Datasets:

patent

/

AIPD_nlp_sentence_dataset_v2

like 1

9. A printed document adapted to be scanned to permit a machine-representation of said document to be recovered with improved accuracy, said printed document comprising: one or more lines of printed human-recognizable characters machine-rendered from original machine-represented characters; and a machine-readable marker including a decimation sequence machine-derived by assigning binary values to respective ones of said original machine-represented characters.

9. A printed document adapted to be scanned to permit a machine-representation of said document to be recovered with improved accuracy, said printed document comprising: one or more lines of printed human-recognizable characters machine-rendered from original machine-represented characters; and a machine-readable marker including a decimation sequence machine-derived by assigning binary values to respective ones of said original machine-represented characters. 10. The document of claim 9 wherein said machine-readable marker further comprises at least one check-sum machine-derived from said original machine-represented characters.

9. A system, comprising: a data processing apparatus; and software stored in non-transitory computer readable storage medium storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: instantiating a virtual machine emulating an operating system of a user device; instantiating, within the virtual machine, a native application that generates application pages for display on a user device within the native application, the native application operating independent of a browser application that can operate on the user device; accessing, within the virtual machine, application pages of the native application, and for each of the application pages: extracting content from the application page, the content including content of a plurality of different content types, the content for each content type being extracted by a corresponding extractor specific to that content type; generating application page data describing content of the application page, the content described by the application page data including text that a user device displays on the application page when the user device displays the application page; and indexing the application page data for the native application in an index that is searchable by a search engine.

9. A system, comprising: a data processing apparatus; and software stored in non-transitory computer readable storage medium storing instructions executable by the data processing apparatus and that upon such execution cause the data processing apparatus to perform operations comprising: instantiating a virtual machine emulating an operating system of a user device; instantiating, within the virtual machine, a native application that generates application pages for display on a user device within the native application, the native application operating independent of a browser application that can operate on the user device; accessing, within the virtual machine, application pages of the native application, and for each of the application pages: extracting content from the application page, the content including content of a plurality of different content types, the content for each content type being extracted by a corresponding extractor specific to that content type; generating application page data describing content of the application page, the content described by the application page data including text that a user device displays on the application page when the user device displays the application page; and indexing the application page data for the native application in an index that is searchable by a search engine. 11. The system of claim 9 , the operations further comprising: receiving, from a publisher of the native application, data specifying application pages to be indexed for the native application; and accessing application pages of the native application comprises accessing only the application pages that are specified to be indexed for the native application.

14. An article, comprising a non-transitory storage medium having stored instructions that enable a machine to: process a domain model of a data storage system, the domain model including classes having attributes including relationship, external, and computed, wherein vertices for the data storage system correspond to a respective one of the classes; generate a semantic model from an instantiation of the domain model based upon a topology of the data storage system to determine the vertices; load topology information from the instantiation of the domain model and the relationships; process updates of the attributes; send messages to a target vertex based on the processing of the updates of the attributes; determine a semantic model for a class of the target vertex; for each message for the target vertex; determine a semantic model for the target vertex for the message, wherein the semantic model has a first expression; update the first expression; find expressions that depend on the first expression; determine whether the found dependent expressions are in the same class as the first expression; create a new output message for a dependent vertex when the found dependent expressions are not in the same class as the first expression; for the found dependent expressions in the same class as the first expression: re-evaluate the found dependent expressions; add to a list of messages to be processed for a vertex corresponding to where the re-evaluated found dependent expressions changes value; generate a new external message if the found dependent expressions are marked for export; and process further attribute updates, wherein an output message for a dependent vertex is sent as a difference between the old and new values of an attribute.

14. An article, comprising a non-transitory storage medium having stored instructions that enable a machine to: process a domain model of a data storage system, the domain model including classes having attributes including relationship, external, and computed, wherein vertices for the data storage system correspond to a respective one of the classes; generate a semantic model from an instantiation of the domain model based upon a topology of the data storage system to determine the vertices; load topology information from the instantiation of the domain model and the relationships; process updates of the attributes; send messages to a target vertex based on the processing of the updates of the attributes; determine a semantic model for a class of the target vertex; for each message for the target vertex; determine a semantic model for the target vertex for the message, wherein the semantic model has a first expression; update the first expression; find expressions that depend on the first expression; determine whether the found dependent expressions are in the same class as the first expression; create a new output message for a dependent vertex when the found dependent expressions are not in the same class as the first expression; for the found dependent expressions in the same class as the first expression: re-evaluate the found dependent expressions; add to a list of messages to be processed for a vertex corresponding to where the re-evaluated found dependent expressions changes value; generate a new external message if the found dependent expressions are marked for export; and process further attribute updates, wherein an output message for a dependent vertex is sent as a difference between the old and new values of an attribute. 15. The article according to claim 14 , wherein at least one of the relationships includes a cardinality comprising an expected size of the relationship.

10. An apparatus for generating language by transforming raw input data that is at least partially expressed in a non-linguistic format into a format that can be expressed linguistically in a textual output, the apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least: generate one or more phrase specifications from the raw input data; identify the one or more phrase specifications that contain at least one aggregatable constituent; generate one or more generalized phrase specifications based on the one or more phrase specifications; identify two or more generalized phrase specifications, wherein the two or more generalized phrase specifications contain at least one aggregatable constituent; generate an aggregated phrase specification from the two or more generalized phrase specifications, wherein the aggregated phrase specification comprises at least one of a combined noun phrase generated from the at least one aggregatable constituents and one or more additional constituents based on a determined level of generalization; and generate the textual output, based at least in part on the aggregated phrase specification, such that it is displayable on a user interface.

10. An apparatus for generating language by transforming raw input data that is at least partially expressed in a non-linguistic format into a format that can be expressed linguistically in a textual output, the apparatus comprising: at least one processor; and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to at least: generate one or more phrase specifications from the raw input data; identify the one or more phrase specifications that contain at least one aggregatable constituent; generate one or more generalized phrase specifications based on the one or more phrase specifications; identify two or more generalized phrase specifications, wherein the two or more generalized phrase specifications contain at least one aggregatable constituent; generate an aggregated phrase specification from the two or more generalized phrase specifications, wherein the aggregated phrase specification comprises at least one of a combined noun phrase generated from the at least one aggregatable constituents and one or more additional constituents based on a determined level of generalization; and generate the textual output, based at least in part on the aggregated phrase specification, such that it is displayable on a user interface. 16. An apparatus according to claim 10 , wherein the at least one memory including the computer program code is further configured to, with the at least one processor, cause the apparatus to: generate the combined noun phrase using the at least one aggregatable constituent in the two or more generalized phrase specifications.

24. A computer readable medium storing a computer program for providing information assistance to a wireless terminal in a wireless communication system, comprising: a code segment that receives a contact information request message specifically requesting a phone number associated with a subscriber terminal, the request generated with a wireless terminal that is other than the subscriber terminal by a requestor that is other than a user of the subscriber terminal; a code segment to query a participating communication provider database of a communication provider providing communication services to the wireless terminal to identify a virtual key of the requestor from unique information included within the contact information request, the virtual key being a universal anonymous identifier of the requestor that is shared among a plurality of different participating businesses; a code segment to access, using the virtual key of the requestor, a consumer internal profile database containing verification data of the requestor and proprietary information of the requestor; a code segment to verify, with the verification data, consent of the requestor to release and use of the proprietary information of the requestor; a code segment responsive to the contact information request that determines how to contact the subscriber terminal; a code segment that generates an authorization request for permission to provide the phone number associated with the subscriber terminal to the wireless terminal, wherein the authorization request includes at least a portion of the proprietary information of the requestor from the consumer internal profile database; a code segment that transmits the authorization request to the subscriber terminal; a code segment that interprets a reply from the subscriber terminal to determine if permission to provide the phone number associated with the subscriber terminal to the wireless terminal was granted; a code segment to determine from the consumer subscriber database based on the virtual key of the requestor, a communication preference of the requestor and compatibility settings of the wireless terminal; and a code segment that generates a response to the wireless terminal that includes the phone number associated with the subscriber terminal when permission is granted, the response generated in accordance with the communication preference and the compatibility settings.

24. A computer readable medium storing a computer program for providing information assistance to a wireless terminal in a wireless communication system, comprising: a code segment that receives a contact information request message specifically requesting a phone number associated with a subscriber terminal, the request generated with a wireless terminal that is other than the subscriber terminal by a requestor that is other than a user of the subscriber terminal; a code segment to query a participating communication provider database of a communication provider providing communication services to the wireless terminal to identify a virtual key of the requestor from unique information included within the contact information request, the virtual key being a universal anonymous identifier of the requestor that is shared among a plurality of different participating businesses; a code segment to access, using the virtual key of the requestor, a consumer internal profile database containing verification data of the requestor and proprietary information of the requestor; a code segment to verify, with the verification data, consent of the requestor to release and use of the proprietary information of the requestor; a code segment responsive to the contact information request that determines how to contact the subscriber terminal; a code segment that generates an authorization request for permission to provide the phone number associated with the subscriber terminal to the wireless terminal, wherein the authorization request includes at least a portion of the proprietary information of the requestor from the consumer internal profile database; a code segment that transmits the authorization request to the subscriber terminal; a code segment that interprets a reply from the subscriber terminal to determine if permission to provide the phone number associated with the subscriber terminal to the wireless terminal was granted; a code segment to determine from the consumer subscriber database based on the virtual key of the requestor, a communication preference of the requestor and compatibility settings of the wireless terminal; and a code segment that generates a response to the wireless terminal that includes the phone number associated with the subscriber terminal when permission is granted, the response generated in accordance with the communication preference and the compatibility settings. 26. The computer readable medium of claim 24 , wherein the response comprises a multi-modal message that includes both a voice-based response and a text-based response as indicated in the consumer subscriber database as the communication preference.

8. The method of claim 1 , wherein constructing a super file comprises: in response to a set of files to be indexed, grouping the files into one or more groups based on similarity of the files; and for each group creating a super file containing all terms or sequences of terms obtained from the associated files.

8. The method of claim 1 , wherein constructing a super file comprises: in response to a set of files to be indexed, grouping the files into one or more groups based on similarity of the files; and for each group creating a super file containing all terms or sequences of terms obtained from the associated files. 9. The method of claim 8 , wherein creating a super file comprises: including in the super file one or more sequences of one or more terms obtained from a file selected from a group of files; for each of remaining files in the group, determining whether each segment of a remaining file exists in the super file; and appending a segment of the remaining file to the super file whether the segment does not exist in the super file.

2. The method of claim 1 further comprising generating a reference model based on the word-level data flow graph.

2. The method of claim 1 further comprising generating a reference model based on the word-level data flow graph. 5. The method of claim 2 further comprising reducing the bit-level data flow graph by finding adders, to produce a reduced bit-level data flow graph.

14. A tangible machine-readable medium having instructions for at least one processor recorded thereon, the instructions comprising: instructions for receiving input indicating at least one atom of a plurality of atoms of handwritten input, the at least one atom having been misrecognized by a recognizer; instructions for displaying a menu of possible recognition results based on the at least one atom; instructions for receiving a selection of one of the possible recognition results as a correction hint; and instructions for leveraging the correction hint to produce a corrected recognition result, the instructions for leveraging the correction hint to produce a corrected recognition result further comprising at least one group of instructions selected from: a first group of instructions for linearly transforming the at least one atom corresponding to the correction hint such that the at least one atom is horizontally or vertically separate from other atoms of the plurality of atoms, a second group of instructions for leveraging the correction hint to correct an over-grouping error of a matrix when the second correction hint indicates that the at least one atom is to be in a single cell of a matrix, and a third group of instructions for recognizing the at least one atom as being under a root structure when the correction hint indicates that a first part of the at least one atom corresponding to the correction hint is under a root structure and a second part of the at least one atom corresponding to the correction hint is not under the root structure.

14. A tangible machine-readable medium having instructions for at least one processor recorded thereon, the instructions comprising: instructions for receiving input indicating at least one atom of a plurality of atoms of handwritten input, the at least one atom having been misrecognized by a recognizer; instructions for displaying a menu of possible recognition results based on the at least one atom; instructions for receiving a selection of one of the possible recognition results as a correction hint; and instructions for leveraging the correction hint to produce a corrected recognition result, the instructions for leveraging the correction hint to produce a corrected recognition result further comprising at least one group of instructions selected from: a first group of instructions for linearly transforming the at least one atom corresponding to the correction hint such that the at least one atom is horizontally or vertically separate from other atoms of the plurality of atoms, a second group of instructions for leveraging the correction hint to correct an over-grouping error of a matrix when the second correction hint indicates that the at least one atom is to be in a single cell of a matrix, and a third group of instructions for recognizing the at least one atom as being under a root structure when the correction hint indicates that a first part of the at least one atom corresponding to the correction hint is under a root structure and a second part of the at least one atom corresponding to the correction hint is not under the root structure. 16. The tangible machine-readable medium of claim 14 , wherein the instructions for leveraging the correction hint to produce a corrected recognition result further comprise: instructions for producing a plurality of second possible recognition results by summing scores corresponding to ones of a plurality of rewriting rules used when producing each one of the plurality of second possible recognition results from the plurality of atoms; instructions for determining whether applying any of the ones of the plurality of rewriting rules to the plurality of atoms to produce the ones of the plurality of second possible recognition results does not conform with the correction hint; instructions for adding a penalty score to ones of the sums of the scores having a corresponding rewriting rule not conforming with the correction hint; and instruction for selecting a best recognition result from the plurality of second possible recognition results, based on the summed scores of each of the ones of the plurality of second possible recognition results.

15. A non-transitory computer-readable storage medium storing computer executable instructions that when executed by a processor perform operations comprising: receiving a search phrase; determining a plurality of color palettes based at least in part on the search phrase being associated with the plurality of color palettes, wherein each color palette of the plurality of color palettes comprise one or more colors; selecting a subset of color palettes from the plurality of color palettes, wherein selecting the subset of color palettes comprises: determining, from the plurality of color palettes, a greater number of color palettes comprising a first color and having a creation time or update time within a threshold period of time than a number of color palettes comprising the first color and having a creation time or update time outside of the threshold period; and determining, from the plurality of color palettes, each color palette of the subset of the plurality of color palettes comprising the first color; selecting a priority color palette from the subset of color palettes, wherein the priority color palette is selected from the subset of color palettes based at least in part on a creation time or update time of the priority color palette; identifying a first set of images corresponding to a first color of the priority color palette, wherein the identification of the first set of images is based at least in part on a first category associated with the first set of images; identifying a second set of images corresponding to a second color of the priority color palette, wherein the identification of the second set of images is based at least in part on a second category associated with the second set of images; and providing the first set of images and the second set of images for presentation.

15. A non-transitory computer-readable storage medium storing computer executable instructions that when executed by a processor perform operations comprising: receiving a search phrase; determining a plurality of color palettes based at least in part on the search phrase being associated with the plurality of color palettes, wherein each color palette of the plurality of color palettes comprise one or more colors; selecting a subset of color palettes from the plurality of color palettes, wherein selecting the subset of color palettes comprises: determining, from the plurality of color palettes, a greater number of color palettes comprising a first color and having a creation time or update time within a threshold period of time than a number of color palettes comprising the first color and having a creation time or update time outside of the threshold period; and determining, from the plurality of color palettes, each color palette of the subset of the plurality of color palettes comprising the first color; selecting a priority color palette from the subset of color palettes, wherein the priority color palette is selected from the subset of color palettes based at least in part on a creation time or update time of the priority color palette; identifying a first set of images corresponding to a first color of the priority color palette, wherein the identification of the first set of images is based at least in part on a first category associated with the first set of images; identifying a second set of images corresponding to a second color of the priority color palette, wherein the identification of the second set of images is based at least in part on a second category associated with the second set of images; and providing the first set of images and the second set of images for presentation. 20. The non-transitory computer-readable storage medium of claim 15 , wherein the search phrase is based at least in part on user input.

12. A device, comprising: at least one processor; a memory device including instructions operable to be executed by the at least one processor to perform a set of actions, configuring the at least one processor to: receive a first utterance from a device, the first utterance including an audible command; determine first data corresponding to the first utterance; obtain second data corresponding to a second utterance, wherein the second utterance is not received from the device; compare the first data corresponding to the first utterance to the second data corresponding to the second utterance; and cancel processing of the first utterance in response to the first data substantially matching the second data.

12. A device, comprising: at least one processor; a memory device including instructions operable to be executed by the at least one processor to perform a set of actions, configuring the at least one processor to: receive a first utterance from a device, the first utterance including an audible command; determine first data corresponding to the first utterance; obtain second data corresponding to a second utterance, wherein the second utterance is not received from the device; compare the first data corresponding to the first utterance to the second data corresponding to the second utterance; and cancel processing of the first utterance in response to the first data substantially matching the second data. 18. The device of claim 12 , wherein the at least one processor is further configured to: receive a plurality of utterances from a plurality of devices at a substantially similar time; and wherein the comparing comprises comparing the plurality or received utterances to each other to determine whether the plurality of received utterances are substantially similar.

18. The method of claim 14 , wherein generating further comprises: generating a feed-forward neural network (FFNN) specialized in providing information most relevant to an end user of the client application; calculating which document is most relevant for the end user; calculating response information based on previously learned calculation functions; building terminology definitions using semantic objects and relations; extracting terminology from particular domain-specific repositories; extracting terminology from one or more domain-specific repositories comprising document management systems (DMS), business applications, and business objects; and organizing data structure and data clusters in the request dispatcher and classifier and the search module container.

18. The method of claim 14 , wherein generating further comprises: generating a feed-forward neural network (FFNN) specialized in providing information most relevant to an end user of the client application; calculating which document is most relevant for the end user; calculating response information based on previously learned calculation functions; building terminology definitions using semantic objects and relations; extracting terminology from particular domain-specific repositories; extracting terminology from one or more domain-specific repositories comprising document management systems (DMS), business applications, and business objects; and organizing data structure and data clusters in the request dispatcher and classifier and the search module container. 19. The method of claim 18 , further comprising: managing training, validation, and test sets for artificial neural networks (ANN) and feed-forward neural networks (FFNN); and controlling cluster data flow of input data used in each domain-specific module.

14. The invention of claim 12 , wherein: step (b) comprises: (b1) generating multi-level hierarchical groupings of Internet Protocol (IP) addresses in the association based on similarities between at least first and second levels of domain names in failed domain-name queries made by hosts corresponding to the IP addresses; (b2) determining, for each hierarchical grouping, a highest percentage of failed domain-name queries for which a most recently added IP address in the hierarchical grouping has at least first and second levels of domain names in common with another IP address in the hierarchical grouping; and (b3) identifying each highest-level hierarchical grouping having its determined percentage more than a specified percentage threshold as a candidate cluster of hosts; and step (e) comprises: (e1) determining, for each cluster chain identified in step (d) and for each of a plurality of time intervals during the time period, a number of new domain names appearing in the failed queries of the cluster chain during the time interval; (e2) determining, for each cluster chain, a freshness metric based on the numbers of new domain names for the plurality of time intervals in the time period; and (e3) detecting one or more malicious software agents on the hosts based on the one or more freshness metrics.

14. The invention of claim 12 , wherein: step (b) comprises: (b1) generating multi-level hierarchical groupings of Internet Protocol (IP) addresses in the association based on similarities between at least first and second levels of domain names in failed domain-name queries made by hosts corresponding to the IP addresses; (b2) determining, for each hierarchical grouping, a highest percentage of failed domain-name queries for which a most recently added IP address in the hierarchical grouping has at least first and second levels of domain names in common with another IP address in the hierarchical grouping; and (b3) identifying each highest-level hierarchical grouping having its determined percentage more than a specified percentage threshold as a candidate cluster of hosts; and step (e) comprises: (e1) determining, for each cluster chain identified in step (d) and for each of a plurality of time intervals during the time period, a number of new domain names appearing in the failed queries of the cluster chain during the time interval; (e2) determining, for each cluster chain, a freshness metric based on the numbers of new domain names for the plurality of time intervals in the time period; and (e3) detecting one or more malicious software agents on the hosts based on the one or more freshness metrics. 15. The invention of claim 14 , wherein the specified percentage threshold is 40%.

1. A machine for designing the logical structure of a large computer program, the machine comprising (a) an input device (11) capable of entering into processing unit (12) of the machine a collection of informational words (10), numerically describing links between different portions of the computer program, said portions being called "logical parts", each link representing a transfer of control of data processing action from one logical part through its port, said port being called "exit", to the port of another logical part, said port being called "entrance"; each informational word containing at least seven numbers, of which three numbers-a logical part number, an exit number, a program line number of the exit-are attributes of the exit of one logical part, the other three of said seven numbers are attributes of the entrance of the linked logical part, said collection of informational words being called "parent collection"; (b) said processing unit (12) having an algorithm of memorizing the entered parent collection and performing a search of informational words by the attributes of a logical part; (c) an output device (15) providing a hard copy printout of informational words (16) arranged in a consecutive order of the numbers of logical parts.

1. A machine for designing the logical structure of a large computer program, the machine comprising (a) an input device (11) capable of entering into processing unit (12) of the machine a collection of informational words (10), numerically describing links between different portions of the computer program, said portions being called "logical parts", each link representing a transfer of control of data processing action from one logical part through its port, said port being called "exit", to the port of another logical part, said port being called "entrance"; each informational word containing at least seven numbers, of which three numbers-a logical part number, an exit number, a program line number of the exit-are attributes of the exit of one logical part, the other three of said seven numbers are attributes of the entrance of the linked logical part, said collection of informational words being called "parent collection"; (b) said processing unit (12) having an algorithm of memorizing the entered parent collection and performing a search of informational words by the attributes of a logical part; (c) an output device (15) providing a hard copy printout of informational words (16) arranged in a consecutive order of the numbers of logical parts. 3. A machine of claim 1, further comprising (d) an output device (15) providing a hard copy printout of informational words (16) in the order of their location in the collection.

1. A method for ingesting and delivering video comprising: crawling, by a crawler component executed by a processor, one or more predetermined video reference sources and selectively ingesting, by an ingest component executed by a processor, one or more videos and their metadata based on predetermined ingest criteria, the ingested metadata including a title for each video and a description for each video, the title and description being maintained by a third party location from which the video and its metadata are ingested; analyzing, by an analysis component executed by a processor, the ingested videos to identify moments in the video by parsing comments relating to the video, identifying a moment if a comment includes a reference to a time in the video and storing the time and a text of the comment in a record of the moment; recording user activity data related to a user's activity with respect to one or more ingested videos, the user activity data including at least data indicating previous search parameters received from the user; rating, by a rating component executed by a processor, the video according to predetermined rating factors, including at least comparing metadata of the video to previous search parameters received from the user; searching, by a search component executed by a processor, at least the text of moment records and the titles and keywords associated with ingested videos based on search parameters received from the user; selectively delivering videos, by a delivery component executed by a processor, based on the results of the searching step in order of their rating as determined by the results of the rating step; displaying moments together with the delivered videos by displaying text of a particular moment at the time of the particular moment as the video is delivered; storing the search parameters received from the user as a channel; and in response to the receipt of a selection of a channel from a user, searching at least the text of moment records based on search parameters stored in association with the channel.

1. A method for ingesting and delivering video comprising: crawling, by a crawler component executed by a processor, one or more predetermined video reference sources and selectively ingesting, by an ingest component executed by a processor, one or more videos and their metadata based on predetermined ingest criteria, the ingested metadata including a title for each video and a description for each video, the title and description being maintained by a third party location from which the video and its metadata are ingested; analyzing, by an analysis component executed by a processor, the ingested videos to identify moments in the video by parsing comments relating to the video, identifying a moment if a comment includes a reference to a time in the video and storing the time and a text of the comment in a record of the moment; recording user activity data related to a user's activity with respect to one or more ingested videos, the user activity data including at least data indicating previous search parameters received from the user; rating, by a rating component executed by a processor, the video according to predetermined rating factors, including at least comparing metadata of the video to previous search parameters received from the user; searching, by a search component executed by a processor, at least the text of moment records and the titles and keywords associated with ingested videos based on search parameters received from the user; selectively delivering videos, by a delivery component executed by a processor, based on the results of the searching step in order of their rating as determined by the results of the rating step; displaying moments together with the delivered videos by displaying text of a particular moment at the time of the particular moment as the video is delivered; storing the search parameters received from the user as a channel; and in response to the receipt of a selection of a channel from a user, searching at least the text of moment records based on search parameters stored in association with the channel. 2. The method of claim 1 , wherein the predetermined rating factors include at least the total number of moments identified for the video.

86. A method for assisting a computer operator to retrieve contact related information from a database when a document includes a name, the method comprising of the steps of: (1) using a first computer program to analyze the document, without direction from the operator, to identify the name, (2) using the identified name and a second computer program to search the database and to locate contact related information associated with the name, and (3) inserting the contact related information into the document, wherein steps (1)-(3) require only a single execute command.

86. A method for assisting a computer operator to retrieve contact related information from a database when a document includes a name, the method comprising of the steps of: (1) using a first computer program to analyze the document, without direction from the operator, to identify the name, (2) using the identified name and a second computer program to search the database and to locate contact related information associated with the name, and (3) inserting the contact related information into the document, wherein steps (1)-(3) require only a single execute command. 87. The method of claim 86 wherein the contact related information comprises an address.

22. A set-top box comprising: a receiver to receive primary programming from a broadcast programming source; a supplemental programming database having content criteria and associated supplemental programming, the supplemental programming being programming that supplements the primary programming; a supplemental programming agent, coupled to the supplemental programming database, the supplemental programming agent comprising a commentary provider to evaluate received primary programming using the content criteria and identify supplemental programming using the database, and a commentary generator module coupled to the commentary provider to generate commentary based on the supplemental programming; and a commentary delivery module, coupled to the commentary generator module, to provide the generated commentary to an element of an entertainment system; wherein the supplemental programming agent comprises a video evaluator to evaluate video of primary programming using the content criteria and identify supplemental programming using the supplemental programming database.

22. A set-top box comprising: a receiver to receive primary programming from a broadcast programming source; a supplemental programming database having content criteria and associated supplemental programming, the supplemental programming being programming that supplements the primary programming; a supplemental programming agent, coupled to the supplemental programming database, the supplemental programming agent comprising a commentary provider to evaluate received primary programming using the content criteria and identify supplemental programming using the database, and a commentary generator module coupled to the commentary provider to generate commentary based on the supplemental programming; and a commentary delivery module, coupled to the commentary generator module, to provide the generated commentary to an element of an entertainment system; wherein the supplemental programming agent comprises a video evaluator to evaluate video of primary programming using the content criteria and identify supplemental programming using the supplemental programming database. 25. The set-top box of claim 22 , wherein the primary programming comprises video and wherein the commentary provider comprises a content evaluator module to evaluate the video of the primary programming using the content criteria and identify supplemental programming using the supplemental programming database.

1. A method comprising: receiving first recognized text corresponding to first speech input from a user; displaying a first tab of a user interface, the first tab corresponding to a first application, wherein the first tab comprises the first recognized text with an icon associated with the first application; receiving second recognized text corresponding to second speech input from the user; displaying, responsive to the first speech input and the second speech input, a second tab of the user interface, the second tab corresponding to a second application, wherein the second application is selected based on the second speech input; receiving third recognized text corresponding to third speech input from the user; and displaying the first tab of the user interface, wherein the first tab further comprises the second recognized text with an icon associated with the second application and the third recognized text with the icon associated with the first application.

1. A method comprising: receiving first recognized text corresponding to first speech input from a user; displaying a first tab of a user interface, the first tab corresponding to a first application, wherein the first tab comprises the first recognized text with an icon associated with the first application; receiving second recognized text corresponding to second speech input from the user; displaying, responsive to the first speech input and the second speech input, a second tab of the user interface, the second tab corresponding to a second application, wherein the second application is selected based on the second speech input; receiving third recognized text corresponding to third speech input from the user; and displaying the first tab of the user interface, wherein the first tab further comprises the second recognized text with an icon associated with the second application and the third recognized text with the icon associated with the first application. 2. The method of claim 1 , wherein the first application comprises a text messaging application and the second application comprises an email application, a social media application, a weather application, or a map application.

1. A computer-implemented method for performing fuzzy full text search, comprising: receiving a search term; initializing a priority queue by storing a first node and an edit distance of zero in the priority queue, wherein the priority queue comprises entries for each node in an inverted token next valid character tree that track the edit distance between the nodes and the search term; exploring paths of the inverted token next valid character tree from the first node to children nodes of the first node: if there are children nodes, removing the first node from the priority queue by deleting an entry for the first node in the priority queue; storing the children nodes and associated edit distances to the search term in the priority queue, wherein the children nodes are stored in the priority queue in an order of smallest edit distance to largest edit distance; exploring paths of the inverted token next valid character tree from the child node having the smallest edit distance to the search term; and in response to the path from the child node ending at a leaf node, providing a result set of document identifiers stored at the leaf node.

1. A computer-implemented method for performing fuzzy full text search, comprising: receiving a search term; initializing a priority queue by storing a first node and an edit distance of zero in the priority queue, wherein the priority queue comprises entries for each node in an inverted token next valid character tree that track the edit distance between the nodes and the search term; exploring paths of the inverted token next valid character tree from the first node to children nodes of the first node: if there are children nodes, removing the first node from the priority queue by deleting an entry for the first node in the priority queue; storing the children nodes and associated edit distances to the search term in the priority queue, wherein the children nodes are stored in the priority queue in an order of smallest edit distance to largest edit distance; exploring paths of the inverted token next valid character tree from the child node having the smallest edit distance to the search term; and in response to the path from the child node ending at a leaf node, providing a result set of document identifiers stored at the leaf node. 2. The method of claim 1 , wherein if the path from the child node ends at a second child node, adding the second child node and an associated edit distance to the search term to the priority queue.

18. A system for presenting content personalized for a user comprising: a processor; memory coupled to the processor; a learning module of a server computer for analyzing and categorizing the content using artificial intelligence and storing the categorized content on a memory of a server computer; a training module of the server computer for capturing explicit preferences of a user comprising user content interests, preferred content type, preferred presentation type, preferred language and preferred presentation format; storing the captured explicit preferences of the user on the memory of the server computer in an internal representation of the user's preferences; storing an internal representation of prior knowledge of the user; and determining a plurality of implicit preferences of the user, wherein the implicit preferences comprise geography, language, or media type; a content processing module of the server computer for mapping the categorized content to the internal representation of the user's preferences and the internal representation of prior knowledge of the user to discover the content relevant to the user, from the categorized content, and to discover the preferred presentation type and formats; and processing the content relevant to the user into the preferred presentation type and format for presenting to the user on a user device; wherein at least one conflict between a conflicting explicit preference and a conflicting implicit preference is resolved by giving precedence to the conflicting explicit preference; and a content presentation module of the server computer for rendering the relevant content in the preferred presentation type and format on the user device.

18. A system for presenting content personalized for a user comprising: a processor; memory coupled to the processor; a learning module of a server computer for analyzing and categorizing the content using artificial intelligence and storing the categorized content on a memory of a server computer; a training module of the server computer for capturing explicit preferences of a user comprising user content interests, preferred content type, preferred presentation type, preferred language and preferred presentation format; storing the captured explicit preferences of the user on the memory of the server computer in an internal representation of the user's preferences; storing an internal representation of prior knowledge of the user; and determining a plurality of implicit preferences of the user, wherein the implicit preferences comprise geography, language, or media type; a content processing module of the server computer for mapping the categorized content to the internal representation of the user's preferences and the internal representation of prior knowledge of the user to discover the content relevant to the user, from the categorized content, and to discover the preferred presentation type and formats; and processing the content relevant to the user into the preferred presentation type and format for presenting to the user on a user device; wherein at least one conflict between a conflicting explicit preference and a conflicting implicit preference is resolved by giving precedence to the conflicting explicit preference; and a content presentation module of the server computer for rendering the relevant content in the preferred presentation type and format on the user device. 23. The system according to claim 18 , wherein mapping the categorized content to the internal representation of prior knowledge of the user comprises determining similarities and differences with the internal representation of prior knowledge of the user.

33. An apparatus comprising: one or more non-transitory computer-readable storage devices comprising processor- executable instructions, the processor-executable instructions capable of causing one or more processors of a server computer system to perform the following method steps: establishing an account for each of a plurality of users, wherein each account is associated with storage space to store one or more documents; storing a first document in the server computer system in a first account, the first document capable of being modified by a plurality of authorized users; enabling access to the first document via a browser-controlled window executing on a client computer by one or more authorized users; associating a set of restrictions with the first document, the restrictions including an ability to modify the first document in one or more permitted ways by one of a first group of users, the first group of users being users whose identities are known to the server computer system; receiving a request to access the first document from a first user, wherein the first user is a member of the first group of users, wherein the request to access accompanies the first user's identification information and authorization information; verifying the identity of the first user; if the first user is authorized to access the first document, then permitting the first user to access the first document via a first browser-controlled window executing on a client computer; and if the first user is authorized to modify the first document, then: (a) applying one or more modifications to the first document, the one or more modifications having been received from the first user; (b) electronically notifying one or more of a second group of users that the first user modified the first document, the second group of users being users whose identities are known to the server computer system; and (c) enabling a second user to further modify the first document, wherein the second user is a member of the second group of users who are notified of the one or more modifications made by the first user to the first document, and wherein the second user is not the same as the first user.

33. An apparatus comprising: one or more non-transitory computer-readable storage devices comprising processor- executable instructions, the processor-executable instructions capable of causing one or more processors of a server computer system to perform the following method steps: establishing an account for each of a plurality of users, wherein each account is associated with storage space to store one or more documents; storing a first document in the server computer system in a first account, the first document capable of being modified by a plurality of authorized users; enabling access to the first document via a browser-controlled window executing on a client computer by one or more authorized users; associating a set of restrictions with the first document, the restrictions including an ability to modify the first document in one or more permitted ways by one of a first group of users, the first group of users being users whose identities are known to the server computer system; receiving a request to access the first document from a first user, wherein the first user is a member of the first group of users, wherein the request to access accompanies the first user's identification information and authorization information; verifying the identity of the first user; if the first user is authorized to access the first document, then permitting the first user to access the first document via a first browser-controlled window executing on a client computer; and if the first user is authorized to modify the first document, then: (a) applying one or more modifications to the first document, the one or more modifications having been received from the first user; (b) electronically notifying one or more of a second group of users that the first user modified the first document, the second group of users being users whose identities are known to the server computer system; and (c) enabling a second user to further modify the first document, wherein the second user is a member of the second group of users who are notified of the one or more modifications made by the first user to the first document, and wherein the second user is not the same as the first user. 42. The apparatus of claim 33 , wherein the server computer system is capable of generating an alarm condition if the first user is not authorized to modify the first document.

1. A rejection grammar process for use in speech recognition of an utterance comprising the steps of: selecting a digitized sub-list of phoneme models from a digitized list of phoneme models in a language, presenting a digitized sequential representation of the utterance to the rejection grammar process, and calculating a first set of probabilities indicating how well the digitized sequential representation of the utterance matches sequential combinations, or paths, of the digitized sub-list of phoneme models.

1. A rejection grammar process for use in speech recognition of an utterance comprising the steps of: selecting a digitized sub-list of phoneme models from a digitized list of phoneme models in a language, presenting a digitized sequential representation of the utterance to the rejection grammar process, and calculating a first set of probabilities indicating how well the digitized sequential representation of the utterance matches sequential combinations, or paths, of the digitized sub-list of phoneme models. 3. A speech recognition process comprising the rejection grammar process as set forth in claim 1 and further comprising the steps of: generating a digitized list of words, comparing the digitized sequential representation of the utterance to sequences of said digitized list of words using an accepted main grammar process, calculating a second set of probabilities from said comparing step, determining the highest probabilities from each of the first and the second sets of probabilities, comparing the highest probabilities from each of the first and second sets of probabilities, if the highest probability is found in the first set of probabilities, rejecting the utterance, and if the highest probability is found in the second set of probabilities, accepting the utterance.

9. The method of claim 6 , wherein creating the feature index from the invisible junction feature descriptors comprises: creating a quantization tree; and adding a feature point to the quantization tree for the invisible junction feature descriptors.

9. The method of claim 6 , wherein creating the feature index from the invisible junction feature descriptors comprises: creating a quantization tree; and adding a feature point to the quantization tree for the invisible junction feature descriptors. 10. The method of claim 9 , wherein the quantization tree and the feature point are stored in a database.

1. A computer-implemented method for an author-centric search, comprising: initializing a first data structure and a second data structure for each of a plurality of documented communications wherein each of the plurality of documented communications has at least one author to which the respective documented communication is attributed; utilizing the first data structure and the second data structure to compute a relevancy score for each of the plurality of documented communications; determining a score for an author of at least one of the plurality of documented communications based in part on the relevancy score for each of the plurality of documented communications authored by the author; prompting a user to enter a search string; parsing the search string into one or more words; populating at least one memory space of the first data structure for each documented communication with data based on the occurrence of the one or more words in the documented communication; populating at least one memory space of the second data structure for each documented communication with a weighted value for an author of a given documented communication that signifies a statistical preference for the data in the corresponding memory space of the first data structure; executing a mathematical function based on an aggregate of the data and the weighted value of the first and second data structures for each documented communication in order to compute the relevancy score for the documented communication; and displaying search results based at least in part upon a ranked listing of one or more author scores, wherein the weighted value for the author comprises a predefined value utilized to create the statistical preference for data in the corresponding memory space of the first data structure, the weighted value for the author being determined based on at least two of: a time of publication for the documented communication, a number of documented communications having the author, a prestige of the documented communication, and a number of authors for the documented communication.

1. A computer-implemented method for an author-centric search, comprising: initializing a first data structure and a second data structure for each of a plurality of documented communications wherein each of the plurality of documented communications has at least one author to which the respective documented communication is attributed; utilizing the first data structure and the second data structure to compute a relevancy score for each of the plurality of documented communications; determining a score for an author of at least one of the plurality of documented communications based in part on the relevancy score for each of the plurality of documented communications authored by the author; prompting a user to enter a search string; parsing the search string into one or more words; populating at least one memory space of the first data structure for each documented communication with data based on the occurrence of the one or more words in the documented communication; populating at least one memory space of the second data structure for each documented communication with a weighted value for an author of a given documented communication that signifies a statistical preference for the data in the corresponding memory space of the first data structure; executing a mathematical function based on an aggregate of the data and the weighted value of the first and second data structures for each documented communication in order to compute the relevancy score for the documented communication; and displaying search results based at least in part upon a ranked listing of one or more author scores, wherein the weighted value for the author comprises a predefined value utilized to create the statistical preference for data in the corresponding memory space of the first data structure, the weighted value for the author being determined based on at least two of: a time of publication for the documented communication, a number of documented communications having the author, a prestige of the documented communication, and a number of authors for the documented communication. 7. The method of claim 1 , the displaying further comprising presenting the name of each author related to each listed author score and a hyperlink to each documented communication associated with the each author.

1. A computer-implemented method, comprising: initializing a pseudo-random number generator with an authentication inkblot seed; drawing one or more blots on an authentication inkblot generation canvas to generate an image resembling an inkblot and determining each blot parameter value as a function of one or more pseudo-random values generated by the pseudo-random number generator initialized with the authentication inkblot seed; displaying the authentication inkblot generation canvas on a graphical output device; receiving one or more alphanumeric characters from an input device in response to each displayed authentication inkblot; sending the one or more alphanumeric characters received in response to each displayed authentication inkblot to a security authority as authentication information; and authenticating a user based on a match between the displayed inkblot and the alphanumeric characters.

1. A computer-implemented method, comprising: initializing a pseudo-random number generator with an authentication inkblot seed; drawing one or more blots on an authentication inkblot generation canvas to generate an image resembling an inkblot and determining each blot parameter value as a function of one or more pseudo-random values generated by the pseudo-random number generator initialized with the authentication inkblot seed; displaying the authentication inkblot generation canvas on a graphical output device; receiving one or more alphanumeric characters from an input device in response to each displayed authentication inkblot; sending the one or more alphanumeric characters received in response to each displayed authentication inkblot to a security authority as authentication information; and authenticating a user based on a match between the displayed inkblot and the alphanumeric characters. 11. The method according to claim 1 , further comprising: receiving audio data from an input device in response to each displayed authentication inkblot; biometrically encoding the audio data; and sending the encoded audio data to a security authority as authentication information.

8. A digital forensic analysis method, comprising: extracting data from input data; detecting suspect data contained in said extracted data using a forensic search tool of a computing platform associated with a first entity, said detecting performed by matching said extracted data with one or more pre-defined data patterns specified by said forensic search tool, wherein said suspect data comprises data identified by said forensic search tool as being associated with inappropriate or illegal activities; including the suspect data and a non-readable and non-modifiable representation of sensitive data in the forensic search tool; outputting a report identifying said suspect data; and outputting said forensic search tool by said computing platform associated with said first entity to at least one computing platform associated with a second entity, wherein the said forensic search tool includes features portion containing features of data, a header, and a search markup language portion, wherein said forensic search tool enables said computing platform associated with said first entity to share said forensic search tool with said at least one computing platform associated with said second entity in a manner that enables utilization of the representation of sensitive data by the second entity while not revealing the actual content of the sensitive data to the second, and wherein said forensic search tool is implemented using said search markup language to permit sharing of said forensic search tool by said computing platform associated with the first entity with said at least one computing platform associated with the second entity.

8. A digital forensic analysis method, comprising: extracting data from input data; detecting suspect data contained in said extracted data using a forensic search tool of a computing platform associated with a first entity, said detecting performed by matching said extracted data with one or more pre-defined data patterns specified by said forensic search tool, wherein said suspect data comprises data identified by said forensic search tool as being associated with inappropriate or illegal activities; including the suspect data and a non-readable and non-modifiable representation of sensitive data in the forensic search tool; outputting a report identifying said suspect data; and outputting said forensic search tool by said computing platform associated with said first entity to at least one computing platform associated with a second entity, wherein the said forensic search tool includes features portion containing features of data, a header, and a search markup language portion, wherein said forensic search tool enables said computing platform associated with said first entity to share said forensic search tool with said at least one computing platform associated with said second entity in a manner that enables utilization of the representation of sensitive data by the second entity while not revealing the actual content of the sensitive data to the second, and wherein said forensic search tool is implemented using said search markup language to permit sharing of said forensic search tool by said computing platform associated with the first entity with said at least one computing platform associated with the second entity. 9. The digital forensic analysis method of claim 8 , further comprising: representing sensitive data using a digital fingerprint to prevent disclosure of said sensitive data to said at least one computing platform associated with a second entity.

15. A method comprising: generating a wiki-type application model, the wiki-type application model being accessible or modifiable by one or more users; using the wiki-type application model to employ one or more features including data suggestion; and modifying the wiki-type application model based upon a context of a user.

15. A method comprising: generating a wiki-type application model, the wiki-type application model being accessible or modifiable by one or more users; using the wiki-type application model to employ one or more features including data suggestion; and modifying the wiki-type application model based upon a context of a user. 16. The method of claim 15 , further comprising storing the wiki-type application model with another wiki-type application model in an Internet-accessible environment.

5. The device of claim 1 being further configured to: apply a text prediction algorithm on the updated sequence of input strokes to predict one or more candidates; and transmit a signal representing the one or more candidates to be provided for selection in a candidate list.

5. The device of claim 1 being further configured to: apply a text prediction algorithm on the updated sequence of input strokes to predict one or more candidates; and transmit a signal representing the one or more candidates to be provided for selection in a candidate list. 7. The device of claim 5 , wherein the device is further configured to determine the probability of each candidate based on preceding context, and wherein the one or more candidates are ordered in the candidate list based on the respective determined probability of each candidate.

1. An annotation method for a three-dimensional model, the method comprising: storing in a computer memory a first set of data representative of the three-dimensional model; storing in the computer memory a second set of data representative of an annotation associated with a first spatial location on the three-dimensional model and a first display view; displaying the three-dimensional model and a first graphical representation of the annotation in a display window according to the first display view, the first graphical representation of the annotation being positioned as specified by the first spatial location associated with the annotation; modifying the displaying of the three-dimensional model in the display window to a second display view different from the first display view; removing, in response to modifying the displaying to the second display view, the first graphical representation of the annotation from the display window; and displaying, in the display window in response to modifying the displaying to the second display view and as a substitute for the removed first graphical representation of the annotation, an annotation indicator representative of the annotation, the annotation indicator being visible on the display window independent of any display view of the three-dimensional model.

1. An annotation method for a three-dimensional model, the method comprising: storing in a computer memory a first set of data representative of the three-dimensional model; storing in the computer memory a second set of data representative of an annotation associated with a first spatial location on the three-dimensional model and a first display view; displaying the three-dimensional model and a first graphical representation of the annotation in a display window according to the first display view, the first graphical representation of the annotation being positioned as specified by the first spatial location associated with the annotation; modifying the displaying of the three-dimensional model in the display window to a second display view different from the first display view; removing, in response to modifying the displaying to the second display view, the first graphical representation of the annotation from the display window; and displaying, in the display window in response to modifying the displaying to the second display view and as a substitute for the removed first graphical representation of the annotation, an annotation indicator representative of the annotation, the annotation indicator being visible on the display window independent of any display view of the three-dimensional model. 13. The method of claim 1 , wherein the first spatial location of the annotation is defined by a plurality of coordinate values.

7. A software application lifecycle management platform computing device, comprising at least one processor and a memory coupled to the processor which is configured to execute programmed instructions comprising and stored in the memory to: obtain software application related data and one or more outcomes of prior corresponding software application deliveries from at least one of a knowledge repository or a learning repository based on the software application related data; generate a set of models based on the outcomes of the prior corresponding software application deliveries wherein the generating further comprises deriving a confidence level for each of the set of models, generating a search query based on the software application related data, and searching the knowledge repository for the outcomes of the prior corresponding software application deliveries based on the search query, wherein the searching is executed against the learning repository when there is no match in the knowledge repository; and output one or more options for selection based on the set of models along with the corresponding confidence level.

7. A software application lifecycle management platform computing device, comprising at least one processor and a memory coupled to the processor which is configured to execute programmed instructions comprising and stored in the memory to: obtain software application related data and one or more outcomes of prior corresponding software application deliveries from at least one of a knowledge repository or a learning repository based on the software application related data; generate a set of models based on the outcomes of the prior corresponding software application deliveries wherein the generating further comprises deriving a confidence level for each of the set of models, generating a search query based on the software application related data, and searching the knowledge repository for the outcomes of the prior corresponding software application deliveries based on the search query, wherein the searching is executed against the learning repository when there is no match in the knowledge repository; and output one or more options for selection based on the set of models along with the corresponding confidence level. 12. The software application lifecycle management platform computing device of claim 7 , wherein the processor coupled to the memory is further configured to execute at least one additional programmed instruction to update at least one of the knowledge repository or the learning repository based on intelligence generated from a selection of one or more of the options.

1. A method for restricting access to digital video content based on recognition of a TV station logo embedded within the video content that varies according to the video usage rights, the method comprising: extracting the TV station logo from the video content by combining several frames of video content; identifying the TV station logo by comparing the TV station logo to known TV station logos that most closely matches said TV station logo extracted from the video content, where the known TV station logos are associated with user profiles of copyright rights holders, and wherein at least some of the known TV station logos are supplied by rights holders for content analysis to identify their owned content; estimating a first match probability of the likely copyright rights holder based on the identified TV station logo; identifying a second media object within at least one frame of the video content different from the TV station logo; extracting at least a second semantic property from the second specified media object within at least one frame of the video content; matching said at least second semantic property of the second specified media object against the known semantic properties of known media objects associated with user profiles of copyright rights holders; comparing matches between said at least second semantic property and the known semantic properties to a second threshold value; estimating a second match probability of the likely copyright rights holder based on the second compared matches; combining the first match probability and the second match probability into a combined match probability; identifying a copyright rights holder based on at least the combined match probability; retrieving rules governing distribution rights of the content based at least on identification of the copyright rights holder; and restricting access to the digital video content in accordance with the retrieved rules.

1. A method for restricting access to digital video content based on recognition of a TV station logo embedded within the video content that varies according to the video usage rights, the method comprising: extracting the TV station logo from the video content by combining several frames of video content; identifying the TV station logo by comparing the TV station logo to known TV station logos that most closely matches said TV station logo extracted from the video content, where the known TV station logos are associated with user profiles of copyright rights holders, and wherein at least some of the known TV station logos are supplied by rights holders for content analysis to identify their owned content; estimating a first match probability of the likely copyright rights holder based on the identified TV station logo; identifying a second media object within at least one frame of the video content different from the TV station logo; extracting at least a second semantic property from the second specified media object within at least one frame of the video content; matching said at least second semantic property of the second specified media object against the known semantic properties of known media objects associated with user profiles of copyright rights holders; comparing matches between said at least second semantic property and the known semantic properties to a second threshold value; estimating a second match probability of the likely copyright rights holder based on the second compared matches; combining the first match probability and the second match probability into a combined match probability; identifying a copyright rights holder based on at least the combined match probability; retrieving rules governing distribution rights of the content based at least on identification of the copyright rights holder; and restricting access to the digital video content in accordance with the retrieved rules. 3. The method of claim 1 , wherein said TV station logo is visibly embedded within the video content.

26. The computer readable medium of claim 24 , wherein the predetermined InitialObjectDescriptor template calls a predetermined Profiles template when InitialObjectDescriptor and Profiles are found by the parsing and calls a predetermined Descr template when Descr is found by the parsing.

26. The computer readable medium of claim 24 , wherein the predetermined InitialObjectDescriptor template calls a predetermined Profiles template when InitialObjectDescriptor and Profiles are found by the parsing and calls a predetermined Descr template when Descr is found by the parsing. 27. The computer readable medium of claim 26 , wherein the predetermined Descr template calls a predetermined esDescr template when Descr and esDescr are found by the parsing and call a predetermined ipmpDescr template when ipmpDescrPtr is found by the parsing.

31. The mobile terminal of claim 30 , wherein, the controller is further configured to enter a menu corresponding to the chosen menu icon when the chosen menu icon is chosen again.

31. The mobile terminal of claim 30 , wherein, the controller is further configured to enter a menu corresponding to the chosen menu icon when the chosen menu icon is chosen again. 32. The mobile terminal of claim 31 , wherein the controller is further configured to output a second control signal for controlling the haptic module to generate a haptic effect corresponding to the entered menu.

1. A system for providing semantic reasoning comprising: an extended semantic model of a specific knowledge domain comprising existing concepts, existing relationships among the existing concepts, and inference logic embedded within each existing concept, wherein each existing concept comprises associated properties and wherein the embedded inference logic is used for inferring values of said associated properties and comprises conditions and processes for drawings inferences about an existing downstream concept that is connected to an existing concept via an existing relationship; a semantic knowledge database being distinct from the extended semantic model and comprising existing nodes and existing links and wherein the existing nodes represent instances of the existing concepts, and the existing links represent instances of the existing relationships among the existing concepts; an inference engine configured to populate the semantic knowledge database with said instances of the existing concepts and said instances of the existing relationships by following the inference logic embedded within each existing concept, and wherein the inference engine adds new nodes and new links to the semantic knowledge database by first receiving external data, next generating instances of fact nodes and associated links representing said external data, and then recursively adding and updating downstream insight nodes and associated links; a computing system comprising at least a processor configured to execute the inference engine operating on the inference logic of the extended semantic model and to host the semantic knowledge database; wherein each existing node comprises existing notes representing instances of the associated properties of each existing concept; wherein the existing links that connect the existing nodes comprise directionality originating from an upstream node and terminating at a downstream node; and wherein the system further comprises a user interface configured to query the semantic knowledge database and to provide decision support to a user.

1. A system for providing semantic reasoning comprising: an extended semantic model of a specific knowledge domain comprising existing concepts, existing relationships among the existing concepts, and inference logic embedded within each existing concept, wherein each existing concept comprises associated properties and wherein the embedded inference logic is used for inferring values of said associated properties and comprises conditions and processes for drawings inferences about an existing downstream concept that is connected to an existing concept via an existing relationship; a semantic knowledge database being distinct from the extended semantic model and comprising existing nodes and existing links and wherein the existing nodes represent instances of the existing concepts, and the existing links represent instances of the existing relationships among the existing concepts; an inference engine configured to populate the semantic knowledge database with said instances of the existing concepts and said instances of the existing relationships by following the inference logic embedded within each existing concept, and wherein the inference engine adds new nodes and new links to the semantic knowledge database by first receiving external data, next generating instances of fact nodes and associated links representing said external data, and then recursively adding and updating downstream insight nodes and associated links; a computing system comprising at least a processor configured to execute the inference engine operating on the inference logic of the extended semantic model and to host the semantic knowledge database; wherein each existing node comprises existing notes representing instances of the associated properties of each existing concept; wherein the existing links that connect the existing nodes comprise directionality originating from an upstream node and terminating at a downstream node; and wherein the system further comprises a user interface configured to query the semantic knowledge database and to provide decision support to a user. 20. The system of claim 1 , wherein adding or updating of an insight node in the semantic knowledge database automatically triggers the inference logic to add or update all downstream insight nodes that can be linked to the insight node and wherein addition or update of downstream insight nodes are inferred from an upstream insight node using the inference logic embedded in an upstream concept whose instance is the triggering insight node.

13. Apparatus of claim 12 further including means for storing a plurality of tables of characters coded as bytes, each table having a portion of the characters addressable by a single nibble and a portion of the character addressable by two nibbles, the characters stored respectively in the two portions being different for each table, means for selecting one of the tables to operate with said means for comparing each byte with characters stored in a character table.

13. Apparatus of claim 12 further including means for storing a plurality of tables of characters coded as bytes, each table having a portion of the characters addressable by a single nibble and a portion of the character addressable by two nibbles, the characters stored respectively in the two portions being different for each table, means for selecting one of the tables to operate with said means for comparing each byte with characters stored in a character table. 14. Apparatus of claim 13 further including means responsive to the value of the byte in the stored group preceeding the byte being compared for selecting one of said plurality of character tables, each character having an associated table of characters arranged in the two portions of the table according to the frequency in which each character in the table follows the associated preceeding character in standard English words.

4. The method of claim 1 , wherein the automatically analyzing comprises analyzing a newly typed string of characters of the segment in real time in the context of the previously entered content of the segment.

4. The method of claim 1 , wherein the automatically analyzing comprises analyzing a newly typed string of characters of the segment in real time in the context of the previously entered content of the segment. 5. The method of claim 4 , wherein the automatically analyzing further comprises identifying a word in the string of characters, comparing the word with a predetermined list of words including synonyms, and making a decision based on a degree of match between the word and the predetermined list of words, how the word should be classified.

2. The method of claim 1 , wherein the translation likelihood factors comprise one or more of: characteristics of an author of the potential snippet; characteristics of content of the potential snippet; characteristics of an expected audience of the potential snippet; a measure of user engagement with the potential snippet thus far; an identification of when the potential snippet was created; an amount of time before a translation of the potential snippet is expected to be needed; a virtual location where the potential snippet is posted; or any combination thereof.

2. The method of claim 1 , wherein the translation likelihood factors comprise one or more of: characteristics of an author of the potential snippet; characteristics of content of the potential snippet; characteristics of an expected audience of the potential snippet; a measure of user engagement with the potential snippet thus far; an identification of when the potential snippet was created; an amount of time before a translation of the potential snippet is expected to be needed; a virtual location where the potential snippet is posted; or any combination thereof. 8. The method of claim 2 , wherein the translation likelihood factors comprise the amount of time before the translation of the potential snippet is expected to be needed, wherein the amount of time before the translation of the potential snippet is expected to be needed is determined based on a computation of when users who are determined likely to request a translation of the snippet are also determined likely to interact with a system that provides translations of the snippet.

17. The method of claim 12 wherein the optimizing is performed using a proximal step algorithm.

17. The method of claim 12 wherein the optimizing is performed using a proximal step algorithm. 18. The method of claim 17 wherein the optimizing is performed using a stochastic proximal step algorithm.

7. A method, comprising: using at least one computer to perform: assigning word-class information to words in a medical report, the assigning comprising: assigning first word-class information to a first word or word sequence in the medical report, wherein the first word or word sequence names a particular medicament; and assigning second word-class information to a second word or word sequence in the medical report; performing at least one action related to the particular medicament and associated with a combination of the first word-class information and the second word-class information, wherein assigning the word class information comprises: identifying a medicament word class as a word class of the first word or word sequence in the medical report; and identifying an allergy word class as a word class of the second word or word sequence in the medical report, wherein the second word or word sequence names an allergy of a patient toward an active agent.

7. A method, comprising: using at least one computer to perform: assigning word-class information to words in a medical report, the assigning comprising: assigning first word-class information to a first word or word sequence in the medical report, wherein the first word or word sequence names a particular medicament; and assigning second word-class information to a second word or word sequence in the medical report; performing at least one action related to the particular medicament and associated with a combination of the first word-class information and the second word-class information, wherein assigning the word class information comprises: identifying a medicament word class as a word class of the first word or word sequence in the medical report; and identifying an allergy word class as a word class of the second word or word sequence in the medical report, wherein the second word or word sequence names an allergy of a patient toward an active agent. 8. The method of claim 7 , wherein performing the at least one action comprises providing a warning that a patient is allergic to the particular medicament.

10. A method of calculating and applying indicia defining computed information to articles comprising: (a) sensing the weight of an article and generating first information signals indicative of the article's weight, (b) speaking selected speech into a microphone and generating electrical speech signals on the output of said microphone, (c) computer processing and analyzing said speech signals and generating first control signals, (d) applying said first information signals and said first control signals to a first electronic computing means and operating said first electronic computing means to perform predetermined electronic computing functions with respect to the information defined by said signals and generating second control signals, and (e) applying said second control signals to control the operation of an intelligible information indicating means to indicate the information defined by said second control signals.

10. A method of calculating and applying indicia defining computed information to articles comprising: (a) sensing the weight of an article and generating first information signals indicative of the article's weight, (b) speaking selected speech into a microphone and generating electrical speech signals on the output of said microphone, (c) computer processing and analyzing said speech signals and generating first control signals, (d) applying said first information signals and said first control signals to a first electronic computing means and operating said first electronic computing means to perform predetermined electronic computing functions with respect to the information defined by said signals and generating second control signals, and (e) applying said second control signals to control the operation of an intelligible information indicating means to indicate the information defined by said second control signals. 11. A method in accordance with claim 10 including operating said printing means to print indicia indicative of the weight of the article sensed.

10. A computer system comprising: one or more processors; a software program, executable on said computer system, the software program configured to cause an in-memory database engine to: access from an in-memory database, metadata associated with graph data of a graph database, the metadata identifying a plurality of nodes of a first node type, a plurality of nodes of a second node type, and a plurality of edges of a first edge type between the plurality of nodes of the first node type and the plurality of nodes of the second node type; formulate a query including the metadata; promulgate the query to the graph database; and receive from the graph database a query result responsive to the query, wherein the software program is further configured to cause the in-memory database engine to, convert the query result into a table, save the table in the in-memory database, display the query result in an overview visualization representing all nodes of the first node type as a first icon, all nodes of the second node type as a second icon, and edges of the first edge type as a single edge between the first icon and the second icon, and display the query result in a node level visualization rendering, each of the plurality of nodes of the first node type and each of the plurality nodes of the second node type as separate nodes; and each of the plurality of edges of the first edge type as separate edges.

10. A computer system comprising: one or more processors; a software program, executable on said computer system, the software program configured to cause an in-memory database engine to: access from an in-memory database, metadata associated with graph data of a graph database, the metadata identifying a plurality of nodes of a first node type, a plurality of nodes of a second node type, and a plurality of edges of a first edge type between the plurality of nodes of the first node type and the plurality of nodes of the second node type; formulate a query including the metadata; promulgate the query to the graph database; and receive from the graph database a query result responsive to the query, wherein the software program is further configured to cause the in-memory database engine to, convert the query result into a table, save the table in the in-memory database, display the query result in an overview visualization representing all nodes of the first node type as a first icon, all nodes of the second node type as a second icon, and edges of the first edge type as a single edge between the first icon and the second icon, and display the query result in a node level visualization rendering, each of the plurality of nodes of the first node type and each of the plurality nodes of the second node type as separate nodes; and each of the plurality of edges of the first edge type as separate edges. 11. The computer system as in claim 10 wherein the software program is configured to cause in-memory database engine to convert the query result into the table in response to an input specifying a plurality of edge types and a plurality of node types displayed in the overview visualization.

10. A system for converting taxiway voice commands into taxiway textual commands, the system comprising: a radio receiver, the radio receiver configured to receive the taxiway voice commands from an air traffic control center; a taxiway command database, the taxiway command database including a plurality of common air traffic control center taxiway commands; a voice recognition processor, the voice recognition processor coupled to the radio receiver and the taxiway command database, the voice recognition processor configured to receive the taxiway voice commands, the voice recognition processor further configured to compare the taxiway voice commands to the plurality of common air traffic control center taxiway commands and to convert the taxiway voice commands into the taxiway textual commands based on the comparison, determine an uncertainty associated with an accuracy of the converted taxiway textual commands based on the conversion of the taxiway voice commands, and determine an alternative taxiway textual command corresponding to each unconverted taxiway voice command based on the uncertainty; and a taxiway clearance display coupled to the voice recognition processor, the taxiway clearance display configured to receive and display the taxiway textual commands, the alternative taxiway textual commands when determined by the voice recognition processor, and an indication of the uncertainty.

10. A system for converting taxiway voice commands into taxiway textual commands, the system comprising: a radio receiver, the radio receiver configured to receive the taxiway voice commands from an air traffic control center; a taxiway command database, the taxiway command database including a plurality of common air traffic control center taxiway commands; a voice recognition processor, the voice recognition processor coupled to the radio receiver and the taxiway command database, the voice recognition processor configured to receive the taxiway voice commands, the voice recognition processor further configured to compare the taxiway voice commands to the plurality of common air traffic control center taxiway commands and to convert the taxiway voice commands into the taxiway textual commands based on the comparison, determine an uncertainty associated with an accuracy of the converted taxiway textual commands based on the conversion of the taxiway voice commands, and determine an alternative taxiway textual command corresponding to each unconverted taxiway voice command based on the uncertainty; and a taxiway clearance display coupled to the voice recognition processor, the taxiway clearance display configured to receive and display the taxiway textual commands, the alternative taxiway textual commands when determined by the voice recognition processor, and an indication of the uncertainty. 11. The system of claim 10 , wherein the taxiway command database includes sounds associated with each of the plurality of common air traffic control center taxiway commands.

12. A non-transitory machine-readable storage medium embodying instructions that, when executed by a machine, cause the machine to perform operations comprising: executing an electronic signature service (ESS) on a web server, the electronic signature service stored as an executable module on one or more memory devices of the machine, the executable module when executed performing operations including: identifying one or more documents associated with a document owner, the one or more documents including a document that comprises content including terms for an agreement between a plurality of users, the plurality of users including at least a signing user, the document being an individual file; receiving a request from a client device associated with the document owner via an application programming interface (API) over a network to pre-tag the document to indicate a location for signature and a signing role for the signing user; in response to receiving an instruction to link the document to a transaction room for signing, creating a non-editable copy of the document for signing on a storage device accessible to the transaction room for the agreement, the non-editable copy being an additional individual file in a non-editable format, the transaction room implemented as a web service accessible by the plurality of users remotely over the network, the non-editable copy of the document for signing viewable by the plurality of users remotely through a graphical user interface of the transaction room, the content of the non-editable copy of the document for signing not being editable by the plurality of users remotely through the graphical user interface of the transaction room; associating the signing user with the signing role; in response to receiving an instruction to transmit the document for signing to at least the signing user, tagging the non-editable copy of the document for signing with one or more tags based on the pre-tag to display data identifying the location for signature for the signing user to sign; and in response to receiving, from the signing user, input information for the document for signing, overlaying the input information on the non-editable copy of the document for signing without altering the terms for the agreement in the non-editable copy of the document for signing.

12. A non-transitory machine-readable storage medium embodying instructions that, when executed by a machine, cause the machine to perform operations comprising: executing an electronic signature service (ESS) on a web server, the electronic signature service stored as an executable module on one or more memory devices of the machine, the executable module when executed performing operations including: identifying one or more documents associated with a document owner, the one or more documents including a document that comprises content including terms for an agreement between a plurality of users, the plurality of users including at least a signing user, the document being an individual file; receiving a request from a client device associated with the document owner via an application programming interface (API) over a network to pre-tag the document to indicate a location for signature and a signing role for the signing user; in response to receiving an instruction to link the document to a transaction room for signing, creating a non-editable copy of the document for signing on a storage device accessible to the transaction room for the agreement, the non-editable copy being an additional individual file in a non-editable format, the transaction room implemented as a web service accessible by the plurality of users remotely over the network, the non-editable copy of the document for signing viewable by the plurality of users remotely through a graphical user interface of the transaction room, the content of the non-editable copy of the document for signing not being editable by the plurality of users remotely through the graphical user interface of the transaction room; associating the signing user with the signing role; in response to receiving an instruction to transmit the document for signing to at least the signing user, tagging the non-editable copy of the document for signing with one or more tags based on the pre-tag to display data identifying the location for signature for the signing user to sign; and in response to receiving, from the signing user, input information for the document for signing, overlaying the input information on the non-editable copy of the document for signing without altering the terms for the agreement in the non-editable copy of the document for signing. 14. The medium of claim 12 , wherein the operations further comprise: in response to receiving additional input information for an additional user of the plurality of users, creating an additional non-editable copy of the document for signing that captures the input information and the additional input information, the additional non-editable copy of the document for signing being different than the non-editable copy of the document for signing; and providing the additional non-editable copy of the document for signing including the input information and the additional input information to at least one of the plurality of users for review through the transaction room.

1. A system comprising: a data processing apparatus; and a non-transitory computer storage medium encoded with a computer program, the program comprising data processing apparatus instructions that when executed by the data processing apparatus cause the data processing apparatus to perform operations comprising: receiving an original query from a user device, the query including a plurality of terms; determining that a term of the original query meets an inaccuracy criterion that is indicative of the term of the original query being a potentially inaccurate term in a context of the original query that is defined by the original query terms, wherein the determination is based at least in part on determining that a resource quality measure that is a measure of quality of resources identified as being responsive to the original query does not meet a resource quality measure threshold, and in response: identifying the term as a potentially inaccurate term; generating one or more derivative queries from the original query, each derivative query not including the potentially inaccurate term; for each of the one or more derivative queries, submitting the derivative query for a search of a resource corpus index of resources and receiving data identifying a respective set of resources that are determined to be responsive to the derivative query, wherein each resource is a web page resource hosted by a server and having a corresponding resource address; determining a corrected term based on the identified resources responsive to each of the one or more derivative queries, wherein the corrected term is determined based on respective sets of resources that are determined to be responsive to the one or more derivative queries and further determined independent of a set of resources identified as being responsive to the original query, and wherein the corrected term is a term that is different from the potentially inaccurate term; generating a corrected query that includes the terms of the original query that are not the potentially inaccurate term and that includes the corrected term substituted for the potentially inaccurate term; performing a search operation that uses the corrected query as input; and providing results of the search operation to the user device in response to the original query.

1. A system comprising: a data processing apparatus; and a non-transitory computer storage medium encoded with a computer program, the program comprising data processing apparatus instructions that when executed by the data processing apparatus cause the data processing apparatus to perform operations comprising: receiving an original query from a user device, the query including a plurality of terms; determining that a term of the original query meets an inaccuracy criterion that is indicative of the term of the original query being a potentially inaccurate term in a context of the original query that is defined by the original query terms, wherein the determination is based at least in part on determining that a resource quality measure that is a measure of quality of resources identified as being responsive to the original query does not meet a resource quality measure threshold, and in response: identifying the term as a potentially inaccurate term; generating one or more derivative queries from the original query, each derivative query not including the potentially inaccurate term; for each of the one or more derivative queries, submitting the derivative query for a search of a resource corpus index of resources and receiving data identifying a respective set of resources that are determined to be responsive to the derivative query, wherein each resource is a web page resource hosted by a server and having a corresponding resource address; determining a corrected term based on the identified resources responsive to each of the one or more derivative queries, wherein the corrected term is determined based on respective sets of resources that are determined to be responsive to the one or more derivative queries and further determined independent of a set of resources identified as being responsive to the original query, and wherein the corrected term is a term that is different from the potentially inaccurate term; generating a corrected query that includes the terms of the original query that are not the potentially inaccurate term and that includes the corrected term substituted for the potentially inaccurate term; performing a search operation that uses the corrected query as input; and providing results of the search operation to the user device in response to the original query. 12. The system of claim 1 , wherein: performing a search operation that uses the corrected query as input comprises submitting the corrected query for a search of the resource corpus and receiving search results identifying resources that are determined to be responsive to the corrected query; and providing results of the search operation to the user device in response to the original query comprises provide a proper subset of the search results identifying resources that are determined to be responsive to the corrected query with search results identifying resources that are determined to be responsive to the original query.

6. A method comprising: causing a virtual assistant to carry out a conversation with a user, wherein the virtual assistant is configured with instructions stored in computerized memory to access features of a knowledge base stored in a computer readable media, the features organized to trigger outputs according to units of vocabulary patterns arranged in the features, wherein the vocabulary patterns are stored in the memory with respective labels and the instructions implement the following steps: receiving a speech input string via the virtual assistant during the conversation; substituting portions of the speech input string with sets of terms bearing corresponding labels that refer back to the respective labels of the knowledge base; converting the speech input string to converted data comprising the sets of terms; matching the respective labels and the corresponding labels to identify a digital response to the speech input; causing the digital response to be presented to the user in real-time via the virtual assistant; and causing a task to be performed at least in part by the virtual assistant.

6. A method comprising: causing a virtual assistant to carry out a conversation with a user, wherein the virtual assistant is configured with instructions stored in computerized memory to access features of a knowledge base stored in a computer readable media, the features organized to trigger outputs according to units of vocabulary patterns arranged in the features, wherein the vocabulary patterns are stored in the memory with respective labels and the instructions implement the following steps: receiving a speech input string via the virtual assistant during the conversation; substituting portions of the speech input string with sets of terms bearing corresponding labels that refer back to the respective labels of the knowledge base; converting the speech input string to converted data comprising the sets of terms; matching the respective labels and the corresponding labels to identify a digital response to the speech input; causing the digital response to be presented to the user in real-time via the virtual assistant; and causing a task to be performed at least in part by the virtual assistant. 9. The method of claim 6 , wherein the task comprises at least one of: outputting content to the user; causing an action be performed by an application that is external to the system; or providing access to a web page.

1. A method comprising, by one or more computing systems: receiving, from a plurality of client systems of a plurality of users, a plurality of search queries, each search query comprising one or more n-grams; identifying a subset of search queries from the plurality of search queries as being queries for visual-media items, each of the search queries in the subset of search queries being identified based on one or more n-grams of the search query being associated with visual-media content; calculating, for each of the n-grams of the search queries of the subset of search queries, a popularity-score based on a count of the search queries in the subset of search queries that include the n-gram, wherein, for each of one or more of the n-grams of the search queries of the subset of search queries, the count of the search queries including the n-gram is a weighted count that weights an occurrence of each search query based on a degree of confidence with which the search query is identified as being a query for visual-media items; determining one or more popular n-grams, wherein each of the popular n-grams is an n-gram of the search queries of the subset of search queries having a popularity-score greater than a threshold popularity-score; and selecting one or more of the popular n-grams for training a visual-concept recognition system, wherein each of the popular n-grams is selected based on whether it is associated with one or more visual concepts.

1. A method comprising, by one or more computing systems: receiving, from a plurality of client systems of a plurality of users, a plurality of search queries, each search query comprising one or more n-grams; identifying a subset of search queries from the plurality of search queries as being queries for visual-media items, each of the search queries in the subset of search queries being identified based on one or more n-grams of the search query being associated with visual-media content; calculating, for each of the n-grams of the search queries of the subset of search queries, a popularity-score based on a count of the search queries in the subset of search queries that include the n-gram, wherein, for each of one or more of the n-grams of the search queries of the subset of search queries, the count of the search queries including the n-gram is a weighted count that weights an occurrence of each search query based on a degree of confidence with which the search query is identified as being a query for visual-media items; determining one or more popular n-grams, wherein each of the popular n-grams is an n-gram of the search queries of the subset of search queries having a popularity-score greater than a threshold popularity-score; and selecting one or more of the popular n-grams for training a visual-concept recognition system, wherein each of the popular n-grams is selected based on whether it is associated with one or more visual concepts. 4. The method of claim 1 , wherein each of one or more of the search queries in the subset of search queries is further identified based on a number of times that prior searches including one or more n-grams of the search query resulted in a user requesting to access a visual-media item.

5. The method of claim 4 wherein the training includes for each category, generating an average of the core tensors of documents within that category.

5. The method of claim 4 wherein the training includes for each category, generating an average of the core tensors of documents within that category. 6. The method of claim 5 wherein the applying of the classifier to the generated core tensor for the document includes selecting as the category for the document the category whose average core tensor is most similar to the generated core tensor for the document.

5. The method of claim 1 , wherein said determining said relationship between said first and second numerical values further comprises: subtracting at least a portion of said first binary string from at least a portion of said second binary string; and determining said relationship based, at least in part, on a result of said subtraction.

5. The method of claim 1 , wherein said determining said relationship between said first and second numerical values further comprises: subtracting at least a portion of said first binary string from at least a portion of said second binary string; and determining said relationship based, at least in part, on a result of said subtraction. 7. The method of claim 5 , wherein said result of said subtraction comprises a sign bit.

1. A system for using a computer to improve a precision ratio when searching a resume database, comprising: a memory device resident in the computer; and a processor disposed in communication with the memory device, the processor configured to: receive a resume; parse the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; store the resume in the resume database; create a parsed resume based on the resume, the parsed resume including each said at least one skill or experience-related phrase located in the resume, the term of experience computed for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase; store the parsed resume in the resume database; send a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and receive a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description.

1. A system for using a computer to improve a precision ratio when searching a resume database, comprising: a memory device resident in the computer; and a processor disposed in communication with the memory device, the processor configured to: receive a resume; parse the resume to: locate at least one skill or experience-related phrase in the resume; determine an experience range for each said at least one skill or experience-related phrase by examining a use of each said at least one skill or experience-related phrase in the resume; and compute a term of experience for each said at least one skill or experience-related phrase based on the experience range, wherein the term of experience for each said at least one skill or experience-related phrase is a summation of the term of experience for each occurrence of the phrase associated with a different experience range; store the resume in the resume database; create a parsed resume based on the resume, the parsed resume including each said at least one skill or experience-related phrase located in the resume, the term of experience computed for each said at least one skill or experience-related phrase, and a relationship between the term of experience and each said at least one skill or experience-related phrase; store the parsed resume in the resume database; send a database query to the resume database, the database query including a job description that includes at least one job requirement, each said at least one job requirement including a required skill or experience-related phrase, and a required term of experience; and receive a result set in response to the database query, wherein the result set includes the resume when the parsed resume satisfies the job description. 32. The system of claim 1 , wherein the processor is further configured to: send a portion of the parsed resume to a candidate.

8. A system comprising: a machine-readable storage device including a program product; and one or more processors operable to execute the program product and perform operations comprising: obtaining a submitted search query, and in response to obtaining the search query: obtaining search results responsive to the search query; selecting a document from a group of documents identified by the search results; generating, from each entity text string in a subset of one or more entity text strings associated with the document one or more candidates for refined search queries, including: identifying three or more terms in the search query that each have a respective term score satisfying a term threshold, where the three or more terms occur in the search query in a particular order relative to each other and combining the three or more terms with the entity text string to generate a candidate, where the three or more terms occur in the candidate in the particular order relative to each other; and identifying one or more of the candidates as being refined search queries to be provided with the search results in response to the search query.

8. A system comprising: a machine-readable storage device including a program product; and one or more processors operable to execute the program product and perform operations comprising: obtaining a submitted search query, and in response to obtaining the search query: obtaining search results responsive to the search query; selecting a document from a group of documents identified by the search results; generating, from each entity text string in a subset of one or more entity text strings associated with the document one or more candidates for refined search queries, including: identifying three or more terms in the search query that each have a respective term score satisfying a term threshold, where the three or more terms occur in the search query in a particular order relative to each other and combining the three or more terms with the entity text string to generate a candidate, where the three or more terms occur in the candidate in the particular order relative to each other; and identifying one or more of the candidates as being refined search queries to be provided with the search results in response to the search query. 10. The system of claim 8 , where the documents are each associated with a ranking, and selecting the document includes selecting a document with a ranking beyond a threshold ranking.

8. The method of claim 6 , wherein the where clause includes an assertion that constrains a type of data item acceptable as an element.

8. The method of claim 6 , wherein the where clause includes an assertion that constrains a type of data item acceptable as an element. 9. The method of claim 8 , wherein the assertion refers to a class description in an ontology.

11. An operating method for a computer comprising steps for: (a) storing a document written in hypertext markup language (HTML), said HTML document including an applet tag for invoking a Universal Client device. (b) storing computer readable first instructions for generating said Universal Client device; (c) storing computer readable second instructions for permitting said computer to utilize a virtual machine; and (d) executing said Universal Client device on said computer using said virtual machine to thereby generate predetermined graphical user interface (GUI) objects and display said GUI objects on said computer responsible to a GUIScript.

11. An operating method for a computer comprising steps for: (a) storing a document written in hypertext markup language (HTML), said HTML document including an applet tag for invoking a Universal Client device. (b) storing computer readable first instructions for generating said Universal Client device; (c) storing computer readable second instructions for permitting said computer to utilize a virtual machine; and (d) executing said Universal Client device on said computer using said virtual machine to thereby generate predetermined graphical user interface (GUI) objects and display said GUI objects on said computer responsible to a GUIScript. 15. The operating method for the computer as recited in claim 11, wherein one of said predetermined GUI objects comprises a MultiMedia presentation.

16. A method of generating a document migration report identifying those documents in a group of documents that may be candidates for use in at least one of a plurality of migration categories, comprising the steps of: providing migration data metrics, said migration data metrics including a range of characteristic document data for each of a plurality of characteristics for at least one of a plurality of migration categories; for each document in a group of documents, assigning characteristic document data for each of said plurality of characteristics; comparing characteristic document data for each document in said group of documents to said migration data metrics to determine which of those documents having characteristic document data that fall within a range specified by said migration data metrics for said one of the plurality of migration categories; saving the identities of those documents having characteristic document data that fall within the ranges specified by said migration data metrics for said one of said plurality of migration categories; and generating a migration report listing the identities of those documents having characteristic document data that fall within the ranges specified by said migration data metrics for said one of said plurality of migration categories.

16. A method of generating a document migration report identifying those documents in a group of documents that may be candidates for use in at least one of a plurality of migration categories, comprising the steps of: providing migration data metrics, said migration data metrics including a range of characteristic document data for each of a plurality of characteristics for at least one of a plurality of migration categories; for each document in a group of documents, assigning characteristic document data for each of said plurality of characteristics; comparing characteristic document data for each document in said group of documents to said migration data metrics to determine which of those documents having characteristic document data that fall within a range specified by said migration data metrics for said one of the plurality of migration categories; saving the identities of those documents having characteristic document data that fall within the ranges specified by said migration data metrics for said one of said plurality of migration categories; and generating a migration report listing the identities of those documents having characteristic document data that fall within the ranges specified by said migration data metrics for said one of said plurality of migration categories. 19. The method of claim 16 in which said step of providing migration data metrics includes the step of providing a range of data with respect to document construction.

2. The computer-implemented method of claim 1 , wherein a particular combined confidence value from the one or more combined confidence values i) corresponds to a particular recognition result from the recognition results and ii) comprises a combination of two or more of the confidence values that correspond to the particular recognition result.

2. The computer-implemented method of claim 1 , wherein a particular combined confidence value from the one or more combined confidence values i) corresponds to a particular recognition result from the recognition results and ii) comprises a combination of two or more of the confidence values that correspond to the particular recognition result. 4. The computer-implemented method of claim 2 , further comprising: weighting the combination of the two or more of the confidence values based on a frequency with which the particular recognition result occurs in the recognition results for the completed portion of the plurality of speech recognition tasks.

15. The method for refining the results of a search, the search results comprising a representation of a selected plurality of reference documents, such reference documents displayed being of relevance to an input text portion comprising one or more search terms, the selected plurality of reference documents comprising a subset of a plurality of documents in a database, the method comprising the steps of: a) using a processor to form a local term index from the search terms in the input text portion, the local term index comprising one or more text terms, each local text term associated with a local text term weight; b) using the processor, receiving and displaying the search results on a user interface, the user interface comprising input means for receiving user input with respect to one or more of the plurality of the displayed reference documents; c) accepting user input on one or more of the displayed reference documents; d) using the processor, re-forming the local term index on the basis of the user input; e) on the basis of the re-formed input local term index, using the processor to query the database to identify one or more documents of enhanced relevance to the input text portion; and f) outputting a representation of the further identified reference documents of enhanced relevance to the user interface for presentation to a user; wherein, the processor comprises a programmable data processing apparatus comprising instructions which execute via the processor to implement the steps (a) to (f); wherein in step a) the local text term weights for each of the local text terms are derived from a global text term index, the global text term index comprising a plurality of text terms associated with global text term weights, wherein the global text term weights are derived from text term analysis of a plurality of documents.

15. The method for refining the results of a search, the search results comprising a representation of a selected plurality of reference documents, such reference documents displayed being of relevance to an input text portion comprising one or more search terms, the selected plurality of reference documents comprising a subset of a plurality of documents in a database, the method comprising the steps of: a) using a processor to form a local term index from the search terms in the input text portion, the local term index comprising one or more text terms, each local text term associated with a local text term weight; b) using the processor, receiving and displaying the search results on a user interface, the user interface comprising input means for receiving user input with respect to one or more of the plurality of the displayed reference documents; c) accepting user input on one or more of the displayed reference documents; d) using the processor, re-forming the local term index on the basis of the user input; e) on the basis of the re-formed input local term index, using the processor to query the database to identify one or more documents of enhanced relevance to the input text portion; and f) outputting a representation of the further identified reference documents of enhanced relevance to the user interface for presentation to a user; wherein, the processor comprises a programmable data processing apparatus comprising instructions which execute via the processor to implement the steps (a) to (f); wherein in step a) the local text term weights for each of the local text terms are derived from a global text term index, the global text term index comprising a plurality of text terms associated with global text term weights, wherein the global text term weights are derived from text term analysis of a plurality of documents. 17. The method as claimed in claim 15 wherein in step a) the local text term weights for each of the local text terms are equal.

1. In an information retrieval system, a computer-implemented method for information processing, comprising: accessing, by a computer system, a set of documents obtained from the information retrieval system; establishing, automatically by the computer system, at least one identifying characteristic within the set of documents; analyzing, by the computer system, the set of documents to obtain a statistical distribution based on values associated with the set of documents, the set of documents having a given size; computing a value of a function that measures distinctiveness of the obtained statistical distribution relative to a baseline statistical distribution of values associated with a baseline set of documents; normalizing the value relative to a distribution of values of the function that measures distinctiveness over a space of document sets, wherein a respective value of the function that measures distinctiveness corresponds to a respective document set within the space of document sets, wherein each document set in the space has a size that is comparable to the given size, and the act of normalizing the value includes an act of performing a computation on the value that accounts for the given size of the set of documents; and outputting a response derived from the normalized value.

1. In an information retrieval system, a computer-implemented method for information processing, comprising: accessing, by a computer system, a set of documents obtained from the information retrieval system; establishing, automatically by the computer system, at least one identifying characteristic within the set of documents; analyzing, by the computer system, the set of documents to obtain a statistical distribution based on values associated with the set of documents, the set of documents having a given size; computing a value of a function that measures distinctiveness of the obtained statistical distribution relative to a baseline statistical distribution of values associated with a baseline set of documents; normalizing the value relative to a distribution of values of the function that measures distinctiveness over a space of document sets, wherein a respective value of the function that measures distinctiveness corresponds to a respective document set within the space of document sets, wherein each document set in the space has a size that is comparable to the given size, and the act of normalizing the value includes an act of performing a computation on the value that accounts for the given size of the set of documents; and outputting a response derived from the normalized value. 10. The method according to claim 1 , wherein the at least one identifying characteristic comprises at least one of at least a portion of: textual information within a document; metadata associated with a document; contextual information associated with a document; non-textual information associated with a document; record information with a database; information associated with a composite entity; and information derivable from a document.

1. A method of operating a computer to perform linguistic analysis, comprising the steps of: splitting an input text into words and sentences; for each sentence, comparing phrases in each sentence with known phrases stored in a database, as follows: for each word in the sentence, comparing a value thereof and values of the words following it with values of words of stored phrases; in the event a match is found between the value of at least two consecutive words and the value of words of a stored phrase, labelling the matched at least two consecutive words with an overphrase that describes the matched value; after a penultimate word has been compared, recasting the sentence by replacing the matched phrases by respective overphrases; and then repeating the step of comparing phrases with the recast sentence until there is no further recasting by the step of using the overphrase in the comparison as a word until there is no further match found.

1. A method of operating a computer to perform linguistic analysis, comprising the steps of: splitting an input text into words and sentences; for each sentence, comparing phrases in each sentence with known phrases stored in a database, as follows: for each word in the sentence, comparing a value thereof and values of the words following it with values of words of stored phrases; in the event a match is found between the value of at least two consecutive words and the value of words of a stored phrase, labelling the matched at least two consecutive words with an overphrase that describes the matched value; after a penultimate word has been compared, recasting the sentence by replacing the matched phrases by respective overphrases; and then repeating the step of comparing phrases with the recast sentence until there is no further recasting by the step of using the overphrase in the comparison as a word until there is no further match found. 3. A method according to claim 1 , wherein the value used in the step of comparing phrases corresponds to a grammatical use of the words.

5. The method of claim 1 , wherein said generating the search assistance list that includes the selected web address comprises: configuring the search assistance list such that the selected web address is configured to be listed first in a display of the search assistance list to the user.

5. The method of claim 1 , wherein said generating the search assistance list that includes the selected web address comprises: configuring the search assistance list such that the selected web address is configured to be listed first in a display of the search assistance list to the user. 6. The method of claim 5 , wherein said enabling comprises: transmitting the search assistance list to a computer of the user.

1. A method for compressing a grammar, the method comprising: receiving a grammar by using a computer, the grammar comprising a set of rules, each rule comprising a set of token classes, wherein a token class is a logical grouping of tokens, and a token is a string of one or more characters; parsing the grammar to identify the set of rules within the grammar and the set of token classes within each rule; identifying, from the set of token classes within each rule, a set of unimportant token classes separate from a set of important token classes, where the set of unimportant token classes are eligible for compression; analyzing the set of unimportant token classes to identify duplicates within the set of unimportant token classes; merging the set of unimportant token classes to generate a merged token class by removing duplicates within the set of unimportant token classes; and substituting the merged token class in the grammar for the set of unimportant token classes to generate a compressed grammar, wherein substituting the merged token class in the grammar for the set of unimportant token classes that were merged to generate the merged token class comprises substituting the merged token class for all instances within the grammar of the set of unimportant token classes that were merged to generate the merged token class.

1. A method for compressing a grammar, the method comprising: receiving a grammar by using a computer, the grammar comprising a set of rules, each rule comprising a set of token classes, wherein a token class is a logical grouping of tokens, and a token is a string of one or more characters; parsing the grammar to identify the set of rules within the grammar and the set of token classes within each rule; identifying, from the set of token classes within each rule, a set of unimportant token classes separate from a set of important token classes, where the set of unimportant token classes are eligible for compression; analyzing the set of unimportant token classes to identify duplicates within the set of unimportant token classes; merging the set of unimportant token classes to generate a merged token class by removing duplicates within the set of unimportant token classes; and substituting the merged token class in the grammar for the set of unimportant token classes to generate a compressed grammar, wherein substituting the merged token class in the grammar for the set of unimportant token classes that were merged to generate the merged token class comprises substituting the merged token class for all instances within the grammar of the set of unimportant token classes that were merged to generate the merged token class. 7. The method of claim 1 , wherein merging the two or more unimportant token classes from the candidate subset to generate a merged token class comprises generating a duplicate-free union of tokens included in each of the two or more unimportant token classes from the candidate subset.

6. The method of claim 1 , wherein performing the at least one operation on the first one of the plurality of transaction documents comprises altering the first one of the plurality of transaction documents.

6. The method of claim 1 , wherein performing the at least one operation on the first one of the plurality of transaction documents comprises altering the first one of the plurality of transaction documents. 7. The method of claim 6 , wherein: the user input comprises a user selection of an approve command, and altering the first one of the plurality of transaction documents comprises physically marking the first one of the plurality of transaction documents with a mark associated with the user, the mark signifying review of the first transaction document by the user and identifying the document as being approved by the user.

6. A method for simultaneously commencing output of disparately encoded electronic documents comprising the steps of: receiving selection data representative of a plurality of different user-selected electronic documents, each of the plurality of documents being encoded in a unique one of a plurality of disparate formats; associating each of the plurality of disparate formats with at least one software module; retrieving the plurality of user-selected electronic documents in accordance with received selection data; communicating each of the plurality of user-selected electronic documents to one of a plurality of corresponding software modules in accordance with an output of associating each of the plurality of formats with at least one software module; acquiring common document output characteristics associated with each of the plurality of selected electronic documents; and communicating configuration data corresponding to acquired document output characteristics to each of the software modules in a format compatible thereto; and commencing a selected document processing operation on each of a series of the user-selected electronic documents by calling the software modules, with each module corresponding to one of the series of user-selected electronic documents in accordance with the common document output characteristics.

6. A method for simultaneously commencing output of disparately encoded electronic documents comprising the steps of: receiving selection data representative of a plurality of different user-selected electronic documents, each of the plurality of documents being encoded in a unique one of a plurality of disparate formats; associating each of the plurality of disparate formats with at least one software module; retrieving the plurality of user-selected electronic documents in accordance with received selection data; communicating each of the plurality of user-selected electronic documents to one of a plurality of corresponding software modules in accordance with an output of associating each of the plurality of formats with at least one software module; acquiring common document output characteristics associated with each of the plurality of selected electronic documents; and communicating configuration data corresponding to acquired document output characteristics to each of the software modules in a format compatible thereto; and commencing a selected document processing operation on each of a series of the user-selected electronic documents by calling the software modules, with each module corresponding to one of the series of user-selected electronic documents in accordance with the common document output characteristics. 7. The method for simultaneously commencing output of disparately encoded electronic documents of claim 6 further comprising the step of prompting an associated user for input of common document output characteristics in accordance with common features associated with each software module.

17. The system of claim 10 , where the expected co-occurrence rate of the related phrase and the first phrase is a function of a number of documents in the document collection that include the first phrase and a number of documents in the document collection that include the related phrase, and the actual co-occurrence rate being a function of a number of times the first phrase appears within a threshold number of words of the related phrase in the document collection.

17. The system of claim 10 , where the expected co-occurrence rate of the related phrase and the first phrase is a function of a number of documents in the document collection that include the first phrase and a number of documents in the document collection that include the related phrase, and the actual co-occurrence rate being a function of a number of times the first phrase appears within a threshold number of words of the related phrase in the document collection. 18. The system of claim 17 , wherein the threshold is about 100.

11. A non-transitory computer-readable storage medium storing computer program instructions executable by data processing apparatus to perform operations comprising: determining, at a user device, that one or more first search queries received in a user interface during a search session are provided to a first search engine; determining, at the user device, that for each of the one or more first search queries, a plurality of respective search results determined by the first search engine as satisfying the respective first search queries are displayed in the user interface; determining, by a computer at the user device, that the respective search results determined by the first search engine as satisfying the respective first search queries do not satisfy an informational need of a user that input the one or more first search queries at the user device; and in response to determining that the respective search results determined by the first search engine do not satisfy an informational need: displaying, in the user interface, a second search query and a third search query that is based on the first search queries, wherein the third search query is different from the second search query; and displaying, in the user interface, a message informing the user of an ability to submit either the second search query or the third search query to a second search engine.

11. A non-transitory computer-readable storage medium storing computer program instructions executable by data processing apparatus to perform operations comprising: determining, at a user device, that one or more first search queries received in a user interface during a search session are provided to a first search engine; determining, at the user device, that for each of the one or more first search queries, a plurality of respective search results determined by the first search engine as satisfying the respective first search queries are displayed in the user interface; determining, by a computer at the user device, that the respective search results determined by the first search engine as satisfying the respective first search queries do not satisfy an informational need of a user that input the one or more first search queries at the user device; and in response to determining that the respective search results determined by the first search engine do not satisfy an informational need: displaying, in the user interface, a second search query and a third search query that is based on the first search queries, wherein the third search query is different from the second search query; and displaying, in the user interface, a message informing the user of an ability to submit either the second search query or the third search query to a second search engine. 14. The medium of claim 11 , wherein displaying a suggestion to provide the second search query to the second search engine comprises: displaying the second search query in the user interface; and displaying a message in the user interface that states that selection of the second search query will result in the second search query being provided to the second search engine.

14. The program storage device as recited in claim 12 , wherein the database includes metadata for at least one website in the database.

14. The program storage device as recited in claim 12 , wherein the database includes metadata for at least one website in the database. 15. The program storage device as recited in claim 14 , wherein the method further comprises the step of comparing a search term that was submitted to the search engine to the metadata, thus producing a list of related websites.

26. The method according to claim 25 , wherein receiving a plurality of descriptive characteristics includes visual findings.

26. The method according to claim 25 , wherein receiving a plurality of descriptive characteristics includes visual findings. 28. The method according to claim 26 , wherein said visual findings are entered through the user interface by selection of an image.

1. A method for creating a relational database schema, comprising: accessing a reference ontology comprising a first number of concepts and a second number of properties; selecting a first set of concepts from the reference ontology; determining a first set of properties from said second number of properties, associated with the selected first set of concepts; determining a second set of concepts associated with the determined first set of properties; and generating a relational database schema comprising a number of tables, of which at least one table pertains to a concept of said second set of concepts; wherein the method is performed by at least one processor.

1. A method for creating a relational database schema, comprising: accessing a reference ontology comprising a first number of concepts and a second number of properties; selecting a first set of concepts from the reference ontology; determining a first set of properties from said second number of properties, associated with the selected first set of concepts; determining a second set of concepts associated with the determined first set of properties; and generating a relational database schema comprising a number of tables, of which at least one table pertains to a concept of said second set of concepts; wherein the method is performed by at least one processor. 4. The method according to claim 1 , further comprising: creating a meta representation comprising transformations between the reference ontology and the generated relational database schema.

10. The method according to claim 1 , further comprising a step of calculating a similarity value by checking the selected tag against one or more other tags assigned to different ones of the properties of the second component.

10. The method according to claim 1 , further comprising a step of calculating a similarity value by checking the selected tag against one or more other tags assigned to different ones of the properties of the second component. 11. The method according to claim 10 , further comprising a step of displaying any one of the calculated similarity value and an indication based on the calculated similarity value, on each property assigned with the other tags.

14. A method for enterprise content management including integrating a plurality of applications and federating information, the method comprising: receiving, by a composite system, a request from a client system; initiating a mediation flow comprising a predetermined mapped process flow configured to achieve a result in response to the received request, the mediation flow comprising: translating, by a manager system, the request from the client system; and performing, by the manager system, one or more high level validations; and retrieving information from a mapping, by an ontology modeling system, of a plurality of entities, the mapping comprising a plurality of attributes; and continuing the mediation flow by invoking, by the manager system, a plurality of composites based at least in part on the request from the client system and some or all the information retrieved from the mapping, the invoking comprising: initiating a plurality of actions each initiated in response to the invoking of one of the plurality of composites, where at least one of the plurality of actions comprises at least one decision block, input or mapped process and wherein: at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a first repository content service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a second repository content service distinct from the first repository content service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a security authentication service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a name and address lookup service; and at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising an account cross reference service.

14. A method for enterprise content management including integrating a plurality of applications and federating information, the method comprising: receiving, by a composite system, a request from a client system; initiating a mediation flow comprising a predetermined mapped process flow configured to achieve a result in response to the received request, the mediation flow comprising: translating, by a manager system, the request from the client system; and performing, by the manager system, one or more high level validations; and retrieving information from a mapping, by an ontology modeling system, of a plurality of entities, the mapping comprising a plurality of attributes; and continuing the mediation flow by invoking, by the manager system, a plurality of composites based at least in part on the request from the client system and some or all the information retrieved from the mapping, the invoking comprising: initiating a plurality of actions each initiated in response to the invoking of one of the plurality of composites, where at least one of the plurality of actions comprises at least one decision block, input or mapped process and wherein: at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a first repository content service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a second repository content service distinct from the first repository content service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a security authentication service; at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising a name and address lookup service; and at least one of the plurality of actions comprises at least one component reference that initiates a component service that invokes at least one additional composite comprising an account cross reference service. 21. The method of claim 14 , wherein the plurality of attributes comprises one or more attribute models.

17. The graphical user interface of claim 15 wherein the indication of the accuracy of the practice gesture currently being performed includes one or more items selected from the group consisting of: an animated hand, one or more motion trails, an iconographic representation, a textual description of the gesture currently being performed, a textual description of a command corresponding to the gesture currently being performed, a positive feedback indicator, and a negative feedback indicator.

17. The graphical user interface of claim 15 wherein the indication of the accuracy of the practice gesture currently being performed includes one or more items selected from the group consisting of: an animated hand, one or more motion trails, an iconographic representation, a textual description of the gesture currently being performed, a textual description of a command corresponding to the gesture currently being performed, a positive feedback indicator, and a negative feedback indicator. 18. The graphical user interface of claim 17 wherein at least one of the positive feedback indicator and the negative feedback indicator comprise an audible indication.

62. An information processing system for filtering and securing from input data, one or more security sensitive words, characters or data objects with an adaptive filter in a computer system, said adaptive filter used in conjunction with a compilation of additional data, the system comprising: an identifier of said security sensitive words, characters or data objects in said compilation of additional data; means for retrieving related data from said compilation of additional data representative of at least one of: contextual characters or data objects related to said security sensitive words, characters or data objects; semiotic words, characters or data objects related to said security sensitive words, characters or data objects; taxonomic words, characters or data objects related to said security sensitive words, characters or data objects; a filter compiled from with said security sensitive words, characters or data objects and the retrieved data related to said security sensitive words, characters or data objects; and an extractor, operable with said filter, for extracting, from said input data, said security sensitive words, characters or data objects and said retrieved data to obtain extracted data and remainder data therefrom; and, means for storing either the extracted data separately from said remainder data or storing partial versions of said extracted data with said remainder data based upon multiple security levels unique to each partial version.

62. An information processing system for filtering and securing from input data, one or more security sensitive words, characters or data objects with an adaptive filter in a computer system, said adaptive filter used in conjunction with a compilation of additional data, the system comprising: an identifier of said security sensitive words, characters or data objects in said compilation of additional data; means for retrieving related data from said compilation of additional data representative of at least one of: contextual characters or data objects related to said security sensitive words, characters or data objects; semiotic words, characters or data objects related to said security sensitive words, characters or data objects; taxonomic words, characters or data objects related to said security sensitive words, characters or data objects; a filter compiled from with said security sensitive words, characters or data objects and the retrieved data related to said security sensitive words, characters or data objects; and an extractor, operable with said filter, for extracting, from said input data, said security sensitive words, characters or data objects and said retrieved data to obtain extracted data and remainder data therefrom; and, means for storing either the extracted data separately from said remainder data or storing partial versions of said extracted data with said remainder data based upon multiple security levels unique to each partial version. 66. An information processing system as claimed in claim 62 wherein said means for retrieving includes means for retrieving taxonomic words, characters or data objects from said compilation of additional data related to said security sensitive words, characters or data objects and based upon categorization and classification as reflected in said compilation of additional data and as related to said security sensitive words, characters or data objects.

1. A computer implemented method for suggesting headlines, comprising: training a machine learning topic model using search logs and historic click through data to account for the potential of a word in a headline to induce a click; receiving, at a computing device, an input of a headline and an article associated with the headline; determining, by a computing device, a topic associated with the article and headline; determining a plurality of words associated with the topic; inputting each of the plurality of words associated with the topic into the trained machine learning topic model to determine a topical click value for each of the plurality of words; and recommending at least one word of the plurality of words having a higher topical click value compared to other words among the plurality of words.

1. A computer implemented method for suggesting headlines, comprising: training a machine learning topic model using search logs and historic click through data to account for the potential of a word in a headline to induce a click; receiving, at a computing device, an input of a headline and an article associated with the headline; determining, by a computing device, a topic associated with the article and headline; determining a plurality of words associated with the topic; inputting each of the plurality of words associated with the topic into the trained machine learning topic model to determine a topical click value for each of the plurality of words; and recommending at least one word of the plurality of words having a higher topical click value compared to other words among the plurality of words. 3. The method of claim 1 , further comprising filtering the search logs and historic click through data to remove common words.

8. A system for integrating a plurality of documents in a first format into a data store holding documents in a second format, the system comprising: a data store comprising a repository configured to store a plurality of documents in the first format and a specification comprising instructions for creating descriptions of the plurality of documents based on attributes of the documents and syntax rules, the repository further configured to supply the documents and specification to a conversion facility; a batch import module adapted to receive from the conversion facility a batch including the plurality of documents in the second format and descriptions of the plurality of documents in the second format generated responsive to the specification, wherein the batch import module is further adapted to import the batch including the plurality of documents in the second format into the data store responsive to the descriptions, and wherein the data store is further configured to provide user access to the plurality of documents in the second format.

8. A system for integrating a plurality of documents in a first format into a data store holding documents in a second format, the system comprising: a data store comprising a repository configured to store a plurality of documents in the first format and a specification comprising instructions for creating descriptions of the plurality of documents based on attributes of the documents and syntax rules, the repository further configured to supply the documents and specification to a conversion facility; a batch import module adapted to receive from the conversion facility a batch including the plurality of documents in the second format and descriptions of the plurality of documents in the second format generated responsive to the specification, wherein the batch import module is further adapted to import the batch including the plurality of documents in the second format into the data store responsive to the descriptions, and wherein the data store is further configured to provide user access to the plurality of documents in the second format. 11. The system of claim 8 wherein the specification comprises an XML Document Type Definition that describes element names and XML syntax rules for creating a description of the document.

15. A system for translating user input into at least one word having multiple characters, the system comprising: a display configured to display a keyboard, wherein the keyboard comprises multiple character indicators; an input device configured to receive a sequence of user inputs; one or more processors; and a memory; wherein the processor and the memory are configured to: encode the sequence of user inputs into a sequence of discrete input directions by selecting, from a set of predetermined primary directions, a discrete direction most closely matching, or exactly matching, each user input; and identify, using the sequence of user inputs, at least one word in a stored dictionary, by matching the sequence of discrete input directions to one or more patterns corresponding to words stored in the dictionary; wherein each of the one or more patterns corresponding to a word specifies a relative directional relationship between; A) a position or area of the keyboard associated with a first character of a pair of sequential characters in the word corresponding to that pattern, and a position or area of the keyboard associated with a second character of the pair of sequential characters; and wherein matching the sequence of discrete input directions to the one or more patterns comprises finding matches between: items in the sequence of discrete input directions, and items in the sequence of discrete directions corresponding to each of the one or more patterns.

15. A system for translating user input into at least one word having multiple characters, the system comprising: a display configured to display a keyboard, wherein the keyboard comprises multiple character indicators; an input device configured to receive a sequence of user inputs; one or more processors; and a memory; wherein the processor and the memory are configured to: encode the sequence of user inputs into a sequence of discrete input directions by selecting, from a set of predetermined primary directions, a discrete direction most closely matching, or exactly matching, each user input; and identify, using the sequence of user inputs, at least one word in a stored dictionary, by matching the sequence of discrete input directions to one or more patterns corresponding to words stored in the dictionary; wherein each of the one or more patterns corresponding to a word specifies a relative directional relationship between; A) a position or area of the keyboard associated with a first character of a pair of sequential characters in the word corresponding to that pattern, and a position or area of the keyboard associated with a second character of the pair of sequential characters; and wherein matching the sequence of discrete input directions to the one or more patterns comprises finding matches between: items in the sequence of discrete input directions, and items in the sequence of discrete directions corresponding to each of the one or more patterns. 19. The system of claim 15 , wherein the set of predetermined primary directions includes at least directions corresponding to up, down, left and right.

1. A computer-readable hardware device containing instructions that, when executed by a computer system, cause the computer system to perform operations comprising: mapping a domain-specific document to an abstract language representation of the document; receiving at least two notational choices, the receiving comprising: receiving a first notational choice, the first notational choice specifying how a first type of items are to be formatted when displayed, and receiving a second notational choice different from the first notational choice, the second notational choice specifying how a second type of items are to be formatted when displayed, wherein the document includes at least one item of the first type of items and at least one item of the second type of items; mapping the abstract language representation to a concrete language representation of the document based on the received at least two notational choices; determining a layout of the concrete language representation; for each of a plurality of elements of the concrete language representation of the document, mapping the element of the concrete language representation to an element of a graphical language representation of the document based on the determined layout; and displaying the document based on the graphical language representation wherein the first type of items are trees so that the first notational choice specifies how trees are to be formatted when displayed, and wherein the second type of items are programming blocks so that the second notational choice specifies how programming blocks are to be formatted when displayed.

1. A computer-readable hardware device containing instructions that, when executed by a computer system, cause the computer system to perform operations comprising: mapping a domain-specific document to an abstract language representation of the document; receiving at least two notational choices, the receiving comprising: receiving a first notational choice, the first notational choice specifying how a first type of items are to be formatted when displayed, and receiving a second notational choice different from the first notational choice, the second notational choice specifying how a second type of items are to be formatted when displayed, wherein the document includes at least one item of the first type of items and at least one item of the second type of items; mapping the abstract language representation to a concrete language representation of the document based on the received at least two notational choices; determining a layout of the concrete language representation; for each of a plurality of elements of the concrete language representation of the document, mapping the element of the concrete language representation to an element of a graphical language representation of the document based on the determined layout; and displaying the document based on the graphical language representation wherein the first type of items are trees so that the first notational choice specifies how trees are to be formatted when displayed, and wherein the second type of items are programming blocks so that the second notational choice specifies how programming blocks are to be formatted when displayed. 6. The computer-readable hardware device of claim 1 wherein the operations further comprise: detecting changes to the document and representing the changes using a pending language representation.

3. A computer-implemented method, comprising: receiving a communication from a computing device, the communication including at least one text portion; analyzing the at least one text portion using a set of environment-specific terms, at least a portion of environment-specific terms in the set each having at least one corresponding autocorrected term determined by running the environment-specific term through at least one text-correction process to generate the at least one corresponding autocorrected term, wherein a given environment-specific term in the set is capable of being associated with a plurality of autocorrected terms, each of the plurality of autocorrected terms corresponding to a different text-correction algorithm; reverting a word in the at least one text portion of the communication to the environment-specific term associated with the corresponding autocorrected term upon a determination, via the at least one processor, that the word matches a corresponding autocorrected term in the set; and processing the communication.

3. A computer-implemented method, comprising: receiving a communication from a computing device, the communication including at least one text portion; analyzing the at least one text portion using a set of environment-specific terms, at least a portion of environment-specific terms in the set each having at least one corresponding autocorrected term determined by running the environment-specific term through at least one text-correction process to generate the at least one corresponding autocorrected term, wherein a given environment-specific term in the set is capable of being associated with a plurality of autocorrected terms, each of the plurality of autocorrected terms corresponding to a different text-correction algorithm; reverting a word in the at least one text portion of the communication to the environment-specific term associated with the corresponding autocorrected term upon a determination, via the at least one processor, that the word matches a corresponding autocorrected term in the set; and processing the communication. 11. The computer-implemented method of claim 3 , further comprising: sending a request to the computing device causing the computing device to prompt a user as to whether to correct the word to the environment-specific term.

14. A system of generating domain name suggestions based on inputs comprising: a non-transitory memory storing instructions; and a processor executing the instructions to cause the system to perform a method comprising: receiving, at a computer, an input source, wherein the input source corresponds to at least one of an image data file, an audio data file, or a metadata source; processing, via the computer, the input source to extract information from the input source; identifying a similar data file that is similar to at least a portion of the input source, wherein the similar data file is extracted from a similar data file source; determining additional information about the similar data file based on contextual data describing the similar data file in the similar data file source; building, via the computer, a submission string based on the extracted information and the additional information; submitting the submission string to a name suggestion service; receiving name suggestions based on the submission string; and providing the name suggestions.

14. A system of generating domain name suggestions based on inputs comprising: a non-transitory memory storing instructions; and a processor executing the instructions to cause the system to perform a method comprising: receiving, at a computer, an input source, wherein the input source corresponds to at least one of an image data file, an audio data file, or a metadata source; processing, via the computer, the input source to extract information from the input source; identifying a similar data file that is similar to at least a portion of the input source, wherein the similar data file is extracted from a similar data file source; determining additional information about the similar data file based on contextual data describing the similar data file in the similar data file source; building, via the computer, a submission string based on the extracted information and the additional information; submitting the submission string to a name suggestion service; receiving name suggestions based on the submission string; and providing the name suggestions. 25. The system of claim 14 , wherein the method comprises: receiving a selection of domain names to register; and registering the domain names.

44. The system of claim 43 , wherein the generating of the at least one data sequence comprises: generating a first respective data set that includes first respective gestural event data; generating a second respective data set that includes second respective state information; and forming a second data sequence to include the first respective data set and the second respective data set.

44. The system of claim 43 , wherein the generating of the at least one data sequence comprises: generating a first respective data set that includes first respective gestural event data; generating a second respective data set that includes second respective state information; and forming a second data sequence to include the first respective data set and the second respective data set. 46. The system of claim 44 , wherein the generating of the second respective data set includes generating a second respective data set offset, wherein the second respective data set offset points to the second respective data set of the second data sequence.

6. The method of claim 4 , wherein the extracting the plurality of insights from the obtained data, resulting in extracted insights, comprises: extracting the plurality of insights from the crawled blog posts.

6. The method of claim 4 , wherein the extracting the plurality of insights from the obtained data, resulting in extracted insights, comprises: extracting the plurality of insights from the crawled blog posts. 10. The method of claim 6 , wherein generating comprises: generating a referred traffic dynamics summary table based on the extracted insights and the measurements of traffic, wherein the referred traffic dynamics summary table aggregates the measurements of traffic associated with the extracted insights across the crawled blog posts to rank the extracted insights.

16. A method for providing search results comprising the steps of: providing sets of data comprising: (a) one or more search engine identifiers of a plurality of search engine identifiers, (b) one or more search engine uniform resource locators of a plurality of search engine uniform resource locators, (c) one or more second placeholder patterns of a plurality of second placeholder patterns, (d) one or more query term separators of a plurality of query term separators, and wherein said search engine identifier of a plurality of search engine identifiers represents a search engine of a plurality of search engines, and wherein said search engine identifier of a plurality of search engines identifiers is linked to components of said sets of data including: (i) said search engine uniform resource locator of a plurality of search engine uniform resource locators, (ii) said second placeholder pattern of a plurality of second placeholder patterns, and (iii) said query term separator of a plurality of query term separators, and wherein said search engine uniform resource locator of a plurality of search engine uniform resource locators includes: (a). a scheme of a plurality of schemes, (b). a host of a plurality of hosts, (c). a path of a plurality of paths, (d). a query of a plurality of queries comprising: a first placeholder pattern of a plurality of first placeholder patterns representing a value of a plurality of values in a name value pair of a plurality of name value pairs, and wherein said second placeholder pattern of a plurality of second placeholder patterns is identical to said first placeholder pattern of a plurality of first placeholder patterns; loading said sets of data; receiving voiced utterances from a user of a plurality of users; converting said voiced utterances into a first data string; matching said first data string to said sets of data, identifying a corresponding said search engine identifier of a plurality of search engine identifiers; retrieving data linked to matched said search engine identifier of a plurality of search engine identifiers; storing retrieved data linked to said matched search engine identifier of a plurality of search engine identifiers in variables; signaling said user of a plurality of users that said first data string matched a corresponding said search engine identifier of a plurality of search engine identifiers; receiving a second set of voiced utterances from said user of a plurality of users specifying a query term to be searched for; converting said second set of voiced utterances into a second data string; modifying said second data string by replacing any spaces in said second data string with retrieved said query term separator linked to said search engine identifier of a plurality of search engine identifiers, creating a modified second data string; replacing said first placeholder pattern of a plurality of placeholder patterns in retrieved said search engine uniform resource locator of a plurality of search engine uniform resource locators with said modified second data string creating a modified search engine uniform resource locator; opening said modified search engine uniform resource locator through a uniform resource locator transmission method of a plurality of uniform resource locator transmission methods; and providing results of the search system.

16. A method for providing search results comprising the steps of: providing sets of data comprising: (a) one or more search engine identifiers of a plurality of search engine identifiers, (b) one or more search engine uniform resource locators of a plurality of search engine uniform resource locators, (c) one or more second placeholder patterns of a plurality of second placeholder patterns, (d) one or more query term separators of a plurality of query term separators, and wherein said search engine identifier of a plurality of search engine identifiers represents a search engine of a plurality of search engines, and wherein said search engine identifier of a plurality of search engines identifiers is linked to components of said sets of data including: (i) said search engine uniform resource locator of a plurality of search engine uniform resource locators, (ii) said second placeholder pattern of a plurality of second placeholder patterns, and (iii) said query term separator of a plurality of query term separators, and wherein said search engine uniform resource locator of a plurality of search engine uniform resource locators includes: (a). a scheme of a plurality of schemes, (b). a host of a plurality of hosts, (c). a path of a plurality of paths, (d). a query of a plurality of queries comprising: a first placeholder pattern of a plurality of first placeholder patterns representing a value of a plurality of values in a name value pair of a plurality of name value pairs, and wherein said second placeholder pattern of a plurality of second placeholder patterns is identical to said first placeholder pattern of a plurality of first placeholder patterns; loading said sets of data; receiving voiced utterances from a user of a plurality of users; converting said voiced utterances into a first data string; matching said first data string to said sets of data, identifying a corresponding said search engine identifier of a plurality of search engine identifiers; retrieving data linked to matched said search engine identifier of a plurality of search engine identifiers; storing retrieved data linked to said matched search engine identifier of a plurality of search engine identifiers in variables; signaling said user of a plurality of users that said first data string matched a corresponding said search engine identifier of a plurality of search engine identifiers; receiving a second set of voiced utterances from said user of a plurality of users specifying a query term to be searched for; converting said second set of voiced utterances into a second data string; modifying said second data string by replacing any spaces in said second data string with retrieved said query term separator linked to said search engine identifier of a plurality of search engine identifiers, creating a modified second data string; replacing said first placeholder pattern of a plurality of placeholder patterns in retrieved said search engine uniform resource locator of a plurality of search engine uniform resource locators with said modified second data string creating a modified search engine uniform resource locator; opening said modified search engine uniform resource locator through a uniform resource locator transmission method of a plurality of uniform resource locator transmission methods; and providing results of the search system. 17. The Method of claim 16 , further comprising: receiving and displaying web pages or other information returned by opening said modified search engine uniform resource locator.

2. The system of claim 1 , wherein the dictionary generator module is further configured to: generate dictionary information that corresponds to a second user, the dictionary information that corresponds to the second user includes a second list of compatible query operators and a description of compatible data types that correspond to each operator in the second list of compatible query operators, wherein the dictionary information that corresponds to the second user is different from the dictionary information that corresponds to the first user.

2. The system of claim 1 , wherein the dictionary generator module is further configured to: generate dictionary information that corresponds to a second user, the dictionary information that corresponds to the second user includes a second list of compatible query operators and a description of compatible data types that correspond to each operator in the second list of compatible query operators, wherein the dictionary information that corresponds to the second user is different from the dictionary information that corresponds to the first user. 3. The system of claim 2 , wherein the query receiver module is further configured to: receive, from the second user, a search query to search for document information in the database, wherein the search query from the second user is different than the search query from the first user.

6. The voice acquisition system of claim 1 , wherein said interior rearview mirror assembly comprises an interior electrochromic rearview mirror assembly having electrically variable reflectivity, and wherein said interior electrochromic rearview mirror assembly includes electronic circuitry for at least adjusting the reflectivity of said interior electrochromic rearview mirror assembly, and wherein said at least one microphone at least one of (a) accesses a component of said electronic circuitry of said interior electrochromic rearview mirror assembly, and (b) shares a component of said electronic circuitry of said interior electrochromic rearview mirror assembly.

6. The voice acquisition system of claim 1 , wherein said interior rearview mirror assembly comprises an interior electrochromic rearview mirror assembly having electrically variable reflectivity, and wherein said interior electrochromic rearview mirror assembly includes electronic circuitry for at least adjusting the reflectivity of said interior electrochromic rearview mirror assembly, and wherein said at least one microphone at least one of (a) accesses a component of said electronic circuitry of said interior electrochromic rearview mirror assembly, and (b) shares a component of said electronic circuitry of said interior electrochromic rearview mirror assembly. 7. The voice acquisition system of claim 6 , wherein said electronic circuitry is associated with at least one mirror-based accessory selected from the group consisting of a global positioning system antenna, a motion sensor, a rain sensor, a video device, an interior light of the vehicle, an automatic toll booth transducer, a security system status indicator, a compass, a compass sensor, a temperature display, a temperature sensor, a tire pressure indicator display, a seat occupancy detection antenna, a seat occupancy detection transducer and a loudspeaker.

9. A system for recommending content items, the system comprising: a hardware processor that: determines a plurality of accessed content items associated with a user, wherein each of a plurality of content items is associated with a plurality of topics; determines the plurality of topics associated with each of the plurality of accessed content items; generates a model of user interests based on the plurality of topics, wherein the model implements a machine learning technique to determine a plurality of weights for assigning to each of the plurality of topics and wherein the model of user interests is generated by: retrieving a user interest profile that includes the plurality of topics associated with the plurality of content items accessed by the user and a plurality of other user interest profiles; generating a decision tree, wherein a portion of the decision tree identifies which of the plurality of other user interest profiles are similar to the user interest profile; determining a subset of the plurality of topics corresponding to the user interest profile and the similar user interest profiles in the portion of the decision tree; and determining a conjunction that models interaction between the subset of the plurality of topics and the plurality of content items; applies the model to determine, for the plurality of content items, a probability that the user watches a content item of the plurality of content items; ranks the plurality of content items based on the determined probability; and selects a subset of the plurality of content items to recommend to the user based on the ranked plurality of content items.

9. A system for recommending content items, the system comprising: a hardware processor that: determines a plurality of accessed content items associated with a user, wherein each of a plurality of content items is associated with a plurality of topics; determines the plurality of topics associated with each of the plurality of accessed content items; generates a model of user interests based on the plurality of topics, wherein the model implements a machine learning technique to determine a plurality of weights for assigning to each of the plurality of topics and wherein the model of user interests is generated by: retrieving a user interest profile that includes the plurality of topics associated with the plurality of content items accessed by the user and a plurality of other user interest profiles; generating a decision tree, wherein a portion of the decision tree identifies which of the plurality of other user interest profiles are similar to the user interest profile; determining a subset of the plurality of topics corresponding to the user interest profile and the similar user interest profiles in the portion of the decision tree; and determining a conjunction that models interaction between the subset of the plurality of topics and the plurality of content items; applies the model to determine, for the plurality of content items, a probability that the user watches a content item of the plurality of content items; ranks the plurality of content items based on the determined probability; and selects a subset of the plurality of content items to recommend to the user based on the ranked plurality of content items. 12. The system of claim 9 , wherein the processor is further configured to: determine, for each of the plurality of topics, related topics, wherein a distance measure between a topic and a related topic is calculated; determine a plurality of topic clusters, wherein one or more of the plurality of topics and one or more related topics are placed in a topic cluster based on the distance measure; map the user interest profile to at least one of the plurality of topic clusters to determine user cluster features; and determine a conjunction that models interaction between the determined user cluster features and the plurality of content items.

11. A system comprising: one or more computing devices; and at least one non-transitory storage device storing instructions operable to cause the one or more computing devices to perform operations comprising: receiving, from a first user device, activity information on an activity performed by a user of the first user device; receiving, from the first user device, a location where the first user device has stayed for at least a threshold amount of time; automatically determining, based on the activity information, a type of the activity; creating a social group based on the location and the type of the activity, including determining a theme of the social group based on the type of the activity; determining that a first condition that a second user device is located at the location or will visit the location is satisfied; determining that a second condition that the second user device seeks information related to the location or related to the theme of the social group is satisfied; and in response to determining that the first and second conditions are satisfied, providing a recommendation to join the social group to the second user device.

11. A system comprising: one or more computing devices; and at least one non-transitory storage device storing instructions operable to cause the one or more computing devices to perform operations comprising: receiving, from a first user device, activity information on an activity performed by a user of the first user device; receiving, from the first user device, a location where the first user device has stayed for at least a threshold amount of time; automatically determining, based on the activity information, a type of the activity; creating a social group based on the location and the type of the activity, including determining a theme of the social group based on the type of the activity; determining that a first condition that a second user device is located at the location or will visit the location is satisfied; determining that a second condition that the second user device seeks information related to the location or related to the theme of the social group is satisfied; and in response to determining that the first and second conditions are satisfied, providing a recommendation to join the social group to the second user device. 13. The system of claim 11 , wherein the social group is an ad hoc group including anonymous participants, the social group being created by the one or more computers without being initiated by the user.

2. The method of claim 1 , wherein the downloading and uploading steps take place through a second server that exposes the first server through a web interface.

2. The method of claim 1 , wherein the downloading and uploading steps take place through a second server that exposes the first server through a web interface. 3. The method of claim 2 , further including exposing the untranslated files grouped by project name.

1. A method performed by a portable capture device for updating a web page, the method comprising: optically or acoustically capturing a portion of a rendered document by the portable capture device, wherein if acoustically captured then the capturing of the portion of the rendered document is performed via a microphone of the portable capture device and includes performing speech recognition on the acoustically captured portion of the rendered document and converting the captured portion to digital content within the portable capture device, and if optically captured then the capturing of the portion of the rendered document includes converting the captured image to digital content within the portable capture device; generating, at the portable capture device, a textual query string from contents of the captured portion of the rendered document; submitting, from the portable capture device, the query string to a query engine that indexes full texts of documents; transmitting, from the portable capture device, an identifier associated with a user of the portable capture device to the query engine; receiving, at the portable capture device and from the query engine a link to an electronic document that includes the captured portion of the rendered document; and transmitting, from the portable capture device to a web page authoring system, the link to be inserted into a predetermined web page authored by the user of the portable capture device and inserting the link into the predetermined web page.

1. A method performed by a portable capture device for updating a web page, the method comprising: optically or acoustically capturing a portion of a rendered document by the portable capture device, wherein if acoustically captured then the capturing of the portion of the rendered document is performed via a microphone of the portable capture device and includes performing speech recognition on the acoustically captured portion of the rendered document and converting the captured portion to digital content within the portable capture device, and if optically captured then the capturing of the portion of the rendered document includes converting the captured image to digital content within the portable capture device; generating, at the portable capture device, a textual query string from contents of the captured portion of the rendered document; submitting, from the portable capture device, the query string to a query engine that indexes full texts of documents; transmitting, from the portable capture device, an identifier associated with a user of the portable capture device to the query engine; receiving, at the portable capture device and from the query engine a link to an electronic document that includes the captured portion of the rendered document; and transmitting, from the portable capture device to a web page authoring system, the link to be inserted into a predetermined web page authored by the user of the portable capture device and inserting the link into the predetermined web page. 3. The method of claim 1 , further comprising inserting into the predetermined web page a portion of the electronic document proximate to the captured portion.

13. The computer-readable program code embedded in the memory of claim 1 , wherein the set of rules, when implemented, checks for permissible roll-ups of aggregates.

13. The computer-readable program code embedded in the memory of claim 1 , wherein the set of rules, when implemented, checks for permissible roll-ups of aggregates. 14. The computer-readable program code embedded in the memory of claim 13 , wherein the permissible aggregate roll-ups are determined by evaluating restrictions included in the new query against restrictions included in the cached query.

22. A method for generating a resource transition probability model based on a usage log including information regarding (i) an identification of clients which requested resources referenced, (ii) an identification of the resources referenced, and (iii) an identification of times when the resources were referenced, the method comprising steps of: a) defining sessions based on the information regarding the identification of clients and the identification of the times; and b) determining resource transition probabilities based on the identification of clients, the identification of resources referenced, and the defined sessions, wherein the resource transition probability model is defined by the determined resource transition probabilities.

22. A method for generating a resource transition probability model based on a usage log including information regarding (i) an identification of clients which requested resources referenced, (ii) an identification of the resources referenced, and (iii) an identification of times when the resources were referenced, the method comprising steps of: a) defining sessions based on the information regarding the identification of clients and the identification of the times; and b) determining resource transition probabilities based on the identification of clients, the identification of resources referenced, and the defined sessions, wherein the resource transition probability model is defined by the determined resource transition probabilities. 28. The method of claim 22 wherein the sessions defined are based on a period of activity in which resources are referenced, followed by a period of inactivity in which no resources are referenced.

8. A non-transitory computer-readable storage medium having stored thereon instructions identifying phrases related to an item from a set of one or more information sources, the instructions upon being executed by one or more processors causing one or more computer systems to: receive a description of the item; perform a search across a corpus of documents to retrieve a search result set of a plurality of documents, wherein each document in the plurality of documents is related to the item based on the description, and wherein each document in the plurality of documents in the search result set comprises a respective plurality of words; determine a first frequency of each word in the plurality of documents of the search result set, wherein the first frequency corresponds to an average number of times the word appears in each document of the search result set; determine a second frequency of each word in the plurality of documents in the search result set, wherein the second frequency corresponds to an average number of times the word appears in each document of the corpus of documents; for each word of the plurality of words, determine a frequency score that is based on a difference between the corresponding first frequency and the corresponding second frequency, wherein the frequency score indicates a level of relevance of the word to the item; identify a predetermined number of highly related words to the item based on the predetermined number of words with the highest frequency scores; select at least one anchor word from the predetermined number of highly related words; and identify at least one phrase including the at least one anchor word by searching each of the plurality of documents in the search result set for the at least one anchor word and identifying at least one word proximal to the at least one anchor word within the plurality of documents.

8. A non-transitory computer-readable storage medium having stored thereon instructions identifying phrases related to an item from a set of one or more information sources, the instructions upon being executed by one or more processors causing one or more computer systems to: receive a description of the item; perform a search across a corpus of documents to retrieve a search result set of a plurality of documents, wherein each document in the plurality of documents is related to the item based on the description, and wherein each document in the plurality of documents in the search result set comprises a respective plurality of words; determine a first frequency of each word in the plurality of documents of the search result set, wherein the first frequency corresponds to an average number of times the word appears in each document of the search result set; determine a second frequency of each word in the plurality of documents in the search result set, wherein the second frequency corresponds to an average number of times the word appears in each document of the corpus of documents; for each word of the plurality of words, determine a frequency score that is based on a difference between the corresponding first frequency and the corresponding second frequency, wherein the frequency score indicates a level of relevance of the word to the item; identify a predetermined number of highly related words to the item based on the predetermined number of words with the highest frequency scores; select at least one anchor word from the predetermined number of highly related words; and identify at least one phrase including the at least one anchor word by searching each of the plurality of documents in the search result set for the at least one anchor word and identifying at least one word proximal to the at least one anchor word within the plurality of documents. 12. The computer-readable storage medium of claim 8 , wherein the instructions upon being executed further cause the one or more computer systems to: exclude duplicate documents from the search result set.

9. The system of claim 8 wherein the processing resource is coupled to the voice recognition unit and the resource manager unit is coupled to the processing resource and the voice recognition unit through bus systems.

9. The system of claim 8 wherein the processing resource is coupled to the voice recognition unit and the resource manager unit is coupled to the processing resource and the voice recognition unit through bus systems. 10. The system of claim 9, wherein the bus systems comprise a bus selected from the group consisting of a 100-BaseX bus and a ATM-switched ethernet backplane bus.

12. A computing system comprising: a data storage system storing: an index comprising a plurality of index entries, the index entries partitioned among a plurality of index partitions, each index partition in the plurality of index partitions associated with at least one website in a plurality of websites; a plurality of external data sets, each external data set in the plurality of external data sets comprising external resources, the external resources within each of the external data sets partitioned among pluralities of external partitions; and a set of computer-executable instructions; and a processing unit, the set of computer-executable instructions, when executed by the processing unit, causes the computing system to: host a plurality of website proxies, each website proxy in the plurality of website proxies associated with a website in the plurality of websites; host a plurality of external data sources, each external data source in the plurality of external data sources associated with a different external data set in the plurality of external data sets; and host a search proxy that: for each given website in the plurality of websites: automatically updates the index such that a given index partition in the plurality of index partitions comprises index entries that map terms in a first set of terms to web pages in the given website that contain terms in the first set of terms, the given website associated with the given index partition; automatically obtains a set of external partition identifiers, each external partition identifier in the set of external partition identifiers identifying external partitions of a given set of external data sources, each external data source in the given set of external data sources being in the plurality of external data sources, each external data source in the given set of external data sources being used by the given website, wherein the search proxy obtains the set of external partition identifiers by: sending a service request to the given website proxy, the given website proxy associated with the given website; and receiving a service response from the given website proxy, the service response comprising the set of external partition identifiers, wherein the given website proxy implements an application programming interface (API) that includes a first method and a second method, wherein the search proxy sends the service request to the given website proxy by invoking the first method and the second method, wherein invoking the first method comprises returning a list of references to each of a plurality of web pages in the given website, wherein invoking the second method comprises returning a copy of one of the plurality of web pages in the given website; and for each given external partition identifier in the set of external partition identifiers, automatically updates the index such that the given index partition comprises index entries that map a second set of terms to external resources in the external partition identified by the given external partition identifier that contain terms in the second set of terms; receives a query request from a querying website proxy in the plurality of website proxies, the query request specifying a query term, the querying website proxy associated with a target website in the plurality of websites; and in response to receiving the query request: automatically identifies a target index partition in the plurality of index partitions, the target website associated with the target index partition; automatically uses index entries in the target index partition to identify a relevant set of resources, each resource in the relevant set of resources containing the query term; and provides a relevant set of resource identifiers to the given website proxy, each resource identifier in the relevant set of resource identifiers identifying a resource in the relevant set of resources.

12. A computing system comprising: a data storage system storing: an index comprising a plurality of index entries, the index entries partitioned among a plurality of index partitions, each index partition in the plurality of index partitions associated with at least one website in a plurality of websites; a plurality of external data sets, each external data set in the plurality of external data sets comprising external resources, the external resources within each of the external data sets partitioned among pluralities of external partitions; and a set of computer-executable instructions; and a processing unit, the set of computer-executable instructions, when executed by the processing unit, causes the computing system to: host a plurality of website proxies, each website proxy in the plurality of website proxies associated with a website in the plurality of websites; host a plurality of external data sources, each external data source in the plurality of external data sources associated with a different external data set in the plurality of external data sets; and host a search proxy that: for each given website in the plurality of websites: automatically updates the index such that a given index partition in the plurality of index partitions comprises index entries that map terms in a first set of terms to web pages in the given website that contain terms in the first set of terms, the given website associated with the given index partition; automatically obtains a set of external partition identifiers, each external partition identifier in the set of external partition identifiers identifying external partitions of a given set of external data sources, each external data source in the given set of external data sources being in the plurality of external data sources, each external data source in the given set of external data sources being used by the given website, wherein the search proxy obtains the set of external partition identifiers by: sending a service request to the given website proxy, the given website proxy associated with the given website; and receiving a service response from the given website proxy, the service response comprising the set of external partition identifiers, wherein the given website proxy implements an application programming interface (API) that includes a first method and a second method, wherein the search proxy sends the service request to the given website proxy by invoking the first method and the second method, wherein invoking the first method comprises returning a list of references to each of a plurality of web pages in the given website, wherein invoking the second method comprises returning a copy of one of the plurality of web pages in the given website; and for each given external partition identifier in the set of external partition identifiers, automatically updates the index such that the given index partition comprises index entries that map a second set of terms to external resources in the external partition identified by the given external partition identifier that contain terms in the second set of terms; receives a query request from a querying website proxy in the plurality of website proxies, the query request specifying a query term, the querying website proxy associated with a target website in the plurality of websites; and in response to receiving the query request: automatically identifies a target index partition in the plurality of index partitions, the target website associated with the target index partition; automatically uses index entries in the target index partition to identify a relevant set of resources, each resource in the relevant set of resources containing the query term; and provides a relevant set of resource identifiers to the given website proxy, each resource identifier in the relevant set of resource identifiers identifying a resource in the relevant set of resources. 13. The computing system of claim 12 , wherein the given website proxy sends the query request to the search proxy in response to receiving a request from a client device for a web page containing a list of web pages that contain the query term; and wherein the given website proxy uses the relevant set of resource identifiers to generate the web page containing the list of web pages that contain the query term.

1. A system, comprising: an information feed; a first device to store information; and a second device in communication with the information feed and the first device, the second device configured to: receive first information comprising one or more portions from the information feed, determine a redundancy portion score associated with each of the one or more portions, wherein the redundancy portion score associated with the each of the one or more portions indicates a degree of redundancy of the each of the one or more portions with second information, determine a first score comprising a total of the redundancy portion scores associated with the each of the one or more portions, compare the first score with a redundancy limit, and cause non-redundant portions of the first information to be stored in the first device.

1. A system, comprising: an information feed; a first device to store information; and a second device in communication with the information feed and the first device, the second device configured to: receive first information comprising one or more portions from the information feed, determine a redundancy portion score associated with each of the one or more portions, wherein the redundancy portion score associated with the each of the one or more portions indicates a degree of redundancy of the each of the one or more portions with second information, determine a first score comprising a total of the redundancy portion scores associated with the each of the one or more portions, compare the first score with a redundancy limit, and cause non-redundant portions of the first information to be stored in the first device. 5. The system of claim 1 , wherein the first device includes a data structure arranged to facilitate identification of risk.

1. A system of a mobile device, Alpha, and a mobile device, Beta; where Alpha is controlled by a first user; where Beta is controlled by a second user; where the first user and the second user are different persons; where Alpha shows a first image; where Alpha makes a data containing an Universal Resource Locator (URL) of the first image; where the data furthermore contains an electronic address of the first user; where Alpha displays the data in a barcode as a second image; where Beta has a camera; where Beta scans the barcode with the camera to obtain an image Phi; where Beta decodes Phi to extract the data; where Beta sends an electronic message to the electronic address of the first user; where the electronic message contains an electronic address of the second user.

1. A system of a mobile device, Alpha, and a mobile device, Beta; where Alpha is controlled by a first user; where Beta is controlled by a second user; where the first user and the second user are different persons; where Alpha shows a first image; where Alpha makes a data containing an Universal Resource Locator (URL) of the first image; where the data furthermore contains an electronic address of the first user; where Alpha displays the data in a barcode as a second image; where Beta has a camera; where Beta scans the barcode with the camera to obtain an image Phi; where Beta decodes Phi to extract the data; where Beta sends an electronic message to the electronic address of the first user; where the electronic message contains an electronic address of the second user. 3. The system of claim 1 , where the electronic address is an email address.

10. A non-transitory, tangible, computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions, when executed by one or more processors, are operable to: receive a conceptual graph comprising one or more conceptual types, one or more relationship types, and one or more arcs; categorize each concept type of the one or more concept types according to the one or more relationship types and the one or more arcs, the computer-executable instructions further configured to categorize each concept type by: determining that each concept type is directly connected to two or more relationship types by two or more arcs pointing in different directions; and categorizing the each concept type as a context linking concept; record, in a non-transitory, tangible computer-readable memory device, the categorization of each concept type of the one or more concept types; identify one or more related terms of at least one particular concept type of the one or more concept types according to the categorization; and search a non-transitory, tangible computer-readable knowledgebase for a plurality of documents for matches to the identified one or more related terms of the at least one particular concept type according to the categorization.

10. A non-transitory, tangible, computer-readable storage medium storing computer-executable instructions, wherein the computer-executable instructions, when executed by one or more processors, are operable to: receive a conceptual graph comprising one or more conceptual types, one or more relationship types, and one or more arcs; categorize each concept type of the one or more concept types according to the one or more relationship types and the one or more arcs, the computer-executable instructions further configured to categorize each concept type by: determining that each concept type is directly connected to two or more relationship types by two or more arcs pointing in different directions; and categorizing the each concept type as a context linking concept; record, in a non-transitory, tangible computer-readable memory device, the categorization of each concept type of the one or more concept types; identify one or more related terms of at least one particular concept type of the one or more concept types according to the categorization; and search a non-transitory, tangible computer-readable knowledgebase for a plurality of documents for matches to the identified one or more related terms of the at least one particular concept type according to the categorization. 14. The non-transitory, tangible, computer-readable storage mediums of claim 10 , the computer-executable instructions further configured to record the categorization by: mapping, to each related term, a category designation designating the category of the related term.

22. A computer readable medium storing a computer program which when executed by at least one processor analyzes a document, the computer program comprising sets of instructions for: receiving the document that comprises a plurality of primitive graphic elements, each primitive graphic element defined as a single object in the document, the document having a drawing order that indicates the order in which the primitive graphic elements are drawn when the unstructured document is displayed; calculating relative positional values for each pair of successive primitive graphic elements in the drawing order, wherein the calculated relative positional values relate to a size of the primitive graphic elements in the pair; based on the calculated relative positional values, defining a cluster of successive primitive graphic elements; identifying a set of sub-clusters of primitive graphic elements in the cluster that satisfy particular constraints; and defining each particular sub-cluster as a single structural graphic element within the document comprising the primitive graphic elements in the particular sub-cluster.

22. A computer readable medium storing a computer program which when executed by at least one processor analyzes a document, the computer program comprising sets of instructions for: receiving the document that comprises a plurality of primitive graphic elements, each primitive graphic element defined as a single object in the document, the document having a drawing order that indicates the order in which the primitive graphic elements are drawn when the unstructured document is displayed; calculating relative positional values for each pair of successive primitive graphic elements in the drawing order, wherein the calculated relative positional values relate to a size of the primitive graphic elements in the pair; based on the calculated relative positional values, defining a cluster of successive primitive graphic elements; identifying a set of sub-clusters of primitive graphic elements in the cluster that satisfy particular constraints; and defining each particular sub-cluster as a single structural graphic element within the document comprising the primitive graphic elements in the particular sub-cluster. 27. The computer readable medium of claim 22 , wherein the particular constraints require that the primitive graphic elements of an identified sub-cluster meet density constraints.

1. A method for use in converting semantic information from a source form to a target form, comprising the steps of: obtaining an input string comprising a portion of the semantic information for conversion from said source form to said target form; first identifying a source term of said input string for conversion, wherein a context of said source term is ambiguous; second identifying a plurality of potential subject matter contexts of said input string including a plurality of different usage contexts for said source term in said source form from a portion of the semantic information other than said input string, wherein said plurality of different usage contexts represent identified potential usage contexts of said contextually ambiguous source term that are identified from said semantic information other than said input string in said source form of said semantic information; based on said plurality of subject matter contexts, establishing a set of at least two alternative candidate conversion terms in said target form for said source term, wherein said alternative candidate conversion terms comprise different possible representations of said contextually ambiguous source term in said target form corresponding to different ones of said plurality of different potential usage contexts; performing, using a computer based system, a statistical analysis at least partially based on said plurality of different usage contexts corresponding to said alternative candidate conversion terms, said statistical analysis including establishing a statistical probability for each of said alternative candidate conversion terms and selecting a selected one of said alternative candidate conversion terms having a highest probability of corresponding to a correct usage context of the source term in said string; and using said selected one of said alternative conversion terms to convert said source term from said source form to said target form.

1. A method for use in converting semantic information from a source form to a target form, comprising the steps of: obtaining an input string comprising a portion of the semantic information for conversion from said source form to said target form; first identifying a source term of said input string for conversion, wherein a context of said source term is ambiguous; second identifying a plurality of potential subject matter contexts of said input string including a plurality of different usage contexts for said source term in said source form from a portion of the semantic information other than said input string, wherein said plurality of different usage contexts represent identified potential usage contexts of said contextually ambiguous source term that are identified from said semantic information other than said input string in said source form of said semantic information; based on said plurality of subject matter contexts, establishing a set of at least two alternative candidate conversion terms in said target form for said source term, wherein said alternative candidate conversion terms comprise different possible representations of said contextually ambiguous source term in said target form corresponding to different ones of said plurality of different potential usage contexts; performing, using a computer based system, a statistical analysis at least partially based on said plurality of different usage contexts corresponding to said alternative candidate conversion terms, said statistical analysis including establishing a statistical probability for each of said alternative candidate conversion terms and selecting a selected one of said alternative candidate conversion terms having a highest probability of corresponding to a correct usage context of the source term in said string; and using said selected one of said alternative conversion terms to convert said source term from said source form to said target form. 6. The method as set forth in claim 1 , wherein said step of obtaining comprises accessing stored data of a legacy data system.

1. A computerized method of searching documents written in a plurality of languages, the method comprising: receiving a first query that includes at least one keyword in a first language; generating a second query by translating the at least one keyword into a second language; applying the first query against documents including at least one document written in the first language and at least one document written in the second language with the at least one keyword in the first language; applying the second query against documents written in the second language; generating a first set of results based on the first query, wherein the first set of results includes each document written in the first language that matches the first query; and generating a second set of results based on the first and second queries, wherein the second set of results includes each document written in the second language that matches at least one of the first query or the second query.

1. A computerized method of searching documents written in a plurality of languages, the method comprising: receiving a first query that includes at least one keyword in a first language; generating a second query by translating the at least one keyword into a second language; applying the first query against documents including at least one document written in the first language and at least one document written in the second language with the at least one keyword in the first language; applying the second query against documents written in the second language; generating a first set of results based on the first query, wherein the first set of results includes each document written in the first language that matches the first query; and generating a second set of results based on the first and second queries, wherein the second set of results includes each document written in the second language that matches at least one of the first query or the second query. 7. The method of claim 1 , further comprising: identifying keywords from each of the plurality of documents; translating each identified keyword into each of the plurality of languages; and creating an index in each of the plurality of languages, wherein the applying the first query uses at least one of the plurality of indexes.

5. The method of claim 1 , wherein the gesture comprises a first gesture and the candidate word comprises a first candidate word, and further comprising in response to the detecting and while the input unit is detected at the presence-sensitive input device: determining, by the computing device, the first candidate word and a second candidate word based at least in part on at least two keys; outputting the first candidate word for display at the first location of the display device; outputting the second candidate word for display at a third location of the display device; and responsive to identifying a second gesture to select the second candidate word over the first candidate word and determining that the input unit is no longer detected at the presence-sensitive input device, outputting the second candidate word for display at the second location of the display device.

5. The method of claim 1 , wherein the gesture comprises a first gesture and the candidate word comprises a first candidate word, and further comprising in response to the detecting and while the input unit is detected at the presence-sensitive input device: determining, by the computing device, the first candidate word and a second candidate word based at least in part on at least two keys; outputting the first candidate word for display at the first location of the display device; outputting the second candidate word for display at a third location of the display device; and responsive to identifying a second gesture to select the second candidate word over the first candidate word and determining that the input unit is no longer detected at the presence-sensitive input device, outputting the second candidate word for display at the second location of the display device. 6. The method of claim 5 , wherein the third location is a predetermined location of the display device that is not based on a detected location of the input unit that performed the first and second gestures.

12. An apparatus for coordinating text messages from a plurality of operator devices to determine a text message to send to an emergency caller device, the apparatus comprising: a processing device adapted to establish an emergency text messaging session, which establishes a media path between the apparatus and the emergency caller device, and adapted to establish a call leg to the session for each of a first operator device and a second operator device; and an interface adapted to receive a first text message from the first operator device and a second text message from the second operator device and provide real-time messaging between the first and the second operators such that each operator device sees contents of the other operator's text messages being typed in real time before any text message is sent to the emergency caller device; wherein the processing device is further adapted to apply a set of rules to the first and the second text messages to determine at least one text message to send to the emergency caller device; and wherein the interface is further adapted to send the at least one text message to the emergency caller device, wherein each text message sent to the emergency caller device is associated with a same identifier; wherein the set of rules comprises at least one of: a rule to send a first text message from a first responding device, and provide an indication to a second responding device that a second text message was not sent; a rule to send a second text message from the second responding device when the second responding device has assigned an override-drop status to the second text message; a rule to send either the first or the second text message based on a role of the first or the second responding device; or a rule to send the first text message delay sending the second text message by a delay time interval.

12. An apparatus for coordinating text messages from a plurality of operator devices to determine a text message to send to an emergency caller device, the apparatus comprising: a processing device adapted to establish an emergency text messaging session, which establishes a media path between the apparatus and the emergency caller device, and adapted to establish a call leg to the session for each of a first operator device and a second operator device; and an interface adapted to receive a first text message from the first operator device and a second text message from the second operator device and provide real-time messaging between the first and the second operators such that each operator device sees contents of the other operator's text messages being typed in real time before any text message is sent to the emergency caller device; wherein the processing device is further adapted to apply a set of rules to the first and the second text messages to determine at least one text message to send to the emergency caller device; and wherein the interface is further adapted to send the at least one text message to the emergency caller device, wherein each text message sent to the emergency caller device is associated with a same identifier; wherein the set of rules comprises at least one of: a rule to send a first text message from a first responding device, and provide an indication to a second responding device that a second text message was not sent; a rule to send a second text message from the second responding device when the second responding device has assigned an override-drop status to the second text message; a rule to send either the first or the second text message based on a role of the first or the second responding device; or a rule to send the first text message delay sending the second text message by a delay time interval. 13. The apparatus of claim 12 , wherein content of the first and second text messages is received into the interface in real time as the content is typed into the first and second operator devices, wherein the interface is further adapted to: send the content of the first text message in real time to the second operator device as the content of the first text message is typed into the first operator device; and send the content of the second text message in real time to the first operator device as the content of the second text message is typed into the second operator device.

2. The document conversion apparatus according to claim 1 , wherein the at least one computer program further comprises program code that, when executed by the computer processor, implements: a processing unit configured to receive a structured document including a first document element and a second document element, the processing unit configured to process a template; a converting unit configured to perform a first binary conversion algorithm on the first document element and to perform a second binary conversion algorithm on the second document element, wherein the second binary conversion algorithm is different from the first binary conversion algorithm; and an output unit configured to output the structured document in the binary format.

2. The document conversion apparatus according to claim 1 , wherein the at least one computer program further comprises program code that, when executed by the computer processor, implements: a processing unit configured to receive a structured document including a first document element and a second document element, the processing unit configured to process a template; a converting unit configured to perform a first binary conversion algorithm on the first document element and to perform a second binary conversion algorithm on the second document element, wherein the second binary conversion algorithm is different from the first binary conversion algorithm; and an output unit configured to output the structured document in the binary format. 3. The document conversion apparatus of claim 2 , wherein the template includes a processing command for outputting at least one of the document elements as a part of the structured document.

19. The method of claim 1 , wherein determining that a first semantic relationship between the first semantic element and the second semantic element exists comprises searching a database for saved semantic relationships between the first semantic element and the second semantic element.

19. The method of claim 1 , wherein determining that a first semantic relationship between the first semantic element and the second semantic element exists comprises searching a database for saved semantic relationships between the first semantic element and the second semantic element. 20. The method of claim 19 , wherein searching a database for saved semantic relationships between the first semantic element and the second semantic element comprises finding a possible semantic element that has a requirement property that matches a capability property of the second semantic element.

1. A method for optimizing inter-node communication in a content distribution system consisting of at least two nodes, the method comprising: generating a mutable warm dictionary for a specific domain according to a current inter-node communication by splitting a content of the current inter-node communication into chunks, searching for a match for each of the chunks in a previous fixed warm dictionary, incrementing a number of hits on said chunk and total number of bytes used in reference to said chunk when the match is found, and adding said chunk into the previous fixed warm dictionary when the match is not found; generating a read-only fixed warm dictionary for the specific domain from the mutable warm dictionary by sorting dictionary entries for the chunks in the mutable warm dictionary according to a weighted number of hits and a normalized total number of bytes, and generating the read-only fixed warm dictionary from one or more top dictionary entries of the sorted mutable warm dictionary by splitting the sorted mutable warm dictionary into a static part and an elimination pool with a predetermined ratio and generating the read-only fixed warm dictionary from the static part; and performing a next inter-node communication for the specific domain according to the read-only fixed warm dictionary.

1. A method for optimizing inter-node communication in a content distribution system consisting of at least two nodes, the method comprising: generating a mutable warm dictionary for a specific domain according to a current inter-node communication by splitting a content of the current inter-node communication into chunks, searching for a match for each of the chunks in a previous fixed warm dictionary, incrementing a number of hits on said chunk and total number of bytes used in reference to said chunk when the match is found, and adding said chunk into the previous fixed warm dictionary when the match is not found; generating a read-only fixed warm dictionary for the specific domain from the mutable warm dictionary by sorting dictionary entries for the chunks in the mutable warm dictionary according to a weighted number of hits and a normalized total number of bytes, and generating the read-only fixed warm dictionary from one or more top dictionary entries of the sorted mutable warm dictionary by splitting the sorted mutable warm dictionary into a static part and an elimination pool with a predetermined ratio and generating the read-only fixed warm dictionary from the static part; and performing a next inter-node communication for the specific domain according to the read-only fixed warm dictionary. 2. The method of claim 1 , wherein the read-only fixed warm dictionary comprises an ingress dictionary for inbound traffic and/or an egress dictionary for outbound traffic.