given RFID tag is read repeatedly in a second given time period, the alert policy also comprising raising an alert when a first device within the RFID network is down, raising an alert when a second device within the RFID network comes up, raising an alert when a new device within the RFID network is discovered, wherein each alert raised comprises the ID, type, source, time, data, and device name associated with the particular RFID tag or device; receiving RFID information from the logical source associated with the RFID network; asserting at least a portion of the tag data to be used in the filter policy into a rules engine (RE), the RE utilizing a rule component that applies rules that are contained within rule sets that adhere to a fixed format comprising event, condition, and action rules, the RE supporting predicates and conditions, wherein the rules are expressed at least in part using a domain specific nomenclature and wherein the rules are interpreted at least in part by a vocabulary component which maps one or more domain specific terms in the domain specific nomenclature to one or more underlying implementing technologies; the RE inferring states and generating a probability distribution over the states based upon a captured set of RFID observations, the inferred states identifying a specific context and action; the RE accepting and deploying an updated rule set in real-time, wherein deploying the updated rule set is accomplished without a restart of the RE; executing the filter policy based at least in part upon the tag data provided by the logical source; and executing the alert policy based at least in part upon the tag data provided by the logical source, wherein a set of alert actions associated with the alert policy comprises one or more of sending email, sending SMS, sending a page, and creating a log. 4. A computer program product comprising physical memory having stored thereon computer-executable instructions which, when executed upon one or more computer processors, causes the one or more processors to perform the method of claim 1 .

16. A computer system for resolving ambiguities in date values associated with an attribute of an entity, the computer system comprising: one or more processors; memory; and one or more programs stored in the memory, the one or more programs comprising instructions to: obtain a first text string associated with an attribute of an entity, wherein the first text string is extracted from a first web document; determine if that the first text string conforms to one or more date formats; assign a first confidence value for each of the date formats for the first text string based on a first number of unknown variables that remain when interpreting the first text string using each of the date formats; obtain a second text string associated with the attribute of the entity, wherein the second text string is extracted from a second web document; determine if that the second text string conforms to one or more date formats; assign a second confidence value for each of the date formats for the second text string based on a second number of unknown variables that remain when interpreting the second text string using each of the date formats; determine a first date string expressed in a date format with a highest first confidence value for the first text string; determine a second date string expressed in a date format with a highest second confidence value for the second text string; and merge a first subset of the first date string and a second subset of the second date string to obtain a date value for the attribute.

16. A computer system for resolving ambiguities in date values associated with an attribute of an entity, the computer system comprising: one or more processors; memory; and one or more programs stored in the memory, the one or more programs comprising instructions to: obtain a first text string associated with an attribute of an entity, wherein the first text string is extracted from a first web document; determine if that the first text string conforms to one or more date formats; assign a first confidence value for each of the date formats for the first text string based on a first number of unknown variables that remain when interpreting the first text string using each of the date formats; obtain a second text string associated with the attribute of the entity, wherein the second text string is extracted from a second web document; determine if that the second text string conforms to one or more date formats; assign a second confidence value for each of the date formats for the second text string based on a second number of unknown variables that remain when interpreting the second text string using each of the date formats; determine a first date string expressed in a date format with a highest first confidence value for the first text string; determine a second date string expressed in a date format with a highest second confidence value for the second text string; and merge a first subset of the first date string and a second subset of the second date string to obtain a date value for the attribute. 17. The system of claim 16 , further comprising instructions to: determine whether the obtained date value is consistent with rules related to the attribute.

10. An apparatus for accessing a redacted document, the apparatus comprising: a processor; and a memory coupled to the processor and including computer readable instructions that, when executed by the processor, are configured to cause the processor to: execute a viewing application for viewing documents, the viewing application comprising: standard code for the viewing application that can not process a container data type; and custom code configured to allow the viewing application to process a container data type; receive a container from a remote computing device comprising: a set of redacted documents corresponding to an original document, each redacted document having a level of redaction corresponding to a viewing location; and a header comprising encryption information for each redacted document in the set of redacted documents; process the container based on a location of the computing device and the custom code; execute a second viewing application for viewing documents, wherein the second viewing application is not configured to process the container data type; open the container using the second viewing application; and display, using the second viewing application, a placeholder document in place of any redacted documents from the set of redacted documents in the container.

10. An apparatus for accessing a redacted document, the apparatus comprising: a processor; and a memory coupled to the processor and including computer readable instructions that, when executed by the processor, are configured to cause the processor to: execute a viewing application for viewing documents, the viewing application comprising: standard code for the viewing application that can not process a container data type; and custom code configured to allow the viewing application to process a container data type; receive a container from a remote computing device comprising: a set of redacted documents corresponding to an original document, each redacted document having a level of redaction corresponding to a viewing location; and a header comprising encryption information for each redacted document in the set of redacted documents; process the container based on a location of the computing device and the custom code; execute a second viewing application for viewing documents, wherein the second viewing application is not configured to process the container data type; open the container using the second viewing application; and display, using the second viewing application, a placeholder document in place of any redacted documents from the set of redacted documents in the container. 11. The apparatus of claim 10 , wherein processing the container comprises: storing a set of custom actions for the container data type; intercepting an application call from the viewing application to perform an action to the container; selecting a custom action from the set of custom actions based on the intercepted application call; and executing the custom action instead of the application call.

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. 8. The method of claim 1 , wherein the one or more DTDs includes at least two different DTDs.

9. A handheld electronic device comprising: an input apparatus; an output apparatus; and a processor apparatus comprising a processor and a memory, wherein the processor apparatus is structured to: detect an ambiguous character-string input that comprises a current character input and a previous character input; generate a plurality of character permutations of the ambiguous character-string input, at least one of the character permutations being a potential artificial variant that is neither a prefix of a word object nor is identical to a word object; output at least one of the character permutations other than the potential artificial variant; determine that the potential artificial variant has been displayed during a current session; based on the determination that the potential artificial variant has been displayed during a current session, output a displayed artificial variant as a representation of the potential artificial variant, wherein the displayed artificial variant is outputted at a position of relatively lower priority than at least one of the outputted character permutations; determine that the displayed artificial variant is not selected; and based on the determination that the displayed artificial variant is not selected, suppress from being output an offspring artificial variant of the unselected artificial variant when a next character input associated with the ambiguous character-string is detected.

9. A handheld electronic device comprising: an input apparatus; an output apparatus; and a processor apparatus comprising a processor and a memory, wherein the processor apparatus is structured to: detect an ambiguous character-string input that comprises a current character input and a previous character input; generate a plurality of character permutations of the ambiguous character-string input, at least one of the character permutations being a potential artificial variant that is neither a prefix of a word object nor is identical to a word object; output at least one of the character permutations other than the potential artificial variant; determine that the potential artificial variant has been displayed during a current session; based on the determination that the potential artificial variant has been displayed during a current session, output a displayed artificial variant as a representation of the potential artificial variant, wherein the displayed artificial variant is outputted at a position of relatively lower priority than at least one of the outputted character permutations; determine that the displayed artificial variant is not selected; and based on the determination that the displayed artificial variant is not selected, suppress from being output an offspring artificial variant of the unselected artificial variant when a next character input associated with the ambiguous character-string is detected. 15. The device of claim 9 , wherein the processor is further structured to: make a second determination that a final set of characters of the suppressed offspring artificial variant corresponds with an N-gram object associated with a frequency object having a frequency value above a predetermined threshold; and based on the second determination, output the suppressed offspring artificial variant.

8. The method of claim 1 , wherein providing the additional information includes providing a notification to at least one of the recipients.

8. The method of claim 1 , wherein providing the additional information includes providing a notification to at least one of the recipients. 10. The method of claim 8 , wherein the notification is the message with the one or more vague terms replaced with the additional information.

1. A computer-implemented method to generate cumulative metric data for a test in a test environment, the method comprising: specifying, from within the test environment, a plurality of test elements within an iterations part of the test, the plurality of test elements including: a first test element being a simulation model having a block property, the simulation model executed from within a second environment that is separate from the test environment, and a second test element that is not a simulation model, the second test element being executable; generating, from within the test environment, at least one test condition for the test, the at least one test condition specifying a number of values for the block property of the simulation model; specifying at least one metric setting for the simulation model; defining a test variable within the test environment; mapping, from within the test environment, the at least one metric setting of the simulation model to the test variable; running, by a computer, the test from within the test environment such that the simulation model is executed within the second environment for a plurality of iterations based on the number of block property values specified in the at least one test condition, and the second test element is executed for the plurality of iterations; generating, during each iteration of the simulation model, metric data based on the at least one metric setting for the simulation model, the metric data generated within the second environment; assigning the metric data generated in the second environment to the test variable of the test environment as a result of the mapping of the at least one metric setting of the simulation model to the test variable so that the metric data from the iterations of the simulation model is accumulated; and providing access to the accumulated metric data from within the test environment.

1. A computer-implemented method to generate cumulative metric data for a test in a test environment, the method comprising: specifying, from within the test environment, a plurality of test elements within an iterations part of the test, the plurality of test elements including: a first test element being a simulation model having a block property, the simulation model executed from within a second environment that is separate from the test environment, and a second test element that is not a simulation model, the second test element being executable; generating, from within the test environment, at least one test condition for the test, the at least one test condition specifying a number of values for the block property of the simulation model; specifying at least one metric setting for the simulation model; defining a test variable within the test environment; mapping, from within the test environment, the at least one metric setting of the simulation model to the test variable; running, by a computer, the test from within the test environment such that the simulation model is executed within the second environment for a plurality of iterations based on the number of block property values specified in the at least one test condition, and the second test element is executed for the plurality of iterations; generating, during each iteration of the simulation model, metric data based on the at least one metric setting for the simulation model, the metric data generated within the second environment; assigning the metric data generated in the second environment to the test variable of the test environment as a result of the mapping of the at least one metric setting of the simulation model to the test variable so that the metric data from the iterations of the simulation model is accumulated; and providing access to the accumulated metric data from within the test environment. 12. The method as in claim 1 , wherein the simulation model is generated with a matrix-based mathematical programming language, a graphical modeling environment, a graphical language, a text-based language, or a text-based modeling language.

1. A method for use in connection with delivering assets to users of a broadcast network, the broadcast network primarily involving synchronized distribution of broadcast content to multiple users, the method comprising: receiving a broadcast content stream at a UED of a network user; receiving a subset of assets at the UED in conjunction with the broadcast content stream, the subset of assets identified by a network interface upstream in the broadcast network with respect to the UED by: monitoring textual information associated with said broadcast content stream; calculating a goodness of fit value for each of the assets according to a matching between the textual information and textual constraints associated with the assets; and identifying the subset of assets as having the highest respective goodness of fit values; determining targeting criteria corresponding to each of the subset of assets; selecting, at the UED, one of the subset of assets for an asset delivery spot as a function of the targeting criteria; and delivering the selected one of the subset of assets via the UED during the asset delivery spot.

1. A method for use in connection with delivering assets to users of a broadcast network, the broadcast network primarily involving synchronized distribution of broadcast content to multiple users, the method comprising: receiving a broadcast content stream at a UED of a network user; receiving a subset of assets at the UED in conjunction with the broadcast content stream, the subset of assets identified by a network interface upstream in the broadcast network with respect to the UED by: monitoring textual information associated with said broadcast content stream; calculating a goodness of fit value for each of the assets according to a matching between the textual information and textual constraints associated with the assets; and identifying the subset of assets as having the highest respective goodness of fit values; determining targeting criteria corresponding to each of the subset of assets; selecting, at the UED, one of the subset of assets for an asset delivery spot as a function of the targeting criteria; and delivering the selected one of the subset of assets via the UED during the asset delivery spot. 11. The method of claim 1 , wherein delivering comprises: delivering the selected one of the subset of assets via the UED during the asset delivery spot from a content stream including the programming.

23. The system of claim 22 , further operable to perform operations comprising: receiving a search query; identifying resources responsive to the search query; generating initial search results identifying the resources responsive to the search query; filtering the initial search results based on resources corresponding to entries in the list to produce filtered search results; and presenting filtered search results in response to the received search query.

23. The system of claim 22 , further operable to perform operations comprising: receiving a search query; identifying resources responsive to the search query; generating initial search results identifying the resources responsive to the search query; filtering the initial search results based on resources corresponding to entries in the list to produce filtered search results; and presenting filtered search results in response to the received search query. 25. The system of claim 23 , where filtering includes removing search results that do not match entries in the list.

8. A system comprising: a memory; and one or more processors coupled to the memory, the one or more processors configured to: receive a request to remove a news item from a list of news items, the list of news items being presented based on receiving a search query; remove the requested news item; responsive to the request, automatically remove news items with content similar to content of the requested news item; form an updated list of news items, based on the removing the requested news item and the removing news items with content similar to content of the requested news item; and provide for presentation the updated list of news items.

8. A system comprising: a memory; and one or more processors coupled to the memory, the one or more processors configured to: receive a request to remove a news item from a list of news items, the list of news items being presented based on receiving a search query; remove the requested news item; responsive to the request, automatically remove news items with content similar to content of the requested news item; form an updated list of news items, based on the removing the requested news item and the removing news items with content similar to content of the requested news item; and provide for presentation the updated list of news items. 9. The system of claim 8 , where the one or more processors are further to: prevent the requested news item and the news items with content similar to the content of the requested news item from being presented based on receiving a subsequent search query.

1. A method implemented by a computing device configured to expose speech engine features via a word training interface, the method comprising: exposing, via the interface, speech engine features for one or more speech engines to a plurality of independent applications wherein the speech engine features comprise one or more features for word training to train a word; receiving, via the interface, a call issued by one of the plurality of independent applications to train a word using one of the one or more speech engines; and, after training the word, receiving, via the interface, a call issued by the one of the plurality of independent applications for adding or replacing information associated with the word in a lexicon associated with at least the one independent applications, the lexicon stored in memory of the computing device and for use during speech recognition.

1. A method implemented by a computing device configured to expose speech engine features via a word training interface, the method comprising: exposing, via the interface, speech engine features for one or more speech engines to a plurality of independent applications wherein the speech engine features comprise one or more features for word training to train a word; receiving, via the interface, a call issued by one of the plurality of independent applications to train a word using one of the one or more speech engines; and, after training the word, receiving, via the interface, a call issued by the one of the plurality of independent applications for adding or replacing information associated with the word in a lexicon associated with at least the one independent applications, the lexicon stored in memory of the computing device and for use during speech recognition. 4. The method of claim 1 comprising receiving a call from a speech server, the call issued by one of the plurality of independent applications and having a parameter; parsing the call to retrieve the parameter; and communicating the parameter to one or the one or more speech engines.

2. The method of claim 1 , wherein the generating comprises extracting one or more search criteria of the context search query from the associated information.

2. The method of claim 1 , wherein the generating comprises extracting one or more search criteria of the context search query from the associated information. 3. The method of claim 2 , wherein the extracting comprises obtaining search criteria from metadata associated with the at least one media object.

15. A non-transitory computer readable storage medium, comprising executable instructions to: supply, by an action framework to a client, a graphical user interface component with an embedded control associated with an action defined by a workflow performed by executable instructions, the action framework being interposed between the client and a business intelligence (BI) platform; identify, by the action framework activation of the embedded control by a user at the client, wherein the activation invokes the action in an action context, wherein the action comprises the workflow performed by executable instructions in a software application and the action context characterizes conditions associated with the software application, the workflow comprising a plurality of actions; augment, by the action framework, the request with an action context characterizing a set of conditions under which the action is requested; form, by the BI platform, a query to a metadata source for the action, wherein the query includes: a first parameter based on the rights of the user, and a second parameter based on a criterion in a request for the action; receive, by the action framework from the BI platform, a set of results from the query, wherein the set of results from the query includes metadata for a suitable action; retrieve, by the action framework, a graphical user interface element using the metadata for the suitable action; insert, by the action framework at the client, the graphical user interface element into a portion of a graphical user interface that is used to invoke the workflow performed by the executable instructions; and return, by the action framework a the client, the metadata and the graphical user interface.

15. A non-transitory computer readable storage medium, comprising executable instructions to: supply, by an action framework to a client, a graphical user interface component with an embedded control associated with an action defined by a workflow performed by executable instructions, the action framework being interposed between the client and a business intelligence (BI) platform; identify, by the action framework activation of the embedded control by a user at the client, wherein the activation invokes the action in an action context, wherein the action comprises the workflow performed by executable instructions in a software application and the action context characterizes conditions associated with the software application, the workflow comprising a plurality of actions; augment, by the action framework, the request with an action context characterizing a set of conditions under which the action is requested; form, by the BI platform, a query to a metadata source for the action, wherein the query includes: a first parameter based on the rights of the user, and a second parameter based on a criterion in a request for the action; receive, by the action framework from the BI platform, a set of results from the query, wherein the set of results from the query includes metadata for a suitable action; retrieve, by the action framework, a graphical user interface element using the metadata for the suitable action; insert, by the action framework at the client, the graphical user interface element into a portion of a graphical user interface that is used to invoke the workflow performed by the executable instructions; and return, by the action framework a the client, the metadata and the graphical user interface. 16. The computer readable storage medium of claim 15 wherein the request specifics target content.

1. A computer-implemented method for building and viewing an interactive multimedia document comprising: determining metadata describing a location for a media file portion within a media file; embedding a reference within a text portion of the interactive multimedia document, the reference including the metadata; interpreting the metadata upon selection of the reference; and displaying the media file portion over the interactive multimedia document based on the interpreted metadata.

1. A computer-implemented method for building and viewing an interactive multimedia document comprising: determining metadata describing a location for a media file portion within a media file; embedding a reference within a text portion of the interactive multimedia document, the reference including the metadata; interpreting the metadata upon selection of the reference; and displaying the media file portion over the interactive multimedia document based on the interpreted metadata. 8. The computer-implemented method of claim 1 , wherein selection of the reference includes one or more of a roll over action or a clicking action of a mouse device.

1. A method for deducing meaning from a natural language input comprising the steps of: (a) receiving an ordered string of separate word objects of a selected language, where each of said word objects includes at least one alphanumeric character and is delimited from an adjacent word object, said ordered string having a length equal to the number of said word objects and having a natural language meaning; (b) selecting a word window having a length that is initially at least two and that is no greater than said length of said ordered string; (c) successively moving said word window along said ordered string, analyzing the meaning of the substring of word objects that fall within said word window, and removing said substring from said ordered string if said substring has a recognized meaning, until all substrings of said ordered string that fit within said window have been analyzed; (d) reducing said word window length; and, (e) repeating steps (c) and (d) until only an unrecognized residual of word objects of said ordered string remains.

1. A method for deducing meaning from a natural language input comprising the steps of: (a) receiving an ordered string of separate word objects of a selected language, where each of said word objects includes at least one alphanumeric character and is delimited from an adjacent word object, said ordered string having a length equal to the number of said word objects and having a natural language meaning; (b) selecting a word window having a length that is initially at least two and that is no greater than said length of said ordered string; (c) successively moving said word window along said ordered string, analyzing the meaning of the substring of word objects that fall within said word window, and removing said substring from said ordered string if said substring has a recognized meaning, until all substrings of said ordered string that fit within said window have been analyzed; (d) reducing said word window length; and, (e) repeating steps (c) and (d) until only an unrecognized residual of word objects of said ordered string remains. 4. A method as recited in claim 1 wherein said step of determining a word window length includes setting said word window length to said length of said ordered string.

1. A system for converting visual illustrations on paper and associated magnetic media retained text and tabulation typesetting data of a printed publication of articles, into universally outputable digital data form retained in master memory, comprising: graphics locator means for determining the insertion locations referenced within said text and tabulations typesetting data representing the positioning of said visual illustrations; scanning means for converting said visual illustrations to digital graphic data; means for generating graphic property data representing the graphics size characteristics of said digital graphic data; means for providing font size data for the text characters represented by said text typesetting data; means for providing font image defining data; formatting means responsive to said insertion location, said text typesetting data, said graphic property data and said font size data for generating device independent formatted page files; and mastering means responsive to said digital graphic data, said device independent formatted page files, and said font image defining data for deriving said universally outputable digital data retained within said master memory.

1. A system for converting visual illustrations on paper and associated magnetic media retained text and tabulation typesetting data of a printed publication of articles, into universally outputable digital data form retained in master memory, comprising: graphics locator means for determining the insertion locations referenced within said text and tabulations typesetting data representing the positioning of said visual illustrations; scanning means for converting said visual illustrations to digital graphic data; means for generating graphic property data representing the graphics size characteristics of said digital graphic data; means for providing font size data for the text characters represented by said text typesetting data; means for providing font image defining data; formatting means responsive to said insertion location, said text typesetting data, said graphic property data and said font size data for generating device independent formatted page files; and mastering means responsive to said digital graphic data, said device independent formatted page files, and said font image defining data for deriving said universally outputable digital data retained within said master memory. 2. The system of claim 1 including: means for altering those portions of said text typesetting data not configured with standardized general mark-up language to SGML configured data incorporating standardized general mark-up language; and said formatting means is responsive to said SGML configured data as said text typesetting data.

9. The method of claim 1 , further comprising: receiving a revised version of the first file in the first file format; converting the revised version of the first file to a first revised file converted format; removing conversion errors from the first revised file in the first file converted format; applying an algorithm to the first revised file in the first file converted format to produce a third file; running a quality control check of the third file; applying a processing program to the third file; comparing the third file to the second file to produce a fourth file; and generating a revised version of the submittal register based on the applied processing program to the fourth file.

9. The method of claim 1 , further comprising: receiving a revised version of the first file in the first file format; converting the revised version of the first file to a first revised file converted format; removing conversion errors from the first revised file in the first file converted format; applying an algorithm to the first revised file in the first file converted format to produce a third file; running a quality control check of the third file; applying a processing program to the third file; comparing the third file to the second file to produce a fourth file; and generating a revised version of the submittal register based on the applied processing program to the fourth file. 10. The method of claim 9 , wherein the fourth file includes markers showing changes between the first file and the revised version of the first file.

16. A tangible storage medium comprising instructions which when executed by a digital processor implement natural language processing of a text input comprising: processing the text to identify candidate titles of works; identifying verbs which are used to introduce direct speech; filtering the candidate titles of works to remove candidate titles of works that are determined to be citations of direct speech from the candidate titles of works, the filtering comprising filtering out expressions linked to a verb identified as being one of the verbs which are used to introduce direct speech; comparing candidate titles of works with a knowledge base which identifies titles of works; and annotating text which includes a candidate title of a work for which a match is found in the knowledge base.

16. A tangible storage medium comprising instructions which when executed by a digital processor implement natural language processing of a text input comprising: processing the text to identify candidate titles of works; identifying verbs which are used to introduce direct speech; filtering the candidate titles of works to remove candidate titles of works that are determined to be citations of direct speech from the candidate titles of works, the filtering comprising filtering out expressions linked to a verb identified as being one of the verbs which are used to introduce direct speech; comparing candidate titles of works with a knowledge base which identifies titles of works; and annotating text which includes a candidate title of a work for which a match is found in the knowledge base. 17. The storage medium of claim 16 , wherein the instructions for annotating the text comprise instructions for identifying the candidate title of the work as a nominative unit.

1. A method of providing navigation on an electronic device comprising a display screen, the method comprising: receiving a request to navigate to a destination; identifying a plurality of routes from a current location of the electronic device to the destination based on the received request; when the request is not a verbal request and the device is in an unlocked mode, (i) presenting the plurality of routes to a user to select one of the plurality of routes, (ii) receiving a selection of one of the routes, and (iii) providing navigational directions on the electronic device from the current location of the electronic device to the destination through the selected route; and when the request is a verbal request and the device is in a locked mode, (i) automatically selecting a single route from the plurality of routes without user input, (ii) displaying a map on the display screen with an overview of the selected route on the map, and (iii) after a predetermined delay and without any additional user input, displaying an animation for transitioning from displaying the overview of the selected route to providing navigational directions on the electronic device from the current location of the electronic device to the destination through the selected route, wherein the overview of the selected route comprises a representation of the entire route that is displayed on the map from the current location to the destination of the route.

1. A method of providing navigation on an electronic device comprising a display screen, the method comprising: receiving a request to navigate to a destination; identifying a plurality of routes from a current location of the electronic device to the destination based on the received request; when the request is not a verbal request and the device is in an unlocked mode, (i) presenting the plurality of routes to a user to select one of the plurality of routes, (ii) receiving a selection of one of the routes, and (iii) providing navigational directions on the electronic device from the current location of the electronic device to the destination through the selected route; and when the request is a verbal request and the device is in a locked mode, (i) automatically selecting a single route from the plurality of routes without user input, (ii) displaying a map on the display screen with an overview of the selected route on the map, and (iii) after a predetermined delay and without any additional user input, displaying an animation for transitioning from displaying the overview of the selected route to providing navigational directions on the electronic device from the current location of the electronic device to the destination through the selected route, wherein the overview of the selected route comprises a representation of the entire route that is displayed on the map from the current location to the destination of the route. 12. The method of claim 1 further comprising: converting a received verbal request to text; and displaying the text on the display screen in order to show how the verbal request is interpreted by the device.

9. The system of claim 7 , wherein the one or more predefined components associated with the detected in-game event includes screenshots, audio, video or text associated with the detected in-game event.

9. The system of claim 7 , wherein the one or more predefined components associated with the detected in-game event includes screenshots, audio, video or text associated with the detected in-game event. 10. The system of claim 9 , wherein the received one or more edits based on user input includes user modifications to the screenshots, audio, video or text associated with the detected in-game event.

27. The method of claim 14 further comprising the step of real-time retrieval of previously entered information during user input using fuzzy-logic to locate contextually consistent prior data to permit a user to select all or portions of the previously entered information to facilitate reuse of existing data during new data entry, to ensure consistency of expression, and to facilitate automated translation.

27. The method of claim 14 further comprising the step of real-time retrieval of previously entered information during user input using fuzzy-logic to locate contextually consistent prior data to permit a user to select all or portions of the previously entered information to facilitate reuse of existing data during new data entry, to ensure consistency of expression, and to facilitate automated translation. 28. The method of claim 27 wherein context is narrowed by comparing similarity of information type definition and determining the semantic distance between elements in the multi-dimensional database matrix based on axes and level within any sub-trees on the axes using predetermined distance parameters based on definitions of axis entries.

5. The storage medium of claim 2 wherein the local intent value comprises determining the local intent at different location bands.

5. The storage medium of claim 2 wherein the local intent value comprises determining the local intent at different location bands. 6. The storage medium of claim 5 further comprising: categorizing the location terms into the location bands; computing the frequency in each of the location bands for the root terms from the plurality of queries; and determining the probability that the root terms appear in each of the location bands.

1. A method for incorporating multimedia content into messages handled by a mobile device, said method comprising: obtaining a message being exchanged between said mobile device and one or more other entities in a data communication system; examining content in said message to determine if one or more portions of said content in said message match predetermined criteria related to the relevance of said content to multimedia content; using one or more profiles associated with a user of said mobile device to determine if the number of matches can be reduced according to the relevance of respective ones of said matches to said user and, if so, removing one or more of said matches; for each match, identifying particular multimedia content to be associated with the corresponding one of said one or more portions of said message, said multimedia content configured to be accessible to said mobile device through a selection associated with said corresponding one of said one or more portions of said content; and modifying said message to include, for each match, a linking mechanism visually identifiable with said corresponding one of said one or more portions, wherein said linking mechanism is configured to reveal said particular multimedia content upon selection thereof.

1. A method for incorporating multimedia content into messages handled by a mobile device, said method comprising: obtaining a message being exchanged between said mobile device and one or more other entities in a data communication system; examining content in said message to determine if one or more portions of said content in said message match predetermined criteria related to the relevance of said content to multimedia content; using one or more profiles associated with a user of said mobile device to determine if the number of matches can be reduced according to the relevance of respective ones of said matches to said user and, if so, removing one or more of said matches; for each match, identifying particular multimedia content to be associated with the corresponding one of said one or more portions of said message, said multimedia content configured to be accessible to said mobile device through a selection associated with said corresponding one of said one or more portions of said content; and modifying said message to include, for each match, a linking mechanism visually identifiable with said corresponding one of said one or more portions, wherein said linking mechanism is configured to reveal said particular multimedia content upon selection thereof. 5. The method according to claim 1 wherein the method is performed at said mobile device.

27. A ranking system comprising: a memory comprising at least one negation term and at least one negation rule; a processor comprising a document ranking application comprising modules executable by the processor to rank documents retrieved from a data source in response to a search request, the document ranking application comprising: a term frequency module to: query the data source to identify a plurality of documents that each comprises a key term, the key term matching a search term in the search request; and determine a corresponding term frequency value for the key term in each of the plurality of documents, the term frequency value comprising a total number of occurrences of the key term in a particular document; a negation module to: retrieve the at least one negation term and the at least one negation rule from the memory; compare the at least one negation term according to the at least one negation rule to other terms in each document that are within a selected proximity of each occurrence of the key term to determine if each occurrence of the key term has a negative context; determine that the at least one negation term matches another term within the selected proximity of the particular occurrence of the key term according to the at least one negation rule and exclude a particular occurrence of the key term in at least one document for having the negative context; and determine a corresponding term weight value for the key term in each document based on each occurrence of the key term that has not been excluded; a ranking module to determine a corresponding relevancy ranking value for each document based on the corresponding term frequency value and corresponding term weight value; and a user interface module to generate a list of document data for display, the list identifying each document of the plurality of documents in order based on the corresponding relevancy ranking value of each document.

27. A ranking system comprising: a memory comprising at least one negation term and at least one negation rule; a processor comprising a document ranking application comprising modules executable by the processor to rank documents retrieved from a data source in response to a search request, the document ranking application comprising: a term frequency module to: query the data source to identify a plurality of documents that each comprises a key term, the key term matching a search term in the search request; and determine a corresponding term frequency value for the key term in each of the plurality of documents, the term frequency value comprising a total number of occurrences of the key term in a particular document; a negation module to: retrieve the at least one negation term and the at least one negation rule from the memory; compare the at least one negation term according to the at least one negation rule to other terms in each document that are within a selected proximity of each occurrence of the key term to determine if each occurrence of the key term has a negative context; determine that the at least one negation term matches another term within the selected proximity of the particular occurrence of the key term according to the at least one negation rule and exclude a particular occurrence of the key term in at least one document for having the negative context; and determine a corresponding term weight value for the key term in each document based on each occurrence of the key term that has not been excluded; a ranking module to determine a corresponding relevancy ranking value for each document based on the corresponding term frequency value and corresponding term weight value; and a user interface module to generate a list of document data for display, the list identifying each document of the plurality of documents in order based on the corresponding relevancy ranking value of each document. 35. The system of claim 27 wherein the user interface module generates the list of document data to identify each of the plurality of documents in descending order based on the corresponding relevancy ranking value of each document.

13. The system of claim 10 , further comprising instructions to perform the operations of: identifying a set of query suggestions for the partial query; and modifying the set of query suggestions to include the query completion template, and wherein the instructions to perform the operations of providing for display the query completion template include instructions to perform the operations of providing for display the modified set of query suggestions.

13. The system of claim 10 , further comprising instructions to perform the operations of: identifying a set of query suggestions for the partial query; and modifying the set of query suggestions to include the query completion template, and wherein the instructions to perform the operations of providing for display the query completion template include instructions to perform the operations of providing for display the modified set of query suggestions. 14. The system of claim 13 , further comprising instructions to perform the operations of: maintaining a database of query completion templates, wherein each query completion template in the database is associated with a list of terms corresponding to a category of information; identifying query terms within the set of query suggestions; and selecting the query completion template for display from the database of query completion templates based on one or more of the query terms within the set of query suggestions appearing within the list of terms associated with the selected query completion template.

1. A computer-implemented process for creating a personal name directory which can be queried to suggest spelling corrections for personal names, comprising: using a computer comprising a processing unit and a memory to perform the following process actions: computing a hash function that maps any personal name in a particular language and misspellings thereof to similar binary codewords; and for each personal name in a directory of personal names in said particular language, using said hash function to produce one or more binary codewords and associating the said codeword or codewords with the personal name.

1. A computer-implemented process for creating a personal name directory which can be queried to suggest spelling corrections for personal names, comprising: using a computer comprising a processing unit and a memory to perform the following process actions: computing a hash function that maps any personal name in a particular language and misspellings thereof to similar binary codewords; and for each personal name in a directory of personal names in said particular language, using said hash function to produce one or more binary codewords and associating the said codeword or codewords with the personal name. 8. The process of claim 1 , wherein the process action of using said hash function to produce one or more binary codewords and associating the codeword or codewords with the personal name, for each personal name in a directory of personal names in said particular language, comprises the actions of: segmenting each personal name in the personal name directory into constituent tokens, wherein each token corresponds to a word in the personal name comprising a continuous string of characters unbroken by a space and whose characters are consistent with the types of characters employed in personal names in said particular language; identifying a set of unique tokens from the constituent tokens of the personal names from the personal name directory; generating an index which for each token in the set of unique tokens identifies all the personal names in the personal name directory that have that token as one of its constituent tokens; applying said hash function to each unique token to produce a binary codeword representation thereof; and associating the binary codeword produced for each unique token with that token in said index.

8. A computer program product for providing a semi-supervised data integration model for named entity classification from a first repository of entity information in view of an auxiliary repository of classification assistance data, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code being executable by a computer to perform a method comprising: comparing training data to named entity candidates taken from the first repository, thereby forming a positive training seed set in view of identified commonality between the training data and the named entity candidates; in view of the positive training seed set, populating a decision tree; in view of populating the decision tree, creating classification rules for classifying the named entity candidates; sampling a number of entities from the named entity candidates; in view of the classification rules, labeling the sampled entities as positive examples and/or negative examples; in view of the positive examples and the auxiliary repository, updating the positive training seed set to include identified commonality between the positive examples and the auxiliary repository; in view of the negative examples and the auxiliary repository, updating a negative training seed set to include negative examples which lack commonality with the auxiliary repository; and in view of both the updated positive and negative training seed sets, updating the decision tree and the classification rules.

8. A computer program product for providing a semi-supervised data integration model for named entity classification from a first repository of entity information in view of an auxiliary repository of classification assistance data, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code being executable by a computer to perform a method comprising: comparing training data to named entity candidates taken from the first repository, thereby forming a positive training seed set in view of identified commonality between the training data and the named entity candidates; in view of the positive training seed set, populating a decision tree; in view of populating the decision tree, creating classification rules for classifying the named entity candidates; sampling a number of entities from the named entity candidates; in view of the classification rules, labeling the sampled entities as positive examples and/or negative examples; in view of the positive examples and the auxiliary repository, updating the positive training seed set to include identified commonality between the positive examples and the auxiliary repository; in view of the negative examples and the auxiliary repository, updating a negative training seed set to include negative examples which lack commonality with the auxiliary repository; and in view of both the updated positive and negative training seed sets, updating the decision tree and the classification rules. 10. The computer program product of claim 8 , comprising: performing the method for each of a plurality of named entity types to determine the classification rules for each of the named entity types, wherein the training data comprise a plurality of data sources comprising only positive examples associated with each of the plurality of named entity types.

16. A computer program product as claimed in claim 14 wherein the target domain is a computer programming model; and the pattern class is a meta-class in an object-oriented model.

16. A computer program product as claimed in claim 14 wherein the target domain is a computer programming model; and the pattern class is a meta-class in an object-oriented model. 17. A computer program product as claimed in claim 16 wherein the target domain is a Unified Modeling Language 2 structure.

10. The system of claim 9 ; wherein the assertion group object is adapted to generate a cumulative score of information objects moved through the assertion gates for visualizing the level of evidence of the assertion.

10. The system of claim 9 ; wherein the assertion group object is adapted to generate a cumulative score of information objects moved through the assertion gates for visualizing the level of evidence of the assertion. 11. The system of claim 10 , wherein the cumulative score accounts for information objects moved through the nested assertion gates for visualizing the level of evidence of the assertion.

1. A machine-implemented method of albuming graphic elements, comprising: identifying candidate relative layouts of graphic elements on a page, wherein each of the candidate relative layouts describes a respective set of layout relationships among the graphic elements; generating for each of the candidate relative layouts a respective set of constraints describing the corresponding set of layout relationships among the graphic elements; determining a respective determinate layout of the graphic elements on the page from each set of constraints; and selecting one of the determinate layouts as a final layout of the graphic elements on the page.

1. A machine-implemented method of albuming graphic elements, comprising: identifying candidate relative layouts of graphic elements on a page, wherein each of the candidate relative layouts describes a respective set of layout relationships among the graphic elements; generating for each of the candidate relative layouts a respective set of constraints describing the corresponding set of layout relationships among the graphic elements; determining a respective determinate layout of the graphic elements on the page from each set of constraints; and selecting one of the determinate layouts as a final layout of the graphic elements on the page. 9. The method of claim 1 , wherein the generating comprises generating relative position constraints preserving relative positions of the graphic elements in each of the candidate relative layouts.

10. A machine learning method comprising: receiving, from a user device, a sequence of at least one letter; determining location information associated with the user device; mapping the received sequence of at least one letter and the location information with a database of multiple terms, the database relating a term to a stored sequence of at least one letter and a location range based on a historical correlation between the term and the stored sequence of at least one letter in the location range; providing a candidate term out of the multiple terms as corresponding to the received sequence of at least one letter based on the mapping; displaying the candidate term as corresponding to the received sequence of at least one letter; receiving a user feedback on the candidate term; and updating the database based on the user feedback.

10. A machine learning method comprising: receiving, from a user device, a sequence of at least one letter; determining location information associated with the user device; mapping the received sequence of at least one letter and the location information with a database of multiple terms, the database relating a term to a stored sequence of at least one letter and a location range based on a historical correlation between the term and the stored sequence of at least one letter in the location range; providing a candidate term out of the multiple terms as corresponding to the received sequence of at least one letter based on the mapping; displaying the candidate term as corresponding to the received sequence of at least one letter; receiving a user feedback on the candidate term; and updating the database based on the user feedback. 12. The machine learning method of claim 10 , wherein updating includes updating a utilization score of the candidate term as related to the received sequence of at least one letter in a location range that encloses the location information.

10. The method of claim 1 , wherein the presentation information source is based on at least one of: audio, visual, tactile information.

10. The method of claim 1 , wherein the presentation information source is based on at least one of: audio, visual, tactile information. 12. The method of claim 10 , wherein the visual information is at least one of video information, video capture of user gestures, textual information.

1. A sentence generating apparatus comprising: recording means for storing a plurality of idioms comprising a verb and having an intrinsic meaning, a plurality of words, a list of related words of said words, word classes of said words, and phonetics of said words; first word selecting means for reading out a first idiom from said recording means and for selecting a word contained in the first idiom as a first word; second word selecting means for reading out a word stored in said recording means and having a pronunciation that is the same as or analogous to said first word and being of the same word class as said first word, based on the phonetics and the word class of the recorded first word, and for selecting the read-out word as a second word; third word selecting means for reading out a next word stored in said recording means and having a semantic relationship with the second word, and selecting the next word as a third word, wherein the third word selecting means determines a semantic relationship of the next word with the second word based on a common word in the list of related words of the next word and the list of relating words of the second word stored in the recording means, and wherein, when no semantic relationship is found between the next word and the second word, the third word selecting means selects a second next word; idiom generating means for generating a second idiom by replacing the first word contained in the first idiom with the second word; and sentence generating means for generating a first sentence comprising the third word as a subject of the first sentence and the first idiom and for generating a second sentence comprising the third word as a subject of the second sentence and the second idiom.

1. A sentence generating apparatus comprising: recording means for storing a plurality of idioms comprising a verb and having an intrinsic meaning, a plurality of words, a list of related words of said words, word classes of said words, and phonetics of said words; first word selecting means for reading out a first idiom from said recording means and for selecting a word contained in the first idiom as a first word; second word selecting means for reading out a word stored in said recording means and having a pronunciation that is the same as or analogous to said first word and being of the same word class as said first word, based on the phonetics and the word class of the recorded first word, and for selecting the read-out word as a second word; third word selecting means for reading out a next word stored in said recording means and having a semantic relationship with the second word, and selecting the next word as a third word, wherein the third word selecting means determines a semantic relationship of the next word with the second word based on a common word in the list of related words of the next word and the list of relating words of the second word stored in the recording means, and wherein, when no semantic relationship is found between the next word and the second word, the third word selecting means selects a second next word; idiom generating means for generating a second idiom by replacing the first word contained in the first idiom with the second word; and sentence generating means for generating a first sentence comprising the third word as a subject of the first sentence and the first idiom and for generating a second sentence comprising the third word as a subject of the second sentence and the second idiom. 3. The sentence generating apparatus according to claim 1 wherein said recording means further has a plurality of adjectives pertinent to the recorded respective idioms; there being provided fourth word selecting means for reading out the adjectives pertinent to the selected idioms from said recording means and for selecting the adjectives as a fourth word; said sentence generating means generating said first sentence made up by said third word, the first idiom and the fourth word and also generating said second sentence made up by said third word, the second idiom and the fourth word.

41. A system for compressing information bearing input signals such as speech to reduce the information content thereof without destroying the intelligibility thereof, said system comprising: input means adapted to receive said input signals; means for Mozer phase adjusting said signals to produce equivalent signals having symmetric portions; and means for deleting selected redundant portions of said equivalent signals.

41. A system for compressing information bearing input signals such as speech to reduce the information content thereof without destroying the intelligibility thereof, said system comprising: input means adapted to receive said input signals; means for Mozer phase adjusting said signals to produce equivalent signals having symmetric portions; and means for deleting selected redundant portions of said equivalent signals. 50. The combination of claim 41 wherein said input signals are audio signals having phonemes and phoneme groups and further including means for deleting preselected signals representative of portions of particular phonemes and phoneme groups from said audio signals, said preselected signals corresponding to those portions lying between every nth pitch period, and wherein said generating means includes means for generating second instruction signals specifying said particular phonemes and phoneme groups so selected and identifying the corresponding values of n.

1. A method of processing an incoming telephone call, the method comprising: at a recipient telephone system, receiving the incoming call including speech; identifying when a Do-Not-Disturb option is set, the Do-Not-Disturb option identifying that a user has requested not to receive telephone calls; recording the incoming call in a voicemail system when the Do-Not-Disturb option is set; performing content analysis to identify content of the speech while recording the incoming call in the voicemail system when the Do-Not-Disturb option is set, the performance of the content analysis including performing speech recognition on the speech to obtain at least one reference word that is included in the speech; interrogating a reference database with the at least one reference word to identify an associated rule; and selectively overriding the Do-Not-Disturb option based on the associated rule.

1. A method of processing an incoming telephone call, the method comprising: at a recipient telephone system, receiving the incoming call including speech; identifying when a Do-Not-Disturb option is set, the Do-Not-Disturb option identifying that a user has requested not to receive telephone calls; recording the incoming call in a voicemail system when the Do-Not-Disturb option is set; performing content analysis to identify content of the speech while recording the incoming call in the voicemail system when the Do-Not-Disturb option is set, the performance of the content analysis including performing speech recognition on the speech to obtain at least one reference word that is included in the speech; interrogating a reference database with the at least one reference word to identify an associated rule; and selectively overriding the Do-Not-Disturb option based on the associated rule. 2. The method of claim 1 , which comprises conferencing in a voice path of the speech with a speech recognition module to perform the speech recognition.

15. The text processing method according to claim 14 , wherein the (b) step comprises deriving, based on the result of the determination in the (a) step, an extent to which the content of the homogeneous segment is included in the second text corresponding to the other first text which includes the homogeneous segment, further deriving, based on the derived extent, a degree to which each segment constituting the first text which is set as the analysis target should be described in the second text corresponding to the first text which is set as the analysis target, and performing the determination using the degree.

15. The text processing method according to claim 14 , wherein the (b) step comprises deriving, based on the result of the determination in the (a) step, an extent to which the content of the homogeneous segment is included in the second text corresponding to the other first text which includes the homogeneous segment, further deriving, based on the derived extent, a degree to which each segment constituting the first text which is set as the analysis target should be described in the second text corresponding to the first text which is set as the analysis target, and performing the determination using the degree. 16. The text processing method according to claim 15 , wherein the (m) step, in addition to the determination regarding the content of the homogeneous segment, comprises computing, for each of the plurality of segments constituting the first text which is set as the analysis target and for the homogeneous segment, an inclusion score representing a possibility of a content of the segment being included in the second text corresponding to the first text which includes the segment, and the (b) step comprises further deriving the degree using the inclusion score computed in the (m) step, such that the degree increase the higher the inclusion score.

1. A computer-implemented method comprising: determining, by a voice action system, that a software application installed on a user device is compatible with a new voice action, wherein the software application is different from the voice action system and the new voice action is specified by an application developer of the software application; determining, by the voice action system, that the software application installed on the user device is compatible with one or more other voice actions; identifying, by the voice action system, one or more trigger terms for triggering the software application to perform the new voice action; identifying, by the voice action system, one or more trigger terms for triggering the software application to perform the one or more other voice actions; ranking, by the voice action system, the new voice action and the one or more other voice actions; biasing, by the voice action system, an automatic speech recognizer to prefer the identified one or more trigger terms of the new voice action over the trigger terms of the one or more other voice actions, wherein the automatic speech recognizer is biased based at least on the ranking; obtaining, by the voice action system, a transcription of an utterance generated by the biased automatic speech recognizer; determining, by the voice action system, that the transcription of the utterance generated by the biased automatic speech recognizer includes a particular trigger term included in the identified one or more trigger terms; and triggering, by the voice action system, execution of the new voice action based at least on determining that the transcription of the utterance generated by the biased automatic speech recognizer includes the particular trigger term.

1. A computer-implemented method comprising: determining, by a voice action system, that a software application installed on a user device is compatible with a new voice action, wherein the software application is different from the voice action system and the new voice action is specified by an application developer of the software application; determining, by the voice action system, that the software application installed on the user device is compatible with one or more other voice actions; identifying, by the voice action system, one or more trigger terms for triggering the software application to perform the new voice action; identifying, by the voice action system, one or more trigger terms for triggering the software application to perform the one or more other voice actions; ranking, by the voice action system, the new voice action and the one or more other voice actions; biasing, by the voice action system, an automatic speech recognizer to prefer the identified one or more trigger terms of the new voice action over the trigger terms of the one or more other voice actions, wherein the automatic speech recognizer is biased based at least on the ranking; obtaining, by the voice action system, a transcription of an utterance generated by the biased automatic speech recognizer; determining, by the voice action system, that the transcription of the utterance generated by the biased automatic speech recognizer includes a particular trigger term included in the identified one or more trigger terms; and triggering, by the voice action system, execution of the new voice action based at least on determining that the transcription of the utterance generated by the biased automatic speech recognizer includes the particular trigger term. 2. The computer-implemented method of claim 1 , wherein biasing the automatic speech recognizer to prefer the identified one or more trigger terms of the new voice action over trigger terms of one or more other voice actions comprises adjusting a language model used by the automatic speech recognizer in performing speech recognition such that the automatic speech recognizer using the adjusted language model has an increased likelihood of detecting trigger terms of the new voice action.

1. A method for recording annotations in an electronic trading environment, the method comprising: receiving real time market data from an electronic exchange comprising a best bid price and a best ask price currently available for a tradeable object; displaying a first graphical interface at a client terminal, wherein the first graphical interface displays the real time market data as the real time market data is being received from the electronic exchange; providing a second graphical interface at the client terminal in relation to the first graphical interface, wherein the second graphical interface is used to record user annotations relative to the real time market data; receiving a first command from a user input device in relation to the first graphical interface to flag a current time as the real time market data is being received and displayed in the first graphical interface; responsive to receiving the first command, creating an incomplete annotation record that comprises the current time that was flagged; displaying an indicator associated with the flagged time that is selectable by a user input device to open the incomplete annotation record; receiving a second command to select the indicator from a user input device at a subsequent time to the flagged time to complete the incomplete annotation record; responsive to the selection of the indicator by the second command, displaying the incomplete annotation record on the second graphical interface; receiving user data corresponding to the flagged time for entry into the incomplete annotation record to create a completed annotation record; and storing the user data associated with the annotation record.

1. A method for recording annotations in an electronic trading environment, the method comprising: receiving real time market data from an electronic exchange comprising a best bid price and a best ask price currently available for a tradeable object; displaying a first graphical interface at a client terminal, wherein the first graphical interface displays the real time market data as the real time market data is being received from the electronic exchange; providing a second graphical interface at the client terminal in relation to the first graphical interface, wherein the second graphical interface is used to record user annotations relative to the real time market data; receiving a first command from a user input device in relation to the first graphical interface to flag a current time as the real time market data is being received and displayed in the first graphical interface; responsive to receiving the first command, creating an incomplete annotation record that comprises the current time that was flagged; displaying an indicator associated with the flagged time that is selectable by a user input device to open the incomplete annotation record; receiving a second command to select the indicator from a user input device at a subsequent time to the flagged time to complete the incomplete annotation record; responsive to the selection of the indicator by the second command, displaying the incomplete annotation record on the second graphical interface; receiving user data corresponding to the flagged time for entry into the incomplete annotation record to create a completed annotation record; and storing the user data associated with the annotation record. 2. The method of claim 1 , further comprising: displaying the second graphical interface in relation to the first graphical interface.

1. A computer-implemented method of constructing an object model reflective of structure of a document, from an unstructured document, comprising: scanning an unstructured markup language representation of the document for one or more markup language glyphs to generate a plurality of text runs, where the text runs comprise one or more semantically structured, selectable representations of the markup language glyphs; creating one or more semantic block containers comprising text runs that correspond to a same semantic block by determining which text runs correspond to the same semantic block; determining a logical structured order of the text runs within the respective one or more semantic blocks; determining an order of the respective one or more semantic blocks in the document; and saving the semantic blocks comprising the order of the text runs and the order of the one or more semantic blocks in the document as the object model to generate a logically structured document comprising semantically structured, selectable representations of the markup language.

1. A computer-implemented method of constructing an object model reflective of structure of a document, from an unstructured document, comprising: scanning an unstructured markup language representation of the document for one or more markup language glyphs to generate a plurality of text runs, where the text runs comprise one or more semantically structured, selectable representations of the markup language glyphs; creating one or more semantic block containers comprising text runs that correspond to a same semantic block by determining which text runs correspond to the same semantic block; determining a logical structured order of the text runs within the respective one or more semantic blocks; determining an order of the respective one or more semantic blocks in the document; and saving the semantic blocks comprising the order of the text runs and the order of the one or more semantic blocks in the document as the object model to generate a logically structured document comprising semantically structured, selectable representations of the markup language. 7. The method of claim 1 , comprising creating a new semantic block container for a current text run when the current text run does not correspond to an existing semantic block.

3. The information processing apparatus according to claim 1 , further comprising a group generation section configured to group together into a group two or more documents, among the plurality of documents, having a similarity greater than or equal to the first criterion, wherein the identification section is configured to identify the second document that belongs to the same group as that of the first document in response to the change made to the first document.

3. The information processing apparatus according to claim 1 , further comprising a group generation section configured to group together into a group two or more documents, among the plurality of documents, having a similarity greater than or equal to the first criterion, wherein the identification section is configured to identify the second document that belongs to the same group as that of the first document in response to the change made to the first document. 5. The information processing apparatus according to claim 3 , wherein, when a set of documents belonging to a first group becomes a subset of a set of documents belonging to a second group, the group generation section deletes the first group and integrates the first group into the second group.

1. A computer-implemented network structure, comprising: a memory that stores instructions to create: a first node that is a semantic Janus unit, wherein the first node possesses an existing time-variable state; a second node containing informational contents; and a link between the first node and the second node, wherein the link contains relational contents that describes the relationship between the first node and the second node, wherein the first node carries out operations on the second node and on the link, wherein the existing time-variable state determines which operations are carried out, and wherein a pattern in an image is recognized by carrying out the operations.

1. A computer-implemented network structure, comprising: a memory that stores instructions to create: a first node that is a semantic Janus unit, wherein the first node possesses an existing time-variable state; a second node containing informational contents; and a link between the first node and the second node, wherein the link contains relational contents that describes the relationship between the first node and the second node, wherein the first node carries out operations on the second node and on the link, wherein the existing time-variable state determines which operations are carried out, and wherein a pattern in an image is recognized by carrying out the operations. 7. The computer-implemented network structure of claim 1 , wherein the first node, the second node and the link are part of a semantic network machine within the computer-implemented network structure, wherein the time-variable state of the first node reflects the situation in the semantic network machine, and wherein the operations are focused on parts of the semantic network machine based on the situation in the semantic network machine.

15. An apparatus to encode auxiliary data into text data, comprising: a data unit group assignor to assign source data to one of a plurality of groups, the source data comprising text data; a symbol group assignor to assign a symbol to be added to the source data to the one of the plurality of groups; and a data unit encoder to generate encoded data by changing a first text character in the source data to be a second text character that is representative of the symbol and represents a same alphanumeric character or non-alphanumeric symbol as the first text character in the source data.

15. An apparatus to encode auxiliary data into text data, comprising: a data unit group assignor to assign source data to one of a plurality of groups, the source data comprising text data; a symbol group assignor to assign a symbol to be added to the source data to the one of the plurality of groups; and a data unit encoder to generate encoded data by changing a first text character in the source data to be a second text character that is representative of the symbol and represents a same alphanumeric character or non-alphanumeric symbol as the first text character in the source data. 18. An apparatus as defined in claim 15 , wherein the data unit encoder is to change the first text character in the source data to the second text character representative of the symbol by selectively replacing the first text character in the source data with the second text character.

13. A computer-implemented method of retrieving/identifying a document comprising text stored in a document repository comprising: storing, at a memory, a graphical structure comprising a first plurality of nodes each representing a person, and a second plurality of nodes each representing a document in the document repository, the nodes being connected by edges according to automatically observed interactions between the represented people and documents, at least some of the nodes having one or more annotations each denoting a topic, an interaction of the interactions at least partially based on at least one of: a consumption activity by a person represented by a first node of the first plurality of nodes of a document represented by a first node of the second plurality of nodes, or a relationship between a first person represented by the first node of the first plurality of nodes, and a second person represented by a second node of the first plurality of nodes; computing, at a processor, distances between nodes of the graphical structure using the topic annotations; receiving, at an input/output controller, an identifier of a user who is represented by one of the first plurality of nodes; and automatically identifying one or more documents from the document repository by using the identifier and using the computed distances between nodes.

13. A computer-implemented method of retrieving/identifying a document comprising text stored in a document repository comprising: storing, at a memory, a graphical structure comprising a first plurality of nodes each representing a person, and a second plurality of nodes each representing a document in the document repository, the nodes being connected by edges according to automatically observed interactions between the represented people and documents, at least some of the nodes having one or more annotations each denoting a topic, an interaction of the interactions at least partially based on at least one of: a consumption activity by a person represented by a first node of the first plurality of nodes of a document represented by a first node of the second plurality of nodes, or a relationship between a first person represented by the first node of the first plurality of nodes, and a second person represented by a second node of the first plurality of nodes; computing, at a processor, distances between nodes of the graphical structure using the topic annotations; receiving, at an input/output controller, an identifier of a user who is represented by one of the first plurality of nodes; and automatically identifying one or more documents from the document repository by using the identifier and using the computed distances between nodes. 14. The method of claim 13 comprising storing the graphical structure with annotations to nodes at least some of which are words which do not occur in the text of the document represented by the node.

23. A non-transitory computer-readable storage medium which stores a database management program for causing a computer to function as a groupware server of a groupware which is connectable, via a network, to an image forming apparatus that functions as a groupware terminal, said groupware server comprising plural document databases configured to store document data, and an attribute database configured to store multiple lists of different plural kinds of attribute information, each kind of the attribute information being setting items unique to each document database, the setting items being required to be set when storing the document data in the document database which when executed by the computer, causes the computer to perform a method comprising: communicating with the image forming apparatus via the network; and writing the document data and the attribute information to said at least one document database, wherein: said communicating causes the computer to send a certain one of the list of attribute information from the attribute database to the image forming apparatus in response to an acquisition request for the certain list of attribute information received from the image forming apparatus, the image forming apparatus including a display screen that displays an input screen to set the unique predetermined setting item based on the information related to the format included in the document database, and said writing causes the computer to write the document data in said at least one document database in response to a write request for the document data having the certain list of attribute information set with the predetermined setting item added to the document data, received by said communicating from the image forming apparatus.

23. A non-transitory computer-readable storage medium which stores a database management program for causing a computer to function as a groupware server of a groupware which is connectable, via a network, to an image forming apparatus that functions as a groupware terminal, said groupware server comprising plural document databases configured to store document data, and an attribute database configured to store multiple lists of different plural kinds of attribute information, each kind of the attribute information being setting items unique to each document database, the setting items being required to be set when storing the document data in the document database which when executed by the computer, causes the computer to perform a method comprising: communicating with the image forming apparatus via the network; and writing the document data and the attribute information to said at least one document database, wherein: said communicating causes the computer to send a certain one of the list of attribute information from the attribute database to the image forming apparatus in response to an acquisition request for the certain list of attribute information received from the image forming apparatus, the image forming apparatus including a display screen that displays an input screen to set the unique predetermined setting item based on the information related to the format included in the document database, and said writing causes the computer to write the document data in said at least one document database in response to a write request for the document data having the certain list of attribute information set with the predetermined setting item added to the document data, received by said communicating from the image forming apparatus. 24. The non-transitory computer-readable storage medium according to claim 23 , wherein said groupware server comprises a user information database configured to store user information that is used to log-in to the groupware, said image forming apparatus comprises a storage medium read part configured to read information from a storage medium recorded with the user information, and said groupware server authenticates the user information when user information matching the user information read by the storage medium read part exists in the user information database.

20. The method of claim 1 , wherein the one or more user input events are provided by a first type of user, the first type of user being associated with one of: a user login, a user record, and cookie.

20. The method of claim 1 , wherein the one or more user input events are provided by a first type of user, the first type of user being associated with one of: a user login, a user record, and cookie. 21. The method of claim 20 , wherein the one or more user input events from the first type of user are used to influence the relevance score of documents to present to a second type of user that has not provided at least one user input event.

5. The method of claim 1 wherein the scoring techniques identify different keywords of a document and calculate significance of sentences based on the identified keywords.

5. The method of claim 1 wherein the scoring techniques identify different keywords of a document and calculate significance of sentences based on the identified keywords. 9. The method of claim 5 wherein a document includes posts and a scoring technique identifies a word of a document as a keyword based on whether a word of a current post occurs in a previous post.

15. The non-transitory storage medium of claim 11 , wherein said comparing comprises determining a count of other standard name formats in said database that are substantially similar to said standard name format of said distinct name, and matching said distinct mane to a most frequently occurring standard name format.

15. The non-transitory storage medium of claim 11 , wherein said comparing comprises determining a count of other standard name formats in said database that are substantially similar to said standard name format of said distinct name, and matching said distinct mane to a most frequently occurring standard name format. 16. The non-transitory storage medium of claim 15 , wherein said matching comprises, upon the count of said other standard name formats exceeding a predetermined number, fuzzy matching said standard name format to the standard names to identify a matching standard name, and assigning the matching standard name to said distinct name as the standard name of said entity.

15. A computer-readable memory device with instructions stored thereon to generate automatic command shell cmdlet code based on a schema, the instructions comprising: receiving the schema that includes one or more of: element declarations, attribute declarations, simple type definitions and complex type definitions, the schema components belonging to a target namespace; reading the schema to create a model for classes, wherein the classes validate constraints within the schema; optimizing the model to translate the schema to an application programming interface (API); and inserting a plug-in to the model to generate a cmdlet for a command shell based on the optimized model by: disabling generation of a default code for the cmdlet, using the plug-in; and generating a plug-in code for the cmdlet, using the plug-in, wherein the cmdlet manipulates data that is structured based on the classes defined by the optimized model at runtime.

15. A computer-readable memory device with instructions stored thereon to generate automatic command shell cmdlet code based on a schema, the instructions comprising: receiving the schema that includes one or more of: element declarations, attribute declarations, simple type definitions and complex type definitions, the schema components belonging to a target namespace; reading the schema to create a model for classes, wherein the classes validate constraints within the schema; optimizing the model to translate the schema to an application programming interface (API); and inserting a plug-in to the model to generate a cmdlet for a command shell based on the optimized model by: disabling generation of a default code for the cmdlet, using the plug-in; and generating a plug-in code for the cmdlet, using the plug-in, wherein the cmdlet manipulates data that is structured based on the classes defined by the optimized model at runtime. 16. The computer-readable memory device of claim 15 , wherein the instructions further comprise: manipulating the data through the API.

1. A method for improving the usability of product feedback data comprising: receiving of a plurality of product feedback search parameters by an intelligent product feedback analytics tool, wherein said plurality of product feedback search parameters pertain to at least one of a product and a group of products; performing a search on plurality of product feedback data sources using the product feedback search parameters to gather product feedback; obtaining a plurality of product feedback search results applicable to the plurality of product feedback search parameters, wherein each product feedback search result comprises at least one of a rating value upon a rating scale and feedback content in a textual format; for each product represented in the obtained plurality of product feedback search results, synthesizing a composite rating value for each rating category of the rating scale defined for the intelligent product feedback analytics tool from rating values contained in product feedback search results that are applicable to the product, wherein the synthesizing comprises: converting the rating value for each product feedback search result to an equivalent rating value with respect to the rating scale defined for the intelligent product feedback analytics tool; assigning each product feedback search result to a rating category of the rating scale defined for the intelligent product feedback analytics tool, wherein the converted rating value of a product feedback search result falls within a rating value range defined for the rating category to which it is assigned; and expressing a quantity of product feedback search results assigned to each rating category as a percentage of a total quantity of product feedback search results that are applicable to the product; for each product represented in the obtained plurality of product feedback search results, analyzing the plurality of product feedback search results for at least one analytic parameter, wherein each analytic parameter represents a commonality among a subset of the product feedback search results that are applicable to the product, wherein said analysis utilizes natural language processing techniques; and presenting the plurality of product feedback search results, composite rating values, and the at least one analytic parameter in an organized manner within a user interface, wherein the at least one analytic parameter presented provides a context for the corresponding composite rating value.

1. A method for improving the usability of product feedback data comprising: receiving of a plurality of product feedback search parameters by an intelligent product feedback analytics tool, wherein said plurality of product feedback search parameters pertain to at least one of a product and a group of products; performing a search on plurality of product feedback data sources using the product feedback search parameters to gather product feedback; obtaining a plurality of product feedback search results applicable to the plurality of product feedback search parameters, wherein each product feedback search result comprises at least one of a rating value upon a rating scale and feedback content in a textual format; for each product represented in the obtained plurality of product feedback search results, synthesizing a composite rating value for each rating category of the rating scale defined for the intelligent product feedback analytics tool from rating values contained in product feedback search results that are applicable to the product, wherein the synthesizing comprises: converting the rating value for each product feedback search result to an equivalent rating value with respect to the rating scale defined for the intelligent product feedback analytics tool; assigning each product feedback search result to a rating category of the rating scale defined for the intelligent product feedback analytics tool, wherein the converted rating value of a product feedback search result falls within a rating value range defined for the rating category to which it is assigned; and expressing a quantity of product feedback search results assigned to each rating category as a percentage of a total quantity of product feedback search results that are applicable to the product; for each product represented in the obtained plurality of product feedback search results, analyzing the plurality of product feedback search results for at least one analytic parameter, wherein each analytic parameter represents a commonality among a subset of the product feedback search results that are applicable to the product, wherein said analysis utilizes natural language processing techniques; and presenting the plurality of product feedback search results, composite rating values, and the at least one analytic parameter in an organized manner within a user interface, wherein the at least one analytic parameter presented provides a context for the corresponding composite rating value. 8. The method of claim 1 , wherein the analyzing of the plurality of product feedback search results further comprises: upon completion of the analysis of a product feedback search result, storing the analyzed product feedback search result in an analytic search results library, wherein the analytic search results library is a knowledgebase of product feedback search results previously processed by the intelligent product feedback analytics tool.

1. A computer-implemented method comprising: determining for each of a plurality of potential database queries, of which at least one of which has not yet been inputted by a user and the results of at least one of these queries have not yet been pre-cached, an indication of estimated query response time using a count of items associated with a selector of each of the potential database queries; based on the indication of estimated query response time of the potential database queries, determining a queue of potential database queries from which potential database queries should be chosen to have their results pre-cached; executing at least some of the potential database queries from the queue; and pre-caching the results of the executed queries.

1. A computer-implemented method comprising: determining for each of a plurality of potential database queries, of which at least one of which has not yet been inputted by a user and the results of at least one of these queries have not yet been pre-cached, an indication of estimated query response time using a count of items associated with a selector of each of the potential database queries; based on the indication of estimated query response time of the potential database queries, determining a queue of potential database queries from which potential database queries should be chosen to have their results pre-cached; executing at least some of the potential database queries from the queue; and pre-caching the results of the executed queries. 7. The computer-implemented method of claim 1 , further comprising: processing a query comprising a plurality of selectors, and at least one disjunctive Boolean operator, using results of one or more conjunctive or single selector queries which have been processed prior to creation of said query.