Datasets:

patent

/

AIPD_nlp_sentence_dataset_v2

like 1

7. A device for speech recognition comprising: a receiver being adapted to receive a first speech signal issued by multiple users; a converter being adapted to perform analog to digital conversion on the first speech signal from the receiving unit to generate a first digital signal after the analog to digital conversion; an extractor being adapted to extract a first speech parameter from the first digital signal, the first speech parameter describing a speech feature of the first speech signal; an execution circuit being adapted to execute control signaling instructed by the first digital signal if the first speech parameter coincides with a first prestored speech parameter in a sample library, the sample library prestoring prestored speech parameters of N users, N≧1, the device further comprising: a filter being adapted to perform signal filtering on the first digital signal so as to obtain at least a first sub signal corresponding to a first user and a second sub signal corresponding to a second user from the filtered first digital signal; wherein the extractor is further adapted to extract, from the first sub signal, a second speech parameter that describes a speech feature of the first sub signal, and extract, from the second sub signal, a third speech parameter that describes a speech feature of the second sub signal, wherein the first speech parameter comprises the second speech parameter and the third speech parameter.

7. A device for speech recognition comprising: a receiver being adapted to receive a first speech signal issued by multiple users; a converter being adapted to perform analog to digital conversion on the first speech signal from the receiving unit to generate a first digital signal after the analog to digital conversion; an extractor being adapted to extract a first speech parameter from the first digital signal, the first speech parameter describing a speech feature of the first speech signal; an execution circuit being adapted to execute control signaling instructed by the first digital signal if the first speech parameter coincides with a first prestored speech parameter in a sample library, the sample library prestoring prestored speech parameters of N users, N≧1, the device further comprising: a filter being adapted to perform signal filtering on the first digital signal so as to obtain at least a first sub signal corresponding to a first user and a second sub signal corresponding to a second user from the filtered first digital signal; wherein the extractor is further adapted to extract, from the first sub signal, a second speech parameter that describes a speech feature of the first sub signal, and extract, from the second sub signal, a third speech parameter that describes a speech feature of the second sub signal, wherein the first speech parameter comprises the second speech parameter and the third speech parameter. 8. The device according to claim 7 , wherein the device further comprises an identification unit implemented by a processor for identifying the first speech signal as a stranger speech if the first speech parameter does not coincide with any of the prestored speech parameters of the N users in the sample library.

2. A method as in claim 1 , wherein binarizing each subimage comprises: performing Otsu's thresholding algorithm to determine a threshold for binarization; detecting if a subimage is blank; detecting when a subimage includes light text on a dark background; and detecting if a subimage has varying background and foreground.

2. A method as in claim 1 , wherein binarizing each subimage comprises: performing Otsu's thresholding algorithm to determine a threshold for binarization; detecting if a subimage is blank; detecting when a subimage includes light text on a dark background; and detecting if a subimage has varying background and foreground. 3. A method as in claim 2 , wherein detecting when a subimage includes light text on a dark background comprises detecting when a subimage includes varying colored text on varying colored background.

24. A computer program embodied on a non-transitory computer readable medium, the computer program being executable by a processor for identifying claims associated with electronic text, the method comprising: accessing electronic text; identifying linguistic content associated with the electronic text, wherein the linguistic content includes a plurality of linguistic features; generating a linguistic structure based on the linguistic content identified, wherein the linguistic structure identifies at least a relationship between a first two or more linguistic features of the plurality of linguistic features; comparing the linguistic structure to a claim template, wherein the claim template identifies the same relationship between a second two or more linguistic features, each of the second two or more linguistic features corresponding to a linguistic feature of the first two or more linguistic features; in response to a determination that each of the first two or more linguistic features is a hyponym of the corresponding linguistic feature in the second two or more linguistic features, identifying a claim within the electronic text.

24. A computer program embodied on a non-transitory computer readable medium, the computer program being executable by a processor for identifying claims associated with electronic text, the method comprising: accessing electronic text; identifying linguistic content associated with the electronic text, wherein the linguistic content includes a plurality of linguistic features; generating a linguistic structure based on the linguistic content identified, wherein the linguistic structure identifies at least a relationship between a first two or more linguistic features of the plurality of linguistic features; comparing the linguistic structure to a claim template, wherein the claim template identifies the same relationship between a second two or more linguistic features, each of the second two or more linguistic features corresponding to a linguistic feature of the first two or more linguistic features; in response to a determination that each of the first two or more linguistic features is a hyponym of the corresponding linguistic feature in the second two or more linguistic features, identifying a claim within the electronic text. 25. The computer program recited in claim 24 , wherein the electronic text comprises electronic media.

14. One or more computer-readable storage media having computer-executable instructions embodied thereon that, when executed by at least one processor, cause the at least one processor to perform acts comprising: scoring an alteration candidate for a query, the alteration candidate comprising multiple alteration terms, the query comprising multiple query terms, and the scoring comprising: computing one or more query-dependent feature scores that are based on dependencies to multiple query terms from each of one or more of the alteration terms; computing one or more intra-candidate-dependent feature scores that are based on dependencies between different terms in the alteration candidate; and computing a candidate score for the candidate using the one or more query-dependent feature scores and the one or more intra-candidate-dependent feature scores; and determining whether to select the candidate to expand the query, the determination using the candidate score.

14. One or more computer-readable storage media having computer-executable instructions embodied thereon that, when executed by at least one processor, cause the at least one processor to perform acts comprising: scoring an alteration candidate for a query, the alteration candidate comprising multiple alteration terms, the query comprising multiple query terms, and the scoring comprising: computing one or more query-dependent feature scores that are based on dependencies to multiple query terms from each of one or more of the alteration terms; computing one or more intra-candidate-dependent feature scores that are based on dependencies between different terms in the alteration candidate; and computing a candidate score for the candidate using the one or more query-dependent feature scores and the one or more intra-candidate-dependent feature scores; and determining whether to select the candidate to expand the query, the determination using the candidate score. 20. The one or more computer-readable storage media of claim 14 , wherein the intra-candidate-dependent feature scores comprise one or more adjacent bigram scores and one or more skip bigram scores.

1. A computer-implemented method for annotating an enterprise service, the method comprising: storing the enterprise service in an enterprise service repository, the enterprise service repository storing a plurality of enterprise services, each enterprise service comprising a callable entity that provides business functionality; generating, by one or more processors, one or more graphs based on one or more artifacts, the one or more artifacts resulting from a development process of the enterprise service; generating, by the one or more processors, one or more metadata repositories based on the one or more artifacts, each metadata repository comprising instance data that is automatically extracted from various sources and corresponds to one of the one or more graphs; storing, by the one or more processors, the one or more graphs and the one or more metadata repositories to a knowledge base provided in a non-transitory computer-readable storage medium; querying, by the one or more processors, the knowledge base to determine one or more annotations based on the one or more graphs and the one or more metadata repositories; annotating, by one or more processors, the enterprise service with the one or more annotations; and storing the one or more annotations in the enterprise service repository.

1. A computer-implemented method for annotating an enterprise service, the method comprising: storing the enterprise service in an enterprise service repository, the enterprise service repository storing a plurality of enterprise services, each enterprise service comprising a callable entity that provides business functionality; generating, by one or more processors, one or more graphs based on one or more artifacts, the one or more artifacts resulting from a development process of the enterprise service; generating, by the one or more processors, one or more metadata repositories based on the one or more artifacts, each metadata repository comprising instance data that is automatically extracted from various sources and corresponds to one of the one or more graphs; storing, by the one or more processors, the one or more graphs and the one or more metadata repositories to a knowledge base provided in a non-transitory computer-readable storage medium; querying, by the one or more processors, the knowledge base to determine one or more annotations based on the one or more graphs and the one or more metadata repositories; annotating, by one or more processors, the enterprise service with the one or more annotations; and storing the one or more annotations in the enterprise service repository. 5. The method of claim 1 , further comprising: generating an enterprise service signature as a concatenation of terms of one or more nodes of the one or more graphs; associating the enterprise service signature to the enterprise service; and storing the enterprise service signature in the enterprise service repository.

1. An educational aid for developing sight-word vocabulary in a student, comprising: a non-syllabified readable format text which is adapted to be or is already memorized verbatim by the student, said text having one or more words and each word having at least one syllable, and said text including a series of notations, each notation denoting at least one letter of said text, wherein portions of said words that require extended pronunciation are presented in a visually extended format so as to emphasize phonetic structure; and reinforcement means, separate from said text but adapted to be used together with said text, for reinforcing the student's sight recognition of words and syllables from said text; wherein said reinforcement means is operable to allow the student to note each successive notation in said text as the student recites said text from memory, and is further operable to allow the student to match specified words and syllables to corresponding words and syllables in said text by using sight recognition.

1. An educational aid for developing sight-word vocabulary in a student, comprising: a non-syllabified readable format text which is adapted to be or is already memorized verbatim by the student, said text having one or more words and each word having at least one syllable, and said text including a series of notations, each notation denoting at least one letter of said text, wherein portions of said words that require extended pronunciation are presented in a visually extended format so as to emphasize phonetic structure; and reinforcement means, separate from said text but adapted to be used together with said text, for reinforcing the student's sight recognition of words and syllables from said text; wherein said reinforcement means is operable to allow the student to note each successive notation in said text as the student recites said text from memory, and is further operable to allow the student to match specified words and syllables to corresponding words and syllables in said text by using sight recognition. 13. The educational aid of claim 1, wherein each word or syllable of said readable format text is displayed in a graphical representation depicting an analog melody pattern.

1. A method for routing a confirmation of receipt of a facsimile or portion thereof, comprising: analyzing, using a processor, text of a facsimile for at least one of a meaning and a context of the text; and routing one or more confirmations to one or more destinations based on the analysis, wherein routing the one or more confirmations comprises routing the one or more confirmations to one or more destinations other than a sender of the facsimile for communicating information to a human other than the sender of the facsimile, wherein the analysis does not include utilizing any optical character recognition (OCR) techniques, and wherein the analysis comprises using one or more techniques selected from the group consisting of: naïve Bayes classification; tf-idf weighting; latent semantic analysis; support vector machine analysis; k-nearest neighbor algorithmic analysis; and decision tree analysis.

1. A method for routing a confirmation of receipt of a facsimile or portion thereof, comprising: analyzing, using a processor, text of a facsimile for at least one of a meaning and a context of the text; and routing one or more confirmations to one or more destinations based on the analysis, wherein routing the one or more confirmations comprises routing the one or more confirmations to one or more destinations other than a sender of the facsimile for communicating information to a human other than the sender of the facsimile, wherein the analysis does not include utilizing any optical character recognition (OCR) techniques, and wherein the analysis comprises using one or more techniques selected from the group consisting of: naïve Bayes classification; tf-idf weighting; latent semantic analysis; support vector machine analysis; k-nearest neighbor algorithmic analysis; and decision tree analysis. 17. A method as recited in claim 1 , wherein the one or more confirmations is routed to a destination other than one associated with an intended recipient of the facsimile, wherein the destination other than one associated with an intended recipient of the facsimile comprises one or more of: a litigation department; a sales department; a human resources department; a marketing department; a billing department; a bookkeeping department; a product development team; a purchasing department; an accounting department; and a hiring department.

1. A method for providing media content in multiple languages, the method comprising: receiving, at a user device, a user selection of a preferred language; receiving, at the user device, a user request to view media content; determining, at a server, whether the media content is available in the preferred language; and without requiring further user interaction, transmitting, from the server to the user device, the media content in an alternate language based on determining the media content is not available in the preferred language.

1. A method for providing media content in multiple languages, the method comprising: receiving, at a user device, a user selection of a preferred language; receiving, at the user device, a user request to view media content; determining, at a server, whether the media content is available in the preferred language; and without requiring further user interaction, transmitting, from the server to the user device, the media content in an alternate language based on determining the media content is not available in the preferred language. 2. The method of claim 1 , wherein the media content is media guidance data related to a media program.

1. A method comprising: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; receiving from the first user a structured query comprising references to one or more selected nodes from the plurality of nodes and one or more selected edges from the plurality of edges; parsing the structured query to identify a first query constraint and one or more second query constraints; identifying an inverse constraint associated with the first query constraint, wherein the first query constraint has been previously flagged as identifying greater than a threshold number of nodes; and generating a query command based on the structured query, wherein the query command comprises the inverse constraint and the one or more second query constraints.

1. A method comprising: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; receiving from the first user a structured query comprising references to one or more selected nodes from the plurality of nodes and one or more selected edges from the plurality of edges; parsing the structured query to identify a first query constraint and one or more second query constraints; identifying an inverse constraint associated with the first query constraint, wherein the first query constraint has been previously flagged as identifying greater than a threshold number of nodes; and generating a query command based on the structured query, wherein the query command comprises the inverse constraint and the one or more second query constraints. 8. The method of claim 1 , wherein: the first query constraint is for a first object-type corresponding to one or more nodes of a first node-type that are each connected by one of the selected edges referenced in the structured query to one or more nodes of a second node-type; and the inverse constraint is for a second object-type corresponding to one or more nodes of the second node-type that are connected by the one of the selected edges referenced in the structured query to one or more nodes of the first node-type.

18. The computer program product of claim 16 , wherein determining the plurality of links to evidence comprises determining a plurality of source reliability information.

18. The computer program product of claim 16 , wherein determining the plurality of links to evidence comprises determining a plurality of source reliability information. 19. The computer program product of claim 18 , wherein the determined source reliability information is selected from a group including at least one of a plurality of journal articles; a plurality of peer reviewed journal articles, a plurality of blogs, a plurality of dates, a plurality of crowd source opinion, a plurality of references, a plurality of on-line sources, a determination of how recent the document was created, a citation usage, and a plurality of ratings.

1. A computerized method for delivering messages to a plurality of subscribers, the method comprising the steps of: receiving, at a computerized delivery system, a plurality of incoming data messages from one or more content providers, wherein the incoming data messages are in XML 1.0 format and comprised of XML market data with pre-defined sets of tags; identifying a content type of at least one of said received messages; checking at least one of said plurality of incoming data messages for errors; forwarding a message to an error queue; building audit messages including error conditions, exceptions, and status conditions; electronically logging error conditions, exceptions, and status conditions; forwarding said received message to at least one processing node within the delivery system, wherein said at least one processing node is associated with the content type of said received message; building a subscriber-specific content message at said processing node by determining a subscription permission code associated with said received message using a permissions database and by transforming the format of said received message from XML 1.0 format to XML 2.0 format; authorizing the delivery of the subscriber-specific content message to at least one of a plurality of said subscribers based on said permission code; and delivering said subscriber-specific content message to at least one of said subscribers in real-time, wherein said delivered messages are in XML 2.0 format.

1. A computerized method for delivering messages to a plurality of subscribers, the method comprising the steps of: receiving, at a computerized delivery system, a plurality of incoming data messages from one or more content providers, wherein the incoming data messages are in XML 1.0 format and comprised of XML market data with pre-defined sets of tags; identifying a content type of at least one of said received messages; checking at least one of said plurality of incoming data messages for errors; forwarding a message to an error queue; building audit messages including error conditions, exceptions, and status conditions; electronically logging error conditions, exceptions, and status conditions; forwarding said received message to at least one processing node within the delivery system, wherein said at least one processing node is associated with the content type of said received message; building a subscriber-specific content message at said processing node by determining a subscription permission code associated with said received message using a permissions database and by transforming the format of said received message from XML 1.0 format to XML 2.0 format; authorizing the delivery of the subscriber-specific content message to at least one of a plurality of said subscribers based on said permission code; and delivering said subscriber-specific content message to at least one of said subscribers in real-time, wherein said delivered messages are in XML 2.0 format. 8. The method of claim 1 , wherein authorizing the delivery of the subscriber-specific content message includes verifying that said at least one of said subscribers is an entity that subscribes to messages having said content type.

10. A tangible computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for generating a product recommendation, the method comprising: receiving graph data indicating vertices and edges of the graph, wherein the vertices represent customers and products and the edges represent purchases; receiving a query of the graph to determine a product recommendation; generating a finite-state machine (FSM) based on the query; executing the query; determining whether a current state of the FSM is a traversal state; in response to the current state being a traversal state, generating a traversal FSM; searching the traversal FSM for a nearest future traversal state; generating a bitmask for the future traversal state; and utilizing the generated bitmask when executing the future traversal state to generate the product recommendation.

10. A tangible computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for generating a product recommendation, the method comprising: receiving graph data indicating vertices and edges of the graph, wherein the vertices represent customers and products and the edges represent purchases; receiving a query of the graph to determine a product recommendation; generating a finite-state machine (FSM) based on the query; executing the query; determining whether a current state of the FSM is a traversal state; in response to the current state being a traversal state, generating a traversal FSM; searching the traversal FSM for a nearest future traversal state; generating a bitmask for the future traversal state; and utilizing the generated bitmask when executing the future traversal state to generate the product recommendation. 17. The computer-readable storage medium of claim 10 , wherein the computer-readable storage medium stores additional instructions that, when executed, cause the computer to perform additional steps comprising: receiving data indicating a new primitive and input/output arguments of the new primitive; and adding the new primitive to a set of primitives.

89. A voice table for use in a text-to-speech synthesis system, wherein the voice table is pruned from an original voice table according to a machine-implemented method comprising: identifying instances in the original voice table; creating feature vectors derived from a machine perception transformation of time-domain samples corresponding to the instances of speech segments in the original voice table onto a feature space, wherein the machine perception transformation is correlated with human perception by using the time-domain samples retaining both amplitude and phase information of the speech segments, which were provided in sound data for a speech synthesis system; clustering the feature vectors using a similarity measure in the feature space; and replacing the clustered instances corresponding to the clustered feature vectors within a radius by a single instance.

89. A voice table for use in a text-to-speech synthesis system, wherein the voice table is pruned from an original voice table according to a machine-implemented method comprising: identifying instances in the original voice table; creating feature vectors derived from a machine perception transformation of time-domain samples corresponding to the instances of speech segments in the original voice table onto a feature space, wherein the machine perception transformation is correlated with human perception by using the time-domain samples retaining both amplitude and phase information of the speech segments, which were provided in sound data for a speech synthesis system; clustering the feature vectors using a similarity measure in the feature space; and replacing the clustered instances corresponding to the clustered feature vectors within a radius by a single instance. 90. The voice table of claim 89 wherein the instances are the instances of a phoneme, a diphone, a syllable, a word, or a sequence unit.

7. The method of claim 1 , wherein the first affinity coefficient is a positive or negative numerical value.

7. The method of claim 1 , wherein the first affinity coefficient is a positive or negative numerical value. 8. The method of claim 7 , wherein the natural-language processing utilizes a dictionary comprising crowd-sourced adjectives or objects.

11. The digital television decoder as claimed in claim 9 , wherein the pixmaps are chopped into rectangles which are drawn successively with each call of a background task.

11. The digital television decoder as claimed in claim 9 , wherein the pixmaps are chopped into rectangles which are drawn successively with each call of a background task. 12. The digital television decoder as claimed in claim 11 , wherein the background task constructs the anticipation band.

21. The method of claim 17 , where translating the terms of the search query into the second language comprises: determining, using one or more processors associated with the one or more server devices, possible translations of the terms of the search query into the second language; and disambiguating, using one or more processors associated with the one or more server devices, among the possible translations of the terms of the search query using the content included in the one or more documents in the second language to identify one of the possible translations as a likely translation of the search query.

21. The method of claim 17 , where translating the terms of the search query into the second language comprises: determining, using one or more processors associated with the one or more server devices, possible translations of the terms of the search query into the second language; and disambiguating, using one or more processors associated with the one or more server devices, among the possible translations of the terms of the search query using the content included in the one or more documents in the second language to identify one of the possible translations as a likely translation of the search query. 22. The method of claim 21 , where the determining possible translations includes: using, by one or more processors associated with the one or more server devices, a dictionary to identify the possible translations of the terms into the second language.

7. The method of claim 1 , wherein encoding a bin further comprises: maintaining a numerical interval comprising an upper interval limit and a lower interval limit, the upper interval limit greater than the lower interval limit, the numerical difference between the upper interval limit and the lower interval limit comprising the range of the numerical interval; and restricting the range of the numerical interval based on the bin and an associated context model, wherein restricting the range of the numerical interval comprises increasing the lower interval limit or decreasing the upper interval limit.

7. The method of claim 1 , wherein encoding a bin further comprises: maintaining a numerical interval comprising an upper interval limit and a lower interval limit, the upper interval limit greater than the lower interval limit, the numerical difference between the upper interval limit and the lower interval limit comprising the range of the numerical interval; and restricting the range of the numerical interval based on the bin and an associated context model, wherein restricting the range of the numerical interval comprises increasing the lower interval limit or decreasing the upper interval limit. 8. The method of claim 7 , wherein producing at least one encoded bit further comprises: outputting an encoded bit if the upper interval limit falls below a first pre-designated threshold or if the lower interval limit rises above a second pre-designated threshold; and expanding the range of the numerical interval based on the outputted bit, wherein expanding the range of the numerical interval comprises decreasing the lower interval limit or increasing the upper interval limit.

1. A method comprising: in a specification mode: specifying a class network having a class, wherein a membership function defines a likelihood that an object of a data network belongs to the class; specifying a process step having a domain and an algorithm, wherein the domain designates the class, and wherein the process step is part of a process hierarchy; specifying a link type that defines a relation between the class and the object; in an execution mode: acquiring table data values; and executing the class network and the process hierarchy on a computer that implements the data network by generating the object of the data network and by selectively linking selected table data values to the object according to the class network and the process hierarchy.

1. A method comprising: in a specification mode: specifying a class network having a class, wherein a membership function defines a likelihood that an object of a data network belongs to the class; specifying a process step having a domain and an algorithm, wherein the domain designates the class, and wherein the process step is part of a process hierarchy; specifying a link type that defines a relation between the class and the object; in an execution mode: acquiring table data values; and executing the class network and the process hierarchy on a computer that implements the data network by generating the object of the data network and by selectively linking selected table data values to the object according to the class network and the process hierarchy. 5. The method of claim 1 , wherein a first plurality of the table data values are spectral intensity values of a digital image, and wherein a second plurality of the table data values are items of metadata relating to the digital image.

23. The method of claim 22 : wherein the client device and the networked device reside on networks that are incommunicable with each other comprising at least one of a firewall separation, a different network separation, a physical separation, and an unreachable connection separation, and wherein the sandboxed application of the security sandbox of the client device and the sandbox reachable service of the networked device communicate with each other through a relay service employed by the pairing server having the discovery module and the relay module to facilitate a trusted communication between the sandboxed application and the sandbox reachable service.

23. The method of claim 22 : wherein the client device and the networked device reside on networks that are incommunicable with each other comprising at least one of a firewall separation, a different network separation, a physical separation, and an unreachable connection separation, and wherein the sandboxed application of the security sandbox of the client device and the sandbox reachable service of the networked device communicate with each other through a relay service employed by the pairing server having the discovery module and the relay module to facilitate a trusted communication between the sandboxed application and the sandbox reachable service. 24. The method of claim 23 : wherein the trusted communication is facilitated such that the sandboxed application never learns at least one of a private IP address and a hardware address of the networked device when: a first NAT device coupled with a network on which the client device operates receives communications from a public IP address of a different network on which the sandbox reachable service operates, and a second NAT device coupled with the different network on which the networked device operates translates the private IP address of the networked device to the public IP address visible to the sandboxed application.

18. The computer-implemented method of claim 16 , wherein the processing the computer program code further comprises: generating executable code that, when executed, creates one or more instances of the one or more handle subclasses and one or more instances of the one or more non-handle subclasses.

18. The computer-implemented method of claim 16 , wherein the processing the computer program code further comprises: generating executable code that, when executed, creates one or more instances of the one or more handle subclasses and one or more instances of the one or more non-handle subclasses. 19. The computer-implemented method of claim 18 , further comprising: executing the executable code.

25. The system of claim 24 , wherein the syllable detector identifies the syllables by identifying voiced segments and syllable boundaries.

25. The system of claim 24 , wherein the syllable detector identifies the syllables by identifying voiced segments and syllable boundaries. 26. The system of claim 25 , wherein the syllable detector identifies vocalic syllables within the range of human speech by evaluating the pitch and voicing ratio computed by a voicing detector.

13. A system for generating one or more prediction models for a workflow comprised of a plurality of activities, comprising: a memory; and at least one hardware device, coupled to the memory, operative to implement the following steps: extracting one or more input features from input data from a plurality of previous executions of said plurality of activities and extracting one or more output features from output data from said plurality of previous executions of said plurality of activities, wherein said plurality of activities execute in one or more computing devices; automatically learning, using at least one processing device, a plurality of prediction functions from one or more input features and one or more output features of said workflow, wherein each of said prediction functions predicts at least one of said output features of at least one of said plurality of activities of said workflow based on one or more of said input features of said at least one activity of said workflow; selecting, using said at least one processing device, one of said plurality of prediction functions for each of said plurality of activities in said workflow based on a particular goal and a succession of said plurality of activities according to a definition of said workflow to generate a selected subset of prediction functions; combining, using said at least one processing device, said selected subset of said plurality of prediction functions to generate said one or more prediction models based on the succession of said plurality of activities according to the definition of said workflow, wherein each of said one or more prediction models predicts a final output feature of said workflow based on one or more of said input features extracted from one or more initial inputs of said workflow; and selecting an instantiation of said workflow for a given input and said particular goal by evaluating a plurality of said one or more prediction models.

13. A system for generating one or more prediction models for a workflow comprised of a plurality of activities, comprising: a memory; and at least one hardware device, coupled to the memory, operative to implement the following steps: extracting one or more input features from input data from a plurality of previous executions of said plurality of activities and extracting one or more output features from output data from said plurality of previous executions of said plurality of activities, wherein said plurality of activities execute in one or more computing devices; automatically learning, using at least one processing device, a plurality of prediction functions from one or more input features and one or more output features of said workflow, wherein each of said prediction functions predicts at least one of said output features of at least one of said plurality of activities of said workflow based on one or more of said input features of said at least one activity of said workflow; selecting, using said at least one processing device, one of said plurality of prediction functions for each of said plurality of activities in said workflow based on a particular goal and a succession of said plurality of activities according to a definition of said workflow to generate a selected subset of prediction functions; combining, using said at least one processing device, said selected subset of said plurality of prediction functions to generate said one or more prediction models based on the succession of said plurality of activities according to the definition of said workflow, wherein each of said one or more prediction models predicts a final output feature of said workflow based on one or more of said input features extracted from one or more initial inputs of said workflow; and selecting an instantiation of said workflow for a given input and said particular goal by evaluating a plurality of said one or more prediction models. 14. The system of claim 13 , wherein said workflow is executed substantially simultaneously with at least two of collection of provenance data of said workflow, generation of an execution plan for said workflow, generation of said one or more prediction models for said workflow, and said generation of said instantiation of said workflow for said given input and said particular goal.

2. A method of providing spoken language interpretation service in a public switched telephone network comprising the steps of: receiving signals associated with a telephone call between a caller and a called party, the signals comprising at least the caller's telephone number and the called party's telephone number; and automatically providing a spoken language interpretation service to the caller and the called party during the telephone call in response to a predetermined characteristic of the caller's telephone number.

2. A method of providing spoken language interpretation service in a public switched telephone network comprising the steps of: receiving signals associated with a telephone call between a caller and a called party, the signals comprising at least the caller's telephone number and the called party's telephone number; and automatically providing a spoken language interpretation service to the caller and the called party during the telephone call in response to a predetermined characteristic of the caller's telephone number. 12. The method of claim 2, in which the public switched telephone network is a long distance telephone network.

7. A computer program product comprising a tangible computer readable recordable storage medium including computer useable program code for identifying one or more inconsistencies between an unstructured document and a back-end fact-base, the computer program product including: computer useable program code for automatically parsing a query document and comparing the document with a back-end fact-base comprising facts relevant to the document; computer useable program code for deriving one or more relevant facts from the query document by identifying one or more fact triples of three categorical elements in the back-end fact-base; computer useable program code for identifying one or more inconsistencies between the one or more relevant facts from the document and the facts stored in the back-end fact-base; and computer useable program code for providing a response to the query document, wherein the response additionally includes the one or more identified inconsistencies.

7. A computer program product comprising a tangible computer readable recordable storage medium including computer useable program code for identifying one or more inconsistencies between an unstructured document and a back-end fact-base, the computer program product including: computer useable program code for automatically parsing a query document and comparing the document with a back-end fact-base comprising facts relevant to the document; computer useable program code for deriving one or more relevant facts from the query document by identifying one or more fact triples of three categorical elements in the back-end fact-base; computer useable program code for identifying one or more inconsistencies between the one or more relevant facts from the document and the facts stored in the back-end fact-base; and computer useable program code for providing a response to the query document, wherein the response additionally includes the one or more identified inconsistencies. 9. The computer program product of claim 7 , wherein the back-end fact-base comprises unstructured and semi-structured documents.

14. A method of informing providers of productive assets, comprising: machine-culling a database of Uniform Commercial Code (UCC) financing statements that each includes a field for collateral information on specific productive assets that are supplied as collateral for a transaction underlying a corresponding UCC financing statement, and a secured party field with secured party information, including identifying productive asset keywords that are contained in corresponding collateral information fields; and machine-organizing output from the database by sorting corresponding secured party information and corresponding collateral information including the identified productive asset keywords from the Uniform Commercial Code financing statements into productive asset categories, wherein the sorting includes linking both equipment types and brand names of manufacturers of the equipment types into at least one particular productive asset category.

14. A method of informing providers of productive assets, comprising: machine-culling a database of Uniform Commercial Code (UCC) financing statements that each includes a field for collateral information on specific productive assets that are supplied as collateral for a transaction underlying a corresponding UCC financing statement, and a secured party field with secured party information, including identifying productive asset keywords that are contained in corresponding collateral information fields; and machine-organizing output from the database by sorting corresponding secured party information and corresponding collateral information including the identified productive asset keywords from the Uniform Commercial Code financing statements into productive asset categories, wherein the sorting includes linking both equipment types and brand names of manufacturers of the equipment types into at least one particular productive asset category. 18. The method of claim 14 , further including presenting the records in a format with hyperlinks for the corresponding secured collateral information and the corresponding secured party information.

4. The scripting engine of claim 1 further comprising a second steganographic decoder that extracts a key that is steganographically coded in a third script, wherein the first steganographic decoder uses the key to extract the hidden script.

4. The scripting engine of claim 1 further comprising a second steganographic decoder that extracts a key that is steganographically coded in a third script, wherein the first steganographic decoder uses the key to extract the hidden script. 5. The scripting engine of claim 4 wherein the third script is the same as the carrier script.

1. A method, utilizing at least one computing processor and memory, of geocoding resources based on contained text, the method comprising: obtaining bodies of text included in resources; identifying, in the bodies of text, tokens referring to geographic locations, each geographic location being referred to by at least one token; identifying canonical identifiers of the geographic locations based on the tokens, each geographic location being associated with at least one canonical identifier; and for a given resource referencing a given geographic location: identifying off-page resources that refer to the given resource; scoring relevance of the given resource to the given geographic location as a function of (i) at least a quantity of first tokens in the given resource, the first tokens corresponding to a given canonical identifier of the given geographic location and (ii) at least a quantity of second tokens in the off-page resources, the second tokens corresponding to the given canonical identifier of the given geographic location; and responsive to the score exceeding a certain threshold, designating the given resource as relevant to the given geographic location in the memory.

1. A method, utilizing at least one computing processor and memory, of geocoding resources based on contained text, the method comprising: obtaining bodies of text included in resources; identifying, in the bodies of text, tokens referring to geographic locations, each geographic location being referred to by at least one token; identifying canonical identifiers of the geographic locations based on the tokens, each geographic location being associated with at least one canonical identifier; and for a given resource referencing a given geographic location: identifying off-page resources that refer to the given resource; scoring relevance of the given resource to the given geographic location as a function of (i) at least a quantity of first tokens in the given resource, the first tokens corresponding to a given canonical identifier of the given geographic location and (ii) at least a quantity of second tokens in the off-page resources, the second tokens corresponding to the given canonical identifier of the given geographic location; and responsive to the score exceeding a certain threshold, designating the given resource as relevant to the given geographic location in the memory. 9. The method of claim 1 , comprising: for the given geographic location, selecting a canonical identifier of an overlapping geographic location that overlaps the given geographic location; and designating the given resource as relevant to the overlapping geographic location by associating the given resource in the memory with the selected canonical identifier.

1. A method comprising: accessing at least one database on one or more processor readable media, by one or more processors, the at least one database comprising: electronic user information including at least one from a group consisting of a trait, a brand-specific preference, and a person-specific identifier of each of a plurality of persons; and electronic advertiser information comprising information associated with at least one branded product and/or service associated with at least one respective advertiser of a plurality of advertisers; receiving, via one or more communication devices that are operatively connected to the one or more processors, first electronic information from a first user computing device associated with a first user, wherein the first electronic information includes at least some user information associated with the first user and information representing at least a trait, a preference, and/or a person-specific identifier; defining, by the one or more processors and in accordance with the first electronic information, a first group of at least two respective persons of the plurality of persons, wherein the first group is custom to the first user; determining, by the one or more processors and in accordance with at least a relationship of at least some user information associated with the first user and the electronic advertiser information, a relevance of the first user to at least two advertisers of the plurality of advertisers; processing, by the one or more processors, to identify one respective person of the first group in accordance with information representing a previously received selection of the one respective person by the first user; selecting, by the one or more processors, one of the at least two advertisers based at least on a relevance of the one respective person of the first group to at least some of the user information representing at least one person's preference of a brand associated with the one of the at least two advertisers; generating, by the one or more processors, advertising information that includes the brand associated with the one of the at least two advertisers, and a person-specific identifier associated with the one respective person of the first group; and transmitting, via the one or more communication devices, by the one or more processors, at least some of the advertising information to the first user computing device.

1. A method comprising: accessing at least one database on one or more processor readable media, by one or more processors, the at least one database comprising: electronic user information including at least one from a group consisting of a trait, a brand-specific preference, and a person-specific identifier of each of a plurality of persons; and electronic advertiser information comprising information associated with at least one branded product and/or service associated with at least one respective advertiser of a plurality of advertisers; receiving, via one or more communication devices that are operatively connected to the one or more processors, first electronic information from a first user computing device associated with a first user, wherein the first electronic information includes at least some user information associated with the first user and information representing at least a trait, a preference, and/or a person-specific identifier; defining, by the one or more processors and in accordance with the first electronic information, a first group of at least two respective persons of the plurality of persons, wherein the first group is custom to the first user; determining, by the one or more processors and in accordance with at least a relationship of at least some user information associated with the first user and the electronic advertiser information, a relevance of the first user to at least two advertisers of the plurality of advertisers; processing, by the one or more processors, to identify one respective person of the first group in accordance with information representing a previously received selection of the one respective person by the first user; selecting, by the one or more processors, one of the at least two advertisers based at least on a relevance of the one respective person of the first group to at least some of the user information representing at least one person's preference of a brand associated with the one of the at least two advertisers; generating, by the one or more processors, advertising information that includes the brand associated with the one of the at least two advertisers, and a person-specific identifier associated with the one respective person of the first group; and transmitting, via the one or more communication devices, by the one or more processors, at least some of the advertising information to the first user computing device. 6. The method of claim 1 , wherein the first electronic information further includes an indication of a purchase of one or more of the at least one of the one or more of branded products and services.

1. A computer-implemented method for determining a set of legal documents to present to a user for acceptance as part of a transaction, the method comprising: receiving, using one or more computing systems, informational data describing a transaction; identifying, using the one or more computing systems, a set of hierarchical electronic documents pertinent to the transaction based at least in part on the received informational data, the set including a root electronic document and one or more dependency electronic documents of the root electronic document, the root electronic document specifying a transaction identifier of the transaction and metadata identifying the one or more dependency electronic documents; selecting, using the one or more computing systems, a subset of electronic documents from the set of hierarchical electronic documents based at least in part on data describing electronic documents that a user involved in the transaction has previously accepted; identifying, using the one or more computing systems, from the selected subset of electronic documents, a current version of an electronic document that has not been accepted by the user; determining, using the one or more computing systems, whether acceptance of the current version is not required responsive to the user having accepted a prior version of the electronic document; responsive to determining that acceptance of the current version is not required and that the user has accepted the prior version, removing, using the one or more computing systems, the current version of the electronic document from the selected subset of electronic documents; and outputting, using the one or more computing systems, informational data pertaining to the selected subset of electronic documents for presenting the selected subset of electronic documents to the user involved in the transaction for acceptance as part of the transaction.

1. A computer-implemented method for determining a set of legal documents to present to a user for acceptance as part of a transaction, the method comprising: receiving, using one or more computing systems, informational data describing a transaction; identifying, using the one or more computing systems, a set of hierarchical electronic documents pertinent to the transaction based at least in part on the received informational data, the set including a root electronic document and one or more dependency electronic documents of the root electronic document, the root electronic document specifying a transaction identifier of the transaction and metadata identifying the one or more dependency electronic documents; selecting, using the one or more computing systems, a subset of electronic documents from the set of hierarchical electronic documents based at least in part on data describing electronic documents that a user involved in the transaction has previously accepted; identifying, using the one or more computing systems, from the selected subset of electronic documents, a current version of an electronic document that has not been accepted by the user; determining, using the one or more computing systems, whether acceptance of the current version is not required responsive to the user having accepted a prior version of the electronic document; responsive to determining that acceptance of the current version is not required and that the user has accepted the prior version, removing, using the one or more computing systems, the current version of the electronic document from the selected subset of electronic documents; and outputting, using the one or more computing systems, informational data pertaining to the selected subset of electronic documents for presenting the selected subset of electronic documents to the user involved in the transaction for acceptance as part of the transaction. 2. The method of claim 1 , wherein the root electronic document is an empty electronic document without content for presenting to the user and serves to identify the dependency electronic documents.

9. One or more computer-storage media having embodied thereon a data structure for a first schema describing a data store, the data structure being useable by a computing device to query the data store, the data structure comprising: a first property description element describing a first individual property of the data store including one or more static attributes and one or more contextual attributes that combine to describe the first individual property wherein each static attribute has a corresponding static attribute value and each contextual attribute has a corresponding contextual attribute value, wherein a static attribute associated with the first individual property is immutable and has the same static attribute value within all schemas that include the first individual property, wherein a contextual attribute is able to have different contextual attribute values among different schemas that include the first individual property, and wherein contextual attribute values are defined within each schema that has the contextual attribute; a property reference element describing a second individual property of the data store by referencing a second property description element from a second schema that includes static attributes and corresponding static attribute values wherein the property reference specifies contextual attributes and corresponding contextual attribute values, wherein the static attributes apply to all schemas that reference the second property description element, and wherein the contextual attributes apply only to the first schema: an item type description element describing an item type for at least one item in the data store, the item type description element including one or more properties that define the item type; and a kind description element describing a kind for at least one item in the data store, the kind description element including one or more properties for the kind, wherein the kind is a collection of logically related item types.

9. One or more computer-storage media having embodied thereon a data structure for a first schema describing a data store, the data structure being useable by a computing device to query the data store, the data structure comprising: a first property description element describing a first individual property of the data store including one or more static attributes and one or more contextual attributes that combine to describe the first individual property wherein each static attribute has a corresponding static attribute value and each contextual attribute has a corresponding contextual attribute value, wherein a static attribute associated with the first individual property is immutable and has the same static attribute value within all schemas that include the first individual property, wherein a contextual attribute is able to have different contextual attribute values among different schemas that include the first individual property, and wherein contextual attribute values are defined within each schema that has the contextual attribute; a property reference element describing a second individual property of the data store by referencing a second property description element from a second schema that includes static attributes and corresponding static attribute values wherein the property reference specifies contextual attributes and corresponding contextual attribute values, wherein the static attributes apply to all schemas that reference the second property description element, and wherein the contextual attributes apply only to the first schema: an item type description element describing an item type for at least one item in the data store, the item type description element including one or more properties that define the item type; and a kind description element describing a kind for at least one item in the data store, the kind description element including one or more properties for the kind, wherein the kind is a collection of logically related item types. 11. The one or more computer-storage media of claim 9 , where the data structure further comprises a property reference list element that acts as a container for one or more property reference elements within the first schema.

20. The apparatus of claim 14 , wherein the operation command is a configuration command for configuring a function or attribute of a function of the one or more network devices.

20. The apparatus of claim 14 , wherein the operation command is a configuration command for configuring a function or attribute of a function of the one or more network devices. 22. The apparatus of claim 20 , wherein the processor is configured to generate information that configures a service on the one or more network devices device based on the configuration command.

1. A computer-implemented method of extracting information from co-occurring Hyper Text Mark-up Language (HTML) structured documents, the method comprising: presenting a list of web sites to a user; receiving one or more of the web sites selected from the user for data extraction; collecting a plurality of co-occurring different HTML structured documents for each of the selected web sites at a computer comprising a processor; forming a plurality of clusters comprising different subsets of the co-occurring HTML structured documents, wherein: each cluster comprises a different HTML structured document of the plurality of co-occurring HTML structured documents as a centroid document and other HTML structured documents of the plurality of co-occurring HTML structured documents that achieve a threshold of similarity with respect to the centroid document, the clusters are formed by comparing each co-occurring HTML structured document to each centroid document of each cluster based on relative structural similarity of HTML data structure of each co-occurring HTML structured document with respect to HTML data structure of each centroid document of each cluster, an alignment algorithm is used to determine the co-occurring HTML structured documents that achieve the threshold of similarity with respect to each centroid document by comparing structured locations of data fields for storing data elements within each centroid document and structured locations of corresponding data fields for storing data elements within each of the co-occurring HTML structured documents, the co-occurring HTML structured documents are compared to each centroid document based on similarity of structured locations of corresponding data fields within the HTML data structures without regard to content of data elements stored in the corresponding data fields within the HTML data structures, and the relative structural similarity of a particular co-occurring HTML structured document with respect to a particular centroid document is penalized when the co-occurring HTML structured document includes a data field that is within the particular centroid document in a different structured location; displaying a list of clusters; displaying the centroid document of a particular cluster selected from the list of clusters; marking a data element on the centroid document of the particular cluster; identifying a data element on each of the other HTML structured documents of the particular cluster that is stored within a data field having a structured location that corresponds to the structured location of the data field storing the marked data element within the centroid document of the particular cluster; and providing a user interface displaying content of data elements identified from the other HTML structured documents of the particular cluster on a computer display.

1. A computer-implemented method of extracting information from co-occurring Hyper Text Mark-up Language (HTML) structured documents, the method comprising: presenting a list of web sites to a user; receiving one or more of the web sites selected from the user for data extraction; collecting a plurality of co-occurring different HTML structured documents for each of the selected web sites at a computer comprising a processor; forming a plurality of clusters comprising different subsets of the co-occurring HTML structured documents, wherein: each cluster comprises a different HTML structured document of the plurality of co-occurring HTML structured documents as a centroid document and other HTML structured documents of the plurality of co-occurring HTML structured documents that achieve a threshold of similarity with respect to the centroid document, the clusters are formed by comparing each co-occurring HTML structured document to each centroid document of each cluster based on relative structural similarity of HTML data structure of each co-occurring HTML structured document with respect to HTML data structure of each centroid document of each cluster, an alignment algorithm is used to determine the co-occurring HTML structured documents that achieve the threshold of similarity with respect to each centroid document by comparing structured locations of data fields for storing data elements within each centroid document and structured locations of corresponding data fields for storing data elements within each of the co-occurring HTML structured documents, the co-occurring HTML structured documents are compared to each centroid document based on similarity of structured locations of corresponding data fields within the HTML data structures without regard to content of data elements stored in the corresponding data fields within the HTML data structures, and the relative structural similarity of a particular co-occurring HTML structured document with respect to a particular centroid document is penalized when the co-occurring HTML structured document includes a data field that is within the particular centroid document in a different structured location; displaying a list of clusters; displaying the centroid document of a particular cluster selected from the list of clusters; marking a data element on the centroid document of the particular cluster; identifying a data element on each of the other HTML structured documents of the particular cluster that is stored within a data field having a structured location that corresponds to the structured location of the data field storing the marked data element within the centroid document of the particular cluster; and providing a user interface displaying content of data elements identified from the other HTML structured documents of the particular cluster on a computer display. 8. The method of claim 1 , further comprising extracting data from the other HTML structured documents of the particular cluster based on the identified data element on each of the other HTML structured documents of the particular cluster.

1. A method implemented in a computer system for translating content, wherein the content has an author who is part of a social network, the method comprising: receiving the content by the computer system; retrieving from the social network, by the computer system, contextual information associated with the content; retrieving from the social network, by the computer system, author information associated with the author; creating, by the computer system, a content-specific dictionary based upon the retrieved contextual information and the retrieved author information; creating, by the computer system, a translation profile based upon the retrieved contextual information, the retrieved author information and the created content-specific dictionary; determining, by the computer system, one of a plurality of generic dictionaries to use for the translating, wherein the determination of the one of the plurality of generic dictionaries to use is based upon the translation profile; and translating the received content by the computer system, using the content-specific dictionary and the determined one of the plurality of generic dictionaries to use.

1. A method implemented in a computer system for translating content, wherein the content has an author who is part of a social network, the method comprising: receiving the content by the computer system; retrieving from the social network, by the computer system, contextual information associated with the content; retrieving from the social network, by the computer system, author information associated with the author; creating, by the computer system, a content-specific dictionary based upon the retrieved contextual information and the retrieved author information; creating, by the computer system, a translation profile based upon the retrieved contextual information, the retrieved author information and the created content-specific dictionary; determining, by the computer system, one of a plurality of generic dictionaries to use for the translating, wherein the determination of the one of the plurality of generic dictionaries to use is based upon the translation profile; and translating the received content by the computer system, using the content-specific dictionary and the determined one of the plurality of generic dictionaries to use. 6. The method of claim 1 , wherein the author information comprises at least one of: (a) a writing style of the author; (b) a language style of the author; (c) a background of the author; (d) one or more personal preferences of the author; or (e) any combination thereof.

10. A computer program product for policy to source code conversion, the computer program product comprising a non-transitory computer readable storage medium having computer-readable program code embodied thereon, which when executed by a computer processor, causes the computer processor to implement a method, the method comprising: receiving policy information in a natural language format; parsing the policy information into a plurality of component strings; performing pattern matching for the plurality of component strings against a list of patterns to produce a reformatted policy; accessing class generator data comprising a plurality of classes and relationships between the classes; identifying at least one class in the plurality of classes and at least one data value associated with the at least one class in the reformatted policy, the identifying based on the class generator data; identifying a class name from a list of synonyms in the class generator data as the at least one class based on the reformatted policy; expanding the at least one data value into a complete list of possible values by expanding numerical values expressed as a range or wildcard into all of the possible values covered by the range or wildcard; creating class instances for each value in the complete list of possible values, the class instances named based on the class name from the list of synonyms in combination with each value in the complete list of possible values; and generating source code from the class instances, the source code configured to create subsequent instances of the class instances.

10. A computer program product for policy to source code conversion, the computer program product comprising a non-transitory computer readable storage medium having computer-readable program code embodied thereon, which when executed by a computer processor, causes the computer processor to implement a method, the method comprising: receiving policy information in a natural language format; parsing the policy information into a plurality of component strings; performing pattern matching for the plurality of component strings against a list of patterns to produce a reformatted policy; accessing class generator data comprising a plurality of classes and relationships between the classes; identifying at least one class in the plurality of classes and at least one data value associated with the at least one class in the reformatted policy, the identifying based on the class generator data; identifying a class name from a list of synonyms in the class generator data as the at least one class based on the reformatted policy; expanding the at least one data value into a complete list of possible values by expanding numerical values expressed as a range or wildcard into all of the possible values covered by the range or wildcard; creating class instances for each value in the complete list of possible values, the class instances named based on the class name from the list of synonyms in combination with each value in the complete list of possible values; and generating source code from the class instances, the source code configured to create subsequent instances of the class instances. 13. The computer program product of claim 10 , wherein the policy is a healthcare policy, the instance of the at least one class is a Common LISP Object, the source code is Java source code, and the natural language format is one of: a text format and an audio format.

13. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving audio data corresponding to an utterance that is spoken by a user of a device and that includes a voice command trigger term and an entity name that is a proper noun; generating, by an automated speech recognizer, a first phonetic representation of a first portion of the utterance that is associated with the entity name that is a proper noun, wherein the first phonetic pronunciation does not phonetically correspond to a previously available phonetic pronunciation of the entity name; generating, by the automated speech recognizer, an initial transcription that (i) is based on the first phonetic representation of the first portion of the utterance, and (ii) includes a transcription of a term that is not a proper noun; in response to the generation of the initial transcription that includes a transcription of the term that is not a proper noun, prompting a user for feedback, wherein prompting the user for feedback comprises: providing, for output to the user on a graphical user interface of the device, a representation of the initial transcription that (i) is based on the first phonetic pronunciation of the first portion of the utterance, and (ii) includes the transcription of the term that is not a proper noun; providing, for output to the user on the graphical user interface, multiple entity names from a set of entity names stored in the pronunciation dictionary, wherein the multiple entity names that are provided for output on the graphical user interface include both (i) entity names that are phonetically close to the entity name included in the utterance, and (ii) entity names that are phonetically unrelated to the entity name included in the utterance; and receiving data corresponding to a selection by the user of a particular entity name of the multiple entity names; generating a different transcription based on the received data corresponding to the particular entity name selected by the user, wherein the different transcription includes an entity name that does not phonetically correspond to the first phonetic representation; updating the pronunciation dictionary to associate (i) the first phonetic representation of the first portion of the utterance that corresponds to the portion of the utterance that is associated with the entity name that is a proper noun with (ii) the entity name in the pronunciation dictionary corresponding to the different transcription that does not phonetically correspond to the first phonetic representation; receiving a subsequent utterance that includes the entity name; and transcribing the subsequent utterance based at least in part on the updated pronunciation dictionary.

13. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving audio data corresponding to an utterance that is spoken by a user of a device and that includes a voice command trigger term and an entity name that is a proper noun; generating, by an automated speech recognizer, a first phonetic representation of a first portion of the utterance that is associated with the entity name that is a proper noun, wherein the first phonetic pronunciation does not phonetically correspond to a previously available phonetic pronunciation of the entity name; generating, by the automated speech recognizer, an initial transcription that (i) is based on the first phonetic representation of the first portion of the utterance, and (ii) includes a transcription of a term that is not a proper noun; in response to the generation of the initial transcription that includes a transcription of the term that is not a proper noun, prompting a user for feedback, wherein prompting the user for feedback comprises: providing, for output to the user on a graphical user interface of the device, a representation of the initial transcription that (i) is based on the first phonetic pronunciation of the first portion of the utterance, and (ii) includes the transcription of the term that is not a proper noun; providing, for output to the user on the graphical user interface, multiple entity names from a set of entity names stored in the pronunciation dictionary, wherein the multiple entity names that are provided for output on the graphical user interface include both (i) entity names that are phonetically close to the entity name included in the utterance, and (ii) entity names that are phonetically unrelated to the entity name included in the utterance; and receiving data corresponding to a selection by the user of a particular entity name of the multiple entity names; generating a different transcription based on the received data corresponding to the particular entity name selected by the user, wherein the different transcription includes an entity name that does not phonetically correspond to the first phonetic representation; updating the pronunciation dictionary to associate (i) the first phonetic representation of the first portion of the utterance that corresponds to the portion of the utterance that is associated with the entity name that is a proper noun with (ii) the entity name in the pronunciation dictionary corresponding to the different transcription that does not phonetically correspond to the first phonetic representation; receiving a subsequent utterance that includes the entity name; and transcribing the subsequent utterance based at least in part on the updated pronunciation dictionary. 17. The computer-readable medium of claim 13 , wherein the operations further comprise: in response to updating a pronunciation dictionary to include the first phonetic representation, increasing a global counter associated with the first phonetic representation.

15. The method of claim 12 , further comprising: receiving a meaningful second text sequence; neurolinguistically analyzing the second text sequence by: extracting elements from the second text sequence; and conducting a second comparison by comparing the elements extracted from the second text sequence to predetermined elements associated with cognitive motivation orientations; wherein second statistical information is derived from the second comparison; the method further comprising determining, based on the second statistical information, a second dominant cognitive motivation orientation set that is expressed within the second text sequence based on the second statistical information; testing fit between the first dominant cognitive motivation orientation set and the second dominant cognitive motivation orientation set; and responsive to a determination that the second dominant cognitive motivation orientation set misfits the first dominant cognitive motivation orientation set, including in the message an identification of the misfit between the second dominant cognitive motivation orientation set and the first dominant cognitive motivation set.

15. The method of claim 12 , further comprising: receiving a meaningful second text sequence; neurolinguistically analyzing the second text sequence by: extracting elements from the second text sequence; and conducting a second comparison by comparing the elements extracted from the second text sequence to predetermined elements associated with cognitive motivation orientations; wherein second statistical information is derived from the second comparison; the method further comprising determining, based on the second statistical information, a second dominant cognitive motivation orientation set that is expressed within the second text sequence based on the second statistical information; testing fit between the first dominant cognitive motivation orientation set and the second dominant cognitive motivation orientation set; and responsive to a determination that the second dominant cognitive motivation orientation set misfits the first dominant cognitive motivation orientation set, including in the message an identification of the misfit between the second dominant cognitive motivation orientation set and the first dominant cognitive motivation set. 17. The method of claim 15 , wherein the first text sequence is an e-mail message and the second text sequence is an unsent e-mail response to the first text sequence.

1. A computer-implemented method executed by one or more processors of a social video search system, the method comprising: receiving a query from a user; obtaining, by the one or more processors, social context information about interactions of the user from a social graph; obtaining, by the one or more processors, a search result using the query; generating, by the one or more processors, an annotation for at least one search result where the annotation indicates the association with a particular source and the relation to the user; and providing, for display to the user, the modified search result and the annotation.

1. A computer-implemented method executed by one or more processors of a social video search system, the method comprising: receiving a query from a user; obtaining, by the one or more processors, social context information about interactions of the user from a social graph; obtaining, by the one or more processors, a search result using the query; generating, by the one or more processors, an annotation for at least one search result where the annotation indicates the association with a particular source and the relation to the user; and providing, for display to the user, the modified search result and the annotation. 9. The method of claim 1 further comprising sending a section divider that is a selectable link for retrieving additional results modified in rank by the social context information.

9. The apparatus of claim 1, wherein said first selection means comprises a plurality of operator-controlled keys, at least some of which are arranged in a predetermined matrix of columns and rows, and a first character set selection key that, when actuated, enables said at least some keys to individually select characters of said first set.

9. The apparatus of claim 1, wherein said first selection means comprises a plurality of operator-controlled keys, at least some of which are arranged in a predetermined matrix of columns and rows, and a first character set selection key that, when actuated, enables said at least some keys to individually select characters of said first set. 13. The apparatus of claim 9, wherein said second selection means includes a cursor display device capable of positioning a cursor in said second display area of said display means adjacent a character of said second set to be selected in order to generate a signal indicative of the position of said selected character in said second display area.

20. A computer implemented method for representing, using, and maintaining regulatory knowledge comprising: providing a knowledge base model for representation of regulatory knowledge, the knowledge base model including a plurality of entities represented and defined by at least one feature-value pair, wherein the feature's values may take multiple formats including numbers, flags, dates, symbolic concepts or relations to symbolic concepts, and relations to other entities, the plurality of entities including: (i) regulations, (ii) symbolic concepts, wherein the symbolic concept includes a structure containing a designated relation that allows for representing a hierarchy of concepts, (iii) procedures, (iv) parameters, (v) decisions, wherein decisions are described by the following additional features: problem statements that are text templates with placeholders that point to other elements of the knowledge base model, the decision type feature having a plurality of symbolic values that designate a type of decision, (vi) rules, wherein rules have relationships to decisions they make, and (vii) service calls, wherein service calls are described by the following additional features: service call message text templates with placeholders that point to other elements of the knowledge base model, and a service call type feature having a plurality of symbolic values that designate a type of a service call, and wherein the service call when executed by an external control apparatus causes certain actions to be taken by certain external software modules, and results of those actions may be returned back for storage; providing a data interface model for representation of data referred to by elements of the knowledge base model, the data interface model comprising a plurality of entities represented and defined by at least one feature-value pair, wherein the feature's values may take multiple formats including numbers, flags, dates, symbolic concepts or relations to symbolic concepts, relations to other entities of the regulatory knowledge base model or to other elements of the data interface model, the plurality of entities including: (i) simple events, (ii) complex events that contain summaries and relationships to simple events, (iii) entities that are referred to by simple events and complex events and that relate to elements of the knowledge base model, and (iv) profiles of entities; providing an interface module; receiving in the interface module an input request in the form of a structured or semi-structured format text message; sending the received input request to a reasoning engine; receiving in the reasoning engine the input request from the interface module; matching the received input request to rules included in a reasoning engine rule base; applying the rules to an internal algorithm; executing the internal algorithm to resolve the input request; producing an output response; sending the output response to the interface module; receiving in the interface module the output response from the reasoning engine; providing a reasoning session model for representation of the reasoning process data, the reasoning session model comprising: (i) a data structure that supports storage of reasoning session records, and (ii) a data structure that supports storage of session events, wherein each session event represents an individual decision that is made using the computer implemented method.

20. A computer implemented method for representing, using, and maintaining regulatory knowledge comprising: providing a knowledge base model for representation of regulatory knowledge, the knowledge base model including a plurality of entities represented and defined by at least one feature-value pair, wherein the feature's values may take multiple formats including numbers, flags, dates, symbolic concepts or relations to symbolic concepts, and relations to other entities, the plurality of entities including: (i) regulations, (ii) symbolic concepts, wherein the symbolic concept includes a structure containing a designated relation that allows for representing a hierarchy of concepts, (iii) procedures, (iv) parameters, (v) decisions, wherein decisions are described by the following additional features: problem statements that are text templates with placeholders that point to other elements of the knowledge base model, the decision type feature having a plurality of symbolic values that designate a type of decision, (vi) rules, wherein rules have relationships to decisions they make, and (vii) service calls, wherein service calls are described by the following additional features: service call message text templates with placeholders that point to other elements of the knowledge base model, and a service call type feature having a plurality of symbolic values that designate a type of a service call, and wherein the service call when executed by an external control apparatus causes certain actions to be taken by certain external software modules, and results of those actions may be returned back for storage; providing a data interface model for representation of data referred to by elements of the knowledge base model, the data interface model comprising a plurality of entities represented and defined by at least one feature-value pair, wherein the feature's values may take multiple formats including numbers, flags, dates, symbolic concepts or relations to symbolic concepts, relations to other entities of the regulatory knowledge base model or to other elements of the data interface model, the plurality of entities including: (i) simple events, (ii) complex events that contain summaries and relationships to simple events, (iii) entities that are referred to by simple events and complex events and that relate to elements of the knowledge base model, and (iv) profiles of entities; providing an interface module; receiving in the interface module an input request in the form of a structured or semi-structured format text message; sending the received input request to a reasoning engine; receiving in the reasoning engine the input request from the interface module; matching the received input request to rules included in a reasoning engine rule base; applying the rules to an internal algorithm; executing the internal algorithm to resolve the input request; producing an output response; sending the output response to the interface module; receiving in the interface module the output response from the reasoning engine; providing a reasoning session model for representation of the reasoning process data, the reasoning session model comprising: (i) a data structure that supports storage of reasoning session records, and (ii) a data structure that supports storage of session events, wherein each session event represents an individual decision that is made using the computer implemented method. 24. The method of claim 20 , wherein the knowledge base model is represented as an ontological model.

1. A control system for communication robot for supporting input of interactive actions to be performed by a communication robot, comprising: a first storage storing in advance information on a plurality of behaviors associated with a plurality of behavior programs including a spontaneous behavior program for performing a spontaneous behavior and a reflex behavior program prepared with inclusion of determination of a precondition and for performing a reflex behavior in response to behavior of a person when the precondition is satisfied; a displayer displaying on a display a list of said plurality of behaviors in a user-selectable manner based on said information stored in said first storage; a detector detecting a user's operation to an input device to select a behavior to be performed by said communication robot from said list of behaviors displayed by said displayer; a behavior decider deciding the behavior to be performed by said communication robot on the basis of a detection result by said detector; a second storage storing the behavior decided by said behavior decider as input history information; an accumulator accumulating a plurality of input history information stored by said second storage; and a generator generating reproductive motion information for interactive actions to be performed by said communication robot on the basis of the plurality of input history information accumulated by said accumulator.

1. A control system for communication robot for supporting input of interactive actions to be performed by a communication robot, comprising: a first storage storing in advance information on a plurality of behaviors associated with a plurality of behavior programs including a spontaneous behavior program for performing a spontaneous behavior and a reflex behavior program prepared with inclusion of determination of a precondition and for performing a reflex behavior in response to behavior of a person when the precondition is satisfied; a displayer displaying on a display a list of said plurality of behaviors in a user-selectable manner based on said information stored in said first storage; a detector detecting a user's operation to an input device to select a behavior to be performed by said communication robot from said list of behaviors displayed by said displayer; a behavior decider deciding the behavior to be performed by said communication robot on the basis of a detection result by said detector; a second storage storing the behavior decided by said behavior decider as input history information; an accumulator accumulating a plurality of input history information stored by said second storage; and a generator generating reproductive motion information for interactive actions to be performed by said communication robot on the basis of the plurality of input history information accumulated by said accumulator. 6. A control system for communication robot as set forth in claim 1 , further comprising a transmitter, when said behavior decider has decided the behavior to be performed by said communication robot, transmitting an execution instruction for said behavior to said communication robot.

6. A system for processing natural language utterances that include requests, and selecting and presenting advertisements based thereon, the system comprising: one or more physical processors programmed with computer program instructions which, when executed, cause the one or more physical processors to: provide a natural language utterance as an input to a speech recognition engine; receive words or phrases, recognized from the natural language utterance, as an output of the speech recognition engine; provide the words or phrases as an input to a conversational language processor; receive, from the conversational language processor, an interpretation of the natural language utterance based on the recognized words or phrases; determine a context for the natural language utterance based at least on the recognized words or phrases; determine that the natural language utterance includes a cross-application request based on the interpretation of the natural language utterance, the cross-application request comprising at least a first request and a second request to be serviced by different context-appropriate applications; provide the first request to a first application to service the first request; provide the second request to a second application to service the second request; select an advertisement based at least on the determined context and either or both of the first request or the second request; generate a service output responsive to the natural language utterance, the service output comprising: (i) a first output received from the first application responsive to the first request; (ii) a second output received from the second application responsive to the second request; and (iii) the selected advertisement; and provide the service output via an output device.

6. A system for processing natural language utterances that include requests, and selecting and presenting advertisements based thereon, the system comprising: one or more physical processors programmed with computer program instructions which, when executed, cause the one or more physical processors to: provide a natural language utterance as an input to a speech recognition engine; receive words or phrases, recognized from the natural language utterance, as an output of the speech recognition engine; provide the words or phrases as an input to a conversational language processor; receive, from the conversational language processor, an interpretation of the natural language utterance based on the recognized words or phrases; determine a context for the natural language utterance based at least on the recognized words or phrases; determine that the natural language utterance includes a cross-application request based on the interpretation of the natural language utterance, the cross-application request comprising at least a first request and a second request to be serviced by different context-appropriate applications; provide the first request to a first application to service the first request; provide the second request to a second application to service the second request; select an advertisement based at least on the determined context and either or both of the first request or the second request; generate a service output responsive to the natural language utterance, the service output comprising: (i) a first output received from the first application responsive to the first request; (ii) a second output received from the second application responsive to the second request; and (iii) the selected advertisement; and provide the service output via an output device. 8. The system of claim 6 , wherein the one or more physical processors are further programmed to: use an environmental model to determine environmental information, wherein the context for the natural language utterance is determined based further on the environmental information.

1. A method for generating speech based on text in one or more languages, implemented at least in part by a computer, the method comprising: providing a phone set for a plurality of languages, the phone set comprising a union of phones of the plurality of languages; training, for the plurality of languages, a multilingual hidden Markov model (HMM) comprising state level sharing across the plurality of languages based on language sentences in each of the plurality of languages without any sentences including a mixture of more than one language; tying states of the multilingual HMM across the plurality of languages and clustering the tied states across the plurality of languages into a single decision based at least in part on a language independent question and a language specific question; receiving text in one or more of the plurality of languages of the multilingual HMM; and generating speech, for the received text, based at least in part on the multilingual HMM.

1. A method for generating speech based on text in one or more languages, implemented at least in part by a computer, the method comprising: providing a phone set for a plurality of languages, the phone set comprising a union of phones of the plurality of languages; training, for the plurality of languages, a multilingual hidden Markov model (HMM) comprising state level sharing across the plurality of languages based on language sentences in each of the plurality of languages without any sentences including a mixture of more than one language; tying states of the multilingual HMM across the plurality of languages and clustering the tied states across the plurality of languages into a single decision based at least in part on a language independent question and a language specific question; receiving text in one or more of the plurality of languages of the multilingual HMM; and generating speech, for the received text, based at least in part on the multilingual HMM. 3. The method of claim 1 , wherein the tied states comprise context-dependent states.

1. A method, comprising: determining, via at least one of one or more computing devices implementing a documentation system in response to obtaining a document for publishing in a node in the documentation system, whether the document corresponds to a topic identifier, the topic identifier uniquely identifying a node within the documentation system, the node corresponding to a plurality of documentation topics; assigning, via at least one of the one or more computing devices, the topic identifier to the document in response to determining that the document has not been assigned the topic identifier; converting, via at least one of the one or more computing devices, topic content associated with the document into a storage format, the storage format being a platform independent format; storing, via at least one of the one or more computing devices, the document in a data store in communication with the at least one computing device, the data store associated with the documentation system, the document being stored in the storage format; triggering, via at least one of the one or more computing devices, conversion of a plurality of documents associated with the node from the storage format to a plurality of publication formats in response to storage of the document, the plurality of publication formats configured for presentation on a client; identifying, via at least one of the one or more computing devices, a respective publication format associated with a respective client device; and transmitting, via at least one of the one or more computing devices, the respective publication format to the respective client device.

1. A method, comprising: determining, via at least one of one or more computing devices implementing a documentation system in response to obtaining a document for publishing in a node in the documentation system, whether the document corresponds to a topic identifier, the topic identifier uniquely identifying a node within the documentation system, the node corresponding to a plurality of documentation topics; assigning, via at least one of the one or more computing devices, the topic identifier to the document in response to determining that the document has not been assigned the topic identifier; converting, via at least one of the one or more computing devices, topic content associated with the document into a storage format, the storage format being a platform independent format; storing, via at least one of the one or more computing devices, the document in a data store in communication with the at least one computing device, the data store associated with the documentation system, the document being stored in the storage format; triggering, via at least one of the one or more computing devices, conversion of a plurality of documents associated with the node from the storage format to a plurality of publication formats in response to storage of the document, the plurality of publication formats configured for presentation on a client; identifying, via at least one of the one or more computing devices, a respective publication format associated with a respective client device; and transmitting, via at least one of the one or more computing devices, the respective publication format to the respective client device. 6. The method of claim 1 , further comprising: generating, via at least one of the one or more computing devices, a user interface facilitating selection of a plurality of documents for submission to the documentation system; and assigning, in the client, a node identifier corresponding to the node with which the plurality of documents are associated.

1. A deception management system (DMS) to detect attackers within a network of computer resources, comprising: a deception deployer planting one or more decoy attack vectors in memory or storage of one or more real resources in the network, an attack vector, of the one or more decoy attack vectors, being an object in a real resource of the network that has a potential to lead an attacker to access or discover a decoy resource of the network; a deception adaptor self-triggering modification of activity logs of login access and data editing for one or more decoy resources, the one or more decoy resources appearing to the attacker as being active in the network; and an access governor authorizing access to resources in the network, and issuing a notification upon recognizing an attempt to access one or more of the decoy resources of the network via one or more of the decoy attack vectors planted by said deception deployer.

1. A deception management system (DMS) to detect attackers within a network of computer resources, comprising: a deception deployer planting one or more decoy attack vectors in memory or storage of one or more real resources in the network, an attack vector, of the one or more decoy attack vectors, being an object in a real resource of the network that has a potential to lead an attacker to access or discover a decoy resource of the network; a deception adaptor self-triggering modification of activity logs of login access and data editing for one or more decoy resources, the one or more decoy resources appearing to the attacker as being active in the network; and an access governor authorizing access to resources in the network, and issuing a notification upon recognizing an attempt to access one or more of the decoy resources of the network via one or more of the decoy attack vectors planted by said deception deployer. 2. The DMS of claim 1 wherein said deception deployer generates the one or more decoy resources.

9. A system for merging search results, comprising: one or more processing units configured to: identify a query from a user; split the query into sub-queries; for each of the sub-queries, determine a user importance value for said each sub-query to quantify how important said each sub-query is to the user relative to how important the others of the sub-queries are to the user, execute said each sub-query to obtain a search result for said each sub-query and using the user importance value determined for said each sub-query to assign a user relevance score to the search result obtained for said each sub-query; and combine the search results for the sub-queries based on the user relevance scores assigned to the search results to obtain merged search results; and wherein: the execution of each of the sub-queries includes identifying a multitude of search results for at least one of the sub-queries; the combining includes grouping said multitude of search results into a plurality of clusters, and computing a relevance score for each of said clusters, wherein each cluster represents a high level entity; the determining a user importance value for said each sub-query includes identifying one of the sub-queries as a primary focus, and identifying another of the sub-queries as providing context, computing a probability p(Q) of each of the sub-queries, and computing information content of each of the sub-queries as log p(Q); and the combining the search results further includes, once the information content of the sub-queries are computed, merging the search results.

9. A system for merging search results, comprising: one or more processing units configured to: identify a query from a user; split the query into sub-queries; for each of the sub-queries, determine a user importance value for said each sub-query to quantify how important said each sub-query is to the user relative to how important the others of the sub-queries are to the user, execute said each sub-query to obtain a search result for said each sub-query and using the user importance value determined for said each sub-query to assign a user relevance score to the search result obtained for said each sub-query; and combine the search results for the sub-queries based on the user relevance scores assigned to the search results to obtain merged search results; and wherein: the execution of each of the sub-queries includes identifying a multitude of search results for at least one of the sub-queries; the combining includes grouping said multitude of search results into a plurality of clusters, and computing a relevance score for each of said clusters, wherein each cluster represents a high level entity; the determining a user importance value for said each sub-query includes identifying one of the sub-queries as a primary focus, and identifying another of the sub-queries as providing context, computing a probability p(Q) of each of the sub-queries, and computing information content of each of the sub-queries as log p(Q); and the combining the search results further includes, once the information content of the sub-queries are computed, merging the search results. 10. The system according to claim 9 , wherein: the execution of each of the sub-queries includes identifying a multitude of entities for the at least one of the sub-queries; and the combining includes grouping said multitude of entities into the plurality of clusters, and merging the clusters based on the relevance scores computed for the clusters.

1. A computer implemented method of detecting global variables in JAVASCRIPT code, and adding local variables in place of said global variables, comprising: receiving by a processor a JAVASCRIPT code containing at least one of a plurality of globally defined functions; generating by the processor at least one call flow graph for each one of said at least one of globally defined functions; generating by the processor an inter-procedural control flow graph for each one of said call flow graph; generating by the processor an inter-procedural dominator graph for each one of said inter-procedural control flow graph; identifying by the processor each of referenced global variables within each of said inter-procedural dominator graph and determining a JAVASCRIPT scope of each of referenced global variables; identifying by the processor at least one of: one or more confined global variables which receive a value within a first JAVASCRIPT scope of each referenced global variable wherein said value is not referenced outside of said first JAVASCRIPT scope, and one or more repeating global variables accessed repeatedly within a second JAVASCRIPT scope of each referenced global variable; and automatically adding by the processor local variables in place of at least one of said confined global variables and said repeating global variables.

1. A computer implemented method of detecting global variables in JAVASCRIPT code, and adding local variables in place of said global variables, comprising: receiving by a processor a JAVASCRIPT code containing at least one of a plurality of globally defined functions; generating by the processor at least one call flow graph for each one of said at least one of globally defined functions; generating by the processor an inter-procedural control flow graph for each one of said call flow graph; generating by the processor an inter-procedural dominator graph for each one of said inter-procedural control flow graph; identifying by the processor each of referenced global variables within each of said inter-procedural dominator graph and determining a JAVASCRIPT scope of each of referenced global variables; identifying by the processor at least one of: one or more confined global variables which receive a value within a first JAVASCRIPT scope of each referenced global variable wherein said value is not referenced outside of said first JAVASCRIPT scope, and one or more repeating global variables accessed repeatedly within a second JAVASCRIPT scope of each referenced global variable; and automatically adding by the processor local variables in place of at least one of said confined global variables and said repeating global variables. 3. The method of claim 1 , further comprising generating the at least one call flow graph from each code segment by a static analysis JAVASCRIPT tool.

7. A computer system for comparing items of anonymized data, the computer system comprising: one or more computer processors, one or more computer readable storage media, and program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to receive a plurality of items of data, each item of the plurality of items of data comprising an anonymized ordered list of words, wherein each word of the anonymized ordered list of words is anonymized in a plurality of forms and is associated with a respective item of data, wherein the plurality of forms comprise: a respective word of the anonymized ordered list of words as the respective word originally appeared, a variation of the respective word, and a metaphone encoding of the respective word; and program instructions to compare a first item of the plurality of items of data with a second item of the plurality of items of data by: comparing each of the plurality of forms of each word in the first item with the corresponding form of each corresponding word in the second item; scoring each comparison of each word in the first item with each respective word in the second item based on: a degree of matching between each of the plurality of forms of each word in the first item with the corresponding form of each corresponding word in the second item; a plurality of weights assigned to each corresponding form of the plurality of forms, wherein a first weight is assigned to the respective word of the anonymized ordered list of words as the respective word originally appeared, a second weight is assigned to the variation of the respective word, and a third weight is assigned to the metaphone encoding of the respective word; and wherein the first weight exceeds the second weight and the second weight exceeds the third weight; and computing a total score for the comparison of the first item and the second item based on the scoring.

7. A computer system for comparing items of anonymized data, the computer system comprising: one or more computer processors, one or more computer readable storage media, and program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to receive a plurality of items of data, each item of the plurality of items of data comprising an anonymized ordered list of words, wherein each word of the anonymized ordered list of words is anonymized in a plurality of forms and is associated with a respective item of data, wherein the plurality of forms comprise: a respective word of the anonymized ordered list of words as the respective word originally appeared, a variation of the respective word, and a metaphone encoding of the respective word; and program instructions to compare a first item of the plurality of items of data with a second item of the plurality of items of data by: comparing each of the plurality of forms of each word in the first item with the corresponding form of each corresponding word in the second item; scoring each comparison of each word in the first item with each respective word in the second item based on: a degree of matching between each of the plurality of forms of each word in the first item with the corresponding form of each corresponding word in the second item; a plurality of weights assigned to each corresponding form of the plurality of forms, wherein a first weight is assigned to the respective word of the anonymized ordered list of words as the respective word originally appeared, a second weight is assigned to the variation of the respective word, and a third weight is assigned to the metaphone encoding of the respective word; and wherein the first weight exceeds the second weight and the second weight exceeds the third weight; and computing a total score for the comparison of the first item and the second item based on the scoring. 9. The computer system of claim 7 , wherein program instructions to compute the total score are further based on a first value associated with unmatched words, based on the degree of matching, in the longer set of the first item and the second item and a second value associated with unmatched words, based on the degree of matching, in the shorter item of the first item and second item, wherein the first value is less than the second value.

46. The search engine of claim 44 , wherein the bitcheck command contains a bitmap including a plurality of compliance bits, each indicating whether a corresponding reference character of a general set of characters is a member of the specified set of characters.

46. The search engine of claim 44 , wherein the bitcheck command contains a bitmap including a plurality of compliance bits, each indicating whether a corresponding reference character of a general set of characters is a member of the specified set of characters. 50. The search engine of claim 46 , wherein the regular expression further includes an exact pattern, a third of the commands comprises a check string command embodying the exact pattern, and the means for processing further comprises: means for executing the check string command in a third of the processors to determine whether the input string matches the exact pattern.

8. A non-transitory computer-readable, tangible data storage memory device having recorded thereon instructions that, when executed, cause a processor to perform operations that comprise: receiving, at a computer system, a source version of an electronic document in a source format; processing the electronic document to generate a target version of the electronic document in a target format, the processing comprising compressing of one or more images embedded in the source version of the electronic document, compressing one or more Type 1 fonts embedded in the source version of the electronic document, and unifying object duplicates embedded in the source version of the electronic document, the target version of the electronic document in the target format including both the compressed one or more images and the compressed one or more Type 1 fonts and excluding one of each of the object duplicates; and outputting the target version of the electronic document in the target.

8. A non-transitory computer-readable, tangible data storage memory device having recorded thereon instructions that, when executed, cause a processor to perform operations that comprise: receiving, at a computer system, a source version of an electronic document in a source format; processing the electronic document to generate a target version of the electronic document in a target format, the processing comprising compressing of one or more images embedded in the source version of the electronic document, compressing one or more Type 1 fonts embedded in the source version of the electronic document, and unifying object duplicates embedded in the source version of the electronic document, the target version of the electronic document in the target format including both the compressed one or more images and the compressed one or more Type 1 fonts and excluding one of each of the object duplicates; and outputting the target version of the electronic document in the target. 12. The non-transitory computer-readable, tangible data storage memory device of claim 8 , wherein the source version of the document is in a TEX format and the target version of the document is in a portable document format (PDF) format.

1. A computer implemented method for benchmarking a brand based on social media strength of said brand, comprising: providing a brand monitoring platform comprising at least one processor configured to monitor said brand in a virtual social media environment; acquiring input information on said brand by said brand monitoring platform; identifying industries related to said brand and competing brands in said identified industries using said acquired input information on said brand by said brand monitoring platform; acquiring social media information related to said brand and said competing brands in said identified industries from a plurality of social media sources in said virtual social media environment by said brand monitoring platform via a network; dynamically generating categories in one or more hierarchical levels in each of said identified industries by said brand monitoring platform based on an independent analysis of said acquired social media information related to said brand and said competing brands from each of said social media sources; sorting said acquired social media information related to said brand and said competing brands in said each of said identified industries into one or more of said dynamically generated categories in said one or more hierarchical levels by said brand monitoring platform using a sorting interface provided by said brand monitoring platform; determining an audience score for said brand and each of said competing brands by measuring an aggregate reach of said brand and said each of said competing brands in said virtual social media environment by said brand monitoring platform based on one or more of a plurality of weighted audience score metric parameters using said sorted social media information; determining an engagement score for said brand and said each of said competing brands by measuring interaction between said brand and said each of said competing brands and their followers by said brand monitoring platform based on one or more of a plurality of weighted engagement score metric parameters using said sorted social media information; generating an aggregate score for said brand and said each of said competing brands by said brand monitoring platform using said determined audience score and said determined engagement score; and determining social media strength of said brand in comparison with said competing brands in said virtual social media environment by assigning a rank to said brand and said each of said competing brands by said brand monitoring platform based on said aggregate score; whereby said brand is benchmarked in comparison with said competing brands in said virtual social media environment based on said social media strength of said brand in comparison with said competing brands in said virtual social media environment.

1. A computer implemented method for benchmarking a brand based on social media strength of said brand, comprising: providing a brand monitoring platform comprising at least one processor configured to monitor said brand in a virtual social media environment; acquiring input information on said brand by said brand monitoring platform; identifying industries related to said brand and competing brands in said identified industries using said acquired input information on said brand by said brand monitoring platform; acquiring social media information related to said brand and said competing brands in said identified industries from a plurality of social media sources in said virtual social media environment by said brand monitoring platform via a network; dynamically generating categories in one or more hierarchical levels in each of said identified industries by said brand monitoring platform based on an independent analysis of said acquired social media information related to said brand and said competing brands from each of said social media sources; sorting said acquired social media information related to said brand and said competing brands in said each of said identified industries into one or more of said dynamically generated categories in said one or more hierarchical levels by said brand monitoring platform using a sorting interface provided by said brand monitoring platform; determining an audience score for said brand and each of said competing brands by measuring an aggregate reach of said brand and said each of said competing brands in said virtual social media environment by said brand monitoring platform based on one or more of a plurality of weighted audience score metric parameters using said sorted social media information; determining an engagement score for said brand and said each of said competing brands by measuring interaction between said brand and said each of said competing brands and their followers by said brand monitoring platform based on one or more of a plurality of weighted engagement score metric parameters using said sorted social media information; generating an aggregate score for said brand and said each of said competing brands by said brand monitoring platform using said determined audience score and said determined engagement score; and determining social media strength of said brand in comparison with said competing brands in said virtual social media environment by assigning a rank to said brand and said each of said competing brands by said brand monitoring platform based on said aggregate score; whereby said brand is benchmarked in comparison with said competing brands in said virtual social media environment based on said social media strength of said brand in comparison with said competing brands in said virtual social media environment. 6. The computer implemented method of claim 1 , wherein said determination of said audience score for said brand and said each of said competing brands by said brand monitoring platform comprises: normalizing measures corresponding to each of said audience score metric parameters; assigning individual weights to said audience score metric parameters; and determining a weighted average of said normalized measures corresponding to said each of said audience score metric parameters using said assigned individual weights.

1. A method, performed by a client, to dynamically generate an application programming interface that enables the client to access a service provided by a server, the method comprising: receiving a request to connect to the server that provides the service, and in response thereto, connecting to the server; downloading an interface definition language file, wherein the interface definition languages file defines the service; generating interface metadata based on the interface definition language file, wherein the interface metadata includes methods, data types, and messages supported by the server; storing the generated interface metadata in a local memory or storage of the client; and in response to a request to execute a method of the service: generating instructions which implement interface bindings for the method based on the stored interface metadata, and executing the method, wherein the executing of the method includes exchanging messages with the server and receiving a result of the method execution from the server.

1. A method, performed by a client, to dynamically generate an application programming interface that enables the client to access a service provided by a server, the method comprising: receiving a request to connect to the server that provides the service, and in response thereto, connecting to the server; downloading an interface definition language file, wherein the interface definition languages file defines the service; generating interface metadata based on the interface definition language file, wherein the interface metadata includes methods, data types, and messages supported by the server; storing the generated interface metadata in a local memory or storage of the client; and in response to a request to execute a method of the service: generating instructions which implement interface bindings for the method based on the stored interface metadata, and executing the method, wherein the executing of the method includes exchanging messages with the server and receiving a result of the method execution from the server. 2. The method of claim 1 , wherein the interface definition language file specifies at least one method and one data type.

22. The method of claim 19 , wherein the conversational voice user interface supports interactions with the plurality of users during an interleaved session.

22. The method of claim 19 , wherein the conversational voice user interface supports interactions with the plurality of users during an interleaved session. 23. The method of claim 22 , wherein queries are processed in an order of receipt during the interleaved session.

1. A method for recognizing characters of an image captured using a camera in a mobile terminal, comprising: capturing, by the camera, an image of a signboard; extracting a text area from the captured image of the signboard; recognizing characters from the extracted text area; generating similar characters of up to a predetermined priority level for each of the recognized characters of the extracted text area; acquiring location information of an area within a predetermined range from a current position of the mobile terminal; extracting at least one store name from the location information; generating at least one text by combining the similar characters according to weights; comparing the at least one text with the extracted at least one store name; and outputting a comparison result.

1. A method for recognizing characters of an image captured using a camera in a mobile terminal, comprising: capturing, by the camera, an image of a signboard; extracting a text area from the captured image of the signboard; recognizing characters from the extracted text area; generating similar characters of up to a predetermined priority level for each of the recognized characters of the extracted text area; acquiring location information of an area within a predetermined range from a current position of the mobile terminal; extracting at least one store name from the location information; generating at least one text by combining the similar characters according to weights; comparing the at least one text with the extracted at least one store name; and outputting a comparison result. 7. The method of claim 1 , wherein comparing the at least one text with the extracted at least one store name comprises: identifying store names similar to the at least one text, and wherein outputting the comparison result comprises: outputting similar store names, for user selection.

9. A system comprising: a storage device; and a processor operatively coupled to the storage device, the processor to: receive an input natural language text including an input word; search a semantic register to identify a matching word corresponding to the input word, wherein the semantic register comprises a plurality of records, each record associating a word with a concept of a semantic class; responsive to successfully identifying the matching word, identify a first plurality of concepts associated with the matching word by the semantic register; rank a plurality of semantic classes associated with the identified first plurality of concepts according to a probability of the input word being associated with a respective semantic class; select a pre-defined number of semantic classes having highest probabilities of the input word being associated with a respective semantic class; iterate through a second plurality of concepts associated, by the semantic register, with the pre-defined number of semantic classes, to identify a concept corresponding to the input word; and responsive to successfully identifying the concept, associate the identified concept with the input word.

9. A system comprising: a storage device; and a processor operatively coupled to the storage device, the processor to: receive an input natural language text including an input word; search a semantic register to identify a matching word corresponding to the input word, wherein the semantic register comprises a plurality of records, each record associating a word with a concept of a semantic class; responsive to successfully identifying the matching word, identify a first plurality of concepts associated with the matching word by the semantic register; rank a plurality of semantic classes associated with the identified first plurality of concepts according to a probability of the input word being associated with a respective semantic class; select a pre-defined number of semantic classes having highest probabilities of the input word being associated with a respective semantic class; iterate through a second plurality of concepts associated, by the semantic register, with the pre-defined number of semantic classes, to identify a concept corresponding to the input word; and responsive to successfully identifying the concept, associate the identified concept with the input word. 11. The system of claim 9 , wherein the semantic register comprises a semantic hierarchy including a plurality of semantic classes, and wherein a semantic class of the plurality of semantic classes comprises a deep model determining a semantic relationship between a parent of the semantic class and a child of the semantic class.

10. A matching service system, comprising: a number of communications ports which provide communications with a plurality of end user devices, the end user devices logically associable with a plurality of end user client accounts of the matching services, the end user client accounts logically associable with end user clients of the matching service; at least one nontransitory processor-readable medium that stores at least one of processor executable instructions or data; and at least one processor communicatively coupled to the communications ports and at least one nontransitory processor-readable medium, and that: for each of a number of respective end user clients, identifies a plurality of potential candidates, each of the potential candidates associated with a value indicative of a quality of a match between the respective potential candidate and the respective end user client; for each of at least two of the potential candidates, determines a size for a respective graphical object based on the respective quality of potential match between the respective potential candidate and the respective end user client, wherein the graphical objects are windows and the at least one processor determines the size of the window based at least in part on an assessment of the quality of a match between the respective potential candidate and the respective end user client, and the at least one processor selects a diagonal dimension of the respective window from at least three sizes, the diagonal dimension for higher quality matches larger than the diagonal dimension for lower quality matches; and causes a presentation to the respective end user client of at least two of the graphical objects at the determined size.

10. A matching service system, comprising: a number of communications ports which provide communications with a plurality of end user devices, the end user devices logically associable with a plurality of end user client accounts of the matching services, the end user client accounts logically associable with end user clients of the matching service; at least one nontransitory processor-readable medium that stores at least one of processor executable instructions or data; and at least one processor communicatively coupled to the communications ports and at least one nontransitory processor-readable medium, and that: for each of a number of respective end user clients, identifies a plurality of potential candidates, each of the potential candidates associated with a value indicative of a quality of a match between the respective potential candidate and the respective end user client; for each of at least two of the potential candidates, determines a size for a respective graphical object based on the respective quality of potential match between the respective potential candidate and the respective end user client, wherein the graphical objects are windows and the at least one processor determines the size of the window based at least in part on an assessment of the quality of a match between the respective potential candidate and the respective end user client, and the at least one processor selects a diagonal dimension of the respective window from at least three sizes, the diagonal dimension for higher quality matches larger than the diagonal dimension for lower quality matches; and causes a presentation to the respective end user client of at least two of the graphical objects at the determined size. 18. The matching service system of claim 10 wherein the at least one processor forwards the graphical object to the end user device associated with the respective end user client, each graphical object including a hyperlink specific to the respective prospective candidate in order to cause causing the presentation to the respective end user client.

7. The method for implementing aggregation combination using rollup depth lists for optimizing database query processing as recited in claim 1 further includes implementing cube aggregation conversion to rollup aggregation for optimizing database query processing.

7. The method for implementing aggregation combination using rollup depth lists for optimizing database query processing as recited in claim 1 further includes implementing cube aggregation conversion to rollup aggregation for optimizing database query processing. 8. The method for implementing aggregation combination using rollup depth lists for optimizing database query processing as recited in claim 7 includes recognizing natural sets of rollup hierarchies within a cube; and converting the cube into the rollup hierarchies.

17. A non-transitory computer-readable storage device storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving data specifying a new voice action submitted by an application developer, the data identifying (i) an application, and (ii) a voice command trigger term; validating the received data; generating a data structure instance that specifies (i) the application, (ii) the voice command trigger term, and (iii) one or more alternate voice command trigger terms that are each determined based at least on the voice command trigger term; after generating the data structure instance, enabling triggering of the new voice action by a spoken utterance based at least on storing the data structure instance at a database that comprises one or more other data structure instances, wherein one or more of the other data structure instances specify (i) an application, and (ii) one or more voice command trigger terms that includes at least one voice command trigger term that is determined based at least on another voice command trigger term in the same data structure instance; after enabling triggering of the new voice action by a spoken utterance and based at least on determining that a transcription of a spoken utterance includes a particular one of the alternate voice command trigger terms that are each determined based at least on the voice command trigger term, selecting a particular data structure instance from the database that specifies the particular one of the alternate voice command trigger terms that are each determined based at least on the voice command trigger term; and identifying a particular application that is specified by the particular data structure instance.

17. A non-transitory computer-readable storage device storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising: receiving data specifying a new voice action submitted by an application developer, the data identifying (i) an application, and (ii) a voice command trigger term; validating the received data; generating a data structure instance that specifies (i) the application, (ii) the voice command trigger term, and (iii) one or more alternate voice command trigger terms that are each determined based at least on the voice command trigger term; after generating the data structure instance, enabling triggering of the new voice action by a spoken utterance based at least on storing the data structure instance at a database that comprises one or more other data structure instances, wherein one or more of the other data structure instances specify (i) an application, and (ii) one or more voice command trigger terms that includes at least one voice command trigger term that is determined based at least on another voice command trigger term in the same data structure instance; after enabling triggering of the new voice action by a spoken utterance and based at least on determining that a transcription of a spoken utterance includes a particular one of the alternate voice command trigger terms that are each determined based at least on the voice command trigger term, selecting a particular data structure instance from the database that specifies the particular one of the alternate voice command trigger terms that are each determined based at least on the voice command trigger term; and identifying a particular application that is specified by the particular data structure instance. 20. The computer-readable device of claim 17 , wherein the operations comprise: identifying one or more data structure instances in the database that each specify (i) an application, and the particular one of the alternate voice command trigger terms that are each determined based at least on the voice command trigger term; requesting a selection of a particular application from among a set of applications that includes the applications specified by the one or more identified data structure instances; receiving data indicating a selection of a particular application from among the set of applications that includes the applications specified by the one or more identified data structure instances; and in response to receiving the data indicating the selection of the particular application, adjusting a strength of a relationship between the identified data structure instance that specifies the particular application and the particular one of the alternate voice command trigger terms that are each determined based at least on the voice command trigger term.

7. A computer-readable storage medium containing a program which, when executed by a processor, performs a process of creating queries querying physical data logically represented by a data abstraction model, the process comprising: receiving an abstract query including logical fields against physical data in a database, the logical fields contained in the abstract query defined by the data abstraction model; determining that the data abstraction model includes logical links associated with the logical fields contained in the abstract query, wherein the logical links define relationships between the associated logical fields and other logical fields; and then: retrieving the associated logical links; and transforming the abstract query into an executable query capable of being executed formatted for execution against the physical data, wherein the transforming is done using the data abstraction model and the retrieved associated logical links.

7. A computer-readable storage medium containing a program which, when executed by a processor, performs a process of creating queries querying physical data logically represented by a data abstraction model, the process comprising: receiving an abstract query including logical fields against physical data in a database, the logical fields contained in the abstract query defined by the data abstraction model; determining that the data abstraction model includes logical links associated with the logical fields contained in the abstract query, wherein the logical links define relationships between the associated logical fields and other logical fields; and then: retrieving the associated logical links; and transforming the abstract query into an executable query capable of being executed formatted for execution against the physical data, wherein the transforming is done using the data abstraction model and the retrieved associated logical links. 8. The computer-readable medium of claim 7 , wherein determining whether the data abstraction model includes the associated logical links comprises: determining, for each result field of the abstract query, whether a corresponding logical field specification includes a logical link.

1. A computerized method for determining metadata associated with an electronic file, the method comprising: receiving, by a computing device, a filename including a first set of characters that represents a name for the electronic file, and a second set of additional characters, the second set of additional characters comprising: a first character representative of an event associated with the electronic file; and a second character representative of a custom action for the event; parsing, by the computing device, the filename to identify the second set of additional characters, wherein the second set of additional characters does not represent either a filename for a second file or a location of the second file; determining, by the computing device, metadata associated with the electronic file based on the second set of additional characters without downloading additional data of the electronic file, the metadata comprising: first metadata that defines an event associated with the electronic file from a first metadata element from a set of metadata elements that comprises the first character, wherein each metadata element in the set of metadata elements comprises a character and metadata associated with the character, and wherein the set of metadata elements is stored separately from the electronic file; and second metadata that defines a custom action for the event from a second metadata element from the set of metadata elements that comprises the second character, and the metadata element for each character from the second set of additional characters is different than metadata elements associated with remaining characters from the second set of additional characters; and processing, by the computing device, the electronic file based on the determined metadata, further comprising: receiving a request to execute an action for the electronic file; determining the request matches the event defined by the first metadata; determining the second metadata requires executing the custom action in addition to the requested action for the electronic file, wherein the custom action is different than the requested action; and executing both the requested action and the custom action for the electronic file.

1. A computerized method for determining metadata associated with an electronic file, the method comprising: receiving, by a computing device, a filename including a first set of characters that represents a name for the electronic file, and a second set of additional characters, the second set of additional characters comprising: a first character representative of an event associated with the electronic file; and a second character representative of a custom action for the event; parsing, by the computing device, the filename to identify the second set of additional characters, wherein the second set of additional characters does not represent either a filename for a second file or a location of the second file; determining, by the computing device, metadata associated with the electronic file based on the second set of additional characters without downloading additional data of the electronic file, the metadata comprising: first metadata that defines an event associated with the electronic file from a first metadata element from a set of metadata elements that comprises the first character, wherein each metadata element in the set of metadata elements comprises a character and metadata associated with the character, and wherein the set of metadata elements is stored separately from the electronic file; and second metadata that defines a custom action for the event from a second metadata element from the set of metadata elements that comprises the second character, and the metadata element for each character from the second set of additional characters is different than metadata elements associated with remaining characters from the second set of additional characters; and processing, by the computing device, the electronic file based on the determined metadata, further comprising: receiving a request to execute an action for the electronic file; determining the request matches the event defined by the first metadata; determining the second metadata requires executing the custom action in addition to the requested action for the electronic file, wherein the custom action is different than the requested action; and executing both the requested action and the custom action for the electronic file. 3. The method of claim 1 , wherein determining the metadata comprises: parsing the second set of additional characters to determine a code; and retrieving metadata from a remote server using the code.

11. The method of claim 10 , further comprising scoring the search results based on one or more of the search intents.

11. The method of claim 10 , further comprising scoring the search results based on one or more of the search intents. 13. The method of claim 11 , wherein the one or more search intents comprise an intent to exclude inner search results, and wherein scoring the search results comprises downgrading the score of each search result corresponding to at least one of the objects of the first set of objects.

8. An system for adding an electronic property to electronically converted documents, the system comprising: a memory; and one or more processors electronically coupled to the memory, the one or more processors, in conjunction with the memory, programmed to cause the system to perform: automatically fragmenting a converted electronic document into fragments; identifying content of each fragment of the converted electronic document; searching for one or more electronic documents corresponding to the converted electronic document using the content from multiple fragments; identifying a first electronic document corresponding to a first fragment; identifying a second electronic document corresponding to a second fragment, the first and second electronic documents comprising different documents; extracting electronic properties from the first and second electronic documents; and applying the electronic properties extracted from the first and second electronic documents to the content of the converted electronic document.

8. An system for adding an electronic property to electronically converted documents, the system comprising: a memory; and one or more processors electronically coupled to the memory, the one or more processors, in conjunction with the memory, programmed to cause the system to perform: automatically fragmenting a converted electronic document into fragments; identifying content of each fragment of the converted electronic document; searching for one or more electronic documents corresponding to the converted electronic document using the content from multiple fragments; identifying a first electronic document corresponding to a first fragment; identifying a second electronic document corresponding to a second fragment, the first and second electronic documents comprising different documents; extracting electronic properties from the first and second electronic documents; and applying the electronic properties extracted from the first and second electronic documents to the content of the converted electronic document. 15. The system as claimed in claim 8 and further comprising a camera for generating the converted electronic document.

1. A method for generating a natural language model for a specific information domain, comprising: building a skeleton of a natural language lexicon for the specific information domain from a source model of the specific information domain, the skeleton comprising terms found in the source model, the source model comprising classification hierarchies for the terms, the terms including objects and attributes; using the skeleton of the natural language lexicon to form a dictionary; applying a set of syntactical rules defining concepts and relationships to the dictionary; expanding the skeleton of the natural language lexicon based on a plurality of reference documents from the specific information domain, wherein expanding the skeleton comprises: clustering and scoring terms for concepts and relationships, and an intersection component for intersecting the syntactic rules and the clustered concepts and relationships; and using the expanded skeleton of the natural language lexicon, provide a natural language processing model for the specific information domain, the natural language processing model utilized by a user in the specific information domain to analyze documents in the specific information domain.

1. A method for generating a natural language model for a specific information domain, comprising: building a skeleton of a natural language lexicon for the specific information domain from a source model of the specific information domain, the skeleton comprising terms found in the source model, the source model comprising classification hierarchies for the terms, the terms including objects and attributes; using the skeleton of the natural language lexicon to form a dictionary; applying a set of syntactical rules defining concepts and relationships to the dictionary; expanding the skeleton of the natural language lexicon based on a plurality of reference documents from the specific information domain, wherein expanding the skeleton comprises: clustering and scoring terms for concepts and relationships, and an intersection component for intersecting the syntactic rules and the clustered concepts and relationships; and using the expanded skeleton of the natural language lexicon, provide a natural language processing model for the specific information domain, the natural language processing model utilized by a user in the specific information domain to analyze documents in the specific information domain. 8. The method as claimed in claim 1 , wherein expanding the skeleton starts at a starting concept or relationship and moves out through neighboring concepts or relationship links in the source model.

4. The device of claim 3 , wherein the decimal representation is based on a count of characters for the text and an area for non-text objects and wherein each character and non-text object has an index computed during rendering of the digital document.

4. The device of claim 3 , wherein the decimal representation is based on a count of characters for the text and an area for non-text objects and wherein each character and non-text object has an index computed during rendering of the digital document. 5. The device of claim 4 , wherein the memory stores instructions to determine the print charges based on a per text page rate for the text and a per image page rate for non-text objects.

8. A program storage device readable by a computer system, tangibly embodying a program of instructions executable by one or more processors of the computer system to perform a method comprising: automatically and programmatically receiving from a software application by an intelligent framework coupled between a high-level language environment and a storage system (a) information regarding definitions of a plurality of data structures associated with a plurality of objects participating in the software application, and (b) information regarding relationships among the plurality of data structures by interrogating the plurality of objects; programmatically and dynamically generating a data definition expression (DDE) to define a structure of a data store inferred by the relationships; causing the storage system to create the structure of the data store by directing the storage system based upon the data definition expression; analyzing a plurality of compiled classes of a database application, the plurality of compiled classes associated with objects that are persisted in a data store of the storage system; determining whether to apply one or more database integrity constraints based upon said analyzed compiled classes; and instructing the storage system to evaluate the one or more database integrity constraints during operations involving the objects.

8. A program storage device readable by a computer system, tangibly embodying a program of instructions executable by one or more processors of the computer system to perform a method comprising: automatically and programmatically receiving from a software application by an intelligent framework coupled between a high-level language environment and a storage system (a) information regarding definitions of a plurality of data structures associated with a plurality of objects participating in the software application, and (b) information regarding relationships among the plurality of data structures by interrogating the plurality of objects; programmatically and dynamically generating a data definition expression (DDE) to define a structure of a data store inferred by the relationships; causing the storage system to create the structure of the data store by directing the storage system based upon the data definition expression; analyzing a plurality of compiled classes of a database application, the plurality of compiled classes associated with objects that are persisted in a data store of the storage system; determining whether to apply one or more database integrity constraints based upon said analyzed compiled classes; and instructing the storage system to evaluate the one or more database integrity constraints during operations involving the objects. 10. The program storage device of claim 8 , wherein the DDE includes one or more statements comprising language statements associated with the storage system.

1. A method for evaluating the text content of a document database with respect to a document population, comprising the steps of: (a) providing a computer system having a user interface with a display; (b) gathering documents from said database into said system; (c) normalizing said gathered documents; (d) fingerprinting said gathered documents; (e) determining a text criteria with respect to said document population; (f) forming a net comprising at least two nodes associated by at least one interaction and displayable at said display as two or more spaced apart nodes connected by an interaction; (g) loading said text criteria into at least one of said nodes; (h) for each document of said database, calculating its geometric relative distance from a said node to derive one or more node attractors; (i) displaying said net at said display in combination with one or more document symbols each representing a said document located in correspondence with said calculated relative distance; (j) visually examining the display of said net and document symbols; and (k) determining from said document symbol locations at said display those documents, if any, which are more likely to correspond with said text criteria.

1. A method for evaluating the text content of a document database with respect to a document population, comprising the steps of: (a) providing a computer system having a user interface with a display; (b) gathering documents from said database into said system; (c) normalizing said gathered documents; (d) fingerprinting said gathered documents; (e) determining a text criteria with respect to said document population; (f) forming a net comprising at least two nodes associated by at least one interaction and displayable at said display as two or more spaced apart nodes connected by an interaction; (g) loading said text criteria into at least one of said nodes; (h) for each document of said database, calculating its geometric relative distance from a said node to derive one or more node attractors; (i) displaying said net at said display in combination with one or more document symbols each representing a said document located in correspondence with said calculated relative distance; (j) visually examining the display of said net and document symbols; and (k) determining from said document symbol locations at said display those documents, if any, which are more likely to correspond with said text criteria. 12. The method of claim 1 in which: said step (k) further comprises the steps: (k1) determining additional text criteria where said document symbol locations are not likely to correspond with said text criteria determined at step (e); and (k2) adding said additional text criteria to said text criteria determined at said step (e).

15. A system, comprising: one or more data processing apparatus; and one or more computer-readable storage devices including instructions executable by the data processing apparatus and upon such execution cause the data processing apparatus to perform operations comprising: receiving a sequence of symbols that have been optically captured from a rendered document; determining that the sequence of symbols includes a particular symbol, word, or phrase that has been mapped to one or more actions; selecting an action from the one or more actions; and transmitting an instruction to a document management system to perform the selected action.

15. A system, comprising: one or more data processing apparatus; and one or more computer-readable storage devices including instructions executable by the data processing apparatus and upon such execution cause the data processing apparatus to perform operations comprising: receiving a sequence of symbols that have been optically captured from a rendered document; determining that the sequence of symbols includes a particular symbol, word, or phrase that has been mapped to one or more actions; selecting an action from the one or more actions; and transmitting an instruction to a document management system to perform the selected action. 17. The system of claim 15 , wherein the operations further comprise: receiving information associated with a location of a capture device used to optically capture the sequence of symbols from the rendered document; wherein selecting the action from the one or more actions is based at least in part on the location of the capture device.

8. A computer-implemented method, comprising: executing an application under test in a layout engine module, wherein the application under test comprises one or more instructions in one scripting language, wherein a selected scripting language engine is configured to interpret the one or more instructions in the one scripting language, and wherein the selected scripting language engine is selected using a user interface of testing options; initializing, in the layout engine module, a debugging session for the application under test, wherein the debugging session is configured to generate output data for the application under test, wherein the debugging session is based on a testing option that selects the selected scripting language engine from among a plurality of scripting language engines, and wherein each scripting language engine of the plurality of scripting language engines is configured to interpret the one scripting language; executing a communication module configured to receive at least packed command data associated with the debugging session; and executing an unpack module configured to establish communication between the communication module and the layout engine module at least to provide unpacked command data based on the packed command data to the layout engine module.

8. A computer-implemented method, comprising: executing an application under test in a layout engine module, wherein the application under test comprises one or more instructions in one scripting language, wherein a selected scripting language engine is configured to interpret the one or more instructions in the one scripting language, and wherein the selected scripting language engine is selected using a user interface of testing options; initializing, in the layout engine module, a debugging session for the application under test, wherein the debugging session is configured to generate output data for the application under test, wherein the debugging session is based on a testing option that selects the selected scripting language engine from among a plurality of scripting language engines, and wherein each scripting language engine of the plurality of scripting language engines is configured to interpret the one scripting language; executing a communication module configured to receive at least packed command data associated with the debugging session; and executing an unpack module configured to establish communication between the communication module and the layout engine module at least to provide unpacked command data based on the packed command data to the layout engine module. 12. The method of claim 8 , wherein the markup language application comprises hypertext markup language (“HTML”).

10. The processing device of claim 8 , wherein the detecting an existence of a tabular structure within handwritten input including a plurality of atoms, further comprises: detecting a left grouping structure based on the plurality of atoms, removing from consideration atoms forming the left grouping structure and leaving a remaining group of atoms for consideration, projecting the remaining group of atoms onto an x-axis and a y-axis to determine a number of rows and a number of columns, assigning ones of the remaining group of atoms to respective cells of the rows and the columns based on a position of each of the respective ones of the remaining group of atoms, merging a pair of the rows of cells or a pair of the columns of cells when at least one empty cell exists to eliminate the at least one empty cell, and validating a final number of rows and a final number of columns.

10. The processing device of claim 8 , wherein the detecting an existence of a tabular structure within handwritten input including a plurality of atoms, further comprises: detecting a left grouping structure based on the plurality of atoms, removing from consideration atoms forming the left grouping structure and leaving a remaining group of atoms for consideration, projecting the remaining group of atoms onto an x-axis and a y-axis to determine a number of rows and a number of columns, assigning ones of the remaining group of atoms to respective cells of the rows and the columns based on a position of each of the respective ones of the remaining group of atoms, merging a pair of the rows of cells or a pair of the columns of cells when at least one empty cell exists to eliminate the at least one empty cell, and validating a final number of rows and a final number of columns. 13. The processing device of claim 10 , wherein the method further comprises: receiving a correction hint with respect to a misrecognition of the tabular structure, the correction hint including at least one atom of a cell and no atoms of any other cell, the correction hint including fewer than all atoms of the cell; and shrinking the at least one atom of the correction hint.

1. A method for creating an electronic database of disambiguated entity mentions from a corpus of electronic documents using a microprocessor, the method comprising: (a) executing on the microprocessor a data harvesting module to automatically extract entity mentions from the electronic documents in the corpus and parse the entity mentions into mention objects; (b) executing on the microprocessor a mention group creation module to create one or more mention groups by automatically grouping the mention objects together according to a distinguishing attribute common to a given class of mention objects; (c) selecting a mention group from the one or more mention groups for comparison processing; (d) executing on the microprocessor a collection of comparison modules that automatically (i) compares every mention object in the selected mention group with every other mention object in the selected mention group to produce a collection of comparison algorithm scores for every pair of mention objects in the selected mention group, and (ii) generates an overall confidence score for every pair of mention objects in the selected mention group based on the collection of comparison algorithm scores for said every pair of mention objects; (e) executing on the microprocessor an entity object creation module to create one or more new entity objects for the selected mention group by automatically (i) grouping together mention objects with other mention objects, based on the confidence scores of each pair of mention objects and a specified confidence threshold, wherein pairs of mention objects having a confidence score greater than or equal to the specified threshold are assigned to the same new entity object, and (ii) merging previously-created entity objects with other previously-created entity objects, based on the confidence scores of each pair of entity objects, and a specified confidence threshold, wherein pairs of entity objects having a confidence score greater than or equal to the specified threshold are assigned to the same new entity object; (f) storing said one or more new entity objects in the electronic database of disambiguated entity mentions; and (g) repeating steps (c) through (f) above until all of the one or more mention groups have been comparison processed.

1. A method for creating an electronic database of disambiguated entity mentions from a corpus of electronic documents using a microprocessor, the method comprising: (a) executing on the microprocessor a data harvesting module to automatically extract entity mentions from the electronic documents in the corpus and parse the entity mentions into mention objects; (b) executing on the microprocessor a mention group creation module to create one or more mention groups by automatically grouping the mention objects together according to a distinguishing attribute common to a given class of mention objects; (c) selecting a mention group from the one or more mention groups for comparison processing; (d) executing on the microprocessor a collection of comparison modules that automatically (i) compares every mention object in the selected mention group with every other mention object in the selected mention group to produce a collection of comparison algorithm scores for every pair of mention objects in the selected mention group, and (ii) generates an overall confidence score for every pair of mention objects in the selected mention group based on the collection of comparison algorithm scores for said every pair of mention objects; (e) executing on the microprocessor an entity object creation module to create one or more new entity objects for the selected mention group by automatically (i) grouping together mention objects with other mention objects, based on the confidence scores of each pair of mention objects and a specified confidence threshold, wherein pairs of mention objects having a confidence score greater than or equal to the specified threshold are assigned to the same new entity object, and (ii) merging previously-created entity objects with other previously-created entity objects, based on the confidence scores of each pair of entity objects, and a specified confidence threshold, wherein pairs of entity objects having a confidence score greater than or equal to the specified threshold are assigned to the same new entity object; (f) storing said one or more new entity objects in the electronic database of disambiguated entity mentions; and (g) repeating steps (c) through (f) above until all of the one or more mention groups have been comparison processed. 9. The method of claim 1 , further comprising executing the collection of comparison modules on the microprocessor so as to automatically (i) compare every entity object in the selected mention group with every other entity object in the selected mention group to produce a collection of comparison algorithm scores for every pair of entity objects in the selected mention group, and (ii) generate an overall confidence score for every pair of entity objects in the selected mention group based on the collection of comparison algorithm scores for said every pair of entity objects.

18. A computing system for generating a product recommendation, the system comprising: one or more processors, a computer-readable medium coupled to the one or more processors having instructions stored thereon that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: receiving graph data indicating vertices and edges of the graph, wherein the vertices represent customers and products and the edges represent purchases; receiving a query of the graph to determine a product recommendation; generating a finite-state machine (FSM) based on the query; executing the query; determining whether a current state of the FSM is a traversal state; in response to the current state being a traversal state, generating a traversal FSM; searching the traversal FSM for a nearest future traversal state; generating a bitmask for the future traversal state; and utilizing the generated bitmask when executing the future traversal state to generate the product recommendation.

18. A computing system for generating a product recommendation, the system comprising: one or more processors, a computer-readable medium coupled to the one or more processors having instructions stored thereon that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: receiving graph data indicating vertices and edges of the graph, wherein the vertices represent customers and products and the edges represent purchases; receiving a query of the graph to determine a product recommendation; generating a finite-state machine (FSM) based on the query; executing the query; determining whether a current state of the FSM is a traversal state; in response to the current state being a traversal state, generating a traversal FSM; searching the traversal FSM for a nearest future traversal state; generating a bitmask for the future traversal state; and utilizing the generated bitmask when executing the future traversal state to generate the product recommendation. 20. The computing system of claim 18 , wherein the query of the graph is expressed with a declarative language.

1. A system comprising hardware and software stored on at least one non-transitory storage medium, said system for managing advisories for complex model nodes comprising: a complex model configured to graphically represent a user-defined system as a plurality of nodes and relationships between the plurality of nodes, wherein the complex model comprises multiple data models that include a notation model and a semantic model, which are two distinct entities that are digitally encoded in a storage medium in a manner distinct from each other, wherein the notational model defines graphical characteristics of the complex model including graphical representations for nodes of the complex model including a shape of the nodes and edges connecting nodes to each other, wherein the semantic model stores capability and requirements parameters of nodes and stores semantic relationships between related nodes used by the advisory manager to determine if existing notifications of related nodes are to be aggregated to or not based on values of the capability and requirements parameters and based on content of the existing notifications; a graphical modeling application stored on at least one non-transitory storage medium configured to support execution of a plurality of operations upon the complex model, wherein said graphical modeling application stores data defining graphical characteristics of the complex model in the notation model and stores data defining semantic characteristics of the complex model in the semantic model, wherein the notation model and the semantic model are stored in the storage medium as separate data entities; the graphical modeling application further configured to generate notifications, wherein the notifications indicate problems or potential problems with a current state of the complex model; and the advisory manager configured to aggregate notifications from different ones of the nodes that are related to each other based on the semantic model information and potential resolutions for the plurality of nodes of the complex model, wherein said aggregated notifications and potential resolutions are visually presented within the graphical modeling application.

1. A system comprising hardware and software stored on at least one non-transitory storage medium, said system for managing advisories for complex model nodes comprising: a complex model configured to graphically represent a user-defined system as a plurality of nodes and relationships between the plurality of nodes, wherein the complex model comprises multiple data models that include a notation model and a semantic model, which are two distinct entities that are digitally encoded in a storage medium in a manner distinct from each other, wherein the notational model defines graphical characteristics of the complex model including graphical representations for nodes of the complex model including a shape of the nodes and edges connecting nodes to each other, wherein the semantic model stores capability and requirements parameters of nodes and stores semantic relationships between related nodes used by the advisory manager to determine if existing notifications of related nodes are to be aggregated to or not based on values of the capability and requirements parameters and based on content of the existing notifications; a graphical modeling application stored on at least one non-transitory storage medium configured to support execution of a plurality of operations upon the complex model, wherein said graphical modeling application stores data defining graphical characteristics of the complex model in the notation model and stores data defining semantic characteristics of the complex model in the semantic model, wherein the notation model and the semantic model are stored in the storage medium as separate data entities; the graphical modeling application further configured to generate notifications, wherein the notifications indicate problems or potential problems with a current state of the complex model; and the advisory manager configured to aggregate notifications from different ones of the nodes that are related to each other based on the semantic model information and potential resolutions for the plurality of nodes of the complex model, wherein said aggregated notifications and potential resolutions are visually presented within the graphical modeling application. 8. The system of claim 1 , wherein the advisory manager IS an integrated component of the graphical modeling application.

11. A non-transitory computer readable medium having computer readable instructions stored thereon that are executable by a processor to: determine that a condition associated with a building has triggered a rule condition for the building, wherein the rule condition is based on an ontology definition associated with the building; generate, upon determining that the condition associated with the building has triggered the rule condition for the building, analytic information associated with the triggered rule condition, wherein: the analytic information is based on the ontology definition; and the analytic information includes temporal and spatial information associated with the triggered rule condition; and display the analytic information associated with the triggered rule condition as part of a display of an operational environment of the building, wherein the display of the analytic information associated with the triggered rule condition includes a display of the temporal information associated with the triggered rule condition as a trend in the spatial information associated with the triggered rule condition.

11. A non-transitory computer readable medium having computer readable instructions stored thereon that are executable by a processor to: determine that a condition associated with a building has triggered a rule condition for the building, wherein the rule condition is based on an ontology definition associated with the building; generate, upon determining that the condition associated with the building has triggered the rule condition for the building, analytic information associated with the triggered rule condition, wherein: the analytic information is based on the ontology definition; and the analytic information includes temporal and spatial information associated with the triggered rule condition; and display the analytic information associated with the triggered rule condition as part of a display of an operational environment of the building, wherein the display of the analytic information associated with the triggered rule condition includes a display of the temporal information associated with the triggered rule condition as a trend in the spatial information associated with the triggered rule condition. 15. The computer readable medium of claim 11 , wherein the analytic information associated with the triggered rule condition includes at least one of: weather conditions associated with the building; electrical demand associated with the building; a status of control setpoints of the building; a temperature of a zone in the building; and an occupancy schedule for the building.

10. A non-transitory computer-readable storage medium having computer-executable instructions stored thereon that, when executed by a computing device, cause the computing device to at least: receive a structured document; parse structural elements from the structured document; generate a text string representing a structure of the structured document from the structural elements, wherein the text string does not comprise textual content from the structured document; derive metadata from the structured document; add the metadata to the text string, the metadata representing a complexity value of the structure of the structured document based at least in part upon a maximum depth of nested structural elements in the structured document; group structural elements in the text string into N-grams utilizing a sliding window; utilize a classifier trained from a plurality of training documents labeled as belonging to a first document class to determine a probability that the structured document belongs to the first document class based on the N-grams, the classifier using the complexity value of the structure of the structured document as a coefficient for a first probability that the structured document belongs to the first document class, wherein the complexity value has a relatively lower value for a first set of documents that are similar and include a simple structure while the complexity value has a relatively higher value for a second set of documents that are relatively less similar and include a relatively more complex structure as compared to the first set of documents; determine whether the first probability that the structured document belongs to the first document class satisfies a threshold value; if the first probability that the structured document belongs to the first document class satisfies the threshold value, classifying the structured document as belonging to the first document class; and if the first probability that the structured document belongs to the first document class does not satisfy the threshold value, utilizing the classifier trained from a plurality of training documents labeled as belonging to the second document class to determine a second probability that the structured document belongs to the second document class based on the text string representing the structure of the structured document.

10. A non-transitory computer-readable storage medium having computer-executable instructions stored thereon that, when executed by a computing device, cause the computing device to at least: receive a structured document; parse structural elements from the structured document; generate a text string representing a structure of the structured document from the structural elements, wherein the text string does not comprise textual content from the structured document; derive metadata from the structured document; add the metadata to the text string, the metadata representing a complexity value of the structure of the structured document based at least in part upon a maximum depth of nested structural elements in the structured document; group structural elements in the text string into N-grams utilizing a sliding window; utilize a classifier trained from a plurality of training documents labeled as belonging to a first document class to determine a probability that the structured document belongs to the first document class based on the N-grams, the classifier using the complexity value of the structure of the structured document as a coefficient for a first probability that the structured document belongs to the first document class, wherein the complexity value has a relatively lower value for a first set of documents that are similar and include a simple structure while the complexity value has a relatively higher value for a second set of documents that are relatively less similar and include a relatively more complex structure as compared to the first set of documents; determine whether the first probability that the structured document belongs to the first document class satisfies a threshold value; if the first probability that the structured document belongs to the first document class satisfies the threshold value, classifying the structured document as belonging to the first document class; and if the first probability that the structured document belongs to the first document class does not satisfy the threshold value, utilizing the classifier trained from a plurality of training documents labeled as belonging to the second document class to determine a second probability that the structured document belongs to the second document class based on the text string representing the structure of the structured document. 15. The non-transitory computer-readable storage medium of claim 10 , wherein the metadata added to the text string comprises an identification of an author of the structured document to be utilized by the classifier.

8. A computer-implemented method of speech recognition by removing an existing sentence from a word-level finite state transducer (FST) having a plurality of states and connecting arcs, the method comprising: determining, using a processor, a prefix subset of states and arcs in the FST matching a prefix portion of the existing sentence and corresponding to at least one other sentence of the FST; determining a suffix subset of states and arcs in the FST matching a suffix portion of the existing sentence and corresponding to at least one other sentence of the FST; removing from the FST any arcs and states between the prefix subset and the suffix subset to create a modified FST without the existing sentence and not satisfying global optimization criteria; and storing the modified FST in memory and dynamically modifying the modified FST using a computer configured as a compiler and using the modified FST for speech recognition, text-to-speech, and/or text processing.

8. A computer-implemented method of speech recognition by removing an existing sentence from a word-level finite state transducer (FST) having a plurality of states and connecting arcs, the method comprising: determining, using a processor, a prefix subset of states and arcs in the FST matching a prefix portion of the existing sentence and corresponding to at least one other sentence of the FST; determining a suffix subset of states and arcs in the FST matching a suffix portion of the existing sentence and corresponding to at least one other sentence of the FST; removing from the FST any arcs and states between the prefix subset and the suffix subset to create a modified FST without the existing sentence and not satisfying global optimization criteria; and storing the modified FST in memory and dynamically modifying the modified FST using a computer configured as a compiler and using the modified FST for speech recognition, text-to-speech, and/or text processing. 12. A method according to claim 8 , further comprising a partial match process to remove a plurality of instances of the existing sentence from the FST.

13. A non-transitory computer-readable storage medium, having instructions stored therein, which when executed, cause a hardware processor to: identify a first text provided by a user; identify a semantic dictionary comprising semantic-syntactic data, the semantic-syntactic data comprising at least one datum specific to the user; identify a first portion of the first text that matches the semantic-syntactic data; generate a node for a semantic-syntactic tree, wherein the node identifies a user ontological object of the semantic-syntactic data corresponding to the first portion of the first text; and store the semantic-syntactic tree comprising the generated node in a data storage device; and perform, using the stored semantic-syntactic tree, natural language processing of at least one of the first text, the first portion of the first text, a second portion of the first text, or a second text provided by the user.

13. A non-transitory computer-readable storage medium, having instructions stored therein, which when executed, cause a hardware processor to: identify a first text provided by a user; identify a semantic dictionary comprising semantic-syntactic data, the semantic-syntactic data comprising at least one datum specific to the user; identify a first portion of the first text that matches the semantic-syntactic data; generate a node for a semantic-syntactic tree, wherein the node identifies a user ontological object of the semantic-syntactic data corresponding to the first portion of the first text; and store the semantic-syntactic tree comprising the generated node in a data storage device; and perform, using the stored semantic-syntactic tree, natural language processing of at least one of the first text, the first portion of the first text, a second portion of the first text, or a second text provided by the user. 16. The non-transitory computer-readable storage medium of claim 13 , wherein the semantic-syntactic data comprises a lexical class.

34. The computer readable medium of claim 27 wherein the code is further executable by the processor for: dividing a consolidated configuration model into the multiple configuration sub-models in accordance with a predetermined data structure; wherein at least one of the configuration queries into multiple configuration sub-queries further comprises dividing the sub-queries in accordance with the sub-model structure.

34. The computer readable medium of claim 27 wherein the code is further executable by the processor for: dividing a consolidated configuration model into the multiple configuration sub-models in accordance with a predetermined data structure; wherein at least one of the configuration queries into multiple configuration sub-queries further comprises dividing the sub-queries in accordance with the sub-model structure. 35. The computer readable medium of claim 34 wherein the predetermined data structure comprises a data structure divided along configuration model part groups, wherein the part groups are a collection of related parts.

3. The method of claim 1 , prior to moving the selected one of the pre-move version of the portion of content or the post-move version of the portion of content to the first location in the document, further comprising receiving an indication of a tracked move of the portion of content from the first location in the document to the second location in the document.

3. The method of claim 1 , prior to moving the selected one of the pre-move version of the portion of content or the post-move version of the portion of content to the first location in the document, further comprising receiving an indication of a tracked move of the portion of content from the first location in the document to the second location in the document. 4. The method of claim 3 , further comprising moving the portion of content to the second location in the document along with any graphical notations for distinguishing edited document content from non-edited document content.

11. The method of claim 10 , wherein determining the set of context data includes determining at least one of an identity of a referral source, a type of referral source, a type of referral, or a set of consumption characteristics.

11. The method of claim 10 , wherein determining the set of context data includes determining at least one of an identity of a referral source, a type of referral source, a type of referral, or a set of consumption characteristics. 14. The method of claim 11 , wherein determining the set of consumption characteristics includes determining at least one of a type of device employed to consume the content, a set of devices associated with the user, a time of consumption, a geographic location of the user, a proximity to other devices, or a proximity to a set of other users.

1. An apparatus comprising: a sensor configured to acquire a context data, wherein the context data provides information of an attribute of an event within the range of the sensor; a processor configured to analyze an attribute of the context data and determine a higher-order context data; a message generator configured to generate a supplemental context message transmittable through a network wherein the supplemental context message includes the higher-order context data, and wherein the supplemental context message comprises a text message identifying the apparatus with a pronoun; and a network interface device configured to communicatively couple the apparatus to the network, and wherein the context data originates from a radio transponder located in a food item container, wherein a signal from the radio transponder identifies at least one of an identity of a food item, an expiration date of the food item and a quantity of the food item in the food item container, wherein the processor determines that at the least one of the expiration date of the food item and the quantity of the food item in the food item container is beyond a certain threshold, and wherein the message generator generates a text message comprising a notification that the least one of the expiration date of the food item and the quantity of the food item in the food item container is beyond the certain threshold.

1. An apparatus comprising: a sensor configured to acquire a context data, wherein the context data provides information of an attribute of an event within the range of the sensor; a processor configured to analyze an attribute of the context data and determine a higher-order context data; a message generator configured to generate a supplemental context message transmittable through a network wherein the supplemental context message includes the higher-order context data, and wherein the supplemental context message comprises a text message identifying the apparatus with a pronoun; and a network interface device configured to communicatively couple the apparatus to the network, and wherein the context data originates from a radio transponder located in a food item container, wherein a signal from the radio transponder identifies at least one of an identity of a food item, an expiration date of the food item and a quantity of the food item in the food item container, wherein the processor determines that at the least one of the expiration date of the food item and the quantity of the food item in the food item container is beyond a certain threshold, and wherein the message generator generates a text message comprising a notification that the least one of the expiration date of the food item and the quantity of the food item in the food item container is beyond the certain threshold. 2. The apparatus of claim 1 , wherein the signal from the radio transponder identifies a temperature of the food item, and wherein the processor determines that the appliance storing the food item container requires maintenance if a plurality of food items are above a specified temperature.

5. The system according to claim 4, further comprising: a fuzzy evaluator for calculating and storing a joined confidence value of each record in the original text database, the joined confidence value of each record based on the fuzzy expected value for each word in that record.

5. The system according to claim 4, further comprising: a fuzzy evaluator for calculating and storing a joined confidence value of each record in the original text database, the joined confidence value of each record based on the fuzzy expected value for each word in that record. 7. The system according to claim 5, wherein the fuzzy evaluator calculates the joined confidence value of a record containing one word to be equal to the fuzzy expected value of the one word.

3. The method of claim 2 , further comprising: receiving query data specifying at least one of a topic and a speaker; and retrieving at least one of a topic cluster and a speaker cluster from the data storage based on the received query data.

3. The method of claim 2 , further comprising: receiving query data specifying at least one of a topic and a speaker; and retrieving at least one of a topic cluster and a speaker cluster from the data storage based on the received query data. 4. The method of claim 3 , further comprising: displaying the at least one cluster group on an associated display in a display sequence corresponding to the time line series associated therewith.

11. An apparatus comprising: at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, determine a multi-dimensional query associated with at least one user device, wherein the multi-dimensional query specifies, at least in part, one or more personas, based, at least in part, on more than one person, associated with the at least one user device; cause, at least in part, an execution of the multi-dimensional query on at least one context-sensitive database to generate one or more results; and determine at least one ordering metric for the one or more results based, at least in part, on one or more user contextual attributes of the at least one user device.

11. An apparatus comprising: at least one processor; and at least one memory including computer program code for one or more programs, the at least one memory and the computer program code configured to, with the at least one processor, cause the apparatus to perform at least the following, determine a multi-dimensional query associated with at least one user device, wherein the multi-dimensional query specifies, at least in part, one or more personas, based, at least in part, on more than one person, associated with the at least one user device; cause, at least in part, an execution of the multi-dimensional query on at least one context-sensitive database to generate one or more results; and determine at least one ordering metric for the one or more results based, at least in part, on one or more user contextual attributes of the at least one user device. 12. An apparatus of claim 11 , wherein the apparatus is further caused to: determine one or more object contextual attributes associated with the one or more results, wherein the at least one ordering metric is further based, at least in part, on the one or more object contextual attributes.

1. A method implemented by a computing system having a processor coupled to a memory for generating an object schema used in mapping between a relational database and objects from an object oriented programming language comprising: receiving program code that describes one or more classes which define objects, wherein the objects are components from an object oriented programming language comprising data structures and functions operable on data; describing members of each class, wherein the members of each class comprise compound members, wherein the compound members comprise a second member and at least one of a plurality of attributes describing the members of each class, and wherein the compound members allow mapping of complex members as inline members of a given class, which allows inline mapping of arrays, structs and entity key members; specifying relationships between the one or more classes; receiving input from a developer through an interface component; generating an object schema using the input received from the interface component to be employed to facilitate mapping the objects described in the received program code to tables in a relational database, wherein data in the relational database describes the objects and the data in the relational database persists, the object schema comprising: a first data structure comprising a plurality of attributes describing the one or more classes which define the objects, the plurality of attributes describing the one or more classes comprising at least a persistence service class attribute designating a persistence service to use when persisting a particular class associated with the persistence service class attribute; a second data structure comprising the plurality of attributes describing the members of each class, the plurality of attributes describing the members of each class comprising at least a hidden attribute that defines if there is a hidden member in a corresponding class and manages the hidden member in a transparent fashion, a key generator attribute designating a user class that is to act as a custom key generator, and a key generator parameter attribute designating parameters to be passed to the custom key generator; a third data structure comprising a plurality of attributes describing the relationships between the one or more classes, the plurality of attributes describing the relationships between the one or more classes comprising at least a relationship name attribute identifying a unique name for a relationship, and a relationship type attribute identifying a type of predefined relationship; and wherein at least one of the members described in the second data structure contains an alias attribute to query a private member, the alias attribute pointing to a public member that is to be utilized in place of the associated private member in text of a query; providing a relational schema that provides details regarding the relational database and utilizes metadata associated with the database to generate an implementation neutral or an implementation specific format that represents the database structure; and providing a mapping schema that provides a mapping between the object schema and the relational schema.

1. A method implemented by a computing system having a processor coupled to a memory for generating an object schema used in mapping between a relational database and objects from an object oriented programming language comprising: receiving program code that describes one or more classes which define objects, wherein the objects are components from an object oriented programming language comprising data structures and functions operable on data; describing members of each class, wherein the members of each class comprise compound members, wherein the compound members comprise a second member and at least one of a plurality of attributes describing the members of each class, and wherein the compound members allow mapping of complex members as inline members of a given class, which allows inline mapping of arrays, structs and entity key members; specifying relationships between the one or more classes; receiving input from a developer through an interface component; generating an object schema using the input received from the interface component to be employed to facilitate mapping the objects described in the received program code to tables in a relational database, wherein data in the relational database describes the objects and the data in the relational database persists, the object schema comprising: a first data structure comprising a plurality of attributes describing the one or more classes which define the objects, the plurality of attributes describing the one or more classes comprising at least a persistence service class attribute designating a persistence service to use when persisting a particular class associated with the persistence service class attribute; a second data structure comprising the plurality of attributes describing the members of each class, the plurality of attributes describing the members of each class comprising at least a hidden attribute that defines if there is a hidden member in a corresponding class and manages the hidden member in a transparent fashion, a key generator attribute designating a user class that is to act as a custom key generator, and a key generator parameter attribute designating parameters to be passed to the custom key generator; a third data structure comprising a plurality of attributes describing the relationships between the one or more classes, the plurality of attributes describing the relationships between the one or more classes comprising at least a relationship name attribute identifying a unique name for a relationship, and a relationship type attribute identifying a type of predefined relationship; and wherein at least one of the members described in the second data structure contains an alias attribute to query a private member, the alias attribute pointing to a public member that is to be utilized in place of the associated private member in text of a query; providing a relational schema that provides details regarding the relational database and utilizes metadata associated with the database to generate an implementation neutral or an implementation specific format that represents the database structure; and providing a mapping schema that provides a mapping between the object schema and the relational schema. 4. A computer readable storage medium having stored thereon computer executable instructions, which when executed by a processor, carry out the method of claim 1 .

1. A method for recognizing an environmental sound at a client device, the method comprising: accessing a client database including a plurality of sound models representing environmental sounds and a plurality of labels, wherein each of the plurality of labels identifies at least one of the plurality of sound models; receiving an input environmental sound and generating an input sound model based on the input environmental sound; determining similarity values between the input sound model and the plurality of sound models to identify one or more sound models of the plurality of sound models that are similar to the input sound model; selecting a first label from one or more labels, of the plurality of labels, associated with the one or more sound models; associating the first label with the input environmental sound based on a confidence level of the first label; and if the confidence level is less than a confidence threshold: transmitting the input sound model to a server; and receiving a second label identifying the input environmental sound from the server.

1. A method for recognizing an environmental sound at a client device, the method comprising: accessing a client database including a plurality of sound models representing environmental sounds and a plurality of labels, wherein each of the plurality of labels identifies at least one of the plurality of sound models; receiving an input environmental sound and generating an input sound model based on the input environmental sound; determining similarity values between the input sound model and the plurality of sound models to identify one or more sound models of the plurality of sound models that are similar to the input sound model; selecting a first label from one or more labels, of the plurality of labels, associated with the one or more sound models; associating the first label with the input environmental sound based on a confidence level of the first label; and if the confidence level is less than a confidence threshold: transmitting the input sound model to a server; and receiving a second label identifying the input environmental sound from the server. 16. The method of claim 1 , wherein the determining the similarity values, the selecting the first label, and the associating the first label are performed within a device that comprises a base station.

3. The computer-implemented method of claim 1 , wherein generating the image index files comprises: aligning each image metric for each region of the gridded digital image to generate an image metric vector for each of the plurality of image metrics.

3. The computer-implemented method of claim 1 , wherein generating the image index files comprises: aligning each image metric for each region of the gridded digital image to generate an image metric vector for each of the plurality of image metrics. 4. The computer-implemented method of claim 3 , wherein generating the image index files further comprises: converting each image metric vector for each of the plurality of image metrics into a binary numerical descriptor.

1. An information retrieval method comprising the steps of generating term-by-data object matrix data to represent information files stored in a computer system, said matrix data being indicative of the frequency of occurrence of selected terms contained in the data objects stored in the information files, decomposing said matrix into a reduced singular value representation composed of distinct term and data object files, in response to a user query, generating a pseudo-object utilizing said selected terms and inserting said pseudo-object into said matrix data, and examining the similarity between said pseudo-object and said term and data object files to generate an information response and storing said response in the system in a form accessible by the user.

1. An information retrieval method comprising the steps of generating term-by-data object matrix data to represent information files stored in a computer system, said matrix data being indicative of the frequency of occurrence of selected terms contained in the data objects stored in the information files, decomposing said matrix into a reduced singular value representation composed of distinct term and data object files, in response to a user query, generating a pseudo-object utilizing said selected terms and inserting said pseudo-object into said matrix data, and examining the similarity between said pseudo-object and said term and data object files to generate an information response and storing said response in the system in a form accessible by the user. 2. The method as recited in claim 1 wherein said step of generating said matrix data includes the step of producing a lexicon database defining said selected terms.

16. A non-transitory machine-readable storage medium that provides instructions that, if executed by a processing device, will cause the processing device to perform operations comprising: generating, by a computing device, a plurality of output documents in a plurality of distinct formats from a master document; and maintaining, by the computing device, the plurality of output documents, said maintaining comprising: receiving an updated master document that includes one or more changes to the master document, wherein each part of the updated master document affected by one of the one or more changes is identified by a tag of a markup language of the updated master document; identifying the parts of the updated master document affected be the one of the one or more changes by locating the tag associated with each part affected by the one of the one or more changes; generating, for each of the plurality of output documents, updated parts of the output document corresponding to each part of the updated master document identified by the tag, wherein the generating further comprises applying a plurality of stylesheets to each part of the updated master document identified by the tag to generate the updated parts of the output document, and updating parts of each of the plurality of output documents with the corresponding updated parts of the output document generated, without updating the entirety of each of the plurality of output documents.

16. A non-transitory machine-readable storage medium that provides instructions that, if executed by a processing device, will cause the processing device to perform operations comprising: generating, by a computing device, a plurality of output documents in a plurality of distinct formats from a master document; and maintaining, by the computing device, the plurality of output documents, said maintaining comprising: receiving an updated master document that includes one or more changes to the master document, wherein each part of the updated master document affected by one of the one or more changes is identified by a tag of a markup language of the updated master document; identifying the parts of the updated master document affected be the one of the one or more changes by locating the tag associated with each part affected by the one of the one or more changes; generating, for each of the plurality of output documents, updated parts of the output document corresponding to each part of the updated master document identified by the tag, wherein the generating further comprises applying a plurality of stylesheets to each part of the updated master document identified by the tag to generate the updated parts of the output document, and updating parts of each of the plurality of output documents with the corresponding updated parts of the output document generated, without updating the entirety of each of the plurality of output documents. 21. The non-transitory machine-readable storage medium of claim 16 , wherein the operations further comprise: changing the master document in response to a request received at a server from a client machine communicatively coupled to the server via a network.

10. The system of claim 9 , wherein a submitter name comprises a name of a person who marked at least one of said question specifier and said answer specifier.

10. The system of claim 9 , wherein a submitter name comprises a name of a person who marked at least one of said question specifier and said answer specifier. 11. The system of claim 10 , wherein said person who marked at least one of said question specifier and said answer specifier is not a participant in said social networking interaction.

6. The computer-implemented method of claim 1 , wherein adapting the classification comprises: adding a data object to the sample set; and adapting the classification mapping based on the addition of the data object to the sample set.

6. The computer-implemented method of claim 1 , wherein adapting the classification comprises: adding a data object to the sample set; and adapting the classification mapping based on the addition of the data object to the sample set. 7. The computer-implemented method of claim 6 , the steps performed by the programmed digital computer further comprising mapping a new set of data objects to the associated class labels based on the adapted classification mapping.

19. A computer-based system for processing one or more citations for inclusion in an electronic document, the system comprising: a processor; a memory communicatively coupled with the processor; computer executable code stored in the memory, the computer executable code comprising: a document rendering application; a citation editing code set comprising: citation interface code set when executed by the processor adapted to present a citation interface and receive a user input representing a set of citation terms related to a citation for inclusion in the electronic document; citation identifying code set adapted to identify a set of at least one citation record from at least one citation library based at least in part on the received set of citation terms; citation selection code set adapted to present a representation of one or more of the identified set of at least one citation record and to receive an electronic signal representing a user selection of a citation from the presented one or more of the set of at least one citation record; and citation insertion code set adapted to insert into the electronic document citation data from the corresponding citation record associated with the selected citation.

19. A computer-based system for processing one or more citations for inclusion in an electronic document, the system comprising: a processor; a memory communicatively coupled with the processor; computer executable code stored in the memory, the computer executable code comprising: a document rendering application; a citation editing code set comprising: citation interface code set when executed by the processor adapted to present a citation interface and receive a user input representing a set of citation terms related to a citation for inclusion in the electronic document; citation identifying code set adapted to identify a set of at least one citation record from at least one citation library based at least in part on the received set of citation terms; citation selection code set adapted to present a representation of one or more of the identified set of at least one citation record and to receive an electronic signal representing a user selection of a citation from the presented one or more of the set of at least one citation record; and citation insertion code set adapted to insert into the electronic document citation data from the corresponding citation record associated with the selected citation. 37. The system of claim 19 , wherein the citation editing code set is adapted to interface the document rendering application with the citation library, the citation editing code set comprising a set of graphical controls selectable via the document rendering application and adapted to execute user-selected citation commands.

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

24. A tangible computer readable storage medium including computer instructions for defining a service monitor for a web service, the computer instructions comprising instructions for: accepting a functional web service that operates as one of a plurality of functional web services all operating on a single server; including in the functional web service at least one monitor data collection function that records at least one monitor data element, the at least one monitor data element characterizing at least one operation of the functional web service, and the at least one monitor data element being made available to the monitoring service; defining at least one functional web service description language (WSDL) document for the functional web service; defining a monitor web service, separate from the functional web service, the monitor web service providing access to the at least one monitor data element recorded by the at least one data collection function included within the functional web service; and including, in the at least one functional web service description language document (WSDL), a reference to a monitoring web service description language (WSDL) document defining the monitoring service, wherein the monitoring web service description language (WSDL) document is separate from the functional web service description language (WSDL) document. 30. The tangible computer readable storage medium according to claim 24 , wherein the monitoring web service provides access to a plurality of monitor data elements recorded by respective data collection functions included in multiple web services.

6. The method according to claim 1 , wherein votes are received from the audience in a round, wherein a round comprises a time period for receiving segment candidates and a time period for voting on the submitted segment candidates.

6. The method according to claim 1 , wherein votes are received from the audience in a round, wherein a round comprises a time period for receiving segment candidates and a time period for voting on the submitted segment candidates. 7. The method according to claim 6 , wherein segment candidates continue to be received during the voting time period.

1. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving content data, the content data comprising text; responsive to determining that the content data is insufficient to accurately determine a natural language in which the text is written by determining that a number of characters of the text is less than a threshold number: identifying an author of the text, the author being a first user of a social networking service; retrieving social graph data corresponding to one or more social graphs associated with the first user, the social graph data being stored in a computer-readable storage device, the social graph data including a first set of language statistics and a second set of language statistics based on posts respectively authored by a second user and a third user that connect with the first user within the social networking service; determining aggregate statistics from the first and second sets of language statistics based on a strength of relationship between the first and second users and a strength of relationship between the first and third users; and determining the natural language that the text is written in as one of a plurality of potential natural languages based on the aggregate statistics included in the social graph data corresponding to the one or more social graphs associated with the author.

1. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving content data, the content data comprising text; responsive to determining that the content data is insufficient to accurately determine a natural language in which the text is written by determining that a number of characters of the text is less than a threshold number: identifying an author of the text, the author being a first user of a social networking service; retrieving social graph data corresponding to one or more social graphs associated with the first user, the social graph data being stored in a computer-readable storage device, the social graph data including a first set of language statistics and a second set of language statistics based on posts respectively authored by a second user and a third user that connect with the first user within the social networking service; determining aggregate statistics from the first and second sets of language statistics based on a strength of relationship between the first and second users and a strength of relationship between the first and third users; and determining the natural language that the text is written in as one of a plurality of potential natural languages based on the aggregate statistics included in the social graph data corresponding to the one or more social graphs associated with the author. 4. The system of claim 1 , wherein the social graph data comprises language statistics regarding posts authored by one or more non-contact users, each of the one or more non-contact users having commented on at least one post authored by the first user within the social networking service.

1. A system comprising: a processor configured to: receive a digital communication including text in a body of the communication corresponding to a schedulable event; identify the schedulable event in the text of the communication body, by comparison of words in the text to predefined words designated as identifying schedulable events; query a user to determine if the schedulable event should be scheduled; and responsive to user confirmation to the query, schedule the schedulable event.

1. A system comprising: a processor configured to: receive a digital communication including text in a body of the communication corresponding to a schedulable event; identify the schedulable event in the text of the communication body, by comparison of words in the text to predefined words designated as identifying schedulable events; query a user to determine if the schedulable event should be scheduled; and responsive to user confirmation to the query, schedule the schedulable event. 3. The system of claim 1 wherein the digital communication is a social network posting.

1. A method for searching objects in a database by means of an index data structure which associates object attribute values to collections of spatial elements—for example tiles of a quadtree or cuboids of an octtree—defined to partition a space, especially a two-dimensional plane or a three-dimensional space, herein a predefined number of spatial elements being combinable to a next-level spatial element, the method comprising: searching the index data structure for a first input search pattern and, if the first input search pattern is associated to a first collection of spatial elements through the index data structure, including all spatial elements from the first collection into a first candidate set of spatial elements, wherein, if the number of spatial elements in the first candidate set exceeds a certain limit, some or all of the spatial elements are combined to a reduced number of next-level spatial elements; searching the index data structure for a second input search pattern and, if the second input search pattern is associated to a second collection of spatial elements through the index data structure, including all spatial elements from the second collection into a second candidate set of spatial elements, wherein, if the number of spatial elements in the second candidate set exceeds a certain limit, some or all of the spatial elements are combined to a reduced number of next-level spatial elements; forming, from the first candidate set and the second candidate set, a combined candidate set of spatial elements; searching, in the combined candidate set of spatial elements, for objects that match the first input search pattern and the input second search pattern to obtain a set of result objects wherein in the combined candidate set formed from the first candidate set and the second candidate set some or all of the spatial elements are combined to a reduced number of next-level spatial elements if the number of spatial elements in the combined candidate set exceeds a predefined threshold value.

1. A method for searching objects in a database by means of an index data structure which associates object attribute values to collections of spatial elements—for example tiles of a quadtree or cuboids of an octtree—defined to partition a space, especially a two-dimensional plane or a three-dimensional space, herein a predefined number of spatial elements being combinable to a next-level spatial element, the method comprising: searching the index data structure for a first input search pattern and, if the first input search pattern is associated to a first collection of spatial elements through the index data structure, including all spatial elements from the first collection into a first candidate set of spatial elements, wherein, if the number of spatial elements in the first candidate set exceeds a certain limit, some or all of the spatial elements are combined to a reduced number of next-level spatial elements; searching the index data structure for a second input search pattern and, if the second input search pattern is associated to a second collection of spatial elements through the index data structure, including all spatial elements from the second collection into a second candidate set of spatial elements, wherein, if the number of spatial elements in the second candidate set exceeds a certain limit, some or all of the spatial elements are combined to a reduced number of next-level spatial elements; forming, from the first candidate set and the second candidate set, a combined candidate set of spatial elements; searching, in the combined candidate set of spatial elements, for objects that match the first input search pattern and the input second search pattern to obtain a set of result objects wherein in the combined candidate set formed from the first candidate set and the second candidate set some or all of the spatial elements are combined to a reduced number of next-level spatial elements if the number of spatial elements in the combined candidate set exceeds a predefined threshold value. 4. The method according to claim 1 , wherein, during the searching of the index data structure for the first input search pattern or the second input search pattern that each represent a sequence of data elements, especially a text string, it is examined whether the first input search pattern or the second input search pattern matches a prefix of an attribute value of an object of a spatial element.

1. A network advertising system, comprising: a primary advertiser database that stores a list of primary advertisers willing to pay a secondary advertiser to (i) embed advertising content into electronic media to which access by a potential customer is controlled by the secondary advertiser, and (ii) make the electronic media with the embedded advertising content viewable by the potential customer in a manner that allows the potential customer to be exposed to an advertisement; a tagging unit that allows a secondary advertiser to embed the advertising content by tagging an item within the electronic media by indicating an area on or near the item, the tagging causing either or both of (i) a visual indicator and (ii) a tag label to be displayed on the electronic media, the tag label being text generated by the secondary advertiser; a text block unit that receives a search query from the secondary advertiser, retrieves primary advertiser information from the primary advertiser database in response to the search query and displays the primary advertiser information to the secondary advertiser, receives the secondary advertiser's selection of the primary advertiser information, and, after the item has been tagged by the secondary advertiser, associates the tagged item with a link of the primary advertiser in response to the selection of the primary advertiser information, wherein no advertisement other than the tag label or visual indicator is displayed with the electronic media, and wherein the link directs the potential customer to a specific site selected by the secondary advertiser; a revenue-generating transaction database that records secondary advertising events for which the primary advertiser is willing to pay; and an accounting unit that tracks what is owed by the primary advertiser based on the events recorded by the revenue-generating transaction database.

1. A network advertising system, comprising: a primary advertiser database that stores a list of primary advertisers willing to pay a secondary advertiser to (i) embed advertising content into electronic media to which access by a potential customer is controlled by the secondary advertiser, and (ii) make the electronic media with the embedded advertising content viewable by the potential customer in a manner that allows the potential customer to be exposed to an advertisement; a tagging unit that allows a secondary advertiser to embed the advertising content by tagging an item within the electronic media by indicating an area on or near the item, the tagging causing either or both of (i) a visual indicator and (ii) a tag label to be displayed on the electronic media, the tag label being text generated by the secondary advertiser; a text block unit that receives a search query from the secondary advertiser, retrieves primary advertiser information from the primary advertiser database in response to the search query and displays the primary advertiser information to the secondary advertiser, receives the secondary advertiser's selection of the primary advertiser information, and, after the item has been tagged by the secondary advertiser, associates the tagged item with a link of the primary advertiser in response to the selection of the primary advertiser information, wherein no advertisement other than the tag label or visual indicator is displayed with the electronic media, and wherein the link directs the potential customer to a specific site selected by the secondary advertiser; a revenue-generating transaction database that records secondary advertising events for which the primary advertiser is willing to pay; and an accounting unit that tracks what is owed by the primary advertiser based on the events recorded by the revenue-generating transaction database. 14. The network advertising system of claim 1 , wherein the tagging causes both of (i) the visual indicator and (ii) the tag label to be displayed on the electronic media.

14. A method for managing color rendering problems, comprising: with a first reviewing application, receiving a document to be submitted for printing; accessing a print queue of a printing infrastructure with an interface module to acquire color rendering information, the color rendering information including information acquired from a printer of the print queue which is predicted to be used for printing the document, the information including settings of the printer which affect the printer's ability to render colors; communicating the acquired color rendering information between the interface module and the first reviewing application; with the first reviewing application: detecting problems relating to color rendering by the printing infrastructure for the document to be submitted for printing, generating a visual representation of the document to be submitted, based on the acquired color rendering information and detected problems, generating corrections for the problems, outputting the visual representation to a first display; providing for a first user to select whether to accept the corrections and to annotate the document; submitting the optionally annotated and corrected document to the interface module; and with at least one of the first reviewing application and a second reviewing application, generating a visual presentation of the submitted document, including providing for annotations comprising a textual description applied by the first user to be reviewed by a second user; and outputting the visual representation to a second display for review by the second user.

14. A method for managing color rendering problems, comprising: with a first reviewing application, receiving a document to be submitted for printing; accessing a print queue of a printing infrastructure with an interface module to acquire color rendering information, the color rendering information including information acquired from a printer of the print queue which is predicted to be used for printing the document, the information including settings of the printer which affect the printer's ability to render colors; communicating the acquired color rendering information between the interface module and the first reviewing application; with the first reviewing application: detecting problems relating to color rendering by the printing infrastructure for the document to be submitted for printing, generating a visual representation of the document to be submitted, based on the acquired color rendering information and detected problems, generating corrections for the problems, outputting the visual representation to a first display; providing for a first user to select whether to accept the corrections and to annotate the document; submitting the optionally annotated and corrected document to the interface module; and with at least one of the first reviewing application and a second reviewing application, generating a visual presentation of the submitted document, including providing for annotations comprising a textual description applied by the first user to be reviewed by a second user; and outputting the visual representation to a second display for review by the second user. 19. The method of claim 14 , further comprising printing the submitted document.

21. A system comprising: a display device; a memory; and a computing device configured to: access an electronic version of a document; display a sequence of words from the electronic document in a user interface rendered on the display device; apply in response to a user-based selection of a first portion of words in the sequence of words from the document, a first indicium to the user-selected first portion of words in the sequence of words; associate a first narration voice to the first portion of words in the sequence of words; and associate a second narration voice to a second portion of words in the sequence of words, the second portion of the words in the sequence of words being different from the first portion of words in the sequence of words.

21. A system comprising: a display device; a memory; and a computing device configured to: access an electronic version of a document; display a sequence of words from the electronic document in a user interface rendered on the display device; apply in response to a user-based selection of a first portion of words in the sequence of words from the document, a first indicium to the user-selected first portion of words in the sequence of words; associate a first narration voice to the first portion of words in the sequence of words; and associate a second narration voice to a second portion of words in the sequence of words, the second portion of the words in the sequence of words being different from the first portion of words in the sequence of words. 25. The system of claim 21 , wherein the computing device is further configured to: generate an audible output corresponding to the words in the sequence of words, with the words in the first portion of words narrated using the first narration voice and the words in the second portion of words remaining unselected and being narrated using the second narration voice.

1. A computer-implemented method for use with a document management system, the computer-implemented method comprising: using a computer system to perform the steps of: retrieving data for a case file from the document management system; creating a visual representation for the case file, the visual representation comprising: a case identifier of the case file; an action field including a data entry field for receiving markings from a user for updating a record in the document management system corresponding to the case file, the markings including a plurality of boxes indicating predetermined actions, user notes to correct the record or prognoses; an index comprising a listing of a first plurality of documents associated with the case file, a first plurality of links to electronic versions of the first plurality of documents in the listing, and a plurality of textual summaries corresponding to the first plurality of documents in the listing, the index divided into a plurality of categories, each category containing a subset of documents in the listing; a plurality of thumbnail images of one or more of the first plurality of documents associated with the case file; a summary of a portion of the first plurality of documents associated with the case file and information specified by the user; and a plurality of related tokens for a plurality of related cases indicating a status of the plurality of related cases and a second plurality of links to electronic versions of a second plurality of documents corresponding to the plurality of related cases; and printing, on a printed medium, a first token that is a physical representation of the retrieved data, the first token comprising the visual representation of the case file.

1. A computer-implemented method for use with a document management system, the computer-implemented method comprising: using a computer system to perform the steps of: retrieving data for a case file from the document management system; creating a visual representation for the case file, the visual representation comprising: a case identifier of the case file; an action field including a data entry field for receiving markings from a user for updating a record in the document management system corresponding to the case file, the markings including a plurality of boxes indicating predetermined actions, user notes to correct the record or prognoses; an index comprising a listing of a first plurality of documents associated with the case file, a first plurality of links to electronic versions of the first plurality of documents in the listing, and a plurality of textual summaries corresponding to the first plurality of documents in the listing, the index divided into a plurality of categories, each category containing a subset of documents in the listing; a plurality of thumbnail images of one or more of the first plurality of documents associated with the case file; a summary of a portion of the first plurality of documents associated with the case file and information specified by the user; and a plurality of related tokens for a plurality of related cases indicating a status of the plurality of related cases and a second plurality of links to electronic versions of a second plurality of documents corresponding to the plurality of related cases; and printing, on a printed medium, a first token that is a physical representation of the retrieved data, the first token comprising the visual representation of the case file. 2. The method of claim 1 further comprising formatting the data and the index to create the visual representation of the case file to fit in a predetermined area of the physical representation.

17. A computerized system for searching a collection of content, comprising: a processor; and memory including instructions that, upon being executed by the processor, cause the computerized system to: identify a visually significant subset of categories of a category tree that categorizes the collection of content, the collection of content including a plurality of items each associated with one or more images, the visually significant subset including the categories of the category tree that are each associated with a respective set of images having a respective size that is greater than a lower size threshold and less than an upper size threshold; receive a search request associated with a query image; identify, among the visually significant subset, a candidate set of categories for the query image based at least in part on the search request, wherein at least one parent category is automatically excluded from the candidate set when the candidate set includes at least one child category of the at least one parent category; determine feature vectors for the query image and cluster descriptors for images of items associated with the candidate set of categories; determine scores quantifying visual similarity between each of the images of items associated with the candidate set of categories with respect to the query image based at least in part on the feature vectors of the query image and the cluster descriptors for the images of items associated with the candidate set of categories, a respective visual similarity score of each image of an item with respect to the query image being weighted based at least in part on a position of a category of the item in the category tree; select a result set from among of the images of items associated with the categories in the candidate set based at least in part on the scores; and provide information corresponding to the result set for presentation.

17. A computerized system for searching a collection of content, comprising: a processor; and memory including instructions that, upon being executed by the processor, cause the computerized system to: identify a visually significant subset of categories of a category tree that categorizes the collection of content, the collection of content including a plurality of items each associated with one or more images, the visually significant subset including the categories of the category tree that are each associated with a respective set of images having a respective size that is greater than a lower size threshold and less than an upper size threshold; receive a search request associated with a query image; identify, among the visually significant subset, a candidate set of categories for the query image based at least in part on the search request, wherein at least one parent category is automatically excluded from the candidate set when the candidate set includes at least one child category of the at least one parent category; determine feature vectors for the query image and cluster descriptors for images of items associated with the candidate set of categories; determine scores quantifying visual similarity between each of the images of items associated with the candidate set of categories with respect to the query image based at least in part on the feature vectors of the query image and the cluster descriptors for the images of items associated with the candidate set of categories, a respective visual similarity score of each image of an item with respect to the query image being weighted based at least in part on a position of a category of the item in the category tree; select a result set from among of the images of items associated with the categories in the candidate set based at least in part on the scores; and provide information corresponding to the result set for presentation. 18. The computerized system according to claim 17 , wherein each category in the visually significant subset is associated with, at least: a respective unique identifier; a respective set of items; a respective set of images associated with the respective set of items; and a respective set of visual descriptors visually characterizing the respective set of images.