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1. A computer-implemented method of assisting a user in selecting items from an electronic catalog of video items, the method comprising: (a) obtaining access to metric values derived from a knowledge base of predetermined mediasets associated with the electronic catalog; wherein the metric values reflect a level of association for selected pairs of video items within the knowledge base of mediasets, and wherein the metric values are not affected by any metadata descriptive of the said video items' content, but rather reflect a relative frequency with which the video items in the pair are associated together by various users; (b) receiving an initial selection of at least one video item to define an initial input video set; (c) generating an output video item navigation list responsive to at least one item of the input video set, based on the metric values derived from the knowledge base; and (d) communicating the generated navigation list to a user. | 1. A computer-implemented method of assisting a user in selecting items from an electronic catalog of video items, the method comprising: (a) obtaining access to metric values derived from a knowledge base of predetermined mediasets associated with the electronic catalog; wherein the metric values reflect a level of association for selected pairs of video items within the knowledge base of mediasets, and wherein the metric values are not affected by any metadata descriptive of the said video items' content, but rather reflect a relative frequency with which the video items in the pair are associated together by various users; (b) receiving an initial selection of at least one video item to define an initial input video set; (c) generating an output video item navigation list responsive to at least one item of the input video set, based on the metric values derived from the knowledge base; and (d) communicating the generated navigation list to a user. 10. The method according to claim 1 wherein the user comprises a remote software process rather than a person. | 0.610348 |
17. The system according to claim 15 wherein said cryptographic engine is configured for performing elliptic cryptography and further configured such that said cryptographic operation utilizes elliptic curve cryptography and said second intermediate value is a first point on an elliptic curve computed by combining a random number with a second point on an elliptic curve derived from said first intermediate value. | 17. The system according to claim 15 wherein said cryptographic engine is configured for performing elliptic cryptography and further configured such that said cryptographic operation utilizes elliptic curve cryptography and said second intermediate value is a first point on an elliptic curve computed by combining a random number with a second point on an elliptic curve derived from said first intermediate value. 18. The system according to claim 17 wherein said second point is derived from converting said first intermediate value into a coordinate of said second point and deriving said second point from said coordinate. | 0.861835 |
1. A method for operating a virtual assistant on an electronic device, the method comprising: receiving, at the electronic device, an audio input; monitoring the audio input to identify a first spoken user input; identifying the first spoken user input in the audio input; determining whether to respond to the first spoken user input based on contextual information associated with the first spoken user input, wherein the contextual information comprises a determined distance between a user and the electronic device when the first spoken user input was received, the determined distance being based on the first spoken user input, wherein determining whether to respond to the first spoken user input comprises calculating a likelihood score that the virtual assistant should respond to the first spoken user input based on the contextual information associated with the first spoken user input, comparing the likelihood score to a threshold value, decreasing the likelihood score in response to the distance being greater than a threshold distance, and increasing the likelihood score in response to the distance being less than the threshold distance; in response to a determination to respond to the first spoken user input: generating a response to the first spoken user input; and monitoring the audio input to identify a second spoken user input; and in response to a determination not to respond to the first spoken user input, monitoring the audio input to identify the second spoken user input without generating the response to the first spoken user input. | 1. A method for operating a virtual assistant on an electronic device, the method comprising: receiving, at the electronic device, an audio input; monitoring the audio input to identify a first spoken user input; identifying the first spoken user input in the audio input; determining whether to respond to the first spoken user input based on contextual information associated with the first spoken user input, wherein the contextual information comprises a determined distance between a user and the electronic device when the first spoken user input was received, the determined distance being based on the first spoken user input, wherein determining whether to respond to the first spoken user input comprises calculating a likelihood score that the virtual assistant should respond to the first spoken user input based on the contextual information associated with the first spoken user input, comparing the likelihood score to a threshold value, decreasing the likelihood score in response to the distance being greater than a threshold distance, and increasing the likelihood score in response to the distance being less than the threshold distance; in response to a determination to respond to the first spoken user input: generating a response to the first spoken user input; and monitoring the audio input to identify a second spoken user input; and in response to a determination not to respond to the first spoken user input, monitoring the audio input to identify the second spoken user input without generating the response to the first spoken user input. 3. The method of claim 1 , wherein generating the response to the first spoken user input comprises one or more of: performing speech-to-text conversion on the first spoken user input; determining a user intent sed on the first spoken user input; determining a task to be performed based on the first spoken user input; determining a parameter for the task to be performed based on the first spoken user input; performing the task to be performed; displaying a text response to the first spoken user input; and outputting an audio response to the first spoken user input. | 0.5 |
2. The method of claim 1 , wherein determining that the term is a vague term comprises: identifying multiple entities that are associated with the vague term in a database. | 2. The method of claim 1 , wherein determining that the term is a vague term comprises: identifying multiple entities that are associated with the vague term in a database. 3. The method of claim 2 , wherein using the user-restricted content associated with the first additional user to determine the additional information that is related to the vague term comprises: selecting a subset of the multiple entities based on the user-restricted content; and determining the additional information based on the selected subset. | 0.899829 |
1. A speech processing apparatus comprising: a speech receiving unit that receives input speech; a speech processing unit that performs a speech recognizing process on the input speech to obtain a recognition candidate; an analyzing unit that performs a morphological analysis of the recognition candidate; a generating unit that: divides, via a processor of the apparatus, the recognition candidate into a plurality of first segments each including at least one morpheme, and generates a plurality of partial character string candidates, each consisting of a subset of the first segments, the subset being obtained by removing one or more of the first segments from the recognition candidate, the subset for each partial character string candidate being different from the other subsets; a first output unit that outputs the partial character string candidates to a display unit; and a selection receiving unit that receives a selection of a partial character string selected from the partial character string candidates. | 1. A speech processing apparatus comprising: a speech receiving unit that receives input speech; a speech processing unit that performs a speech recognizing process on the input speech to obtain a recognition candidate; an analyzing unit that performs a morphological analysis of the recognition candidate; a generating unit that: divides, via a processor of the apparatus, the recognition candidate into a plurality of first segments each including at least one morpheme, and generates a plurality of partial character string candidates, each consisting of a subset of the first segments, the subset being obtained by removing one or more of the first segments from the recognition candidate, the subset for each partial character string candidate being different from the other subsets; a first output unit that outputs the partial character string candidates to a display unit; and a selection receiving unit that receives a selection of a partial character string selected from the partial character string candidates. 2. The apparatus according to claim 1 , wherein the speech receiving unit receives the input speech in a first language, and wherein the apparatus further comprises: a translating unit that translates the received partial character string selection into a second language to obtain a translation result; and a second output unit that outputs the translation result. | 0.565156 |
15. A system comprising: a processor; memory; the processor being connected for accessing the memory; and string data stored by the memory; the string data comprising two or more data units, each of which can be accessed by the processor; the data units including, for each of a set of two or more acceptable strings of characters, a respective sequence of data units that the processor can access using character data indicating the string's characters; the set of acceptable strings including a first string that is in a first subset of categories, each category in the first subset being one of a set of two or more categories; the first string's sequence of data units including a respective ending subsequence of data units that the processor can access at the end of the first string's sequence and use to obtain first string ending data indicating that the first string is one of the acceptable strings and indicating the first subset of categories; the first string's ending subsequence including: acceptance information indicating that a string at the end of whose respective sequence the processor can access the ending subsequence is one of the set of acceptable strings; and category set information indicating the first subset of categories; the first subset of categories including at least one of the set of categories. | 15. A system comprising: a processor; memory; the processor being connected for accessing the memory; and string data stored by the memory; the string data comprising two or more data units, each of which can be accessed by the processor; the data units including, for each of a set of two or more acceptable strings of characters, a respective sequence of data units that the processor can access using character data indicating the string's characters; the set of acceptable strings including a first string that is in a first subset of categories, each category in the first subset being one of a set of two or more categories; the first string's sequence of data units including a respective ending subsequence of data units that the processor can access at the end of the first string's sequence and use to obtain first string ending data indicating that the first string is one of the acceptable strings and indicating the first subset of categories; the first string's ending subsequence including: acceptance information indicating that a string at the end of whose respective sequence the processor can access the ending subsequence is one of the set of acceptable strings; and category set information indicating the first subset of categories; the first subset of categories including at least one of the set of categories. 20. The system of claim 15 in which the set of categories includes a category for words and a category for roman numerals. | 0.693275 |
11. The computer program product as recited in claim 10 , wherein the at least one attribute of the set of attributes is a subsystem attribute. | 11. The computer program product as recited in claim 10 , wherein the at least one attribute of the set of attributes is a subsystem attribute. 12. The computer program product as recited in claim 11 , further comprising instructions for defining a search scope for assembling the set of system objects. | 0.956212 |
16. An information associating apparatus characterized in comprising: a memory unit which stores an association degree dictionary storing the association degree between key words included in queries used for searching during a past predetermined time interval, an initialization unit which generates initial groups for grouping key words stored in said association degree dictionary according to the association degree, and a grouping unit which groups associated key words by sequentially making groups satisfying predetermined conditions into one group by using said initial groups and the association degree between key words stored in said association degree dictionary. | 16. An information associating apparatus characterized in comprising: a memory unit which stores an association degree dictionary storing the association degree between key words included in queries used for searching during a past predetermined time interval, an initialization unit which generates initial groups for grouping key words stored in said association degree dictionary according to the association degree, and a grouping unit which groups associated key words by sequentially making groups satisfying predetermined conditions into one group by using said initial groups and the association degree between key words stored in said association degree dictionary. 19. An information associating apparatus according to claim 16 wherein: said association degree dictionary composed of an interval association degree dictionary which stores the degree of interval association found by calculating the association degree between said two queries based on the minimum time interval which is the smallest value among time intervals in which each of said extracted queries for each search user from queries used for searching during a past predetermined time interval, and adding said association degrees calculated for a plurality of each of said search users, and a correlation degree dictionary which stores the degree of correlation of key words found by compiling the queries for each search user in a predetermined time interval from queries used for searching during said past predetermined time interval, calculating for each of said users the number of uses of key words among said queries in each predetermined time interval, calculating the number of uses of each key word for all of said search users, and calculating the coefficient of correlation between two key words based on the number of uses of each key word, and further characterized in said initialization unit generating initial groups for grouping key words according to the interval association degree and the correlation degree stored in said interval association degree dictionary, and said grouping unit grouping associated key words by sequentially making the groups which satisfy predetermined conditions into one group using said initial groups and the interval association degree of key words stored in said interval association degree dictionary and the correlation degree of key words stored in said correlation degree dictionary. | 0.558201 |
10. A system, comprising: a memory; and one or more processing units, communicatively coupled to the memory, wherein the memory stores instructions to configure the one or more processing units to: obtain a first plurality of messages for a first user, wherein the first plurality of messages comprises: one or more messages in each of a first plurality of formats; and one or more messages sent or received via each of a first plurality of protocols; create one or more associations between one or more of the first plurality of messages, wherein the instructions to create one or more associations between one or more of the first plurality of messages comprise instructions to: perform a semantic analysis on the first plurality of messages; and create one or more clusters of messages from the first plurality of messages based, at least in part, on the semantic analysis, wherein a cluster of messages comprises two or more messages that are associated together; receive a query from the first user requesting at least one message from the first plurality of messages; generate one or more index search terms based, at least in part, on the received query; and generate a result set of messages in response to the generated one or more index search terms, wherein the result set is based, at least in part, on one or more index search parameters for one or more of the generated one or more index search terms, and wherein at least one of the one or more index search parameters is determined individually for the first user. | 10. A system, comprising: a memory; and one or more processing units, communicatively coupled to the memory, wherein the memory stores instructions to configure the one or more processing units to: obtain a first plurality of messages for a first user, wherein the first plurality of messages comprises: one or more messages in each of a first plurality of formats; and one or more messages sent or received via each of a first plurality of protocols; create one or more associations between one or more of the first plurality of messages, wherein the instructions to create one or more associations between one or more of the first plurality of messages comprise instructions to: perform a semantic analysis on the first plurality of messages; and create one or more clusters of messages from the first plurality of messages based, at least in part, on the semantic analysis, wherein a cluster of messages comprises two or more messages that are associated together; receive a query from the first user requesting at least one message from the first plurality of messages; generate one or more index search terms based, at least in part, on the received query; and generate a result set of messages in response to the generated one or more index search terms, wherein the result set is based, at least in part, on one or more index search parameters for one or more of the generated one or more index search terms, and wherein at least one of the one or more index search parameters is determined individually for the first user. 16. The system of claim 10 , wherein at least one of the one or more index search parameters is based, at least in part, on historic patterns of communications of the first user. | 0.627473 |
13. A computing system, comprising: nonvolatile memory storing non-transitory executable instructions; and a processor to execute the non-transitory executable instructions to: in response to a query regarding a relationship among keywords, use one or more web search engines to identify highly ranked web pages related to the keywords and highly ranked ontologies related to the keywords; extract semantics that are related to the keywords from the highly ranked web pages; combine the highly ranked ontologies and the extracted semantics to form an integrated ontology; identify relationships that are related to the keywords from the integrated ontology, the identify relationships comprising: from the integrated ontology, add one or more formulas that each includes at least one of the keywords as candidate formulas to a candidate pool, and perform an iterative process, comprising: record any candidate formula that includes all of the keywords as one of the relationships and remove the recorded candidate formula from the candidate pool, for each candidate formula in the candidate pool, determine one or more formulas from the integrated ontology that are relevant to the candidate formula, for each relevant formula, determine an implicit formula implied from the relevant formula and a corresponding candidate formula, and repeat the iterative process; and rank the identified relationships. | 13. A computing system, comprising: nonvolatile memory storing non-transitory executable instructions; and a processor to execute the non-transitory executable instructions to: in response to a query regarding a relationship among keywords, use one or more web search engines to identify highly ranked web pages related to the keywords and highly ranked ontologies related to the keywords; extract semantics that are related to the keywords from the highly ranked web pages; combine the highly ranked ontologies and the extracted semantics to form an integrated ontology; identify relationships that are related to the keywords from the integrated ontology, the identify relationships comprising: from the integrated ontology, add one or more formulas that each includes at least one of the keywords as candidate formulas to a candidate pool, and perform an iterative process, comprising: record any candidate formula that includes all of the keywords as one of the relationships and remove the recorded candidate formula from the candidate pool, for each candidate formula in the candidate pool, determine one or more formulas from the integrated ontology that are relevant to the candidate formula, for each relevant formula, determine an implicit formula implied from the relevant formula and a corresponding candidate formula, and repeat the iterative process; and rank the identified relationships. 14. The computing system of claim 13 , wherein the instructions to rank the identified relationships include instructions executable by the processor to: determine a weight of any formula extracted from a highly ranked web page or originally located in a highly ranked ontology based on an order of the highly ranked web page or the highly ranked ontology provided by the one or more web search engines; determine a weight of any implicit formula that is implied from two or more formulas based on weights of the two or more formulas and a number of iterations that generated the implicit formula; and rank the relationships by weight. | 0.5 |
1. A system, comprising: an account database comprising account data associated with one or more accounts, each of the one or more accounts representing an account receivable; and a processor functionally coupled to the account database, wherein said processor is configured to receive selection criteria, to search said account database for one or more accounts having account data that satisfies at least a portion of said selection criteria, provide a summary of any of said one or more accounts having account data that satisfies at least a portion of said selection criteria, wherein said summary includes a balance of the account but does not personally identify said one or more accounts having account data that satisfies at least a portion of said selection criteria to receive an offer from a buyer for at least one of the said one or more accounts having account data that satisfies at least a portion of said selection criteria; and to accept automatically the offer in response to the offer fulfilling a term of a commitment for the at least one of the said one or more accounts having account data that satisfies at least a portion of said selection criteria, the term of the commitment comprising a fixed price upon which a seller automatically accepts the offer. | 1. A system, comprising: an account database comprising account data associated with one or more accounts, each of the one or more accounts representing an account receivable; and a processor functionally coupled to the account database, wherein said processor is configured to receive selection criteria, to search said account database for one or more accounts having account data that satisfies at least a portion of said selection criteria, provide a summary of any of said one or more accounts having account data that satisfies at least a portion of said selection criteria, wherein said summary includes a balance of the account but does not personally identify said one or more accounts having account data that satisfies at least a portion of said selection criteria to receive an offer from a buyer for at least one of the said one or more accounts having account data that satisfies at least a portion of said selection criteria; and to accept automatically the offer in response to the offer fulfilling a term of a commitment for the at least one of the said one or more accounts having account data that satisfies at least a portion of said selection criteria, the term of the commitment comprising a fixed price upon which a seller automatically accepts the offer. 4. The system of claim 1 , wherein the account data is not personally-identifiable account data. | 0.573097 |
1. A computer implemented method for object tracking, comprising accessing a video feed that captures an object in at least a portion of the video feed; co-training separate appearance models with the video feed, the models comprise a generative model to capture appearance variations of the object in the video feed and a discriminative model to discriminate the object from the object's background as captured by the video feed; using a sliding window to process data from the video feed; advancing the sliding window to focus the discriminative model on recent appearance variations of the object in the video feed; generating object information corresponding to the object based a Bayesian framework that combines likelihood function outputs corresponding to the generative model and the discriminative model; updating the generative model and the discriminative model using the object information; and tracking the object based on the object information. | 1. A computer implemented method for object tracking, comprising accessing a video feed that captures an object in at least a portion of the video feed; co-training separate appearance models with the video feed, the models comprise a generative model to capture appearance variations of the object in the video feed and a discriminative model to discriminate the object from the object's background as captured by the video feed; using a sliding window to process data from the video feed; advancing the sliding window to focus the discriminative model on recent appearance variations of the object in the video feed; generating object information corresponding to the object based a Bayesian framework that combines likelihood function outputs corresponding to the generative model and the discriminative model; updating the generative model and the discriminative model using the object information; and tracking the object based on the object information. 2. The method of claim 1 , wherein the object information comprises position, size, and rotation information. | 0.703824 |
12. The method of claim 8 , wherein text cohesion is determined based upon factors from the group consisting of referential cohesion, causal cohesion, connective non-causal cohesion, and thematic continuity. | 12. The method of claim 8 , wherein text cohesion is determined based upon factors from the group consisting of referential cohesion, causal cohesion, connective non-causal cohesion, and thematic continuity. 16. The method of claim 12 , wherein referential cohesion measures are computed selectively (a) with lexical overlap calculated with and without stemming, and (b) considering noun overlap in up to three previous sentences. | 0.932342 |
15. An image learning device comprising: an image segmentation module that performs a segmentation operation on a first image having annotations to segment the first image into one or more image regions; a feature vector extraction module that extracts image feature vectors and text feature vectors from all the image regions to obtain an image feature matrix and a text feature matrix; a sub-space projection module that projects the image feature matrix and the text feature matrix into a sub-space so as to maximize covariance between an image feature and a text feature, thereby obtaining the projected image feature matrix and the text feature matrix; a storage device, and a storage module that stores the projected image feature matrix and the text feature matrix; and a processor, and a graph building module that establishes first links between the image regions based on the projected image feature matrix; establishes second links between the first image and the image regions based on a result of the segmentation operation; establishes third links between the first image and the annotations based on the first image having the annotations; establishes fourth links between the annotations based on the projected text feature matrix; calculates weights of all the links; and obtains a graph showing a triangular relationship between the first image, the image regions, and the annotations based on all the links and the weights of the links corresponding to the links. | 15. An image learning device comprising: an image segmentation module that performs a segmentation operation on a first image having annotations to segment the first image into one or more image regions; a feature vector extraction module that extracts image feature vectors and text feature vectors from all the image regions to obtain an image feature matrix and a text feature matrix; a sub-space projection module that projects the image feature matrix and the text feature matrix into a sub-space so as to maximize covariance between an image feature and a text feature, thereby obtaining the projected image feature matrix and the text feature matrix; a storage device, and a storage module that stores the projected image feature matrix and the text feature matrix; and a processor, and a graph building module that establishes first links between the image regions based on the projected image feature matrix; establishes second links between the first image and the image regions based on a result of the segmentation operation; establishes third links between the first image and the annotations based on the first image having the annotations; establishes fourth links between the annotations based on the projected text feature matrix; calculates weights of all the links; and obtains a graph showing a triangular relationship between the first image, the image regions, and the annotations based on all the links and the weights of the links corresponding to the links. 16. An image automatic annotation device for making an annotation on an input second image, the image automatic annotation device comprising the image learning device according to claim 15 , a preliminary processing module, a graph update module, and an annotation module, wherein the preliminary processing module includes: a unit that receives the second image; a unit that performs the segmentation operation on the second image to segment the second image into one or more image regions; a unit that extracts image feature vectors from all the image regions to obtain an image feature matrix of the second image; and a unit that projects the image feature matrix of the second image into the sub-space to obtain a projected image feature matrix of the second image, the graph update module includes: a unit that establishes fifth links between the image region nodes of the second image and the image region nodes in the graph based on the projected first image feature matrix and the second image feature matrix and establishes sixth links between the second image and the image region nodes based on a result of the segmentation operation; a unit that determines weights of the links of the fifth links and the sixth links; and a unit that updates the graph based on the fifth links and the sixth links and the weights of the links corresponding to the fifth links and the sixth links, and the annotation module includes: a unit that generates a restart vector corresponding to the second image and acquires a predetermined number of annotations most closely related to the second image with a random walk with restart; and a unit that makes the annotations on the second image using keywords corresponding to the predetermined number of annotations. | 0.503472 |
31. A method of teaching a language written in kanji characters, comprising the steps of: presenting a compilation of approximately 180-240 key kanji in a systematic order; providing phonetic readings of the key kanji in Roman characters, hiragana and katakana; reinforcing the phonetic readings of the key kanji with a compilation of common homophones of the key kanji; increasing the recognition of said key kanji by presenting radicals associated with the key kanji and the names of the key kanji; providing the meanings of the key kanji; and presenting a writing in kanji in combination with at least one of the phonetic reading; the English translation; or JIS Code information. | 31. A method of teaching a language written in kanji characters, comprising the steps of: presenting a compilation of approximately 180-240 key kanji in a systematic order; providing phonetic readings of the key kanji in Roman characters, hiragana and katakana; reinforcing the phonetic readings of the key kanji with a compilation of common homophones of the key kanji; increasing the recognition of said key kanji by presenting radicals associated with the key kanji and the names of the key kanji; providing the meanings of the key kanji; and presenting a writing in kanji in combination with at least one of the phonetic reading; the English translation; or JIS Code information. 34. The method of claim 31 which further comprises presenting the names of the radicals and further increasing the number of kanji learned by providing at least an on-yomi reading for a portion of the radicals that double as kanji. | 0.5 |
13. A non-transitory computer readable medium with computer readable instructions for circuit design, comprising: computer instructions creating a functional coverage model; computer instructions running random simulations from at least one seed; computer instructions merging coverage logs of the functional coverage model generated by verification of a hardware description language circuit design, as the coverage logs are generated, without waiting for all pending coverage logs; and computer instructions analyzing the merged coverage logs, refining the functional coverage model, and deleting at least part of previous coverage logs, responsive to said merging. | 13. A non-transitory computer readable medium with computer readable instructions for circuit design, comprising: computer instructions creating a functional coverage model; computer instructions running random simulations from at least one seed; computer instructions merging coverage logs of the functional coverage model generated by verification of a hardware description language circuit design, as the coverage logs are generated, without waiting for all pending coverage logs; and computer instructions analyzing the merged coverage logs, refining the functional coverage model, and deleting at least part of previous coverage logs, responsive to said merging. 15. The computer readable medium of claim 13 , further comprising: computer instructions generating a coverage report, responsive to said merging and to a predetermined condition being met. | 0.675772 |
21. The apparatus of claim 20 , wherein said codebook stores, for the plural predetermined speech parameter vectors, respective codes representing the respective speech parameter vectors, and said means for obtaining a speech parameter vector is configured to quantize each set of speech parameters obtained from respective one of the plurality of the frames in the portion of the input speech by using said codebook to obtain the code. | 21. The apparatus of claim 20 , wherein said codebook stores, for the plural predetermined speech parameter vectors, respective codes representing the respective speech parameter vectors, and said means for obtaining a speech parameter vector is configured to quantize each set of speech parameters obtained from respective one of the plurality of the frames in the portion of the input speech by using said codebook to obtain the code. 26. The apparatus of claim 21 , further comprising: an unvoiced portion deciding part that decides whether each frame of said input speech is an unvoiced portion; a voiced portion deciding part that decides whether each frame of said input speech is a voiced portion; a speech sub-block deciding part that decides that every portion preceded and succeeded by more than a predetermined number of unvoiced portions and including a voiced portion is a speech sub-block; a speech block deciding part that decides that when an average power of said voiced portion included in the last speech sub-block in said sequence of speech sub-blocks is smaller than a product of the average power of said speech sub-block and a constant, the sequence of the speech sub-blocks is a speech block; and a summarized portion output part that decides that a speech block including a speech sub-block which is decided as emphasized by said emphasized state deciding part is a portion of summarized speech, and that outputs said speech block as the portion of summarized speech. | 0.85031 |
8. A computer-readable storage medium storing instructions which, when executed by a processor, perform a ranking method, the method comprising: performing a search on a database according to search criteria; receiving, from the database over a network, a document resulting from the search, the document containing terms that match the search criteria; calculating a standard deviation of a probability distribution function representing a distribution of the terms in the document that match the search criteria; determining relative distances between the terms in the document that match the search criteria according to the standard deviation; calculating a proximity boost value using the relative distances; applying the proximity boost value to a base relevancy score of the document to determine a relevancy ranking for the document; and ranking the document according to the relevancy ranking. | 8. A computer-readable storage medium storing instructions which, when executed by a processor, perform a ranking method, the method comprising: performing a search on a database according to search criteria; receiving, from the database over a network, a document resulting from the search, the document containing terms that match the search criteria; calculating a standard deviation of a probability distribution function representing a distribution of the terms in the document that match the search criteria; determining relative distances between the terms in the document that match the search criteria according to the standard deviation; calculating a proximity boost value using the relative distances; applying the proximity boost value to a base relevancy score of the document to determine a relevancy ranking for the document; and ranking the document according to the relevancy ranking. 9. The computer-readable storage medium of claim 8 , further comprising determining a lead boost value by calculating an influence estimate according to an influence function; and applying the influence estimate to the base relevancy score of the document. | 0.615894 |
16. A machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform a method comprising: receiving a query from a client machine; retrieving a data set based on the query; the data set including a plurality of data units; a data unit of the plurality of data units being representative of an item, the data unit includes a value of an attribute of the item represented by the data unit; performing a first operation that organizes the data set into a first plurality of clusters; performing a second operation that partitions the first plurality of clusters into a second plurality of clusters and a third plurality of clusters, the second plurality of clusters being characterized by an attribute common to each cluster of the second plurality of clusters, a cluster of the second plurality of clusters includes the data unit; the attribute common to each cluster of the second plurality of clusters is the attribute of the item, the third plurality clusters being characterized by absence of the attribute from each cluster of the third plurality clusters; and storing the second plurality of clusters in a database. | 16. A machine-readable storage medium comprising instructions that, when executed by one or more processors of a machine, cause the machine to perform a method comprising: receiving a query from a client machine; retrieving a data set based on the query; the data set including a plurality of data units; a data unit of the plurality of data units being representative of an item, the data unit includes a value of an attribute of the item represented by the data unit; performing a first operation that organizes the data set into a first plurality of clusters; performing a second operation that partitions the first plurality of clusters into a second plurality of clusters and a third plurality of clusters, the second plurality of clusters being characterized by an attribute common to each cluster of the second plurality of clusters, a cluster of the second plurality of clusters includes the data unit; the attribute common to each cluster of the second plurality of clusters is the attribute of the item, the third plurality clusters being characterized by absence of the attribute from each cluster of the third plurality clusters; and storing the second plurality of clusters in a database. 17. The machine-readable storage medium of claim 16 , wherein: the first plurality of clusters includes a first cluster; the second operation divides the first cluster into first and second portions and determines that the first portion is to be included in the second plurality of clusters; and the second portion is absent from the second plurality of clusters. | 0.539172 |
9. The apparatus of claim 1 , wherein the combinatorial logic is configured to indicate a load-store collision if the load and store word masks indicate a word overlap within the cache line and otherwise to indicate no load-store collision. | 9. The apparatus of claim 1 , wherein the combinatorial logic is configured to indicate a load-store collision if the load and store word masks indicate a word overlap within the cache line and otherwise to indicate no load-store collision. 10. The apparatus of claim 9 , wherein the combinatorial logic comprises: shifters, configured to shift the load and store word masks to their respective locations within the cache line prior to using the load and store word masks to detect the load-store collision. | 0.890394 |
9. A ranking system comprising: a memory comprising at least one negation term; a processor comprising: a document ranking application comprising modules executable by the processor to process a plurality of documents retrieved from a data source, the document ranking application comprising: a token generation module to generate a corresponding token for each word in document data included in at least one of the plurality of documents; and a tagging module to: retrieve the at least one negation term from the memory; compare the at least one negation term to other terms included in the document data for the at least one document that are within a selected proximity of each word; assign a negative tag to the corresponding token for a particular word if the at least one negation term matches any other terms within the selected proximity of the particular word; assign a positive tag to the corresponding token for the particular word if the at least one negation term does not match any of the other terms within the selected proximity of the particular word; and store processed document data for the at least one document in a data store, the processed document data comprising document content, tokens, and the tags assigned to each of the tokens; a document data display application comprising modules executable by the processor to display document data retrieved from the data store in response to a search request, the document data display application comprising: a token analysis module to: receive the search request comprising document identification data; identify the processed document data in the data store that corresponds to the document identification data; and search the processed document data for tokens assigned the positive context tag; and a display module generates the processed document data for display with visual indicators for each word where the corresponding token is assigned the positive context tag; and an analytics application comprising modules executable by the processor to analyze the processed document data retrieved from the data store in response to another search request, the analytics application comprising: an analytics module to: receive the other search request comprising at least one of the document identification data and document preparer identification data; identify predictive document data and corresponding result documents data from the processed document data in the data store that correspond to the at least one of the document identification data and the document preparer identification data; identify corresponding tokens in the predictive document data and the corresponding result document data that correspond to the same particular word and identify the tags assigned to each of the identified corresponding tokens; assign an accuracy rating to the predictive document data based on the tags assigned to each of the identified corresponding tokens, wherein the accuracy rating has a first value when each of the identified corresponding tokens are both assigned the positive context tag, and wherein the accuracy rating has a second value when one of the identified corresponding tokens is assigned the positive context tag and another one of identified corresponding tokens is assigned the negative context tag; and store the accuracy rating for the particular predictive document in the memory. | 9. A ranking system comprising: a memory comprising at least one negation term; a processor comprising: a document ranking application comprising modules executable by the processor to process a plurality of documents retrieved from a data source, the document ranking application comprising: a token generation module to generate a corresponding token for each word in document data included in at least one of the plurality of documents; and a tagging module to: retrieve the at least one negation term from the memory; compare the at least one negation term to other terms included in the document data for the at least one document that are within a selected proximity of each word; assign a negative tag to the corresponding token for a particular word if the at least one negation term matches any other terms within the selected proximity of the particular word; assign a positive tag to the corresponding token for the particular word if the at least one negation term does not match any of the other terms within the selected proximity of the particular word; and store processed document data for the at least one document in a data store, the processed document data comprising document content, tokens, and the tags assigned to each of the tokens; a document data display application comprising modules executable by the processor to display document data retrieved from the data store in response to a search request, the document data display application comprising: a token analysis module to: receive the search request comprising document identification data; identify the processed document data in the data store that corresponds to the document identification data; and search the processed document data for tokens assigned the positive context tag; and a display module generates the processed document data for display with visual indicators for each word where the corresponding token is assigned the positive context tag; and an analytics application comprising modules executable by the processor to analyze the processed document data retrieved from the data store in response to another search request, the analytics application comprising: an analytics module to: receive the other search request comprising at least one of the document identification data and document preparer identification data; identify predictive document data and corresponding result documents data from the processed document data in the data store that correspond to the at least one of the document identification data and the document preparer identification data; identify corresponding tokens in the predictive document data and the corresponding result document data that correspond to the same particular word and identify the tags assigned to each of the identified corresponding tokens; assign an accuracy rating to the predictive document data based on the tags assigned to each of the identified corresponding tokens, wherein the accuracy rating has a first value when each of the identified corresponding tokens are both assigned the positive context tag, and wherein the accuracy rating has a second value when one of the identified corresponding tokens is assigned the positive context tag and another one of identified corresponding tokens is assigned the negative context tag; and store the accuracy rating for the particular predictive document in the memory. 11. The system claim 9 wherein the selected proximity comprises a first selected number of words immediately preceding the particular word and a second selected number of words immediately following the particular word. | 0.564155 |
13. A display system, comprising: a display, configured to display textual elements; a processor to control the display to display the textual elements; wherein the processor is configurable, to control the display to display the textual elements in a plurality of different languages, the display comprising a plurality of characters within at least one textual element to form a word, to graphically predetermine where the textual elements are to be displayed on the display, and to automatically size the text elements based on the plurality of different languages when graphically predetermining where the textual elements are to be displayed on the display based upon which language translation contains the maximum number of characters for the word. | 13. A display system, comprising: a display, configured to display textual elements; a processor to control the display to display the textual elements; wherein the processor is configurable, to control the display to display the textual elements in a plurality of different languages, the display comprising a plurality of characters within at least one textual element to form a word, to graphically predetermine where the textual elements are to be displayed on the display, and to automatically size the text elements based on the plurality of different languages when graphically predetermining where the textual elements are to be displayed on the display based upon which language translation contains the maximum number of characters for the word. 14. The display system of claim 13 , wherein the processor is configurable to automatically size the textual elements based on a maximum character count of text to be displayed in the textual elements. | 0.565507 |
1. A method of displaying relevance ranked results on a computer used in Internet searching, comprising: generating a set of queries; executing each of the set of queries on an Internet search engine to develop a corresponding result set; selecting a limited number of documents from each corresponding result set; developing a subjective rating for each of the limited number of documents with respect to a subjective criteria, the subjective criteria including a count of clicks for each of the limited number of documents, the count of clicks decaying exponentially over time and including clicks where the query producing each document is unrelated to the generated set of queries; programming a machine learning categorization tool at least in part using the subjective rating of each of the limited number of documents; performing a query that returns a set of documents; generating an absolute relevance score for at least a portion of the set of documents using the machine learning categorization tool; creating a subset of documents from the at least a portion of the set of documents, each document in the subset of documents having its respective absolute relevance score above a threshold value; selecting one or more related refinements based on characteristics of documents in the subset of documents; displaying on the computer the one or more related refinements; and displaying on the computer the subset of documents in an order by highest relevance to the query based on the absolute relevance score of each document of the subset of documents. | 1. A method of displaying relevance ranked results on a computer used in Internet searching, comprising: generating a set of queries; executing each of the set of queries on an Internet search engine to develop a corresponding result set; selecting a limited number of documents from each corresponding result set; developing a subjective rating for each of the limited number of documents with respect to a subjective criteria, the subjective criteria including a count of clicks for each of the limited number of documents, the count of clicks decaying exponentially over time and including clicks where the query producing each document is unrelated to the generated set of queries; programming a machine learning categorization tool at least in part using the subjective rating of each of the limited number of documents; performing a query that returns a set of documents; generating an absolute relevance score for at least a portion of the set of documents using the machine learning categorization tool; creating a subset of documents from the at least a portion of the set of documents, each document in the subset of documents having its respective absolute relevance score above a threshold value; selecting one or more related refinements based on characteristics of documents in the subset of documents; displaying on the computer the one or more related refinements; and displaying on the computer the subset of documents in an order by highest relevance to the query based on the absolute relevance score of each document of the subset of documents. 2. The method of claim 1 , further comprising: computing an inter judge agreement rate based on the subjective rating; and alerting the plurality of judges when the inter judge agreement rate falls below a limit. | 0.579044 |
1. A computer-implemented method, comprising: receiving a query and a current version of a document; receiving quality of result data for a plurality of versions of the document and the query, the quality of result data specifying a respective version-specific quality of result statistic for each of the versions of the document with respect to the query; calculating a weight for the version-specific quality of result statistics corresponding to each version of the document, wherein the weight for a particular version of the document is determined at least in part on an estimate of a difference between the particular version and the current version of the document, and wherein calculating the weight for a particular version of the document comprises: obtaining a representation of the particular version of the document, wherein the representation is a first time distribution of shingles, calculating a difference score by comparing the first time distribution of shingles representing the particular version of the document to a second time distribution of shingles representing the current version of the document, wherein each shingle is a contiguous subsequence of one or more tokens in the document, and wherein each shingle is associated with a particular time that the shingle is first observed in a version of the document such that a distribution of the times associated with the shingles in a version of the document corresponds to the representation of the version of the document, and using the difference score to calculate a corresponding weight for the particular version of the document; determining a weighted overall quality of result statistic for the document with respect to the query, wherein determining the weighted overall quality of result statistic comprises weighting each version-specific quality of result statistic with the calculated weight and combining the weighted version-specific quality of result statistics; and associating the weighted overall quality of result statistic with the document. | 1. A computer-implemented method, comprising: receiving a query and a current version of a document; receiving quality of result data for a plurality of versions of the document and the query, the quality of result data specifying a respective version-specific quality of result statistic for each of the versions of the document with respect to the query; calculating a weight for the version-specific quality of result statistics corresponding to each version of the document, wherein the weight for a particular version of the document is determined at least in part on an estimate of a difference between the particular version and the current version of the document, and wherein calculating the weight for a particular version of the document comprises: obtaining a representation of the particular version of the document, wherein the representation is a first time distribution of shingles, calculating a difference score by comparing the first time distribution of shingles representing the particular version of the document to a second time distribution of shingles representing the current version of the document, wherein each shingle is a contiguous subsequence of one or more tokens in the document, and wherein each shingle is associated with a particular time that the shingle is first observed in a version of the document such that a distribution of the times associated with the shingles in a version of the document corresponds to the representation of the version of the document, and using the difference score to calculate a corresponding weight for the particular version of the document; determining a weighted overall quality of result statistic for the document with respect to the query, wherein determining the weighted overall quality of result statistic comprises weighting each version-specific quality of result statistic with the calculated weight and combining the weighted version-specific quality of result statistics; and associating the weighted overall quality of result statistic with the document. 2. The method of claim 1 , wherein each of the plurality of versions of the document is stored at a same address at a different respective period of time. | 0.630655 |
20. The system of claim 11 , wherein one of said additional elements that describes how drawing is performed comprises an element that describes a geometric region. | 20. The system of claim 11 , wherein one of said additional elements that describes how drawing is performed comprises an element that describes a geometric region. 21. The system of claim 20 , wherein said one element has properties that can be expressed multiple ways. | 0.95452 |
11. A system, comprising: a processor; and a memory containing a content management system (CMS) program configured to detect configuration conflicts between configuration files in the CMS by performing the steps of: storing a configuration set associated with one or more documents managed by the CMS, wherein each document of the one or more documents has a corresponding document type; receiving a content processing rule to be applied to one or more documents, wherein the content processing rule defines an operation to be performed by the CMS whenever a document of a document type specified by the content processing rule is checked-in to or checked-out from the CMS, and wherein the operation to be performed by the CMS includes, at least in part, modifying at least one document attribute in the one or more documents; determining that the at least one document attribute referenced by the content processing rule is a member of a repeating attribute group specified by a document type configuration associated with the document type specified in the content processing rule, wherein the repeating attribute group specifies a plurality of document attributes that should occur with the same number of values in instances of the document type; upon determining that, when applied to a first instance of the document type, the content processing rule could modify the first instance of the document type to include a differing number of values for the plurality of document attributes specified in the repeating attribute group, notifying a system administrator; generating an external schema validation rule configured to ensure that a number of occurrences of the plurality of document attributes in the first instance of the document type matches the number of occurrences of the plurality of document attributes in the modified first instance of the document type; and accepting the received content processing rule, whereby the operation defined by the content processing rule will be performed by the CMS whenever documents of the document type associated with the content processing rule are checked-in to or checked-out of the CMS. | 11. A system, comprising: a processor; and a memory containing a content management system (CMS) program configured to detect configuration conflicts between configuration files in the CMS by performing the steps of: storing a configuration set associated with one or more documents managed by the CMS, wherein each document of the one or more documents has a corresponding document type; receiving a content processing rule to be applied to one or more documents, wherein the content processing rule defines an operation to be performed by the CMS whenever a document of a document type specified by the content processing rule is checked-in to or checked-out from the CMS, and wherein the operation to be performed by the CMS includes, at least in part, modifying at least one document attribute in the one or more documents; determining that the at least one document attribute referenced by the content processing rule is a member of a repeating attribute group specified by a document type configuration associated with the document type specified in the content processing rule, wherein the repeating attribute group specifies a plurality of document attributes that should occur with the same number of values in instances of the document type; upon determining that, when applied to a first instance of the document type, the content processing rule could modify the first instance of the document type to include a differing number of values for the plurality of document attributes specified in the repeating attribute group, notifying a system administrator; generating an external schema validation rule configured to ensure that a number of occurrences of the plurality of document attributes in the first instance of the document type matches the number of occurrences of the plurality of document attributes in the modified first instance of the document type; and accepting the received content processing rule, whereby the operation defined by the content processing rule will be performed by the CMS whenever documents of the document type associated with the content processing rule are checked-in to or checked-out of the CMS. 12. The system of claim 11 , wherein the configuration set includes a collection of XML artifacts, including at least one of an XML schema, document type definition (DTD), XML stylesheet, and XSLT transform. | 0.528552 |
3. A method for indexing documents in a data processing system, said documents including a reference to at least one material, comprising: inputting a document into said data processing system; extracting at least one alphanumeric string from said document; determining relevant alphanumeric strings from said extracted alphanumeric strings by processing said extracted alphanumeric strings utilizing at least one algorithm by comparing, in sequence and in combination, said extracted alphanumeric strings with material terms in at least a dictionary database of common material terms; matching said relevant alphanumeric strings with material alphanumeric strings stored in said data processing system; and storing said matched alphanumeric strings in respective matched records in said data processing system, the method further comprising cross-referencing said matched alphanumeric strings with matching master materials alphanumeric strings in said data processing system. | 3. A method for indexing documents in a data processing system, said documents including a reference to at least one material, comprising: inputting a document into said data processing system; extracting at least one alphanumeric string from said document; determining relevant alphanumeric strings from said extracted alphanumeric strings by processing said extracted alphanumeric strings utilizing at least one algorithm by comparing, in sequence and in combination, said extracted alphanumeric strings with material terms in at least a dictionary database of common material terms; matching said relevant alphanumeric strings with material alphanumeric strings stored in said data processing system; and storing said matched alphanumeric strings in respective matched records in said data processing system, the method further comprising cross-referencing said matched alphanumeric strings with matching master materials alphanumeric strings in said data processing system. 4. The method of claim 3 wherein said document is an updated document and further comprising: comparing said matched alphanumeric strings with said stored documents; and storing changed alphanumeric strings in said data processing system. | 0.5 |
29. The method of claim 28 , wherein determining the at least one keyword comprises selecting at least one keyword based upon the ranking of the graph nodes. | 29. The method of claim 28 , wherein determining the at least one keyword comprises selecting at least one keyword based upon the ranking of the graph nodes. 30. The method of claim 29 , wherein determining the at least one keyword comprises forming at least one multi-word key word from the selected keywords. | 0.954997 |
11. A method of identifying words from a sound block, the method comprising acts of: determining, with a speech recognizer including at least one processor, word scores for words in a word graph by applying a phonemic language model to at least one phoneme of the words in the word graph; deriving a best path through the word graph based, at least in part, on the word scores determined for the words in the word graph; and outputting a speech recognition result including the words in the word graph corresponding to the best path. | 11. A method of identifying words from a sound block, the method comprising acts of: determining, with a speech recognizer including at least one processor, word scores for words in a word graph by applying a phonemic language model to at least one phoneme of the words in the word graph; deriving a best path through the word graph based, at least in part, on the word scores determined for the words in the word graph; and outputting a speech recognition result including the words in the word graph corresponding to the best path. 19. The method according to claim 11 , wherein the phonemic language model is an m-gram language model or a compact variagram. | 0.649231 |
1. A method, comprising: receiving a plurality of semantic structures associated with a text corpus; identifying, by a processing device, a first semantic structure and a second semantic structure, wherein the first semantic structure comprises a first substructure and a second substructure, wherein the second semantic structure comprises a third substructure and a fourth substructure, and wherein the first substructure is similar to the third substructure in view of a first similarity criterion; and responsive to determining that the second substructure is similar to the fourth substructure in view of a second similarity criterion, associating, with a certain concept of an ontology associated with the text corpus, objects represented by the second substructure and the fourth substructure. | 1. A method, comprising: receiving a plurality of semantic structures associated with a text corpus; identifying, by a processing device, a first semantic structure and a second semantic structure, wherein the first semantic structure comprises a first substructure and a second substructure, wherein the second semantic structure comprises a third substructure and a fourth substructure, and wherein the first substructure is similar to the third substructure in view of a first similarity criterion; and responsive to determining that the second substructure is similar to the fourth substructure in view of a second similarity criterion, associating, with a certain concept of an ontology associated with the text corpus, objects represented by the second substructure and the fourth substructure. 2. The method of claim 1 , wherein the ontology comprises one or more concepts, each concept associated with one or more instances of the concept represented by one or more objects. | 0.873259 |
7. A non-transitory computer-readable storage medium comprising instructions executable by a computer processor, the instructions comprising: instructions for receiving a query associated with a user of a social networking system; instructions for obtaining a result set comprising a plurality of objects from an object store of the social networking system that match the query, the plurality of objects including a first object having a first type and obtained based on the query using a first search algorithm, and a second object having a second type different from the first type and obtained based on the query using a second search algorithm; instructions for ordering at least a plurality of the objects of the result set based at least in part on measures of affinities of the user for the objects, an affinity of the user for an object comprising at least one from a group consisting of: a distance on a social graph between the user and the object, and a similarity between the user and the object, the social graph having nodes corresponding to objects and edges corresponding to relationships of the objects; and instructions for providing at least a portion of the result set to a client device. | 7. A non-transitory computer-readable storage medium comprising instructions executable by a computer processor, the instructions comprising: instructions for receiving a query associated with a user of a social networking system; instructions for obtaining a result set comprising a plurality of objects from an object store of the social networking system that match the query, the plurality of objects including a first object having a first type and obtained based on the query using a first search algorithm, and a second object having a second type different from the first type and obtained based on the query using a second search algorithm; instructions for ordering at least a plurality of the objects of the result set based at least in part on measures of affinities of the user for the objects, an affinity of the user for an object comprising at least one from a group consisting of: a distance on a social graph between the user and the object, and a similarity between the user and the object, the social graph having nodes corresponding to objects and edges corresponding to relationships of the objects; and instructions for providing at least a portion of the result set to a client device. 11. The non-transitory computer-readable storage medium of claim 7 , wherein the objects of the result set are grouped within the result set based at least in part on a search algorithm that produced them, the search algorithms including one or more of a second-order connections search, a history search, and a global importance search. | 0.5 |
10. An apparatus, comprising: an input device, wherein the input device comprises an interface, wherein the interface comprises a plurality of keys, wherein each of the plurality of keys corresponds to one or more characters; at least one processor programmed to receive the sequential string of characters through the input device that corresponds to a word, compare the received sequential string of characters with a word corpus, generate the at least two candidate words, wherein each of the at least two candidate words comprises a string of characters from the word corpus, calculate a probability of erroneously inputting any given character of the received sequential string of characters through an input device, wherein the erroneous inputting of a character of the string of characters comprises any of poor spelling by the user, mis-striking a key of the plurality of keys, wherein the wrong key is entered, or mis-actuation of a key of the plurality of keys, wherein the key is not entered properly and either the character is not entered or is double entered, generate variable error costs, wherein the variable error costs are determined by the calculated probability of erroneously inputting any given character of the received sequential string of characters, and calculate an editing distance for each of the at least two candidate words using the generated variable error costs, wherein the editing distance is the degree of attenuation between each of the candidate words and the received sequential string of characters; and a selector configured to select a preferred candidate from the at least two candidate words using the editing distance, wherein the preferred candidate word has the smallest editing distance of all the editing distances of the at least two candidate words. | 10. An apparatus, comprising: an input device, wherein the input device comprises an interface, wherein the interface comprises a plurality of keys, wherein each of the plurality of keys corresponds to one or more characters; at least one processor programmed to receive the sequential string of characters through the input device that corresponds to a word, compare the received sequential string of characters with a word corpus, generate the at least two candidate words, wherein each of the at least two candidate words comprises a string of characters from the word corpus, calculate a probability of erroneously inputting any given character of the received sequential string of characters through an input device, wherein the erroneous inputting of a character of the string of characters comprises any of poor spelling by the user, mis-striking a key of the plurality of keys, wherein the wrong key is entered, or mis-actuation of a key of the plurality of keys, wherein the key is not entered properly and either the character is not entered or is double entered, generate variable error costs, wherein the variable error costs are determined by the calculated probability of erroneously inputting any given character of the received sequential string of characters, and calculate an editing distance for each of the at least two candidate words using the generated variable error costs, wherein the editing distance is the degree of attenuation between each of the candidate words and the received sequential string of characters; and a selector configured to select a preferred candidate from the at least two candidate words using the editing distance, wherein the preferred candidate word has the smallest editing distance of all the editing distances of the at least two candidate words. 11. The apparatus of claim 10 , wherein the characters comprise any of alphabetic symbols, syllabic symbols, or ideographic symbols. | 0.593978 |
7. A computer-readable storage medium encoded with executable instructions for causing a programmable processor to: select a MUN transformation, wherein the instructions to select the MUN transformation comprise instructions to: receive a source report dimensional member reference and a target report dimensional member reference; and select the MUN transformation based upon: a source model type associated with the source dimensional member reference; and a target model type associated with the target dimensional member reference; and transform a MUN of a first data source into a MUN of a second data source, the instructions to transform comprising at least one of: instructions to transform a first OLAP MUN to a second OLAP MUN, the first OLAP MUN and second OLAP MUN being of different source technologies; or instructions to transform a DMR MUN to an OLAP MUN. | 7. A computer-readable storage medium encoded with executable instructions for causing a programmable processor to: select a MUN transformation, wherein the instructions to select the MUN transformation comprise instructions to: receive a source report dimensional member reference and a target report dimensional member reference; and select the MUN transformation based upon: a source model type associated with the source dimensional member reference; and a target model type associated with the target dimensional member reference; and transform a MUN of a first data source into a MUN of a second data source, the instructions to transform comprising at least one of: instructions to transform a first OLAP MUN to a second OLAP MUN, the first OLAP MUN and second OLAP MUN being of different source technologies; or instructions to transform a DMR MUN to an OLAP MUN. 8. The computer-readable storage medium of claim 7 , wherein the instructions to select the MUN transformation comprise instructions to: select a different source OLAP to OLAP transformation when the underlying data source of both of the source model and target model are OLAP from different source data types; and select a DMR to OLAP transformation when the underlying data source of the source model is DMR and the underlying data source of the target model is OLAP. | 0.78164 |
6. The computer-readable medium as recited in claim 1 , wherein the components further comprise a transaction component configured to: cause data updates to a resource maintained at network location that occur when the client computing device is disconnected from the network to be stored by the cache component, and cause the data updates to be synchronized with the resource maintained at the network location when a network connection is re-established. | 6. The computer-readable medium as recited in claim 1 , wherein the components further comprise a transaction component configured to: cause data updates to a resource maintained at network location that occur when the client computing device is disconnected from the network to be stored by the cache component, and cause the data updates to be synchronized with the resource maintained at the network location when a network connection is re-established. 7. The computer-readable medium as recited in claim 6 , wherein causing the data updates to be synchronized at a network location when a network connection is re-established includes creating a transaction that describes the data update serialized in XML for transmission over the network. | 0.861781 |
13. A system for intelligent control of a web browser session, comprising: at least one emulating engine operable to utilize a web browser session to execute instructions, contained in a plurality of unique tags in a script, to perform a task at a controlling website of a host server specified in the script, the at least one emulating engine comprising an emulator queue operable to hold a plurality of scripts for processing by the at least one emulating engine for automatic control of a web browser session in response to the processing of a script; a controlling engine operable to receive for receiving a plurality of scripts and managing manage the distribution of the plurality of scripts for processing by the at least one emulating engine; and at least one requesting server, the at least one requesting server comprising a plurality of script templates for creating the script. | 13. A system for intelligent control of a web browser session, comprising: at least one emulating engine operable to utilize a web browser session to execute instructions, contained in a plurality of unique tags in a script, to perform a task at a controlling website of a host server specified in the script, the at least one emulating engine comprising an emulator queue operable to hold a plurality of scripts for processing by the at least one emulating engine for automatic control of a web browser session in response to the processing of a script; a controlling engine operable to receive for receiving a plurality of scripts and managing manage the distribution of the plurality of scripts for processing by the at least one emulating engine; and at least one requesting server, the at least one requesting server comprising a plurality of script templates for creating the script. 14. The system of claim 13 , further comprising at least one requesting workstation and an interface workstation, the interface workstation comprising the controlling engine and the at least one emulating engine. | 0.599315 |
9. A system comprising: one or more processing devices; and one or more non-transitory computer-readable media coupled to the one or more processing devices having instructions stored thereon which, when executed by the one or more processing devices, cause the one or more processing devices to perform operations comprising: scanning data that is maintained on multiple social networks, wherein scanning comprises identifying, by one or more processors, data that is associated with a social entity; determining one or more characteristics of the identified data; generating, for each of the one or more characteristics, a reference to the identified data that indicates the characteristic; algorithmically comparing one or more generated references to one or more known references, wherein the one or more known references are references to characteristics of identified data that have been assigned a level of risk, and wherein the one or more generated references that are compared to the one or more known references are dynamically selected from a group of generated references; determining, based on the algorithmic comparisons, a risk score for a social entity; and determining, based on a statistical algorithm, a confidence score for the risk score, wherein the confidence score indicates the reliability of the determined risk score. | 9. A system comprising: one or more processing devices; and one or more non-transitory computer-readable media coupled to the one or more processing devices having instructions stored thereon which, when executed by the one or more processing devices, cause the one or more processing devices to perform operations comprising: scanning data that is maintained on multiple social networks, wherein scanning comprises identifying, by one or more processors, data that is associated with a social entity; determining one or more characteristics of the identified data; generating, for each of the one or more characteristics, a reference to the identified data that indicates the characteristic; algorithmically comparing one or more generated references to one or more known references, wherein the one or more known references are references to characteristics of identified data that have been assigned a level of risk, and wherein the one or more generated references that are compared to the one or more known references are dynamically selected from a group of generated references; determining, based on the algorithmic comparisons, a risk score for a social entity; and determining, based on a statistical algorithm, a confidence score for the risk score, wherein the confidence score indicates the reliability of the determined risk score. 12. The system of claim 9 , further comprising: generating, based on the determined confidence score, a normalized risk score for the social entity. | 0.735079 |
19. A system for displaying an electronic document, the system comprising: a handheld device operated by a user and configured to render a current page of an electronic document on a screen of the handheld device; a display server configured to render an adjacent page of the electronic document on a display external to the handheld device, wherein the adjacent page is adjacent to the current page within the electronic document; and a reading device configured to receive the electronic document and provide the current page to the handheld device and the adjacent page to the display server. | 19. A system for displaying an electronic document, the system comprising: a handheld device operated by a user and configured to render a current page of an electronic document on a screen of the handheld device; a display server configured to render an adjacent page of the electronic document on a display external to the handheld device, wherein the adjacent page is adjacent to the current page within the electronic document; and a reading device configured to receive the electronic document and provide the current page to the handheld device and the adjacent page to the display server. 20. The system of claim 19 , wherein the reading device is the handheld device. | 0.674623 |
3. A method of enabling input on a handheld electronic device that comprises an output apparatus, an input apparatus comprising a plurality of input keys, and a memory having stored therein a plurality of language objects, at least some of the keys having at least one character assigned thereto, the method comprising: detecting selection of a set of keys; responsive to detecting a first selection of one of the keys, initiating a text entry session on the handheld electronic device; terminating the text entry session; detecting a post-termination key selection indicating an entry of a character and, responsive thereto, resuming the text entry session; and responsive to the resuming of the text entry session, locating a language object that corresponds with the set of key selections plus the post-termination key selection. | 3. A method of enabling input on a handheld electronic device that comprises an output apparatus, an input apparatus comprising a plurality of input keys, and a memory having stored therein a plurality of language objects, at least some of the keys having at least one character assigned thereto, the method comprising: detecting selection of a set of keys; responsive to detecting a first selection of one of the keys, initiating a text entry session on the handheld electronic device; terminating the text entry session; detecting a post-termination key selection indicating an entry of a character and, responsive thereto, resuming the text entry session; and responsive to the resuming of the text entry session, locating a language object that corresponds with the set of key selections plus the post-termination key selection. 4. The method of claim 3 , further comprising determining that a focus of the processor apparatus is on a location abutting the text entry session, and detecting a selection of a key at the location as the post-termination key selection. | 0.5 |
17. A method for analyzing an electronic communication for behavioral assessment data, the method comprising: receiving, by a control processor, a single electronic communication in text form from a communicant; analyzing the text of the electronic communication by mining the text of the electronic communication and applying a predetermined linguistic-based psychological behavioral model to the text of the electronic communication; and generating behavioral assessment data including a personality type corresponding to the analyzed text of the electronic communication. | 17. A method for analyzing an electronic communication for behavioral assessment data, the method comprising: receiving, by a control processor, a single electronic communication in text form from a communicant; analyzing the text of the electronic communication by mining the text of the electronic communication and applying a predetermined linguistic-based psychological behavioral model to the text of the electronic communication; and generating behavioral assessment data including a personality type corresponding to the analyzed text of the electronic communication. 23. The method of claim 17 , which further comprises adapting the predetermined linguistic-based psychological behavioral model to assess distress levels in a communication, the method further comprising generating distress assessment data corresponding to the analyzed text. | 0.794506 |
1. A method performed on a programmable processor, comprising: receiving, at the programmable processor, a first keyword entered into a search engine to search for Internet content; obtaining, via the programmable processor, categories that corresponds to the first keyword, the categories comprising second keywords that relate to the first keyword, second keywords in the categories having associated confidence scores, where a confidence score represents an indication of how often a keyword is hit within a corresponding category; presenting, on a display device, the categories that correspond to the first keyword; receiving, at the programmable processor, a selection corresponding to at least one of the categories; generating, via the programmable processor, third keywords associated with the selection, wherein generating the third keywords comprises obtaining all or part of the second keywords in the at least one of the categories, and ranking obtained second keywords according to confidence score; and incorporating, via the programmable processor, the third keywords into advertising content. | 1. A method performed on a programmable processor, comprising: receiving, at the programmable processor, a first keyword entered into a search engine to search for Internet content; obtaining, via the programmable processor, categories that corresponds to the first keyword, the categories comprising second keywords that relate to the first keyword, second keywords in the categories having associated confidence scores, where a confidence score represents an indication of how often a keyword is hit within a corresponding category; presenting, on a display device, the categories that correspond to the first keyword; receiving, at the programmable processor, a selection corresponding to at least one of the categories; generating, via the programmable processor, third keywords associated with the selection, wherein generating the third keywords comprises obtaining all or part of the second keywords in the at least one of the categories, and ranking obtained second keywords according to confidence score; and incorporating, via the programmable processor, the third keywords into advertising content. 2. The method of claim 1 , wherein the first keyword is received via a graphical user interface (GUI). | 0.739278 |
1. A method of recognizing names from a text string entered according to one of a plurality of spoken languages for providing helpful actions in association with recognized names, the method being implemented at least in part by a computer and comprising: receiving, by the computer, a previously generated text string; passing the text string to a name recognizer application; determining whether a particular spoken language is associated with the text string; applying a set of name rules of the spoken language associated with the text string to a plurality of individual words comprising the text string, the set of name rules comprising grammatical rules and sentence structure rules in the spoken language; determining whether any of the plurality of individual words comprise a name according to the set of name rules of the spoken language associated with the text string; if any of the plurality of individual words comprise a name, generating a list of user actions that may be performed on the name, wherein generating the list of actions that may be performed on the name comprises, analyzing the language associated with the text string, and determining if the name exists in a user contacts database, associating the list of actions with the name, returning the name and the list of user actions associated with the name to a host application with which the text string was previously generated for providing the list of user actions associated with the name, and marking the name in the text string to indicate actions are available in association with the name; and providing to a user the list of user actions in association with the name. | 1. A method of recognizing names from a text string entered according to one of a plurality of spoken languages for providing helpful actions in association with recognized names, the method being implemented at least in part by a computer and comprising: receiving, by the computer, a previously generated text string; passing the text string to a name recognizer application; determining whether a particular spoken language is associated with the text string; applying a set of name rules of the spoken language associated with the text string to a plurality of individual words comprising the text string, the set of name rules comprising grammatical rules and sentence structure rules in the spoken language; determining whether any of the plurality of individual words comprise a name according to the set of name rules of the spoken language associated with the text string; if any of the plurality of individual words comprise a name, generating a list of user actions that may be performed on the name, wherein generating the list of actions that may be performed on the name comprises, analyzing the language associated with the text string, and determining if the name exists in a user contacts database, associating the list of actions with the name, returning the name and the list of user actions associated with the name to a host application with which the text string was previously generated for providing the list of user actions associated with the name, and marking the name in the text string to indicate actions are available in association with the name; and providing to a user the list of user actions in association with the name. 11. The method of claim 1 , wherein applying the set of name rules of the spoken language associated with the text string to the plurality of individual words comprising the text string, includes determining whether any words in the text string are followed by a location designation. | 0.516685 |
1. A query plan execution system comprising: a memory; one or more processors; a plan guide metadata store that stores one or more plan guides that are each associated with one or more queries, wherein each plan guide comprises one or more hints that are supplied by a user independently of the creation of and without modifying the associated one or more queries, wherein each plan guide is one of multiple types including object, SQL, and template types; and an execution environment that, upon receiving a query to be executed, accesses the plan guide metadata store to determine whether the query is associated with one or more of the plan guides, and upon locating a matching plan guide, modifies at least one query statement of the query with the one or more hints of the matching plan guide such that the one or more hints are used to guide an optimization process that generates a query plan for the query wherein: when the query is part of a stored procedure, the matching plan guide is of type object, when the query is part of a batch of query statements, the matching plan guide is of type SQL, and when the matching plan guide is of type template, the matching plan guide directs the execution environment to force parameterization of the query. | 1. A query plan execution system comprising: a memory; one or more processors; a plan guide metadata store that stores one or more plan guides that are each associated with one or more queries, wherein each plan guide comprises one or more hints that are supplied by a user independently of the creation of and without modifying the associated one or more queries, wherein each plan guide is one of multiple types including object, SQL, and template types; and an execution environment that, upon receiving a query to be executed, accesses the plan guide metadata store to determine whether the query is associated with one or more of the plan guides, and upon locating a matching plan guide, modifies at least one query statement of the query with the one or more hints of the matching plan guide such that the one or more hints are used to guide an optimization process that generates a query plan for the query wherein: when the query is part of a stored procedure, the matching plan guide is of type object, when the query is part of a batch of query statements, the matching plan guide is of type SQL, and when the matching plan guide is of type template, the matching plan guide directs the execution environment to force parameterization of the query. 3. The system of claim 1 , wherein the query is part of an entity comprising one of a batch of query statements, a module, or a stored procedure, and wherein the execution environment parameterizes a statement of the entity using forced parameterization. | 0.552632 |
16. The method of claim 15 further comprising the step of: operating a selection device to instantaneously switch the system from one context to another. | 16. The method of claim 15 further comprising the step of: operating a selection device to instantaneously switch the system from one context to another. 17. The method of claim 16 further comprising the step of; storing at least one user application in a recognition server for a plurality of speech recognition units in a network to enable the applications to be recognized concurrently in the network. | 0.914175 |
9. A method for providing automated call center post-call processing, comprising: automatically processing a call through a call center by executing a customer support scenario controlled by an agent via one or more scripts; providing a sliding control to the agent and varying a level of automation used in executing the customer support scenario by altering a course of at least one of the scripts; identifying verbal speech utterances from a speaker in a stream of user messages recorded during the customer support scenario and parsed from the call; storing the stream of user messages into a database maintained by the call center; and processing the user messages following completion of the call comprising identifying aspects of the call, wherein the aspects comprise at least one of a general flow of the call and one or more characteristics of the speaker, and manipulating at least one of the verbal speech utterances, wherein the manipulation comprises at least one of ranking the at least one verbal speech utterance and editing the at least one verbal speech utterance. | 9. A method for providing automated call center post-call processing, comprising: automatically processing a call through a call center by executing a customer support scenario controlled by an agent via one or more scripts; providing a sliding control to the agent and varying a level of automation used in executing the customer support scenario by altering a course of at least one of the scripts; identifying verbal speech utterances from a speaker in a stream of user messages recorded during the customer support scenario and parsed from the call; storing the stream of user messages into a database maintained by the call center; and processing the user messages following completion of the call comprising identifying aspects of the call, wherein the aspects comprise at least one of a general flow of the call and one or more characteristics of the speaker, and manipulating at least one of the verbal speech utterances, wherein the manipulation comprises at least one of ranking the at least one verbal speech utterance and editing the at least one verbal speech utterance. 10. A method according to claim 9 , further comprising: generating a transcript of the stream of user messages; and storing the transcript into the database. | 0.525311 |
10. The computer readable medium of claim 9 wherein the data results include rows in a table found from the execution of the separate query portions, and wherein rows duplicated between the data results from the separate query portions are removed from one of the data results. | 10. The computer readable medium of claim 9 wherein the data results include rows in a table found from the execution of the separate query portions, and wherein rows duplicated between the data results from the separate query portions are removed from one of the data results. 13. The computer readable medium of claim 10 wherein record IDs of an index to the database are found as data results and are combined together, and further comprising accessing and joining rows of different tables in the database pointed to by the record IDs to provide the final results table. | 0.899936 |
6. A computer-readable storage medium having computer-executable instructions for causing a computer system to control electronic components using multimodal integration, said computer-executable instructions comprising: accepting inputs from: a pointer-based object selection process module that identifies an electronic component selected by a user via a pointing device in association with at least one camera and at least one light-emitting diode that are used for identifying the electronic component selected by the user, a gesture recognition process module that recognizes one or more motions performed by the user in three-dimensional space via the pointing device in association with at least one accelerometer that is used for detecting motion of the pointing device, and a speech control process module that identifies the electronic component the user desires to manipulate and a command the user desires to implement; integrating said inputs from the pointer-based object selection process module and the speech control process module to arrive at a unified interpretation of what electronic component the user wants to control; and integrating said inputs from the gesture recognition process module and the speech control process module to arrive at a unified interpretation of what control action is desired, wherein the electronic components being controlled are separate from the computer system but are in communication with the computer system via a computer network. | 6. A computer-readable storage medium having computer-executable instructions for causing a computer system to control electronic components using multimodal integration, said computer-executable instructions comprising: accepting inputs from: a pointer-based object selection process module that identifies an electronic component selected by a user via a pointing device in association with at least one camera and at least one light-emitting diode that are used for identifying the electronic component selected by the user, a gesture recognition process module that recognizes one or more motions performed by the user in three-dimensional space via the pointing device in association with at least one accelerometer that is used for detecting motion of the pointing device, and a speech control process module that identifies the electronic component the user desires to manipulate and a command the user desires to implement; integrating said inputs from the pointer-based object selection process module and the speech control process module to arrive at a unified interpretation of what electronic component the user wants to control; and integrating said inputs from the gesture recognition process module and the speech control process module to arrive at a unified interpretation of what control action is desired, wherein the electronic components being controlled are separate from the computer system but are in communication with the computer system via a computer network. 11. The computer-readable storage medium of claim 6 , wherein the instruction for accepting inputs, comprises a sub-instruction for inputting from the speech control process module an indication as to what command the user wants implemented based on a word or phase spoken by the user. | 0.542142 |
9. A process of preparing a source program that accesses an application through an application program interface having a method with an argument, the argument having a type associated therewith, the source program having an internal object representing a call to the method, the call having a parameter associated therewith, the parameter representing instructions in the program, the process comprising: with at least one processor: determining, based on an indicator in the source program, whether an external semantic data structure is to be created to represent the instructions represented by the parameter, wherein the external semantic data structure is to be created when the parameter has a delegate type; when the external semantic data structure is to be created, automatically creating in memory the external semantic data structure representing the parameter representing the instructions, based on the type of the argument of the method of the application program interface wherein the external data structure can be passed to an external application and converted to executable instructions for the external application to perform; and when the external semantic data structure is not to be created, converting the internal object into object code. | 9. A process of preparing a source program that accesses an application through an application program interface having a method with an argument, the argument having a type associated therewith, the source program having an internal object representing a call to the method, the call having a parameter associated therewith, the parameter representing instructions in the program, the process comprising: with at least one processor: determining, based on an indicator in the source program, whether an external semantic data structure is to be created to represent the instructions represented by the parameter, wherein the external semantic data structure is to be created when the parameter has a delegate type; when the external semantic data structure is to be created, automatically creating in memory the external semantic data structure representing the parameter representing the instructions, based on the type of the argument of the method of the application program interface wherein the external data structure can be passed to an external application and converted to executable instructions for the external application to perform; and when the external semantic data structure is not to be created, converting the internal object into object code. 10. The process of claim 9 , wherein the program is in a source code language. | 0.673295 |
1. A method for representing field structures in a markup language document, comprising: inputting at a computing device an application document that has been generated by a word-processing application that uses a file format that is specific to the application, wherein the file format is in a non-markup language format that is native to the application and the file format comprises unique properties for describing fields within the document, wherein the unique properties are defined by the application; determining at the computing device one or more unique properties corresponding to a field that relates to at least one section of the application document; determining at the computing device whether the field is a complex field or a simple field; mapping the determined properties of the field into at least one of a markup language element, an attribute, and/or a value, wherein the field is designated with a simple field markup language element when the field is determined to be a simple field; and storing at the computing device the mapped properties of the field in the markup language document whereby applications different from the application can understand the mapped field properties stored in the markup language document. | 1. A method for representing field structures in a markup language document, comprising: inputting at a computing device an application document that has been generated by a word-processing application that uses a file format that is specific to the application, wherein the file format is in a non-markup language format that is native to the application and the file format comprises unique properties for describing fields within the document, wherein the unique properties are defined by the application; determining at the computing device one or more unique properties corresponding to a field that relates to at least one section of the application document; determining at the computing device whether the field is a complex field or a simple field; mapping the determined properties of the field into at least one of a markup language element, an attribute, and/or a value, wherein the field is designated with a simple field markup language element when the field is determined to be a simple field; and storing at the computing device the mapped properties of the field in the markup language document whereby applications different from the application can understand the mapped field properties stored in the markup language document. 7. The method of claim 1 , further comprising: determining whether properties associated with all fields of the application document have been stored in the markup language document; and processing further fields when the properties associated with all fields have not been stored in the markup language document. | 0.561429 |
4. The method of claim 1 , wherein step (b) further comprises: obtaining a total likelihood score α r for each of the plurality of speech audio files. | 4. The method of claim 1 , wherein step (b) further comprises: obtaining a total likelihood score α r for each of the plurality of speech audio files. 6. The method of claim 4 , further comprising using the mathematical equation β r = α r f r to determine the average frame likelihood score of an audio file, wherein β r is the average frame likelihood score, α r is a total likelihood score of the audio file, and f r is a number of feature frames of the audio file. | 0.931828 |
1. A mobile device configured to communicate with at least one server over a network to facilitate allocation of conversational resources, the mobile device comprising: at least one processor configured to: in response to receiving a request for a conversational service, determine, based at least in part on available conversational resources at the mobile device, which one of the following three ways is to be used for processing the requested conversational service: (1) processing the requested conversational service locally using the mobile device, (2) processing the requested conversational service remotely using the at least one server, and (3) processing the requested conversational service at least in part locally using the mobile device and at least in part remotely using the at least one server, wherein the determining is performed without evaluating whether processing the requested conversational service locally produces acceptable results; and automatically communicate with the at least one server in furtherance of processing of the requested conversational service, when it is determined that the requested conversational service is to be processed partially or fully using the at least one server. | 1. A mobile device configured to communicate with at least one server over a network to facilitate allocation of conversational resources, the mobile device comprising: at least one processor configured to: in response to receiving a request for a conversational service, determine, based at least in part on available conversational resources at the mobile device, which one of the following three ways is to be used for processing the requested conversational service: (1) processing the requested conversational service locally using the mobile device, (2) processing the requested conversational service remotely using the at least one server, and (3) processing the requested conversational service at least in part locally using the mobile device and at least in part remotely using the at least one server, wherein the determining is performed without evaluating whether processing the requested conversational service locally produces acceptable results; and automatically communicate with the at least one server in furtherance of processing of the requested conversational service, when it is determined that the requested conversational service is to be processed partially or fully using the at least one server. 5. The mobile device of claim 1 , wherein processing the requested conversational service comprises performing speech recognition on a speech waveform, and the at least one processor is configured to automatically communicate with the at least one server by: transmitting a compressed speech waveform corresponding to the speech waveform. | 0.710568 |
1. A method for profiling network traffic of a network, comprising: obtaining a first plurality of packets associated with a first server in the network from a plurality of flows in the network traffic; extracting a first plurality of features corresponding to the plurality of flows from the first plurality of packets; iteratively reducing, using a computer, the first plurality of features, comprising: in a first iteration based on a first window size: dividing a first feature and a second feature of the first plurality of features into a first plurality of sections and a second plurality of sections, respectively, wherein a size of at least one section of the first plurality of sections and the second plurality of sections is based on the first window size: comparing a first section of the first plurality of sections and a second section of the second plurality of sections to generate a first matching token based on a pre-determined criterion; retaining, if at least the first matching token exceeds a first pre-determined threshold, the first section and the second section in the first feature and the second feature, respectively; removing, if at least the first matching token is less than a second pre-determined threshold, the first section and the second section from the first feature and the second feature, respectively; and in a second iteration subsequent to the first iteration and based on a second window size reduced from the first window size: dividing the first feature and a third feature of the first plurality of features into a third plurality of sections and a fourth plurality of sections, respectively, wherein a size of at least one section of the third plurality of sections and the fourth plurality of sections is based on the second window size: comparing a third section of the third plurality of sections and a fourth section of the fourth plurality of sections to generate a second matching token based on the pre-determined criterion; retaining, if at least the second matching token exceeds a third pre-determined threshold, the third section and the fourth section in the first feature and the third feature, respectively; removing, if at least the second matching token is less than a fourth pre-determined threshold, the third section and the fourth section from the first feature and the third feature, respectively; determining, using the computer, a first packet content signature based on the first plurality of features by at least iteratively reducing the first plurality of features, wherein the packet content signature is associated with a network application running on the first server; and determining, using the computer, a second server in the network as running the network application by analyzing a second plurality of packets associated with the second server in the network traffic based on the first packet content signature. | 1. A method for profiling network traffic of a network, comprising: obtaining a first plurality of packets associated with a first server in the network from a plurality of flows in the network traffic; extracting a first plurality of features corresponding to the plurality of flows from the first plurality of packets; iteratively reducing, using a computer, the first plurality of features, comprising: in a first iteration based on a first window size: dividing a first feature and a second feature of the first plurality of features into a first plurality of sections and a second plurality of sections, respectively, wherein a size of at least one section of the first plurality of sections and the second plurality of sections is based on the first window size: comparing a first section of the first plurality of sections and a second section of the second plurality of sections to generate a first matching token based on a pre-determined criterion; retaining, if at least the first matching token exceeds a first pre-determined threshold, the first section and the second section in the first feature and the second feature, respectively; removing, if at least the first matching token is less than a second pre-determined threshold, the first section and the second section from the first feature and the second feature, respectively; and in a second iteration subsequent to the first iteration and based on a second window size reduced from the first window size: dividing the first feature and a third feature of the first plurality of features into a third plurality of sections and a fourth plurality of sections, respectively, wherein a size of at least one section of the third plurality of sections and the fourth plurality of sections is based on the second window size: comparing a third section of the third plurality of sections and a fourth section of the fourth plurality of sections to generate a second matching token based on the pre-determined criterion; retaining, if at least the second matching token exceeds a third pre-determined threshold, the third section and the fourth section in the first feature and the third feature, respectively; removing, if at least the second matching token is less than a fourth pre-determined threshold, the third section and the fourth section from the first feature and the third feature, respectively; determining, using the computer, a first packet content signature based on the first plurality of features by at least iteratively reducing the first plurality of features, wherein the packet content signature is associated with a network application running on the first server; and determining, using the computer, a second server in the network as running the network application by analyzing a second plurality of packets associated with the second server in the network traffic based on the first packet content signature. 2. The method of claim 1 , wherein each of the first plurality of features comprises a pre-determined number of bytes of each of a pre-determined number of packets of one of the plurality of flows. | 0.591343 |
1. A method executed by one or more computing devices for characterizing a document, the method comprising: generating, by at least one of the one or more computing devices, one or more sets of taxonomic nouns corresponding to a document, wherein the one or more sets of taxonomic nouns comprise one or more of: a set of first taxonomic nouns based upon classification information generated by an author of the document; a set of second taxonomic nouns based upon one or more user-generated tags characterizing at least a portion of the document; a set of third taxonomic nouns based upon one or more search terms utilized to access the document; or a set of fourth taxonomic nouns based upon the attributes related to a method of access of the document; generating, by at least one of the one or more computing devices, a set of fifth taxonomic nouns by processing the document based upon one or more pattern rules and a dictionary of known terms, wherein the one or more pattern rules specify a method of extracting terms from the document; and aggregating, by at least one of the one or more computing devices, at least one of the one or more sets of taxonomic nouns with the set of fifth taxonomic nouns into a composite set of taxonomic nouns; and characterizing, by at least one of the one or more computing devices, the document based on the composite set of taxonomic nouns. | 1. A method executed by one or more computing devices for characterizing a document, the method comprising: generating, by at least one of the one or more computing devices, one or more sets of taxonomic nouns corresponding to a document, wherein the one or more sets of taxonomic nouns comprise one or more of: a set of first taxonomic nouns based upon classification information generated by an author of the document; a set of second taxonomic nouns based upon one or more user-generated tags characterizing at least a portion of the document; a set of third taxonomic nouns based upon one or more search terms utilized to access the document; or a set of fourth taxonomic nouns based upon the attributes related to a method of access of the document; generating, by at least one of the one or more computing devices, a set of fifth taxonomic nouns by processing the document based upon one or more pattern rules and a dictionary of known terms, wherein the one or more pattern rules specify a method of extracting terms from the document; and aggregating, by at least one of the one or more computing devices, at least one of the one or more sets of taxonomic nouns with the set of fifth taxonomic nouns into a composite set of taxonomic nouns; and characterizing, by at least one of the one or more computing devices, the document based on the composite set of taxonomic nouns. 2. The method of claim 1 , wherein the classification information generated by the author of the document comprises one or more of: a form of the document, content of the document, a function of the document, or metadata assigned to the document. | 0.753633 |
1. A computer-implemented method comprising: identifying, by a computer, in one or more document corpora of a data source, a topic of interest based upon one or more concurring topics identified in the one or more document corpora; automatically extracting, by the computer, from a document corpus, data associated with a plurality of co-occurring topics based on the topic of interest; in response to automatically extracting the data associated with the plurality of co-occurring topics, extracting, by the computer, a plurality of topic identifiers from the plurality of co-occurring topics; generating, by the computer, a periodic topic model comprising a set of one or more term vectors by comparing topic significance among the plurality of topic identifiers; periodically creating, by the computer, new topic ID models using data content in the periodic topic model by identifying a similarity of topics, wherein the new topic ID models are stored in an in-memory database; and linking, by the computer, data in the in-memory database for automated discovery of new topics. | 1. A computer-implemented method comprising: identifying, by a computer, in one or more document corpora of a data source, a topic of interest based upon one or more concurring topics identified in the one or more document corpora; automatically extracting, by the computer, from a document corpus, data associated with a plurality of co-occurring topics based on the topic of interest; in response to automatically extracting the data associated with the plurality of co-occurring topics, extracting, by the computer, a plurality of topic identifiers from the plurality of co-occurring topics; generating, by the computer, a periodic topic model comprising a set of one or more term vectors by comparing topic significance among the plurality of topic identifiers; periodically creating, by the computer, new topic ID models using data content in the periodic topic model by identifying a similarity of topics, wherein the new topic ID models are stored in an in-memory database; and linking, by the computer, data in the in-memory database for automated discovery of new topics. 9. The method of claim 1 , wherein the set of the one or more term vectors in the periodic topic computer model corresponds to a second set of the one or more term vectors. | 0.550455 |
2. The method of claim 1 wherein decrypting the scanned text includes decrypting the scanned text using a session key. | 2. The method of claim 1 wherein decrypting the scanned text includes decrypting the scanned text using a session key. 5. The method of claim 2 wherein the session key includes information about a capture. | 0.898539 |
29. The method according to claim 26 , wherein receipt of the structured reply causes a processor to contact the user submitting the structured suggestion. | 29. The method according to claim 26 , wherein receipt of the structured reply causes a processor to contact the user submitting the structured suggestion. 30. The method according to claim 29 , wherein the processor contacts the user via e-mail. | 0.953887 |
43. A method of social search and/or social interactive knowledge discovery comprising an implementation using a portion or whole capacity of one or more non-transitory computer readable media with a set of instructions thereon, executable by one or more processing apparatuses, configured, while being or is executed, to perform: providing, using one or more data processing or computing devices, a searching utility environment wherein a participant can input a query or content; providing an interactive knowledge discovery session related to a body of knowledge in response to a participant's input to the searching utility; providing a social and interactive environment for one or more participants wherein at least one participant can input content; accessing or building a first one or more data structures corresponding to at least one participation matrix representing participation of ontological subjects of a first predefined order into partitions or ontological subjects of a second predefined order of a body of knowledge; accessing, or building in real time, a second one or more data structures corresponding to association strengths between a plurality of ontological subjects of a predefined order; wherein said association strength is a function of: i. probability of occurrences of some of the ontological subjects of the first order in partitions or ontological subjects of a predefined order of the body of knowledge, and ii. co-occurrences of some ontological subjects of the first order in some of partitions or ontological subjects of a predefined order; accessing evaluated, or evaluating in real time, value significances for one or more partitions or one or more ontological subjects of the body of knowledge, based on data of one or more of said first and second one or more data structures and in respect to at least one significance aspect of the one or more partitions or one or more ontological subjects of the body of knowledge; and providing, using one or more data processing or computing devices, a content viewable by one or more participants based on one or more inputs from one or more participants in the session or using one or more sets of ontological subjects or one or more partitions of the body of knowledge based on the evaluated value significances of the one or more partitions and/or one or more ontological subjects of the body of knowledge. | 43. A method of social search and/or social interactive knowledge discovery comprising an implementation using a portion or whole capacity of one or more non-transitory computer readable media with a set of instructions thereon, executable by one or more processing apparatuses, configured, while being or is executed, to perform: providing, using one or more data processing or computing devices, a searching utility environment wherein a participant can input a query or content; providing an interactive knowledge discovery session related to a body of knowledge in response to a participant's input to the searching utility; providing a social and interactive environment for one or more participants wherein at least one participant can input content; accessing or building a first one or more data structures corresponding to at least one participation matrix representing participation of ontological subjects of a first predefined order into partitions or ontological subjects of a second predefined order of a body of knowledge; accessing, or building in real time, a second one or more data structures corresponding to association strengths between a plurality of ontological subjects of a predefined order; wherein said association strength is a function of: i. probability of occurrences of some of the ontological subjects of the first order in partitions or ontological subjects of a predefined order of the body of knowledge, and ii. co-occurrences of some ontological subjects of the first order in some of partitions or ontological subjects of a predefined order; accessing evaluated, or evaluating in real time, value significances for one or more partitions or one or more ontological subjects of the body of knowledge, based on data of one or more of said first and second one or more data structures and in respect to at least one significance aspect of the one or more partitions or one or more ontological subjects of the body of knowledge; and providing, using one or more data processing or computing devices, a content viewable by one or more participants based on one or more inputs from one or more participants in the session or using one or more sets of ontological subjects or one or more partitions of the body of knowledge based on the evaluated value significances of the one or more partitions and/or one or more ontological subjects of the body of knowledge. 56. The method of claim 43 , wherein a session is started for producing new contents. | 0.648731 |
14. The method of claim 1 , wherein: a rate of occurrence is associated with at least one of the multiple components corresponding to the proper name, each of the speech recognition candidates is ranked based on the rate of occurrence associated with the at least one of the multiple components, and checking, for each speech recognition candidate, the representative word for each proper name component against one or more words representing proper name entries in a database on the communication device further comprises checking each speech recognition candidate in an order based on its ranking. | 14. The method of claim 1 , wherein: a rate of occurrence is associated with at least one of the multiple components corresponding to the proper name, each of the speech recognition candidates is ranked based on the rate of occurrence associated with the at least one of the multiple components, and checking, for each speech recognition candidate, the representative word for each proper name component against one or more words representing proper name entries in a database on the communication device further comprises checking each speech recognition candidate in an order based on its ranking. 15. The method of claim 14 , wherein the order is from highest ranked speech recognition candidate to lowest ranked speech recognition candidate. | 0.862216 |
11. A computer system for improving search results from a search engine, the system comprising: a processor and memory configured to execute software instructions embodied in the following software components; a user interface component configured to interact with a search user to receive information describing content that the search user wants to find and to deliver results to the search user; a semantic selection component configured to receive a selection of one or more categories that semantically refine the content that the search user wants to find, wherein the selected categories identify content without one or more inherent ambiguities of keywords; a filtering component configured to receive zero or more filters from the search user that further refine the content that the search user wants to find; a library component configured to store in a data store data that describes one or more categories, filters, and other information used by the system; a search engine selection component configured to select a search engine external to the system to which to provide a query and from which to receive one or more search results; a search string generation component configured to generate a search string for delivery to a search engine based on one or more received categories and filters; a search engine interface component configured to communicate with one or more selected search engines to provide the generated search string and receive one or more search results from the search engine for presentation to the user; and a results processing component configured to manage information gathered from search user interaction with the received search results. | 11. A computer system for improving search results from a search engine, the system comprising: a processor and memory configured to execute software instructions embodied in the following software components; a user interface component configured to interact with a search user to receive information describing content that the search user wants to find and to deliver results to the search user; a semantic selection component configured to receive a selection of one or more categories that semantically refine the content that the search user wants to find, wherein the selected categories identify content without one or more inherent ambiguities of keywords; a filtering component configured to receive zero or more filters from the search user that further refine the content that the search user wants to find; a library component configured to store in a data store data that describes one or more categories, filters, and other information used by the system; a search engine selection component configured to select a search engine external to the system to which to provide a query and from which to receive one or more search results; a search string generation component configured to generate a search string for delivery to a search engine based on one or more received categories and filters; a search engine interface component configured to communicate with one or more selected search engines to provide the generated search string and receive one or more search results from the search engine for presentation to the user; and a results processing component configured to manage information gathered from search user interaction with the received search results. 19. The system of claim 11 wherein the results processing component is further configured to provide an editorial control through which the search user can indicate relative relevance of search results so that future search results can be sorted or filtered based on the results users have found relevant in the past. | 0.5 |
24. A system to operate within a host organization, the system comprising: a processor to execute instructions stored in memory of the system; an analysis engine to generate indices from a dataset of columns and rows, the indices representing probabilistic relationships between the rows and the columns of the dataset; a predictive database system to store the indices; a request interface to expose the predictive database system; the request interface to receive a query for the predictive database system specifying a SIMILAR command term, a specified row as a parameter for the SIMILAR command term, and a specified column as a parameter for the SIMILAR command term; a query interface to query the predictive database system using the SIMILAR command term and passing the specified row and the specified column to generate a predictive record set; and the request interface to further return the predictive record set responsive to the query, the predictive record set having a plurality of elements therein, each of the returned elements of the predictive record set including (i) a row identifier which corresponds to a row of the dataset assessed to be similar, according to a latent structure, to the specified row passed with the SIMILAR command term based on the specified column and (ii) a confidence indicator which indicates a likelihood of a latent relationship between the specified row passed with the SIMILAR command and the row identifier returned for the respective element; and wherein request interface is to further return one of: (i) a most similar row compared to the specified row passed with the SIMILAR command term responsive to the query based on the predictive record set returned and a confidence indicator for each of the similar rows returned with the predictive record set; (ii) a least similar row compared to the specified row passed with the SIMILAR command term responsive to the query based on the predictive record set returned and a confidence indicator for each of the similar rows returned with the predictive record set; and (iii) a related product in a recommender system responsive to a search by an Internet user, wherein the related product corresponds to the one of the similar rows returned with the predictive record set. | 24. A system to operate within a host organization, the system comprising: a processor to execute instructions stored in memory of the system; an analysis engine to generate indices from a dataset of columns and rows, the indices representing probabilistic relationships between the rows and the columns of the dataset; a predictive database system to store the indices; a request interface to expose the predictive database system; the request interface to receive a query for the predictive database system specifying a SIMILAR command term, a specified row as a parameter for the SIMILAR command term, and a specified column as a parameter for the SIMILAR command term; a query interface to query the predictive database system using the SIMILAR command term and passing the specified row and the specified column to generate a predictive record set; and the request interface to further return the predictive record set responsive to the query, the predictive record set having a plurality of elements therein, each of the returned elements of the predictive record set including (i) a row identifier which corresponds to a row of the dataset assessed to be similar, according to a latent structure, to the specified row passed with the SIMILAR command term based on the specified column and (ii) a confidence indicator which indicates a likelihood of a latent relationship between the specified row passed with the SIMILAR command and the row identifier returned for the respective element; and wherein request interface is to further return one of: (i) a most similar row compared to the specified row passed with the SIMILAR command term responsive to the query based on the predictive record set returned and a confidence indicator for each of the similar rows returned with the predictive record set; (ii) a least similar row compared to the specified row passed with the SIMILAR command term responsive to the query based on the predictive record set returned and a confidence indicator for each of the similar rows returned with the predictive record set; and (iii) a related product in a recommender system responsive to a search by an Internet user, wherein the related product corresponds to the one of the similar rows returned with the predictive record set. 28. The system of claim 24 , further comprising: a web-server to implement the request interface; wherein the web-server is to receive as input, a plurality of access requests from one or more client devices from among a plurality of customer organizations communicably interfaced with the host organization via a network; a multi-tenant database system with predictive database functionality to implement the predictive database system; and wherein each customer organization is an entity selected from the group consisting of: a separate and distinct remote organization, an organizational group within the host organization, a business partner of the host organization, or a customer organization that subscribes to cloud computing services provided by the host organization. | 0.567224 |
23. The method of claim 22 , further comprising displaying a plurality of particular completion candidates in the search list with the part of each particular completion candidate matching the partial text entry displayed in a manner different from the remaining part of each of the particular completion candidates displayed in the search list. | 23. The method of claim 22 , further comprising displaying a plurality of particular completion candidates in the search list with the part of each particular completion candidate matching the partial text entry displayed in a manner different from the remaining part of each of the particular completion candidates displayed in the search list. 24. The method of claim 23 , further comprising highlighting the part of each particular completion candidate displayed in the search list that makes up the partial text entry. | 0.925031 |
1. A computer-implemented method for determining a common sequence of ordered statements, comprising: creating a global list comprising a first set of links generated from a first sequence of statements of a first script, wherein a link in the first set of links indicates an ordered mapping between a source statement and a destination statement selected from the first sequence of statements, and an ordered mapping indicates that a source statement is executed before a destination statement is executed; adding, to the global list, a second set of links generated from a second sequence of statements of a second script, wherein a link in the second set of links indicates an ordered mapping between a source statement and a destination statement selected from the second sequence of statements; determining, from the global list, two or more links having equivalent source statements and equivalent destination statements; adding at least one of the two or more links to a first group of common sequences; and storing the first group of common sequences in a database. | 1. A computer-implemented method for determining a common sequence of ordered statements, comprising: creating a global list comprising a first set of links generated from a first sequence of statements of a first script, wherein a link in the first set of links indicates an ordered mapping between a source statement and a destination statement selected from the first sequence of statements, and an ordered mapping indicates that a source statement is executed before a destination statement is executed; adding, to the global list, a second set of links generated from a second sequence of statements of a second script, wherein a link in the second set of links indicates an ordered mapping between a source statement and a destination statement selected from the second sequence of statements; determining, from the global list, two or more links having equivalent source statements and equivalent destination statements; adding at least one of the two or more links to a first group of common sequences; and storing the first group of common sequences in a database. 5. The computer-implemented method of claim 1 , wherein at least one link in the first group of common sequences is assigned a keyword. | 0.921569 |
10. The method according to claim 1 , further comprising transforming one or more of the text documents to a paper document. | 10. The method according to claim 1 , further comprising transforming one or more of the text documents to a paper document. 12. The method according to claim 10 , further comprising transforming the paper document to an image document. | 0.941361 |
1. A computer-implemented method of identifying suspicious usage of an object, the method comprising: receiving a query from a client device regarding an object trusted as non-malicious by a security module executing on the client device, the query including an identifier of the object and a set of usage attributes describing a usage of the object on the client device; identifying a set of usage facts associated with the identified object, the set of usage facts describing typical usages of the identified object on a plurality of client devices; comparing, by a computer, the set of usage facts associated with the identified object and the set of usage attributes included in the query from the client device; responsive to a threshold number of usage attributes from the set of usage attributes not matching the set of usage facts associated with the identified object, classifying the usage of the identified object on the client device as suspicious; responsive to the threshold number of usage attributes from the set of usage attributes matching the set of usage facts associated with the identified object, classifying the usage of the identified object on the client device as non-suspicious; and providing a report to the client device including the classification of the usage of the identified object on the client device. | 1. A computer-implemented method of identifying suspicious usage of an object, the method comprising: receiving a query from a client device regarding an object trusted as non-malicious by a security module executing on the client device, the query including an identifier of the object and a set of usage attributes describing a usage of the object on the client device; identifying a set of usage facts associated with the identified object, the set of usage facts describing typical usages of the identified object on a plurality of client devices; comparing, by a computer, the set of usage facts associated with the identified object and the set of usage attributes included in the query from the client device; responsive to a threshold number of usage attributes from the set of usage attributes not matching the set of usage facts associated with the identified object, classifying the usage of the identified object on the client device as suspicious; responsive to the threshold number of usage attributes from the set of usage attributes matching the set of usage facts associated with the identified object, classifying the usage of the identified object on the client device as non-suspicious; and providing a report to the client device including the classification of the usage of the identified object on the client device. 11. The computer-implemented method of claim 1 , wherein the report further includes reputation information associated with the identified object, the reputation information indicating a likelihood that the identified object trusted as non-malicious contains malware and wherein a lower reputation indicates a higher likelihood that the object contains malware. | 0.593854 |
10. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a search query requesting a search of a collection of custom content resources, wherein resources in the collection of custom content resources are resources exposed to a search engine by a user; obtaining a custom content search result that the search engine has identified in response to the search query using a custom search index generated from the collection of custom content resources; obtaining an indication of relative importance for a custom content resource identified by the custom content search result, the indication of relative importance being an indication of the importance of the custom content resource relative to other resources in the collection of resources and being assigned by the user that exposed the custom content resource to the search engine; determining a score for the custom content search result based on the indication of relative importance for the custom content resource; and ranking the custom content search result with one or more other custom content search results that were identified by the search engine in response to the received query, using the determined score. | 10. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving a search query requesting a search of a collection of custom content resources, wherein resources in the collection of custom content resources are resources exposed to a search engine by a user; obtaining a custom content search result that the search engine has identified in response to the search query using a custom search index generated from the collection of custom content resources; obtaining an indication of relative importance for a custom content resource identified by the custom content search result, the indication of relative importance being an indication of the importance of the custom content resource relative to other resources in the collection of resources and being assigned by the user that exposed the custom content resource to the search engine; determining a score for the custom content search result based on the indication of relative importance for the custom content resource; and ranking the custom content search result with one or more other custom content search results that were identified by the search engine in response to the received query, using the determined score. 11. The system of claim 10 , wherein the operations further comprise receiving, by user input from the user, the indication of relative importance for the custom content resource, including receiving a user selection of one of at least two different indications of relative importance for the custom content resource. | 0.503503 |
4. The system according to claim 3 , wherein the processing unit of the at least one print driver further comprises a set of programmable instructions configured for: assigning a prioritization identifier to the printer-readable format; and storing in the at least one of the at least two caches, for the document, at least one of the document key identifier associated with the document; the prioritization identifier assigned to the printer-readable format; and the printer-readable format corresponding to the document and the document key identifier. | 4. The system according to claim 3 , wherein the processing unit of the at least one print driver further comprises a set of programmable instructions configured for: assigning a prioritization identifier to the printer-readable format; and storing in the at least one of the at least two caches, for the document, at least one of the document key identifier associated with the document; the prioritization identifier assigned to the printer-readable format; and the printer-readable format corresponding to the document and the document key identifier. 7. The system according to claim 4 , wherein the at least two caches comprises a first cache and a second cache, and wherein the printer-readable format is stored in the first cache, the processing unit of the at least one print driver further comprises a set of programmable instructions configured for: removing the printer-readable format from the first cache if a priority threshold for the prioritization identifier has not been met for the printer-readable format. | 0.861887 |
26. An article of manufacture including one or more computer-readable media having sequences of instructions stored thereon, which when executed by a processor, cause the processor to obfuscate a program code sequence independently of compiling or executing the program code sequence by: replacing original class names of classes of the program code sequence with corresponding non-descriptive class names; replacing original field names of fields of the program code sequence with corresponding non-descriptive field names; generating a class inheritance hierarchy of the program code sequence such that naming dependencies among methods of the program code are identified; replacing consistently original method names of inherited methods with corresponding non-descriptive method names in accordance with naming dependencies determined by the class inheritance hierarchy; replacing consistently original method names of overridden methods with corresponding non-descriptive method names in accordance with the naming dependencies determined by the class inheritance hierarchy; and replacing original method names of remaining non-renamed methods of each class of the program code sequence with corresponding non-descriptive method names in accordance with the naming dependencies determined by the class inheritance hierarchy. | 26. An article of manufacture including one or more computer-readable media having sequences of instructions stored thereon, which when executed by a processor, cause the processor to obfuscate a program code sequence independently of compiling or executing the program code sequence by: replacing original class names of classes of the program code sequence with corresponding non-descriptive class names; replacing original field names of fields of the program code sequence with corresponding non-descriptive field names; generating a class inheritance hierarchy of the program code sequence such that naming dependencies among methods of the program code are identified; replacing consistently original method names of inherited methods with corresponding non-descriptive method names in accordance with naming dependencies determined by the class inheritance hierarchy; replacing consistently original method names of overridden methods with corresponding non-descriptive method names in accordance with the naming dependencies determined by the class inheritance hierarchy; and replacing original method names of remaining non-renamed methods of each class of the program code sequence with corresponding non-descriptive method names in accordance with the naming dependencies determined by the class inheritance hierarchy. 29. The article described in claim 26 wherein the replacing consistently original method names of inherited methods, of non-inherited methods and remaining non-renamed methods comprise: sequentially replacing the original method names of the program code sequence with the corresponding non-descriptive method names according to an ordered list of unique non-descriptive names; and starting at a predetermined location in the ordered list of unique non-descriptive names for each class such that original method names are replaced with the corresponding non-descriptive method names that maintain distinguishing characteristics with parameter lists of each of the methods of the program code sequence. | 0.5 |
6. The method of claim 5 , wherein the step of accessing textual postings is performed by a software program that runs automated tasks over the Internet by a crawling program customized for various Internet domains to extract metadata and relevant posting author information as they crawl, including who made the posting and their contact information, along with other stored metadata indicating what may have been learned about this user from past postings. | 6. The method of claim 5 , wherein the step of accessing textual postings is performed by a software program that runs automated tasks over the Internet by a crawling program customized for various Internet domains to extract metadata and relevant posting author information as they crawl, including who made the posting and their contact information, along with other stored metadata indicating what may have been learned about this user from past postings. 7. The method of claim 6 , further including the step of running a software module in a user/representative's Internet-connected computer that reroutes bidirectional private communications from a central site computer to the Internet to conceal the fact that web accesses are part of a centralized web crawling activity. | 0.832155 |
9. A method for collecting and analyzing structured user feedback on websites, said method comprising: generating, using a computer, website user structured feedback forms for receiving website user feedback on website user interaction with a website-based process, said structured feedback forms comprising user selectable feedback messages provided in a categorized and nested structure; determining, based on a website action of a given user, that the given user intends to cancel a transaction associated with the website-based process or abandon the website-based process; upon making said determination, automatically presenting the given user with at least one of the generated website user structured feedback forms or an invitation to enter feedback using at least one of the generated website user structured feedback forms; interfacing with a web analytics service; receiving from the web analytics service web behavior analysis relating to behaviors of the multiplicity of website users; automatically collecting and analyzing, using said computer, said website user feedback entered in said structured feedback forms including factoring the received web behavior analysis in said automatic analysis; and providing, using said computer, at least one analysis report based on said website user feedback from a multiplicity of website users, said at least one analysis report comprising a structured analysis report based on said categorized and nested structure, wherein at least one analysis report includes an integration of the received web behavior analysis; and wherein said automatic analyzing includes analyzing website user feedback in relation to each of two or more stages in the website-based process separately for each stage, factoring into the stage specific analysis web behavior analysis relating to each of the two or more stages and reporting the results of the analysis in relation to the each of two or more stages separately for each stage. | 9. A method for collecting and analyzing structured user feedback on websites, said method comprising: generating, using a computer, website user structured feedback forms for receiving website user feedback on website user interaction with a website-based process, said structured feedback forms comprising user selectable feedback messages provided in a categorized and nested structure; determining, based on a website action of a given user, that the given user intends to cancel a transaction associated with the website-based process or abandon the website-based process; upon making said determination, automatically presenting the given user with at least one of the generated website user structured feedback forms or an invitation to enter feedback using at least one of the generated website user structured feedback forms; interfacing with a web analytics service; receiving from the web analytics service web behavior analysis relating to behaviors of the multiplicity of website users; automatically collecting and analyzing, using said computer, said website user feedback entered in said structured feedback forms including factoring the received web behavior analysis in said automatic analysis; and providing, using said computer, at least one analysis report based on said website user feedback from a multiplicity of website users, said at least one analysis report comprising a structured analysis report based on said categorized and nested structure, wherein at least one analysis report includes an integration of the received web behavior analysis; and wherein said automatic analyzing includes analyzing website user feedback in relation to each of two or more stages in the website-based process separately for each stage, factoring into the stage specific analysis web behavior analysis relating to each of the two or more stages and reporting the results of the analysis in relation to the each of two or more stages separately for each stage. 18. The method according to claim 9 , wherein said automatically collecting and analyzing comprises automatically providing contact information for website users providing feedback so as to enable said website administrator to respond to said feedback. | 0.571338 |
1. A method of evaluating a particular document relating to property, the method comprising: from a set of pre-selected documents, selecting the particular document, wherein each pre-selected document has associated therewith one or more search linkages that identify how the pre-selected document was selected, using user-supplied inputs, from a larger set of documents relating to property and wherein the set of pre-selected documents also have associated therewith one or more organizational linkages, each of which organizational linkages identifies a relationship between at least two pre-selected documents; using the one or more search linkages associated with the particular document to determine a relevance factor associated with the document, wherein using the one or more search linkages associated with the particular document to determine a relevance factor associated with the document comprises determining a baseline relevance factor and thereafter adjusting the relevance factor based on one or more specific comparisons; further comprising using the one or more organizational linkages to determine the relevance factor associated with the particular document, wherein using the one or more organizational linkages to determine the relevance factor associated with the particular document comprises adjusting a baseline relevance factor if a record date of the particular document predates a specific good stop associated with the document; and displaying to a user information relating to the document, wherein the information includes the relevance factor. | 1. A method of evaluating a particular document relating to property, the method comprising: from a set of pre-selected documents, selecting the particular document, wherein each pre-selected document has associated therewith one or more search linkages that identify how the pre-selected document was selected, using user-supplied inputs, from a larger set of documents relating to property and wherein the set of pre-selected documents also have associated therewith one or more organizational linkages, each of which organizational linkages identifies a relationship between at least two pre-selected documents; using the one or more search linkages associated with the particular document to determine a relevance factor associated with the document, wherein using the one or more search linkages associated with the particular document to determine a relevance factor associated with the document comprises determining a baseline relevance factor and thereafter adjusting the relevance factor based on one or more specific comparisons; further comprising using the one or more organizational linkages to determine the relevance factor associated with the particular document, wherein using the one or more organizational linkages to determine the relevance factor associated with the particular document comprises adjusting a baseline relevance factor if a record date of the particular document predates a specific good stop associated with the document; and displaying to a user information relating to the document, wherein the information includes the relevance factor. 7. The method of claim 1 , wherein adjusting the relevance factor based on one or more specific comparisons comprises adjusting the baseline relevance factor based on a comparison between a location associated with the particular document and a location supplied by a user. | 0.58939 |
1. A method of creating a grammar for a natural language dialog system from a descriptor of a device, the method comprising: creating, on a computing device, instances of universal grammar rules for the natural-language dialog as a new grammar based on the device descriptor, the universal grammar rules including a plurality of selected domain objects, each of the selected domain objects including one or more attributes associated with the device, wherein the creating comprises: creating a bridging rule for each broad category of queries in the universal grammar rules; selectively including domain objects as domain objects in the new grammar; creating bridging rules for domain object attributes; and selectively including attributes in the new grammar; wherein the device descriptor specifies functions of the device that are available to an end user through the domain objects for implementing the grammar. | 1. A method of creating a grammar for a natural language dialog system from a descriptor of a device, the method comprising: creating, on a computing device, instances of universal grammar rules for the natural-language dialog as a new grammar based on the device descriptor, the universal grammar rules including a plurality of selected domain objects, each of the selected domain objects including one or more attributes associated with the device, wherein the creating comprises: creating a bridging rule for each broad category of queries in the universal grammar rules; selectively including domain objects as domain objects in the new grammar; creating bridging rules for domain object attributes; and selectively including attributes in the new grammar; wherein the device descriptor specifies functions of the device that are available to an end user through the domain objects for implementing the grammar. 8. The method of claim 1 wherein a domain object allows the device to dynamically join a network, obtain an IP address, convey its capabilities, and learn about presence and capabilities of other devices. | 0.554873 |
42. A computer implemented method for providing navigation options at a client machine without any additional computer program physically installed on said machine, said method occurring entirely at points removed from said machine, said method comprising: receiving a request for a resource at a proxy; extracting and storing a resource identifier from said request at said proxy; forwarding said request for said resource from said proxy to a location having said resource; receiving the resource at the proxy in response to forwarding the request; thereafter parsing the received resource based on the resource identifier to match the received resource with the previously stored resource identifier, analyzing a plurality of templates using at least the previously stored resource identifier to obtain a template associated with the resource; using a the template associated with the received resource identified by the previously stored resource identifier to identify one or more recognized elements in the resource; embedding data into the resource at the proxy based on the one or more recognized elements; and recognizing the data at the proxy and thereafter providing a navigation option at said client machine based on the data. | 42. A computer implemented method for providing navigation options at a client machine without any additional computer program physically installed on said machine, said method occurring entirely at points removed from said machine, said method comprising: receiving a request for a resource at a proxy; extracting and storing a resource identifier from said request at said proxy; forwarding said request for said resource from said proxy to a location having said resource; receiving the resource at the proxy in response to forwarding the request; thereafter parsing the received resource based on the resource identifier to match the received resource with the previously stored resource identifier, analyzing a plurality of templates using at least the previously stored resource identifier to obtain a template associated with the resource; using a the template associated with the received resource identified by the previously stored resource identifier to identify one or more recognized elements in the resource; embedding data into the resource at the proxy based on the one or more recognized elements; and recognizing the data at the proxy and thereafter providing a navigation option at said client machine based on the data. 46. The computer implemented method of claim 42 wherein said navigation option comprises a pop-up menu having a list of links. | 0.592339 |
1. A non-transitory computer readable memory medium that stores program instructions for analyzing a graphical program, wherein the program instructions are executable by a processor to: display the graphical program on a display, wherein the graphical program comprises a plurality of interconnected nodes that visually indicate functionality of the graphical program; perform a semantic edit operation on the graphical program in response to user input, wherein the semantic edit operation is performed by a first process; perform semantic analysis of the graphical program in response to said performing the semantic edit operation, wherein the semantic analysis is performed by a second process, and wherein the second process is asynchronous with respect to the first process; display results from the semantic analysis of the graphical program in response to completion of the semantic analysis; and perform one or more times: during said performing the semantic analysis, perform another semantic edit operation on the graphical program in response to next user input, wherein the other semantic edit operation is performed by the first process; and in response to said performing the other semantic edit operation, preemptively terminate and re-initiate performing the semantic analysis with respect to the graphical program in the second process; wherein to display results from the semantic analysis of the graphical program in response to completion of the semantic analysis, the program instructions are executable to: display results from the re-initiated semantic analysis of the graphical program in response to completion of the re-initiated semantic analysis. | 1. A non-transitory computer readable memory medium that stores program instructions for analyzing a graphical program, wherein the program instructions are executable by a processor to: display the graphical program on a display, wherein the graphical program comprises a plurality of interconnected nodes that visually indicate functionality of the graphical program; perform a semantic edit operation on the graphical program in response to user input, wherein the semantic edit operation is performed by a first process; perform semantic analysis of the graphical program in response to said performing the semantic edit operation, wherein the semantic analysis is performed by a second process, and wherein the second process is asynchronous with respect to the first process; display results from the semantic analysis of the graphical program in response to completion of the semantic analysis; and perform one or more times: during said performing the semantic analysis, perform another semantic edit operation on the graphical program in response to next user input, wherein the other semantic edit operation is performed by the first process; and in response to said performing the other semantic edit operation, preemptively terminate and re-initiate performing the semantic analysis with respect to the graphical program in the second process; wherein to display results from the semantic analysis of the graphical program in response to completion of the semantic analysis, the program instructions are executable to: display results from the re-initiated semantic analysis of the graphical program in response to completion of the re-initiated semantic analysis. 14. The non-transitory computer readable memory medium of claim 1 , wherein the graphical program comprises a graphical data flow program. | 0.63609 |
2. The computer implemented method of claim 1 , wherein the attachment metadata generator is called responsive to receiving the request from a user modifying the document, and wherein calling the attachment metadata generator further comprises the attachment metadata generator: calling a file type identifier to determine a file type of the attachment; responsive to a determination of a file type, identifying a decoder file, to form an identified decoder file; and determining whether the identified decoder file is obtained. | 2. The computer implemented method of claim 1 , wherein the attachment metadata generator is called responsive to receiving the request from a user modifying the document, and wherein calling the attachment metadata generator further comprises the attachment metadata generator: calling a file type identifier to determine a file type of the attachment; responsive to a determination of a file type, identifying a decoder file, to form an identified decoder file; and determining whether the identified decoder file is obtained. 3. The computer implemented method of claim 2 , wherein the decoder file implements a common application programming interface. | 0.806701 |
40. A method according to claim 39 in which said first pattern storing step comprises storing any one of a signal representative of a nominal paradigm, a signal representative of a verbal paradigm, and a signal indicative of an address of a second linguistic information pattern. | 40. A method according to claim 39 in which said first pattern storing step comprises storing any one of a signal representative of a nominal paradigm, a signal representative of a verbal paradigm, and a signal indicative of an address of a second linguistic information pattern. 42. A method according to claim 40 in which said first pattern storing step comprises storing a signal representative of a nominal suffix pattern. | 0.922161 |
1. A method comprising steps of: receiving one or more criteria that identifies particular nodes within one or more XML documents to exclude from query evaluation; based on the one or more criteria, generating a representation of the one or more XML documents that excludes the particular nodes; receiving a query that specifies a path operation based on a path, wherein one or more of said particular nodes is under said path in the one or more XML documents; and using the representation to compute the path operation as if the one or more of said particular nodes are not in the one or more XML documents; wherein the steps are performed by one or more computing devices. | 1. A method comprising steps of: receiving one or more criteria that identifies particular nodes within one or more XML documents to exclude from query evaluation; based on the one or more criteria, generating a representation of the one or more XML documents that excludes the particular nodes; receiving a query that specifies a path operation based on a path, wherein one or more of said particular nodes is under said path in the one or more XML documents; and using the representation to compute the path operation as if the one or more of said particular nodes are not in the one or more XML documents; wherein the steps are performed by one or more computing devices. 4. The method of claim 1 , wherein generating a representation includes storing the representation in a memory of a database server that is operating on the one or more computing devices. | 0.807771 |
11. A computer-implemented system for accessing data objects in a named data network including a plurality of routers, the system comprising: a first router, wherein: the first router is configured to receive a named data object request identifying a first one of the data objects; the first router is configured to receive at least a portion of a named graph, wherein the named graph comprises data entities and/or structures comprising a plurality of named data objects and identifies associated data objects, wherein the associated data objects include the first data object, wherein the named graph specifies a node corresponding to each of the identified associated data objects, and wherein each node represents a location at one of the routers; the first router is configured to retrieve the first data object; and the first router is configured to retrieve, based at least in part upon the received named graph, at least one additional identified associated data object when the first data object is retrieved, said at least one additional associated data object is identified based on a strength of a relationship with the requested named data object. | 11. A computer-implemented system for accessing data objects in a named data network including a plurality of routers, the system comprising: a first router, wherein: the first router is configured to receive a named data object request identifying a first one of the data objects; the first router is configured to receive at least a portion of a named graph, wherein the named graph comprises data entities and/or structures comprising a plurality of named data objects and identifies associated data objects, wherein the associated data objects include the first data object, wherein the named graph specifies a node corresponding to each of the identified associated data objects, and wherein each node represents a location at one of the routers; the first router is configured to retrieve the first data object; and the first router is configured to retrieve, based at least in part upon the received named graph, at least one additional identified associated data object when the first data object is retrieved, said at least one additional associated data object is identified based on a strength of a relationship with the requested named data object. 12. The computer-implemented system of claim 11 , wherein said strength of the relationship is based on a high probability that by fetching the requested data object, the at least one additional associated data object will be fetched subsequently. | 0.768356 |
11. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: access a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first-user node corresponding to a first user associated with an online social network; and one or more second-user nodes that each correspond to a second user associated with the online social network, each of the second-user nodes being within a threshold degree of separation from the first-user node; receive from the first user a text query comprising one or more character strings; identify one or more of the second-user nodes, each of the identified second-user node corresponding to one or more of the character strings; identify one or more of the edges, each of the identified edges being connected to one of the second-user nodes, and each of the identified edges corresponding to one or more of the character strings; and generate one or more recommended queries that each comprise references to one or more of the identified second-user nodes and one or more of the identified edges. | 11. A system comprising: one or more processors; and a memory coupled to the processors comprising instructions executable by the processors, the processors operable when executing the instructions to: access a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first-user node corresponding to a first user associated with an online social network; and one or more second-user nodes that each correspond to a second user associated with the online social network, each of the second-user nodes being within a threshold degree of separation from the first-user node; receive from the first user a text query comprising one or more character strings; identify one or more of the second-user nodes, each of the identified second-user node corresponding to one or more of the character strings; identify one or more of the edges, each of the identified edges being connected to one of the second-user nodes, and each of the identified edges corresponding to one or more of the character strings; and generate one or more recommended queries that each comprise references to one or more of the identified second-user nodes and one or more of the identified edges. 14. The system of claim 11 , wherein to identify one or more of the second-user nodes comprises, for each character string to: determining for each of the second-user nodes whether the second-user node matches the character string; and identifying each second-user node that matches the character string. | 0.5 |
8. The method as recited in claim 1 , further comprising comparing the first portion of the auditory data to the lexicon to determine if there is a match to a second keyword from the lexicon. | 8. The method as recited in claim 1 , further comprising comparing the first portion of the auditory data to the lexicon to determine if there is a match to a second keyword from the lexicon. 9. The method as recited in claim 8 , wherein archiving includes associating the auditory data with the video data. | 0.903996 |
17. A computer program product including instructions, stored on a non-transitory computer-readable storage medium, that when executed by one or more computers, cause the one or more computers to perform operations comprising: maintaining a collection of uniform resource locator (URL) patterns, wherein each URL pattern is associated with a respective label; receiving a search query that includes a query term and a label of interest from a client device; generating, for the label of interest, a domain filter that satisfies a maximum size threshold and a maximum false positive error rate threshold, wherein generating the domain filter includes: iteratively adjusting a size of the domain filter, wherein in each iteration, the method comprises: identifying a new set of one or more URL patterns as a current set of offsets, wherein each of the one or more URL patterns is associated with a respective label that matches the label of interest; processing the URL patterns in the collection of URL patterns to generate an offset error for the current set of offsets; and determining whether or not the offset error for the current set of offsets is greater than an offset error for a best set of offsets, (i) and if so, performing a next iteration unless no new set of one or more URL patterns is identifiable, (ii) and otherwise, determining whether or not a current size of the domain filter satisfies the maximum size threshold and a current error rate for the domain filter satisfies the maximum false positive error rate threshold, (a) and if so, replacing values of the best set of offsets with values of the current set of offsets and performing the next iteration unless no new set of one or more URL patterns is identifiable, (b) and otherwise, performing the next iteration unless no new set of one or more URL patterns is identifiable; and upon determining that no new set of one or more URL patterns is identifiable, generating the domain filter for the label of interest using values of the best set of offsets; and filtering search results that are relevant to the query term with the domain filter to generate a plurality of filtered search results. | 17. A computer program product including instructions, stored on a non-transitory computer-readable storage medium, that when executed by one or more computers, cause the one or more computers to perform operations comprising: maintaining a collection of uniform resource locator (URL) patterns, wherein each URL pattern is associated with a respective label; receiving a search query that includes a query term and a label of interest from a client device; generating, for the label of interest, a domain filter that satisfies a maximum size threshold and a maximum false positive error rate threshold, wherein generating the domain filter includes: iteratively adjusting a size of the domain filter, wherein in each iteration, the method comprises: identifying a new set of one or more URL patterns as a current set of offsets, wherein each of the one or more URL patterns is associated with a respective label that matches the label of interest; processing the URL patterns in the collection of URL patterns to generate an offset error for the current set of offsets; and determining whether or not the offset error for the current set of offsets is greater than an offset error for a best set of offsets, (i) and if so, performing a next iteration unless no new set of one or more URL patterns is identifiable, (ii) and otherwise, determining whether or not a current size of the domain filter satisfies the maximum size threshold and a current error rate for the domain filter satisfies the maximum false positive error rate threshold, (a) and if so, replacing values of the best set of offsets with values of the current set of offsets and performing the next iteration unless no new set of one or more URL patterns is identifiable, (b) and otherwise, performing the next iteration unless no new set of one or more URL patterns is identifiable; and upon determining that no new set of one or more URL patterns is identifiable, generating the domain filter for the label of interest using values of the best set of offsets; and filtering search results that are relevant to the query term with the domain filter to generate a plurality of filtered search results. 22. The product of claim 17 , wherein the operations further comprise: generating count information for the collection of URL patterns, wherein the count information includes a respective count of a number of URL patterns in the collection of URL patterns having each distinct URL pattern length. | 0.540594 |
1. A method of generating procedural language code for extracting data from an operational system, the method comprising: accepting a declarative specification; and generating procedural language code from the declarative specification to execute a data extraction, transformation and loading process defined by the declarative specification. | 1. A method of generating procedural language code for extracting data from an operational system, the method comprising: accepting a declarative specification; and generating procedural language code from the declarative specification to execute a data extraction, transformation and loading process defined by the declarative specification. 5. The method of claim 1 , wherein the declarative specification includes at least one of a scalar function, a vector function, parameterized declarative extraction specifications, custom ABAP code or a lookup operation. | 0.668091 |
11. The article of manufacture of claim 10 , wherein the one or more programs which when executed further implement the steps of: d) querying the user for textual annotations for the predictions; e) using the annotations to identify additional covariates to create an extended set of covariates; and f) using the extended set of covariates to improve the accuracy of the statistical model. | 11. The article of manufacture of claim 10 , wherein the one or more programs which when executed further implement the steps of: d) querying the user for textual annotations for the predictions; e) using the annotations to identify additional covariates to create an extended set of covariates; and f) using the extended set of covariates to improve the accuracy of the statistical model. 13. The article of manufacture of claim 11 , wherein the textual annotations comprise tags. | 0.84095 |
13. The apparatus of claim 11 , wherein the at least one memory is also configured to store information defining the selected second widget independently of the information defining the placeholder widget. | 13. The apparatus of claim 11 , wherein the at least one memory is also configured to store information defining the selected second widget independently of the information defining the placeholder widget. 14. The apparatus of claim 13 , wherein the at least one processor is configured to transform the instance of the placeholder widget into the instance of the selected second widget further by: inserting the instance of the selected second widget into the prototype GUI in place of the instance of the placeholder widget, wherein a layout of the prototype GUI remains unchanged. | 0.821887 |
20. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more first processors of a device, cause the one or more first processors to: access a first response file generated during a first execution of a first recording of a base script on a system that includes at least one second processor and at least one memory and a second response file generated during a second execution of a second recording of the base script on the system, the base script defining operations to be executed in testing performance of the system; determine first dynamic value data that describes one or more first dynamic values stored in the first response file and second dynamic value data that describes one or more second dynamic values stored in the second response file; analyze the first dynamic value data and the second dynamic value data to identify candidate parameters for correlation within the base script; generate a correlated script using the identified candidate parameters and the base script; and store the correlated script. | 20. A non-transitory computer-readable medium storing instructions, the instructions comprising: one or more instructions that, when executed by one or more first processors of a device, cause the one or more first processors to: access a first response file generated during a first execution of a first recording of a base script on a system that includes at least one second processor and at least one memory and a second response file generated during a second execution of a second recording of the base script on the system, the base script defining operations to be executed in testing performance of the system; determine first dynamic value data that describes one or more first dynamic values stored in the first response file and second dynamic value data that describes one or more second dynamic values stored in the second response file; analyze the first dynamic value data and the second dynamic value data to identify candidate parameters for correlation within the base script; generate a correlated script using the identified candidate parameters and the base script; and store the correlated script. 21. The computer-readable medium of claim 20 , further comprising: causing the system to execute the first recording of the base script to generate the first response file; causing the system to execute the second recording of the base script again to generate the second response file; and storing a dynamic value list that comprises the first dynamic value data and the second dynamic value data. | 0.546645 |
1. A computer implemented method of generating a dynamic three dimensional (3D) scene defined in a markup language document, comprising: receiving, through a computer, a markup language document defining a 3D scene, the markup language document comprising markup language commands that import 3D model data representing a 3D model in a non-markup language data format and manipulate objects associated with the 3D model data by invoking one or more behaviors associated with the object; creating the objects in memory from the 3D model data; manipulating one or more of the objects according to the markup language commands to present through a display interface the 3D model with dynamic behavior in the 3D scene, and manipulating one or more of the objects according to one or more non-3d data quantitative values received from a remote data source to present through the display interface the 3D model with dynamic behavior in the 3D scene. | 1. A computer implemented method of generating a dynamic three dimensional (3D) scene defined in a markup language document, comprising: receiving, through a computer, a markup language document defining a 3D scene, the markup language document comprising markup language commands that import 3D model data representing a 3D model in a non-markup language data format and manipulate objects associated with the 3D model data by invoking one or more behaviors associated with the object; creating the objects in memory from the 3D model data; manipulating one or more of the objects according to the markup language commands to present through a display interface the 3D model with dynamic behavior in the 3D scene, and manipulating one or more of the objects according to one or more non-3d data quantitative values received from a remote data source to present through the display interface the 3D model with dynamic behavior in the 3D scene. 6. The method of claim 1 , wherein the markup language commands are different from commands defined in the non-markup language data format. | 0.664875 |
9. The method of claim 8 , wherein the first value represents a size of a smallest bounding box that encompasses the first and second primitive graphic elements. | 9. The method of claim 8 , wherein the first value represents a size of a smallest bounding box that encompasses the first and second primitive graphic elements. 10. The method of claim 9 , wherein the size of the smallest bounding box is calculated as a sum of a width and height of the bounding box divided by a sum of a width and height of a page containing the primitive graphic elements. | 0.93125 |
32. The system according to claim 1 , further comprising an extension and modification facility that allows users and content developers to configure behavior of the agent architecture. | 32. The system according to claim 1 , further comprising an extension and modification facility that allows users and content developers to configure behavior of the agent architecture. 33. The system according to claim 32 , wherein the extension and modification facility can be used to extend or modify behavior of the plurality of domain agents. | 0.90084 |
1. A system comprising: a search engine structured to search metadata in each webpage of a plurality of webpages within a collaborative website based on at least one search term input into the search engine, wherein the collaborative website is a wiki and the metadata comprises a plurality of words that represent each webpage; a score weighing component configured to: determine a parsing relevance factor for each said webpage based on a number of occurrences in the metadata for one or more words of the plurality of words, wherein the one or more words are associated with the plurality of webpages and are related to the at least one search term entered into the search engine; score each said webpage based on importance or popularity of each said webpage to the collaborative website community; and determine an aggregate score for the at least one search term based on the score and the parsing relevance factor; a tag cloud generator configured to produce a tag cloud based on results of the search engine and the aggregate score, wherein the tag cloud includes the one or more words of the plurality of words associated with the plurality of webpages with one or more documents and that are related to the at least one search term entered into the search engine; and at least one computing device comprising a processor that executes the search engine and the tag cloud generator, wherein a list of webpages relevant to the at least one search term are displayed simultaneously with the tag cloud in a graphical user interface. | 1. A system comprising: a search engine structured to search metadata in each webpage of a plurality of webpages within a collaborative website based on at least one search term input into the search engine, wherein the collaborative website is a wiki and the metadata comprises a plurality of words that represent each webpage; a score weighing component configured to: determine a parsing relevance factor for each said webpage based on a number of occurrences in the metadata for one or more words of the plurality of words, wherein the one or more words are associated with the plurality of webpages and are related to the at least one search term entered into the search engine; score each said webpage based on importance or popularity of each said webpage to the collaborative website community; and determine an aggregate score for the at least one search term based on the score and the parsing relevance factor; a tag cloud generator configured to produce a tag cloud based on results of the search engine and the aggregate score, wherein the tag cloud includes the one or more words of the plurality of words associated with the plurality of webpages with one or more documents and that are related to the at least one search term entered into the search engine; and at least one computing device comprising a processor that executes the search engine and the tag cloud generator, wherein a list of webpages relevant to the at least one search term are displayed simultaneously with the tag cloud in a graphical user interface. 4. The system of claim 1 , wherein the one or more words in the tag cloud are hyperlinks. | 0.960282 |
1. A method to adjust an automatic speech recognition (ASR) engine, comprising: receiving, by a social media gateway of a contact center, social network information from a social network; modifying, by the social media gateway of the contact center, the social network information, wherein the modifying comprises filtering the social network information and redacting the filtered social network information based on a relevancy of the social network information to the ASR engine; data mining, by a dialog engine of the contact center, the modified social network information to extract one or more characteristics; inferring, by the dialog engine of the contact center, a trend from the extracted one or more characteristics; adding, by the dialog engine of the contact center, one or more words or phrases related to the trend to a recognition grammar of the ASR engine; calculating, by the dialog engine of the contact center, a magnitude of adjustment to weights of the added one or more words or phrases in the recognition grammar of the ASR engine based upon a shaped sliding window, and adjusting, by the dialog engine of the contact center, the ASR engine by adjusting a speech recognition weighting of the ASR engine based upon the calculated magnitude of adjustment, wherein the adjustment to the speech recognition weighting of the ASR engine has a limited duration. | 1. A method to adjust an automatic speech recognition (ASR) engine, comprising: receiving, by a social media gateway of a contact center, social network information from a social network; modifying, by the social media gateway of the contact center, the social network information, wherein the modifying comprises filtering the social network information and redacting the filtered social network information based on a relevancy of the social network information to the ASR engine; data mining, by a dialog engine of the contact center, the modified social network information to extract one or more characteristics; inferring, by the dialog engine of the contact center, a trend from the extracted one or more characteristics; adding, by the dialog engine of the contact center, one or more words or phrases related to the trend to a recognition grammar of the ASR engine; calculating, by the dialog engine of the contact center, a magnitude of adjustment to weights of the added one or more words or phrases in the recognition grammar of the ASR engine based upon a shaped sliding window, and adjusting, by the dialog engine of the contact center, the ASR engine by adjusting a speech recognition weighting of the ASR engine based upon the calculated magnitude of adjustment, wherein the adjustment to the speech recognition weighting of the ASR engine has a limited duration. 6. The method of claim 1 , wherein adjusting the ASR engine comprises adjusting the recognition grammar used by the ASR engine. | 0.590992 |
1. A computer-implemented method, comprising: receiving a request for a plurality of data items, the request specifying a search condition; searching a data store comprising a plurality of data objects representing data items for data items satisfying the search condition, the plurality of data objects comprising one or more media objects, one or more tag objects and one or more page objects, where: a media object represents an item of digital media and is an instantiation of a media object class; a tag object represents a category of digital media and is an instantiation of a tag object class and each media object can be associated with zero or more tag objects; and a page object defines a relationship between a tag object and a media object; generating a collection of data objects representing data items that satisfy the search condition; using an iterator to sequentially access the data items represented by the data objects in the collection; and providing the data items to a user interface. | 1. A computer-implemented method, comprising: receiving a request for a plurality of data items, the request specifying a search condition; searching a data store comprising a plurality of data objects representing data items for data items satisfying the search condition, the plurality of data objects comprising one or more media objects, one or more tag objects and one or more page objects, where: a media object represents an item of digital media and is an instantiation of a media object class; a tag object represents a category of digital media and is an instantiation of a tag object class and each media object can be associated with zero or more tag objects; and a page object defines a relationship between a tag object and a media object; generating a collection of data objects representing data items that satisfy the search condition; using an iterator to sequentially access the data items represented by the data objects in the collection; and providing the data items to a user interface. 4. The method of claim 1 , wherein: the search condition specifies one or more digital media items including one or more of a digital image, video stream, audio stream or text document; and generating the collection of data objects comprises identifying one or more categories of digital media associated with the specified digital media items, where the collection of data objects comprises tag objects representing the identified digital media categories. | 0.577546 |
16. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause a computing device to: receive an indication of a gesture, the gesture being entered by a user at a first location of a touchscreen operatively coupled to the computing device; determine a context of the gesture, based at least in part on type of gesture and the type of information that is displayed proximate the first location of the touchscreen when the gesture is entered; determine whether the gesture includes a two-finger double-tap gesture; responsive to determining that the received gesture includes the two-finger double-tap gesture, execute an application predetermined by the user to perform an action associated with the context; and responsive to determining that the gesture does not include the two-finger double-tap gesture output, for display, a prompt indicating a plurality of applications for the user to select an application from to perform an action associated with the context of the gesture, wherein the application that is predetermined by the user and each of the plurality of applications indicated by the prompt is a computer program that is executable by the computing device to perform the respective action. | 16. A non-transitory computer-readable medium storing instructions that, when executed by one or more processors, cause a computing device to: receive an indication of a gesture, the gesture being entered by a user at a first location of a touchscreen operatively coupled to the computing device; determine a context of the gesture, based at least in part on type of gesture and the type of information that is displayed proximate the first location of the touchscreen when the gesture is entered; determine whether the gesture includes a two-finger double-tap gesture; responsive to determining that the received gesture includes the two-finger double-tap gesture, execute an application predetermined by the user to perform an action associated with the context; and responsive to determining that the gesture does not include the two-finger double-tap gesture output, for display, a prompt indicating a plurality of applications for the user to select an application from to perform an action associated with the context of the gesture, wherein the application that is predetermined by the user and each of the plurality of applications indicated by the prompt is a computer program that is executable by the computing device to perform the respective action. 17. The computer-readable medium of claim 16 , wherein the context is further determined based on information stored in a memory of the computing device when the gesture is received. | 0.620743 |
11. A method comprising: crawling and indexing voice sites and storing results in a voice site index, wherein each voice site comprises a voice driven application that includes one or more voice pages hosted on servers or computers in a telecom infrastructure; receiving a search request in voice from a user via a telephone; performing speech recognition on the voice search request and converting the request from voice to text; parsing the text search request; performing, in response to the parsed search request, a search on the voice site index and ranking the search results; filtering search results based on at least one of location, emotion and context; and presenting the filtered search results to the user in categories to enable easy voice browsing of the search results by the user. | 11. A method comprising: crawling and indexing voice sites and storing results in a voice site index, wherein each voice site comprises a voice driven application that includes one or more voice pages hosted on servers or computers in a telecom infrastructure; receiving a search request in voice from a user via a telephone; performing speech recognition on the voice search request and converting the request from voice to text; parsing the text search request; performing, in response to the parsed search request, a search on the voice site index and ranking the search results; filtering search results based on at least one of location, emotion and context; and presenting the filtered search results to the user in categories to enable easy voice browsing of the search results by the user. 14. A method in accordance with claim 11 , wherein the crawling comprises extracting text prompts from voice sites. | 0.618259 |
33. The system of claim 32 , wherein the user-context attributes module for identifying the plurality of user-context attributes is adapted to generate a term measure based on at least a first frequency that the extracted term occurs in at least one of the one or more words and an index of content. | 33. The system of claim 32 , wherein the user-context attributes module for identifying the plurality of user-context attributes is adapted to generate a term measure based on at least a first frequency that the extracted term occurs in at least one of the one or more words and an index of content. 34. The system of claim 33 , wherein the search query module for generating a plurality of implicit search queries comprising terms is further executable to generate a plurality of implicit search queries comprising terms selected responsive at least in part to the term measure. | 0.869925 |
1. A method, in a configuration system, for enabling users to create and use a collection of template rules to generate custom product-configuration rules, the method comprising: enabling a user to submit one or more example rules for a rule pattern; in response to a user submitting one or more example rules for a rule pattern, identifying any variables in the example rules; enabling a user to select which of the identified variables will be customizable in instances of the rule pattern; creating the rule pattern from the submitted example rules, wherein, for each submitted example rule, the rule pattern includes a corresponding template rule and wherein the selected variables are customizable fields in the template rules; adding the rule pattern to a rule pattern library, wherein a user is able to select the rule pattern as a basis for creating custom configuration rules for a product; in response to a user selecting the rule pattern from the library, generating a user interface in which the customizable fields for each template rule in the rule pattern are displayed and a user is able to enter values for the customizable fields; and generating configuration rules for a product from the template rules and the values entered by the user for the customizable fields. | 1. A method, in a configuration system, for enabling users to create and use a collection of template rules to generate custom product-configuration rules, the method comprising: enabling a user to submit one or more example rules for a rule pattern; in response to a user submitting one or more example rules for a rule pattern, identifying any variables in the example rules; enabling a user to select which of the identified variables will be customizable in instances of the rule pattern; creating the rule pattern from the submitted example rules, wherein, for each submitted example rule, the rule pattern includes a corresponding template rule and wherein the selected variables are customizable fields in the template rules; adding the rule pattern to a rule pattern library, wherein a user is able to select the rule pattern as a basis for creating custom configuration rules for a product; in response to a user selecting the rule pattern from the library, generating a user interface in which the customizable fields for each template rule in the rule pattern are displayed and a user is able to enter values for the customizable fields; and generating configuration rules for a product from the template rules and the values entered by the user for the customizable fields. 8. The method of claim 1 , further comprising generating constraints from the generated configuration rules. | 0.915635 |
15. A computer-readable storage device encoded with a computer program, the computer program comprising computer executable instructions configured for: associating an image descriptor, of the GUI widget, with a content of an active field in the text field, wherein the image descriptor of the GUI widget and the content of the active field in the text field are substantially similar, and wherein the GUI widget and the text field are both displayed on a GUI; and in response to the image descriptor of the GUI widget changing, automatically modifying the content of the active field in the text field and changing an appearance of the GUI widget to represent the changed image descriptor of the GUI widget. | 15. A computer-readable storage device encoded with a computer program, the computer program comprising computer executable instructions configured for: associating an image descriptor, of the GUI widget, with a content of an active field in the text field, wherein the image descriptor of the GUI widget and the content of the active field in the text field are substantially similar, and wherein the GUI widget and the text field are both displayed on a GUI; and in response to the image descriptor of the GUI widget changing, automatically modifying the content of the active field in the text field and changing an appearance of the GUI widget to represent the changed image descriptor of the GUI widget. 16. The computer-readable storage device of claim 15 , wherein the computer executable instructions are configured such that changing the content of the active field in the text field results in a change to an appearance of the GUI widget from a first shape to a second shape. | 0.595708 |
26. The system of claim 25 , wherein the processor is further configured to restore the colors of the second paragraph of the source document to the generated document using the second pair of replacement colors as indices into the stored list of colors. | 26. The system of claim 25 , wherein the processor is further configured to restore the colors of the second paragraph of the source document to the generated document using the second pair of replacement colors as indices into the stored list of colors. 27. The system of claim 26 , wherein the processor is further configured to create a tag corresponding to the second paragraph of the generated document. | 0.914706 |
1. A method for automatically adding process nodes to print production workflows by inferring knowledge from asset metadata tags and using said knowledge during process network generation, comprising: providing a print product description; extracting asset metadata from a plurality of resources associated with said print product description; processing said asset metadata through an automated reasoning system in order to infer relevant information from said asset metadata to form inferred metadata; and utilizing said inferred metadata to add and parameterize a process node to a process network. | 1. A method for automatically adding process nodes to print production workflows by inferring knowledge from asset metadata tags and using said knowledge during process network generation, comprising: providing a print product description; extracting asset metadata from a plurality of resources associated with said print product description; processing said asset metadata through an automated reasoning system in order to infer relevant information from said asset metadata to form inferred metadata; and utilizing said inferred metadata to add and parameterize a process node to a process network. 4. The method of claim 1 wherein said automated reasoning system further comprises ontology-based reasoning. | 0.635553 |
9. The method of claim 1 wherein determining the at least one weighted discrepancy parameter includes determining a first plurality of business rules that are relevant to the transaction and determining a fraud metric for each of the first plurality of business rules based on the set of transactions, and determining the at least one action parameter includes selecting one of the first plurality of business rules based on the fraud metric of each rule and defining the at least one action parameter based on the business rule selected. | 9. The method of claim 1 wherein determining the at least one weighted discrepancy parameter includes determining a first plurality of business rules that are relevant to the transaction and determining a fraud metric for each of the first plurality of business rules based on the set of transactions, and determining the at least one action parameter includes selecting one of the first plurality of business rules based on the fraud metric of each rule and defining the at least one action parameter based on the business rule selected. 13. The method of claim 9 wherein determining the at least one weighted discrepancy parameter includes determining a fare category violated based on the application of a business rule to the set of transactions. | 0.837243 |
4. The computer-implemented method of claim 1 , wherein the first pose that is identified by the mobile computing device comprises a telephone pose that indicates that the mobile computing device is being held up to the user's ear. | 4. The computer-implemented method of claim 1 , wherein the first pose that is identified by the mobile computing device comprises a telephone pose that indicates that the mobile computing device is being held up to the user's ear. 6. The computer-implemented method of claim 4 , wherein the second pose that is identified by the mobile computing device comprises a personal digital assistant (PDA) pose that indicates that the mobile computing device is being held at least a threshold distance away from the user's body. | 0.95059 |
15. A computer-readable storage medium that is not a transient signal, the computer-readable medium comprising executable instructions, which when executed by a processor, cause the processor to perform operations comprising: receiving a telephonic communication comprising speech transcribing the telephonic communication to generate a transcript; detecting a tone generated by a telephone within the telephonic communication; and responsive to detecting the tone, supplementing the transcript with additional information. | 15. A computer-readable storage medium that is not a transient signal, the computer-readable medium comprising executable instructions, which when executed by a processor, cause the processor to perform operations comprising: receiving a telephonic communication comprising speech transcribing the telephonic communication to generate a transcript; detecting a tone generated by a telephone within the telephonic communication; and responsive to detecting the tone, supplementing the transcript with additional information. 17. The computer-readable storage medium of claim 15 , wherein the operation of supplementing the transcript with additional information comprises supplementing a portion of the transcript associated with a predetermined amount of time with the additional information. | 0.5 |
3. A computer-implemented method comprising: receiving a backup request; constructing a command to extract data of some but not all rows in a database table using information from a parameter file, wherein the parameter file comprises a list of tables entered via a command line user interface to restrict data that is selected for export; executing the command; in response to executing the command, receiving the data of some but not all rows in the table; translating the data into a markup language version; and transmitting the markup language version to at least one of a backup and restore module or an archive file. | 3. A computer-implemented method comprising: receiving a backup request; constructing a command to extract data of some but not all rows in a database table using information from a parameter file, wherein the parameter file comprises a list of tables entered via a command line user interface to restrict data that is selected for export; executing the command; in response to executing the command, receiving the data of some but not all rows in the table; translating the data into a markup language version; and transmitting the markup language version to at least one of a backup and restore module or an archive file. 5. The method of claim 3 wherein: the parameter file comprises at least one parameter for identifying the some but not all rows of the table. | 0.806011 |
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