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AIPD_nlp_sentence_dataset_v2

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7. The method of claim 1 , wherein the relevance comprises a relevance matrix providing the relevance scores for the relevance of a given advertisement to each of the job candidates.

7. The method of claim 1 , wherein the relevance comprises a relevance matrix providing the relevance scores for the relevance of a given advertisement to each of the job candidates. 8. The method of claim 7 , wherein the value comprises a value matrix providing value scores for the value of presenting a given advertisement to each of the job candidates, the value scores calculated based on the relevance scores.

5. A method according to claim 1 , wherein additional potential input entries in said database each associate a target token sequence with at least one potential additional token sequence, and wherein said step of identifying additional potential input comprises the steps of: comparing tokens in said user input to said target token sequences; and selecting a set of at least one of said additional potential input entries in response to said step of comparing.

5. A method according to claim 1 , wherein additional potential input entries in said database each associate a target token sequence with at least one potential additional token sequence, and wherein said step of identifying additional potential input comprises the steps of: comparing tokens in said user input to said target token sequences; and selecting a set of at least one of said additional potential input entries in response to said step of comparing. 8. A method according to claim 5 , wherein said database further includes an importance value in correspondence with each association of a potential additional token sequence with a target token sequence, and wherein said step of comparing tokens in said user input to said target token sequences includes a step of calculating a confidence value of a given association in said database between a potential additional token sequence and a target token sequence, said confidence value being dependent upon both the importance value of the given association and a correlation between said tokens in said user input and the target token sequence of the given association.

11. The computer-implemented automatic Arabic text image optical character recognition method according to claim 10 , wherein each of the input Arabic text rows has a height and the step of segmenting each of the input Arabic text rows includes the step of segmenting the stack segments into an upper segment and a lower segment, the upper and lower segments each having a height of ¼ of the height of the corresponding input Arabic text row.

11. The computer-implemented automatic Arabic text image optical character recognition method according to claim 10 , wherein each of the input Arabic text rows has a height and the step of segmenting each of the input Arabic text rows includes the step of segmenting the stack segments into an upper segment and a lower segment, the upper and lower segments each having a height of ¼ of the height of the corresponding input Arabic text row. 12. The computer-implemented automatic Arabic text image optical character recognition method according to claim 11 , wherein the step of segmenting each of the input Arabic text rows further includes segmenting the stack segments into four intermediate segments between the upper segment and the lower segment, each of the intermediate segments having a height of ⅛ of the corresponding input Arabic text row.

19. An article of manufacture comprising: computer executable instructions stored on non-transitory computer readable media, which, when executed by a computer, causes the computer to perform operations comprising: receiving data characterizing each of a plurality of documents within each of a plurality of document sets; grouping the plurality of documents into a plurality of stacks using one or more grouping algorithms, wherein key words are identified in each document and weights specified by a scorecard scoring model are assigned to variables corresponding to each key word, wherein a scoring algorithm, using corresponding variables and weights, provides a score for each document which is used by the grouping algorithm when grouping the documents; identifying a prime document for each stack, the prime document including attributes representative of the entire stack; providing data characterizing documents for each stack including at least the identified prime document to at least one human reviewer; receiving user-generated input from the human reviewer categorizing each provided document; providing data characterizing the user-generated input; evaluating, by at least one data processor, identified grouping errors using at least one of Z-test techniques and multiple regression techniques; determining, by at least one data processor based on the evaluating, a relative contribution of the variables used by the grouping algorithm to the grouping errors; and modifying, by at least one data processor, the grouping algorithm so that at least one weight assigned by the grouping algorithm off-sets the relative contribution of the variables used by the grouping algorithm to an error rate, wherein documents in subsequently received sets of documents are grouped using the modified grouping algorithm.

19. An article of manufacture comprising: computer executable instructions stored on non-transitory computer readable media, which, when executed by a computer, causes the computer to perform operations comprising: receiving data characterizing each of a plurality of documents within each of a plurality of document sets; grouping the plurality of documents into a plurality of stacks using one or more grouping algorithms, wherein key words are identified in each document and weights specified by a scorecard scoring model are assigned to variables corresponding to each key word, wherein a scoring algorithm, using corresponding variables and weights, provides a score for each document which is used by the grouping algorithm when grouping the documents; identifying a prime document for each stack, the prime document including attributes representative of the entire stack; providing data characterizing documents for each stack including at least the identified prime document to at least one human reviewer; receiving user-generated input from the human reviewer categorizing each provided document; providing data characterizing the user-generated input; evaluating, by at least one data processor, identified grouping errors using at least one of Z-test techniques and multiple regression techniques; determining, by at least one data processor based on the evaluating, a relative contribution of the variables used by the grouping algorithm to the grouping errors; and modifying, by at least one data processor, the grouping algorithm so that at least one weight assigned by the grouping algorithm off-sets the relative contribution of the variables used by the grouping algorithm to an error rate, wherein documents in subsequently received sets of documents are grouped using the modified grouping algorithm. 32. An article as in claim 19 , wherein the data characterizing documents for each stack provided to the at least one human reviewer comprise reference numbers for such documents.

1. A method of evaluating a query against a data repository comprising a non-transitory storage device having at least one data partition, the method comprising: receiving a query at a dispatcher; communicating the query from the dispatcher to a director, the director comprising a module enabled to determine at least one repository node needed to execute the query, wherein the at least one repository node is in the data repository; dividing the query into at least two subqueries at the director, each subquery corresponding to pertinent information residing in different collections of the data repository; dividing at least one partition comprising tenant data into a set of at least two collections, wherein the partition resides on the at least one repository node; defining the context at the director for each subquery so as to encompass a collection containing the information pertinent to each subquery; communicating the subqueries from the director to the dispatcher; distributing at least one of the subqueries to a subdispatcher; evaluating the at least one of the subqueries against the defined context for the at least one of the subqueries context at the subdispatcher; gathering the information responsive to the at least one subquery; and returning the information as the response to the received query.

1. A method of evaluating a query against a data repository comprising a non-transitory storage device having at least one data partition, the method comprising: receiving a query at a dispatcher; communicating the query from the dispatcher to a director, the director comprising a module enabled to determine at least one repository node needed to execute the query, wherein the at least one repository node is in the data repository; dividing the query into at least two subqueries at the director, each subquery corresponding to pertinent information residing in different collections of the data repository; dividing at least one partition comprising tenant data into a set of at least two collections, wherein the partition resides on the at least one repository node; defining the context at the director for each subquery so as to encompass a collection containing the information pertinent to each subquery; communicating the subqueries from the director to the dispatcher; distributing at least one of the subqueries to a subdispatcher; evaluating the at least one of the subqueries against the defined context for the at least one of the subqueries context at the subdispatcher; gathering the information responsive to the at least one subquery; and returning the information as the response to the received query. 2. The method of claim 1 , wherein the evaluation of the subquery is affected by an extension to XQuery.

18. A computer-implemented method, comprising: generating a first score for a first set of rewrite rules, generating the first score comprising: rewriting multiple first strings of text based on the first set of rewrite rules, transmitting the rewrites of the multiple first strings of text over one or more networks, and generating the score based on user interactions with the transmitted rewrites of the multiple first strings of text; generating a second score for a second set of rewrite rules, generating the second score comprising: rewriting multiple second strings of text based on the second set of rewrite rules, transmitting the rewrites of the multiple second strings of text over one or more of the networks, and generating the second score based on second user interactions with the transmitted rewrites of the multiple second strings of text; identifying a future string of text from a given electronic resource, the given electronic resource being in addition to electronic resources that include the multiple first strings of text and the multiple second strings of text; selecting, for the future string of text from the given electronic resource, the first set of rewrite rules and the second set of rewrite rules based on: the first score for the first set of rewrite rules that is based on the first user interactions with the transmitted rewrites of the multiple first strings of text, and the second score for the set of rewrite rules that is based on the second user interactions with the transmitted rewrites of the multiple second strings of text, wherein the selecting comprises selecting the first set of rewrite rules and the second set of rewrite rules in lieu of other sets of the rewrite rules; generating one or more first rewrites of the future string of text based on the first set of rewrite rules and the future string of text; generating one or more second rewrites of the future string of text based on the second set of rewrite rules and the future string of text; determining effectiveness scores for each of the first rewrites and the second rewrites based on one or more objective functions; selecting a subset of the first and second rewrites based on the effectiveness scores; and providing the subset to one or more computing devices.

18. A computer-implemented method, comprising: generating a first score for a first set of rewrite rules, generating the first score comprising: rewriting multiple first strings of text based on the first set of rewrite rules, transmitting the rewrites of the multiple first strings of text over one or more networks, and generating the score based on user interactions with the transmitted rewrites of the multiple first strings of text; generating a second score for a second set of rewrite rules, generating the second score comprising: rewriting multiple second strings of text based on the second set of rewrite rules, transmitting the rewrites of the multiple second strings of text over one or more of the networks, and generating the second score based on second user interactions with the transmitted rewrites of the multiple second strings of text; identifying a future string of text from a given electronic resource, the given electronic resource being in addition to electronic resources that include the multiple first strings of text and the multiple second strings of text; selecting, for the future string of text from the given electronic resource, the first set of rewrite rules and the second set of rewrite rules based on: the first score for the first set of rewrite rules that is based on the first user interactions with the transmitted rewrites of the multiple first strings of text, and the second score for the set of rewrite rules that is based on the second user interactions with the transmitted rewrites of the multiple second strings of text, wherein the selecting comprises selecting the first set of rewrite rules and the second set of rewrite rules in lieu of other sets of the rewrite rules; generating one or more first rewrites of the future string of text based on the first set of rewrite rules and the future string of text; generating one or more second rewrites of the future string of text based on the second set of rewrite rules and the future string of text; determining effectiveness scores for each of the first rewrites and the second rewrites based on one or more objective functions; selecting a subset of the first and second rewrites based on the effectiveness scores; and providing the subset to one or more computing devices. 19. The method of claim 18 , wherein the first set of rewrite rules includes at least a first rewrite rule and a second rewrite rule, and wherein generating the first rewrites comprises: generating an intermediate rewrite by applying first rewrite rule; and generating a final rewrite of the first rewrites based on applying the second rewrite rule to the intermediate rewrite.

1. A method for pausing or resuming a VoiceXML dialog processed by a multimodal application, the method implemented with the multimodal application operating on a multimodal device supporting multiple modes of interaction including a voice mode and one or more non-voice modes, the multimodal application operatively coupled to a VoiceXML interpreter, the VoiceXML interpreter interpreting the VoiceXML dialog to be paused, the method comprising: providing a script variable to hold a pause keyword or a resume keyword that a script evaluates to when at least a portion of a user utterance is received via the multimodal application, and matches one or more words in a pause control grammar specified by the multimodal application; generating a pause event when the VoiceXML interpreter evaluates the script to the pause keyword; wherein generating the pause event is supported by utilizing a VoiceXML Form Interpretation Algorithm (FIA); wherein the FIA interprets the dialog instructions sequentially to identify the dialogs operating under one or more non-voice modes or one or more voice modes; responsive to the pause event, temporarily pausing the VoiceXML dialog by the VoiceXML interpreter; generating a resume event when the VoiceXML interpreter evaluates the script to the resume keyword; and responsive to the resume event, resuming the VoiceXML dialog.

1. A method for pausing or resuming a VoiceXML dialog processed by a multimodal application, the method implemented with the multimodal application operating on a multimodal device supporting multiple modes of interaction including a voice mode and one or more non-voice modes, the multimodal application operatively coupled to a VoiceXML interpreter, the VoiceXML interpreter interpreting the VoiceXML dialog to be paused, the method comprising: providing a script variable to hold a pause keyword or a resume keyword that a script evaluates to when at least a portion of a user utterance is received via the multimodal application, and matches one or more words in a pause control grammar specified by the multimodal application; generating a pause event when the VoiceXML interpreter evaluates the script to the pause keyword; wherein generating the pause event is supported by utilizing a VoiceXML Form Interpretation Algorithm (FIA); wherein the FIA interprets the dialog instructions sequentially to identify the dialogs operating under one or more non-voice modes or one or more voice modes; responsive to the pause event, temporarily pausing the VoiceXML dialog by the VoiceXML interpreter; generating a resume event when the VoiceXML interpreter evaluates the script to the resume keyword; and responsive to the resume event, resuming the VoiceXML dialog. 3. The method of claim 1 wherein: when the pause event is generated for dialogs operating under one or more voice modes, the multimodal application is playing a prompt through a text-to-speech (‘TTS’) engine and listening for voice input; temporarily pausing the VoiceXML dialog further comprises suspending by the multimodal application play of the prompt through the TTS engine, stopping listening for voice input, stopping a no-input timer, and waiting for the resume event; and resuming the VoiceXML dialog further comprises resuming by the multimodal application play of the prompt through the TTS engine, resuming listening for voice input, and restarting the no-input timer.

1. In a digital medium environment for distractor removal in an image, a method implemented by at least one computing device, the method comprising: forming, by the at least one computing device, a plurality of segments from the image; calculating, by the at least one computing device, a score for each of the plurality of segments that is indicative of a relative likelihood that a respective said segment is considered a distractor within the image, the calculating based on at least one distractor model trained using machine learning; classifying, by the at least one computing device, the plurality of segments as comprising salient objects that are less likely to be considered important to a user and salient objects that are more likely to be considered important to the user based on the calculated scores for the respective segments; outputting, by the at least one computing device, the classifications for the plurality of segments; and performing, by the at least one computing device, a modification to at least one segment of the plurality of segments based on the classifications of the plurality of segments.

1. In a digital medium environment for distractor removal in an image, a method implemented by at least one computing device, the method comprising: forming, by the at least one computing device, a plurality of segments from the image; calculating, by the at least one computing device, a score for each of the plurality of segments that is indicative of a relative likelihood that a respective said segment is considered a distractor within the image, the calculating based on at least one distractor model trained using machine learning; classifying, by the at least one computing device, the plurality of segments as comprising salient objects that are less likely to be considered important to a user and salient objects that are more likely to be considered important to the user based on the calculated scores for the respective segments; outputting, by the at least one computing device, the classifications for the plurality of segments; and performing, by the at least one computing device, a modification to at least one segment of the plurality of segments based on the classifications of the plurality of segments. 6. A method as described in claim 1 , wherein the scores for each of the plurality of segments is further based on respective locations of each of the plurality of segments within the image.

1. A method to provide internet-based services targeted to a geographic location, the method comprising: receiving a request from a user to provide internet-based services based on a target geographic location; obtaining a plurality of candidate geographic locations associated with the user, each candidate geographic location being associated with a respective candidate confidence level; calculating, with a computer, for one of the candidate geographic locations, a respective aggregate probabilistic utility score, the aggregate probabilistic utility score being based, at least in part, on distances from the respective candidate geographic location to the other candidate geographic locations and the confidence level scores of the other candidate geographic locations; selecting a geographic location based, at least in part, on the aggregate probabilistic utility score from among the candidate geographic locations; and providing internet-based services to the user targeting the selected geographic location.

1. A method to provide internet-based services targeted to a geographic location, the method comprising: receiving a request from a user to provide internet-based services based on a target geographic location; obtaining a plurality of candidate geographic locations associated with the user, each candidate geographic location being associated with a respective candidate confidence level; calculating, with a computer, for one of the candidate geographic locations, a respective aggregate probabilistic utility score, the aggregate probabilistic utility score being based, at least in part, on distances from the respective candidate geographic location to the other candidate geographic locations and the confidence level scores of the other candidate geographic locations; selecting a geographic location based, at least in part, on the aggregate probabilistic utility score from among the candidate geographic locations; and providing internet-based services to the user targeting the selected geographic location. 16. The method of claim 1 , further comprising: identifying an interstitial geographic location between candidate geographic locations; and wherein the aggregate probabilistic utility score is based, at least in part, on distances to the interstitial geographic location.

1. An apparatus for clustering process models each consisting of model elements comprising a text phrase which describes in a natural language a process activity according to a process modeling language grammar and a natural language grammar, wherein said apparatus comprises: (a) a process object ontology memory for storing a process object ontology; (b) a distance calculation unit for calculating a distance matrix employing said processing modeling language grammar and said natural language grammar, wherein said distance matrix consists of distances each indicating a dissimilarity of a pair of said process models; and (c) a clustering unit which partitions said process models into a set of clusters based on said calculated distance matrix.

1. An apparatus for clustering process models each consisting of model elements comprising a text phrase which describes in a natural language a process activity according to a process modeling language grammar and a natural language grammar, wherein said apparatus comprises: (a) a process object ontology memory for storing a process object ontology; (b) a distance calculation unit for calculating a distance matrix employing said processing modeling language grammar and said natural language grammar, wherein said distance matrix consists of distances each indicating a dissimilarity of a pair of said process models; and (c) a clustering unit which partitions said process models into a set of clusters based on said calculated distance matrix. 3. The apparatus according to claim 1 , wherein said clustering unit partitions said process models by means of a menoid-based clustering algorithm.

9. A system for creating a single collaborative review of a product or service offering, the system comprising: a means for receiving, by a web server, a first textual statement from a user directed to a first aspect of an offering, wherein the first textual statement is categorized by the user using a list of statement categories; a means for receiving, by the web server, a plurality of votes responsive to the first textual statement, each of the received votes comprising one of agree or disagree; a means for receiving, by the web server, a second textual statement from the user directed to a second aspect of the offering, wherein the second textual statement is categorized by the user using the list of statement categories; a means for receiving, by the web server, a plurality of votes responsive to the second textual statement, each of the received votes comprising one of agree or disagree; and a means for calculating, by an application logic processor executing on the web server, an overall rating for the offering based on a score of the plurality of votes for the first textual statement, wherein the score for the first textual statement is calculated by summing the number of received agree votes and subtracting the sum of the number of disagree votes for the first textual statement, and a score of the plurality of votes for the second textual statement, wherein the score for the second textual statement is calculated by summing the number of received agree votes and subtracting the sum of the number of disagree votes for the second textual statement.

9. A system for creating a single collaborative review of a product or service offering, the system comprising: a means for receiving, by a web server, a first textual statement from a user directed to a first aspect of an offering, wherein the first textual statement is categorized by the user using a list of statement categories; a means for receiving, by the web server, a plurality of votes responsive to the first textual statement, each of the received votes comprising one of agree or disagree; a means for receiving, by the web server, a second textual statement from the user directed to a second aspect of the offering, wherein the second textual statement is categorized by the user using the list of statement categories; a means for receiving, by the web server, a plurality of votes responsive to the second textual statement, each of the received votes comprising one of agree or disagree; and a means for calculating, by an application logic processor executing on the web server, an overall rating for the offering based on a score of the plurality of votes for the first textual statement, wherein the score for the first textual statement is calculated by summing the number of received agree votes and subtracting the sum of the number of disagree votes for the first textual statement, and a score of the plurality of votes for the second textual statement, wherein the score for the second textual statement is calculated by summing the number of received agree votes and subtracting the sum of the number of disagree votes for the second textual statement. 13. The system of claim 9 , further comprising means for calculating, by the application logic processor, an overall rating for the offering using the score for the first textual statement and the score for the second textual statement.

1. A method comprising: outputting for display on a graphical user interface of a client device, one or more media object identifiers based on a history log of media data usage of the client device; automatically generating an arrangement, without user interaction, of the one or more media object identifiers for display on the graphical user interface; receiving an override operation, the override operation altering the history log of media data usage; and automatically re-arranging the one or more media object identifiers of the arrangement in accordance with the altered history log of media data usage.

1. A method comprising: outputting for display on a graphical user interface of a client device, one or more media object identifiers based on a history log of media data usage of the client device; automatically generating an arrangement, without user interaction, of the one or more media object identifiers for display on the graphical user interface; receiving an override operation, the override operation altering the history log of media data usage; and automatically re-arranging the one or more media object identifiers of the arrangement in accordance with the altered history log of media data usage. 3. The method of claim 1 , wherein the override operation comprises at least one of an addition, deletion and adjust modifying operation.

6. The method of claim 2 , wherein different reliabilities of positioning said annotation are associated with each method, so as to determine a most reliable method, and wherein a computation of said annotation position is based on the most reliable methods.

6. The method of claim 2 , wherein different reliabilities of positioning said annotation are associated with each method, so as to determine a most reliable method, and wherein a computation of said annotation position is based on the most reliable methods. 7. The method of claim 6 , wherein a reliability distribution function indicating a reliability of at least one method at different points of said image.

16. An apparatus that translates a computer generated log output message file from a first language to a second language, said apparatus comprising: an input device that receives a log output message file containing a plurality of log output messages in a first language; a processor that: processes said plurality of log output messages into a canonical form by including at least one message variable field in at least one of said plurality of log output messages, said at least one message variable field comprising data indicating a position of said at least one message variable field in said at least one of said plurality of log output messages; analyzes each character of said at least one of said plurality of log output messages in said first language and identifies occurrences of any character, word, or phrase, according to said first language, in a message index file; matches characters, words, and phrases in said at least one of said plurality of log output messages to pre-established codes in said message index file, producing a matched message index comprising a string of data for each pre-established code having a match, each element of said string of data corresponding to said pre-established code on an element-by-element basis; compares, on an element-by-element basis, each string of data against every other string of data in said matched message index, identifying elements in a first string of data being completely overlapped by elements in another string of data as ambiguous matches; resolves said ambiguous matches by removing codes matched to ones of said characters, words, and phrases that have overlap with characters, words, and phrases matched to different codes; and translates said at least one of said plurality of log output messages into a second language using said codes in said matched message index by substituting characters, words, and phrases in said first language corresponding to matched codes with characters, words, and phrases in said second language corresponding to said matched codes, producing a log output message in said second language, said second language being different from said first language; and an output device that outputs said log output message in said second language.

16. An apparatus that translates a computer generated log output message file from a first language to a second language, said apparatus comprising: an input device that receives a log output message file containing a plurality of log output messages in a first language; a processor that: processes said plurality of log output messages into a canonical form by including at least one message variable field in at least one of said plurality of log output messages, said at least one message variable field comprising data indicating a position of said at least one message variable field in said at least one of said plurality of log output messages; analyzes each character of said at least one of said plurality of log output messages in said first language and identifies occurrences of any character, word, or phrase, according to said first language, in a message index file; matches characters, words, and phrases in said at least one of said plurality of log output messages to pre-established codes in said message index file, producing a matched message index comprising a string of data for each pre-established code having a match, each element of said string of data corresponding to said pre-established code on an element-by-element basis; compares, on an element-by-element basis, each string of data against every other string of data in said matched message index, identifying elements in a first string of data being completely overlapped by elements in another string of data as ambiguous matches; resolves said ambiguous matches by removing codes matched to ones of said characters, words, and phrases that have overlap with characters, words, and phrases matched to different codes; and translates said at least one of said plurality of log output messages into a second language using said codes in said matched message index by substituting characters, words, and phrases in said first language corresponding to matched codes with characters, words, and phrases in said second language corresponding to said matched codes, producing a log output message in said second language, said second language being different from said first language; and an output device that outputs said log output message in said second language. 17. The apparatus of claim 16 , said processor further generating said pre-established codes in said message index file that identify a correspondence of characters, words, and phrases in said first language with characters, words, and phrases in said second language corresponding in meaning to said characters, words, and phrases of said first language.

14. The computer storage medium of claim 13 , in which the operations further comprise: calculating the frequency of occurrence of the alternative query; calculating the user satisfaction score for the alternative query; and computing a rank for the alternative query as a function of the frequency of occurrence and the user satisfaction score, in which the alternative query is identified as the highly-ranked query based on the rank.

14. The computer storage medium of claim 13 , in which the operations further comprise: calculating the frequency of occurrence of the alternative query; calculating the user satisfaction score for the alternative query; and computing a rank for the alternative query as a function of the frequency of occurrence and the user satisfaction score, in which the alternative query is identified as the highly-ranked query based on the rank. 15. The computer storage medium of claim 14 , in which the user satisfaction score is based on an inverse revision frequency.

8. A non-transitory computer-readable storage medium for matching audio sequences, the computer-readable medium storing processor-executable instructions comprising: instructions for deriving a first probability density function P M outputting a probability that an initial correspondence score for a pair of chroma vectors of an audio sequence indicates a semantic correspondence between the chroma vectors; instructions for deriving a second probability density function P R outputting a probability that the initial correspondence score for a pair of chroma vectors of an audio sequence indicates that the chroma vectors have a random correspondence, the deriving of P R comprising: randomly selecting a set of pairs of audio sequences; deriving initial correspondence scores for the set of pairs of audio sequences; and fitting the initial correspondence scores to a probability distribution; instructions for deriving, using P M and P R , a match function indicating whether a given pair of chroma vectors of an audio sequence correspond semantically; instructions for obtaining a first audio sequence; instructions for comparing, using the match function, the first audio sequence with a plurality of known audio sequences; and instructions for, based on the comparing, identifying a best-matching audio sequence for the first audio sequence from the known audio sequences.

8. A non-transitory computer-readable storage medium for matching audio sequences, the computer-readable medium storing processor-executable instructions comprising: instructions for deriving a first probability density function P M outputting a probability that an initial correspondence score for a pair of chroma vectors of an audio sequence indicates a semantic correspondence between the chroma vectors; instructions for deriving a second probability density function P R outputting a probability that the initial correspondence score for a pair of chroma vectors of an audio sequence indicates that the chroma vectors have a random correspondence, the deriving of P R comprising: randomly selecting a set of pairs of audio sequences; deriving initial correspondence scores for the set of pairs of audio sequences; and fitting the initial correspondence scores to a probability distribution; instructions for deriving, using P M and P R , a match function indicating whether a given pair of chroma vectors of an audio sequence correspond semantically; instructions for obtaining a first audio sequence; instructions for comparing, using the match function, the first audio sequence with a plurality of known audio sequences; and instructions for, based on the comparing, identifying a best-matching audio sequence for the first audio sequence from the known audio sequences. 13. The non-transitory computer-readable storage medium of claim 8 , the instructions further comprising instructions for deriving the match function as a logarithm of a ratio of P M and P R .

18. A non-transitory computer readable storage medium for generating project specific configuration data, the computer readable storage medium comprising computer code instructions executable by a computer and comprising instructions for: receiving, via a data interface, a plurality of items of project template data; storing, using a database connection, the project template data; receiving, via the data interface, question configuration data representing at least one question and at least one associated candidate answer; storing, using the database connection, the question configuration data; receiving, via the data interface, rule data representing a rule relating the project template data and the question configuration data; storing, using the database connection, the rule data; sending, via the data interface, question data from the question configuration data; receiving, via the data interface, answer data in response to the question data; and generating project specific configuration data from the project template data in accordance with the answer data and the rule data, wherein the rule data maps the answer data to the items of project template data to select items of project template data, wherein the selected items of project template data are added to build the project configuration data.

18. A non-transitory computer readable storage medium for generating project specific configuration data, the computer readable storage medium comprising computer code instructions executable by a computer and comprising instructions for: receiving, via a data interface, a plurality of items of project template data; storing, using a database connection, the project template data; receiving, via the data interface, question configuration data representing at least one question and at least one associated candidate answer; storing, using the database connection, the question configuration data; receiving, via the data interface, rule data representing a rule relating the project template data and the question configuration data; storing, using the database connection, the rule data; sending, via the data interface, question data from the question configuration data; receiving, via the data interface, answer data in response to the question data; and generating project specific configuration data from the project template data in accordance with the answer data and the rule data, wherein the rule data maps the answer data to the items of project template data to select items of project template data, wherein the selected items of project template data are added to build the project configuration data. 24. The non-transitory computer readable storage medium as claimed in claim 18 , wherein the project template data comprises risk template data representing at least one risk template.

27. A digital conversation generating processor-implemented method, comprising: instantiating a processor-implemented dialogue agent; identifying an individual target for conversation; initiating a conversational dialogue between the individual target and the dialogue agent; recording a first dialogue segment from the individual target as part of the conversational dialogue, wherein the first dialogue segment is a subportion of the conversational dialogue; responding to the first dialogue segment from the individual target with an at least one subsequent response dialogue segment, wherein the at least one subsequent response dialogue segment is a subportion of the conversational dialogue; recording a subsequent dialogue segment from the individual target, wherein the subsequent dialogue segment is a subportion of the conversational dialogue; retrieving the recorded interactive dialogue between the individual target and the dialogue agent; allocating a value point to each interactive dialogue segment of the interactive dialogue; creating a digital conversation asset comprising at least the retrieved interactive dialogue associated with the allocated value point to each subsequent interactive dialogue segment of the interactive dialogue; determining a value for the digital conversation asset at least based on the allocated value point to each subsequent interactive dialogue segment of the interactive dialogue; and providing the created digital conversation asset associated with the determined value for exchange.

27. A digital conversation generating processor-implemented method, comprising: instantiating a processor-implemented dialogue agent; identifying an individual target for conversation; initiating a conversational dialogue between the individual target and the dialogue agent; recording a first dialogue segment from the individual target as part of the conversational dialogue, wherein the first dialogue segment is a subportion of the conversational dialogue; responding to the first dialogue segment from the individual target with an at least one subsequent response dialogue segment, wherein the at least one subsequent response dialogue segment is a subportion of the conversational dialogue; recording a subsequent dialogue segment from the individual target, wherein the subsequent dialogue segment is a subportion of the conversational dialogue; retrieving the recorded interactive dialogue between the individual target and the dialogue agent; allocating a value point to each interactive dialogue segment of the interactive dialogue; creating a digital conversation asset comprising at least the retrieved interactive dialogue associated with the allocated value point to each subsequent interactive dialogue segment of the interactive dialogue; determining a value for the digital conversation asset at least based on the allocated value point to each subsequent interactive dialogue segment of the interactive dialogue; and providing the created digital conversation asset associated with the determined value for exchange. 47. The method of claim 27 , wherein a digital conversation asset comprises a text-to-speech module that converts a dialogue script input to speech.

1. An anchor assembly comprising: an anchor body comprising an anchor formed in one piece with a yoke; said yoke has first and second arms and forms a U shape; a shaft spanning the yoke of the anchor body between the first and second arms of the yoke; a saddle having a first bore, wherein the shaft is received through said first bore; said saddle adapted to receive a member; a compression unit that is positioned in a second bore of the saddle adjacent the shaft, and said compression unit adapted to be adjacent the member received in said saddle; a set that is received in said saddle and adapted to selectively apply force against the member received in said saddle and thereby apply force through said compression unit to said shaft; and wherein said compression unit includes a first recess that is adapted to receive the member and a second recess that can receive the shaft.

1. An anchor assembly comprising: an anchor body comprising an anchor formed in one piece with a yoke; said yoke has first and second arms and forms a U shape; a shaft spanning the yoke of the anchor body between the first and second arms of the yoke; a saddle having a first bore, wherein the shaft is received through said first bore; said saddle adapted to receive a member; a compression unit that is positioned in a second bore of the saddle adjacent the shaft, and said compression unit adapted to be adjacent the member received in said saddle; a set that is received in said saddle and adapted to selectively apply force against the member received in said saddle and thereby apply force through said compression unit to said shaft; and wherein said compression unit includes a first recess that is adapted to receive the member and a second recess that can receive the shaft. 3. The anchor assembly of claim 1 wherein said first recess is not aligned with said second recess.

101. The computer program product of claim 74 , wherein the computer program product is configured such that the plurality of message summaries comprise second information derived from a second message of a plurality of second messages associated with a second online forum that is different from the first online forum.

101. The computer program product of claim 74 , wherein the computer program product is configured such that the plurality of message summaries comprise second information derived from a second message of a plurality of second messages associated with a second online forum that is different from the first online forum. 108. The computer program product of claim 101 , wherein the computer program product is configured such that the first on-line forum is associated with a first website, and the second on-line forum is associated with a second website.

1. In a computing environment, a method for persisting data clippings categorized according to metadata associated with the clippings at the time of the creation of the clippings, the method comprising: detecting that a user has selected one or more items from a source file that is stored on a memory storage device, the items is captured for inclusion in a clipping; determining the format of each item included in the clipping, wherein at least one of the items includes a plurality of different formats where at least one of the plurality of different formats includes a greater amount of item formatting information than another format; identifying a file path for the source file from which the clipping was selected, the file path to access additional items from the source file; generating associated metadata about the selected clipping including the determined formats of each item in the selected clipping and an activatable hyperlink that, upon activation, is configured to access the source file using a stored file path linking the clipping to the source file; for each item of the clipping: determining that the items include a plurality of different formats, each different format including a greater or lesser amount of item formatting information in comparison to the other formats, such that a format with a greater or lesser amount of item formatting information than the format in which the item was initially captured for inclusion in the clipping is selectable by the user for inserting the item; persisting the item in the determined plurality of different formats based on item type along with the associated metadata, the item is configured for insertion into software application fields in any of the plurality of formats; and inserting the items into one or more data fields of a software application in a format different than the format in which the item was initially captured for inclusion in the clipping, the format is selected by the application and based on at least some of the associated metadata, the selected format for each item selected from among the plurality of formats the item was persisted in; receiving a user request to access one or more additional items from the source file; based on the received user request, activating the hyperlink to access the one or more additional items in the source file using the hyperlink provided in the associated metadata; and providing a user interface having a plurality of user-selectable views, wherein at least one of the user-selectable views displays a thumbnail in a user-preferred format corresponding to at least one of the clippings, and wherein at least one of the user-selectable views displays a list view including text corresponding to the clippings.

1. In a computing environment, a method for persisting data clippings categorized according to metadata associated with the clippings at the time of the creation of the clippings, the method comprising: detecting that a user has selected one or more items from a source file that is stored on a memory storage device, the items is captured for inclusion in a clipping; determining the format of each item included in the clipping, wherein at least one of the items includes a plurality of different formats where at least one of the plurality of different formats includes a greater amount of item formatting information than another format; identifying a file path for the source file from which the clipping was selected, the file path to access additional items from the source file; generating associated metadata about the selected clipping including the determined formats of each item in the selected clipping and an activatable hyperlink that, upon activation, is configured to access the source file using a stored file path linking the clipping to the source file; for each item of the clipping: determining that the items include a plurality of different formats, each different format including a greater or lesser amount of item formatting information in comparison to the other formats, such that a format with a greater or lesser amount of item formatting information than the format in which the item was initially captured for inclusion in the clipping is selectable by the user for inserting the item; persisting the item in the determined plurality of different formats based on item type along with the associated metadata, the item is configured for insertion into software application fields in any of the plurality of formats; and inserting the items into one or more data fields of a software application in a format different than the format in which the item was initially captured for inclusion in the clipping, the format is selected by the application and based on at least some of the associated metadata, the selected format for each item selected from among the plurality of formats the item was persisted in; receiving a user request to access one or more additional items from the source file; based on the received user request, activating the hyperlink to access the one or more additional items in the source file using the hyperlink provided in the associated metadata; and providing a user interface having a plurality of user-selectable views, wherein at least one of the user-selectable views displays a thumbnail in a user-preferred format corresponding to at least one of the clippings, and wherein at least one of the user-selectable views displays a list view including text corresponding to the clippings. 5. The method of claim 1 wherein persisting the item in a plurality of formats based on item type along with the associated metadata includes persisting size information in association with at least some of the clippings.

1. A method of detecting text in a television video display table, comprising: saving a frame of video representing an image to a memory device; determining that the frame of video contains a table having cells containing text; storing a working copy of the frame of video to a memory; isolating text in the table by: removing any table boundaries from the image; removing any cell boundaries from the image; determining if the image has three dimensional or shadow attributes in the table boundaries or cell boundaries and removing any three dimensional or shadow attributes identified, wherein determining if the image has three dimensional or shadow attributes in the table boundaries or cell boundaries is carried out by finding line patterns adjacent and outside table or cell boundaries that track a table or cell boundary; where determining if a cell has three dimensional or shadow attributes is carried out by subtracting a variable rectangular band of pixels from other cell values to see what size band maximizes cancellation in order to distinguish the cell from the text area; thereby producing text isolated against a contrasting color background; and processing the isolated text using an optical character recognition (OCR) engine to extract the text as data.

1. A method of detecting text in a television video display table, comprising: saving a frame of video representing an image to a memory device; determining that the frame of video contains a table having cells containing text; storing a working copy of the frame of video to a memory; isolating text in the table by: removing any table boundaries from the image; removing any cell boundaries from the image; determining if the image has three dimensional or shadow attributes in the table boundaries or cell boundaries and removing any three dimensional or shadow attributes identified, wherein determining if the image has three dimensional or shadow attributes in the table boundaries or cell boundaries is carried out by finding line patterns adjacent and outside table or cell boundaries that track a table or cell boundary; where determining if a cell has three dimensional or shadow attributes is carried out by subtracting a variable rectangular band of pixels from other cell values to see what size band maximizes cancellation in order to distinguish the cell from the text area; thereby producing text isolated against a contrasting color background; and processing the isolated text using an optical character recognition (OCR) engine to extract the text as data. 7. The method according to claim 1 , wherein removing the boundaries of the cells and the tables is carried out by matching a display to a template in order to locate the boundaries.

1. A method for converting a semantic markup representation of a document into a physical markup representation of the document, comprising: calculating a logical minimum width equal to the minimum width required to display all screen objects within the document at their normal size; creating a physical markup representation of the document, the physical markup representation having a width at least as wide as the logical minimum width; and conforming the physical markup representation to a target size, including a target width, conforming the physical markup representation comprising: testing whether a scaling factor derived from a ratio of the target width to the logical minimum width is less than a specified threshold: rotating the pages of the physical markup representation by plus or minus 90° based on testing whether the scaling factor is less than the specified threshold; and scaling the width of the physical markup representation by the scaling factor or by a recalculated scaling factor derived from a new ratio of the target width to a new logical minimum width of the rotated pages.

1. A method for converting a semantic markup representation of a document into a physical markup representation of the document, comprising: calculating a logical minimum width equal to the minimum width required to display all screen objects within the document at their normal size; creating a physical markup representation of the document, the physical markup representation having a width at least as wide as the logical minimum width; and conforming the physical markup representation to a target size, including a target width, conforming the physical markup representation comprising: testing whether a scaling factor derived from a ratio of the target width to the logical minimum width is less than a specified threshold: rotating the pages of the physical markup representation by plus or minus 90° based on testing whether the scaling factor is less than the specified threshold; and scaling the width of the physical markup representation by the scaling factor or by a recalculated scaling factor derived from a new ratio of the target width to a new logical minimum width of the rotated pages. 2. The method of claim 1 , the method further comprising: incorporating the physical markup representation into a newly created document.

18. A device comprising: a memory containing programming instructions; and a processor coupled to the memory, to execute the programming instructions to: receive personal information relating to a user, the personal information including at least one of a geographic location of the user, information provided by the user when registering art account, or information based on a browsing history of the user; receive a first web page requested by the user; identify one or more terms in the first web page; locate at least one additional web page by submitting a plurality of different search queries to a search engine, where each of the plurality of different search queries includes a different combination of terms from the one or more terms in the first web page and terms based on the personal information relating to the user; embed a reference to the at least one additional web page into the first web page next to the identified word or phrase to form a modified first web page; and transmit the modified first web page to the user.

18. A device comprising: a memory containing programming instructions; and a processor coupled to the memory, to execute the programming instructions to: receive personal information relating to a user, the personal information including at least one of a geographic location of the user, information provided by the user when registering art account, or information based on a browsing history of the user; receive a first web page requested by the user; identify one or more terms in the first web page; locate at least one additional web page by submitting a plurality of different search queries to a search engine, where each of the plurality of different search queries includes a different combination of terms from the one or more terms in the first web page and terms based on the personal information relating to the user; embed a reference to the at least one additional web page into the first web page next to the identified word or phrase to form a modified first web page; and transmit the modified first web page to the user. 19. The device of claim 18 , where the instructions to locate at least one additional web page comprise instructions to rank results returned by the search engine based on at least one of a relevance score of a document, a number of times a document was selected, or a date of a document.

1. A system for managing an autonomous actor network, the system comprising: a metadata collector configured to obtain metadata information associated with the autonomous actor network and autonomous actors included therein; an autonomous actor, said autonomous actor including a self-assessment identifier indicative of: metadata elements stored by the autonomous actor, a quantity of metadata information for each metadata element stored by the autonomous actor, and a relationship between the metadata elements for the autonomous actor and the quantity of metadata information stored for each metadata element, wherein the relationship includes a threshold result; and a processor configured to generate an assessment value for the autonomous actor based on the obtained metadata information and the self-assessment identifier, wherein the processor is configured to generate the assessment value at least in part by comparing the threshold result to a combination of the metadata elements for the autonomous actor and the quantity of metadata information stored for each metadata element in accordance with an identified process.

1. A system for managing an autonomous actor network, the system comprising: a metadata collector configured to obtain metadata information associated with the autonomous actor network and autonomous actors included therein; an autonomous actor, said autonomous actor including a self-assessment identifier indicative of: metadata elements stored by the autonomous actor, a quantity of metadata information for each metadata element stored by the autonomous actor, and a relationship between the metadata elements for the autonomous actor and the quantity of metadata information stored for each metadata element, wherein the relationship includes a threshold result; and a processor configured to generate an assessment value for the autonomous actor based on the obtained metadata information and the self-assessment identifier, wherein the processor is configured to generate the assessment value at least in part by comparing the threshold result to a combination of the metadata elements for the autonomous actor and the quantity of metadata information stored for each metadata element in accordance with an identified process. 11. The system of claim 1 , wherein the assessment value identifies a quantity of an overall goal achieved by the associated autonomous actor.

1. A method for identifying actions by semantic analysis of a natural language input, comprising: receiving a natural language input from a user; performing a semantic analysis of the natural language input to identify probable matches to a plurality of scripts as a function of an initial semantic mapping associated with each script; probabilistically scoring using a computer processor and sorting the identified scripts to construct a rank ordered list of probable scripts; and presenting the rank ordered list of probable scripts to the user via a user interface.

1. A method for identifying actions by semantic analysis of a natural language input, comprising: receiving a natural language input from a user; performing a semantic analysis of the natural language input to identify probable matches to a plurality of scripts as a function of an initial semantic mapping associated with each script; probabilistically scoring using a computer processor and sorting the identified scripts to construct a rank ordered list of probable scripts; and presenting the rank ordered list of probable scripts to the user via a user interface. 4. The method of claim 1 wherein the scripts within the rank ordered list of probable scripts are user selectable via the user interface.

10. A system, comprising: a memory unit for storing a computer program for checking documents using colloquialisms; and a processor coupled to the memory unit, wherein the processor is configured to execute the program instructions of the computer program comprising: tracking colloquialisms used in messages by users in a social network, wherein said colloquialisms are words or phrases used in informal online communications, wherein said colloquialisms comprise words or phrases that vary from region to region; identifying relationships between senders and recipients of said messages using said colloquialisms; generating a social graph to depict relations between said users in said social network based on said identified relationships; formulating usage patterns of said colloquialisms among said users of said social graph; generating a rule set based on said social graph; and reviewing a document for spelling and/or grammatical errors and/or for making contextual relevant recommendations using said generated rule set.

10. A system, comprising: a memory unit for storing a computer program for checking documents using colloquialisms; and a processor coupled to the memory unit, wherein the processor is configured to execute the program instructions of the computer program comprising: tracking colloquialisms used in messages by users in a social network, wherein said colloquialisms are words or phrases used in informal online communications, wherein said colloquialisms comprise words or phrases that vary from region to region; identifying relationships between senders and recipients of said messages using said colloquialisms; generating a social graph to depict relations between said users in said social network based on said identified relationships; formulating usage patterns of said colloquialisms among said users of said social graph; generating a rule set based on said social graph; and reviewing a document for spelling and/or grammatical errors and/or for making contextual relevant recommendations using said generated rule set. 13. The system as recited in claim 10 , wherein the program instructions of the computer program further comprise: generating said rule set based on said social graph and said usage patterns of said colloquialisms among said users of said social graph.

9. The method of claim 1 , wherein the review search criteria further specify a desired product characteristic.

9. The method of claim 1 , wherein the review search criteria further specify a desired product characteristic. 10. The method of claim 9 , wherein the desired product characteristic is good service, quality, or affordability.

1. A computer-implemented method comprising: receiving, at a search system from a user device associated with a user, user input comprising one or more characters of a partial search query; determining that the one or more characters of the partial search query correspond to a trigger query; in response to determining that the one or more characters of the partial search query correspond to a trigger query, determining a predicted query for the trigger query, the predicted query comprising the trigger query and additional information for refining the trigger query; and providing the predicted query to the user device for presentation to the user prior to the user submitting a search query to the search system.

1. A computer-implemented method comprising: receiving, at a search system from a user device associated with a user, user input comprising one or more characters of a partial search query; determining that the one or more characters of the partial search query correspond to a trigger query; in response to determining that the one or more characters of the partial search query correspond to a trigger query, determining a predicted query for the trigger query, the predicted query comprising the trigger query and additional information for refining the trigger query; and providing the predicted query to the user device for presentation to the user prior to the user submitting a search query to the search system. 3. The method of claim 1 , wherein providing the predicted query to the user device comprises providing the predicted query to the user device prior to providing search results in response to the user input.

26. The computerized system of claim 25 , wherein the computer program product stored on the computer-readable medium further comprise instructions that, when read into the RAM and executed on the processor, cause the processor to, if the first tokenized set does not comprise an equal number of tokens as the second tokenized set, tokenize the first term and the second term by three-step tokenization.

26. The computerized system of claim 25 , wherein the computer program product stored on the computer-readable medium further comprise instructions that, when read into the RAM and executed on the processor, cause the processor to, if the first tokenized set does not comprise an equal number of tokens as the second tokenized set, tokenize the first term and the second term by three-step tokenization. 27. The computerized system of claim 26 , wherein the computer program product stored on the computer-readable medium further comprise instructions that, when read into the RAM and executed on the processor, cause the processor to: a. tokenize the first term and the second term to create a third tokenized set comprising a plurality of third tokens comprising at least one phoneme and a fourth tokenized set comprising a plurality of fourth tokens comprising at least one phoneme; b. after the processes tokenizes the first term and the second term, compare the third tokenized set to the fourth tokenized set to determine if the third tokenized set comprises an equal number of tokens as the fourth tokenized set; c. determine if the third tokenized set comprises an equal number of tokens as the fourth tokenized set, and if so compare the third tokens to the fourth tokens to determine if the tokens are identical or phonetically equivalent; and d. output from the processor an indicator of whether the first term and second term are phonetically equivalent.

1. A computer program product, comprising a computer usable medium having a computer readable program code embodied therein, the computer readable program code adapted to be executed to implement a method for automatically generating a package design, the method comprising: receiving, from a user via an input device, a packaging intent comprising one or more constraints, wherein the one or more constraints comprise one or more of the following industry constraints: trade or industry association guidelines; brand identification guidelines; instructions for product use; coding for quality assurance; expiration dates; or dietary and nutritional information; automatically generating, with a processing module and a semantic knowledge base, one or more external graphical layout rules and one or more structural design rules based on the one or more constraints, wherein the external graphical layout rules are associated with a plurality of graphical assets and guide a relationship between a graphical asset and layout of each graphical asset on one or more exterior surfaces of the package; automatically generating a three dimensional representation of a package design based on the one or more external graphical layout rules and the one or more structural design rules, wherein automatically generating a three dimensional representation comprises, for at least one graphical asset of the plurality of graphical assets, determining an exterior surface location, on the three dimensional representation, associated with the at least one graphical asset and determining one or more boundaries associated with the at least one graphical asset based at least in part on the one or more industry constraints; and displaying the three dimensional representation of the package design, wherein displaying the three dimensional representation comprises displaying the at least one of the plurality of graphical assets at the determined exterior surface location and within the determined boundaries associated with the graphical asset.

1. A computer program product, comprising a computer usable medium having a computer readable program code embodied therein, the computer readable program code adapted to be executed to implement a method for automatically generating a package design, the method comprising: receiving, from a user via an input device, a packaging intent comprising one or more constraints, wherein the one or more constraints comprise one or more of the following industry constraints: trade or industry association guidelines; brand identification guidelines; instructions for product use; coding for quality assurance; expiration dates; or dietary and nutritional information; automatically generating, with a processing module and a semantic knowledge base, one or more external graphical layout rules and one or more structural design rules based on the one or more constraints, wherein the external graphical layout rules are associated with a plurality of graphical assets and guide a relationship between a graphical asset and layout of each graphical asset on one or more exterior surfaces of the package; automatically generating a three dimensional representation of a package design based on the one or more external graphical layout rules and the one or more structural design rules, wherein automatically generating a three dimensional representation comprises, for at least one graphical asset of the plurality of graphical assets, determining an exterior surface location, on the three dimensional representation, associated with the at least one graphical asset and determining one or more boundaries associated with the at least one graphical asset based at least in part on the one or more industry constraints; and displaying the three dimensional representation of the package design, wherein displaying the three dimensional representation comprises displaying the at least one of the plurality of graphical assets at the determined exterior surface location and within the determined boundaries associated with the graphical asset. 13. The computer program product of claim 1 wherein: the one or more constraints further comprise a warehousing constraint; and said automatically generating one or more structural design rules comprises: accessing the semantic knowledge base to obtain one or more structural requirements, selecting from the one or more structural requirements an applicable package size based on the warehousing constraint; and causing the structural design rules to correspond to the applicable package size.

74. A method for discovering resources in a peer-to-peer network, the method comprising: a peer node broadcasting a discovery query message specifying a type of resource on the network; and the peer node receiving advertisements for the specified type of resource in response to said discovery query message, wherein advertisements include a peer advertisement and a content or service advertisement, wherein one or more other peer nodes publish the peer and content or service advertisements on the peer-to-peer network; wherein the service or content advertisement comprises an identification of a corresponding service or content and an indication of how to access the corresponding service or content; wherein the peer advertisement comprises an identification of a corresponding one of said peers and communication address for the corresponding one of said peers, wherein one or more of said peer advertisements further comprises an indication of a service or a content provided by the peer corresponding to that peer advertisement; wherein each advertisement is a programming language independent metadata document formatted in accordance with a peer-to-peer protocol.

74. A method for discovering resources in a peer-to-peer network, the method comprising: a peer node broadcasting a discovery query message specifying a type of resource on the network; and the peer node receiving advertisements for the specified type of resource in response to said discovery query message, wherein advertisements include a peer advertisement and a content or service advertisement, wherein one or more other peer nodes publish the peer and content or service advertisements on the peer-to-peer network; wherein the service or content advertisement comprises an identification of a corresponding service or content and an indication of how to access the corresponding service or content; wherein the peer advertisement comprises an identification of a corresponding one of said peers and communication address for the corresponding one of said peers, wherein one or more of said peer advertisements further comprises an indication of a service or a content provided by the peer corresponding to that peer advertisement; wherein each advertisement is a programming language independent metadata document formatted in accordance with a peer-to-peer protocol. 82. The method as recited in claim 74 , wherein the resource type specifies one of a peer node, a peer group, a pipe, a pipe endpoint, content, or a service.

15. A system for automatically analyzing a conversation between a plurality ofusers, the system comprising: a data collection module on a computer comprising a processor and memory configured to receive signals corresponding to a training dataset including a plurality of data sequences related to the conversation; a feature extraction module on the computer configured to extract at least one feature from the received training dataset based on predefined feature categories; a learning module on the computer configured to: formulate a plurality of tasks for being learned from the training dataset based on the extracted at least one feature, wherein each of the plurality of tasks is related to at least one predefined label; provide a model for each of the plurality of formulated tasks, wherein the model includes one or more parameters having a set of parameters common to the plurality of formulated tasks, wherein the set of parameters includes at least one label dependency factor, that is an explicit parameter, which is explicitly shared with each of the plurality of formulated tasks; optimize values for the one or more parameters and the at least one explicit parameter to create an optimized model; and create a trained model for each of the plurality of formulated tasks using an optimized value of the at least one explicit parameter and corresponding values of the one or more parameters; and a classification module on the computer configured to assign the at least one predefined label for each of the plurality of formulated tasks on to a live dataset based on the created trained model, wherein the computer is configured to output signals corresponding to the live dataset assigned with the at least one predefined label for each of the plurality of formulated tasks.

15. A system for automatically analyzing a conversation between a plurality ofusers, the system comprising: a data collection module on a computer comprising a processor and memory configured to receive signals corresponding to a training dataset including a plurality of data sequences related to the conversation; a feature extraction module on the computer configured to extract at least one feature from the received training dataset based on predefined feature categories; a learning module on the computer configured to: formulate a plurality of tasks for being learned from the training dataset based on the extracted at least one feature, wherein each of the plurality of tasks is related to at least one predefined label; provide a model for each of the plurality of formulated tasks, wherein the model includes one or more parameters having a set of parameters common to the plurality of formulated tasks, wherein the set of parameters includes at least one label dependency factor, that is an explicit parameter, which is explicitly shared with each of the plurality of formulated tasks; optimize values for the one or more parameters and the at least one explicit parameter to create an optimized model; and create a trained model for each of the plurality of formulated tasks using an optimized value of the at least one explicit parameter and corresponding values of the one or more parameters; and a classification module on the computer configured to assign the at least one predefined label for each of the plurality of formulated tasks on to a live dataset based on the created trained model, wherein the computer is configured to output signals corresponding to the live dataset assigned with the at least one predefined label for each of the plurality of formulated tasks. 16. The system of claim 15 , wherein the set of parameters include at least one parameter having variance specific to each of the plurality of formulated tasks.

6. A system for mitigating denial of service attacks against and improving performance of an Internet search system, said system comprising: an input/output portion for: receiving a request for information, said request comprising at least one search expression; and a memory portion, wherein said memory portion stores previous requests for information; and a processor portion for: searching, with said at least one search expression instead of a hash value based on said at least one search expression, said memory portion for an indication as to whether said information is in external memory; if a result of searching said memory portion is indicative of said information being in said external memory and said information is in said memory portion, providing said information from said memory portion; if said result of searching said memory portion is indicative of said information being in said external memory and said information is not in said memory portion, querying with said at least one search expression via said input/output portion said external memory for said information; and if said result of searching said memory portion is indicative of said information not being in said external memory, forgoing a query of said external memory; if on a condition that said result of searching said memory portion is indicative of said at least one search expression not being in said memory portion: computing at least one hash value based on said at least one search expression; querying with said at least one hash value a probabilistic detector, wherein said probabilistic detector is populated with at least one computed hash value based on each expression in an index of said external memory, for an indication as to whether said information is in said external memory; determining if said queried for indication is indicative of said information being in said external memory; and if said queried for indication is indicative of said information being in said external memory, querying with said at least one search expression, and not with the at least one hash value based on said at least one search expression, said external memory for said information.

6. A system for mitigating denial of service attacks against and improving performance of an Internet search system, said system comprising: an input/output portion for: receiving a request for information, said request comprising at least one search expression; and a memory portion, wherein said memory portion stores previous requests for information; and a processor portion for: searching, with said at least one search expression instead of a hash value based on said at least one search expression, said memory portion for an indication as to whether said information is in external memory; if a result of searching said memory portion is indicative of said information being in said external memory and said information is in said memory portion, providing said information from said memory portion; if said result of searching said memory portion is indicative of said information being in said external memory and said information is not in said memory portion, querying with said at least one search expression via said input/output portion said external memory for said information; and if said result of searching said memory portion is indicative of said information not being in said external memory, forgoing a query of said external memory; if on a condition that said result of searching said memory portion is indicative of said at least one search expression not being in said memory portion: computing at least one hash value based on said at least one search expression; querying with said at least one hash value a probabilistic detector, wherein said probabilistic detector is populated with at least one computed hash value based on each expression in an index of said external memory, for an indication as to whether said information is in said external memory; determining if said queried for indication is indicative of said information being in said external memory; and if said queried for indication is indicative of said information being in said external memory, querying with said at least one search expression, and not with the at least one hash value based on said at least one search expression, said external memory for said information. 11. A system in accordance with claim 6 , wherein said memory portion comprises local memory.

20. The method of claim 18 , further comprising the steps of: damping a change in the calculated value of the at least one parameter by applying a filtering operation to produce a damped value; and setting the calculated value equal to the damped value.

20. The method of claim 18 , further comprising the steps of: damping a change in the calculated value of the at least one parameter by applying a filtering operation to produce a damped value; and setting the calculated value equal to the damped value. 22. The method of claim 20 , wherein the step of damping a change in the calculated value further comprises the step of applying a slew-rate-limiter to limit a maximum rate of change of calculated value with respect to previous values of the at least one parameter to produce a damped value.

1. A computer-implemented method for automated generation of web sites, the method comprising: (a) generating a plurality of web page templates and storing them in a template library on a content server; (b) establishing a network connection between the content server and a client; launching a site builder application on a client, the site builder application comprising a plurality of site builder wizards configured to receive and process site content data; (c) acquiring the web page templates from the template library and rendering them to a user via a first site builder wizard; (d) rendering to the user a web page design choices via a second site builder wizard; providing a third site builder wizard to a user for selecting a web page structure; presenting a user with a wizard for filling in a web page text and graphics; generating a preview of the web page and rendering it to the user; (e) sending the web page to a specialist for a usability assessment; and (f) publishing the web page upon completion of the usability assessment, wherein: the templates are generated based on keywords and weight coefficients of the keywords, and each set of the keywords provides a basic web page color scheme using a color scheme shift vector; and wherein the shift vector adjusts the web page color scheme on an element by element basis and adjusts a positioning of the elements on the web page based on the keywords and the weight coefficients.

1. A computer-implemented method for automated generation of web sites, the method comprising: (a) generating a plurality of web page templates and storing them in a template library on a content server; (b) establishing a network connection between the content server and a client; launching a site builder application on a client, the site builder application comprising a plurality of site builder wizards configured to receive and process site content data; (c) acquiring the web page templates from the template library and rendering them to a user via a first site builder wizard; (d) rendering to the user a web page design choices via a second site builder wizard; providing a third site builder wizard to a user for selecting a web page structure; presenting a user with a wizard for filling in a web page text and graphics; generating a preview of the web page and rendering it to the user; (e) sending the web page to a specialist for a usability assessment; and (f) publishing the web page upon completion of the usability assessment, wherein: the templates are generated based on keywords and weight coefficients of the keywords, and each set of the keywords provides a basic web page color scheme using a color scheme shift vector; and wherein the shift vector adjusts the web page color scheme on an element by element basis and adjusts a positioning of the elements on the web page based on the keywords and the weight coefficients. 9. The method of claim 1 , wherein the user is given a choice of languages for the web page.

1. A method for document analysis, comprising the steps of: designating a subset of relevant documents from a document collection; using a greedy algorithm to establish a query coverage set of words or terms, wherein at each stage thereof a single word or term from the subset of relevant documents is included in the query coverage set, wherein the single word or term minimizes a distance measurement between the document collection and the query coverage set, wherein the distance measurement is determined by constructing a difficulty model for a topic by computing a plurality of distances comprising a first distance between the query coverage set and the document collection (d(Q,C)), a second distance among the query coverage set (d(Q,Q)); a third distance between the subset of relevant documents and the document collection (d(R,C)), a fourth distance among the subset of relevant documents (d(R,R)), and a fifth distance between the query coverage set and the subset of relevant documents (d(Q,R)); storing the query coverage set in a database; constructing a set of queries from the query coverage set, each of the queries having a number of terms; executing the queries in a search engine to generate respective results; responsively to the respective results determining an average precision for each of the queries by considering the subset of relevant documents as representing the document collection; categorizing the queries by analyzing the average precision against the number of terms thereof; and reporting respective abilities of the categorized queries to find information in the subset of relevant documents.

1. A method for document analysis, comprising the steps of: designating a subset of relevant documents from a document collection; using a greedy algorithm to establish a query coverage set of words or terms, wherein at each stage thereof a single word or term from the subset of relevant documents is included in the query coverage set, wherein the single word or term minimizes a distance measurement between the document collection and the query coverage set, wherein the distance measurement is determined by constructing a difficulty model for a topic by computing a plurality of distances comprising a first distance between the query coverage set and the document collection (d(Q,C)), a second distance among the query coverage set (d(Q,Q)); a third distance between the subset of relevant documents and the document collection (d(R,C)), a fourth distance among the subset of relevant documents (d(R,R)), and a fifth distance between the query coverage set and the subset of relevant documents (d(Q,R)); storing the query coverage set in a database; constructing a set of queries from the query coverage set, each of the queries having a number of terms; executing the queries in a search engine to generate respective results; responsively to the respective results determining an average precision for each of the queries by considering the subset of relevant documents as representing the document collection; categorizing the queries by analyzing the average precision against the number of terms thereof; and reporting respective abilities of the categorized queries to find information in the subset of relevant documents. 7. A method as claimed in claim 1 , including simulating changes to text of the document collection to improve an ability to find the subset of relevant documents.

13. A method comprising: parsing inputs received from a plurality of sources into surface semantics represented in a semantic representation by utilizing a language model, each of the plurality of sources corresponding to a different modality; providing environmental data associated with at least one of the inputs, the data comprising one or both of current data or historical data; adapting the language model to enhance accuracy of the parsing by utilizing the environmental data to compute at least one environmentally-specific conditional probability of at least one phrase of the inputs received from the plurality of sources; utilizing the semantic representation to generate discourse semantics; utilizing the discourse semantics to synthesize one or more responses to the inputs received from the plurality of sources; further comprising: generating, as a function of the environmental data, a confidence level for an intent associated with the inputs received from the plurality of sources; evaluating a first input of the inputs, the first input having a first modality initially employed as a primary modality; based on the generated confidence level, providing feedback to request a second input of the inputs having a second modality different from the first modality, and substituting the second modality for the first modality as the primary modality until the environmental data changes.

13. A method comprising: parsing inputs received from a plurality of sources into surface semantics represented in a semantic representation by utilizing a language model, each of the plurality of sources corresponding to a different modality; providing environmental data associated with at least one of the inputs, the data comprising one or both of current data or historical data; adapting the language model to enhance accuracy of the parsing by utilizing the environmental data to compute at least one environmentally-specific conditional probability of at least one phrase of the inputs received from the plurality of sources; utilizing the semantic representation to generate discourse semantics; utilizing the discourse semantics to synthesize one or more responses to the inputs received from the plurality of sources; further comprising: generating, as a function of the environmental data, a confidence level for an intent associated with the inputs received from the plurality of sources; evaluating a first input of the inputs, the first input having a first modality initially employed as a primary modality; based on the generated confidence level, providing feedback to request a second input of the inputs having a second modality different from the first modality, and substituting the second modality for the first modality as the primary modality until the environmental data changes. 19. A computer-readable storage medium having stored thereon computer executable components for carrying out the method of claim 13 .

13. The method of claim 1 , further comprising: receiving a query including one or more query terms that describes an audience that a consumer is attempting to target; searching the database for matching user lists based on the query terms; and presenting matching user lists responsive to the query.

13. The method of claim 1 , further comprising: receiving a query including one or more query terms that describes an audience that a consumer is attempting to target; searching the database for matching user lists based on the query terms; and presenting matching user lists responsive to the query. 19. The method of claim 13 , wherein the received query includes use data describing an intended use of data in a candidate user list and the method includes providing user lists that include subscription restrictions that match and allow the use.

1. A method comprising: under control of one or more processors configured with executable instructions, receiving crawled web pages corresponding to a plurality of uniform resource locators (URLs) provided to a web crawler; sorting the crawled web pages into a plurality of labeled groups based at least in part on user behavior information reflecting behavior of users with respect to at least some of the crawled web pages; and establishing one or more hierarchical relationships between the plurality of labeled groups based at least in part on a determined relative priority of each labeled group for inclusion in an index, the one or more hierarchical relationships between the plurality of labeled groups including at least one hierarchical relationship between a first labeled group of the plurality of labeled groups and a second labeled group of the plurality of labeled groups.

1. A method comprising: under control of one or more processors configured with executable instructions, receiving crawled web pages corresponding to a plurality of uniform resource locators (URLs) provided to a web crawler; sorting the crawled web pages into a plurality of labeled groups based at least in part on user behavior information reflecting behavior of users with respect to at least some of the crawled web pages; and establishing one or more hierarchical relationships between the plurality of labeled groups based at least in part on a determined relative priority of each labeled group for inclusion in an index, the one or more hierarchical relationships between the plurality of labeled groups including at least one hierarchical relationship between a first labeled group of the plurality of labeled groups and a second labeled group of the plurality of labeled groups. 2. The method according to claim 1 , further comprising representing the one or more hierarchical relationships between the plurality of labeled groups in a directed graph in which the plurality of labeled groups are vertices of the directed graph and edges of the directed graph indicate a higher or lower level of the determined relative priority between connected vertices.

1. A method of optimizing MOSFET device production comprising: defining, using a computer, key independent parameters; formulating key independent parameters into a canonical variational form, wherein the canonical variational form comprises a key independent parameter extracted at nominal, or target, device specifications plus a product of magnitude of a variation of the key independent parameter, relative to a skew of a distribution on device characteristics, and a selected distribution; calculating theoretical extracted parameters using at least one of key independent parameters in canonical variational form, physics-based analytical models, and corner models; calculating simulated characteristics of a device using at least one of key independent parameters in canonical form or theoretical extracted parameters using a variational model; extracting target data parameters based on at least one of measured data and predicted data; comparing the simulated characteristics to the target data parameters; modifying the theoretical extracted parameters based on the comparison to the target data parameters; modifying the key independent parameters in canonical form based on the modified theoretical extracted parameters; calculating and outputting the simulated characteristics based on the modified theoretical extracted parameters and the modified key independent parameters in canonical form; and modifying the key independent parameters in the device production using the simulated characteristics.

1. A method of optimizing MOSFET device production comprising: defining, using a computer, key independent parameters; formulating key independent parameters into a canonical variational form, wherein the canonical variational form comprises a key independent parameter extracted at nominal, or target, device specifications plus a product of magnitude of a variation of the key independent parameter, relative to a skew of a distribution on device characteristics, and a selected distribution; calculating theoretical extracted parameters using at least one of key independent parameters in canonical variational form, physics-based analytical models, and corner models; calculating simulated characteristics of a device using at least one of key independent parameters in canonical form or theoretical extracted parameters using a variational model; extracting target data parameters based on at least one of measured data and predicted data; comparing the simulated characteristics to the target data parameters; modifying the theoretical extracted parameters based on the comparison to the target data parameters; modifying the key independent parameters in canonical form based on the modified theoretical extracted parameters; calculating and outputting the simulated characteristics based on the modified theoretical extracted parameters and the modified key independent parameters in canonical form; and modifying the key independent parameters in the device production using the simulated characteristics. 4. The method of claim 1 , wherein the method of extracting the theoretical statistical parameters based on the target data parameters comprises at least one of: identifying and measuring data parameters and distribution of data parameters in process control monitoring; extracting statistical model parameters from measured data parameters; and determining a distribution of model parameters from the measured data parameters and the distribution of the measured data parameters.

1. A method for creating and editing an electronic document and for converting a number in a computer system comprising a memory storage and a processing unit, the method comprising: receiving by the computer system a portion of the electronic document as a string of text; analyzing the string of text to determine whether the string of text includes a number expressed using digit shapes by identifying the number expressed using digit shapes regardless of a language in which the digit shapes are expressed; in response to determining that the string of text includes the number expressed as digit shapes, semantically labeling by the computer system the number with schema information by associating the string of text with an inline eXtensible Markup Language (XML) tag belonging to at least one semantic category, indicating that the number is convertible and the semantic categories are being stored in the electronic document; displaying, in a user interface on a display device, the string of text and an indication that the number has been semantically labeled; receiving by the computer system a selection of the indication in the user interface; in response to receiving the selection of the indication, providing by the computer system a dropdown menu in the user interface on the display device displaying a list of actions for converting the number expressed as digit shapes in the semantically labeled string of text, the list of actions being identified upon the schema information; receiving by the computer system a selection of an action from the list of actions in the dropdown menu; in response to receiving the selection of an action, generating by the computer system a converted number by converting the number expressed using digit shapes to the same number expressed as text; and replacing the number in the electronic document with the converted number in the string of text.

1. A method for creating and editing an electronic document and for converting a number in a computer system comprising a memory storage and a processing unit, the method comprising: receiving by the computer system a portion of the electronic document as a string of text; analyzing the string of text to determine whether the string of text includes a number expressed using digit shapes by identifying the number expressed using digit shapes regardless of a language in which the digit shapes are expressed; in response to determining that the string of text includes the number expressed as digit shapes, semantically labeling by the computer system the number with schema information by associating the string of text with an inline eXtensible Markup Language (XML) tag belonging to at least one semantic category, indicating that the number is convertible and the semantic categories are being stored in the electronic document; displaying, in a user interface on a display device, the string of text and an indication that the number has been semantically labeled; receiving by the computer system a selection of the indication in the user interface; in response to receiving the selection of the indication, providing by the computer system a dropdown menu in the user interface on the display device displaying a list of actions for converting the number expressed as digit shapes in the semantically labeled string of text, the list of actions being identified upon the schema information; receiving by the computer system a selection of an action from the list of actions in the dropdown menu; in response to receiving the selection of an action, generating by the computer system a converted number by converting the number expressed using digit shapes to the same number expressed as text; and replacing the number in the electronic document with the converted number in the string of text. 2. The method of claim 1 , further comprising: determining a current user interface language setting for an application program associated with the electronic document; and generating at least one menu item of the dropdown menu in a language specified by the current user interface language setting.

14. The method of claim 11 , wherein the plurality of non-coherent integrations comprises a plurality of log likelihood ratios for the plurality of first hypotheses, wherein a log likelihood ratio for a first hypothesis comprises the natural logarithm of a ratio of a probability of a non-coherent integration conditioned on a presence of the satellite signal to a probability of the non-coherent integration conditioned on an absence of the satellite signal.

14. The method of claim 11 , wherein the plurality of non-coherent integrations comprises a plurality of log likelihood ratios for the plurality of first hypotheses, wherein a log likelihood ratio for a first hypothesis comprises the natural logarithm of a ratio of a probability of a non-coherent integration conditioned on a presence of the satellite signal to a probability of the non-coherent integration conditioned on an absence of the satellite signal. 16. The method of claim 14 , wherein the plurality of extended non-coherent integrations comprises a plurality of log likelihood ratios for the plurality of second hypotheses, wherein a log likelihood ratio for a second hypothesis comprises the natural logarithm of a ratio of a probability of an extended non-coherent integration conditioned on a presence of the satellite signal to a probability of the extended non-coherent integration conditioned on an absence of the satellite signal.