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13. An adaptive social tagging system, comprising: a computer-implemented structural aspect comprising a plurality of objects, and at least one relationship between a first object and a second object; a usage aspect, comprising captured usage behaviors, wherein the usage behaviors are associated with one or more users and wherein at least one behavior is associated with a user tagging an object; and a function to generate an adaptive recommendation for delivery to a user based, at least in part, on inferring interests from a plurality of the usage behaviors associated with the one or more users, wherein at least one usage behavior is associated with a user tagging an object.

13. An adaptive social tagging system, comprising: a computer-implemented structural aspect comprising a plurality of objects, and at least one relationship between a first object and a second object; a usage aspect, comprising captured usage behaviors, wherein the usage behaviors are associated with one or more users and wherein at least one behavior is associated with a user tagging an object; and a function to generate an adaptive recommendation for delivery to a user based, at least in part, on inferring interests from a plurality of the usage behaviors associated with the one or more users, wherein at least one usage behavior is associated with a user tagging an object. 17. The adaptive social tagging system of claim 13 , wherein a function to generate an adaptive recommendation for delivery to a user based, at least in part, on inferring interests from a plurality of the usage behaviors associated with the one or more users, wherein at least one usage behavior is associated with a user tagging an object comprises: a function that automatically modifies a structural element, wherein the function that automatically modifies a structural element is selected from the group consisting of a function to generate a new relationship, a function to modify an existing relationship, a function to delete an existing relationship, a function to add an object, a function to modify an object, and a function to delete an object.

1. A method for semi-supervised insight discovery, the method being implemented by one or more data processors and comprising: seeking, by at least one data processor, pair-wise relationships between large numbers of entities, in a variety of domain specific contexts, from appropriately filtered and customized transaction data; representing, by at least one data processor, the pair-wise relationships between the entities in a graph structure containing a set of nodes representing entities, and a set of edges representing strength of relationships between pairs of nodes; discovering, by at least one data processor, insights in the form of relationship patterns of interest that may be projected or scored on individual or groups of transactions or customers; and using, by at least one data processor, said insights to make data-driven-decisions for a variety of business goals; said graph structure comprising any of the following types of structures: a sub-graph comprising a subset of a graph, created by picking a subset of nodes and edges from an original graph, a sub-graph comprising any of: node based sub-graphs which are created by selecting a subset of the nodes and by keeping only those edges between selected nodes; and edge based sub-graphs which are created by pruning a set of edges from the graph and removing all nodes that are rendered disconnected from the graph; a neighborhood of a target product comprising a sub-graph that contains the target product and all the products that are connected to the target product with consistency strength above a predefined threshold to show the top most affiliated products for a given target product; a bundle structure comprising a sub-set of products wherein each product in the bundle has a high consistency connection with all the other products in the bundle, wherein each product in a bundle is assigned a product density with respect to the bundle which is high if the product has high consistency connection with other products in the bundle and low otherwise; and a bridge structure comprising a collection of two or more, otherwise disconnected, product groups that are bridged by one or more bridge product(s).

1. A method for semi-supervised insight discovery, the method being implemented by one or more data processors and comprising: seeking, by at least one data processor, pair-wise relationships between large numbers of entities, in a variety of domain specific contexts, from appropriately filtered and customized transaction data; representing, by at least one data processor, the pair-wise relationships between the entities in a graph structure containing a set of nodes representing entities, and a set of edges representing strength of relationships between pairs of nodes; discovering, by at least one data processor, insights in the form of relationship patterns of interest that may be projected or scored on individual or groups of transactions or customers; and using, by at least one data processor, said insights to make data-driven-decisions for a variety of business goals; said graph structure comprising any of the following types of structures: a sub-graph comprising a subset of a graph, created by picking a subset of nodes and edges from an original graph, a sub-graph comprising any of: node based sub-graphs which are created by selecting a subset of the nodes and by keeping only those edges between selected nodes; and edge based sub-graphs which are created by pruning a set of edges from the graph and removing all nodes that are rendered disconnected from the graph; a neighborhood of a target product comprising a sub-graph that contains the target product and all the products that are connected to the target product with consistency strength above a predefined threshold to show the top most affiliated products for a given target product; a bundle structure comprising a sub-set of products wherein each product in the bundle has a high consistency connection with all the other products in the bundle, wherein each product in a bundle is assigned a product density with respect to the bundle which is high if the product has high consistency connection with other products in the bundle and low otherwise; and a bridge structure comprising a collection of two or more, otherwise disconnected, product groups that are bridged by one or more bridge product(s). 13. The method of claim 1 , wherein the graph comprises any of the following parameters: customization parameters which define the scope of a graph by identifying a transaction data slice used to build said graph; context parameters which define the nature of relationships between products and customers in said graphs; and consistency parameters which define the strength of relationships between products in product graphs.

25. A computer program product, encoded on a non-transitory computer-readable storage device, operable to cause data processing apparatus to perform operations comprising: receiving a content access history of a user, the content access history including one or more user actions, each user action being associated with a content item upon which the user action is performed; identifying one or more action trails from the content access history, each action trail including a sequence of user actions corresponding to content items relating to a topic, wherein identifying a particular action trail includes: clustering the user actions into a series of segments using one or more temporal criteria; splitting a segment of the series of segments into multiple segments when a topical coherence value of the segment satisfies a threshold coherence value, wherein the topical coherence value of the segment measures a similarity between content items corresponding to user actions in the segment; calculating semantic similarities between the content items, wherein the semantic similarities change as a function of the series of segments; and adding one or more segments of the series of segments to the action trail, when the semantic similarities between content items corresponding to the user actions in the one or more segments and content items corresponding to the user actions in another segment satisfy a similarity threshold; and providing the action trails for display on a display device.

25. A computer program product, encoded on a non-transitory computer-readable storage device, operable to cause data processing apparatus to perform operations comprising: receiving a content access history of a user, the content access history including one or more user actions, each user action being associated with a content item upon which the user action is performed; identifying one or more action trails from the content access history, each action trail including a sequence of user actions corresponding to content items relating to a topic, wherein identifying a particular action trail includes: clustering the user actions into a series of segments using one or more temporal criteria; splitting a segment of the series of segments into multiple segments when a topical coherence value of the segment satisfies a threshold coherence value, wherein the topical coherence value of the segment measures a similarity between content items corresponding to user actions in the segment; calculating semantic similarities between the content items, wherein the semantic similarities change as a function of the series of segments; and adding one or more segments of the series of segments to the action trail, when the semantic similarities between content items corresponding to the user actions in the one or more segments and content items corresponding to the user actions in another segment satisfy a similarity threshold; and providing the action trails for display on a display device. 29. The product of claim 25 , wherein calculating semantic similarities between the content items comprises calculating calculating the semantic similarities between content items of different segments.

14. A spine implant comprising: an elongated member having a first end, a second end, and a platform located between the first end and the second end, said platform including a leaf spring which has a plurality of layers; a first bone anchor adapted to be connected to the first end of the elongated member and configured to engage a first pedicle of a first vertebra; a second bone anchor adapted to be connected to the second end of the elongated member and configured to engage a second pedicle of the first vertebra; and a vertical rod assembly having a first end connected to the platform, and a second end configured for attachment to a second vertebra; such that, when secured between the first vertebra and second vertebra, the vertical rod assembly transmits load from the second vertebra to the platform, the platform transmits said load to the first end and second end of the elongated member via the leaf spring, and the first end and second end of the elongated member transmit said load to the first pedicle and the second pedicle of the first vertebra via the first bone anchor and the second bone anchor.

14. A spine implant comprising: an elongated member having a first end, a second end, and a platform located between the first end and the second end, said platform including a leaf spring which has a plurality of layers; a first bone anchor adapted to be connected to the first end of the elongated member and configured to engage a first pedicle of a first vertebra; a second bone anchor adapted to be connected to the second end of the elongated member and configured to engage a second pedicle of the first vertebra; and a vertical rod assembly having a first end connected to the platform, and a second end configured for attachment to a second vertebra; such that, when secured between the first vertebra and second vertebra, the vertical rod assembly transmits load from the second vertebra to the platform, the platform transmits said load to the first end and second end of the elongated member via the leaf spring, and the first end and second end of the elongated member transmit said load to the first pedicle and the second pedicle of the first vertebra via the first bone anchor and the second bone anchor. 15. The spine implant of claim 14 wherein said layers of said leaf spring have graduated lengths from a shorter length layer to a longer length layer.

14. The computing device of claim 12 , wherein the operations further include pruning the outer arcs to exclude arcs representing possible head-modifier dependency between words in the sentence separated by a distance greater than a second distance threshold before pruning the index set based on the augmented vine parsing algorithm.

14. The computing device of claim 12 , wherein the operations further include pruning the outer arcs to exclude arcs representing possible head-modifier dependency between words in the sentence separated by a distance greater than a second distance threshold before pruning the index set based on the augmented vine parsing algorithm. 15. The computing device of claim 14 , wherein the second distance threshold is based on a determination of a longest head-modifier dependency distance observed in training data.

11. A system comprising: a device configured to initiate a call comprising a spoken statement; and an automated response tool comprising: a parser configured to: parse the spoken statement to detect a plurality of words in the spoken statement; and generate a parse tree based on the detected plurality of words; an invoker configured to: determine, based on the parse tree, a plurality of potential services to invoke to respond to the spoken statement; and calculate a confidence score for each potential service of the plurality of potential services by determining a shortest distance between a first node and a second node for each potential service, the first node representing the plurality of words, the second node representing that potential service, each confidence score indicating a likelihood that a potential service is a service requested by the spoken statement; and an extractor configured to determine, for each potential service of the plurality of potential services: a parameter used during execution of that potential service; and a value of the determined parameter based on the parse tree, wherein the invoker is further configured to issue a command to invoke a potential service of the plurality of potential services with the highest confidence score based on the shortest distance using a value of a determined parameter.

11. A system comprising: a device configured to initiate a call comprising a spoken statement; and an automated response tool comprising: a parser configured to: parse the spoken statement to detect a plurality of words in the spoken statement; and generate a parse tree based on the detected plurality of words; an invoker configured to: determine, based on the parse tree, a plurality of potential services to invoke to respond to the spoken statement; and calculate a confidence score for each potential service of the plurality of potential services by determining a shortest distance between a first node and a second node for each potential service, the first node representing the plurality of words, the second node representing that potential service, each confidence score indicating a likelihood that a potential service is a service requested by the spoken statement; and an extractor configured to determine, for each potential service of the plurality of potential services: a parameter used during execution of that potential service; and a value of the determined parameter based on the parse tree, wherein the invoker is further configured to issue a command to invoke a potential service of the plurality of potential services with the highest confidence score based on the shortest distance using a value of a determined parameter. 12. The system of claim 11 , wherein the invoker is further configured to update a confidence score for each potential service of the plurality of potential services based on the value for the determined parameter used during execution of that potential service.

1. A message passing machine intended for use in an LDPC decoder comprising: a first number of processing units of a processor, the processing units operating in parallel to decode a received signal, each processing unit successively receiving messages of a first type and successively providing messages of a second type based on a first processing of the messages of the first type, and receiving messages of the second type, and providing processed messages of the first type based on a second processing of the messages of the second type, the second processing being different from the first processing; a storage unit in a random access memory (RAM) coupled to the processing units, the storage unit stores first words and second words when the first and second words are received by the storage unit from the processing units, wherein each first word comprises messages of the first type in a number equal to said first number, and each second word comprises messages of the second type in a number equal to said first number; wherein each first word from the first words comprises messages of the first type, each provided by a different processing unit, each message of the first type being at a position in the first word which depends on the associated processing unit; and each second word from the second words comprising messages of the second type, each provided by a different processing unit, each message of the second type being at a position in the second word which depends on the associated processing unit; a shift control unit coupled to a rearrangement unit in a read-only memory (ROM), the shift control unit being configured to generate first shift control information for the first words and second shift control information for the second words, wherein the shift control unit is configured to provide the first shift control information and the second shift control information to the rearrangement unit; the rearrangement unit configured to, when the rearrangement unit reads at least one of the first words and the second words from the storage unit and receives the first and second shift control information from the shift control unit: to rearrange the first at least partially based on the first shift control information to provide rearranged first words; to rearrange the second words at least partially based on the second shift control information to provide rearranged second words; to provide, to each processing unit, for each first rearranged word, a message of the first type at a position in the first rearranged word which depends on the processing unit; and to provide to each processing unit, for each second rearranged word, a message of the second type at a position in the second rearranged word which depends on the processing unit; wherein the rearrangement unit provides said message of the first type at the position in the first rearranged word which depends on the first shift control information and said message of the second type at a position in the second rearranged word which depends on the second shift control information, or wherein the rearrangement unit writes each message of the first type at a position in the first rearranged word which depends on the first shift control information and each message of the second type at a position in the second rearranged word which depends on the second shift control information.

1. A message passing machine intended for use in an LDPC decoder comprising: a first number of processing units of a processor, the processing units operating in parallel to decode a received signal, each processing unit successively receiving messages of a first type and successively providing messages of a second type based on a first processing of the messages of the first type, and receiving messages of the second type, and providing processed messages of the first type based on a second processing of the messages of the second type, the second processing being different from the first processing; a storage unit in a random access memory (RAM) coupled to the processing units, the storage unit stores first words and second words when the first and second words are received by the storage unit from the processing units, wherein each first word comprises messages of the first type in a number equal to said first number, and each second word comprises messages of the second type in a number equal to said first number; wherein each first word from the first words comprises messages of the first type, each provided by a different processing unit, each message of the first type being at a position in the first word which depends on the associated processing unit; and each second word from the second words comprising messages of the second type, each provided by a different processing unit, each message of the second type being at a position in the second word which depends on the associated processing unit; a shift control unit coupled to a rearrangement unit in a read-only memory (ROM), the shift control unit being configured to generate first shift control information for the first words and second shift control information for the second words, wherein the shift control unit is configured to provide the first shift control information and the second shift control information to the rearrangement unit; the rearrangement unit configured to, when the rearrangement unit reads at least one of the first words and the second words from the storage unit and receives the first and second shift control information from the shift control unit: to rearrange the first at least partially based on the first shift control information to provide rearranged first words; to rearrange the second words at least partially based on the second shift control information to provide rearranged second words; to provide, to each processing unit, for each first rearranged word, a message of the first type at a position in the first rearranged word which depends on the processing unit; and to provide to each processing unit, for each second rearranged word, a message of the second type at a position in the second rearranged word which depends on the processing unit; wherein the rearrangement unit provides said message of the first type at the position in the first rearranged word which depends on the first shift control information and said message of the second type at a position in the second rearranged word which depends on the second shift control information, or wherein the rearrangement unit writes each message of the first type at a position in the first rearranged word which depends on the first shift control information and each message of the second type at a position in the second rearranged word which depends on the second shift control information. 2. The message passing machine of claim 1 , wherein the rearrangement unit and a message write unit simultaneously perform read and write operations from and into the storage unit.

7. The visual cue system of claim 1 , wherein the regimen key includes a first graphic associated with a function of the first consumer product package.

7. The visual cue system of claim 1 , wherein the regimen key includes a first graphic associated with a function of the first consumer product package. 8. The visual cue system of claim 7 , wherein the regimen key includes a second graphic different than the first graphic on the regimen key that is associated with a function of the second consumer product package.

1. A method for anonymizing selected content in a document, the method comprising: receiving as input a document comprising content; determining a first context in which said document was prepared; determining a second context in which said document is permitted to be viewed; identifying named entities and at least two types of named entity data of said named entities in the document based on said first context and said second context; assigning a user access privilege to said user based on historical data of previous access privileges for said user, said first context, and said second context; comparing the named entities identified in the document with a pre-defined set of named entities and at least one type of named entity data identified for said user with said user access privilege to view the document based on the first context and the second context; concealing the named entities identified in the document that match with the pre-defined set of named entities and said at least one type of named entity data; and providing as output an anonymized document to the user, wherein the set of pre-defined named entities and said at least one type of named entity data have been concealed, and another of said at least two types of named entity data of said named entities is displayed to said user, but is concealed to another user without said user access privilege.

1. A method for anonymizing selected content in a document, the method comprising: receiving as input a document comprising content; determining a first context in which said document was prepared; determining a second context in which said document is permitted to be viewed; identifying named entities and at least two types of named entity data of said named entities in the document based on said first context and said second context; assigning a user access privilege to said user based on historical data of previous access privileges for said user, said first context, and said second context; comparing the named entities identified in the document with a pre-defined set of named entities and at least one type of named entity data identified for said user with said user access privilege to view the document based on the first context and the second context; concealing the named entities identified in the document that match with the pre-defined set of named entities and said at least one type of named entity data; and providing as output an anonymized document to the user, wherein the set of pre-defined named entities and said at least one type of named entity data have been concealed, and another of said at least two types of named entity data of said named entities is displayed to said user, but is concealed to another user without said user access privilege. 5. The method of claim 1 , wherein the named entities include security sensitive words, characters or objects.

9. A computer implemented method, comprising: receiving a search query; identifying a plurality of documents that are responsive to the search query, the plurality of documents including a first document; determining a first data measure for the first document, wherein the first data measure is indicative of an amount of data usage required to load the first document; determining that the search query is non-navigational; ranking the first document relative to other of the documents based on the first data measure and based on determining that the search query is non-navigational; and providing search results for display in response to the search query, wherein providing the search results comprises providing a first search result that is based on the first document, providing additional search results that are based on other of the documents, and providing the first search result and the additional search results based on the ranking.

9. A computer implemented method, comprising: receiving a search query; identifying a plurality of documents that are responsive to the search query, the plurality of documents including a first document; determining a first data measure for the first document, wherein the first data measure is indicative of an amount of data usage required to load the first document; determining that the search query is non-navigational; ranking the first document relative to other of the documents based on the first data measure and based on determining that the search query is non-navigational; and providing search results for display in response to the search query, wherein providing the search results comprises providing a first search result that is based on the first document, providing additional search results that are based on other of the documents, and providing the first search result and the additional search results based on the ranking. 12. The method of claim 9 , further comprising: receiving a second search query; determining that the second search query is navigational; and in response to determining that the second search query is navigational, preventing determination of rankings of documents responsive to the second search query that are based on data measures of the documents.

13. A processing device, comprising: one or more processors; memory, in communication with the one or more processors; an output module, defined in the memory, executable by the one or more processors, and configured to graph relationship data, the graphed relationship data comprising: representations of individual ones of a plurality of entities, the plurality of entities extracted from documents obtained based at least in part on a search term, each of the plurality of entities related to, but distinct from, the search term, wherein sizes of the representations of individual ones of the plurality of entities and the representation of the search term are not all equal; edges between at least some of the representations of the plurality of entities, each edge forming a pair of two entities and indicating a relationship between entities of the pair; and a representation of the search term having an edge connected to each of the representations of the plurality of entities.

13. A processing device, comprising: one or more processors; memory, in communication with the one or more processors; an output module, defined in the memory, executable by the one or more processors, and configured to graph relationship data, the graphed relationship data comprising: representations of individual ones of a plurality of entities, the plurality of entities extracted from documents obtained based at least in part on a search term, each of the plurality of entities related to, but distinct from, the search term, wherein sizes of the representations of individual ones of the plurality of entities and the representation of the search term are not all equal; edges between at least some of the representations of the plurality of entities, each edge forming a pair of two entities and indicating a relationship between entities of the pair; and a representation of the search term having an edge connected to each of the representations of the plurality of entities. 15. The processing device as recited in claim 13 , wherein: a size of the representation of the search term is larger than a size of any of the representations of the plurality of entities.

33. A computer system, comprising: a target processor; a shared code cache facility; and translator code for translating a subject program code into target code executable on said target processor, said translator code comprising code executable by said target processor to: provide a first translator instance which translates the subject code of a first program into the target code including translating a first portion of the subject code into a portion of the target code; cache said portion of the target code in the shared code cache facility; and provide a second translator instance which translates the subject code of a second program into the target code, wherein the second translator instance is different from the first translator instance and operates simultaneously with the first translator instance, and wherein the second translator instance retrieves the cached portion of the target code from the shared code cache facility upon a compatibility detection between said cached portion of the target code and a second portion of the subject code in the second program, including loading the portion of the target code in the shared code cache facility into a portion of memory which is shared amongst at least the first and second translator instances; and, copying at least one part of the shared code cache facility to a private portion of memory associated with the second translator instance upon modification of the at least one part of the shared code cache facility by the second translator instance.

33. A computer system, comprising: a target processor; a shared code cache facility; and translator code for translating a subject program code into target code executable on said target processor, said translator code comprising code executable by said target processor to: provide a first translator instance which translates the subject code of a first program into the target code including translating a first portion of the subject code into a portion of the target code; cache said portion of the target code in the shared code cache facility; and provide a second translator instance which translates the subject code of a second program into the target code, wherein the second translator instance is different from the first translator instance and operates simultaneously with the first translator instance, and wherein the second translator instance retrieves the cached portion of the target code from the shared code cache facility upon a compatibility detection between said cached portion of the target code and a second portion of the subject code in the second program, including loading the portion of the target code in the shared code cache facility into a portion of memory which is shared amongst at least the first and second translator instances; and, copying at least one part of the shared code cache facility to a private portion of memory associated with the second translator instance upon modification of the at least one part of the shared code cache facility by the second translator instance. 44. The computer system combination of claim 33 wherein the portion of target code is converted into a single cache unit comprising a subject program and all its associated libraries.

5. The method of claim 1 , further comprising: associating the one or more tuning hints with a plurality of query language statements.

5. The method of claim 1 , further comprising: associating the one or more tuning hints with a plurality of query language statements. 6. The method of claim 5 , further comprising: determining a name for each query block of each statement; and associating the one or more tuning hints with one or more query blocks using the query block names.

13. A document processing method, comprising the steps of: (a) acquiring document data; (b) extracting character strings that correspond to at least one of a heading, a title, or a subtitle as bookmark candidate character strings from the acquired document data; (c) deriving respective features of the extracted bookmark candidate character strings, and categorizing said bookmark candidate character strings having a common feature into one group and creating a format for the group based on the common feature of the group; (d) displaying said extracted bookmark candidate character strings in a list form, and displaying the format corresponding to said bookmark candidate character strings; (e) correcting the format in response to receiving a correcting operation given to the displayed format from a user; (f) when the format is corrected, extracting the character strings again that have the common featured of the corrected format from the acquired document data as said bookmark's candidate character strings; and (g) generating bookmark data based on said character strings extracted from the acquired document data and adding the generated bookmark data to the acquired document data.

13. A document processing method, comprising the steps of: (a) acquiring document data; (b) extracting character strings that correspond to at least one of a heading, a title, or a subtitle as bookmark candidate character strings from the acquired document data; (c) deriving respective features of the extracted bookmark candidate character strings, and categorizing said bookmark candidate character strings having a common feature into one group and creating a format for the group based on the common feature of the group; (d) displaying said extracted bookmark candidate character strings in a list form, and displaying the format corresponding to said bookmark candidate character strings; (e) correcting the format in response to receiving a correcting operation given to the displayed format from a user; (f) when the format is corrected, extracting the character strings again that have the common featured of the corrected format from the acquired document data as said bookmark's candidate character strings; and (g) generating bookmark data based on said character strings extracted from the acquired document data and adding the generated bookmark data to the acquired document data. 14. The document processing method according to claim 13 , wherein in said step (c), the respective features of character strings are arranged in a hierarchical structure based on features shared in common among said character strings, and in said step (d), said character strings extracted in said step (b) are associated with said hierarchical structure and displayed.

6. A method for content-driven healthcare location relationship management, the method comprising: receiving, at a microprocessor, one or more location identifiers for a content-based clinical application; assigning, with the microprocessor, one or more locations to a source role and a target role based on the received one or more location identifiers and an ontology, wherein the ontology is represented in a directed acyclic graph navigable to identify the ontology for the one or more locations, wherein the directed acyclic graph includes a plurality of available ontologies for selection of a location relationship, wherein the plurality of available ontologies includes an “is a” ontology and an “is part of” ontology; validating a conflict of the source role and the target role between the one or more locations; identifying, with the microprocessor, a location relationship between the validated source role and target role based on the received one or more location identifiers and the ontology; associating, with the microprocessor, the validated source role and target role with the identified location relationship; and utilizing the associated source role, target role, and location relationship to configure with the microprocessor, one or more content items forming the content-based clinical application.

6. A method for content-driven healthcare location relationship management, the method comprising: receiving, at a microprocessor, one or more location identifiers for a content-based clinical application; assigning, with the microprocessor, one or more locations to a source role and a target role based on the received one or more location identifiers and an ontology, wherein the ontology is represented in a directed acyclic graph navigable to identify the ontology for the one or more locations, wherein the directed acyclic graph includes a plurality of available ontologies for selection of a location relationship, wherein the plurality of available ontologies includes an “is a” ontology and an “is part of” ontology; validating a conflict of the source role and the target role between the one or more locations; identifying, with the microprocessor, a location relationship between the validated source role and target role based on the received one or more location identifiers and the ontology; associating, with the microprocessor, the validated source role and target role with the identified location relationship; and utilizing the associated source role, target role, and location relationship to configure with the microprocessor, one or more content items forming the content-based clinical application. 9. The method of claim 6 , wherein identifying the location relationship further comprises determining, with the microprocessor, one or more allowed location relationships between the source role and the target role based on a terminology definition provided by the ontology.

2. The non-transitory computer-readable medium of claim 1 , further comprising instructions configured to cause the computer to: receive a request for a KPI value; select a KPI query that corresponds to the requested KPI; execute the selected KPI query on the tax data warehouse; and return results to the selected KPI query.

2. The non-transitory computer-readable medium of claim 1 , further comprising instructions configured to cause the computer to: receive a request for a KPI value; select a KPI query that corresponds to the requested KPI; execute the selected KPI query on the tax data warehouse; and return results to the selected KPI query. 3. The non-transitory computer-readable medium of claim 2 , further comprising instructions configured to cause the computer to: receive a user specified range of values for a selected KPI; store the range of values in a threshold table in the tax data warehouse; and when a KPI query corresponding to the selected KPI is executed, communicate a returned valued for the selected KPI as compared to the range of values.

17. An apparatus for searching for a string of characters on a web page, comprising: input means for receiving a user input containing a text search string to be identified on a web page loaded in a web browser on a computer, the web page being displayed to the user on a computer display; means for determining a common substring between the text search string and a hypertext markup language representation of the web page; means for identifying a document object model tree node that includes the common substring; means for verifying that a remainder of the text search string and the common substring is included in one or more surrounding nodes of the document object model tree, wherein the means for verifying includes: means for examining one or more nodes located to the left of the node with the common substring in the document object model tree to match characters left of the common substring in the text search string; and means for examining one or more nodes located to the right of the node with the common substring in the document object model tree to match characters right of the common substring in the text search string; and means for displaying to the user on the computer display the location of the text search string on the web page.

17. An apparatus for searching for a string of characters on a web page, comprising: input means for receiving a user input containing a text search string to be identified on a web page loaded in a web browser on a computer, the web page being displayed to the user on a computer display; means for determining a common substring between the text search string and a hypertext markup language representation of the web page; means for identifying a document object model tree node that includes the common substring; means for verifying that a remainder of the text search string and the common substring is included in one or more surrounding nodes of the document object model tree, wherein the means for verifying includes: means for examining one or more nodes located to the left of the node with the common substring in the document object model tree to match characters left of the common substring in the text search string; and means for examining one or more nodes located to the right of the node with the common substring in the document object model tree to match characters right of the common substring in the text search string; and means for displaying to the user on the computer display the location of the text search string on the web page. 18. The apparatus of claim 17 , wherein the means for determining a common substring include: means for identifying a longest common substring between the text search string and the hypertext markup language representation of the web page.

1. A system comprising: one or more processors; and memory storing computer-executable instructions that, when executed, cause the one or more processors to perform acts comprising: determining a desired range of time of a reading session based at least in part on user input received from a user; determining a reading rate associated with the user; calculating a range of words to be included in the reading session based on the desired range of time and the reading rate; determining one or more candidate endpoints located within a text-based document with the range of words, the one or more candidate endpoints being logical breaks usable to segment the text-based document; selecting an endpoint from the one or more candidate endpoints to create a chapter segment, the chapter segment, when read by the user, being expected to be completed within the desired range of time; inserting a graphic at a location associated with the endpoint, the graphic to indicate completion of the chapter segment; and causing display of the text-based document and the graphic at a user device.

1. A system comprising: one or more processors; and memory storing computer-executable instructions that, when executed, cause the one or more processors to perform acts comprising: determining a desired range of time of a reading session based at least in part on user input received from a user; determining a reading rate associated with the user; calculating a range of words to be included in the reading session based on the desired range of time and the reading rate; determining one or more candidate endpoints located within a text-based document with the range of words, the one or more candidate endpoints being logical breaks usable to segment the text-based document; selecting an endpoint from the one or more candidate endpoints to create a chapter segment, the chapter segment, when read by the user, being expected to be completed within the desired range of time; inserting a graphic at a location associated with the endpoint, the graphic to indicate completion of the chapter segment; and causing display of the text-based document and the graphic at a user device. 2. The system as recited in claim 1 , wherein the one or more processors further perform acts comprising determining a title for the chapter segment based at least in part on an analysis of text included in the chapter segment.

8. The method according to claim 1 , including: selecting a reference prototype for each allograph to be modified; determining the distance value for each reference prototype; determining an average of the determined distance values; and, modifying the weighting of each allograph in accordance with the distance value of the respective reference prototype and the average distance value.

8. The method according to claim 1 , including: selecting a reference prototype for each allograph to be modified; determining the distance value for each reference prototype; determining an average of the determined distance values; and, modifying the weighting of each allograph in accordance with the distance value of the respective reference prototype and the average distance value. 9. The method according to claim 8 , the reference prototype being the prototype having the lowest distance value for the respective allograph.

15. A method as claimed in claim 1 , further comprising the steps of: analysing the message to determine the recipient of the message; placing the message in a category based on the determined recipient; storing the category in one or more data stores; and wherein the category is associated with the sender of the message.

15. A method as claimed in claim 1 , further comprising the steps of: analysing the message to determine the recipient of the message; placing the message in a category based on the determined recipient; storing the category in one or more data stores; and wherein the category is associated with the sender of the message. 19. A method as claimed in claim 15 , further comprising comparing the measure of the language content used in messages from one user placed in one category against the measure of the language content used in messages from the same user placed in other categories.

13. A computer-readable storage medium storing computer executable instructions which, when executed by a computer, will cause computer to perform a method of adapting and personalizing a deep neural network (DNN) model for automatic speech recognition (ASR), the method comprising: receiving a plurality of utterances, each of the plurality of utterances comprising a plurality of speech features for a plurality of speakers from one or more ASR tasks; applying a decomposition process to two or more matrices in the DNN model; and in response to applying the decomposition process, adapting the DNN model to include a decomposed matrix that is generated from decomposition processing of the two or more matrices.

13. A computer-readable storage medium storing computer executable instructions which, when executed by a computer, will cause computer to perform a method of adapting and personalizing a deep neural network (DNN) model for automatic speech recognition (ASR), the method comprising: receiving a plurality of utterances, each of the plurality of utterances comprising a plurality of speech features for a plurality of speakers from one or more ASR tasks; applying a decomposition process to two or more matrices in the DNN model; and in response to applying the decomposition process, adapting the DNN model to include a decomposed matrix that is generated from decomposition processing of the two or more matrices. 17. The computer-readable storage medium of claim 13 , wherein applying the decomposition process further comprises applying singular value decomposition (SVD) to the two or more matrices in the DNN model.

1. A system for interaction with datasets in support of scholarly commentary and other commentary, comprising a computer having a processor and a memory and a set of modules each comprising code executing in the processor, including: an editor module for a dataset container file (DCF) creator to create a DCF in which a location and a structure of one or more datasets is input, wherein at least one dataset comprises a tabular arrangement of data, the one or more datasets being stored in a database within the DCF; an import module configured to import a first dataset having a first format from the defined location; a dataset processing module configured to convert the first dataset of the first format into the defined structure; an interface module operative to obtain author-commentary and associate the author-commentary with the first dataset in response to interaction with a user, wherein the author-commentary is included in the DCF; and a synchronization module configured to coordinate on a display a presentation of a portion of at least one of the datasets defined in the DCF in accordance with a selected position on a timeline by querying the datasets in the DCF, returning a subset of the one or more datasets, and presenting one or more multimedia visualizations of that subset on the display, wherein the presentation includes the author-commentary within the timeline and wherein the selected position is input through the editor module, wherein the editor module is further configured to allow positioning of at least one of media objects and the visualizations on the timeline and defining the visual appearance and behavior of the visualizations the at least one of the media objects and the visualizations depicting one or more representations of the one or more datasets.

1. A system for interaction with datasets in support of scholarly commentary and other commentary, comprising a computer having a processor and a memory and a set of modules each comprising code executing in the processor, including: an editor module for a dataset container file (DCF) creator to create a DCF in which a location and a structure of one or more datasets is input, wherein at least one dataset comprises a tabular arrangement of data, the one or more datasets being stored in a database within the DCF; an import module configured to import a first dataset having a first format from the defined location; a dataset processing module configured to convert the first dataset of the first format into the defined structure; an interface module operative to obtain author-commentary and associate the author-commentary with the first dataset in response to interaction with a user, wherein the author-commentary is included in the DCF; and a synchronization module configured to coordinate on a display a presentation of a portion of at least one of the datasets defined in the DCF in accordance with a selected position on a timeline by querying the datasets in the DCF, returning a subset of the one or more datasets, and presenting one or more multimedia visualizations of that subset on the display, wherein the presentation includes the author-commentary within the timeline and wherein the selected position is input through the editor module, wherein the editor module is further configured to allow positioning of at least one of media objects and the visualizations on the timeline and defining the visual appearance and behavior of the visualizations the at least one of the media objects and the visualizations depicting one or more representations of the one or more datasets. 9. The system of claim 1 , wherein the portion of at least one of the datasets comprises one or more objects depicting one or more representations of the at least one of the datasets, and wherein the interface module further comprises a timeline editor configured to associate the one or more objects with a location on the timeline.

1. A method, comprising: receiving computer code, the receiving being performed by a device; performing a static verification analysis of the computer code to locate a point in the code that, under at least one set of states of variables in the computer code, causes an error in an execution of the computer code, the static analysis being performed by analyzing a first plurality of possible execution paths of the computer code based on an over-approximation of states, and the performing is being performed by the device; back-propagating, from the located point, through a second plurality of possible execution paths, the second plurality of possible execution paths being obtained based on an under-approximation of the states that were over-approximated, and the back-propagating being performed by the device; determining, based on the back-propagating, a second point in the computer code as a potential cause of the error, the determining being performed by the device; analyzing, using empiric techniques and based on semantic information for the computer code, the computer code to determine a category for the potential cause of the error, the analyzing the computer code being performed by the device, and the category comprising one of: a first category when the cause of the error is determined to be within the computer code, or a second category when the cause of the error is determined to be due to an input to the computer code; and storing output information associated with the second point in the computer code, the storing being performed by the device.

1. A method, comprising: receiving computer code, the receiving being performed by a device; performing a static verification analysis of the computer code to locate a point in the code that, under at least one set of states of variables in the computer code, causes an error in an execution of the computer code, the static analysis being performed by analyzing a first plurality of possible execution paths of the computer code based on an over-approximation of states, and the performing is being performed by the device; back-propagating, from the located point, through a second plurality of possible execution paths, the second plurality of possible execution paths being obtained based on an under-approximation of the states that were over-approximated, and the back-propagating being performed by the device; determining, based on the back-propagating, a second point in the computer code as a potential cause of the error, the determining being performed by the device; analyzing, using empiric techniques and based on semantic information for the computer code, the computer code to determine a category for the potential cause of the error, the analyzing the computer code being performed by the device, and the category comprising one of: a first category when the cause of the error is determined to be within the computer code, or a second category when the cause of the error is determined to be due to an input to the computer code; and storing output information associated with the second point in the computer code, the storing being performed by the device. 8. The method of claim 1 , where the computer code corresponds to code generated based on a model created in a technical computing environment.

11. The method of claim 10 , further comprising operating the computer processor to perform operations comprising prompting a user to define one or more quality goals in accordance with which business process entities are to be selected for invocation at stages of an active instance of the business process.

11. The method of claim 10 , further comprising operating the computer processor to perform operations comprising prompting a user to define one or more quality goals in accordance with which business process entities are to be selected for invocation at stages of an active instance of the business process. 12. The method of claim 11 , wherein at least one of the quality goals corresponds to one of: maximizing average quality per business process instance; and maintaining business process instance quality above a threshold value.

1. An apparatus configured to provide a tagging interface for tagging content external to an internal database system, the apparatus comprising: a display device; a memory device configured to store a set of instructions; and at least one processor configured to execute the set of instructions to perform the following operations: electronically present, on the display device, an enhanced web browser for viewing an external web page, the enhanced web browser including a tagging interface comprising: a tag-type selection input that enables a user to designate one of a plurality of tag-types for a tag, wherein the plurality of tag-types comprises an object tag type and a property tag-type; a create-tag selection input that enables a user to create a tag with a designated tag-type and associate the tag with a selected portion of content from the external web page; and an export selection input that enables the user to export the tag and the external web page to the internal database system.

1. An apparatus configured to provide a tagging interface for tagging content external to an internal database system, the apparatus comprising: a display device; a memory device configured to store a set of instructions; and at least one processor configured to execute the set of instructions to perform the following operations: electronically present, on the display device, an enhanced web browser for viewing an external web page, the enhanced web browser including a tagging interface comprising: a tag-type selection input that enables a user to designate one of a plurality of tag-types for a tag, wherein the plurality of tag-types comprises an object tag type and a property tag-type; a create-tag selection input that enables a user to create a tag with a designated tag-type and associate the tag with a selected portion of content from the external web page; and an export selection input that enables the user to export the tag and the external web page to the internal database system. 4. The apparatus of claim 1 , wherein the tag-type selection input includes a link tag option for defining a relationship between at least two entities.

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

1. One or more computer-readable storage devices that store executable instructions to provide search results, the executable instructions, when executed by a computer, causing the computer to perform acts comprising: receiving a query from a user; determining that the query is one to be asked to a person in addition to, or instead of, a search engine; comparing said query to a corpus of information to obtain objective results; comparing said query to a social graph to identify one or more people whose relationship to said user meets a closeness condition and who have an aspect of relevance to said query; creating person results that comprise said one or more people and, for each of said one or more people, an explanation of each person's relevance to said query, said social graph indicating attributes for people in said social graph, said explanation of a given person's relevance comprising an attribute that is indicated in said social graph for said given person, said attribute matching a term in said query; and providing, to said user, a set of results that comprise said objective results and said person results. 7. The one or more computer-readable storage devices of claim 1 , said determining that said query is answerable with subjective or socially-derived information being performed after a comparison of said query to said social graph, said determining being based on whether there are a sufficient number of people in said social graph who meet said closeness condition and have said aspect of relevance.

14. A system comprising: one or more processors; and a computer readable medium coupled to the data processing apparatus, having instructions stored thereon which, when executed by the data processing apparatus, cause the data processing apparatus to perform operations comprising: accessing, by at least one processor, a corpus of documents; determining, by the at least one processor, that a particular document by a particular author and in the corpus of documents includes two or more different content pieces that each occur in at least one of one or more other documents in the corpus of documents; determining, by the at least one processor, a quantity of (i) other documents in the corpus of documents whose content pieces are included in the particular document by the particular author and in the corpus of documents, or (ii) authors associated with the other documents in the corpus of documents whose content pieces are included in the particular document by the particular author and in the corpus of documents; adjusting, by the at least one processor, a rank of the particular author in relation to other authors based at least in part on the quantity of (i) other documents in the corpus of documents whose content pieces are included in the particular document by the particular author and in the corpus of documents, or (ii) authors associated with the other documents in the corpus of documents whose content pieces are included in the particular document by the particular author and in the corpus of documents; and indexing, by the at least one processor, a quantity of the particular document and other documents by the particular author at a greater frequency than a quantity of documents by another author who is ranked lower than the particular author, wherein the quantity of the particular document and other documents by the particular author is greater than the quantity of documents by the other author who is ranked lower than the particular author.

14. A system comprising: one or more processors; and a computer readable medium coupled to the data processing apparatus, having instructions stored thereon which, when executed by the data processing apparatus, cause the data processing apparatus to perform operations comprising: accessing, by at least one processor, a corpus of documents; determining, by the at least one processor, that a particular document by a particular author and in the corpus of documents includes two or more different content pieces that each occur in at least one of one or more other documents in the corpus of documents; determining, by the at least one processor, a quantity of (i) other documents in the corpus of documents whose content pieces are included in the particular document by the particular author and in the corpus of documents, or (ii) authors associated with the other documents in the corpus of documents whose content pieces are included in the particular document by the particular author and in the corpus of documents; adjusting, by the at least one processor, a rank of the particular author in relation to other authors based at least in part on the quantity of (i) other documents in the corpus of documents whose content pieces are included in the particular document by the particular author and in the corpus of documents, or (ii) authors associated with the other documents in the corpus of documents whose content pieces are included in the particular document by the particular author and in the corpus of documents; and indexing, by the at least one processor, a quantity of the particular document and other documents by the particular author at a greater frequency than a quantity of documents by another author who is ranked lower than the particular author, wherein the quantity of the particular document and other documents by the particular author is greater than the quantity of documents by the other author who is ranked lower than the particular author. 17. The system of claim 14 , wherein adjusting the rank of the particular author comprises adjusting the rank of the particular author based at least partly on a count of original content pieces in one or more other documents authored by the particular author, wherein the original content pieces are content pieces that do not occur in the corpus of documents.

23. A method for transmitting an electronic document for embedding a written signature, comprising: forming a placeholder electronic document containing content to be attested to by a signature; adding a signing individual to the signer list; selecting a signing individual from a signer list to enable a selected signature location for the signing individual to be added to the placeholder electronic document; placing at least one signature tag for the selected signing individual into the placeholder electronic document, wherein each of the at least one signature tag defines a location for a signature within the electronic document to sign at the location; securing the placeholder electronic document to form a secure electronic document containing content configured to be uneditable and enabling the secure electronic document to accept written signatures from the signing individuals at the signature tag locations; transmitting the secure electronic document to the at least one signing individual for the purpose of obtaining a signature; and sizing an unsigned signature bounding box on a signature capture device based on a type of the signature tag at the signature location, wherein the signature bounding box is displayed independently of a display of the secure electronic document.

23. A method for transmitting an electronic document for embedding a written signature, comprising: forming a placeholder electronic document containing content to be attested to by a signature; adding a signing individual to the signer list; selecting a signing individual from a signer list to enable a selected signature location for the signing individual to be added to the placeholder electronic document; placing at least one signature tag for the selected signing individual into the placeholder electronic document, wherein each of the at least one signature tag defines a location for a signature within the electronic document to sign at the location; securing the placeholder electronic document to form a secure electronic document containing content configured to be uneditable and enabling the secure electronic document to accept written signatures from the signing individuals at the signature tag locations; transmitting the secure electronic document to the at least one signing individual for the purpose of obtaining a signature; and sizing an unsigned signature bounding box on a signature capture device based on a type of the signature tag at the signature location, wherein the signature bounding box is displayed independently of a display of the secure electronic document. 24. A method as in claim 23 , further comprising obtaining a signature within the secure electronic document from the at least one signing individual using a signature capture device as the signature is written by the signing individual, the signature capture device being configured to enable the signing individual to inscribe their signature onto the signature capture device within the signature bounding box to allow the signing individual's signature to be embedded into the secure electronic document at the signature tag that indicates a location for the signing individual's signature.

5. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform acts comprising: providing, to a user device that is physically separate from a speech interface device, a first graphical interface displaying a plurality of historical interaction records, a historical interaction record of the plurality of historical interaction records associated with information regarding a historical speech interaction conducted at least in part through the speech interface device between a speech interface platform and a user, wherein the information indicates recognized speech from a user utterance and at least one of (a) an intent of the user that was understood by the speech interface platform from the recognized speech, (b) text corresponding to speech generated by the speech interface platform in response to the user utterance, or (c) an action performed in response to the user utterance; accepting, from the user device that is physically separate from the speech interface device via the first graphical interface displayed at the user device, a selection of the historical interaction record; and based at least in part on the selection, providing to the user device a second graphical interface displaying at least a portion of the information regarding the historical speech interaction and accepting, within the second graphical interface displayed by the user device, one or more edits or evaluations from the user regarding at least some of the at least the portion of the information regarding the historical speech interaction for improving future speech recognition and intent understanding on a subsequent audio signal received from the speech interface device.

5. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform acts comprising: providing, to a user device that is physically separate from a speech interface device, a first graphical interface displaying a plurality of historical interaction records, a historical interaction record of the plurality of historical interaction records associated with information regarding a historical speech interaction conducted at least in part through the speech interface device between a speech interface platform and a user, wherein the information indicates recognized speech from a user utterance and at least one of (a) an intent of the user that was understood by the speech interface platform from the recognized speech, (b) text corresponding to speech generated by the speech interface platform in response to the user utterance, or (c) an action performed in response to the user utterance; accepting, from the user device that is physically separate from the speech interface device via the first graphical interface displayed at the user device, a selection of the historical interaction record; and based at least in part on the selection, providing to the user device a second graphical interface displaying at least a portion of the information regarding the historical speech interaction and accepting, within the second graphical interface displayed by the user device, one or more edits or evaluations from the user regarding at least some of the at least the portion of the information regarding the historical speech interaction for improving future speech recognition and intent understanding on a subsequent audio signal received from the speech interface device. 11. The one or more non-transitory computer-readable media of claim 5 , wherein the one or more edits or evaluations comprise a correction to the understood intent.

8. A system for searching, the system comprising one or more processors and one or more memory devices coupled to the one or more processors, the one or more memory devices storing executable and operational data effective to cause the one or more processors to: receive first queries, from a user; select a plurality of head queries from among the first queries; cluster the first queries, exclusive of the plurality of head queries, to the plurality of head queries by: calculating similarity scores for at least a portion of the first queries relative to the plurality of head queries by evaluating response similarity between user selections of search results for the at least the portion of the first queries and user selections of search results for the plurality of head queries, by evaluating an equation: Sim ( q 1 , q 2 ) = P 1 · P 2  P 1  2 ⁢  P 2  2 where Sim (q 1 , q 2 ) is a similarity score of a first query q 1 , of the at least the portion of the first queries, q 2 is a head query of the plurality of head queries, P 1 is a vector of user selection counts for search results of q 1 , and P 2 is a vector of user selection counts for search results of q 2 ; and clustering the at least the portion of the first queries to the plurality of head queries according to the similarity scores; associate one or more categories with each head query of the plurality of head queries; receive a second query; determine a similarity between the second query and at least one of a selected head query of the plurality of head queries; associate the second query with the selected head query of the plurality of head queries according to the similarity between the second query and the at least one of the selected head query; and identify one or more documents relevant to the second query using the one or more categories associated with the selected head query of the plurality of head queries.

8. A system for searching, the system comprising one or more processors and one or more memory devices coupled to the one or more processors, the one or more memory devices storing executable and operational data effective to cause the one or more processors to: receive first queries, from a user; select a plurality of head queries from among the first queries; cluster the first queries, exclusive of the plurality of head queries, to the plurality of head queries by: calculating similarity scores for at least a portion of the first queries relative to the plurality of head queries by evaluating response similarity between user selections of search results for the at least the portion of the first queries and user selections of search results for the plurality of head queries, by evaluating an equation: Sim ( q 1 , q 2 ) = P 1 · P 2  P 1  2 ⁢  P 2  2 where Sim (q 1 , q 2 ) is a similarity score of a first query q 1 , of the at least the portion of the first queries, q 2 is a head query of the plurality of head queries, P 1 is a vector of user selection counts for search results of q 1 , and P 2 is a vector of user selection counts for search results of q 2 ; and clustering the at least the portion of the first queries to the plurality of head queries according to the similarity scores; associate one or more categories with each head query of the plurality of head queries; receive a second query; determine a similarity between the second query and at least one of a selected head query of the plurality of head queries; associate the second query with the selected head query of the plurality of head queries according to the similarity between the second query and the at least one of the selected head query; and identify one or more documents relevant to the second query using the one or more categories associated with the selected head query of the plurality of head queries. 9. The system of claim 8 , wherein the executable and operational data are further effective to cause the one or more processors to calculate the similarity scores for the at least the portion of the first queries relative to the plurality of head queries by determining co-occurrences of the at least the portion of the first queries with the plurality of head queries in a same user session.

1. A handheld computing device, comprising: a user interface; a digital data processor coupled to the user interface and programmed to perform operations comprising: over time, monitoring and recording cues describing the device environment and monitoring and recording user performed actions of configuring the device and operating its application programs; learning which if any of the recorded cues and combinations of recorded cues are relevant predictors of which of the recorded user actions; for each user action having a learned relevant predictor, planning one or more of the following types of machine-executed actions: configuring the device to streamline user performance of the user action; causing the device to perform the user action; responsive to occurrence of learned relevant predictors of user actions, performing the machine-executed actions planned for the learned relevant predictors that occurred; the operations further comprising prioritizing interpretation of inherently ambiguous user-entered text input by favoring a disambiguated interpretation consistent with the present environment of the device, where the present environment of the device includes detected geographic location and the prioritizing operation comprises planning a disambiguation operation comprising favoring interpretations of user-entered text input consistent with said geographic location.

1. A handheld computing device, comprising: a user interface; a digital data processor coupled to the user interface and programmed to perform operations comprising: over time, monitoring and recording cues describing the device environment and monitoring and recording user performed actions of configuring the device and operating its application programs; learning which if any of the recorded cues and combinations of recorded cues are relevant predictors of which of the recorded user actions; for each user action having a learned relevant predictor, planning one or more of the following types of machine-executed actions: configuring the device to streamline user performance of the user action; causing the device to perform the user action; responsive to occurrence of learned relevant predictors of user actions, performing the machine-executed actions planned for the learned relevant predictors that occurred; the operations further comprising prioritizing interpretation of inherently ambiguous user-entered text input by favoring a disambiguated interpretation consistent with the present environment of the device, where the present environment of the device includes detected geographic location and the prioritizing operation comprises planning a disambiguation operation comprising favoring interpretations of user-entered text input consistent with said geographic location. 3. The device of claim 1 , where the operation of configuring of the device to streamline user performance of the user action includes at least the following operations: configuring hardware of the device; starting an application program or system function of the device; starting an operation whose initiation is represented upon one or more menus provided by the device; bypassing or prioritizing one or more components of one or more menus provided by the device; and entering a hardware or software mode of the device.

11. The computer system of claim 10 , wherein: using the maximum a posteriori probability process includes restricting estimation of statistical changes such that an amount of acoustic parameters from the baseline acoustic speech model that have an estimated statistical change is less than a total number of acoustic parameters included in the baseline acoustic speech model, further comprising storing the changes as acoustic parameter adaptation data linked to the first speaker.

11. The computer system of claim 10 , wherein: using the maximum a posteriori probability process includes restricting estimation of statistical changes such that an amount of acoustic parameters from the baseline acoustic speech model that have an estimated statistical change is less than a total number of acoustic parameters included in the baseline acoustic speech model, further comprising storing the changes as acoustic parameter adaptation data linked to the first speaker. 13. The computer system of claim 11 , wherein restricting estimation of statistical changes includes imposing a penalty on movement of exponential family variables when calculating statistical change.

1. A system that facilitates speech translation, comprising: a processor; a speech recognition component operated by the processor that processes sensed data of a current context and facilitates a speech recognition process based on the sensed data; a historical activities component operated by the processor that stores historical data associated with the speech recognition process; a language model operated by the processor that is created to recognize speech of the user and which is updated based on interactions with a user and on responses of a foreign language speakers, wherein the foreign language speaker is a person being addressed and provides the responses via a backchannel between the system and a device of the foreign language speaker; and a language opportunity component operated by the processor that improves the speech recognition process by pushing a training session of one or more terms to the user which increases likelihood of success when using the one or more terms during the speech recognition process.

1. A system that facilitates speech translation, comprising: a processor; a speech recognition component operated by the processor that processes sensed data of a current context and facilitates a speech recognition process based on the sensed data; a historical activities component operated by the processor that stores historical data associated with the speech recognition process; a language model operated by the processor that is created to recognize speech of the user and which is updated based on interactions with a user and on responses of a foreign language speakers, wherein the foreign language speaker is a person being addressed and provides the responses via a backchannel between the system and a device of the foreign language speaker; and a language opportunity component operated by the processor that improves the speech recognition process by pushing a training session of one or more terms to the user which increases likelihood of success when using the one or more terms during the speech recognition process. 5. The system of claim 1 , further comprising a simulator component utilized for training a user how to speak a foreign language.

1. A method for searching a text that comprises a sequence of symbols for occurrences of a pattern of the symbols, using a sequence of evaluations at respective positions in the text, the method comprising: performing a first evaluation of whether the pattern occurs in a current position in the text, wherein the performing comprises: positioning the pattern so as to end at the current position in the text, comparing the symbols of the pattern to the corresponding symbols of the text while progressing from an end to a beginning of the pattern, and upon finding a mismatch between the pattern and the text, calculating the jump to the subsequent position depending at least on the mismatch; if the pattern does not occur in the current position, calculating a size of a jump to a subsequent position in the text based on results of the first evaluation; and performing a second evaluation of whether the pattern occurs in the subsequent position in the text.

1. A method for searching a text that comprises a sequence of symbols for occurrences of a pattern of the symbols, using a sequence of evaluations at respective positions in the text, the method comprising: performing a first evaluation of whether the pattern occurs in a current position in the text, wherein the performing comprises: positioning the pattern so as to end at the current position in the text, comparing the symbols of the pattern to the corresponding symbols of the text while progressing from an end to a beginning of the pattern, and upon finding a mismatch between the pattern and the text, calculating the jump to the subsequent position depending at least on the mismatch; if the pattern does not occur in the current position, calculating a size of a jump to a subsequent position in the text based on results of the first evaluation; and performing a second evaluation of whether the pattern occurs in the subsequent position in the text. 7. The method according to claim 1 , wherein performing the first evaluation comprises updating a data structure that indicates the positions in the text in which the pattern cannot occur, and wherein calculating the size of the jump comprises computing the size of the jump based on the updated data structure.

1. Apparatus which receives spoken input training words and a subsequent spoken input command word and generates a correlation function that is indicative of the resemblance of the command word to each training word, comprising: a. feature extraction means for processing received input words and generating digital feature output signals on particular ones of a number of feature output lines, the particular ones being dependent upon the features present in an input word; b. means for storing, as a time dependent matrix, the presence or absence status of the feature signals which occur during each training word; c. means for storing, as a time dependent matrix, the presence or absence status of the feature signals which occur during the command word; and d. means for comparing, member by member, the command word matrix with each training word matrix and for generating a correlation figure which reflects each matrix comparison, the member comparisons taking account only of the presence of features in the matrices being compared.

1. Apparatus which receives spoken input training words and a subsequent spoken input command word and generates a correlation function that is indicative of the resemblance of the command word to each training word, comprising: a. feature extraction means for processing received input words and generating digital feature output signals on particular ones of a number of feature output lines, the particular ones being dependent upon the features present in an input word; b. means for storing, as a time dependent matrix, the presence or absence status of the feature signals which occur during each training word; c. means for storing, as a time dependent matrix, the presence or absence status of the feature signals which occur during the command word; and d. means for comparing, member by member, the command word matrix with each training word matrix and for generating a correlation figure which reflects each matrix comparison, the member comparisons taking account only of the presence of features in the matrices being compared. 4. Apparatus as defined by claim 1 further comprising means for comparing, on a time shifted basis, the command word matrix with each training word matrix and for generating a supplementary correlation figure which reflects each such comparison.

11. In a computer network comprising a server system and a client system, a server-controlled method for generating a style sheet used by the client system to format a document for presentation on an output device attached to the client system comprising the steps of: retrieving the document and a layout generator; and using the layout generator to perform the steps of: interrogating the output device coupled to the client system to determine a set of capabilities of the output device; based upon the set of capabilities of the output device, generating a style sheet having a plurality of style definitions; and sending the style sheet and the document to the client system.

11. In a computer network comprising a server system and a client system, a server-controlled method for generating a style sheet used by the client system to format a document for presentation on an output device attached to the client system comprising the steps of: retrieving the document and a layout generator; and using the layout generator to perform the steps of: interrogating the output device coupled to the client system to determine a set of capabilities of the output device; based upon the set of capabilities of the output device, generating a style sheet having a plurality of style definitions; and sending the style sheet and the document to the client system. 16. The server-controlled method of claim 11, wherein the style sheet is embedded in the document.

14. A contents management apparatus, comprising: an interface unit configured to connect to at least one external device; a touch screen configured to display at least one first graphical user interface object representing at least one external device connected to the contents management apparatus and second graphical user interface objects representing contents stored in the at least one connected external device; and at least one processor control unit configured to: receive a selection of a first or second graphical user interface object of the displayed first and second graphical user interface objects; detect an input drag of the selected graphical user interface object; filter, in response to detection of the input drag, the displayed first and second graphical user interface objects based on one or more attributes associated with the dragged graphical user interface object; and cause the touch screen to display, in response to filtration of the displayed first and second graphical user interface objects, a filtered set of graphical user interface objects, wherein causation of the touch screen to display the filtered set of graphical user interface objects comprises the at least one processor being configured to: detect a drag of a search object comprising a keyword to an area, the area comprising a display of the first and second graphical user interface objects; check metadata associated with the first and second graphical user interface objects displayed in proximity to the search object; and cause the touch screen to display graphical user interface objects stuck to the search object, the stuck graphical user interface objects comprising metadata comprising the keyword.

14. A contents management apparatus, comprising: an interface unit configured to connect to at least one external device; a touch screen configured to display at least one first graphical user interface object representing at least one external device connected to the contents management apparatus and second graphical user interface objects representing contents stored in the at least one connected external device; and at least one processor control unit configured to: receive a selection of a first or second graphical user interface object of the displayed first and second graphical user interface objects; detect an input drag of the selected graphical user interface object; filter, in response to detection of the input drag, the displayed first and second graphical user interface objects based on one or more attributes associated with the dragged graphical user interface object; and cause the touch screen to display, in response to filtration of the displayed first and second graphical user interface objects, a filtered set of graphical user interface objects, wherein causation of the touch screen to display the filtered set of graphical user interface objects comprises the at least one processor being configured to: detect a drag of a search object comprising a keyword to an area, the area comprising a display of the first and second graphical user interface objects; check metadata associated with the first and second graphical user interface objects displayed in proximity to the search object; and cause the touch screen to display graphical user interface objects stuck to the search object, the stuck graphical user interface objects comprising metadata comprising the keyword. 18. The contents management apparatus of claim 14 , wherein the at least one processor is further configured to: receive information corresponding to an input drag of a graphical user interface object of the filtered set of graphical user interface objects; determine an input drag direction based on the information; and filter the filtered set of graphical user interface objects based on at least one attribute associated with the input drag direction.

20. A computer-readable medium having computer-executable instructions for: performing a presentation, on a display device, of a customized visualization in an industrial automation environment, comprising further instructions for: determining data relating to an industrial automation environment in connection with presenting a first data visualization, including the data, on a first display device, wherein the first data visualization comprises a first display object subset; capturing context information pertaining to the first data visualization; determining a second display object subset facilitating presenting of the data as a function of the context information, wherein the first display object subset and second display object subset comprise at least one display object selected from a set of display objects and the first display object subset and the second display object subset are non-overlapping; selecting the second display object subset; and updating, dynamically, the first data visualization with a second data visualization displaying the data with the second display object subset.

20. A computer-readable medium having computer-executable instructions for: performing a presentation, on a display device, of a customized visualization in an industrial automation environment, comprising further instructions for: determining data relating to an industrial automation environment in connection with presenting a first data visualization, including the data, on a first display device, wherein the first data visualization comprises a first display object subset; capturing context information pertaining to the first data visualization; determining a second display object subset facilitating presenting of the data as a function of the context information, wherein the first display object subset and second display object subset comprise at least one display object selected from a set of display objects and the first display object subset and the second display object subset are non-overlapping; selecting the second display object subset; and updating, dynamically, the first data visualization with a second data visualization displaying the data with the second display object subset. 23. The computer-readable medium of claim 20 , further comprising capturing at least one of: a role of an entity, entity access rights, prior interactions by the entity, a current entity state, entity preferences, or historical data in connection with inferring or determining a current or future intent of the entity.

1. A method, comprising: receiving user input to an input component of an information handling device; generating a machine based representation of the user input; analyzing, using a processor, the representation of the user input; forming, using a processor, a tag based on contextual user data related to the user input; and providing, using a processor, an indication of the tag.

1. A method, comprising: receiving user input to an input component of an information handling device; generating a machine based representation of the user input; analyzing, using a processor, the representation of the user input; forming, using a processor, a tag based on contextual user data related to the user input; and providing, using a processor, an indication of the tag. 10. The method of claim 1 , wherein the user input is selected from the group of user inputs consisting of physical keyboard input, soft key input, audio input, and handwriting input.

19. The method of claim 18 , wherein the processing step further includes using the presentation data to present the electronic image on a presentation device, and to retrieve the information data, whereupon retrieving the information data the processing step uses the information data to present the information contain in the region on the presentation device.

19. The method of claim 18 , wherein the processing step further includes using the presentation data to present the electronic image on a presentation device, and to retrieve the information data, whereupon retrieving the information data the processing step uses the information data to present the information contain in the region on the presentation device. 39. The method of claim 19 , wherein the processing step further includes retrieving and presenting the information data with additional business process buttons.

1. A method, comprising: identifying a first network comprising one or more indexed classes of artificial neurons; and determining one or more tags for the one or more indexed classes of artificial neurons regardless of their indexing, wherein determining the one or more tags for the one or more indexed classes of artificial neurons comprises: 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.

1. A method, comprising: identifying a first network comprising one or more indexed classes of artificial neurons; and determining one or more tags for the one or more indexed classes of artificial neurons regardless of their indexing, wherein determining the one or more tags for the one or more indexed classes of artificial neurons comprises: 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. 2. The method of claim 1 , wherein determining the one or more indexed classes of artificial neurons comprises using an unsupervised learning algorithm.

1. A computer system comprising: a storage for storing a list of menu options corresponding to functions and for storing a description of said menu options; an input for receiving a first user input indicating a designation of one of said list of menu options and for receiving a second user input indicating a selection of said one of said list of menu options; a processor for determining in response to said input which of said menu options is currently designated by said user, for retrieving and providing to a user said description of said currently designated menu option prior to receipt of said second user input, and for executing said function based on the receipt of said second user input relating to said selection of said one of said list, wherein said description is stored apart from said function.

1. A computer system comprising: a storage for storing a list of menu options corresponding to functions and for storing a description of said menu options; an input for receiving a first user input indicating a designation of one of said list of menu options and for receiving a second user input indicating a selection of said one of said list of menu options; a processor for determining in response to said input which of said menu options is currently designated by said user, for retrieving and providing to a user said description of said currently designated menu option prior to receipt of said second user input, and for executing said function based on the receipt of said second user input relating to said selection of said one of said list, wherein said description is stored apart from said function. 2. The computer system of claim 1, wherein said description includes image files.

8. The system of claim 7 wherein said format element includes a color merge element wherein an area on the display defined by two overlapping expandable container images displays a color different from the colors unique to the two overlapping expandable container images.

8. The system of claim 7 wherein said format element includes a color merge element wherein an area on the display defined by two overlapping expandable container images displays a color different from the colors unique to the two overlapping expandable container images. 9. The system of claim 8 wherein the color in the area on the display defined by two overlapping expandable container images has a spectral relationship to each of the colors in the two overlapping expandable container images.

1. A method comprising: receiving a set of text derived from a speech-to-text translation of an audio signal; comparing the set of text to reference text to identify errors in the received set of text; producing a respective weighted value for each of the identified errors, a magnitude of each of the weighted values varying depending on a type of the translation error; and utilizing the weighted values to generate a metric indicating a level of quality of the set of text with respect to the reference text.

1. A method comprising: receiving a set of text derived from a speech-to-text translation of an audio signal; comparing the set of text to reference text to identify errors in the received set of text; producing a respective weighted value for each of the identified errors, a magnitude of each of the weighted values varying depending on a type of the translation error; and utilizing the weighted values to generate a metric indicating a level of quality of the set of text with respect to the reference text. 4. The method as in claim 1 , wherein the errors include at least one type from the group consisting of: i) a word substitution type errors, ii) a word insertion type errors, and iii) a word omission type errors.

1. A computer-implemented method comprising: in response to receiving the query, selecting, from a search corpus, a set of documents that are relevant to the query; wherein the set of documents includes at least a first document and a second document; for each particular document within at least a subset of the set of documents, extracting one or more lists contained within that particular document and adding the one or more lists into a set of lists; wherein extracting one or more lists includes, extracting a first list from the first document and extracting a second list from the second document; for each particular list in the set of lists, generating a list score for the particular list based at least in part on a number of occurrences of items in the particular list within other lists in the set of lists; wherein generating a list score includes generating a first list score for the first list extracted from the first document, and generating a second list score for the second list extracted from the second document; for each particular document within at least the subset of documents, generating a document score for the particular document based at least in part on the list score generated for at least one list contained within the particular document; wherein generating a document score includes generating a first document score for the first document based, at least in part, on the first list score generated for the first list that was extracted from the first document; generating a second document score for the second document based, at least in part, on the second list score generated for the second list that was extracted from the second document; and generating a search results page that presents references to selected documents from at least the subset of documents in an order that is based at least in part on the document scores generated for the selected documents; wherein the method is performed by one or more computing devices.

1. A computer-implemented method comprising: in response to receiving the query, selecting, from a search corpus, a set of documents that are relevant to the query; wherein the set of documents includes at least a first document and a second document; for each particular document within at least a subset of the set of documents, extracting one or more lists contained within that particular document and adding the one or more lists into a set of lists; wherein extracting one or more lists includes, extracting a first list from the first document and extracting a second list from the second document; for each particular list in the set of lists, generating a list score for the particular list based at least in part on a number of occurrences of items in the particular list within other lists in the set of lists; wherein generating a list score includes generating a first list score for the first list extracted from the first document, and generating a second list score for the second list extracted from the second document; for each particular document within at least the subset of documents, generating a document score for the particular document based at least in part on the list score generated for at least one list contained within the particular document; wherein generating a document score includes generating a first document score for the first document based, at least in part, on the first list score generated for the first list that was extracted from the first document; generating a second document score for the second document based, at least in part, on the second list score generated for the second list that was extracted from the second document; and generating a search results page that presents references to selected documents from at least the subset of documents in an order that is based at least in part on the document scores generated for the selected documents; wherein the method is performed by one or more computing devices. 10. The method of claim 1 , wherein the step of generating the search results page that presents references to the selected result documents comprises placing, with each reference to each particular selected result document within the search results page, at least a subset of list items contained within a highest-scoring list extracted from that particular selected result document.

41. A data collection system comprising: a data collection terminal having a encoded information reader device; and a computer spaced apart from said data collection terminal that receives from a user identification of first and second files for transfer to said data collection terminal, prompts a user to enter at least one action indicator for each file identified by a user, creates a single data package incorporating file data corresponding to the identified first and second files and at least one action indicator, and enables a transfer of the single data package to said data collection terminal.

41. A data collection system comprising: a data collection terminal having a encoded information reader device; and a computer spaced apart from said data collection terminal that receives from a user identification of first and second files for transfer to said data collection terminal, prompts a user to enter at least one action indicator for each file identified by a user, creates a single data package incorporating file data corresponding to the identified first and second files and at least one action indicator, and enables a transfer of the single data package to said data collection terminal. 58. The data collection system of claim 41 , wherein the computer is configured to display a tree diagram displaying indicators of said first and second files, and wherein said computer is further configured to display at least one of a compression selection designator and encryption selection designator in said tree diagram, and wherein said computer is configured to compress and/or encrypt file data of said single data package in accordance with the position of said compression and/or encryption selection data indicated represented in said tree diagram.

1. A method of automatically configuring a portlet, the method comprising: receiving a portlet with content to be rendered as a portlet window object within a portal; examining the content of the portlet for discovering a contextual aspect; and automatically adjusting at least one attribute of the portlet window object based on the discovered contextual aspect.

1. A method of automatically configuring a portlet, the method comprising: receiving a portlet with content to be rendered as a portlet window object within a portal; examining the content of the portlet for discovering a contextual aspect; and automatically adjusting at least one attribute of the portlet window object based on the discovered contextual aspect. 9. The method of claim 1 , wherein one of the contextual aspect and the attribute information are user editable.

13. A computer-implemented method of operating a computerized search engine to identify and rank relevant documents from a corpus of citationally-related source documents, said computer-implemented method comprising the following steps executed, in order, by a computing device configured with specific computer-executable instructions: (1) receiving an input search query comprising a first set of identification information identifying a set of input documents selected from said corpus; (2) using said first set of identification information to ascertain, from a search index stored on an associated data storage device, a second set of identification information identifying a set of output documents selected from said corpus, said search index comprising: (a) a third set of identification information identifying potential input documents that may be selected from said corpus; (b) a fourth set of identification information identifying, for each said potential input document, a selected number of citationally-related potential output documents selected from said corpus; and (c) a first numerical score that is statistically correlated to the probability that a direct citation exists between each corresponding pair of citationally-related potential input document and potential output document, and wherein said first numerical score is calculated based on how many indirect citations exist between each said pair of citationally related documents and, for each indirect citation, how many citation links separate each said pair of citationally-related documents; (3) calculating, responsive to receiving said input search query, a second numerical score that is statistically correlated to the probability that a direct citation exists between any document comprising said set of input documents and each corresponding document comprising said set of output documents, and wherein said second numerical score is calculated based at least in part on said first numerical score; (4) generating a search query result set comprising identification information identifying one or more of said output documents and wherein said search query result set is sorted or ranked in accordance with said second numerical score; and (5) storing said search query result set.

13. A computer-implemented method of operating a computerized search engine to identify and rank relevant documents from a corpus of citationally-related source documents, said computer-implemented method comprising the following steps executed, in order, by a computing device configured with specific computer-executable instructions: (1) receiving an input search query comprising a first set of identification information identifying a set of input documents selected from said corpus; (2) using said first set of identification information to ascertain, from a search index stored on an associated data storage device, a second set of identification information identifying a set of output documents selected from said corpus, said search index comprising: (a) a third set of identification information identifying potential input documents that may be selected from said corpus; (b) a fourth set of identification information identifying, for each said potential input document, a selected number of citationally-related potential output documents selected from said corpus; and (c) a first numerical score that is statistically correlated to the probability that a direct citation exists between each corresponding pair of citationally-related potential input document and potential output document, and wherein said first numerical score is calculated based on how many indirect citations exist between each said pair of citationally related documents and, for each indirect citation, how many citation links separate each said pair of citationally-related documents; (3) calculating, responsive to receiving said input search query, a second numerical score that is statistically correlated to the probability that a direct citation exists between any document comprising said set of input documents and each corresponding document comprising said set of output documents, and wherein said second numerical score is calculated based at least in part on said first numerical score; (4) generating a search query result set comprising identification information identifying one or more of said output documents and wherein said search query result set is sorted or ranked in accordance with said second numerical score; and (5) storing said search query result set. 16. The computer-implemented method of claim 13 wherein said search query result set is aggregated by output document.

16. The computer-readable medium of claim 15 , wherein the operations further comprise: receiving a plurality of sets of predictive modeling training data from a first plurality of client computing systems; for each set of plurality of sets of predictive modeling training data: using the training data and a plurality of training functions to train a plurality of predictive models; generating a respective score for each of the plurality of trained predictive models, where each score represents an estimation of the effectiveness of the trained predictive model; and selecting a trained predictive model from among the plurality of trained predictive models based on the generated scores; wherein a plurality of trained predictive models are thereby generated and selected; storing the plurality of selected trained predictive models in the repository of trained predictive models.

16. The computer-readable medium of claim 15 , wherein the operations further comprise: receiving a plurality of sets of predictive modeling training data from a first plurality of client computing systems; for each set of plurality of sets of predictive modeling training data: using the training data and a plurality of training functions to train a plurality of predictive models; generating a respective score for each of the plurality of trained predictive models, where each score represents an estimation of the effectiveness of the trained predictive model; and selecting a trained predictive model from among the plurality of trained predictive models based on the generated scores; wherein a plurality of trained predictive models are thereby generated and selected; storing the plurality of selected trained predictive models in the repository of trained predictive models. 18. The computer-readable medium of claim 16 , wherein the operations further comprise: providing a web page accessible by the client computing system that is configured to browse the repository of trained predictive models.

6. The system architecture of claim 5, wherein load numbers are tabulated and stored by the load balancing circuit.

6. The system architecture of claim 5, wherein load numbers are tabulated and stored by the load balancing circuit. 7. The system architecture of claim 6, wherein the load balancing circuit identifies the preferred processor circuit by comparing the usage numbers and the load numbers for each processor circuit.

15. The method of claim 11 , wherein the brand item profile comprises a collection of data corresponding to a particular brand item to be displayed to one or more SMS members via the particular SMS account.

15. The method of claim 11 , wherein the brand item profile comprises a collection of data corresponding to a particular brand item to be displayed to one or more SMS members via the particular SMS account. 16. The method of claim 15 , wherein the brand item is selected from the group consisting of: a retail location of the marketer, a branch location of the marketer, a franchise location of the marketer, a product of the marketer, a product line of the marketer, a service of the marketer, a consumer segment, a trademark of the marketer.

17. A product placement system for selecting at least one product record for display in a user interface rendered by a computing device, the system comprising: a computing device adapted to analyze at least a portion of a document for at least a frequency of words in the document; a computing device adapted to construct a query search string based on the analysis of the document, the query search string at least partially based on words of the document having the highest frequencies; a computing device adapted to apply the query search string to a products database, the products database including a plurality of product records which include information regarding products, to identify at least one product record in the products database that satisfies the query search string; a computing device adapted to select at least one of the identified product records for embedding into the document and display in the user interface, and a computing device adapted to embed at least one of the selected product records into the document for display in the user interface, wherein the document is not stored within the products database.

17. A product placement system for selecting at least one product record for display in a user interface rendered by a computing device, the system comprising: a computing device adapted to analyze at least a portion of a document for at least a frequency of words in the document; a computing device adapted to construct a query search string based on the analysis of the document, the query search string at least partially based on words of the document having the highest frequencies; a computing device adapted to apply the query search string to a products database, the products database including a plurality of product records which include information regarding products, to identify at least one product record in the products database that satisfies the query search string; a computing device adapted to select at least one of the identified product records for embedding into the document and display in the user interface, and a computing device adapted to embed at least one of the selected product records into the document for display in the user interface, wherein the document is not stored within the products database. 21. The system of claim 17 , wherein the user interface is a web page graphically rendered by a browser.

2. A computer program product comprising a computer-readable storage medium having computer-readable program code instructions stored therein comprising: a first set of instructions for identifying at least one new resource to add to a cloud, the cloud comprising at least one preexisting resource; a second set of instructions for creating an ontology extension for the at least one new resource including metadata associated with the at least one new resource; a third set of instructions for creating a relationship between the at least one new resource and the at least one preexisting resource, evaluating the relationship, and storing information regarding the relationship among the metadata included in the ontology extension; and a fourth set of instructions for storing the ontology extension.

2. A computer program product comprising a computer-readable storage medium having computer-readable program code instructions stored therein comprising: a first set of instructions for identifying at least one new resource to add to a cloud, the cloud comprising at least one preexisting resource; a second set of instructions for creating an ontology extension for the at least one new resource including metadata associated with the at least one new resource; a third set of instructions for creating a relationship between the at least one new resource and the at least one preexisting resource, evaluating the relationship, and storing information regarding the relationship among the metadata included in the ontology extension; and a fourth set of instructions for storing the ontology extension. 12. The computer program product of claim 2 , wherein the metadata associated with the at least one new resource comprises instance information that includes capabilities supported by each of the at least one new resource.

1. A method of generating speech from text messages, comprising: determining a speech feature vector for a voice associated with a source of a first text message; comparing the speech feature vector to a plurality of speaker models, wherein the plurality of speaker models are unrelated to the source of the first text message; based on the comparison, selecting one of the speaker models as a preferred match for the voice; associating the selected speaker model with the source of the first text message; if the speech feature vector cannot be determined, selecting one of the speaker models as a default selection; generating speech from the text message based on the selected speaker model; and automatically generating speech from subsequent text messages received from the source of the first text message, based on the selected speaker model.

1. A method of generating speech from text messages, comprising: determining a speech feature vector for a voice associated with a source of a first text message; comparing the speech feature vector to a plurality of speaker models, wherein the plurality of speaker models are unrelated to the source of the first text message; based on the comparison, selecting one of the speaker models as a preferred match for the voice; associating the selected speaker model with the source of the first text message; if the speech feature vector cannot be determined, selecting one of the speaker models as a default selection; generating speech from the text message based on the selected speaker model; and automatically generating speech from subsequent text messages received from the source of the first text message, based on the selected speaker model. 5. The method of claim 1 , wherein: the speech feature vector comprises a feature vectors for a Gaussian mixture model; and the step of comparing comprises comparing a first Gaussian mixture model associated with the speech feature vector with a plurality of second Gaussian mixture models, each second Gaussian mixture model associated with at least one of the speaker models.

1. A method of generating speech from text messages, comprising: determining a speech feature vector for a voice associated with a source of a first text message; comparing the speech feature vector to a plurality of speaker models, wherein the plurality of speaker models are unrelated to the source of the first text message; based on the comparison, selecting one of the speaker models as a preferred match for the voice; associating the selected speaker model with the source of the first text message; if the speech feature vector cannot be determined, selecting one of the speaker models as a default selection; generating speech from the text message based on the selected speaker model; and automatically generating speech from subsequent text messages received from the source of the first text message, based on the selected speaker model.

1. A method of generating speech from text messages, comprising: determining a speech feature vector for a voice associated with a source of a first text message; comparing the speech feature vector to a plurality of speaker models, wherein the plurality of speaker models are unrelated to the source of the first text message; based on the comparison, selecting one of the speaker models as a preferred match for the voice; associating the selected speaker model with the source of the first text message; if the speech feature vector cannot be determined, selecting one of the speaker models as a default selection; generating speech from the text message based on the selected speaker model; and automatically generating speech from subsequent text messages received from the source of the first text message, based on the selected speaker model. 3. The method of claim 1 , wherein the step of determining comprises: requesting an endpoint that is the source of the text message to provide the speech feature vector; and receiving the speech feature vector from the endpoint.

9. A method comprising: receiving at an input module of a query rewrite input language (QRIL) processor device, a one or more QRIL records, each QRIL record comprising a trigger value, a query rewrite value, and one or more metaflag elements comprising a query rewrite type metaflag that identifies each QRIL record as associated with a query rewrite type, wherein the QRIL processor device comprises a memory and one or more processors coupled to the memory; identifying, by a rewrite resolver module, a first query rewrite type for a first QRIL record of the one or more QRIL records; processing, by the rewrite resolver module, using the first query rewrite type, the first QRIL record to identify a set of precedence issues between the first QRIL record and at least one overlapping or conflicting QRIL record; identifying, by a search engine rewrite customization module, a first search engine and a first rewrite semantic structure associated with the first search engine; generating, by the search engine rewrite customization module, a first standardized rewrite from the first QRIL record, the set of precedence issues, and the first rewrite semantic structure, wherein the first standardized rewrite comprises a standardized trigger value, a standardized rewrite expression for rewriting an input query for the first search engine, and a bag of words dictionary; and providing, by the QRIL processor device, the first standardized rewrite to facilitate executing a user query using the first standardized rewrite.

9. A method comprising: receiving at an input module of a query rewrite input language (QRIL) processor device, a one or more QRIL records, each QRIL record comprising a trigger value, a query rewrite value, and one or more metaflag elements comprising a query rewrite type metaflag that identifies each QRIL record as associated with a query rewrite type, wherein the QRIL processor device comprises a memory and one or more processors coupled to the memory; identifying, by a rewrite resolver module, a first query rewrite type for a first QRIL record of the one or more QRIL records; processing, by the rewrite resolver module, using the first query rewrite type, the first QRIL record to identify a set of precedence issues between the first QRIL record and at least one overlapping or conflicting QRIL record; identifying, by a search engine rewrite customization module, a first search engine and a first rewrite semantic structure associated with the first search engine; generating, by the search engine rewrite customization module, a first standardized rewrite from the first QRIL record, the set of precedence issues, and the first rewrite semantic structure, wherein the first standardized rewrite comprises a standardized trigger value, a standardized rewrite expression for rewriting an input query for the first search engine, and a bag of words dictionary; and providing, by the QRIL processor device, the first standardized rewrite to facilitate executing a user query using the first standardized rewrite. 10. The method of claim 9 further comprising: analyzing, using a segmenter module, a first trigger value of the first QRIL to identify one or more trigger segments; and analyzing, using the segmenter module, the one or more QRIL records to identify trigger values that match at least one of the one or more trigger segments.

18. A computer-implemented method for automatically determining an execution order of a scripted workflow, comprising: selecting a first scripted action from a plurality of actions, wherein the plurality of actions are contemporaneously selectable with respect to the first scripted action; executing the first selected scripted action if sufficient parameter information is available to execute the selected first scripted action; selecting a second scripted action from the plurality of actions in response to determining that there is insufficient parameter information to execute the first selected scripted action; executing the second selected action and; wherein the second scripted action converts data from an incompatible data type into a compatible data type and wherein the scripted action are selected from candidate actions chosen according to a determination of relevance relative to previously chosen action and need for conversion of data to compatible data types.

18. A computer-implemented method for automatically determining an execution order of a scripted workflow, comprising: selecting a first scripted action from a plurality of actions, wherein the plurality of actions are contemporaneously selectable with respect to the first scripted action; executing the first selected scripted action if sufficient parameter information is available to execute the selected first scripted action; selecting a second scripted action from the plurality of actions in response to determining that there is insufficient parameter information to execute the first selected scripted action; executing the second selected action and; wherein the second scripted action converts data from an incompatible data type into a compatible data type and wherein the scripted action are selected from candidate actions chosen according to a determination of relevance relative to previously chosen action and need for conversion of data to compatible data types. 19. The computer-implemented method of claim 18 further comprising executing a third selected action from the plurality of actions.

8. A computer program product comprising a computer readable storage medium having a set of instructions stored therein which, when executed by a processor, causes the processor to process task-oriented electronic messages by: identifying an electronic message generated by a first user with an electronic communication tool and directed to a first recipient; intercepting the electronic message before the electronic message is available to the first recipient; analyzing the electronic message to identity a set of requests to perform a corresponding set of tasks; responsive to identifying the set of requests, composing a task statement that summarizes each request to perform a corresponding task; sending, to the first recipient, the electronic message using the electronic communication tool; receiving a reply message from the first recipient; determining that one or more tasks of the corresponding set of tasks are not addressed in the reply message; responsive to a determination that the one or more tasks are not addressed in the reply message, generating an interactive interface including the task statement and a corresponding set of selectable disposition actions for each of the one or more tasks that is not addressed including respond later, respond now, ignore, delegate, open the electronic message in a native messaging application, and already answered; displaying, to the first recipient, the electronic message and the interactive interlace including the task statement and the corresponding set of selectable disposition actions; responsive to selection, by the first recipient, of a disposition action from the corresponding set of selectable disposition actions, taking the disposition action; and responsive to selection of the disposition action to ignore a first task of the corresponding set of tasks, recording the first task as addressed to prevent generation of the first task in a subsequent interactive interface corresponding to the electronic message.

8. A computer program product comprising a computer readable storage medium having a set of instructions stored therein which, when executed by a processor, causes the processor to process task-oriented electronic messages by: identifying an electronic message generated by a first user with an electronic communication tool and directed to a first recipient; intercepting the electronic message before the electronic message is available to the first recipient; analyzing the electronic message to identity a set of requests to perform a corresponding set of tasks; responsive to identifying the set of requests, composing a task statement that summarizes each request to perform a corresponding task; sending, to the first recipient, the electronic message using the electronic communication tool; receiving a reply message from the first recipient; determining that one or more tasks of the corresponding set of tasks are not addressed in the reply message; responsive to a determination that the one or more tasks are not addressed in the reply message, generating an interactive interface including the task statement and a corresponding set of selectable disposition actions for each of the one or more tasks that is not addressed including respond later, respond now, ignore, delegate, open the electronic message in a native messaging application, and already answered; displaying, to the first recipient, the electronic message and the interactive interlace including the task statement and the corresponding set of selectable disposition actions; responsive to selection, by the first recipient, of a disposition action from the corresponding set of selectable disposition actions, taking the disposition action; and responsive to selection of the disposition action to ignore a first task of the corresponding set of tasks, recording the first task as addressed to prevent generation of the first task in a subsequent interactive interface corresponding to the electronic message. 13. The computer program product of claim 8 , further comprising: monitoring, according to a pre-defined schedule, the electronic communication tool for the electronic message directed to the first recipient.

1. A method of goal-oriented searching, the method comprising: providing a graphical user interface (GUI) to a user device from a server, the GUI including an input field accessible by a user to provide a text input and a selectable indicator accessible by the user to select one of a plurality of goal-oriented searches, each of the plurality of goal-oriented searches comprising a pre-defined query stored at a server prior to interaction by the user; receiving a user input including the text input and a selection corresponding to the selectable indicator indicating a selected one of the plurality of pre-defined goal oriented searches; retrieving a first document based on the text input; searching one or more data sources based on data extracted from the first document and according to search parameters defined by the selected one of the plurality of pre-defined goal oriented searches to identify a set of documents; applying a rule derived from explicit user interactions and implicit user interactions to produce a matrix including highest probability keywords identified from the search results; identifying a plurality of search results using a greedy algorithm; retrieving ancillary information from a secondary search of at least one other data source using a query that is related to data from the plurality of search results, the ancillary information including associative data that is not included within the search results; correlating the search results with the ancillary information to identify associations between search results to produce augmented search results; refining the rule based on the data; applying the refined rule to filter the set of documents based on the data extracted from the first document to produce a first filtered results; and providing an interface to the user device to present multiple views of the data, the multiple views including a first view and a second view that present the first filtered results in different contexts.

1. A method of goal-oriented searching, the method comprising: providing a graphical user interface (GUI) to a user device from a server, the GUI including an input field accessible by a user to provide a text input and a selectable indicator accessible by the user to select one of a plurality of goal-oriented searches, each of the plurality of goal-oriented searches comprising a pre-defined query stored at a server prior to interaction by the user; receiving a user input including the text input and a selection corresponding to the selectable indicator indicating a selected one of the plurality of pre-defined goal oriented searches; retrieving a first document based on the text input; searching one or more data sources based on data extracted from the first document and according to search parameters defined by the selected one of the plurality of pre-defined goal oriented searches to identify a set of documents; applying a rule derived from explicit user interactions and implicit user interactions to produce a matrix including highest probability keywords identified from the search results; identifying a plurality of search results using a greedy algorithm; retrieving ancillary information from a secondary search of at least one other data source using a query that is related to data from the plurality of search results, the ancillary information including associative data that is not included within the search results; correlating the search results with the ancillary information to identify associations between search results to produce augmented search results; refining the rule based on the data; applying the refined rule to filter the set of documents based on the data extracted from the first document to produce a first filtered results; and providing an interface to the user device to present multiple views of the data, the multiple views including a first view and a second view that present the first filtered results in different contexts. 7. The method of claim 1 , wherein the goal-oriented query comprises an asset identifying search to identify a potentially valuable asset from a plurality of assets identified in the first document.

17. A system for determining items or people of potential interest to recommend to users in a computer-based network, the system comprising: one or more server computers; wherein the one or more server computers comprise one or more processors capable of: processing a communication to be received from an input/output port to be related to one or more types of computer-based social behavior for multiple users of a computing network; deriving a semantically-sensitive vocabulary taxonomy to be based on the word-based social behavior, the semantically-sensitive vocabulary taxonomy to indicate one or more meanings for one or more words; determining two or more implied topic-specific social networks based at least in part on the obtained social behavior and utilizing the semantically-sensitive vocabulary-based taxonomy, at least one word to have a first meaning within a first implied topic-specific social network and a second meaning, different from the first meaning, within a second implied topic-specific social network; and facilitating presentation by transmitting a communication to display a graphical user interface to the user including a recommendation of an item or person of potential interest to a user in at least one of the two or more implied topic-specific social networks, wherein the recommended item is to be determined based on social behavior associated with users in the at least one of the two or more implied topic-specific social networks; facilitating presentation, within the graphical user interface, of an indication of a rationale to be utilized to determined that the item or person may be of interest to the user; and facilitating presentation, within the graphical user interface, of an opportunity for the user to provide feedback to be related to the recommendation.

17. A system for determining items or people of potential interest to recommend to users in a computer-based network, the system comprising: one or more server computers; wherein the one or more server computers comprise one or more processors capable of: processing a communication to be received from an input/output port to be related to one or more types of computer-based social behavior for multiple users of a computing network; deriving a semantically-sensitive vocabulary taxonomy to be based on the word-based social behavior, the semantically-sensitive vocabulary taxonomy to indicate one or more meanings for one or more words; determining two or more implied topic-specific social networks based at least in part on the obtained social behavior and utilizing the semantically-sensitive vocabulary-based taxonomy, at least one word to have a first meaning within a first implied topic-specific social network and a second meaning, different from the first meaning, within a second implied topic-specific social network; and facilitating presentation by transmitting a communication to display a graphical user interface to the user including a recommendation of an item or person of potential interest to a user in at least one of the two or more implied topic-specific social networks, wherein the recommended item is to be determined based on social behavior associated with users in the at least one of the two or more implied topic-specific social networks; facilitating presentation, within the graphical user interface, of an indication of a rationale to be utilized to determined that the item or person may be of interest to the user; and facilitating presentation, within the graphical user interface, of an opportunity for the user to provide feedback to be related to the recommendation. 18. The system of claim 17 , comprising a database for storing one or more types of word-based social behavior for multiple users.

23. The system of claim 22 , wherein the task analytics module is programmed to aggregate and sort data corresponding to at least one of task participant productivity, task participant work quality, task participant on-time percentage, and task participant relationship data.

23. The system of claim 22 , wherein the task analytics module is programmed to aggregate and sort data corresponding to at least one of task participant productivity, task participant work quality, task participant on-time percentage, and task participant relationship data. 26. The system of claim 23 , wherein the task analytics module is programmed to aggregate task data by sorting a plurality of projects and monitoring the productivity of each task participant associated with a particular project.

13. The system of claim 9 , wherein the system further comprises a means of representing a hardware component having dynamically selectable operation on a sample-by-sample basis.

13. The system of claim 9 , wherein the system further comprises a means of representing a hardware component having dynamically selectable operation on a sample-by-sample basis. 14. The system of claim 13 , wherein the system further comprises means for translating imperative language functions to hardware description language for runtime operation.

1. A method programmed in a non-transitory memory of a device comprising: a. capturing social networking information, including the social networking information of a user, from a social networking system; b. analyzing the social networking information of the user, including: i. determining interests of the user; and ii. storing the interests of the user in a data structure; c. processing the social networking information, including parsing the social networking information into parsed information; d. fact checking, with the device, the social networking information by comparing the parsed information with source information to generate fact checking results, including indicating when the parsed information is factually accurate and indicating when the parsed information is factually inaccurate; e. summarizing the social networking information to generate a summary of the social networking information, including determining total strengths of sentences within the social networking information, wherein a total strength of a sentence is based on a strength of a lexical chain, the interests of the user, and factual accuracy of the sentence based on the fact checking results generated by fact checking the social networking information, wherein summarizing the social networking information utilizes the interests of the user stored in the data structure by increasing the strength of the lexical chain when a word in the lexical chain matches at least one of the interests in the data structure, wherein lexical chaining includes selecting a set of candidate words or phrases, finding an appropriate chain using relatedness criteria among members of chains for each candidate word, and inserting a word in the lexical chain when the word is found, wherein the total strength of the sentence is increased when the sentence is factually accurate, wherein the summary of the social networking information includes the fact checking results; and f. providing the summary of the social networking information in real-time.

1. A method programmed in a non-transitory memory of a device comprising: a. capturing social networking information, including the social networking information of a user, from a social networking system; b. analyzing the social networking information of the user, including: i. determining interests of the user; and ii. storing the interests of the user in a data structure; c. processing the social networking information, including parsing the social networking information into parsed information; d. fact checking, with the device, the social networking information by comparing the parsed information with source information to generate fact checking results, including indicating when the parsed information is factually accurate and indicating when the parsed information is factually inaccurate; e. summarizing the social networking information to generate a summary of the social networking information, including determining total strengths of sentences within the social networking information, wherein a total strength of a sentence is based on a strength of a lexical chain, the interests of the user, and factual accuracy of the sentence based on the fact checking results generated by fact checking the social networking information, wherein summarizing the social networking information utilizes the interests of the user stored in the data structure by increasing the strength of the lexical chain when a word in the lexical chain matches at least one of the interests in the data structure, wherein lexical chaining includes selecting a set of candidate words or phrases, finding an appropriate chain using relatedness criteria among members of chains for each candidate word, and inserting a word in the lexical chain when the word is found, wherein the total strength of the sentence is increased when the sentence is factually accurate, wherein the summary of the social networking information includes the fact checking results; and f. providing the summary of the social networking information in real-time. 10. The method of claim 1 further comprising merging multiple content items with disparate views into a merged content item, including maintaining a relative position of each sentence when merging the multiple content items, wherein the social networking information comprises the merged content item.

1. An apparatus, comprising: at least one processor; and a non-transitory memory storing computer-readable instructions that, when executed by the at least one processor, cause the apparatus to: transmit to a group of users, a first document including a data item field, the group of users including a first portion of the group including a first plurality of users and a second portion of the group including a second plurality of users different from the first plurality of users; receive, from a first user of the group of users, first user input accessing the first document; provide to the first user of the group of users, access to the first document and the data item field, the data item field including a first data item, wherein the first data item is a first numerical item that is visible in the first document; receive, from a second user of the group of users, second user input accessing the first document; provide to the second user of the group of users, access to the first document and the data item field, the data item field including a second data item different from the first data item, wherein the second data item is a numerical item that is visible in the first document, wherein alternating users accessing the first document and the data item field access data items in the data item field alternating between the first data item and the second data item, and wherein users accessing the first document with the first data item in the data item field form the first plurality of users forming the first portion of the group of users and users accessing the first document with the second data item in the data item field form the second plurality of users forming the second portion of the group of users; receive data identifying a disclosure, the disclosure including one of the first data item and the second data item; responsive to receiving data identifying disclosure of the first data item, identifying users of the first plurality of users as a potential source of the disclosure; and responsive to receiving data identifying disclosure of the second data item, identifying the users of the second plurality of users as a potential source of the disclosure.

1. An apparatus, comprising: at least one processor; and a non-transitory memory storing computer-readable instructions that, when executed by the at least one processor, cause the apparatus to: transmit to a group of users, a first document including a data item field, the group of users including a first portion of the group including a first plurality of users and a second portion of the group including a second plurality of users different from the first plurality of users; receive, from a first user of the group of users, first user input accessing the first document; provide to the first user of the group of users, access to the first document and the data item field, the data item field including a first data item, wherein the first data item is a first numerical item that is visible in the first document; receive, from a second user of the group of users, second user input accessing the first document; provide to the second user of the group of users, access to the first document and the data item field, the data item field including a second data item different from the first data item, wherein the second data item is a numerical item that is visible in the first document, wherein alternating users accessing the first document and the data item field access data items in the data item field alternating between the first data item and the second data item, and wherein users accessing the first document with the first data item in the data item field form the first plurality of users forming the first portion of the group of users and users accessing the first document with the second data item in the data item field form the second plurality of users forming the second portion of the group of users; receive data identifying a disclosure, the disclosure including one of the first data item and the second data item; responsive to receiving data identifying disclosure of the first data item, identifying users of the first plurality of users as a potential source of the disclosure; and responsive to receiving data identifying disclosure of the second data item, identifying the users of the second plurality of users as a potential source of the disclosure. 7. The apparatus of claim 1 , wherein the first plurality of users is approximately one half of the group of users and the second plurality of users is approximately another half of the group of users.

1. A computer-implemented method comprising: determining a particular language based at least in part on both content of text submitted by a user and a source IP address that is associated with the user; and based on having determined the particular language for the user, presenting, to the user, one or more content items that are associated with the particular language; wherein the content of the text does not expressly state the particular language.

1. A computer-implemented method comprising: determining a particular language based at least in part on both content of text submitted by a user and a source IP address that is associated with the user; and based on having determined the particular language for the user, presenting, to the user, one or more content items that are associated with the particular language; wherein the content of the text does not expressly state the particular language. 12. The method of claim 1 , wherein the context of text includes search query terms submitted by the user to a search engine to search for documents related to the search query terms.

12. A method of adjusting a voice prompt of a system based upon a state of a user of the system, the method comprising: receiving an utterance of the user; obtaining utterance parameters from the utterance, the utterance parameters indicating the state of the user; generating an utterance parameter vector based upon the obtained utterance parameters; converting the utterance parameter vector to an indication representing the state of the user; determining the state of the user based upon the indication; and adjusting the voice prompt based upon the determined state of the user, wherein obtaining utterance parameters comprises: partitioning the utterance into segments; and assigning one of a plurality of classifications to each segment, each classification corresponding to at least one of a plurality of states of the user, and wherein generating the utterance parameter vector comprises: determining the number of segments for each classification; and dividing the number of segments for each classification by a total number of segments in the utterance.

12. A method of adjusting a voice prompt of a system based upon a state of a user of the system, the method comprising: receiving an utterance of the user; obtaining utterance parameters from the utterance, the utterance parameters indicating the state of the user; generating an utterance parameter vector based upon the obtained utterance parameters; converting the utterance parameter vector to an indication representing the state of the user; determining the state of the user based upon the indication; and adjusting the voice prompt based upon the determined state of the user, wherein obtaining utterance parameters comprises: partitioning the utterance into segments; and assigning one of a plurality of classifications to each segment, each classification corresponding to at least one of a plurality of states of the user, and wherein generating the utterance parameter vector comprises: determining the number of segments for each classification; and dividing the number of segments for each classification by a total number of segments in the utterance. 22. The method of claim 12 , further comprising adjusting a graphical character display corresponding to the voice prompt based upon the determined state of the user.

7. The method of claim 1 , wherein the sentiment value represents a dislike of the remote participant towards an aspect of the conversation.

7. The method of claim 1 , wherein the sentiment value represents a dislike of the remote participant towards an aspect of the conversation. 8. The method of claim 7 , further comprising: processing the current data and the conversation data to create cognitive information, wherein the aspect of the conversation is derived from the cognitive information.

5. A signature matching engine stored in units of substrings to which signature strings for distinguishing harmful packets included in introduction traffic are tokenized, comprising: an internal memory block having a first memory table including a first substring included in both a first signature string and a second signature string, and having a memory table that includes a second substring from among substrings of the first signature string, wherein the second substring was stored in the internal memory block when the first memory table including the first substring was already linked to a memory table including another second substring from among substrings of the second signature string, and wherein the memory table that includes the second substring is linked to the first memory table; and an external memory block having stored therein a memory table that includes a substring from among substrings of a signature string, wherein the substring stored in the external memory was stored in the external memory when a substring previous to the substring stored in the external memory was not already linked to a memory table of another substring.

5. A signature matching engine stored in units of substrings to which signature strings for distinguishing harmful packets included in introduction traffic are tokenized, comprising: an internal memory block having a first memory table including a first substring included in both a first signature string and a second signature string, and having a memory table that includes a second substring from among substrings of the first signature string, wherein the second substring was stored in the internal memory block when the first memory table including the first substring was already linked to a memory table including another second substring from among substrings of the second signature string, and wherein the memory table that includes the second substring is linked to the first memory table; and an external memory block having stored therein a memory table that includes a substring from among substrings of a signature string, wherein the substring stored in the external memory was stored in the external memory when a substring previous to the substring stored in the external memory was not already linked to a memory table of another substring. 10. The signature matching engine of claim 5 , wherein, when the memory table including the substrings is stored in the external memory block, the substrings are sequentially arranged from an arbitrary external memory block address.

1. A decoding method for sequence translation, the method comprising: employing a processor that executes instructions retained in a computer memory, the instructions, when executed by the processor, implement at least the following operations: receiving sequence data requiring sequence translation; front-loading an estimated future distortion penalty in translating a remainder of the sequence of data; creating a search space of possible next-phrase translations; reducing the search space based in part on the estimated future distortion penalty; and selecting a translation candidate for the sequence data.

1. A decoding method for sequence translation, the method comprising: employing a processor that executes instructions retained in a computer memory, the instructions, when executed by the processor, implement at least the following operations: receiving sequence data requiring sequence translation; front-loading an estimated future distortion penalty in translating a remainder of the sequence of data; creating a search space of possible next-phrase translations; reducing the search space based in part on the estimated future distortion penalty; and selecting a translation candidate for the sequence data. 4. The decoding method of claim 1 , the sequence translation is language translation from a first language to a second language.

1. A method of enabling a system designer to generate a dialog application program for instructing a computer controlled voice response system for providing a user interactive voice service, said method comprising the steps of: selecting two or more interaction program modules from a group of predefined interaction program modules, each program module including one or more system designer selectable parameters for further defining a particular user transaction function to be performed by said program module and specifying the logical interconnection of said selected two or more program modules to generate said application program to provide said user interactive voice service.

1. A method of enabling a system designer to generate a dialog application program for instructing a computer controlled voice response system for providing a user interactive voice service, said method comprising the steps of: selecting two or more interaction program modules from a group of predefined interaction program modules, each program module including one or more system designer selectable parameters for further defining a particular user transaction function to be performed by said program module and specifying the logical interconnection of said selected two or more program modules to generate said application program to provide said user interactive voice service. 8. The method of claim 1 wherein said module selecting step includes the step of: identifying a prompt or announcement signal to be outputted to a user in response to a user interaction with said application program.

1. A computer program product embodied in a computer readable storage medium for construction of rules for use in a complex event processing application program, the computer program product comprising the programming instructions for: providing a rule construction interface for constructing rules for a rule set of a complex event processing system, said rules comprising definitions of one or more detected events and corresponding actions, said interface being arranged to enable a user definition of new events or actions during a rule construction process; in response to an identification of a new event or action during said rule construction process via said rule construction interface, generating a corresponding event or action logical construct for representing said event or action in said complex event processing system; generating an intermediate logical construct arranged to provide a data connection for said event or action logical construct; and linking said event or action logical construct to a corresponding action or event logical construct via said intermediate logical construct.

1. A computer program product embodied in a computer readable storage medium for construction of rules for use in a complex event processing application program, the computer program product comprising the programming instructions for: providing a rule construction interface for constructing rules for a rule set of a complex event processing system, said rules comprising definitions of one or more detected events and corresponding actions, said interface being arranged to enable a user definition of new events or actions during a rule construction process; in response to an identification of a new event or action during said rule construction process via said rule construction interface, generating a corresponding event or action logical construct for representing said event or action in said complex event processing system; generating an intermediate logical construct arranged to provide a data connection for said event or action logical construct; and linking said event or action logical construct to a corresponding action or event logical construct via said intermediate logical construct. 6. The computer program product as recited in claim 1 further comprising the programming instructions for: in response to a definition of a new touch point for a given action or event for specifying a source of input data for said corresponding event logical construct or a target of output data for said corresponding action logical construct, generating a corresponding touch point logical construct associated with said event or action logical construct and identifying said source or said target.

1. A method comprising: collecting usage data that indicates how frequently users interact with annotations for entities that are referenced in documents that are presented to the users; based at least in part on the usage data, generating weights for features that are associated with the entities that are referenced in the documents; wherein a particular weight of a particular feature is based at least in part on how frequently users interact with annotations of entities having the particular feature; identifying a set of identified entities within a document; determining a ranking for the identified entities that belong to said set of identified entities based, at least in part, on (a) feature scores for each of the identified entities, wherein the feature scores correspond to features associated with the identified entities, wherein the particular feature is associated with at least one of the identified entities; and (b) weights, including the particular weight, for the features that are associated with the identified entities; based at least in part on the ranking, automatically selecting a subset of the identified entities for annotation, wherein the subset includes fewer than all of the identified entities; automatically generating an annotated version of the document by, for each entity in the subset, adding to the document a control for displaying additional information about the entity, wherein the additional information about the entity and the control associated with the entity were not in the document before the step of automatically generating the annotated version of the document; wherein at least the steps of generating the weights, determining the ranking, automatically selecting the subset, and automatically generating the annotated version are performed by one or more computing devices.

1. A method comprising: collecting usage data that indicates how frequently users interact with annotations for entities that are referenced in documents that are presented to the users; based at least in part on the usage data, generating weights for features that are associated with the entities that are referenced in the documents; wherein a particular weight of a particular feature is based at least in part on how frequently users interact with annotations of entities having the particular feature; identifying a set of identified entities within a document; determining a ranking for the identified entities that belong to said set of identified entities based, at least in part, on (a) feature scores for each of the identified entities, wherein the feature scores correspond to features associated with the identified entities, wherein the particular feature is associated with at least one of the identified entities; and (b) weights, including the particular weight, for the features that are associated with the identified entities; based at least in part on the ranking, automatically selecting a subset of the identified entities for annotation, wherein the subset includes fewer than all of the identified entities; automatically generating an annotated version of the document by, for each entity in the subset, adding to the document a control for displaying additional information about the entity, wherein the additional information about the entity and the control associated with the entity were not in the document before the step of automatically generating the annotated version of the document; wherein at least the steps of generating the weights, determining the ranking, automatically selecting the subset, and automatically generating the annotated version are performed by one or more computing devices. 27. The method of claim 1 , wherein automatically generating the annotated version is performed before a request for the document is received, storing the annotated version until the request is received, and providing the annotated version in response to the request.

1. A method for previewing a web page, comprising: receiving a typeset main document from a middleware server, wherein the typeset main document is obtained by loading a main document of a web page link requested to be previewed in accordance with a web page previewing request after the middleware server receives the web page previewing request sent in accordance with a web page previewing triggering instruction, and by typesetting at least a part of the main document, and wherein loading the main document excludes loading an external CSS (Cascading Style Sheet) associated with the main document, and typesetting the main document includes writing an internal CSS into the main document; and capturing at least the part of the typeset main document and scaling the captured typeset main document in accordance with a screen size of a mobile terminal to generate a preview image for the mobile terminal to display.

1. A method for previewing a web page, comprising: receiving a typeset main document from a middleware server, wherein the typeset main document is obtained by loading a main document of a web page link requested to be previewed in accordance with a web page previewing request after the middleware server receives the web page previewing request sent in accordance with a web page previewing triggering instruction, and by typesetting at least a part of the main document, and wherein loading the main document excludes loading an external CSS (Cascading Style Sheet) associated with the main document, and typesetting the main document includes writing an internal CSS into the main document; and capturing at least the part of the typeset main document and scaling the captured typeset main document in accordance with a screen size of a mobile terminal to generate a preview image for the mobile terminal to display. 6. The method of claim 1 , further comprising: obtaining at least a part of a web page from the typeset main document; and capturing at least the part of the web page and scaling the captured web page in accordance with the screen size of the mobile terminal to generate the preview image for the mobile terminal to display.

15. A method for querying incomplete and uncertain information in graph data, the method comprising: using a computing system comprising one or more processors running a computer application to: create an incomplete graph data set comprising the plurality of graphs by inserting a variable into each blank subject node, each blank predicate and each blank object node in each graph within the plurality of graphs; and create an uncertain graph data set from the incomplete data graph set by substituting alternative values for all variables in the incomplete data graph, wherein each variable is replaced by a given group of alternative values, each group of alternative values selected from a set of alternative values comprising a union of all subsets of a set of all uniform resource identifiers in the received graph data and all subsets of a set of all literals in the received graph data; receiving a query from a user over graph data comprising a plurality of graphs, each graph comprising a subject node, an object node and a predicate extending from the subject node to the object node, each subject node comprising a uniform resource identifier or a blank subject node, each predicate comprising a uniform resource identifier or a blank predicate and each object node comprising a uniform resource identifier, a literal or a blank object node; identifying certain answers to the query over the graph data, each certain answer comprising a certain value obtained from a given graph in the plurality of graphs that is equivalent for any alternative value of at least one of the subject node, the object node and the predicate of that given graph; identifying potential answers to the query over the graph data by processing the query over the incomplete data set, each potential answer comprising two or more potential values for at least one of the subject node, the object node and the predicate from a given graph; identifying certain potential answers to the query over the graph data using the uncertain graph data set, each certain potential answer having a number of potential values below a prescribed threshold; and communicating the certain answers and the certain potential answers to the user in response to the query.

15. A method for querying incomplete and uncertain information in graph data, the method comprising: using a computing system comprising one or more processors running a computer application to: create an incomplete graph data set comprising the plurality of graphs by inserting a variable into each blank subject node, each blank predicate and each blank object node in each graph within the plurality of graphs; and create an uncertain graph data set from the incomplete data graph set by substituting alternative values for all variables in the incomplete data graph, wherein each variable is replaced by a given group of alternative values, each group of alternative values selected from a set of alternative values comprising a union of all subsets of a set of all uniform resource identifiers in the received graph data and all subsets of a set of all literals in the received graph data; receiving a query from a user over graph data comprising a plurality of graphs, each graph comprising a subject node, an object node and a predicate extending from the subject node to the object node, each subject node comprising a uniform resource identifier or a blank subject node, each predicate comprising a uniform resource identifier or a blank predicate and each object node comprising a uniform resource identifier, a literal or a blank object node; identifying certain answers to the query over the graph data, each certain answer comprising a certain value obtained from a given graph in the plurality of graphs that is equivalent for any alternative value of at least one of the subject node, the object node and the predicate of that given graph; identifying potential answers to the query over the graph data by processing the query over the incomplete data set, each potential answer comprising two or more potential values for at least one of the subject node, the object node and the predicate from a given graph; identifying certain potential answers to the query over the graph data using the uncertain graph data set, each certain potential answer having a number of potential values below a prescribed threshold; and communicating the certain answers and the certain potential answers to the user in response to the query. 17. The method of claim 15 , wherein the step of identifying potential answers to the query further comprises processing the query over the incomplete data set to identify the potential answers, each potential answer comprising a variable in a given graph in at least one of the subject node, the object node and the predicate of that given graph that can yield the two or more potential values.

12. Non-transitory computer readable media for storing executable instructions for controlling the operation of computers on a plurality of segments of an MPP relational database for latent Dirichlet allocation (LDA) processing on said segments in parallel a subset of a dataset, the dataset comprising a plurality of documents, each document being a mixture of topics where each topic is characterized by a probability distribution over a vocabulary of words, said LDA processing comprising: distributing subsets of said documents of said dataset to said plurality of segments, where each one of said documents of a subset is distributed to and stored on one single segment of said relational database; determining in parallel on each segment for each document of the subset on said segment a per-word and a per-document topic count; performing in parallel on each segment LDA analysis using said determined topic counts determine to assign words to a new topic; calculating in parallel on each segment per-word and per-document probability distributions of topic assignments; iterating said determining, said performing, and said calculating steps on each segment until a predetermined stop condition is satisfied, and storing results locally in memory on each segment, said iterating comprises updating topic assignments of words at each iteration by providing on each segment two work tables for holding topic assignments that alternate roles as an input table and as an output table, a first work table storing topic assignments from a previous iteration and serving as an input table of topic assignments to a next iteration, and a second work table serving as an output table for updated topic assignments from said next iteration, and alternating roles of said first and second tables for input and output on each said iteration for updating topic assignments; and aggregating results from said plurality of segments to form an inference model.

12. Non-transitory computer readable media for storing executable instructions for controlling the operation of computers on a plurality of segments of an MPP relational database for latent Dirichlet allocation (LDA) processing on said segments in parallel a subset of a dataset, the dataset comprising a plurality of documents, each document being a mixture of topics where each topic is characterized by a probability distribution over a vocabulary of words, said LDA processing comprising: distributing subsets of said documents of said dataset to said plurality of segments, where each one of said documents of a subset is distributed to and stored on one single segment of said relational database; determining in parallel on each segment for each document of the subset on said segment a per-word and a per-document topic count; performing in parallel on each segment LDA analysis using said determined topic counts determine to assign words to a new topic; calculating in parallel on each segment per-word and per-document probability distributions of topic assignments; iterating said determining, said performing, and said calculating steps on each segment until a predetermined stop condition is satisfied, and storing results locally in memory on each segment, said iterating comprises updating topic assignments of words at each iteration by providing on each segment two work tables for holding topic assignments that alternate roles as an input table and as an output table, a first work table storing topic assignments from a previous iteration and serving as an input table of topic assignments to a next iteration, and a second work table serving as an output table for updated topic assignments from said next iteration, and alternating roles of said first and second tables for input and output on each said iteration for updating topic assignments; and aggregating results from said plurality of segments to form an inference model. 13. The non-transitory computer readable media of claim 12 , wherein each segment has an object library of processing modules comprising executable objects for controlling the segment to perform user defined functions, and an executable object being called by an executing SQL query when said query requires functionality provided by said called executable object.

1. In a system including a computing environment coupled to a capture device for capturing image data from a field of view of the capture device, the image data representing a position of a user, a method of estimating user body position comprising: (a) receiving image data from the field of view; (b) applying one or more computer models for generating body part proposals from the image data, at least one computer model accounting for missing joint information by using a position of the missing joint identified in a past frame as a basis for the position of the missing joint in the current frame; and (c) analyzing the one or more computer models produced in said step (b) by one or more methodologies to choose at least one computer model of the one or more computer models estimated to provide the best body part proposal.

1. In a system including a computing environment coupled to a capture device for capturing image data from a field of view of the capture device, the image data representing a position of a user, a method of estimating user body position comprising: (a) receiving image data from the field of view; (b) applying one or more computer models for generating body part proposals from the image data, at least one computer model accounting for missing joint information by using a position of the missing joint identified in a past frame as a basis for the position of the missing joint in the current frame; and (c) analyzing the one or more computer models produced in said step (b) by one or more methodologies to choose at least one computer model of the one or more computer models estimated to provide the best body part proposal. 6. The method of claim 1 , said step (b) of applying one or more computer models comprising the step of applying one or more computer models based on computing body part proposals from the image data and generating one or more skeletal hypotheses from the body part proposals by a known configuration of how body parts are connected in humans.

1. A method of displaying pages of information on an electronic screen, the method comprising: receiving a first page of information including first text; rendering the first page of information including the first text on the electronic screen at a first zoom setting; after rendering the first page of information at the first zoom setting, accepting zoom input from a user through a user interface; rendering the first page of information including the first text on the electronic screen at a second zoom setting different than the first zoom setting responsive to the zoom input; saving in electronic memory a target text size representing a size of the first text on the electronic screen at the second zoom setting; receiving a second page of information including second text different than the first text; determining a third zoom setting responsive to the target text size and responsive to the second text; and rendering the second page of information including the second text on the electronic screen at a third zoom setting; wherein determining the third zoom setting comprises determining the third zoom setting responsive to the target text size and responsive to the second text to normalize a size of the second text rendered on the electronic screen at the third zoom setting relative to a size of the first text rendered on the electronic screen at the second zoom setting.

1. A method of displaying pages of information on an electronic screen, the method comprising: receiving a first page of information including first text; rendering the first page of information including the first text on the electronic screen at a first zoom setting; after rendering the first page of information at the first zoom setting, accepting zoom input from a user through a user interface; rendering the first page of information including the first text on the electronic screen at a second zoom setting different than the first zoom setting responsive to the zoom input; saving in electronic memory a target text size representing a size of the first text on the electronic screen at the second zoom setting; receiving a second page of information including second text different than the first text; determining a third zoom setting responsive to the target text size and responsive to the second text; and rendering the second page of information including the second text on the electronic screen at a third zoom setting; wherein determining the third zoom setting comprises determining the third zoom setting responsive to the target text size and responsive to the second text to normalize a size of the second text rendered on the electronic screen at the third zoom setting relative to a size of the first text rendered on the electronic screen at the second zoom setting. 4. A method according to claim 1 wherein the second and third zoom settings are different.

1. A method for ranking based on interpersonal distances, comprising: obtaining, by a ranking server, objects queried by a query request initiated by a user from a user client and obtaining a reference user group corresponding to each queried object; obtaining, by the ranking server, interpersonal distances between users in the reference user group and the user who initiates the query request, and obtaining rating scores of each of the objects queried by the query request that are given by the users in the reference user group; and determining, by the ranking server, a user relationship ranking index of each of the objects queried based on the interpersonal distances and the rating scores, and ordering the objects based on respective user relationship ranking indices of the objects.

1. A method for ranking based on interpersonal distances, comprising: obtaining, by a ranking server, objects queried by a query request initiated by a user from a user client and obtaining a reference user group corresponding to each queried object; obtaining, by the ranking server, interpersonal distances between users in the reference user group and the user who initiates the query request, and obtaining rating scores of each of the objects queried by the query request that are given by the users in the reference user group; and determining, by the ranking server, a user relationship ranking index of each of the objects queried based on the interpersonal distances and the rating scores, and ordering the objects based on respective user relationship ranking indices of the objects. 5. The method of claim 1 , further comprising: determining weight factors based on the interpersonal distances, the weight factors decreasing as the interpersonal distances increase; and determining the user relationship ranking index of each queried object based on the interpersonal distances between the users in the reference user group and the user who initiates the query request and the rating scores of each object queried by the request that are given by the users in the reference user group, including calculating an average value of weighted rating scores based on the interpersonal distances associated with the users of the reference user group to obtain the user relationship ranking index.

14. A non-transitory computer readable medium storing computer readable instructions that, when executed, cause an apparatus to: receive an identifier for a network document; perform an on-demand analysis of the network document to determine a search engine score for the network document, wherein the on-demand analysis of the network document includes: determining a number of links included in the network document by analyzing a structure of the network document; determining a number of incoming links to the network document; and generating separate specific traffic-independent scoring analyses for each of the links included in the network document, wherein each of the separate specific traffic-independent scoring analyses are visually-navigable; and generate, based on the received identifier and independently of a user-specified search word or phrase, a display of the search engine score along with a first level of scoring detail for the network document, wherein the search engine score is determined by evaluating the network document using one or more traffic-independent scoring factors and wherein the network document is ranked based on the one or more traffic-independent scoring factors, and wherein the ranking is determined by combining the search engine score and a link flow distribution that indicates the likelihood that a user will access the network document relative to a second network document, wherein the network document and the second network document are within the same web site; receive a request to display details of the one or more traffic-independent scoring factors; in response to the request: generate the details of the one or more traffic-independent scoring factors by performing an on-demand analysis of the one or more traffic-independent scoring factors; and generate a display of a second level of scoring detail including the details of the one or more traffic-independent scoring factors, wherein the second level of scoring detail includes a plurality of non-traffic attributes.

14. A non-transitory computer readable medium storing computer readable instructions that, when executed, cause an apparatus to: receive an identifier for a network document; perform an on-demand analysis of the network document to determine a search engine score for the network document, wherein the on-demand analysis of the network document includes: determining a number of links included in the network document by analyzing a structure of the network document; determining a number of incoming links to the network document; and generating separate specific traffic-independent scoring analyses for each of the links included in the network document, wherein each of the separate specific traffic-independent scoring analyses are visually-navigable; and generate, based on the received identifier and independently of a user-specified search word or phrase, a display of the search engine score along with a first level of scoring detail for the network document, wherein the search engine score is determined by evaluating the network document using one or more traffic-independent scoring factors and wherein the network document is ranked based on the one or more traffic-independent scoring factors, and wherein the ranking is determined by combining the search engine score and a link flow distribution that indicates the likelihood that a user will access the network document relative to a second network document, wherein the network document and the second network document are within the same web site; receive a request to display details of the one or more traffic-independent scoring factors; in response to the request: generate the details of the one or more traffic-independent scoring factors by performing an on-demand analysis of the one or more traffic-independent scoring factors; and generate a display of a second level of scoring detail including the details of the one or more traffic-independent scoring factors, wherein the second level of scoring detail includes a plurality of non-traffic attributes. 26. The non-transitory compute readable medium of claim 14 , wherein the search engine score of the network document includes a link flow for the network document reduced by at least one penalty factor.

1. A system for providing continuous automated verification of user identity and intent, comprising: at least one server for communicating with a network; at least one network interface card associated with the at least one server for providing access to data flow through the network; a processor within each of the at least one server, the processor implementing a first processing node and a second processing node for: monitoring, prior to granting at least one user access to the network, at the first processing node associated with the network, a mirrored live-data flow of a live-data flow passing through the first processing node in a non-intrusive manner that does not affect the live-data flow passing through the first processing node, wherein the live-data flow comprises data that is in active transmission between endpoints in the network and prior to storage of the data within the live-data flow in a database; detecting relevant network access and activity in the mirrored live data flow; dynamically generating a first set of verification criteria at the second processing node based on live data inputs from the mirrored live-data flow and external data sources to verify an identify and an activity of the at least one user attempting to access the network prior to access and performing an activity on the network, wherein the first set of verification criteria comprise a first set of dynamically generated dialogue of questions with associated answers to be provided by the at least one user; dynamically generating a second set of verification criteria at the second processing node based on the responses provided by the at least one user to the first set of dynamically generated dialogue of questions to verify the identity and the activity of the at least one user attempting to access the network, wherein the second set of verification criteria comprise a second set of dynamically generated dialogue of questions with associated answers to be provided by the at least one user; dynamically adjusting a required threshold level at which the first and second verification criteria must be met by the at least one user attempting the network access in order to allow or deny the network access and activity by the at least one user; denying the relevant network access and activity if the verification criteria are not met at the required threshold level, to preempt unverified and unwanted access to and activity on the network by the at least one user; allowing the relevant network access and activity if the verification criteria are met at the required threshold level; and continuing to monitor and verify the user identity and the user activity for a dynamic time period after access and activity on the network is granted, to ensure continued user identity and activity fidelity.

1. A system for providing continuous automated verification of user identity and intent, comprising: at least one server for communicating with a network; at least one network interface card associated with the at least one server for providing access to data flow through the network; a processor within each of the at least one server, the processor implementing a first processing node and a second processing node for: monitoring, prior to granting at least one user access to the network, at the first processing node associated with the network, a mirrored live-data flow of a live-data flow passing through the first processing node in a non-intrusive manner that does not affect the live-data flow passing through the first processing node, wherein the live-data flow comprises data that is in active transmission between endpoints in the network and prior to storage of the data within the live-data flow in a database; detecting relevant network access and activity in the mirrored live data flow; dynamically generating a first set of verification criteria at the second processing node based on live data inputs from the mirrored live-data flow and external data sources to verify an identify and an activity of the at least one user attempting to access the network prior to access and performing an activity on the network, wherein the first set of verification criteria comprise a first set of dynamically generated dialogue of questions with associated answers to be provided by the at least one user; dynamically generating a second set of verification criteria at the second processing node based on the responses provided by the at least one user to the first set of dynamically generated dialogue of questions to verify the identity and the activity of the at least one user attempting to access the network, wherein the second set of verification criteria comprise a second set of dynamically generated dialogue of questions with associated answers to be provided by the at least one user; dynamically adjusting a required threshold level at which the first and second verification criteria must be met by the at least one user attempting the network access in order to allow or deny the network access and activity by the at least one user; denying the relevant network access and activity if the verification criteria are not met at the required threshold level, to preempt unverified and unwanted access to and activity on the network by the at least one user; allowing the relevant network access and activity if the verification criteria are met at the required threshold level; and continuing to monitor and verify the user identity and the user activity for a dynamic time period after access and activity on the network is granted, to ensure continued user identity and activity fidelity. 16. The system of claim 1 , wherein the first and the second verification criteria further comprises at least one of current or previous location, current or previous usage, current or previous transmitted content, current or previous purchases, current or previous interactions, current or previous sessions, current or previous network activity, or current or previous interactivity with other users or devices.

18. The computer readable medium of claim 15 , wherein identifying a second controlling keyword based on the tiebreaker rule comprises: determining that a first keyword from the two keywords has a less specific match with the phrase than a second keyword from the two keywords; determining that a first quality score for the first keyword exceeds a second quality score for the second keyword; and selecting, in response to the determination, the first keyword as the second controlling keyword.

18. The computer readable medium of claim 15 , wherein identifying a second controlling keyword based on the tiebreaker rule comprises: determining that a first keyword from the two keywords has a less specific match with the phrase than a second keyword from the two keywords; determining that a first quality score for the first keyword exceeds a second quality score for the second keyword; and selecting, in response to the determination, the first keyword as the second controlling keyword. 19. The computer readable medium of claim 18 , wherein the instructions cause the one or more data processing apparatus to perform operations comprising: identifying a maximum bid associated with the second keyword; and associating, with the first keyword, an adjusted bid that does not exceed the maximum bid associated with the second keyword.

1. A system that facilitates analyzing content of a multi-dimensional structure, the system comprising: an interface component that collects statements in a declarative language and relays the statements; a calculation component that receives relayed statements from the interface component, the statements being in a declarative language relating to modifying data, and executes such statements against the multi-dimensional structure, the calculation component recognizes that the statements relate to a recursive calculation assigned as a value of a cell in the multi-dimensional structure, the recursive calculation including a recursive reference back to the cell, the execution of the relayed statements modifying a portion of the data stored within the multi-dimensional structure; a pass generation component that, in response to the calculation component receiving the relayed statements and prior to the execution of the relayed statements by the calculation component, creates at least one pass, each pass including the portion of the data stored within the multi-dimensional structure as the portion of the data existed prior to the calculation component executed the relayed statements; and a pass analysis component that analyzes a previous pass and selects a value within a previous pass that enables the recursive calculation to complete through utilization of cells at multiple prior passes to complete a calculation or assignment, wherein storage operatively coupled to a processor retains at least a portion of the calculation component or the pass generation component.

1. A system that facilitates analyzing content of a multi-dimensional structure, the system comprising: an interface component that collects statements in a declarative language and relays the statements; a calculation component that receives relayed statements from the interface component, the statements being in a declarative language relating to modifying data, and executes such statements against the multi-dimensional structure, the calculation component recognizes that the statements relate to a recursive calculation assigned as a value of a cell in the multi-dimensional structure, the recursive calculation including a recursive reference back to the cell, the execution of the relayed statements modifying a portion of the data stored within the multi-dimensional structure; a pass generation component that, in response to the calculation component receiving the relayed statements and prior to the execution of the relayed statements by the calculation component, creates at least one pass, each pass including the portion of the data stored within the multi-dimensional structure as the portion of the data existed prior to the calculation component executed the relayed statements; and a pass analysis component that analyzes a previous pass and selects a value within a previous pass that enables the recursive calculation to complete through utilization of cells at multiple prior passes to complete a calculation or assignment, wherein storage operatively coupled to a processor retains at least a portion of the calculation component or the pass generation component. 9. The system of claim 1 , further comprising a freeze component that pins a value of a selected cell to a current value.

13. The one or more computer storage media devices of claim 11 , wherein propagating category metadata further comprises: associating the domain with the content category.

13. The one or more computer storage media devices of claim 11 , wherein propagating category metadata further comprises: associating the domain with the content category. 15. The one or more computer storage media devices of claim 13 , further comprising: analyzing content in the domain to determine that the domain is related to the content category; and calculating a confidence level that indicates a likelihood that the domain is related to the content category.

1. A system for switching emulation of an executable file, the system comprising: a processor and memory operably coupled to the at least one processor; a first emulator stored on the memory and executable by the processor and including a first virtual environment, the first emulator configured to process a set of instructions in a first instruction set, wherein the first virtual environment is unique to the first instruction set; a second emulator stored on the memory and executable by the processor and including a second virtual environment, the second emulator configured to process a set of instructions in a second instruction set, wherein the second virtual environment is unique to the second instruction set; and an analyzer including: a converter including converting logic stored on the memory and executable by the processor, the converting logic comprising instructions to remove non-functional code from a script related to the executable file, then convert the script into pseudocode, the pseudocode comprising an intermediary form of commands decipherable by one of the first emulator or the second emulator, and an emulator switcher including processing logic stored on the memory and executable by the processor, the processing logic comprising instructions to process the pseudocode between the first emulator and the second emulator by switching between the first emulator and the second emulator based on at least one switching criteria, the at least one switching criteria including a pseudocode processing task specific to one of the first instruction set or second instruction set, wherein the first virtual environment comprises an interpreter of a language in which the script was written, and the first emulator processes the first instruction set by reading a plurality of pseudocode commands from the converted script, determining an action for each of the pseudocode commands using the interpreter, performing emulation of the actions, and writing the results of the emulation to an emulator operation log.

1. A system for switching emulation of an executable file, the system comprising: a processor and memory operably coupled to the at least one processor; a first emulator stored on the memory and executable by the processor and including a first virtual environment, the first emulator configured to process a set of instructions in a first instruction set, wherein the first virtual environment is unique to the first instruction set; a second emulator stored on the memory and executable by the processor and including a second virtual environment, the second emulator configured to process a set of instructions in a second instruction set, wherein the second virtual environment is unique to the second instruction set; and an analyzer including: a converter including converting logic stored on the memory and executable by the processor, the converting logic comprising instructions to remove non-functional code from a script related to the executable file, then convert the script into pseudocode, the pseudocode comprising an intermediary form of commands decipherable by one of the first emulator or the second emulator, and an emulator switcher including processing logic stored on the memory and executable by the processor, the processing logic comprising instructions to process the pseudocode between the first emulator and the second emulator by switching between the first emulator and the second emulator based on at least one switching criteria, the at least one switching criteria including a pseudocode processing task specific to one of the first instruction set or second instruction set, wherein the first virtual environment comprises an interpreter of a language in which the script was written, and the first emulator processes the first instruction set by reading a plurality of pseudocode commands from the converted script, determining an action for each of the pseudocode commands using the interpreter, performing emulation of the actions, and writing the results of the emulation to an emulator operation log. 2. The system for switching emulation of an executable file of claim 1 , wherein the first emulator is a script emulator and the first virtual environment is a pseudocode environment, the second emulator is a machine code emulator and the second virtual environment is a machine code environment, and the at least one switching criteria is a transition from pseudocode to machine code.

9. The method of claim 8 further comprising: instantiating a widget assembly application, the widget assembly application having menu displays identifying widget content or widget types for selection by a user of the widget assembly application.

9. The method of claim 8 further comprising: instantiating a widget assembly application, the widget assembly application having menu displays identifying widget content or widget types for selection by a user of the widget assembly application. 14. The method of claim 9 wherein the widget assembly application includes a plurality of widget templates, the widget templates serving as a basis for template types in one or more menus of the widget assembly application.

12. The storage medium of claim 10 further comprising instructions that upon execution cause the computer to store the names and accepted or rejected name equivalents in a database.

12. The storage medium of claim 10 further comprising instructions that upon execution cause the computer to store the names and accepted or rejected name equivalents in a database. 13. The storage medium of claim 12 further comprising instructions that upon execution cause the computer to modify the plurality of learned rules based on the contents of the database.

16. An event processing agent, comprising: processing resources including at least one first processor and a memory; a first connection to a channel on an event bus configured to receive a stream of events, each said event having a predefined event type; and a second connection to an ontology management component; wherein the event processing agent, in cooperation with the processing resources, is configured to execute predefined queries on events received over the first connection, each said query conforming to a query language, the query language being enhanced via a semantic extension corresponding to an ontology; wherein the ontology management includes a first storage location storing mappings between concepts of the query language and concepts of the ontology that enhances the query language, and is configured to, when an enhanced query, defined in accordance with the query language enhanced via the semantic extension and to be executed on a received event by the event processing agent includes references to ontology concepts using semantics extension enhancement in the enhanced query, generate, in accordance with the stored mapping between the concepts of the query language and the concepts of the ontology that enhances the query language, a translated query with the references to the ontology concepts in the enhanced query being translated into queries processable by the event processing agent in accordance with the query language without the semantic extension enhancement; and wherein the concepts of the ontology are classes, and wherein the generating of the translated query comprises, for the enhanced query: retrieving a class definition for all referenced classes from a corresponding ontology; determining whether the referenced classes are marked as being handled; when the referenced classes are marked as being handled, transforming the respective class definition to the query language, and compiling the translated query; and when the referenced classes are not marked as being handled: when the respective class does not have a corresponding mapping, replacing the class with a union of all of its sub-classes; when the respective class has a corresponding mapping but no sub-classes, removing the reference to the class; and when the respective class has a corresponding mapping and any sub-classes, adding a union with all sub-classes to the class and marking the class as handled.

16. An event processing agent, comprising: processing resources including at least one first processor and a memory; a first connection to a channel on an event bus configured to receive a stream of events, each said event having a predefined event type; and a second connection to an ontology management component; wherein the event processing agent, in cooperation with the processing resources, is configured to execute predefined queries on events received over the first connection, each said query conforming to a query language, the query language being enhanced via a semantic extension corresponding to an ontology; wherein the ontology management includes a first storage location storing mappings between concepts of the query language and concepts of the ontology that enhances the query language, and is configured to, when an enhanced query, defined in accordance with the query language enhanced via the semantic extension and to be executed on a received event by the event processing agent includes references to ontology concepts using semantics extension enhancement in the enhanced query, generate, in accordance with the stored mapping between the concepts of the query language and the concepts of the ontology that enhances the query language, a translated query with the references to the ontology concepts in the enhanced query being translated into queries processable by the event processing agent in accordance with the query language without the semantic extension enhancement; and wherein the concepts of the ontology are classes, and wherein the generating of the translated query comprises, for the enhanced query: retrieving a class definition for all referenced classes from a corresponding ontology; determining whether the referenced classes are marked as being handled; when the referenced classes are marked as being handled, transforming the respective class definition to the query language, and compiling the translated query; and when the referenced classes are not marked as being handled: when the respective class does not have a corresponding mapping, replacing the class with a union of all of its sub-classes; when the respective class has a corresponding mapping but no sub-classes, removing the reference to the class; and when the respective class has a corresponding mapping and any sub-classes, adding a union with all sub-classes to the class and marking the class as handled. 19. The agent of claim 16 , wherein events of a certain event type are considered instances of corresponding ontology class(es) to which that certain event type is mapped, and/or events communicated via a certain channel are considered instances of corresponding ontology class(es) to which that certain channel is mapped.

1. A method, comprising: detecting, by a computer system, receipt of one or more text-based electronic communications; identifying, by the computer system and in the one or more text-based electronic communications, first data of interest, the first data of interest comprising a predetermined characteristic, the computer system associated with sending the one or more text-based electronic communications; extracting, by the computer system, a plurality of instances of the identified first data of interest from a plurality of the text-based electronic communications sent to a plurality of recipients, wherein each text-based electronic communication includes first data of interest with a common predetermined characteristic, and wherein each text-based electronic communication includes first data or interest differing from first data of interest of other text-based electronic communications; obtaining, by the computer system and for each identified first data of interest, an initial first set of associated data that is associated with the extracted first data of interest, each initial first set of associated data from at least one electronic resource; and displaying, by the computer system and independently of the text-based electronic communications and the at least one electronic resource, a plurality of instances of the extracted first data of interest, each instance of the extracted first data of interest displayed with the corresponding obtained initial first set of associated data.

1. A method, comprising: detecting, by a computer system, receipt of one or more text-based electronic communications; identifying, by the computer system and in the one or more text-based electronic communications, first data of interest, the first data of interest comprising a predetermined characteristic, the computer system associated with sending the one or more text-based electronic communications; extracting, by the computer system, a plurality of instances of the identified first data of interest from a plurality of the text-based electronic communications sent to a plurality of recipients, wherein each text-based electronic communication includes first data of interest with a common predetermined characteristic, and wherein each text-based electronic communication includes first data or interest differing from first data of interest of other text-based electronic communications; obtaining, by the computer system and for each identified first data of interest, an initial first set of associated data that is associated with the extracted first data of interest, each initial first set of associated data from at least one electronic resource; and displaying, by the computer system and independently of the text-based electronic communications and the at least one electronic resource, a plurality of instances of the extracted first data of interest, each instance of the extracted first data of interest displayed with the corresponding obtained initial first set of associated data. 12. The method of claim 1 , wherein the display of the plurality of the plurality of instances of the extracted first data of interest and corresponding initial first sets of associated data is available to the user and not available to the intended recipients of the text-based electronic communications.

6. The system of claim 5 wherein the statistical parsing engine is configured to identify the portions of the unstructured data input by mapping the portions of the unstructured data input to slots in the predefined data structure.

6. The system of claim 5 wherein the statistical parsing engine is configured to identify the portions of the unstructured data input by mapping the portions of the unstructured data input to slots in the predefined data structure. 7. The system of claim 6 wherein the tokenization component is configured to identify the predefined data structure based on the input from the application.

20. The data storage device of claim 19 , further including instructions causing the processor nodes to each sort the local index of identified array of reservoir data blocks allocated to that node.

20. The data storage device of claim 19 , further including instructions causing the processor nodes to each sort the local index of identified array of reservoir data blocks allocated to that node. 21. The data storage device of claim 20 , further including instructions causing the processor nodes to form a list of the sorted local index of identified array of reservoir data blocks allocated to that node.

1. A method of providing layout information to be used in generating a display of data in a graphical user interface by storing schema definitions in an XML Schema Definition (XSD) schema, the method comprising: in a computer system that is configured to contain a repository of schema definitions according to UN/CEFACT Core Components Technical Specification (CCTS) for several data components, storing, within a schema definition for a data component from the repository of schema definitions for data components, layout information for the data component, each of the data components configured for defining semantics, according to CCTS, of portions of data included in an electronic communication from a sending business entity received at a receiving business entity, the electronic communication including a portion of data associated with the data component that specifies semantics of the portion of data according to CCTS, the layout information comprising XHTML, XFORMS, XSLT, or XSL-FO to define a visual appearance of the portion of data when the portion of data is presented to the receiving business entity, the visual appearance including at least one user interface element for presenting the portion of data; and outputting, for display, the portion of data with a visual appearance defined by the layout information.

1. A method of providing layout information to be used in generating a display of data in a graphical user interface by storing schema definitions in an XML Schema Definition (XSD) schema, the method comprising: in a computer system that is configured to contain a repository of schema definitions according to UN/CEFACT Core Components Technical Specification (CCTS) for several data components, storing, within a schema definition for a data component from the repository of schema definitions for data components, layout information for the data component, each of the data components configured for defining semantics, according to CCTS, of portions of data included in an electronic communication from a sending business entity received at a receiving business entity, the electronic communication including a portion of data associated with the data component that specifies semantics of the portion of data according to CCTS, the layout information comprising XHTML, XFORMS, XSLT, or XSL-FO to define a visual appearance of the portion of data when the portion of data is presented to the receiving business entity, the visual appearance including at least one user interface element for presenting the portion of data; and outputting, for display, the portion of data with a visual appearance defined by the layout information. 2. The method of claim 1 , wherein the layout information further comprises label information defining a label for the data component.

2. A request content identification system for analyzing a request sentence (input request sentence) inputted in a natural language format and identifying a request content, comprising: a common rule storing unit configured to store a common rule for a syntax analysis that does not depend upon the request content; a request-unique rule storing unit configured to store request-unique rules for the syntax analysis unique to each request content; a generating unit configured to generate audio recognition result candidates by performing an audio recognition process for an audio-inputted input request sentence; a request analysis processing unit configured to perform the syntax analysis for each audio recognition result candidate of said input request sentence by employing the common rule for a syntax analysis that does not depend upon the request content, and the request-unique rule for the syntax analysis unique to each request content; a score computing unit configured to calculate, for each of the audio recognition result candidates, an integration score obtained by combining an audio recognition score and a syntax analysis score for each request-unique rule employed in the syntax analysis; and a request identification result generating unit configured to identify the request content corresponding to the request-unique rule employed in the syntax analysis having a highest integration score as a request content corresponding to said inputted request sentence.

2. A request content identification system for analyzing a request sentence (input request sentence) inputted in a natural language format and identifying a request content, comprising: a common rule storing unit configured to store a common rule for a syntax analysis that does not depend upon the request content; a request-unique rule storing unit configured to store request-unique rules for the syntax analysis unique to each request content; a generating unit configured to generate audio recognition result candidates by performing an audio recognition process for an audio-inputted input request sentence; a request analysis processing unit configured to perform the syntax analysis for each audio recognition result candidate of said input request sentence by employing the common rule for a syntax analysis that does not depend upon the request content, and the request-unique rule for the syntax analysis unique to each request content; a score computing unit configured to calculate, for each of the audio recognition result candidates, an integration score obtained by combining an audio recognition score and a syntax analysis score for each request-unique rule employed in the syntax analysis; and a request identification result generating unit configured to identify the request content corresponding to the request-unique rule employed in the syntax analysis having a highest integration score as a request content corresponding to said inputted request sentence. 6. The request content identification system according to claim 2 , further comprising a request content cluster storing unit configured to store a request content cluster obtained by clustering the request contents resembling each other; and wherein said request identification result generating unit is configured to collect at least said integration scores for each said request content cluster, select a most excellent analysis result candidate cluster, and generate it as an identification result of the request content.

11. A computer program product embodied on a non-transitory computer readable medium, comprising: code for storing a plurality of original documents including a plurality of original values, including a first document including first values and a second document including second values; code for processing at least a part of the first document and at least a part of the second document, resulting in at least one object including at least one reference to at least one of the plurality of original values of at least one of the plurality of original documents; code for receiving a user selection of one or more computer-readable semantic tags; code for receiving a user selection of one or more of the original values; code for mapping the one or more of the computer-readable semantic tags to the one or more of the original values; code for outputting a presentation that is based on at least a portion of the at least one object, the presentation capable of including at least a portion of the original values including the at least one original value, where the computer program product is configured such that, based on the at least one reference of the at least one object to the at least one original value of the at least one original document, a change to the at least one original value of the at least one original document results in a corresponding change in an instance of the presentation; code for outputting a report that is based on at least a portion of the at least one object, the report capable of including at least a portion of the original values including the at least one original value, where the computer program product is configured such that, based on the at least one reference of the at least one object to the at least one original value of the at least one original document, a change to the at least one original value of the at least one original document results in a corresponding change in an instance of the report; and code for outputting at least one computer-readable Extensible Markup Language (XML)-compliant data document that is based on at least a portion of the at least one object and at least a portion of the mapping, the at least one computer-readable XML-compliant data document capable of including a plurality of line items with at least a portion of the original values including the at least one original value and at least some of the computer-readable semantic tags, where the computer program product is configured such that, based on the at least one reference of the at least one object to the at least one original value of the at least one original document, a change to the at least one original value of the at least one original document results in a corresponding change in an instance of the at least one computer-readable XML-compliant data document:, said computer program product configured such that the at least some of the computer-readable semantic tags are each computer-readably coupled to the at least portion of the original values of at least one computer-readable XML-compliant data document.

11. A computer program product embodied on a non-transitory computer readable medium, comprising: code for storing a plurality of original documents including a plurality of original values, including a first document including first values and a second document including second values; code for processing at least a part of the first document and at least a part of the second document, resulting in at least one object including at least one reference to at least one of the plurality of original values of at least one of the plurality of original documents; code for receiving a user selection of one or more computer-readable semantic tags; code for receiving a user selection of one or more of the original values; code for mapping the one or more of the computer-readable semantic tags to the one or more of the original values; code for outputting a presentation that is based on at least a portion of the at least one object, the presentation capable of including at least a portion of the original values including the at least one original value, where the computer program product is configured such that, based on the at least one reference of the at least one object to the at least one original value of the at least one original document, a change to the at least one original value of the at least one original document results in a corresponding change in an instance of the presentation; code for outputting a report that is based on at least a portion of the at least one object, the report capable of including at least a portion of the original values including the at least one original value, where the computer program product is configured such that, based on the at least one reference of the at least one object to the at least one original value of the at least one original document, a change to the at least one original value of the at least one original document results in a corresponding change in an instance of the report; and code for outputting at least one computer-readable Extensible Markup Language (XML)-compliant data document that is based on at least a portion of the at least one object and at least a portion of the mapping, the at least one computer-readable XML-compliant data document capable of including a plurality of line items with at least a portion of the original values including the at least one original value and at least some of the computer-readable semantic tags, where the computer program product is configured such that, based on the at least one reference of the at least one object to the at least one original value of the at least one original document, a change to the at least one original value of the at least one original document results in a corresponding change in an instance of the at least one computer-readable XML-compliant data document:, said computer program product configured such that the at least some of the computer-readable semantic tags are each computer-readably coupled to the at least portion of the original values of at least one computer-readable XML-compliant data document. 14. The computer program product of claim 11 , wherein the computer program product is configured for validating the at least one computer-readable XML-compliant data document by: identifying at least a subset of a plurality of computer-readable rules including at least one of: a computer-readable datatype rule for validation of a type of original values, a computer-readable calculation rule for validation of a calculation involving original values, or a computer-readable unit rule for validation of a unit of original values; and processing at least the portion of the original values of the at least one computer-readable XML-compliant data document, utilizing the at least subset of the computer-readable rules and at least a portion of the computer-readable sematic tags of the at least one computer-readable XML-compliant data document.

12. A method for conversing in a plurality of languages, comprising: establishing a plurality of real-time conference areas wherein each real-time conference area supports a language and is operated in parallel with the other conference areas such that each conference area contains the same messages in the same order, said plurality of real-time conference areas managed by an online service conference manager that manages translations of messages from each conference area for broadcast of translated messages to the other conference areas; posting a first message from a first user onto a first of said plurality of real-time conference areas for access by a plurality of computer users currently connected to said first of said plurality of real-time conference areas based on a specified preference for a first language, said first message in said first language and originating from a spoken communication; automatically determining that said first message posted to said first real-time conference area is untranslated; automatically translating said first message into a second language after determining said first message is untranslated; automatically posting said translated message to a second of said real-time conference areas for access by a plurality of computer users currently connected to said second of said plurality of real-time conference areas based on a specified preference for said second language; posting a response to said translated message onto said second of said plurality of real-time conference areas for access by said plurality of users currently connected to said second of said plurality of real-time conference areas, said response in said second language and originating from a spoken communication; automatically determining that said response posted to said second real-time conference area is untranslated; automatically translating said response into said first language after determining said response is untranslated; and automatically posting said translated response in said first language onto said first real-time conference area for access by said plurality of computer users currently connect to said first real-time conference area.

12. A method for conversing in a plurality of languages, comprising: establishing a plurality of real-time conference areas wherein each real-time conference area supports a language and is operated in parallel with the other conference areas such that each conference area contains the same messages in the same order, said plurality of real-time conference areas managed by an online service conference manager that manages translations of messages from each conference area for broadcast of translated messages to the other conference areas; posting a first message from a first user onto a first of said plurality of real-time conference areas for access by a plurality of computer users currently connected to said first of said plurality of real-time conference areas based on a specified preference for a first language, said first message in said first language and originating from a spoken communication; automatically determining that said first message posted to said first real-time conference area is untranslated; automatically translating said first message into a second language after determining said first message is untranslated; automatically posting said translated message to a second of said real-time conference areas for access by a plurality of computer users currently connected to said second of said plurality of real-time conference areas based on a specified preference for said second language; posting a response to said translated message onto said second of said plurality of real-time conference areas for access by said plurality of users currently connected to said second of said plurality of real-time conference areas, said response in said second language and originating from a spoken communication; automatically determining that said response posted to said second real-time conference area is untranslated; automatically translating said response into said first language after determining said response is untranslated; and automatically posting said translated response in said first language onto said first real-time conference area for access by said plurality of computer users currently connect to said first real-time conference area. 15. The method of claim 12 further comprising the step of converting said translated response from text-to-speech for a participant in said first real-time conference area.

10. One or more computer-readable storage media embodying computer-executable instructions, the computer-executable instructions being executable by a computing device to perform operations comprising: displaying a plurality of content elements as search results in a search results region of a graphical user interface (GUI), the search results based at least in part on one or more search terms provided as input to the GUI; receiving an edit, via the GUI, to one of the content elements in the search result to generate an edited content element; adding, via the GUI, an indication of the edited content element to a content region of the GUI configured to be populated with indications of content to be used for a page of an electronic document associated with a future publication date and time; displaying, via the GUI, the page of the electronic document including how the edited content element is currently configured to appear in the page of the electronic document at the future publication date and time; and storing the page including the edited content element for publication at the future publication date and time.

10. One or more computer-readable storage media embodying computer-executable instructions, the computer-executable instructions being executable by a computing device to perform operations comprising: displaying a plurality of content elements as search results in a search results region of a graphical user interface (GUI), the search results based at least in part on one or more search terms provided as input to the GUI; receiving an edit, via the GUI, to one of the content elements in the search result to generate an edited content element; adding, via the GUI, an indication of the edited content element to a content region of the GUI configured to be populated with indications of content to be used for a page of an electronic document associated with a future publication date and time; displaying, via the GUI, the page of the electronic document including how the edited content element is currently configured to appear in the page of the electronic document at the future publication date and time; and storing the page including the edited content element for publication at the future publication date and time. 13. The one or more computer readable storage media of claim 10 , further comprising receiving, via the GUI, further edits to the edited content element after said adding, including changing content in the edited content element on the page.

6. A computer program product for providing contextual feedback of rules proximity based on co-occurrence history, the computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code for selecting a rule for editing in a rules editor executing in memory of a computer; computer readable program code for identifying different rules also having been applied to an input in common with the selected rule; and, computer readable program code for displaying the identified different rules in the rules editor in connection with the selected rule.

6. A computer program product for providing contextual feedback of rules proximity based on co-occurrence history, the computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code for selecting a rule for editing in a rules editor executing in memory of a computer; computer readable program code for identifying different rules also having been applied to an input in common with the selected rule; and, computer readable program code for displaying the identified different rules in the rules editor in connection with the selected rule. 9. The computer program product of claim 6 , wherein the computer readable program code for identifying different rules also having been applied to an input in common with the selected rule, comprises computer readable program code for identifying in a rule correlation table different rules having respective normalized values derived from corresponding respective counts of common inputs for the selected rule that exceeds a threshold value.

1. A method comprising: identifying a data record for deletion from a database and storage in a data archive, the data record comprising a plurality of data record attributes, each of the plurality of data record attributes comprising a value that comprises at least one term; creating an archive record that comprises a first subset of attribute values of the plurality of data record attributes and an index record that comprises a second subset of attribute values of the plurality of data record attributes; storing the archive record in a data archive that is stored separately from the database; adding a reference to a location of the archive record in the data archive to the new index record; adding the new index record to a dictionary-based archive index that is stored separately from the database, the dictionary-based archive index comprising a plurality of index records and a dictionary, the adding of the index record to the dictionary-based archive index comprising identifying every term of the second subset of attribute values of the plurality of data record attributes and adding each of the terms to the dictionary except for those terms that are already in the dictionary, wherein at least one index record of the plurality of index records in the dictionary-based archive index comprises one term from terms stored in the dictionary, references to locations of multiple archive records in the data archive that contain the one term, and information regarding locations of the one term within the referenced multiple archive records, the location information including indications, for each of the multiple of archive records referenced by the at least one index record, respective attributes of the each of the multiple archive records in which the one term is found; deleting the data record from the database; determining whether an attribute value of the plurality of attribute values is required for frequent user read access; and if the attribute value is not required for frequent user read access, deleting the attribute value from the dictionary-based archive index.

1. A method comprising: identifying a data record for deletion from a database and storage in a data archive, the data record comprising a plurality of data record attributes, each of the plurality of data record attributes comprising a value that comprises at least one term; creating an archive record that comprises a first subset of attribute values of the plurality of data record attributes and an index record that comprises a second subset of attribute values of the plurality of data record attributes; storing the archive record in a data archive that is stored separately from the database; adding a reference to a location of the archive record in the data archive to the new index record; adding the new index record to a dictionary-based archive index that is stored separately from the database, the dictionary-based archive index comprising a plurality of index records and a dictionary, the adding of the index record to the dictionary-based archive index comprising identifying every term of the second subset of attribute values of the plurality of data record attributes and adding each of the terms to the dictionary except for those terms that are already in the dictionary, wherein at least one index record of the plurality of index records in the dictionary-based archive index comprises one term from terms stored in the dictionary, references to locations of multiple archive records in the data archive that contain the one term, and information regarding locations of the one term within the referenced multiple archive records, the location information including indications, for each of the multiple of archive records referenced by the at least one index record, respective attributes of the each of the multiple archive records in which the one term is found; deleting the data record from the database; determining whether an attribute value of the plurality of attribute values is required for frequent user read access; and if the attribute value is not required for frequent user read access, deleting the attribute value from the dictionary-based archive index. 3. The method of claim 1 , further comprising: accepting a query from a user for a desired archive record; performing a search of the dictionary-based archive index to find the desired archive record; and returning one or more of the values from the index record for the desired archive record in response to the query.

15. A wireless device, comprising: a memory and a processor that are respectively adapted to store and execute instructions that implement operations, the operations comprising: computing a location of the wireless device; predicting a future activity of a user based on user context and the computed location; determining a direction in which the wireless device is being pointed; determining a field of view associated with the direction; retrieving, from at least one network resource, information regarding at least one business within the determined field of view that relates to the predicted future activity, the retrieving being based at least on the computed location, the determined field of view, and the predicted future activity, and wherein the at least one network resource includes information identifying a type of business for each of the at least one business; accessing user preferences; inferring that at least a portion of the retrieved information may be of potential interest to the user, wherein the inferring is based upon: the user preferences, a satiation model that employs an amount of time since the user stopped at a location associated a particular type of business, and availability of the particular type of business in the direction in which the location aware wireless device is being pointed; and presenting at least the inferred portion of the retrieved information to the user.

15. A wireless device, comprising: a memory and a processor that are respectively adapted to store and execute instructions that implement operations, the operations comprising: computing a location of the wireless device; predicting a future activity of a user based on user context and the computed location; determining a direction in which the wireless device is being pointed; determining a field of view associated with the direction; retrieving, from at least one network resource, information regarding at least one business within the determined field of view that relates to the predicted future activity, the retrieving being based at least on the computed location, the determined field of view, and the predicted future activity, and wherein the at least one network resource includes information identifying a type of business for each of the at least one business; accessing user preferences; inferring that at least a portion of the retrieved information may be of potential interest to the user, wherein the inferring is based upon: the user preferences, a satiation model that employs an amount of time since the user stopped at a location associated a particular type of business, and availability of the particular type of business in the direction in which the location aware wireless device is being pointed; and presenting at least the inferred portion of the retrieved information to the user. 19. The wireless device of claim 15 , wherein the retrieved information includes information regarding a business located inside or behind a structure situated in the direction.

3. The method of claim 1 , further comprising: presenting the representative question to a human operator via a user interface; receiving the correct answer from the human operator; and applying the correct answer to all suspect interpretations in the cluster to generate corrected segments of text for the suspect interpretations in the cluster.

3. The method of claim 1 , further comprising: presenting the representative question to a human operator via a user interface; receiving the correct answer from the human operator; and applying the correct answer to all suspect interpretations in the cluster to generate corrected segments of text for the suspect interpretations in the cluster. 4. The method of claim 3 , further comprising: analyzing a previous correct answer to improve estimating the error probability for the first segment of text.

10. A system comprising one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving an expression in a query language, the expression having a query language construct representing an algebraic data type, wherein the expression specifies two or more alternative subtypes; generating, for each of the alternative subtypes, a respective domain relation having domain tuples that satisfy a definition of the alternative subtype within the expression; generating a respective domain id relation for each of the domain relations of the alternative subtypes, wherein the domain id relation for a corresponding domain relation of an alternative subtype has domain id tuples that each assign a respective unique domain identifier to each of the domain tuples belonging to the corresponding domain relation of the alternative subtype; generating a union relation for the algebraic data type, wherein the union relation assigns a respective branch identifier to each of the two or more alternative subtypes and, for each of the domain id relations, defines union tuples that each have i) a respective unique domain identifier of a domain id tuple of the corresponding domain id relation and ii) a branch identifier for the alternative subtype to which the domain id relation belongs; assigning unique union identifiers to each of the union tuples belonging to the union relation; generating a respective injector relation for each of the alternative subtypes, wherein each injector relation for an alternative subtype has injector tuples, each injector tuple having i) a first element from a particular domain tuple of the domain relation for the alternative subtype and ii) a union identifier assigned to a union tuple having (a) a unique domain identifier of the particular domain tuple according to the domain id relation for the alternative subtype and (b) a branch identifier for the alternative subtype; receiving a query referencing a variable having the algebraic data type, the algebraic data type having the two or more alternative subtypes; computing query results for the query including identifying one or more injector tuples that satisfy the query, each injector tuple satisfying the query belonging to one of the injector relations generated for the two or more alternative subtypes of the algebraic data type referenced by the query; and providing the computed query results in response to receiving the query.

10. A system comprising one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving an expression in a query language, the expression having a query language construct representing an algebraic data type, wherein the expression specifies two or more alternative subtypes; generating, for each of the alternative subtypes, a respective domain relation having domain tuples that satisfy a definition of the alternative subtype within the expression; generating a respective domain id relation for each of the domain relations of the alternative subtypes, wherein the domain id relation for a corresponding domain relation of an alternative subtype has domain id tuples that each assign a respective unique domain identifier to each of the domain tuples belonging to the corresponding domain relation of the alternative subtype; generating a union relation for the algebraic data type, wherein the union relation assigns a respective branch identifier to each of the two or more alternative subtypes and, for each of the domain id relations, defines union tuples that each have i) a respective unique domain identifier of a domain id tuple of the corresponding domain id relation and ii) a branch identifier for the alternative subtype to which the domain id relation belongs; assigning unique union identifiers to each of the union tuples belonging to the union relation; generating a respective injector relation for each of the alternative subtypes, wherein each injector relation for an alternative subtype has injector tuples, each injector tuple having i) a first element from a particular domain tuple of the domain relation for the alternative subtype and ii) a union identifier assigned to a union tuple having (a) a unique domain identifier of the particular domain tuple according to the domain id relation for the alternative subtype and (b) a branch identifier for the alternative subtype; receiving a query referencing a variable having the algebraic data type, the algebraic data type having the two or more alternative subtypes; computing query results for the query including identifying one or more injector tuples that satisfy the query, each injector tuple satisfying the query belonging to one of the injector relations generated for the two or more alternative subtypes of the algebraic data type referenced by the query; and providing the computed query results in response to receiving the query. 14. The system of claim 10 , wherein the injector relations are mutually disjoint.