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19. The system as described in claim 17 , wherein the predicting means includes means for forming a plurality of cropped portions of the image and processing each of the plurality of cropped portions of the image by a trained convolutional network of the model independently, one to another.
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19. The system as described in claim 17 , wherein the predicting means includes means for forming a plurality of cropped portions of the image and processing each of the plurality of cropped portions of the image by a trained convolutional network of the model independently, one to another. 20. The system as described in claim 19 , wherein the predicting means further comprising means for generating the predicted bounding box based on a result of the processing of each of the plurality of cropped portions of the image.
| 0.840434 |
10. The apparatus of claim 1 further comprising a rod pusher separately attachable to the first tool portion, the rod pusher having a sleeve and a driving end, the sleeve receivable over the first tool portion elongate body and operably attachable to the elongate body for rotating thereabout, with the rotational movement of the sleeve also translating the driving end along the elongate body.
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10. The apparatus of claim 1 further comprising a rod pusher separately attachable to the first tool portion, the rod pusher having a sleeve and a driving end, the sleeve receivable over the first tool portion elongate body and operably attachable to the elongate body for rotating thereabout, with the rotational movement of the sleeve also translating the driving end along the elongate body. 11. The apparatus of claim 10 wherein the first tool portion has an outer guide and advancement structure and the rod pusher has an inner guide and advancement structure mateable to the outer guide and advancement structure.
| 0.909941 |
4. A computer interface, comprising: a computer hosting resources for access by a user; a user input device; memory; a simulated digital life form stored in the memory and having a plurality of attributes, including at least one attribute indicative of the vitality of the digital life form; code stored in the memory and operative to provide a plurality of actions which may be accomplished by the digital life form; and a selection criteria for selecting from said plurality of actions, said selection criteria being stored in the memory; wherein repeated selection of actions which do not contribute to the vitality of the digital life form will result in the simulated death of the digital life form, and said digital life form perceives a plurality of objects in an environment including input from the user input device; said objects are identified by the digital life form by comparing percepts previously formed and stored in the memory by the digital life form with present percepts of said objects; the percepts are perceived properties of the objects by the digital life form; and said actions are selected primarily to optimize vitality dependant upon the particular objects perceived so as to benefit the digital life form wherein benefit is defined as serving the needs of the digital life form by keeping it alive, and said actions are selected secondarily to respond to the input from the user input device.
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4. A computer interface, comprising: a computer hosting resources for access by a user; a user input device; memory; a simulated digital life form stored in the memory and having a plurality of attributes, including at least one attribute indicative of the vitality of the digital life form; code stored in the memory and operative to provide a plurality of actions which may be accomplished by the digital life form; and a selection criteria for selecting from said plurality of actions, said selection criteria being stored in the memory; wherein repeated selection of actions which do not contribute to the vitality of the digital life form will result in the simulated death of the digital life form, and said digital life form perceives a plurality of objects in an environment including input from the user input device; said objects are identified by the digital life form by comparing percepts previously formed and stored in the memory by the digital life form with present percepts of said objects; the percepts are perceived properties of the objects by the digital life form; and said actions are selected primarily to optimize vitality dependant upon the particular objects perceived so as to benefit the digital life form wherein benefit is defined as serving the needs of the digital life form by keeping it alive, and said actions are selected secondarily to respond to the input from the user input device. 5. The computer interface of claim 4 , wherein: some of said attributes function as simulated feelings that serve as warning indicators for the effect of certain actions on the vitality of the digital life form; and said actions are taken to optimize at least one of a plurality of simulated feelings.
| 0.5 |
1. An apparatus for accessing and managing a relational database, said apparatus comprising: a processor; an arrangement for querying a relational database; and an arrangement for accessing semantically relevant query results from the relational database, said accessing arrangement configured to: access at least one ontology; extract domain knowledge from at least one ontology; and employ the domain knowledge in obtaining the semantically relevant query results from the relational database; wherein said semantically relevant query results comprise direct results obtained directly from relational database tables, inferred results inferred utilizing information explicitly listed in the relational database and the at least one ontology, and related results obtained utilizing data in the relational database tables and one or more definitions of similarity of concepts and individuals based on the at least one ontology; and wherein said accessing arrangement acts to: apply a query generalization strategy, the query generalization strategy comprising applying strategies to an original query to obtain a generalized level of queries comprising one or more general queries and repeatedly applying the strategies to the generalized level of queries until a prespecified number of results is obtained; and rank results obtained through the query generalization strategy based on a number generalizations performed.
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1. An apparatus for accessing and managing a relational database, said apparatus comprising: a processor; an arrangement for querying a relational database; and an arrangement for accessing semantically relevant query results from the relational database, said accessing arrangement configured to: access at least one ontology; extract domain knowledge from at least one ontology; and employ the domain knowledge in obtaining the semantically relevant query results from the relational database; wherein said semantically relevant query results comprise direct results obtained directly from relational database tables, inferred results inferred utilizing information explicitly listed in the relational database and the at least one ontology, and related results obtained utilizing data in the relational database tables and one or more definitions of similarity of concepts and individuals based on the at least one ontology; and wherein said accessing arrangement acts to: apply a query generalization strategy, the query generalization strategy comprising applying strategies to an original query to obtain a generalized level of queries comprising one or more general queries and repeatedly applying the strategies to the generalized level of queries until a prespecified number of results is obtained; and rank results obtained through the query generalization strategy based on a number generalizations performed. 7. The apparatus according to claim 1 , wherein said accessing arrangement comprises a description logic reasoner configured to obtain the inferred results based on domain knowledge in the at least one ontology and data listed in the relational database, the description logic reasoner allowing for inferring query results not explicitly stated in the relational database.
| 0.543514 |
15. The machine-readable medium of claim 14 wherein the query state assigned to a particular query for a particular time period is a normal query state or a deviated query state.
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15. The machine-readable medium of claim 14 wherein the query state assigned to a particular query for a particular time period is a normal query state or a deviated query state. 16. The machine-readable medium of claim 15 wherein the assigning is based on a particular query rate of the rate of the plurality of queries for the particular time period, the cost of the normal-to-deviated query state transition, and the deviated-to-normal query state transition.
| 0.810675 |
14. A system for formatting a medical transcription obtained from performing automatic speech recognition on a medical dictation, the system comprising: at least one storage device including a data set that stores a plurality of fields, each of the plurality of fields defining data of a particular type and each of the plurality of fields belonging to one or more sets of a plurality of sets, each set of the plurality of sets associated with a respective category type of medical transcription; at least one computer to receive the medical transcription and a work type code identifying a category type of the medical transcription, the at least one computer capable of accessing the database to select a first set from the plurality of sets based, at least in part, on the worktype code, the first set having a plurality of fields indicating a format for the medical transcription, the at least one computer programmed to implement: a natural language processing module configured to automatically analyze the medical transcription to identify at least one indicating phrase associated with at least one of the plurality of fields and to determine whether text disposed proximately to the at least one indicating phrase is of the particular type corresponding to the at least one of the plurality of fields, the natural language processing module adapted to format the document by associating the text disposed proximately to the at least one indicating phrase with the at least one of the plurality of fields if the text is of the particular type corresponding to the at least one of the plurality of fields such that, when the medical transcription is displayed, the text is displayed as data in the corresponding at least one of the plurality of fields.
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14. A system for formatting a medical transcription obtained from performing automatic speech recognition on a medical dictation, the system comprising: at least one storage device including a data set that stores a plurality of fields, each of the plurality of fields defining data of a particular type and each of the plurality of fields belonging to one or more sets of a plurality of sets, each set of the plurality of sets associated with a respective category type of medical transcription; at least one computer to receive the medical transcription and a work type code identifying a category type of the medical transcription, the at least one computer capable of accessing the database to select a first set from the plurality of sets based, at least in part, on the worktype code, the first set having a plurality of fields indicating a format for the medical transcription, the at least one computer programmed to implement: a natural language processing module configured to automatically analyze the medical transcription to identify at least one indicating phrase associated with at least one of the plurality of fields and to determine whether text disposed proximately to the at least one indicating phrase is of the particular type corresponding to the at least one of the plurality of fields, the natural language processing module adapted to format the document by associating the text disposed proximately to the at least one indicating phrase with the at least one of the plurality of fields if the text is of the particular type corresponding to the at least one of the plurality of fields such that, when the medical transcription is displayed, the text is displayed as data in the corresponding at least one of the plurality of fields. 20. The system of claim 14 , wherein at least a portion of the transcription is normalized and the at least one indicating phrase comprises a normalized language phrase.
| 0.588608 |
33. A computer implemented method for developing a classifier for classifying electronic communications comprising: (a) defining a domain of electronic communications on which a classifier is to operate, wherein the electronic communications are user-generated; (b) collecting a set of electronic communications from the domain; (c) eliciting labeling criteria from a user by querying a user to identify a phrase that indicates that a communication is not related to a concept and receiving the phrase; (d) labeling, by the system, electronic communications from the set of electronic communications according, at least in part, to the labeling criteria elicited from the user; (e) labeling, by the user, electronic communications from the set of electronic communications; (f) building the electronic communications classifier according to a combination of labels applied to electronic communications in (d) and (e); (g) deploying the classifier for use in classifying electronic communications based upon the combination of labels; and (h) storing a labeled set of electronic communications labeled by the classifier in a memory.
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33. A computer implemented method for developing a classifier for classifying electronic communications comprising: (a) defining a domain of electronic communications on which a classifier is to operate, wherein the electronic communications are user-generated; (b) collecting a set of electronic communications from the domain; (c) eliciting labeling criteria from a user by querying a user to identify a phrase that indicates that a communication is not related to a concept and receiving the phrase; (d) labeling, by the system, electronic communications from the set of electronic communications according, at least in part, to the labeling criteria elicited from the user; (e) labeling, by the user, electronic communications from the set of electronic communications; (f) building the electronic communications classifier according to a combination of labels applied to electronic communications in (d) and (e); (g) deploying the classifier for use in classifying electronic communications based upon the combination of labels; and (h) storing a labeled set of electronic communications labeled by the classifier in a memory. 43. The computer implemented method of claim 33 , wherein the eliciting (c) involves an interactive session with the user.
| 0.739051 |
6. A computer-implemented method of assessing a subjective answer, the method performed by one or more hardware processors, comprising: receiving first data representative of a domain associated with a question; receiving second data representative of an answer in an essay form to the question, the second data comprising a plurality of statements that make up the answer in the essay form; searching a database of sources to retrieve information associated with the domain; determining whether a statement is accurate or inaccurate, for each of the plurality of statements based on matching the statement with the information associated with the domain according to an accuracy threshold; determining an overall score for the answer based on a number of statements in the answer in the essay form determined to be accurate, a number of statements in the answer in the essay form determined to be inaccurate, a number of duplicate statements in the answer in the essay form relative to a total number of statements in the answer; generating visual graphics representing accurate and inaccurate statements and the overall score; displaying the visual graphics on a display device; searching a database of answers to the question to identify a plurality of comparative statements comprising answers provided by a plurality of individuals in answering the question; matching the statement with the plurality of comparative statements to determine whether the statement is accurate or inaccurate, the comparative statements identified from an essay-type of answers given by the plurality of individuals responsive to the question.
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6. A computer-implemented method of assessing a subjective answer, the method performed by one or more hardware processors, comprising: receiving first data representative of a domain associated with a question; receiving second data representative of an answer in an essay form to the question, the second data comprising a plurality of statements that make up the answer in the essay form; searching a database of sources to retrieve information associated with the domain; determining whether a statement is accurate or inaccurate, for each of the plurality of statements based on matching the statement with the information associated with the domain according to an accuracy threshold; determining an overall score for the answer based on a number of statements in the answer in the essay form determined to be accurate, a number of statements in the answer in the essay form determined to be inaccurate, a number of duplicate statements in the answer in the essay form relative to a total number of statements in the answer; generating visual graphics representing accurate and inaccurate statements and the overall score; displaying the visual graphics on a display device; searching a database of answers to the question to identify a plurality of comparative statements comprising answers provided by a plurality of individuals in answering the question; matching the statement with the plurality of comparative statements to determine whether the statement is accurate or inaccurate, the comparative statements identified from an essay-type of answers given by the plurality of individuals responsive to the question. 10. The method of claim 6 , further comprising performing a computer-implemented natural language technique that classifies the question and determines the domain.
| 0.665369 |
18. An article of manufacture including a non-transitory computer-readable storage medium having stored thereon program instructions that, upon execution by a computing device, cause the computing device to perform operations comprising: receiving training samples for training a neural network to learn an acoustic speech model, wherein at least one training sample of the training samples represents at least one phone of captured speech; determining a curriculum function for acoustic speech modeling, wherein the curriculum function assigns a difficulty value for a designated training sample of the training samples based on a combination comprising a duration value for the designated training sample and a sound quality value for the designated training sample; for each training sample of the training samples, determining a corresponding difficulty value for the training sample using the curriculum function; ordering the training samples based on the corresponding difficulty values for the training samples; presented presenting the ordered training samples to train the neural network on at least a portion of the acoustic speech model; and recognizing a received speech sample using the trained neural network.
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18. An article of manufacture including a non-transitory computer-readable storage medium having stored thereon program instructions that, upon execution by a computing device, cause the computing device to perform operations comprising: receiving training samples for training a neural network to learn an acoustic speech model, wherein at least one training sample of the training samples represents at least one phone of captured speech; determining a curriculum function for acoustic speech modeling, wherein the curriculum function assigns a difficulty value for a designated training sample of the training samples based on a combination comprising a duration value for the designated training sample and a sound quality value for the designated training sample; for each training sample of the training samples, determining a corresponding difficulty value for the training sample using the curriculum function; ordering the training samples based on the corresponding difficulty values for the training samples; presented presenting the ordered training samples to train the neural network on at least a portion of the acoustic speech model; and recognizing a received speech sample using the trained neural network. 22. The article of manufacture of claim 18 , wherein the combination further comprises an estimate from a posteriori estimator function.
| 0.714712 |
1. A computer-implemented method comprising: aggregating news documents from one or more news sources; grouping the news documents into a plurality of news collections, each of the plurality of news collections including a sub-set of the news documents having related content; determining objects described by the plurality of news collections, the objects collectively forming a set of objects; determining an overall relevance of each of the plurality of news collections by determining a number of news sources in each of the plurality of news collections reporting on a related topic; determining a level of interest in the objects described by the plurality of news collections by determining a number of other news collections mentioning the objects and a number of search queries searching for information about the objects during a predetermined timeframe; determining a significance of the objects in the plurality of news collections by determining a number of times that the objects appear in titles of the news documents of the plurality of news collections, a centrality of the objects in the news documents of the plurality of news collections, the centrality of the objects being based on where the objects are mentioned in a body of the news documents, and a pertinence of events described by the plurality of news collections involving the objects; determining a relevance of each of the plurality of news collections with respect to the objects respectively described by the plurality of news collections, the relevance being based on the overall relevance of each of the plurality of news collections, the level of interest in the objects described by the plurality of news collections, and the significance of the objects in the plurality of news collections; and determining one or more news collections from the plurality of news collections to be associated with a first object included in the set of objects based on the relevance of the one or more news collections to the first object.
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1. A computer-implemented method comprising: aggregating news documents from one or more news sources; grouping the news documents into a plurality of news collections, each of the plurality of news collections including a sub-set of the news documents having related content; determining objects described by the plurality of news collections, the objects collectively forming a set of objects; determining an overall relevance of each of the plurality of news collections by determining a number of news sources in each of the plurality of news collections reporting on a related topic; determining a level of interest in the objects described by the plurality of news collections by determining a number of other news collections mentioning the objects and a number of search queries searching for information about the objects during a predetermined timeframe; determining a significance of the objects in the plurality of news collections by determining a number of times that the objects appear in titles of the news documents of the plurality of news collections, a centrality of the objects in the news documents of the plurality of news collections, the centrality of the objects being based on where the objects are mentioned in a body of the news documents, and a pertinence of events described by the plurality of news collections involving the objects; determining a relevance of each of the plurality of news collections with respect to the objects respectively described by the plurality of news collections, the relevance being based on the overall relevance of each of the plurality of news collections, the level of interest in the objects described by the plurality of news collections, and the significance of the objects in the plurality of news collections; and determining one or more news collections from the plurality of news collections to be associated with a first object included in the set of objects based on the relevance of the one or more news collections to the first object. 5. The computer-implemented method of claim 1 , wherein the first object includes one or more of an entity, an event, and a topic.
| 0.633601 |
14. The apparatus according to claim 12 , wherein said record of said node table contains said node identifier.
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14. The apparatus according to claim 12 , wherein said record of said node table contains said node identifier. 15. The apparatus according to claim 14 , wherein said record of said node table further comprises a field for said simple property of the corresponding node, a simple property being capable of taking at most one value per node.
| 0.942731 |
1. A method comprising: identifying, by a processor, a first entity referenced in a document, wherein the first entity is identified using a first word or phrase located in a first portion of the document and having a first root word, wherein identifying the first entity comprises: identifying an n-gram in the document corresponding to the first entity, wherein identifying the n-gram comprises: converting text in the document to a root form of the text by performing at least one of (i) converting a plural form of the text to a singular form of the text or (ii) converting a possessive version of the text to a non-possessive version of the text, removing, from the text, at least one of (i) an article or (ii) a preposition, splitting the text into token elements, and applying, to the text, at least one of segmentation, n-gram extraction, or part-of-speech tagging, accessing a feature ontology, wherein the feature ontology comprises a mapping between a plurality of entities identified as n-grams and a plurality of classifications for the entities, wherein the feature ontology includes a character class that maps character entities to corresponding character references in the document, a setting class that maps setting entities to corresponding setting references in the document, and an emotion class that maps emotion entities to corresponding emotion reference in the document, and modifying the feature ontology to include the n-gram corresponding to the first entity; associating, by the processor, the first entity with a multimedia asset; determining, by the processor, that a second word or phrase in a second portion of the document refers to the first entity, wherein the second word or phrase includes a second root word that is different from the first root word in the first word or phrase; generating, by the processor, a layout for the second portion of the document based on determining that the second word or phrase refers to the first entity, wherein the layout includes the multimedia asset associated with the first entity; and rendering, by the processor, the layout with the second portion of the document for display.
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1. A method comprising: identifying, by a processor, a first entity referenced in a document, wherein the first entity is identified using a first word or phrase located in a first portion of the document and having a first root word, wherein identifying the first entity comprises: identifying an n-gram in the document corresponding to the first entity, wherein identifying the n-gram comprises: converting text in the document to a root form of the text by performing at least one of (i) converting a plural form of the text to a singular form of the text or (ii) converting a possessive version of the text to a non-possessive version of the text, removing, from the text, at least one of (i) an article or (ii) a preposition, splitting the text into token elements, and applying, to the text, at least one of segmentation, n-gram extraction, or part-of-speech tagging, accessing a feature ontology, wherein the feature ontology comprises a mapping between a plurality of entities identified as n-grams and a plurality of classifications for the entities, wherein the feature ontology includes a character class that maps character entities to corresponding character references in the document, a setting class that maps setting entities to corresponding setting references in the document, and an emotion class that maps emotion entities to corresponding emotion reference in the document, and modifying the feature ontology to include the n-gram corresponding to the first entity; associating, by the processor, the first entity with a multimedia asset; determining, by the processor, that a second word or phrase in a second portion of the document refers to the first entity, wherein the second word or phrase includes a second root word that is different from the first root word in the first word or phrase; generating, by the processor, a layout for the second portion of the document based on determining that the second word or phrase refers to the first entity, wherein the layout includes the multimedia asset associated with the first entity; and rendering, by the processor, the layout with the second portion of the document for display. 9. The method of claim 1 , wherein the document comprises an electronic book and wherein the layout is rendered for display by an electronic book reader application.
| 0.935609 |
1. A system for providing an automated media service, comprising: one or more memories designed to store computer program code; and one or more processors designed to execute the computer program code stored in the one or more memories, the computer program code designed to cause the one or more processors to perform at least the following: enable users and producers to subscribe to the media service at a website on the Internet; search content on the Internet in order to identify a topic, the topic indicative of relevant news or events, the topic indicative of a type of media content that will be requested for uploading from the producers; publish the topic to the producers; receive and store media content uploaded from the producers that relate to the topic in the one or more memories; enable the users to select and download the media content from the website over the Internet; enable the users to upload media content ratings for the media content to the website over the Internet; determine a producer rating for each of the producers based at least in part upon the media content ratings; and prevent the download of the media content from a first producer from the website over the Internet based at least in part upon the producer rating associated with the first producer; and permit the download of the media content from a second producer from the website over the Internet based at least in part upon the producer rating associated with the second producer.
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1. A system for providing an automated media service, comprising: one or more memories designed to store computer program code; and one or more processors designed to execute the computer program code stored in the one or more memories, the computer program code designed to cause the one or more processors to perform at least the following: enable users and producers to subscribe to the media service at a website on the Internet; search content on the Internet in order to identify a topic, the topic indicative of relevant news or events, the topic indicative of a type of media content that will be requested for uploading from the producers; publish the topic to the producers; receive and store media content uploaded from the producers that relate to the topic in the one or more memories; enable the users to select and download the media content from the website over the Internet; enable the users to upload media content ratings for the media content to the website over the Internet; determine a producer rating for each of the producers based at least in part upon the media content ratings; and prevent the download of the media content from a first producer from the website over the Internet based at least in part upon the producer rating associated with the first producer; and permit the download of the media content from a second producer from the website over the Internet based at least in part upon the producer rating associated with the second producer. 5. The system of claim 1 , wherein the computer program code is further designed to cause the one or more processors to: communicate an advertisement to a user with the media content.
| 0.554688 |
9. A system for speaker verification, the system comprising: an extraction module configured to identify a target speaker's speech, using a known speaker voiceprint, from an audio recording that includes the target speaker's speech and the known speaker's speech, the known speaker voiceprint corresponding to the known speaker, wherein using the known speaker voiceprint includes enabling exclusion of speech segments of the known speaker's speech to reduce a total number of speech segments used to verify the target speaker's speech to improve accuracy with reduced processing time or power for verifying relative to having all speech segments of the target and known speaker's speech under consideration; and a reporting module configured to report a representation of the extracted target speaker's speech.
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9. A system for speaker verification, the system comprising: an extraction module configured to identify a target speaker's speech, using a known speaker voiceprint, from an audio recording that includes the target speaker's speech and the known speaker's speech, the known speaker voiceprint corresponding to the known speaker, wherein using the known speaker voiceprint includes enabling exclusion of speech segments of the known speaker's speech to reduce a total number of speech segments used to verify the target speaker's speech to improve accuracy with reduced processing time or power for verifying relative to having all speech segments of the target and known speaker's speech under consideration; and a reporting module configured to report a representation of the extracted target speaker's speech. 16. The system of claim 9 , wherein the reporting module is configure to report the representation of the extracted target speaker's speech by reporting at least one of an extracted target speaker's speech's speaker, a score, a pointer, encoded data, and a signal.
| 0.5 |
1. A non-transitory computer readable medium encoded with program instructions which are executed by a computer to provide a method of generating internal citations for a formatted document, the instructions comprising the steps of: a) obtaining graphic representations of each page of the formatted document, b) optically recognizing characters on each page of the formatted document, and determining the position of the characters on each page, c) obtaining a separate and distinct text version of the formatted document, d) parsing text from the text version, the parsed text being separate and distinct from the recognized characters, e) correlating the recognized characters with the parsed text to determine an internal citation for each sentence, wherein the internal citation identifies the document and a citation location inside the document where the corresponding sentence is found, wherein the citation location comprises one or more of: i) an internal citation page number; ii) an internal citation column number; iii) an internal citation line number; iv) an internal citation paragraph number; and v) an internal citation sentence number, and f) creating a data structure storing data determined in the correlating step.
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1. A non-transitory computer readable medium encoded with program instructions which are executed by a computer to provide a method of generating internal citations for a formatted document, the instructions comprising the steps of: a) obtaining graphic representations of each page of the formatted document, b) optically recognizing characters on each page of the formatted document, and determining the position of the characters on each page, c) obtaining a separate and distinct text version of the formatted document, d) parsing text from the text version, the parsed text being separate and distinct from the recognized characters, e) correlating the recognized characters with the parsed text to determine an internal citation for each sentence, wherein the internal citation identifies the document and a citation location inside the document where the corresponding sentence is found, wherein the citation location comprises one or more of: i) an internal citation page number; ii) an internal citation column number; iii) an internal citation line number; iv) an internal citation paragraph number; and v) an internal citation sentence number, and f) creating a data structure storing data determined in the correlating step. 10. The computer readable medium of claim 1 wherein the determining the position of the characters substep further includes at least one of the group of: a) assembling lines, b) allocating lines to columns, and c) calculating line numbers.
| 0.57566 |
11. A computer system comprising: one or more processors; a software program stored on a non-transitory computer readable storage medium and configured to cause the one or more processors to: provide in a database layer, a database engine and a database comprising data organized according to a relational model; provide in an application layer, an entity relationship data model and a query engine in communication with the database engine; cause the database engine to receive via the query engine a query in a database language that has been extended to include an entity type and an association, the query further comprising a path expression including a filter element suffix followed by nested projection clauses specifying a relationship between a specified entity and an associated entity; cause the database engine to return to the query engine a query result set comprising data of the associated entity matching the nested projection clauses of the path expression, wherein if the path expression includes an optional flattening symbol, the query result set comprises the data in a result set type structure that is flattened, and wherein if the path expression omits the optional flattening symbol, the query result set comprises the data in the result set type structure that corresponds to the nested projection clauses; and cause the database engine to store the data in the database according to the result set type structure.
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11. A computer system comprising: one or more processors; a software program stored on a non-transitory computer readable storage medium and configured to cause the one or more processors to: provide in a database layer, a database engine and a database comprising data organized according to a relational model; provide in an application layer, an entity relationship data model and a query engine in communication with the database engine; cause the database engine to receive via the query engine a query in a database language that has been extended to include an entity type and an association, the query further comprising a path expression including a filter element suffix followed by nested projection clauses specifying a relationship between a specified entity and an associated entity; cause the database engine to return to the query engine a query result set comprising data of the associated entity matching the nested projection clauses of the path expression, wherein if the path expression includes an optional flattening symbol, the query result set comprises the data in a result set type structure that is flattened, and wherein if the path expression omits the optional flattening symbol, the query result set comprises the data in the result set type structure that corresponds to the nested projection clauses; and cause the database engine to store the data in the database according to the result set type structure. 15. A computer system as in claim 11 wherein the database comprises an in memory database.
| 0.515192 |
35. The data processing system according to claim 32 , wherein said data structure further comprises the descriptor element factory that produces a plurality of descriptor elements, said descriptor elements being used by said parser.
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35. The data processing system according to claim 32 , wherein said data structure further comprises the descriptor element factory that produces a plurality of descriptor elements, said descriptor elements being used by said parser. 38. The data processing system according to claim 35 , wherein said descriptor elements are arranged as a composite tree structure.
| 0.941722 |
5. One or more computer-readable media storing computer-executable instructions that, when executed on one or more processors, perform acts comprising: generating a first corpus of phrases each comprising at least two grammatically-correct words; filtering the first corpus of phrases to define a second corpus of phrases, wherein the filtering the first corpus of phrases comprises: determining a commonality of words of the multiple phrases of the first corpus of phrases; and filtering out phrases of the first corpus of phrases to define a second corpus of phrases based at least in part on the determined commonality of the words of the multiple phrases; outputting phrases of the second corpus of phrases to each of multiple users; receiving selections of phrases from each of the multiple users; and responsive to the receiving of the selection, associating a selected phrase with each respective user of the multiple users.
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5. One or more computer-readable media storing computer-executable instructions that, when executed on one or more processors, perform acts comprising: generating a first corpus of phrases each comprising at least two grammatically-correct words; filtering the first corpus of phrases to define a second corpus of phrases, wherein the filtering the first corpus of phrases comprises: determining a commonality of words of the multiple phrases of the first corpus of phrases; and filtering out phrases of the first corpus of phrases to define a second corpus of phrases based at least in part on the determined commonality of the words of the multiple phrases; outputting phrases of the second corpus of phrases to each of multiple users; receiving selections of phrases from each of the multiple users; and responsive to the receiving of the selection, associating a selected phrase with each respective user of the multiple users. 14. One or more computer-readable media as recited in claim 5 , wherein the filtering of the first corpus of phrases further comprises: determining a source that generated each of multiple phrases of the first corpus of phrases; and filtering out phrases of the first corpus of phrases based at least in part on the determined sources that generated each of the multiple phrases.
| 0.585292 |
7. The model of claim 6 , the predictive component determines a probability of information value to a user given evidence of the user's interest in at least one of a potential site and topic.
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7. The model of claim 6 , the predictive component determines a probability of information value to a user given evidence of the user's interest in at least one of a potential site and topic. 8. The model of claim 7 , the probability formulated as:
Pr(Information Value|E 1 ,E 2 , . . . E J ); wherein Pr is the probability, Information Value relates to an importance of the site and topic to the user given evidence E relating to attributes of information importance, and J being an integer.
| 0.880048 |
13. The method of claim 9 , wherein calculating the image profile confidence level comprises: calculating a standard deviation of the black pixel distribution in each row; calculating the black pixel density as a ratio of a total number of black pixels in an image area to a total number of pixels in the image area; and setting the image profile confidence level equal to the smaller of (i) a function of the standard deviation and (ii) a function of the black pixel density.
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13. The method of claim 9 , wherein calculating the image profile confidence level comprises: calculating a standard deviation of the black pixel distribution in each row; calculating the black pixel density as a ratio of a total number of black pixels in an image area to a total number of pixels in the image area; and setting the image profile confidence level equal to the smaller of (i) a function of the standard deviation and (ii) a function of the black pixel density. 14. The method of claim 13 , wherein calculating the image profile confidence level further comprises: adjusting the standard deviation of the black pixel distribution based on a maximum allowable standard deviation and a minimum allowable standard deviation; and adjusting the black pixel density based on a maximum allowable black pixel density and a minimum allowable black pixel density.
| 0.890223 |
13. A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions that, when executed by a processor, cause a system to perform operations comprising: performing a region division structured query language (SQL) statement rewrite operation on the SQL statement, the region division SQL statement rewrite operation identifying a plurality of SQL statement regions; specifying a rewrite focus priority for a particular SQL statement region in the plurality of SQL statement regions, the rewrite focus priority providing an indication of a particular amount of resource to be expended on the particular SQL statement region during an optimization operation on the particular SQL statement region, the rewrite focus priority indicating that the optimization operation is to be performed on the particular SQL statement region before other SQLs statement region in the plurality of SQL statement regions; performing a region preferential SQL statement optimization operation on the particular SQL statement region based on the rewrite focus priority indicating that the optimization operation is to be performed on the particular SQL statement region before other SQLs statement region in the plurality of SQL statement regions and based upon the indication of the particular amount of resource to be expended on the particular SQL statement region, the SQL statement optimization operation recursively performing a rewrite optimization on the particular SQL statement region according to the specified rewrite focus priority.
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13. A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions that, when executed by a processor, cause a system to perform operations comprising: performing a region division structured query language (SQL) statement rewrite operation on the SQL statement, the region division SQL statement rewrite operation identifying a plurality of SQL statement regions; specifying a rewrite focus priority for a particular SQL statement region in the plurality of SQL statement regions, the rewrite focus priority providing an indication of a particular amount of resource to be expended on the particular SQL statement region during an optimization operation on the particular SQL statement region, the rewrite focus priority indicating that the optimization operation is to be performed on the particular SQL statement region before other SQLs statement region in the plurality of SQL statement regions; performing a region preferential SQL statement optimization operation on the particular SQL statement region based on the rewrite focus priority indicating that the optimization operation is to be performed on the particular SQL statement region before other SQLs statement region in the plurality of SQL statement regions and based upon the indication of the particular amount of resource to be expended on the particular SQL statement region, the SQL statement optimization operation recursively performing a rewrite optimization on the particular SQL statement region according to the specified rewrite focus priority. 18. The non-transitory, computer-readable storage medium of claim 13 , wherein: the specifying is provided via a user-specified input where the user is able to inference how to rewrite the SQL statement.
| 0.572572 |
1. A system for package fill determination comprising a system controller; a data storage element; a historical data set acquisition element; a sampling manufacturing period acquisition element; a variance model acquisition element; a estimation technique acquisition element; a variance component set acquisition element; a first constraint set acquisition element; a first probability acquisition element; and a product data set acquisition element; wherein said system controller: (i) obtains a historical data set via said historical data set acquisition element; (ii) obtains a sampling manufacturing period via said sampling manufacturing period acquisition element; (iii) obtains a variance model via said variance model acquisition element; (iv) obtains an estimation technique via said estimation technique acquisition element, wherein steps (i), (ii), (iii) and (iv) may be conducted in any order; (v) determines a variance component set, acquired via said variance component set acquisition element, using said variance model, said estimation technique, and said historical data set; and (vi) determines a first target by the method comprising the steps of: a) obtaining a first constraint set via said first constraint set acquisition element; b) obtaining a first probability via said first probability selection element; c) obtaining a product data set via said product data set acquisition element, wherein steps (a), (b) and (c) may be conducted in any order; and d) calculating said first target utilizing said variance component set such that the probability of satisfying said first constraint set is at least as great as said first probability.
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1. A system for package fill determination comprising a system controller; a data storage element; a historical data set acquisition element; a sampling manufacturing period acquisition element; a variance model acquisition element; a estimation technique acquisition element; a variance component set acquisition element; a first constraint set acquisition element; a first probability acquisition element; and a product data set acquisition element; wherein said system controller: (i) obtains a historical data set via said historical data set acquisition element; (ii) obtains a sampling manufacturing period via said sampling manufacturing period acquisition element; (iii) obtains a variance model via said variance model acquisition element; (iv) obtains an estimation technique via said estimation technique acquisition element, wherein steps (i), (ii), (iii) and (iv) may be conducted in any order; (v) determines a variance component set, acquired via said variance component set acquisition element, using said variance model, said estimation technique, and said historical data set; and (vi) determines a first target by the method comprising the steps of: a) obtaining a first constraint set via said first constraint set acquisition element; b) obtaining a first probability via said first probability selection element; c) obtaining a product data set via said product data set acquisition element, wherein steps (a), (b) and (c) may be conducted in any order; and d) calculating said first target utilizing said variance component set such that the probability of satisfying said first constraint set is at least as great as said first probability. 9. The system of claim 1 wherein said first constraint set comprises a constraint selected from the group consisting of product aesthetic constraints, product promotion constraints, product packaging constraints, regulatory constraints, and combinations thereof.
| 0.577507 |
1. A method of electronically trapping a printed color page including a plurality of color regions, the method comprising the steps of: (a) creating, according to a set of trapping rules, a proposed trap area for a color region of interest; (b) determining a cutout from the proposed trap area if one or more color regions that do not overlap the proposed trap area are in such close proximity to the color region of interest that an undesirable trap would result without the modification; and (c) creating a resultant trap area for the color region of interest which is equivalent to the proposed trap area less the cutout.
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1. A method of electronically trapping a printed color page including a plurality of color regions, the method comprising the steps of: (a) creating, according to a set of trapping rules, a proposed trap area for a color region of interest; (b) determining a cutout from the proposed trap area if one or more color regions that do not overlap the proposed trap area are in such close proximity to the color region of interest that an undesirable trap would result without the modification; and (c) creating a resultant trap area for the color region of interest which is equivalent to the proposed trap area less the cutout. 2. The method of claim 1 and further including the step of comparing the proposed trap area to color regions to determine if there are any intersections between the two areas and, if one or more intersections are present, modifying the resultant trap area to exclude the color region or regions from the resultant trap area.
| 0.803607 |
8. 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 (i) a natural language query submitted by a user that requests information relating to a context associated with a prior consumption of a media item, and (ii) ambient environmental data obtained from an environment of a user; identifying a particular media item based on detecting a match between one or more features of the ambient environmental data obtained from the environment of the user and one or more features of the particular media item; determining that the particular media item is identified in a media consumption database that identifies media items that are identified as having been previously consumed by the user; accessing, at the media consumption database, information that (i) identifies a context associated with the previous consumption of the particular media item by the user, and that is (ii) identified as being responsive to the natural language query submitted by the user; and providing a response to the natural language query submitted by the user that includes at least a portion of the information accessed at the media consumption database that (i) identifies the context associated with the previous consumption of the particular media item by the user, and that is (ii) identified as being responsive to the natural language query submitted by the user.
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8. 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 (i) a natural language query submitted by a user that requests information relating to a context associated with a prior consumption of a media item, and (ii) ambient environmental data obtained from an environment of a user; identifying a particular media item based on detecting a match between one or more features of the ambient environmental data obtained from the environment of the user and one or more features of the particular media item; determining that the particular media item is identified in a media consumption database that identifies media items that are identified as having been previously consumed by the user; accessing, at the media consumption database, information that (i) identifies a context associated with the previous consumption of the particular media item by the user, and that is (ii) identified as being responsive to the natural language query submitted by the user; and providing a response to the natural language query submitted by the user that includes at least a portion of the information accessed at the media consumption database that (i) identifies the context associated with the previous consumption of the particular media item by the user, and that is (ii) identified as being responsive to the natural language query submitted by the user. 13. The system of claim 8 , wherein accessing the information that (i) identifies a context associated with the previous consumption of the particular media item by the user, and that is (ii) identified as being responsive to the natural language query submitted by the user comprises accessing, at the media consumption database, information that indicates at least one of a location, a time, a date, or a method of consumption of the particular media item by the user.
| 0.638164 |
1. A method for targeting advertisements to users, the method comprising: using at least one computer system to perform method steps comprising: for a plurality of advertisers: receiving explicit criteria from a plurality of advertisers; providing search results to each of the plurality of advertisers responsive to the explicit criteria; receiving feedback from each of the plurality of advertisers about the search results; determining implicit criteria about which users the plurality of advertisers wish to target based on the feedback received from the plurality of advertisers, the implicit criteria indicating hidden preferences of the advertisers identified from the feedback from each of the plurality of advertisers; for a plurality of users: receiving explicit user criteria providing information about each of the users, the criteria providing information about which advertisements the users should view; providing the users with search results using the explicit user criteria for one or more searches conducted by each of the users; receiving user feedback regarding the search results; determining implicit user criteria based on the feedback provided by the users; creating a plurality of advertiser/ad profiles each using the explicit and implicit advertiser/ad criteria for a given advertiser/ad; creating a plurality of user profiles each using the explicit and implicit user criteria for a given user; comparing the advertiser/ad profiles and the user profiles to generate relevance scores and determine matches between a particular advertiser/ad profile and a particular user profile; determining which of the advertisements to present to each of the plurality of users based on placement factors including computing relevance of each of the advertisements to each of the plurality of users, computing value of each of the plurality of users to each of the advertisers based on the relevance of each of the advertisements to each of the plurality of users, and computing a price for presenting the advertisement to each of the plurality of users; and presenting to each of the plurality of users the advertisements for which a positive determination to place the advertisement is made.
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1. A method for targeting advertisements to users, the method comprising: using at least one computer system to perform method steps comprising: for a plurality of advertisers: receiving explicit criteria from a plurality of advertisers; providing search results to each of the plurality of advertisers responsive to the explicit criteria; receiving feedback from each of the plurality of advertisers about the search results; determining implicit criteria about which users the plurality of advertisers wish to target based on the feedback received from the plurality of advertisers, the implicit criteria indicating hidden preferences of the advertisers identified from the feedback from each of the plurality of advertisers; for a plurality of users: receiving explicit user criteria providing information about each of the users, the criteria providing information about which advertisements the users should view; providing the users with search results using the explicit user criteria for one or more searches conducted by each of the users; receiving user feedback regarding the search results; determining implicit user criteria based on the feedback provided by the users; creating a plurality of advertiser/ad profiles each using the explicit and implicit advertiser/ad criteria for a given advertiser/ad; creating a plurality of user profiles each using the explicit and implicit user criteria for a given user; comparing the advertiser/ad profiles and the user profiles to generate relevance scores and determine matches between a particular advertiser/ad profile and a particular user profile; determining which of the advertisements to present to each of the plurality of users based on placement factors including computing relevance of each of the advertisements to each of the plurality of users, computing value of each of the plurality of users to each of the advertisers based on the relevance of each of the advertisements to each of the plurality of users, and computing a price for presenting the advertisement to each of the plurality of users; and presenting to each of the plurality of users the advertisements for which a positive determination to place the advertisement is made. 10. The method of claim 1 , wherein determining which of the advertisements to present further comprises determining an order in which to present the advertisements to the users.
| 0.599528 |
8. The method of claim 7 , wherein providing, for display to the advertiser, the one or more terms comprises: providing misrecognition frequencies that each indicate a frequency that the expected pronunciation of the textual representation of the candidate adword is misrecognized as a respective term.
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8. The method of claim 7 , wherein providing, for display to the advertiser, the one or more terms comprises: providing misrecognition frequencies that each indicate a frequency that the expected pronunciation of the textual representation of the candidate adword is misrecognized as a respective term. 9. The method of claim 8 , comprising: providing data indicating whether an advertisement was displayed when the expected pronunciation of the textual representation of the candidate adword is misrecognized as the respective term.
| 0.966886 |
19. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: identifying a particular query term of an original search query; identifying a candidate synonym for the particular query term; accessing stored data that specifies, for a pair of terms that includes the particular query term and the candidate synonym of the particular query term, a confidence value for a non-adjacent query term of the original search query that is not adjacent to the particular query term in the original search query; determining that, in the stored data that specifies, for the pair of terms that includes the particular query term and the candidate synonym of the particular query term, the confidence value for the non-adjacent query term satisfies a threshold; and determining to revise the original search query to include the candidate synonym of the particular query term, based on determining that the confidence value for the non-adjacent query term satisfies the threshold.
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19. A system comprising: one or more computers; and a computer-readable medium coupled to the one or more computers having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: identifying a particular query term of an original search query; identifying a candidate synonym for the particular query term; accessing stored data that specifies, for a pair of terms that includes the particular query term and the candidate synonym of the particular query term, a confidence value for a non-adjacent query term of the original search query that is not adjacent to the particular query term in the original search query; determining that, in the stored data that specifies, for the pair of terms that includes the particular query term and the candidate synonym of the particular query term, the confidence value for the non-adjacent query term satisfies a threshold; and determining to revise the original search query to include the candidate synonym of the particular query term, based on determining that the confidence value for the non-adjacent query term satisfies the threshold. 24. The system of claim 19 , the operations further comprising: determining, in the context of a second non-adjacent query term to the particular query term, that the candidate synonym is a definitive non-synonym for the particular query term; and determining not to revise the original search query, based on determining that the candidate synonym is a definitive non-synonym for the particular query term.
| 0.550125 |
1. A method comprising, by a computing system: receiving, from a client system of a first user of an online social network, an indication of the first user accessing a query field associated with a currently accessed page of the online social network, the online social network being associated with a plurality of entities, wherein the currently accessed page is a unique profile page of a particular entity of the plurality of entities; identifying the particular entity of the plurality of entities corresponding to the profile page generating one or more structured queries based on the particular entity corresponding to the profile page, each structured query comprising a reference to the particular entity corresponding to the profile page and one or more additional query tokens; and sending, to the client system of the first user, responsive to the user accessing the query field, instructions for displaying one or more suggested queries on the page, wherein the one or more suggested queries correspond to one or more of the structured queries, respectively, and wherein each suggested query that is displayed is selectable by the first user to retrieve search results corresponding to the selected query.
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1. A method comprising, by a computing system: receiving, from a client system of a first user of an online social network, an indication of the first user accessing a query field associated with a currently accessed page of the online social network, the online social network being associated with a plurality of entities, wherein the currently accessed page is a unique profile page of a particular entity of the plurality of entities; identifying the particular entity of the plurality of entities corresponding to the profile page generating one or more structured queries based on the particular entity corresponding to the profile page, each structured query comprising a reference to the particular entity corresponding to the profile page and one or more additional query tokens; and sending, to the client system of the first user, responsive to the user accessing the query field, instructions for displaying one or more suggested queries on the page, wherein the one or more suggested queries correspond to one or more of the structured queries, respectively, and wherein each suggested query that is displayed is selectable by the first user to retrieve search results corresponding to the selected query. 9. The method of claim 1 , wherein the structured queries are displayed in association with the query field associated with the profile page.
| 0.646493 |
1. A method comprising: receiving, by a system comprising a processor, speech data; detecting, by the system, a missing segment in the speech data resulting from an interruption occurring in a communication network conveying the speech data; generating, by the system, a plurality of hypothetical segments for the missing segment; determining, by the system, a duration of the missing segment; evaluating, by the system and according to a duration model which is based on a mean and a variance of duration for individual context-dependent phoneme acoustic models associated with the plurality of hypothetical segments, the plurality of hypothetical segments according to a context of speech determined from the speech data and the duration of the missing segment to identify a possible segment that represents the missing segment of the speech data to yield an identified segment; and inserting the identified segment into the speech data to replace the missing segment.
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1. A method comprising: receiving, by a system comprising a processor, speech data; detecting, by the system, a missing segment in the speech data resulting from an interruption occurring in a communication network conveying the speech data; generating, by the system, a plurality of hypothetical segments for the missing segment; determining, by the system, a duration of the missing segment; evaluating, by the system and according to a duration model which is based on a mean and a variance of duration for individual context-dependent phoneme acoustic models associated with the plurality of hypothetical segments, the plurality of hypothetical segments according to a context of speech determined from the speech data and the duration of the missing segment to identify a possible segment that represents the missing segment of the speech data to yield an identified segment; and inserting the identified segment into the speech data to replace the missing segment. 4. The method of claim 1 , wherein the evaluating of the plurality of hypothetical segments is further based on a lexicon.
| 0.640323 |
17. The one or more tangible computer-readable storage media of claim 9 , wherein each portion has a length that does not exceed the length limit.
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17. The one or more tangible computer-readable storage media of claim 9 , wherein each portion has a length that does not exceed the length limit. 18. The one or more tangible computer-readable storage media of claim 17 , wherein, when multiple portions in the plurality of portions each include the highest number of the one or more keywords, the abstract is the one of the multiple portions that has a greatest total number of the keywords, including keywords that are repeated.
| 0.945911 |
6. The computer-implemented method of claim 1 , wherein generating feedback options related to the item is responsive to receiving a request from the buyer, the request being to submit feedback regarding the item.
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6. The computer-implemented method of claim 1 , wherein generating feedback options related to the item is responsive to receiving a request from the buyer, the request being to submit feedback regarding the item. 7. The computer-implemented method of claim 6 , further including prompting the buyer to submit feedback regarding the item.
| 0.892462 |
14. The method according to claim 1 , wherein the similarity of two character strings is calculated according to a linear optimization method, in that a maximum of a numerical value that shows the similarity of the character strings is sought, the maximum value from a limiting condition that no character of the character strings to be compared may belong to more than one fragment.
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14. The method according to claim 1 , wherein the similarity of two character strings is calculated according to a linear optimization method, in that a maximum of a numerical value that shows the similarity of the character strings is sought, the maximum value from a limiting condition that no character of the character strings to be compared may belong to more than one fragment. 16. The method according to claim 14 , wherein an iteration process that converges from the bottom or the top, respectively, for the solving of the linear optimization problem is interrupted when the numerical value of the similarity reaches a threshold value or exceeds or falls below it, respectively.
| 0.830307 |
18. A non-transitory computer-readable medium storing a computer program for processing related datasets, the computer program including instructions for causing a computer to: receive over an input device or port records from multiple datasets, the records of a given dataset having one or more values for one or more respective fields; and process records from each of the multiple datasets in a data processing system, the processing including analyzing at least one constraint specification stored in a data storage system to determine a processing order for the multiple datasets, the constraint specification specifying one or more constraints for preserving referential integrity or statistical consistency among a group of related datasets that includes the multiple datasets, applying one or more transformations to records from each of the multiple datasets in the determined processing order, where the transformations are applied to records from a first dataset of the multiple datasets before the transformations are applied to records from a second dataset of the multiple datasets, and the transformations applied to the records from the second dataset are applied based at least in part on results of applying the transformations to the records from the first dataset and at least one constraint between the first dataset and the second dataset specified by the constraint specification, and storing or outputting results of the transformations to the records from each of the multiple datasets.
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18. A non-transitory computer-readable medium storing a computer program for processing related datasets, the computer program including instructions for causing a computer to: receive over an input device or port records from multiple datasets, the records of a given dataset having one or more values for one or more respective fields; and process records from each of the multiple datasets in a data processing system, the processing including analyzing at least one constraint specification stored in a data storage system to determine a processing order for the multiple datasets, the constraint specification specifying one or more constraints for preserving referential integrity or statistical consistency among a group of related datasets that includes the multiple datasets, applying one or more transformations to records from each of the multiple datasets in the determined processing order, where the transformations are applied to records from a first dataset of the multiple datasets before the transformations are applied to records from a second dataset of the multiple datasets, and the transformations applied to the records from the second dataset are applied based at least in part on results of applying the transformations to the records from the first dataset and at least one constraint between the first dataset and the second dataset specified by the constraint specification, and storing or outputting results of the transformations to the records from each of the multiple datasets. 25. The medium of claim 18 , wherein at least one constraint for preserving statistical consistency specified by the constraint specification is based on an equivalence between a field of the second dataset and a field of the first dataset.
| 0.695301 |
1. A method of searching in a second dataset using a query from a first dataset, the method comprising: receiving a first query using the first dataset, the first query being generated using a first collation associated with the first dataset, the first collation having a case sensitivity flag, an accent use sensitivity flag, a character width sensitivity flag, and a kana sensitivity flag for a first human language; rewriting the first query to form a second query, the second query comprising a second collation and a residue predicate, the second collation comprising a superset of the first collation, the second collation of the second query being broader than the first collation of the first query and being insensitive with respect to at least one of case, accent use, character width, and kana, the second collation encompassing the first collation, the second collation having an associated index for the second collation, and the residue predicate comprising an original search term from the first query, wherein the residue predicate is selected to ensure that a set of results returned in response to the second query satisfies the case sensitivity flag, the accent use sensitivity flag, the character width sensitivity flag, and the kana sensitivity flag of the first collation; optimizing the second query by choosing an index plan that targets an index associated with multiple human languages that is useful in searching across a multiplicity of human language collations; executing the second query to search the first dataset; and returning information satisfying the first query; wherein the first and second datasets each comprise one of a database, a user session and an explicit user query.
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1. A method of searching in a second dataset using a query from a first dataset, the method comprising: receiving a first query using the first dataset, the first query being generated using a first collation associated with the first dataset, the first collation having a case sensitivity flag, an accent use sensitivity flag, a character width sensitivity flag, and a kana sensitivity flag for a first human language; rewriting the first query to form a second query, the second query comprising a second collation and a residue predicate, the second collation comprising a superset of the first collation, the second collation of the second query being broader than the first collation of the first query and being insensitive with respect to at least one of case, accent use, character width, and kana, the second collation encompassing the first collation, the second collation having an associated index for the second collation, and the residue predicate comprising an original search term from the first query, wherein the residue predicate is selected to ensure that a set of results returned in response to the second query satisfies the case sensitivity flag, the accent use sensitivity flag, the character width sensitivity flag, and the kana sensitivity flag of the first collation; optimizing the second query by choosing an index plan that targets an index associated with multiple human languages that is useful in searching across a multiplicity of human language collations; executing the second query to search the first dataset; and returning information satisfying the first query; wherein the first and second datasets each comprise one of a database, a user session and an explicit user query. 4. The method of claim 1 , wherein the index that is useful in searching across a multiplicity of human language collations is an index containing Unicode characters.
| 0.92247 |
1. A computer program product for routing a facsimile, the computer program product comprising a non-transitory computer readable medium having program code embodied therewith, the program code readable/executable by the processor to cause the processor to: receive a facsimile in a computer readable format; locate one or more keywords in the facsimile, wherein at least two of the keywords are not adjacent in the facsimile; analyze the facsimile to determine at least one of a meaning of the facsimile and a context of the facsimile; attempt to initiate a business process based at least in part on analysis; detect a problem with the attempt to initiate the business process; generate a notification of the problem; and route at least a portion of the facsimile comprising text to one or more destinations based at least in part on the analysis.
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1. A computer program product for routing a facsimile, the computer program product comprising a non-transitory computer readable medium having program code embodied therewith, the program code readable/executable by the processor to cause the processor to: receive a facsimile in a computer readable format; locate one or more keywords in the facsimile, wherein at least two of the keywords are not adjacent in the facsimile; analyze the facsimile to determine at least one of a meaning of the facsimile and a context of the facsimile; attempt to initiate a business process based at least in part on analysis; detect a problem with the attempt to initiate the business process; generate a notification of the problem; and route at least a portion of the facsimile comprising text to one or more destinations based at least in part on the analysis. 3. The computer program product as recited in claim 1 , wherein the attempt is further based at least in part on the determined context of the facsimile, wherein the determined context of the facsimile comprises an intended business process for the facsimile, and wherein the attempted business process corresponds to the intended business process.
| 0.541667 |
1. A method of representing model-operative patterns, comprising: specifying a pattern codification for a particular pattern, the pattern codification comprising a structural definition portion and a behavioral definition portion, wherein: the pattern codification for the particular pattern is decoupled from executable code that carries out each operation for implementing the particular pattern; the structural definition portion defines each of at least one role used in the particular pattern and each of at least one relationship used in the particular pattern, wherein each of the at least one relationship involves at least one of the at least one role; when the particular pattern is composed from other composited patterns, the behavioral definition portion specifies each of at least one constraint that must be met before the particular pattern can be applied and identifies how to use ones of the at least one role of the particular pattern and the at least one relationship of the particular pattern for constraining expressions that are defined using at least one role and at least one relationship of the other composited patterns; and when the particular pattern is not composed from other composited patterns, the behavioral definition portion identifies the executable code that carries out each of at least one operation to invoke for implementing the particular pattern when the particular pattern is applied; comprehending the particular pattern in a particular model by identifying elements of the model that are candidate participants for each of the at least one pattern role of the particular pattern, for each of the at least one relationship involving the each role; executing a pattern operation using the comprehended pattern to determine whether each of the at least one constraint of the particular pattern is met; and responsive to determining that each of the at least one constraint is met, concluding that the identified elements of the model together comprise an occurrence of the particular pattern.
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1. A method of representing model-operative patterns, comprising: specifying a pattern codification for a particular pattern, the pattern codification comprising a structural definition portion and a behavioral definition portion, wherein: the pattern codification for the particular pattern is decoupled from executable code that carries out each operation for implementing the particular pattern; the structural definition portion defines each of at least one role used in the particular pattern and each of at least one relationship used in the particular pattern, wherein each of the at least one relationship involves at least one of the at least one role; when the particular pattern is composed from other composited patterns, the behavioral definition portion specifies each of at least one constraint that must be met before the particular pattern can be applied and identifies how to use ones of the at least one role of the particular pattern and the at least one relationship of the particular pattern for constraining expressions that are defined using at least one role and at least one relationship of the other composited patterns; and when the particular pattern is not composed from other composited patterns, the behavioral definition portion identifies the executable code that carries out each of at least one operation to invoke for implementing the particular pattern when the particular pattern is applied; comprehending the particular pattern in a particular model by identifying elements of the model that are candidate participants for each of the at least one pattern role of the particular pattern, for each of the at least one relationship involving the each role; executing a pattern operation using the comprehended pattern to determine whether each of the at least one constraint of the particular pattern is met; and responsive to determining that each of the at least one constraint is met, concluding that the identified elements of the model together comprise an occurrence of the particular pattern. 16. The method according to claim 1 , further comprising determining, using the specified pattern codification for the particular pattern, whether the particular pattern can be applied to elements of a domain model.
| 0.643929 |
11. A system for recovering from an error in a speech recognition system, comprising: a first non-transitory module that, by a processor, receives a first command recognized from a first speech utterance from a first language model, receives a second command recognized from the first speech utterance from a second language model, and determines at least one of similarities and dissimilarities between the first command and the second command; a second non-transitory module that, by a processor, determines a root cause by processing the first command and the second command with at least one rule of an error model based on the similarities and dissimilarities; and a third non-transitory module that, by a processor, selectively executes a recovery process based on the root cause.
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11. A system for recovering from an error in a speech recognition system, comprising: a first non-transitory module that, by a processor, receives a first command recognized from a first speech utterance from a first language model, receives a second command recognized from the first speech utterance from a second language model, and determines at least one of similarities and dissimilarities between the first command and the second command; a second non-transitory module that, by a processor, determines a root cause by processing the first command and the second command with at least one rule of an error model based on the similarities and dissimilarities; and a third non-transitory module that, by a processor, selectively executes a recovery process based on the root cause. 13. The system of claim 11 wherein the recovery process includes generating at least one of prompt data and interaction sequence data to recover from the root cause.
| 0.600948 |
7. A non-transitory computer readable storage medium storing computer program instructions capable of being executed by a computer processor on a computing device, the computer program instructions defining the steps of: scanning, by a client-side module executing on a computing device, a Document Object Model (DOM) of a first web page displayed by a browser on a display of the computing device to determine a location of a primary search query user input area associated with the first web page; determining, by the client-side module, that a search query has been entered by a user into the primary search query user input area; in response to the determining, automatically entering, by the client-side module, the search query entered by the user into the primary search query user input area into a secondary search query user input area associated with a predetermined second web page, the second web page determined by the client-side module based on web browsing history of the user; displaying in a first content area of the browser the result of a search performed by a search tool represented by the first web page on the search query; and displaying in a second content area of the browser the result of a search performed by a search tool represented by the second web page on the search query.
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7. A non-transitory computer readable storage medium storing computer program instructions capable of being executed by a computer processor on a computing device, the computer program instructions defining the steps of: scanning, by a client-side module executing on a computing device, a Document Object Model (DOM) of a first web page displayed by a browser on a display of the computing device to determine a location of a primary search query user input area associated with the first web page; determining, by the client-side module, that a search query has been entered by a user into the primary search query user input area; in response to the determining, automatically entering, by the client-side module, the search query entered by the user into the primary search query user input area into a secondary search query user input area associated with a predetermined second web page, the second web page determined by the client-side module based on web browsing history of the user; displaying in a first content area of the browser the result of a search performed by a search tool represented by the first web page on the search query; and displaying in a second content area of the browser the result of a search performed by a search tool represented by the second web page on the search query. 11. The non-transitory computer readable storage medium of claim 7 wherein the step of displaying results of the search performed by the search tool represented by the first web page further comprises the step of displaying personalized results of the search.
| 0.525447 |
1. A method, comprising: receiving user input to an input component of an information handling device; generating a machine based representation of the user input; analyzing, using a processor, the representation of the user input; forming, using a processor, a tag based on contextual user data related to the user input; and providing, using a processor, an indication of the tag.
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1. A method, comprising: receiving user input to an input component of an information handling device; generating a machine based representation of the user input; analyzing, using a processor, the representation of the user input; forming, using a processor, a tag based on contextual user data related to the user input; and providing, using a processor, an indication of the tag. 6. The method of claim 1 , further comprising: determining user interaction with the indication of the tag; and providing output containing contextual data of the tag to the user.
| 0.676154 |
4. The method of claim 2 , further comprising: interpreting the script to produce one or more prompts; and sending the one or more prompts to the media communications server.
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4. The method of claim 2 , further comprising: interpreting the script to produce one or more prompts; and sending the one or more prompts to the media communications server. 10. The method of claim 4 , wherein the one or more prompts comprise a voice recognition instruction, the method further comprising: instructing the media communications server to play the voice recognition instruction; and receiving a voice recognition result.
| 0.823359 |
1. A mobile communication terminal having a mobile flash mounted thereto, comprising: a mobile input device section to input a reproduction request of a flash movie; a Man Machine Interface (MMI) to load a corresponding movie file based on the reproduction request; a communication bridge module to perform a communication with the MMI to monitor navigation events; a memory section to store configuration information of the mobile communication terminal; a mobile flash engine section to parse the configuration information read from the memory section to map the flash movie with the configuration information, and to analyze the parsed configuration information according to the navigation events; and a mobile flash play section to output the mapped contents through a display section.
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1. A mobile communication terminal having a mobile flash mounted thereto, comprising: a mobile input device section to input a reproduction request of a flash movie; a Man Machine Interface (MMI) to load a corresponding movie file based on the reproduction request; a communication bridge module to perform a communication with the MMI to monitor navigation events; a memory section to store configuration information of the mobile communication terminal; a mobile flash engine section to parse the configuration information read from the memory section to map the flash movie with the configuration information, and to analyze the parsed configuration information according to the navigation events; and a mobile flash play section to output the mapped contents through a display section. 4. The mobile communication terminal according to claim 1 , further comprising a mobile platform interface section to receive and to transfer the analyzed information from the mobile flash engine section to mobile flash play section.
| 0.558273 |
11. The processor readable non-transitory medium of claim 10 having processor executable instructions thereon, which when executed by a processor further cause the processor to: receive, as input into a document set of the workflow instance, one or more documents from an input activity of the workflow instance, the input comprising: document metadata associated with the one or more documents comprising the document set; select, by an output activity of the workflow instance, the one or more documents from the document set for input by designating the document metadata corresponding to the one or more documents; and select, by a processing activity of the workflow instance, the one or more documents from the document set to input by designating the corresponding document metadata.
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11. The processor readable non-transitory medium of claim 10 having processor executable instructions thereon, which when executed by a processor further cause the processor to: receive, as input into a document set of the workflow instance, one or more documents from an input activity of the workflow instance, the input comprising: document metadata associated with the one or more documents comprising the document set; select, by an output activity of the workflow instance, the one or more documents from the document set for input by designating the document metadata corresponding to the one or more documents; and select, by a processing activity of the workflow instance, the one or more documents from the document set to input by designating the corresponding document metadata. 12. The processor readable non-transitory medium of claim 11 having processor executable instructions thereon, which when executed by a processor further cause the processor to designate a store location or a storage container for the workflow instance.
| 0.782764 |
16. The method of claim 11 further comprising: responding to receipt of a command to execute the second software, by instantiating the first software to obtain an instance and invoking a script engine with the instance passed in its entirety as a parameter, to execute the first method of the first name in the first software during execution of the second software.
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16. The method of claim 11 further comprising: responding to receipt of a command to execute the second software, by instantiating the first software to obtain an instance and invoking a script engine with the instance passed in its entirety as a parameter, to execute the first method of the first name in the first software during execution of the second software. 17. The method of claim 16 wherein: the first software is executed in combination with an initial version of second software prior to preparation and storage of the new instruction; and the first software is executed unchanged in combination with a current version of second software subsequent to preparation and storage of the new instruction.
| 0.891195 |
9. A computer readable storage medium containing a program which, when executed by one or more processors, performs a method for managing relationships between logical fields in a data abstraction model, wherein the logical fields correspond to physical fields in a database, the operation comprising: accessing a structure with links between logical branches of the data abstraction model defining logical fields, wherein some of logical fields share a common name, wherein the links allow for the joining of data structures containing the physical fields when executing an abstract query containing a reference to a common name shared by multiple logical fields, and wherein each link defines a path between different data structures of a physical representation of the data in the database; and transforming the abstract query into an executable query using the accessed structure, wherein transforming comprises generating logic to join a plurality of the data structures as defined by the one or more links.
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9. A computer readable storage medium containing a program which, when executed by one or more processors, performs a method for managing relationships between logical fields in a data abstraction model, wherein the logical fields correspond to physical fields in a database, the operation comprising: accessing a structure with links between logical branches of the data abstraction model defining logical fields, wherein some of logical fields share a common name, wherein the links allow for the joining of data structures containing the physical fields when executing an abstract query containing a reference to a common name shared by multiple logical fields, and wherein each link defines a path between different data structures of a physical representation of the data in the database; and transforming the abstract query into an executable query using the accessed structure, wherein transforming comprises generating logic to join a plurality of the data structures as defined by the one or more links. 13. The computer readable storage medium of claim 9 , wherein the physical representation is a relational representation.
| 0.570603 |
15. A computer program product for summarizing a first unit of text data with relation to the contents of multiple documents in an existing document collection, the computer program product including a computer-readable medium encoded with computer program instructions, wherein the computer program instructions, when executed by a processor, cause the processor to perform predetermined operations comprising: creating a subspace for the existing document collection without first posting a query, an input involving latent semantic indexing; performing one of a domain driven text summarization, an example type query driven text summarization, and a term type query driven text summarization on a selected document; recomposing a vector using a projection in the subspace representing the contents of multiple documents in the existing document collection when performing the domain driven text summarization or the example type query driven text summarization; computing term relationships representing similarities between query terms and the contents of multiple documents in the existing document collection using a term-term matrix associated with an original term space when performing the term type query driven text summarization; computing a term weight that is representative of the relevance of a term to a second unit of text data with relation to the contents of multiple documents in the document collection, the computing of the term weight including generation of the subspace using the document collection for projection of the text data into the subspace and back into term space in order to get weights for all the terms in the document collection; comparing the computed term weight to a predetermined threshold; returning a relevant term based at least in part on a result of the comparison; summing a plurality of relevant term weights based on a number of occurrences of a plurality of corresponding relevant terms in a segment of the first unit of text data; comparing a plurality of summations based on a plurality of corresponding segments of the first unit of text data to identify a text summarization segment; and returning the text summarization segment.
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15. A computer program product for summarizing a first unit of text data with relation to the contents of multiple documents in an existing document collection, the computer program product including a computer-readable medium encoded with computer program instructions, wherein the computer program instructions, when executed by a processor, cause the processor to perform predetermined operations comprising: creating a subspace for the existing document collection without first posting a query, an input involving latent semantic indexing; performing one of a domain driven text summarization, an example type query driven text summarization, and a term type query driven text summarization on a selected document; recomposing a vector using a projection in the subspace representing the contents of multiple documents in the existing document collection when performing the domain driven text summarization or the example type query driven text summarization; computing term relationships representing similarities between query terms and the contents of multiple documents in the existing document collection using a term-term matrix associated with an original term space when performing the term type query driven text summarization; computing a term weight that is representative of the relevance of a term to a second unit of text data with relation to the contents of multiple documents in the document collection, the computing of the term weight including generation of the subspace using the document collection for projection of the text data into the subspace and back into term space in order to get weights for all the terms in the document collection; comparing the computed term weight to a predetermined threshold; returning a relevant term based at least in part on a result of the comparison; summing a plurality of relevant term weights based on a number of occurrences of a plurality of corresponding relevant terms in a segment of the first unit of text data; comparing a plurality of summations based on a plurality of corresponding segments of the first unit of text data to identify a text summarization segment; and returning the text summarization segment. 22. The computer program product of claim 15 , wherein the step of computing further comprises recomposing a vector representation in the original term space, the vector representation being based at least in part on a projection of an original vector representation in a predetermined vector subspace.
| 0.639403 |
12. A method of communicating between a first computer protected by a first firewall and a second computer protected by a different second firewall via a third intermediate computer, comprising the steps of: receiving at the third intermediate computer a request transmitted from the second computer through the second firewall, wherein the request is to establish a receive channel between the second computer and the third intermediate computer; transmitting from the third intermediate computer a response to the request, the response establishing a receive channel between the third intermediate computer and the second computer that is to be kept open for subsequent transmissions by the third intermediate computer; receiving at the third intermediate computer data transmitted from the first computer through the first firewall via a network connection initiated by the first computer; determining that the data received from the first computer is intended to be delivered to the second computer; and transmitting the data to the second computer via the receive channel, wherein the data received from the first computer comprises an HTTP message encrypted using encryption keys shared between the first computer and the third intermediate computer, and wherein the third intermediate computer decrypts the HTTP message received from the first computer and re-encrypts the HTTP message using encryption keys shared between the third intermediate computer and the second computer.
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12. A method of communicating between a first computer protected by a first firewall and a second computer protected by a different second firewall via a third intermediate computer, comprising the steps of: receiving at the third intermediate computer a request transmitted from the second computer through the second firewall, wherein the request is to establish a receive channel between the second computer and the third intermediate computer; transmitting from the third intermediate computer a response to the request, the response establishing a receive channel between the third intermediate computer and the second computer that is to be kept open for subsequent transmissions by the third intermediate computer; receiving at the third intermediate computer data transmitted from the first computer through the first firewall via a network connection initiated by the first computer; determining that the data received from the first computer is intended to be delivered to the second computer; and transmitting the data to the second computer via the receive channel, wherein the data received from the first computer comprises an HTTP message encrypted using encryption keys shared between the first computer and the third intermediate computer, and wherein the third intermediate computer decrypts the HTTP message received from the first computer and re-encrypts the HTTP message using encryption keys shared between the third intermediate computer and the second computer. 13. The method of claim 12 , wherein decrypting the HTTP message comprises decrypting encrypted header information, the encrypted header information comprising one or more of an encrypted IP address, an encrypted username of said second computer, an encrypted header length, an encrypted message length, an encrypted application identifier, an encrypted time and date stamp, and an encrypted message type.
| 0.598066 |
6. A method comprising: generating, at a social networking system, a structured query based on information received from a user, the structured query including a focal search object and a connected search object; updating a reverse index to include an identifier for structured query, the reverse index storing a plurality of structured query identifiers based on focal search objects and the connected search objects in the structured queries; receiving an action; accessing the reverse index to determine whether the received action causes an object maintained by the social networking system to match the structured query; and responsive to determining that the received action causes the object to match the structured query, storing a link to the object in association with the structured query.
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6. A method comprising: generating, at a social networking system, a structured query based on information received from a user, the structured query including a focal search object and a connected search object; updating a reverse index to include an identifier for structured query, the reverse index storing a plurality of structured query identifiers based on focal search objects and the connected search objects in the structured queries; receiving an action; accessing the reverse index to determine whether the received action causes an object maintained by the social networking system to match the structured query; and responsive to determining that the received action causes the object to match the structured query, storing a link to the object in association with the structured query. 13. The method of claim 6 , further comprising: responsive to storing the link to the object in association with the structured query, incrementing a notification count for the structured query.
| 0.622791 |
1. A non-transitory computer-readable media comprising instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: receiving a first handwriting input from a user, the first handwriting input comprising a plurality of handwritten strokes distributed along a respective writing direction associated with a handwriting input area of a handwriting input interface; rendering each of the plurality of handwritten strokes in the handwriting input area as the handwritten stroke is provided by the user; starting a respective fading process for the plurality of handwritten strokes of the first handwriting input, wherein during the respective fading process, the rendering of the plurality of handwritten strokes in the handwriting input area becomes increasingly faded; receiving a second handwriting input from the user over a region of the handwriting input area occupied by a faded plurality of handwritten strokes of the first handwriting input; and in response to receiving the second handwriting input: rendering the second handwriting input in the handwriting input area; and clearing all the faded plurality of handwritten strokes of the first handwriting input from the handwriting input area.
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1. A non-transitory computer-readable media comprising instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: receiving a first handwriting input from a user, the first handwriting input comprising a plurality of handwritten strokes distributed along a respective writing direction associated with a handwriting input area of a handwriting input interface; rendering each of the plurality of handwritten strokes in the handwriting input area as the handwritten stroke is provided by the user; starting a respective fading process for the plurality of handwritten strokes of the first handwriting input, wherein during the respective fading process, the rendering of the plurality of handwritten strokes in the handwriting input area becomes increasingly faded; receiving a second handwriting input from the user over a region of the handwriting input area occupied by a faded plurality of handwritten strokes of the first handwriting input; and in response to receiving the second handwriting input: rendering the second handwriting input in the handwriting input area; and clearing all the faded plurality of handwritten strokes of the first handwriting input from the handwriting input area. 4. The media of claim 1 , wherein the respective fading process for each recognition unit is started when a predetermined time period has elapsed after the recognition unit is completed by the user.
| 0.645699 |
1. A computer-implemented method comprising: a) accepting, for each of at least one advertiser, by an advertising system including one or more computers, information from at least one advertiser document, wherein the at least one advertiser document defines an inventory of at least one of products and services offered on an online Website of the at least one advertiser; b) generating ads for the at least one advertiser, by the advertising system, each of the generated ads including i) a creative, and ii) offer information, using the accepted information from the at least one advertiser document; c) generating, by the advertising system, an index mapping information extracted from the at least one advertiser document to one of (A) advertiser document identifiers for the at least one advertiser document on which the extracted information is found, and (B) ad identifiers for ads generated from the at least one advertiser document on which the extracted information is found; d) accepting, by the advertising system, additional information, wherein the additional information is one of (A) search query information and (B) document relevance information; e) determining, by the advertising system, one or more ads relevant to the additional information using the index generated and the additional information; and f) serving at least one of the determined one or more relevant ads for rendering on a client device, wherein the offer information is expressed procedurally.
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1. A computer-implemented method comprising: a) accepting, for each of at least one advertiser, by an advertising system including one or more computers, information from at least one advertiser document, wherein the at least one advertiser document defines an inventory of at least one of products and services offered on an online Website of the at least one advertiser; b) generating ads for the at least one advertiser, by the advertising system, each of the generated ads including i) a creative, and ii) offer information, using the accepted information from the at least one advertiser document; c) generating, by the advertising system, an index mapping information extracted from the at least one advertiser document to one of (A) advertiser document identifiers for the at least one advertiser document on which the extracted information is found, and (B) ad identifiers for ads generated from the at least one advertiser document on which the extracted information is found; d) accepting, by the advertising system, additional information, wherein the additional information is one of (A) search query information and (B) document relevance information; e) determining, by the advertising system, one or more ads relevant to the additional information using the index generated and the additional information; and f) serving at least one of the determined one or more relevant ads for rendering on a client device, wherein the offer information is expressed procedurally. 24. The computer-implemented method of claim 1 , further comprising: g) generating, by the advertising system, another index mapping one of (A) advertiser document identifiers and (B) ad identifiers for ads generated from the at least one advertiser document, to information extracted from the at least one advertiser document.
| 0.619638 |
1. A method of converting strings to a common language comprising: determining a user-selected target language; associating a user-selected primary input language and at least one user-selected secondary input language with the target language, wherein the target language is common to, and different from, the primary input language and the at least one secondary input language; obtaining a string of at least one character; converting the obtained string from the primary input language to the target language if the obtained string corresponds to a valid string in the primary input language by using a phonetic lexicon to interpret the obtained string in the target language based upon a phonetic correspondence of the obtained string in the primary input language; converting the obtained string from at least one secondary input language to the target language if the obtained string corresponds to a valid string in the corresponding secondary input language and is not a valid string in the primary input language by using a translation lexicon to translate the obtained string from the secondary language to the target language; and outputting the converted string in the target language to an output device.
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1. A method of converting strings to a common language comprising: determining a user-selected target language; associating a user-selected primary input language and at least one user-selected secondary input language with the target language, wherein the target language is common to, and different from, the primary input language and the at least one secondary input language; obtaining a string of at least one character; converting the obtained string from the primary input language to the target language if the obtained string corresponds to a valid string in the primary input language by using a phonetic lexicon to interpret the obtained string in the target language based upon a phonetic correspondence of the obtained string in the primary input language; converting the obtained string from at least one secondary input language to the target language if the obtained string corresponds to a valid string in the corresponding secondary input language and is not a valid string in the primary input language by using a translation lexicon to translate the obtained string from the secondary language to the target language; and outputting the converted string in the target language to an output device. 2. The method according to claim 1 , wherein: obtaining a string comprises obtaining at least one character entered into a computer using a keyboard; further comprising: performing an iterative process if the obtained string is not converted from the primary input language to the target language by: obtaining a next keyboard entry modifying the string; attempting to convert the modified string from the primary input language to the target language; determining if the string is complete; and ending the iterative process if the modified string is determined to be complete.
| 0.641471 |
1. A method comprising: receiving an arbitrary natural language communication from a user; applying a concept recognition process to automatically derive a representation of concepts embodied in the communication; using the concept representation to provide to a human agent information useful in responding to the natural language communication, wherein the information provided to the human agent includes a plurality of possible responses to the user's communication; enabling the human agent to select a response from the plurality of possible responses; and delivering the selected response to the user.
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1. A method comprising: receiving an arbitrary natural language communication from a user; applying a concept recognition process to automatically derive a representation of concepts embodied in the communication; using the concept representation to provide to a human agent information useful in responding to the natural language communication, wherein the information provided to the human agent includes a plurality of possible responses to the user's communication; enabling the human agent to select a response from the plurality of possible responses; and delivering the selected response to the user. 2. The method of claim 1 in which the arbitrary natural language communication is expressed in speech.
| 0.717735 |
1. A system for facilitating transactions comprising: a computing system, having a processor and a memory, for executing programmable instructions that implement a data store, the data store including processing information associated with one or more transaction phrase tokens, wherein the one or more transaction phrase tokens are associated with transaction accounts via the processing information, and wherein at least one transaction phrase token of the one or more transaction phrase tokens consists of an unambiguous set of characters selected in its entirety by a transaction phrase token holder; and a computing system, having a processor and a memory, for executing programmable instructions that implement a transaction phrase token processing service, the transaction phrase token processing service processing a request from a requestor to complete a transaction related to a good or service, wherein the request includes a representation of a selected transaction phrase token provided verbally or in writing by a transaction phrase token holder to the requestor, wherein the transaction phrase token processing service accesses the processing information associated with the selected transaction phrase token, wherein the processing information associated with the selected transaction phrase token: identifies a transaction account associated with the selected transaction phrase token based on a transaction account identifier distinct from the selected transaction phrase token, and comprises one or more rules for processing transactions related to goods or services, and wherein the transaction phrase token processing service: identifies a rule from the one or more rules included in the processing information, wherein the identified rule is associated with the good or service related to the request; processes the request using the identified rule; sends an approval request to the transaction phrase token holder regarding the processed request; receives a response to the approval request from the transaction phrase token holder; updates the identified rule based at least in part on the response to the approval request that is received from the transaction phrase token holder; and automatically accepts or rejects a subsequent request to complete a transaction based at least in part on the update of the identified rule.
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1. A system for facilitating transactions comprising: a computing system, having a processor and a memory, for executing programmable instructions that implement a data store, the data store including processing information associated with one or more transaction phrase tokens, wherein the one or more transaction phrase tokens are associated with transaction accounts via the processing information, and wherein at least one transaction phrase token of the one or more transaction phrase tokens consists of an unambiguous set of characters selected in its entirety by a transaction phrase token holder; and a computing system, having a processor and a memory, for executing programmable instructions that implement a transaction phrase token processing service, the transaction phrase token processing service processing a request from a requestor to complete a transaction related to a good or service, wherein the request includes a representation of a selected transaction phrase token provided verbally or in writing by a transaction phrase token holder to the requestor, wherein the transaction phrase token processing service accesses the processing information associated with the selected transaction phrase token, wherein the processing information associated with the selected transaction phrase token: identifies a transaction account associated with the selected transaction phrase token based on a transaction account identifier distinct from the selected transaction phrase token, and comprises one or more rules for processing transactions related to goods or services, and wherein the transaction phrase token processing service: identifies a rule from the one or more rules included in the processing information, wherein the identified rule is associated with the good or service related to the request; processes the request using the identified rule; sends an approval request to the transaction phrase token holder regarding the processed request; receives a response to the approval request from the transaction phrase token holder; updates the identified rule based at least in part on the response to the approval request that is received from the transaction phrase token holder; and automatically accepts or rejects a subsequent request to complete a transaction based at least in part on the update of the identified rule. 9. The system as recited in claim 1 , wherein the transaction phrase token processing service further updates the processing information based upon receipt of a rejection by the transaction phrase token holder corresponding to the at least one transaction phrase token.
| 0.540855 |
11. A computer program product comprising a non-transitory computer-readable medium having control logic stored therein for causing a computer to assess and manage a work-related musculoskeletal injury associated with at least one work site, the control logic comprising computer-readable program code for causing the computer to: receive musculoskeletal injury categories; structure storage of relationships between the musculoskeletal injury categories by tabulating a table structure that facilitates computational linkage between specific musculoskeletal injury categories and generalized musculoskeletal injury categories, wherein tabulating the table structure comprises joining, to the table structure, at least one of the following: a doctor-patient diagnosis history table, a patient corrective procedures table, demographic data, statistical data, and occupational data; draw relationships between the musculoskeletal injury categories and current procedural terminology by applying specialized medical knowledge, wherein the relationships between the musculoskeletal injury categories and the current procedural terminology comprises drawing relationships between specific procedural terminology and generalized procedural terminology, the relationships being determined, at least in part, by analyzing the table structure to determine trends, the trends being indicative of the relationships between the musculoskeletal injury categories and the current procedural terminology; gather for each work site, statistics on work-related musculoskeletal injuries associated with a relatively high frequency; and utilize the relationships and the statistics to compile and retrieve data that facilitates improved work-related musculoskeletal injury resolution wherein improved work-related musculoskeletal injury resolution comprises at least one of the following: effective treatment of the work-related musculoskeletal injury; faster resolution and payment of an insurance claim associated with the work-related musculoskeletal injury; reduction in lost work time associated with the work-related musculoskeletal injury; and reduction in medical cost associated with the work-related musculoskeletal injury.
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11. A computer program product comprising a non-transitory computer-readable medium having control logic stored therein for causing a computer to assess and manage a work-related musculoskeletal injury associated with at least one work site, the control logic comprising computer-readable program code for causing the computer to: receive musculoskeletal injury categories; structure storage of relationships between the musculoskeletal injury categories by tabulating a table structure that facilitates computational linkage between specific musculoskeletal injury categories and generalized musculoskeletal injury categories, wherein tabulating the table structure comprises joining, to the table structure, at least one of the following: a doctor-patient diagnosis history table, a patient corrective procedures table, demographic data, statistical data, and occupational data; draw relationships between the musculoskeletal injury categories and current procedural terminology by applying specialized medical knowledge, wherein the relationships between the musculoskeletal injury categories and the current procedural terminology comprises drawing relationships between specific procedural terminology and generalized procedural terminology, the relationships being determined, at least in part, by analyzing the table structure to determine trends, the trends being indicative of the relationships between the musculoskeletal injury categories and the current procedural terminology; gather for each work site, statistics on work-related musculoskeletal injuries associated with a relatively high frequency; and utilize the relationships and the statistics to compile and retrieve data that facilitates improved work-related musculoskeletal injury resolution wherein improved work-related musculoskeletal injury resolution comprises at least one of the following: effective treatment of the work-related musculoskeletal injury; faster resolution and payment of an insurance claim associated with the work-related musculoskeletal injury; reduction in lost work time associated with the work-related musculoskeletal injury; and reduction in medical cost associated with the work-related musculoskeletal injury. 15. The computer program product of claim 11 , wherein the computer-readable program code for causing the computer to draw relationships between the musculoskeletal injury categories comprises computer-readable program code for causing the computer to delineate a type of relationships between international classification of disease (ICD) codes wherein the type of relationship comprises at least one of the following: a parent-child relationship wherein one parent ICD code represents a general condition that can be caused by a more specific condition represented by a child ICD code; a sibling-sibling relationship wherein at least two ICD codes represent conditions of an equal level of specificity and are related one of the following: commonly coupled symptoms and commonly confused diagnoses; and a relative-distant relative relationship comprising a relationship drawn between diagnoses that does not fit one of the following: the parent-child and the sibling-sibling relationship.
| 0.5 |
9. A system for recommending content items, the system comprising: a hardware processor that: determines a plurality of accessed content items associated with a user, wherein each of a plurality of content items is associated with a plurality of topics; determines the plurality of topics associated with each of the plurality of accessed content items; generates a model of user interests based on the plurality of topics, wherein the model implements a machine learning technique to determine a plurality of weights for assigning to each of the plurality of topics and wherein the model of user interests is generated by: retrieving a user interest profile that includes the plurality of topics associated with the plurality of content items accessed by the user and a plurality of other user interest profiles; generating a decision tree, wherein a portion of the decision tree identifies which of the plurality of other user interest profiles are similar to the user interest profile; determining a subset of the plurality of topics corresponding to the user interest profile and the similar user interest profiles in the portion of the decision tree; and determining a conjunction that models interaction between the subset of the plurality of topics and the plurality of content items; applies the model to determine, for the plurality of content items, a probability that the user watches a content item of the plurality of content items; ranks the plurality of content items based on the determined probability; and selects a subset of the plurality of content items to recommend to the user based on the ranked plurality of content items.
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9. A system for recommending content items, the system comprising: a hardware processor that: determines a plurality of accessed content items associated with a user, wherein each of a plurality of content items is associated with a plurality of topics; determines the plurality of topics associated with each of the plurality of accessed content items; generates a model of user interests based on the plurality of topics, wherein the model implements a machine learning technique to determine a plurality of weights for assigning to each of the plurality of topics and wherein the model of user interests is generated by: retrieving a user interest profile that includes the plurality of topics associated with the plurality of content items accessed by the user and a plurality of other user interest profiles; generating a decision tree, wherein a portion of the decision tree identifies which of the plurality of other user interest profiles are similar to the user interest profile; determining a subset of the plurality of topics corresponding to the user interest profile and the similar user interest profiles in the portion of the decision tree; and determining a conjunction that models interaction between the subset of the plurality of topics and the plurality of content items; applies the model to determine, for the plurality of content items, a probability that the user watches a content item of the plurality of content items; ranks the plurality of content items based on the determined probability; and selects a subset of the plurality of content items to recommend to the user based on the ranked plurality of content items. 11. The system of claim 9 , wherein the processor is further configured to: select the subset of the plurality of topics associated with each of the plurality of content items, wherein the subset of the plurality of topics is selected based on the plurality of assigned weights.
| 0.62338 |
3. The computer readable medium of claim 2, wherein said sequence of instructions further comprise: parsing each subdocument into a plurality of terms; and generating a term list that associates each term with said subdocument that includes that term.
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3. The computer readable medium of claim 2, wherein said sequence of instructions further comprise: parsing each subdocument into a plurality of terms; and generating a term list that associates each term with said subdocument that includes that term. 4. The computer readable medium of claim 3, wherein said sequence of instructions further comprise: selecting a plurality of terms; and linking said terms by a logical operator.
| 0.83313 |
1. A computer implemented method of detecting global variables in JAVASCRIPT code, and adding local variables in place of said global variables, comprising: receiving by a processor a JAVASCRIPT code containing at least one of a plurality of globally defined functions; generating by the processor at least one call flow graph for each one of said at least one of globally defined functions; generating by the processor an inter-procedural control flow graph for each one of said call flow graph; generating by the processor an inter-procedural dominator graph for each one of said inter-procedural control flow graph; identifying by the processor each of referenced global variables within each of said inter-procedural dominator graph and determining a JAVASCRIPT scope of each of referenced global variables; identifying by the processor at least one of: one or more confined global variables which receive a value within a first JAVASCRIPT scope of each referenced global variable wherein said value is not referenced outside of said first JAVASCRIPT scope, and one or more repeating global variables accessed repeatedly within a second JAVASCRIPT scope of each referenced global variable; and automatically adding by the processor local variables in place of at least one of said confined global variables and said repeating global variables.
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1. A computer implemented method of detecting global variables in JAVASCRIPT code, and adding local variables in place of said global variables, comprising: receiving by a processor a JAVASCRIPT code containing at least one of a plurality of globally defined functions; generating by the processor at least one call flow graph for each one of said at least one of globally defined functions; generating by the processor an inter-procedural control flow graph for each one of said call flow graph; generating by the processor an inter-procedural dominator graph for each one of said inter-procedural control flow graph; identifying by the processor each of referenced global variables within each of said inter-procedural dominator graph and determining a JAVASCRIPT scope of each of referenced global variables; identifying by the processor at least one of: one or more confined global variables which receive a value within a first JAVASCRIPT scope of each referenced global variable wherein said value is not referenced outside of said first JAVASCRIPT scope, and one or more repeating global variables accessed repeatedly within a second JAVASCRIPT scope of each referenced global variable; and automatically adding by the processor local variables in place of at least one of said confined global variables and said repeating global variables. 6. The method of claim 1 , further comprising identifying said JAVASCRIPT scope of said referenced global variables within a node of said inter-procedural dominator graph by a text search of said inter-procedural dominator graph wherein JAVASCRIPT keywords and/or JAVASCRIPT syntax are used to identify references to global variables.
| 0.821809 |
1. A method of securing a display of advertisements on web browsers while handling an interpreted markup file in an operating system of a computer device, the method comprising: receiving, in response to a request for a web page by a requestor, a markup file and interpreting the markup file in a virtual machine, the markup file comprising a first scripting language code and a set of displayable elements of the web page; converting the set of displayable elements of the markup file interpreted in the virtual machine to a modified markup file including a second scripting language code and the set of displayable elements in the form of at least one corresponding image; and serving the image to the requestor as the web page, wherein the web page served as the image includes an interactive function, which can be performed by the requestor, which mirrors an original interactive function that can be performed on the web page when not served as an image; wherein a decision to convert and serve the web page as an image is independent of any action by the requestor.
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1. A method of securing a display of advertisements on web browsers while handling an interpreted markup file in an operating system of a computer device, the method comprising: receiving, in response to a request for a web page by a requestor, a markup file and interpreting the markup file in a virtual machine, the markup file comprising a first scripting language code and a set of displayable elements of the web page; converting the set of displayable elements of the markup file interpreted in the virtual machine to a modified markup file including a second scripting language code and the set of displayable elements in the form of at least one corresponding image; and serving the image to the requestor as the web page, wherein the web page served as the image includes an interactive function, which can be performed by the requestor, which mirrors an original interactive function that can be performed on the web page when not served as an image; wherein a decision to convert and serve the web page as an image is independent of any action by the requestor. 12. The method of claim 1 , wherein the set of displayable elements includes at least one advertisement.
| 0.612069 |
1. A method for career matching assessment, comprising: accessing on an application on a target network device with one or more processors from a server network device with one or more processors via a communications network, one or more electronic questionnaires created for a selected job opening for a first job seeker, the one or more electronic questionnaires including: (1) a plurality of non-self assessment questions for the first job seeker that are answered by the seekers as if the first job seeker were actually an employer offering the selected job opening instead of the job seeker seeking the selected job opening and (2) a plurality of general questions that focus on different aspects of a working environment and working relationships and do not access any underlying personality traits of the first job seekers; sending the one or more electronic questionnaires completed on the application on the target network device for the first job seeker to the server network device via the communications network for the selected job opening; processing the completed one or more electronic questionnaires from first job seeker on the server network device to create a first electronic profile for the first job seeker, wherein the created first electronic profile measures attributes of models of working environments, problem solving, communication and inter-personal skills related to job performance and job satisfaction for the first job seeker for the selected job opening; invoking a matching process to assess an amount of overlap between the created first electronic profile for the first job seeker and a plurality of other electronic profiles of created by a plurality of other job seekers and the employer profile created by an employer for the selected job opening; creating an electronic priority list from the assessed amount of overlap to list job seeker candidates in rank order for the selected job opening most desirable to the employer, wherein the priority list includes a prediction of job performance, job satisfaction and long term job retention for the job seeker candidates for the selected job opening for the employer; sending an automatic notification from the server network device to the application on the target network device via the communications network to indicate a priority ranking for the selected job opening for the job seeker; and displaying with the application on the target network device the automatic notification to indicate a priority ranking for the selected job opening for the job seeker.
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1. A method for career matching assessment, comprising: accessing on an application on a target network device with one or more processors from a server network device with one or more processors via a communications network, one or more electronic questionnaires created for a selected job opening for a first job seeker, the one or more electronic questionnaires including: (1) a plurality of non-self assessment questions for the first job seeker that are answered by the seekers as if the first job seeker were actually an employer offering the selected job opening instead of the job seeker seeking the selected job opening and (2) a plurality of general questions that focus on different aspects of a working environment and working relationships and do not access any underlying personality traits of the first job seekers; sending the one or more electronic questionnaires completed on the application on the target network device for the first job seeker to the server network device via the communications network for the selected job opening; processing the completed one or more electronic questionnaires from first job seeker on the server network device to create a first electronic profile for the first job seeker, wherein the created first electronic profile measures attributes of models of working environments, problem solving, communication and inter-personal skills related to job performance and job satisfaction for the first job seeker for the selected job opening; invoking a matching process to assess an amount of overlap between the created first electronic profile for the first job seeker and a plurality of other electronic profiles of created by a plurality of other job seekers and the employer profile created by an employer for the selected job opening; creating an electronic priority list from the assessed amount of overlap to list job seeker candidates in rank order for the selected job opening most desirable to the employer, wherein the priority list includes a prediction of job performance, job satisfaction and long term job retention for the job seeker candidates for the selected job opening for the employer; sending an automatic notification from the server network device to the application on the target network device via the communications network to indicate a priority ranking for the selected job opening for the job seeker; and displaying with the application on the target network device the automatic notification to indicate a priority ranking for the selected job opening for the job seeker. 10. The method of claim 1 wherein questions on the one or more electronic questionnaires do not assess any underlying personality traits of the employer providing the selected job opening.
| 0.591182 |
16. A method for a thorough search of a hyperlinked document database, comprising the steps of: receiving a search request including search parameters and a search starting point; adding documents found at the search starting point and within a distance factor to the search starting point to a processing list; if a respective document in the processing list is a compressed document, decompressing the document to produce a plain text version of the document; searching the documents according to the search parameters and for references to other documents to append to the processing list; and returning a list of processed documents which meet the search criteria to a user.
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16. A method for a thorough search of a hyperlinked document database, comprising the steps of: receiving a search request including search parameters and a search starting point; adding documents found at the search starting point and within a distance factor to the search starting point to a processing list; if a respective document in the processing list is a compressed document, decompressing the document to produce a plain text version of the document; searching the documents according to the search parameters and for references to other documents to append to the processing list; and returning a list of processed documents which meet the search criteria to a user. 19. The method as recited in claim 16 wherein the distance factor is a number of hyperlinks traveled from a document at the original starting point.
| 0.673006 |
12. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving a search query from a user, the user having a plurality of social affinity groups, each social affinity group identifying a group of users and the user as a proper subset of users of a network; receiving search results responsive to the search query, each search result referencing a corresponding resource that is determined to be responsive to the search query; identifying search results referencing resources that each have an association with one or more of the social affinity groups, where each association corresponds to one of a plurality of association types, each of the plurality of association types specifying one of a plurality of user actions performed by one or more different users of the one or more social affinity groups, the user actions including a user creation of an associated resource and a user endorsement of an associated resource; selecting one of the identified search results for annotation, wherein the selection is based in part on a pre-determined hierarchy of association types that specifies a different priority for each user action specified by an association type, and the selected search result has an association that corresponds to an association type with a highest priority among association types of the associations of the identified search results; annotating the selected search result, the annotation describing the association of one of the social affinity groups with the resource the selected search result references, and further identifying the social affinity group, the annotation comprising: determining a number of users that are members of the one of the social affinity groups; for each of a plurality of annotation terms, wherein each annotation term describes a relative threshold of a number of users that are members of the one of the social affinity groups, determining a target threshold for the annotation term, and wherein the target threshold for each annotation term is different from the target threshold for each other annotation term; determining, for each annotation term of the plurality of annotation terms, a threshold value based, at least in part, on the number of users that are members of the one of the social affinity groups and the target threshold for the annotation term; comparing the number of users that are members of the one of the social affinity groups to the threshold values; and applying, as the annotation, the annotation term having a target threshold that is i) less than the number of users that are members of the one of the social affinity groups and ii) that is greater than each other target threshold this is less than the number of users that are members of the one of the social affinity groups; and presenting the annotated search result to the user.
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12. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by data processing apparatus cause the data processing apparatus to perform operations comprising: receiving a search query from a user, the user having a plurality of social affinity groups, each social affinity group identifying a group of users and the user as a proper subset of users of a network; receiving search results responsive to the search query, each search result referencing a corresponding resource that is determined to be responsive to the search query; identifying search results referencing resources that each have an association with one or more of the social affinity groups, where each association corresponds to one of a plurality of association types, each of the plurality of association types specifying one of a plurality of user actions performed by one or more different users of the one or more social affinity groups, the user actions including a user creation of an associated resource and a user endorsement of an associated resource; selecting one of the identified search results for annotation, wherein the selection is based in part on a pre-determined hierarchy of association types that specifies a different priority for each user action specified by an association type, and the selected search result has an association that corresponds to an association type with a highest priority among association types of the associations of the identified search results; annotating the selected search result, the annotation describing the association of one of the social affinity groups with the resource the selected search result references, and further identifying the social affinity group, the annotation comprising: determining a number of users that are members of the one of the social affinity groups; for each of a plurality of annotation terms, wherein each annotation term describes a relative threshold of a number of users that are members of the one of the social affinity groups, determining a target threshold for the annotation term, and wherein the target threshold for each annotation term is different from the target threshold for each other annotation term; determining, for each annotation term of the plurality of annotation terms, a threshold value based, at least in part, on the number of users that are members of the one of the social affinity groups and the target threshold for the annotation term; comparing the number of users that are members of the one of the social affinity groups to the threshold values; and applying, as the annotation, the annotation term having a target threshold that is i) less than the number of users that are members of the one of the social affinity groups and ii) that is greater than each other target threshold this is less than the number of users that are members of the one of the social affinity groups; and presenting the annotated search result to the user. 13. The computer storage medium of claim 12 , wherein the plurality of association types includes two or more of: a creation type that indicates a resource was created by a corresponding social affinity group; an endorsement type that indicates a resource was endorsed by a corresponding social affinity group; a share type that indicates a resource was shared by a corresponding social affinity group; a tag type that indicates a resource was tagged by a corresponding social affinity group; or a comment type that indicates a resource was commented on by a corresponding social affinity group.
| 0.506204 |
1. A unified activity manager for use in a collaborative environment comprising: at least one computer system in which the unified activity manager executes; an activity list view provided by the unified activity manager, the activity list view comprising a hierarchical listing of activities; an activity view provided by the unified activity manager, the activity view comprising a rendering of properties associated with a selected activity in said activity list view; a persons and roles view displayed concurrently in a single screen with the activity view and provided by the unified activity manager, the persons and roles view comprising at least a listing of collaborators available for association with said selected activity in said activity list view; and, a placeholder management module coupled to the unified activity manager, the module comprising program code enabled to display a placeholder for a collaborator designated to perform a task in an activity in the activity view in lieu of reference to a specific collaborator.
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1. A unified activity manager for use in a collaborative environment comprising: at least one computer system in which the unified activity manager executes; an activity list view provided by the unified activity manager, the activity list view comprising a hierarchical listing of activities; an activity view provided by the unified activity manager, the activity view comprising a rendering of properties associated with a selected activity in said activity list view; a persons and roles view displayed concurrently in a single screen with the activity view and provided by the unified activity manager, the persons and roles view comprising at least a listing of collaborators available for association with said selected activity in said activity list view; and, a placeholder management module coupled to the unified activity manager, the module comprising program code enabled to display a placeholder for a collaborator designated to perform a task in an activity in the activity view in lieu of reference to a specific collaborator. 2. The unified activity manager of claim 1 , wherein said activity view further comprises a listing of collaborators associated with said selected activity in said activity list view, a listing of roles associated with said selected activity in said activity list view, a listing of resources associated with said selected activity in said activity list view, and a listing of events associated with said selected activity in said activity list view.
| 0.5 |
8. A non-transitory computer readable medium storing a computer program which when executed by at least one processor selects content in a document created from a template comprising a set of template pages preconfigured with fields and placeholder content, the computer program comprising sets of instructions for: displaying a page of the document based on one of the preconfigured template pages of the template used to create the document, said page comprising a field storing template-based placeholder content or storing user-generated content, wherein the preconfigured template pages are initially populated with the placeholder content that is replaceable with the user-generated content; receiving, at the document, a selection of a portion of the content, wherein the selection is based on a click operation within the field of either the placeholder content or user-generated content; and in response to receiving, at the document, the selection: determining whether the field contains the placeholder content or the user-generated content; when the field contains the placeholder content: automatically selecting within the field all of the placeholder content of the field when the selection comprises clicking on the placeholder content of the field; and when the field contains the user-generated content: selecting within the field only the portion of the user-generated content of the field.
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8. A non-transitory computer readable medium storing a computer program which when executed by at least one processor selects content in a document created from a template comprising a set of template pages preconfigured with fields and placeholder content, the computer program comprising sets of instructions for: displaying a page of the document based on one of the preconfigured template pages of the template used to create the document, said page comprising a field storing template-based placeholder content or storing user-generated content, wherein the preconfigured template pages are initially populated with the placeholder content that is replaceable with the user-generated content; receiving, at the document, a selection of a portion of the content, wherein the selection is based on a click operation within the field of either the placeholder content or user-generated content; and in response to receiving, at the document, the selection: determining whether the field contains the placeholder content or the user-generated content; when the field contains the placeholder content: automatically selecting within the field all of the placeholder content of the field when the selection comprises clicking on the placeholder content of the field; and when the field contains the user-generated content: selecting within the field only the portion of the user-generated content of the field. 9. The non-transitory computer readable medium of claim 8 , wherein the computer program further comprises sets of instructions for replacing, in response to an operation that provides other content for inserting in the page, the selected content of the field with the other provided content.
| 0.588251 |
19. The computer-readable storage medium of claim 18 , further comprising instructions for causing at least one programmable processor to perform operations comprising: sending at least one signal comprising an audio representation of the speech-recognized text to the audio communication device for output by the audio communication device.
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19. The computer-readable storage medium of claim 18 , further comprising instructions for causing at least one programmable processor to perform operations comprising: sending at least one signal comprising an audio representation of the speech-recognized text to the audio communication device for output by the audio communication device. 20. The computer-readable storage medium of claim 19 , further comprising instructions for causing the at least one programmable processor to perform operations comprising: receiving, by the computer, one or more signals corresponding to a correction to the speech-recognized text from the audio communication device; and modifying the speech-recognized text based on the correction to generate the output text.
| 0.878659 |
1. A method of operating an electronic device comprising the steps of: initiating entry of a content string by receiving a first key selection input, said first key corresponding to a first set of more than one textual characters; determining a most probable completion alternative using a personalized and learning database, said completion alternative being either (a) a most probable character selected from said first set of more than one textual characters or (b) a most probable sub-string, said sub-string beginning with said most probable character and including at least one additional character; displaying the most probable completion alternative in a content string entry line of a display of said electronic device; receiving a second input, said second input being either a second key corresponding to a second set of more than one textual characters or a selection key; and adding the most probable completion alternative to the content string entry line of said display for said second input being said selection key and said most probable completion alternative being the most probable sub-string, and adding a second completion alternative for said second input being said second key, said second completion alternative being a most probable second sub-string, said second sub-string beginning with said most probable first character and including said most probable second character and at least a most probable third character; wherein a user interface is provided that comprises a navigation key having a first set of controls, said first set of controls in an editing mode, for acceptance or non-acceptance of the most probable completion alternative currently displayed at the display and a second set of controls, said second set of controls in the editing mode, for changing or overriding the most probable completion alternative currently displayed at the display; wherein said first of controls are configured for scrolling a cursor right one character at a time or scrolling the cursor left one character at a time when said first set of controls are in a navigation mode; wherein said second set of controls are configured for scrolling the cursor down one line at a time or scrolling the cursor up one line at a time, when said second set of controls are in the navigation mode; and wherein: a right control of said first set of controls is configured for, in navigation mode and in a hold and press mode, jumping the cursor to the right one word at a time; a left control of said first set of controls is configured for, in navigation mode and in the hold and press mode, jumping the cursor left one word at a time; the left control being further configured for, in editing mode and in the hold and press mode, dismissing prediction and locking a last key press entry.
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1. A method of operating an electronic device comprising the steps of: initiating entry of a content string by receiving a first key selection input, said first key corresponding to a first set of more than one textual characters; determining a most probable completion alternative using a personalized and learning database, said completion alternative being either (a) a most probable character selected from said first set of more than one textual characters or (b) a most probable sub-string, said sub-string beginning with said most probable character and including at least one additional character; displaying the most probable completion alternative in a content string entry line of a display of said electronic device; receiving a second input, said second input being either a second key corresponding to a second set of more than one textual characters or a selection key; and adding the most probable completion alternative to the content string entry line of said display for said second input being said selection key and said most probable completion alternative being the most probable sub-string, and adding a second completion alternative for said second input being said second key, said second completion alternative being a most probable second sub-string, said second sub-string beginning with said most probable first character and including said most probable second character and at least a most probable third character; wherein a user interface is provided that comprises a navigation key having a first set of controls, said first set of controls in an editing mode, for acceptance or non-acceptance of the most probable completion alternative currently displayed at the display and a second set of controls, said second set of controls in the editing mode, for changing or overriding the most probable completion alternative currently displayed at the display; wherein said first of controls are configured for scrolling a cursor right one character at a time or scrolling the cursor left one character at a time when said first set of controls are in a navigation mode; wherein said second set of controls are configured for scrolling the cursor down one line at a time or scrolling the cursor up one line at a time, when said second set of controls are in the navigation mode; and wherein: a right control of said first set of controls is configured for, in navigation mode and in a hold and press mode, jumping the cursor to the right one word at a time; a left control of said first set of controls is configured for, in navigation mode and in the hold and press mode, jumping the cursor left one word at a time; the left control being further configured for, in editing mode and in the hold and press mode, dismissing prediction and locking a last key press entry. 2. The method of operating an electronic device as defined in claim 1 , further comprising the steps of: detecting a user input for going back in the content string after the adding step; and eliminating the most probable completion alternative from the content string.
| 0.562369 |
1. A method, comprising: using a computer to perform: collecting information about a user manipulation of a stylus in relation to a tablet device associated with the computer; recognizing, from the collected information, a stylus gesture performed by the user via manipulation of the stylus, such that: the stylus gesture is one of a plurality of stylus gestures that are recognized by the computer to perform at least one of a plurality of actions in a graphics application that comprises a natural media painting application, at least some of the stylus gestures are mapped to user manipulation of the stylus at a distance from the tablet device, at least some of the stylus gestures involve contact of the stylus with the tablet device, and the stylus gestures include a brush switching gesture in which a proximity of the stylus to the tablet changes from a first position relative to the tablet to a second position that is further away from the tablet and with at least a rate of change that corresponds to the brush switching gesture, the first position being within a first pre-defined distance threshold relative the tablet and the second position being beyond a second pre-defined distance threshold, and switching between paintbrushes of a brush tool being performed responsive to recognition of the brush switching gesture; determining which of the plurality of actions to perform based on the recognized stylus gesture; and performing a painting function for a digital image in the graphics application including performing the determined actions.
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1. A method, comprising: using a computer to perform: collecting information about a user manipulation of a stylus in relation to a tablet device associated with the computer; recognizing, from the collected information, a stylus gesture performed by the user via manipulation of the stylus, such that: the stylus gesture is one of a plurality of stylus gestures that are recognized by the computer to perform at least one of a plurality of actions in a graphics application that comprises a natural media painting application, at least some of the stylus gestures are mapped to user manipulation of the stylus at a distance from the tablet device, at least some of the stylus gestures involve contact of the stylus with the tablet device, and the stylus gestures include a brush switching gesture in which a proximity of the stylus to the tablet changes from a first position relative to the tablet to a second position that is further away from the tablet and with at least a rate of change that corresponds to the brush switching gesture, the first position being within a first pre-defined distance threshold relative the tablet and the second position being beyond a second pre-defined distance threshold, and switching between paintbrushes of a brush tool being performed responsive to recognition of the brush switching gesture; determining which of the plurality of actions to perform based on the recognized stylus gesture; and performing a painting function for a digital image in the graphics application including performing the determined actions. 8. The method of claim 1 , wherein the plurality of stylus gestures includes shaking the stylus towards the tablet, shaking the stylus away from the tablet, and twisting the stylus about the major axis of the stylus; and wherein the action that is performed in response to recognition of shaking the stylus towards the tablet includes splattering paint; wherein the action that is performed in response to recognition of shaking the stylus away from the tablet includes cleaning the brush tool; and wherein the action that is performed in response to recognition of twisting the stylus includes homogenizing the colors of paint on the brush tool.
| 0.603554 |
18. A retail mining method for extracting actionable insights and data-driven decisions from transaction data, the method being implemented by one or more data processors and comprising: data pre-processing by at least one data processor, wherein raw transaction data are filtered and customized; said filtering cleaning said data by removing data elements that are to be excluded from analysis; said customization creating different slices of said filtered transaction data that may be analyzed separately and whose results may be compared for further insight generation; graph generation, by at least one data processor, to create graphs that capture all pair-wise relationships between entities in a variety of contexts, said graph generation step comprising: context-instance creation wherein a number of context instances are created from said transaction data slice; co-occurrence counting wherein, for each pair of products, a co-occurrence count is computed as the number of context instances in which two products co-occurred; and co-occurrence consistency, wherein, once all co-occurrence counting is done, information theoretic consistency measures are computed for each pair of products, resulting in a graph; and insight discovery and decisioning, by at least one data processor, from said graphs, wherein said graphs serve as a model or internal representation of knowledge extracted from transaction data, said insight discovery and decisioning step further comprising any of: product related insight discovery, wherein graph theory and machine learning algorithms are applied to said graphs to discover patterns of interest, including product bundles, bridge products, product phrases, and product neighborhoods; wherein said patterns may be used to make decisions; and customer related decisioning, wherein a graph is used as a model to decisions; said graphs comprising any of the following types of structures: a sub-graph comprising a subset of a graph, created by picking a subset of nodes and edges from an original graph, a sub-graph comprising any of: node based sub-graphs which are created by selecting a subset of the nodes and by keeping only those edges between selected nodes; and edge based sub-graphs which are created by pruning a set of edges from the graph and removing all nodes that are rendered disconnected from the graph; a neighborhood of a target product comprising a sub-graph that contains the target product and all the products that are connected to the target product with consistency strength above a predefined threshold to show the top most affiliated products for a given target product; a bundle structure comprising a sub-set of products wherein each product in the bundle has a high consistency connection with all the other products in the bundle, wherein each product in a bundle is assigned a product density with respect to the bundle which is high if the product has high consistency connection with other products in the bundle and low otherwise; and a bridge structure comprising a collection of two or more, otherwise disconnected, product groups that are bridged by one or more bridge product(s).
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18. A retail mining method for extracting actionable insights and data-driven decisions from transaction data, the method being implemented by one or more data processors and comprising: data pre-processing by at least one data processor, wherein raw transaction data are filtered and customized; said filtering cleaning said data by removing data elements that are to be excluded from analysis; said customization creating different slices of said filtered transaction data that may be analyzed separately and whose results may be compared for further insight generation; graph generation, by at least one data processor, to create graphs that capture all pair-wise relationships between entities in a variety of contexts, said graph generation step comprising: context-instance creation wherein a number of context instances are created from said transaction data slice; co-occurrence counting wherein, for each pair of products, a co-occurrence count is computed as the number of context instances in which two products co-occurred; and co-occurrence consistency, wherein, once all co-occurrence counting is done, information theoretic consistency measures are computed for each pair of products, resulting in a graph; and insight discovery and decisioning, by at least one data processor, from said graphs, wherein said graphs serve as a model or internal representation of knowledge extracted from transaction data, said insight discovery and decisioning step further comprising any of: product related insight discovery, wherein graph theory and machine learning algorithms are applied to said graphs to discover patterns of interest, including product bundles, bridge products, product phrases, and product neighborhoods; wherein said patterns may be used to make decisions; and customer related decisioning, wherein a graph is used as a model to decisions; said graphs comprising any of the following types of structures: a sub-graph comprising a subset of a graph, created by picking a subset of nodes and edges from an original graph, a sub-graph comprising any of: node based sub-graphs which are created by selecting a subset of the nodes and by keeping only those edges between selected nodes; and edge based sub-graphs which are created by pruning a set of edges from the graph and removing all nodes that are rendered disconnected from the graph; a neighborhood of a target product comprising a sub-graph that contains the target product and all the products that are connected to the target product with consistency strength above a predefined threshold to show the top most affiliated products for a given target product; a bundle structure comprising a sub-set of products wherein each product in the bundle has a high consistency connection with all the other products in the bundle, wherein each product in a bundle is assigned a product density with respect to the bundle which is high if the product has high consistency connection with other products in the bundle and low otherwise; and a bridge structure comprising a collection of two or more, otherwise disconnected, product groups that are bridged by one or more bridge product(s). 19. The method of claim 18 , wherein said transaction data comprise a time-stamped sequence of market baskets and reflect a mixture of both intentional and impulsive customer behavior.
| 0.624435 |
11. The method of claim 1 , wherein said plurality of encoder modes comprises a NELP encoder mode, wherein the speech signal is represented by a residual signal generated by filtering the speech signal with a Linear Predictive Coding (LPC) analysis filter, and wherein said encoding comprises: (i) estimating the energy of the residual signal, and (ii) selecting a codevector from a first codebook, wherein said codevector approximates said estimated energy; and wherein decoding comprises: (i) generating a random vector, (ii) retrieving said codevector from a second codebook, (iii) scaling said random vector based on said codevector, such that the energy of said scaled random vector approximates said estimated energy, and (iv) filtering said scaled random vector with a LPC synthesis filter, wherein said filtered scaled random vector forms said synthesized speech signal.
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11. The method of claim 1 , wherein said plurality of encoder modes comprises a NELP encoder mode, wherein the speech signal is represented by a residual signal generated by filtering the speech signal with a Linear Predictive Coding (LPC) analysis filter, and wherein said encoding comprises: (i) estimating the energy of the residual signal, and (ii) selecting a codevector from a first codebook, wherein said codevector approximates said estimated energy; and wherein decoding comprises: (i) generating a random vector, (ii) retrieving said codevector from a second codebook, (iii) scaling said random vector based on said codevector, such that the energy of said scaled random vector approximates said estimated energy, and (iv) filtering said scaled random vector with a LPC synthesis filter, wherein said filtered scaled random vector forms said synthesized speech signal. 13. The method of claim 11 , wherein said first codebook and said second codebook are stochastic codebooks.
| 0.73191 |
9. A method for transmitting data packets including data formatted in an binary extensible markup language (XML) from a first system to a second system, comprising: providing a parser configured to convert from an extensible markup language (XML) representation that is compatible with standard XML to an extensible binary representation that is configured to reduce a number of bits required to represent common data as compared to the XML representation; accessing an XML representation according to a document type definition (DTD), the XML representation including element start tags, element end tags and data values; parsing the XML representation to generate a single data stream binary representation of the XML representation by providing binary data representations for element start tags and data values and by not providing binary data representations for element end tags; wherein the binary data representations are each formed using X-bit bytes; and wherein consistent extensible encoding is provided for each binary data representation by using a most-significant-bit of each X-bit byte as a termination indicator bit where a first logic level indicates the byte is a termination byte and a second logic level indicates that more bytes are included in a multi-byte data word; generating data packets for the single data stream binary representation that is formed using the X-bit bytes; and transmitting the data packets for the single data stream binary representation from a first interface associated with a first system through a data channel to a second interface associated with a second system; wherein the element start tags are represented using positive integer binary data representations; and wherein the data values are represented using binary data representations selected from a group comprising a string, an integer, a floating point number, an enumerated value, a pattern, and a packed component.
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9. A method for transmitting data packets including data formatted in an binary extensible markup language (XML) from a first system to a second system, comprising: providing a parser configured to convert from an extensible markup language (XML) representation that is compatible with standard XML to an extensible binary representation that is configured to reduce a number of bits required to represent common data as compared to the XML representation; accessing an XML representation according to a document type definition (DTD), the XML representation including element start tags, element end tags and data values; parsing the XML representation to generate a single data stream binary representation of the XML representation by providing binary data representations for element start tags and data values and by not providing binary data representations for element end tags; wherein the binary data representations are each formed using X-bit bytes; and wherein consistent extensible encoding is provided for each binary data representation by using a most-significant-bit of each X-bit byte as a termination indicator bit where a first logic level indicates the byte is a termination byte and a second logic level indicates that more bytes are included in a multi-byte data word; generating data packets for the single data stream binary representation that is formed using the X-bit bytes; and transmitting the data packets for the single data stream binary representation from a first interface associated with a first system through a data channel to a second interface associated with a second system; wherein the element start tags are represented using positive integer binary data representations; and wherein the data values are represented using binary data representations selected from a group comprising a string, an integer, a floating point number, an enumerated value, a pattern, and a packed component. 11. The method of claim 9 , wherein the second system comprises a data storage system.
| 0.729851 |
23. The apparatus of claim 22 , further comprising program instructions configured to: repeating each of the analysing each sub-clause and testing for at least one another clause of the one or more remaining sub-clauses.
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23. The apparatus of claim 22 , further comprising program instructions configured to: repeating each of the analysing each sub-clause and testing for at least one another clause of the one or more remaining sub-clauses. 24. The apparatus of claim 23 , further comprising program instructions configured to: generate a sub-query associated with a second sub-clause having the largest proportion of values to variables of said remaining sub-clauses.
| 0.897479 |
38. A computer readable storage medium having stored thereon programming instructions for filtering and securing from input data, one or more security sensitive words, characters or data objects with an adaptive filter in a computer system, said adaptive filter used in conjunction with a compilation of additional data, the instructions comprising: identifying said security sensitive words, characters or data objects in said compilation of additional data; retrieving related data from said compilation of additional data representative of at least one of: contextual characters or data objects related to said security sensitive words, characters or data objects; semiotic words, characters or data objects related to said security sensitive words, characters or data objects; taxonomic words, characters or data objects related to said security sensitive words, characters or data objects; compiling a filter with said security sensitive words, characters or data objects and the retrieved data related to said security sensitive words, characters or data objects; and extracting, from said input data, with said filter, said security sensitive words, characters or data objects and said retrieved data to obtain extracted data and remainder data therefrom; and storing either the extracted data separately from said remainder data or storing partial versions of said extracted data with said remainder data based upon multiple security levels unique to each partial version.
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38. A computer readable storage medium having stored thereon programming instructions for filtering and securing from input data, one or more security sensitive words, characters or data objects with an adaptive filter in a computer system, said adaptive filter used in conjunction with a compilation of additional data, the instructions comprising: identifying said security sensitive words, characters or data objects in said compilation of additional data; retrieving related data from said compilation of additional data representative of at least one of: contextual characters or data objects related to said security sensitive words, characters or data objects; semiotic words, characters or data objects related to said security sensitive words, characters or data objects; taxonomic words, characters or data objects related to said security sensitive words, characters or data objects; compiling a filter with said security sensitive words, characters or data objects and the retrieved data related to said security sensitive words, characters or data objects; and extracting, from said input data, with said filter, said security sensitive words, characters or data objects and said retrieved data to obtain extracted data and remainder data therefrom; and storing either the extracted data separately from said remainder data or storing partial versions of said extracted data with said remainder data based upon multiple security levels unique to each partial version. 43. A computer readable storage medium with programming instructions for filtering and securing data as claimed in claim 38 , wherein retrieving includes retrieving contextual words, characters or data objects from said compilation of additional data related to said security sensitive words, characters or data objects based upon predetermined statistical analysis of said additional data relative to said security sensitive words, characters or data objects.
| 0.55985 |
1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain (1) a model for detecting a keyword in an audio sample and (2) a first detection threshold corresponding to the model, wherein a detection score greater than the first detection threshold indicates that the keyword is present in the audio sample, and wherein the detection score is computed using the audio sample and the model; determine a first cost of computing a first incorrect detection hypothesis, wherein the first incorrect detection hypothesis corresponds to a detection score greater than the first detection threshold for an audio sample in which the keyword is not present, and wherein the first cost represents a cost of computing the first incorrect detection hypothesis at least a predetermined time period after computation of all prior incorrect detection hypotheses occurring before the first incorrect detection hypothesis; determine a second cost of computing a second incorrect detection hypothesis, wherein the second cost represents a cost of computing the second incorrect detection hypothesis within the predetermined time period following the first incorrect detection hypothesis, and wherein the second cost is different than the first cost; determine a second detection threshold based at least partly on the first and second costs, wherein the second detection threshold is determined such that the first and second costs are minimized; transmit the second detection threshold to a client device; receive audio data from the client device, wherein the client device transmits the audio data based at least partly on a detection score, determined using the audio data, satisfying the second detection threshold; and performing automatic speech recognition using at least a portion of the audio data to determine that data representing the keyword is present in the audio data, wherein the keyword comprises a word likely indicating device-directed speech.
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1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: obtain (1) a model for detecting a keyword in an audio sample and (2) a first detection threshold corresponding to the model, wherein a detection score greater than the first detection threshold indicates that the keyword is present in the audio sample, and wherein the detection score is computed using the audio sample and the model; determine a first cost of computing a first incorrect detection hypothesis, wherein the first incorrect detection hypothesis corresponds to a detection score greater than the first detection threshold for an audio sample in which the keyword is not present, and wherein the first cost represents a cost of computing the first incorrect detection hypothesis at least a predetermined time period after computation of all prior incorrect detection hypotheses occurring before the first incorrect detection hypothesis; determine a second cost of computing a second incorrect detection hypothesis, wherein the second cost represents a cost of computing the second incorrect detection hypothesis within the predetermined time period following the first incorrect detection hypothesis, and wherein the second cost is different than the first cost; determine a second detection threshold based at least partly on the first and second costs, wherein the second detection threshold is determined such that the first and second costs are minimized; transmit the second detection threshold to a client device; receive audio data from the client device, wherein the client device transmits the audio data based at least partly on a detection score, determined using the audio data, satisfying the second detection threshold; and performing automatic speech recognition using at least a portion of the audio data to determine that data representing the keyword is present in the audio data, wherein the keyword comprises a word likely indicating device-directed speech. 5. The system of claim 1 , wherein the executable instructions to determine the second detection threshold comprise executable instructions to minimize a cost function.
| 0.54186 |
13. The computer-implemented method as recited in claim 9 , wherein the locked print module is further configured to examine header data to determine whether the electronic document contained in the PDF print data is a policy-enabled document.
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13. The computer-implemented method as recited in claim 9 , wherein the locked print module is further configured to examine header data to determine whether the electronic document contained in the PDF print data is a policy-enabled document. 14. The computer-implemented method as recited in claim 13 , wherein the locked print module is further configured to recognize one or more PJL commands contained in the header data that indicate that the electronic document contained in the PDF print data is a policy-enabled document.
| 0.928401 |
3. The method of claim 2 , further comprising: upon determining the second asset has been reclassified, reevaluating, by operation of the one or more computer processors, the refined classification assigned to the first asset against the refinement criteria.
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3. The method of claim 2 , further comprising: upon determining the second asset has been reclassified, reevaluating, by operation of the one or more computer processors, the refined classification assigned to the first asset against the refinement criteria. 5. The method of claim 3 , further comprising: comparing a weight assigned to a user who assigned the classification to the second asset with a weight assigned to a user who reclassified the second asset; undoing the refined classification of the second asset if the weight of the user who assigned the classification to the second asset exceeds the weight assigned to the user who reclassified the second by a specified threshold; and retaining the refined classification of the second asset if the weight of the user who assigned the classification to the second asset does not exceed the weight assigned to the user who reclassified the second by the specified threshold.
| 0.667304 |
1. A system comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the system to perform a set of operations, the set of operations comprising: receiving, as part of a conversation session, a message from a user device, wherein the conversation session is between a user of the user device and an electronic conversational agent; determining, based on the message and one or more factors associated with the conversation session, a behavior measure associated with the user; determining, based on analyzing the behavior measure in relation to one or more historical factors associated with a subset of other users of the electronic conversational agent, whether the user is exhibiting anomalous behavior; when it is determined that the user is exhibiting anomalous behavior, automatically adapting the electronic conversational agent based on the determined anomalous behavior; and continuing the conversation session based on the adapted electronic conversational agent.
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1. A system comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the system to perform a set of operations, the set of operations comprising: receiving, as part of a conversation session, a message from a user device, wherein the conversation session is between a user of the user device and an electronic conversational agent; determining, based on the message and one or more factors associated with the conversation session, a behavior measure associated with the user; determining, based on analyzing the behavior measure in relation to one or more historical factors associated with a subset of other users of the electronic conversational agent, whether the user is exhibiting anomalous behavior; when it is determined that the user is exhibiting anomalous behavior, automatically adapting the electronic conversational agent based on the determined anomalous behavior; and continuing the conversation session based on the adapted electronic conversational agent. 2. The system of claim 1 , wherein determining the behavior measure comprises: computing one or more averages for the one or more factors; and generating the behavior measure based on an evaluation of the one or more averages using one or more thresholds.
| 0.642707 |
9. The method of claim 6 , further comprising: detecting a series of taps in substantially the same location on the scanning surface; determining a quantity of taps of the series of taps in substantially the same location on the scanning surface; and expanding the bound region by a factor proportional to the quantity of taps in response to determining the quantity of taps of the series of taps in substantially the same location on the scanning surface.
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9. The method of claim 6 , further comprising: detecting a series of taps in substantially the same location on the scanning surface; determining a quantity of taps of the series of taps in substantially the same location on the scanning surface; and expanding the bound region by a factor proportional to the quantity of taps in response to determining the quantity of taps of the series of taps in substantially the same location on the scanning surface. 10. The method of claim 9 , wherein the series of taps comprises a series of at least two taps.
| 0.849485 |
14. The system of claim 12 , wherein the instructions further include instructions that, when executed by the at least one processor, cause the system to: responsive to determining that the threshold value fails to meet the predetermined acceptance value, mark the first configuration item for manual reconciliation.
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14. The system of claim 12 , wherein the instructions further include instructions that, when executed by the at least one processor, cause the system to: responsive to determining that the threshold value fails to meet the predetermined acceptance value, mark the first configuration item for manual reconciliation. 17. The system of claim 14 , wherein the instructions further include instructions that, when executed by the at least one processor, cause the system to: displaying information for a plurality of statistical rules as part of a manual reconciliation process, the information being ordered by respective associated threshold values for the plurality of statistical rules.
| 0.782934 |
83. The method as recited in claim 74 , wherein the resources are services, wherein one of the one or more advertisements includes a service class advertisement, wherein said service class advertisement comprises one or more service implementation advertisements, wherein each service implementation advertisement describes a different service implementation specific to a different computing platform.
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83. The method as recited in claim 74 , wherein the resources are services, wherein one of the one or more advertisements includes a service class advertisement, wherein said service class advertisement comprises one or more service implementation advertisements, wherein each service implementation advertisement describes a different service implementation specific to a different computing platform. 84. The method as recited in claim 83 , further comprising the peer node accessing a service implementation described by one of the one or more service implementation advertisements, wherein the service implementation is specific to the peer node's particular computing platform.
| 0.871108 |
16. A method comprising: parsing a first one or more text messages sent from the mobile device during a session to identify one of a plurality of commands and one of a plurality of types of the enterprise work records; determining, using historical data stored in a local memory and without querying the enterprise database, that the identified command and the identified type of enterprise work record were previously identified by parsing a previous one or more text messages sent from the mobile device during the session; identifying, responsive to the determination, one or more fields of the identified type of enterprise work record required by the enterprise database to be populated to carry out the identified command; sending a request message to the mobile device, the request message requesting user input to populate the one or more fields; parsing a second text message sent from the mobile device during the session to identify field data for the one or more fields; and sending instructions to the enterprise database to carry out the identified command with respect to the identified type of enterprise work record using the identified field data.
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16. A method comprising: parsing a first one or more text messages sent from the mobile device during a session to identify one of a plurality of commands and one of a plurality of types of the enterprise work records; determining, using historical data stored in a local memory and without querying the enterprise database, that the identified command and the identified type of enterprise work record were previously identified by parsing a previous one or more text messages sent from the mobile device during the session; identifying, responsive to the determination, one or more fields of the identified type of enterprise work record required by the enterprise database to be populated to carry out the identified command; sending a request message to the mobile device, the request message requesting user input to populate the one or more fields; parsing a second text message sent from the mobile device during the session to identify field data for the one or more fields; and sending instructions to the enterprise database to carry out the identified command with respect to the identified type of enterprise work record using the identified field data. 17. The method of claim 16 , further comprising: retrieving, from the historical data and without querying the enterprise database, a set of most-frequently used commands and a set of most-frequently accessed enterprise work records or types of enterprise work records; and sending one or more prompt messages to the mobile device, the one or more prompt messages indicating the set of most-frequently used commands and the set of most-frequently accessed enterprise work records or types of enterprise work records, the one or more prompt messages prompting a user of the mobile device to select one of the most-frequently used commands and one of the most-frequently accessed types of enterprise work records as the identified command and the identified type of enterprise work record.
| 0.634508 |
6. A computer-implemented method, comprising: receiving, by a computer system, an image; receiving data associated with the image, the data including a plurality of parameters describing presentation of the image, individual parameters of the plurality of parameters corresponding to at least one of characteristic parameters or rule parameters; generating an asset identification code, the asset identification code identifying at least the image and the data; storing the image and the data in association with the asset identification code; receiving a translation of a text string based at least in part on a request that includes the asset identification code, the translation of the text string comprising a translated text string corresponding to a language code that comprises a regional identifier and a language identifier, the regional identifier indicating a particular geographic region and the language identifier indicating a particular language supported within the particular geographic region; providing the image including the translated text string to a user device in accordance with the plurality of parameters; and causing the user device to display the image based in part on the language code and the plurality of parameters, the displayed image including the translated text string.
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6. A computer-implemented method, comprising: receiving, by a computer system, an image; receiving data associated with the image, the data including a plurality of parameters describing presentation of the image, individual parameters of the plurality of parameters corresponding to at least one of characteristic parameters or rule parameters; generating an asset identification code, the asset identification code identifying at least the image and the data; storing the image and the data in association with the asset identification code; receiving a translation of a text string based at least in part on a request that includes the asset identification code, the translation of the text string comprising a translated text string corresponding to a language code that comprises a regional identifier and a language identifier, the regional identifier indicating a particular geographic region and the language identifier indicating a particular language supported within the particular geographic region; providing the image including the translated text string to a user device in accordance with the plurality of parameters; and causing the user device to display the image based in part on the language code and the plurality of parameters, the displayed image including the translated text string. 7. The computer-implemented method of claim 6 , wherein the rule parameters comprise at least one of a spacing parameter, a placement parameter, a widow/orphan parameter, a character-spacing parameter, a hyphenation parameter, a boundary parameter indicating at least a boundary of an overlay, a special character parameter, a text flow parameter, or a directional text parameter, and wherein the characteristic parameters comprise at least one of a text parameter, a font parameter, a size parameter, a non-text element parameter, a color parameter, or a text style parameter.
| 0.5 |
8. A computer-readable storage device storing computer-executable instructions that, when executed by a processor of a policy intelligence rules system of a policy layer of a policy realization framework of a communications network, cause the processor to perform operations comprising: receiving, from a policy and charging rules function of a network layer of the policy realization framework, a policy request associated with a request for a network resource; sending, to a master policy repository, the policy request; receiving, from the master policy repository, a plurality of policies pertaining to the request for the network resource of the policy request, wherein the plurality of policies pertaining to the request for the network resource comprise at least one operator policy provided by a network operator and at least one subscriber specific policy provided by a subscriber associated with the request for the network resource; analyzing the plurality of policies to determine whether any policy conflicts exist between any of the plurality of policies; in response to determining that a policy conflict exists between a first policy of the plurality of policies and a second policy of the plurality of policies, determining that the first policy has precedence over the second policy, wherein the first policy comprises the at least one operator policy and the second policy comprises the at least one subscriber specific policy; resolving the policy conflict by giving precedence to the first policy over the second policy; generating, based on the first policy having precedence over the second policy, a rule describing a course of action for the communications network to take in response to the request for the network resource of the policy request; and sending the rule to a policy configuration and provisioning server of the policy layer for use in instructing the policy and charging rules function of the network layer of the policy realization framework.
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8. A computer-readable storage device storing computer-executable instructions that, when executed by a processor of a policy intelligence rules system of a policy layer of a policy realization framework of a communications network, cause the processor to perform operations comprising: receiving, from a policy and charging rules function of a network layer of the policy realization framework, a policy request associated with a request for a network resource; sending, to a master policy repository, the policy request; receiving, from the master policy repository, a plurality of policies pertaining to the request for the network resource of the policy request, wherein the plurality of policies pertaining to the request for the network resource comprise at least one operator policy provided by a network operator and at least one subscriber specific policy provided by a subscriber associated with the request for the network resource; analyzing the plurality of policies to determine whether any policy conflicts exist between any of the plurality of policies; in response to determining that a policy conflict exists between a first policy of the plurality of policies and a second policy of the plurality of policies, determining that the first policy has precedence over the second policy, wherein the first policy comprises the at least one operator policy and the second policy comprises the at least one subscriber specific policy; resolving the policy conflict by giving precedence to the first policy over the second policy; generating, based on the first policy having precedence over the second policy, a rule describing a course of action for the communications network to take in response to the request for the network resource of the policy request; and sending the rule to a policy configuration and provisioning server of the policy layer for use in instructing the policy and charging rules function of the network layer of the policy realization framework. 9. The computer-readable storage device of claim 8 , wherein the operations further comprise identifying the policy conflict, wherein identifying the policy conflict comprises creating data that identifies the first policy and the second policy involved in the policy conflict.
| 0.80086 |
1. Apparatus for responding to a request message sent from a remote user device for web page information by generating web page code capable of being interpreted by a browser within the remote user device for displaying one or more web pages and for outputting a response message comprising the web page code, the apparatus comprising: extracting means for extracting from the request message information determining a device type identifier identifying the remote user device which sent the request message as being one of a set of possible remote user device types having different capabilities of processing and displaying web page code; a processor for operating a code generating engine to generate the web page code; first memory means for storing the web page information as a content document comprising a set of instructions authored in a script language for generating the web page code; and second memory means for storing device dependent information for each of the set of possible remote user device types; wherein the code generating engine comprises interpreting means for interpreting the instructions authored in the script language with reference to selected device dependent information corresponding to the device type identifier of the remote user device which sent the request message, the code generating engine thereby being operable to generate the web page code in a form in which the web page code is tailored to the capabilities of the remote user device for processing and displaying web page code; wherein the content document comprises at least one component name identifying a respective data component, and wherein the apparatus comprises a data structure in which at least one data component exists as a set of data objects defining multiple versions of the data component where the data objects have different data properties suited to the different capabilities of processing and displaying web page code of the different remote user devices; and means for selecting a data object from the set of data objects identified by a component name for inclusion in the web page code on the basis of the device type identifier of the remote user device which sent the request message; wherein the selecting means is operable to look up a predetermined selection of data object using a component policy table in a case where selection of the version of data component for the remote user device is predetermined by an author of the content document, and wherein the selecting means is further operable to determine technical attributes of the remote user device and to select the data object by comparing the technical attributes with data properties of each data object in a case where no version of the data component for the remote user device has been predetermined by the author of the content document, wherein the technical attributes of the remote user device are defined in a device policy table.
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1. Apparatus for responding to a request message sent from a remote user device for web page information by generating web page code capable of being interpreted by a browser within the remote user device for displaying one or more web pages and for outputting a response message comprising the web page code, the apparatus comprising: extracting means for extracting from the request message information determining a device type identifier identifying the remote user device which sent the request message as being one of a set of possible remote user device types having different capabilities of processing and displaying web page code; a processor for operating a code generating engine to generate the web page code; first memory means for storing the web page information as a content document comprising a set of instructions authored in a script language for generating the web page code; and second memory means for storing device dependent information for each of the set of possible remote user device types; wherein the code generating engine comprises interpreting means for interpreting the instructions authored in the script language with reference to selected device dependent information corresponding to the device type identifier of the remote user device which sent the request message, the code generating engine thereby being operable to generate the web page code in a form in which the web page code is tailored to the capabilities of the remote user device for processing and displaying web page code; wherein the content document comprises at least one component name identifying a respective data component, and wherein the apparatus comprises a data structure in which at least one data component exists as a set of data objects defining multiple versions of the data component where the data objects have different data properties suited to the different capabilities of processing and displaying web page code of the different remote user devices; and means for selecting a data object from the set of data objects identified by a component name for inclusion in the web page code on the basis of the device type identifier of the remote user device which sent the request message; wherein the selecting means is operable to look up a predetermined selection of data object using a component policy table in a case where selection of the version of data component for the remote user device is predetermined by an author of the content document, and wherein the selecting means is further operable to determine technical attributes of the remote user device and to select the data object by comparing the technical attributes with data properties of each data object in a case where no version of the data component for the remote user device has been predetermined by the author of the content document, wherein the technical attributes of the remote user device are defined in a device policy table. 31. Apparatus as claimed in claim 1 , comprising a cache memory operable to store a copy of web page code output in a response message; and means for outputting web page code from the stored copy in response to receiving a further request message for the same web page information.
| 0.542584 |
1. A method for providing text flow around a non-rectangular graphic, comprising: using a processor to find a two-dimensional area of intersection, if any, between a proposed text rectangle and the graphic; using the processor to determine a bounding rectangle of the two-dimensional area of intersection; using the processor to subtract the bounding rectangle of the two-dimensional area of intersection from the proposed text rectangle; and using the processor to identify as a valid text area within the proposed text rectangle a valid rectangle, if any, that remains after the bounding rectangle has been subtracted from the proposed rectangle.
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1. A method for providing text flow around a non-rectangular graphic, comprising: using a processor to find a two-dimensional area of intersection, if any, between a proposed text rectangle and the graphic; using the processor to determine a bounding rectangle of the two-dimensional area of intersection; using the processor to subtract the bounding rectangle of the two-dimensional area of intersection from the proposed text rectangle; and using the processor to identify as a valid text area within the proposed text rectangle a valid rectangle, if any, that remains after the bounding rectangle has been subtracted from the proposed rectangle. 5. A method as recited in claim 1 , wherein identifying as a valid text area within the proposed text rectangle a valid rectangle, if any, that is not within the bounds in the x-direction of an area of intersection between the proposed text rectangle and the graphic includes: sorting two or more areas of intersection by their respective minimum x-coordinates; combining overlapping or adjacent areas of intersection; and using the sorted and combined, if applicable, areas of intersection to find any valid text areas.
| 0.514286 |
4. The method of claim 1 , wherein the setting of the call word comprises: displaying a user interface (UI) which is used to set the call word of the external input apparatus connected through the external input terminal.
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4. The method of claim 1 , wherein the setting of the call word comprises: displaying a user interface (UI) which is used to set the call word of the external input apparatus connected through the external input terminal. 5. The method of claim 4 , wherein the UI is displayed after the broadcast receiving apparatus is initially turned on.
| 0.952909 |
1. A method for testing a vulnerability of a web site, comprising: receiving a first set of addresses; identifying a second set of addresses by analyzing a first set of web pages located at the first set of addresses; identifying a third set of addresses by analyzing a first set of document object models (DOMs) associated with the first set of web pages and associated with a second set of web pages located at the second set of addresses; probing a third set of web pages for presence of a set of vulnerabilities using a document object model (DOM) analysis script to analyze a second set of document object models (DOMs) associated with the third set of web pages as a set of attack vectors is applied to the third set of web pages, wherein the third set of web pages is located at the first, second, and third sets of addresses, and the DOM analysis script is inserted into the third set of web pages; and determining presence of the set of vulnerabilities for the third set of web pages based on a set of results from the probing, wherein the attack vectors are designed to exploit a vulnerability of a web page.
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1. A method for testing a vulnerability of a web site, comprising: receiving a first set of addresses; identifying a second set of addresses by analyzing a first set of web pages located at the first set of addresses; identifying a third set of addresses by analyzing a first set of document object models (DOMs) associated with the first set of web pages and associated with a second set of web pages located at the second set of addresses; probing a third set of web pages for presence of a set of vulnerabilities using a document object model (DOM) analysis script to analyze a second set of document object models (DOMs) associated with the third set of web pages as a set of attack vectors is applied to the third set of web pages, wherein the third set of web pages is located at the first, second, and third sets of addresses, and the DOM analysis script is inserted into the third set of web pages; and determining presence of the set of vulnerabilities for the third set of web pages based on a set of results from the probing, wherein the attack vectors are designed to exploit a vulnerability of a web page. 3. The method of claim 1 , wherein the DOM analysis script is inserted into the third set of web pages using a proxy.
| 0.675267 |
87. The at least one non-transitory computer-readable storage medium of claim 61 , wherein the method further comprises allowing a human user to make edits to the text report.
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87. The at least one non-transitory computer-readable storage medium of claim 61 , wherein the method further comprises allowing a human user to make edits to the text report. 89. The at least one non-transitory computer-readable storage medium of claim 87 , wherein the method further comprises prompting the human user to add information to the text report to comply with one or more report content standards.
| 0.937246 |
24. A system comprising: a plurality of objects associated with a course; and a pre-specified locale associated with the course, wherein the pre-specified locale has associated therewith an attribute identifying the pre-specified locale as mandatory or elective, wherein the plurality of objects and the pre-specified locale are stored in a computer-accessible memory.
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24. A system comprising: a plurality of objects associated with a course; and a pre-specified locale associated with the course, wherein the pre-specified locale has associated therewith an attribute identifying the pre-specified locale as mandatory or elective, wherein the plurality of objects and the pre-specified locale are stored in a computer-accessible memory. 29. The system of claim 24 , wherein the pre-specified locale identifies a format for numbers.
| 0.778756 |
1. A system, comprising: a user context language model engine including, logic to cause a processor to associate one or more key words with each of one or more types of user context information, logic to cause the processor to identify user context information associated with each of one or more users, and logic to cause the processor to generate a user context vocabulary of words, for each of the one or more users, from the key words associated with the corresponding user context information; a product language model engine including, logic to cause the processor to associate one or more key words with each of one or more product categories, and logic to cause the processor to generate a product vocabulary of words from the key words corresponding to the product categories; an acoustic model engine to convert user input speech to a first set of one or more words; and a word selection engine to select a second set of one or more words from one or more of a corresponding one of the user context vocabulary of words and the product vocabulary of words that correlate to the first set of one or more words.
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1. A system, comprising: a user context language model engine including, logic to cause a processor to associate one or more key words with each of one or more types of user context information, logic to cause the processor to identify user context information associated with each of one or more users, and logic to cause the processor to generate a user context vocabulary of words, for each of the one or more users, from the key words associated with the corresponding user context information; a product language model engine including, logic to cause the processor to associate one or more key words with each of one or more product categories, and logic to cause the processor to generate a product vocabulary of words from the key words corresponding to the product categories; an acoustic model engine to convert user input speech to a first set of one or more words; and a word selection engine to select a second set of one or more words from one or more of a corresponding one of the user context vocabulary of words and the product vocabulary of words that correlate to the first set of one or more words. 10. The system of claim 1 , further including: a background audio language model engine including: logic to cause the processor to associate one or more key words with each of one or more media content identifications, logic to cause the processor to identify the media content indications from audio accompanying the user input speech, and logic to cause the processor to generate media content vocabularies of words from the key words of identified media content identifications; and a scoring engine to assign scores to the user context vocabulary of words and the media content vocabulary of words; wherein the word selection engine includes logic to cause the processor to select the second set of one of more words from one or more of the user context vocabulary of words, the product vocabulary of words, and the media content vocabulary of words, at least partially in response to the scores.
| 0.5 |
6. A computer-readable storage medium containing an executable component for configuring an annotation system for managing annotations created for data objects manipulated by one or more applications on a network which, when executed by a processor, performs operations comprising: identifying a plurality of annotatable heterogeneous data objects, each manipulated by a corresponding one of a plurality of applications on the network, wherein each of the plurality of applications specifies an indexing mechanism for indexing data objects associated with a representative application, and wherein the indexing mechanism for each of the plurality of applications is different from one another; and providing a set of one or more configuration tools configured to: allow a user to define an annotation structure containing one or more annotation fields for annotations created for a respective application, and wherein one or more of the annotation fields are used to store metadata included in a given annotation and wherein one or more of the annotation fields store metadata used to index an annotation according to the indexing mechanism and mapping function associated with the respective application; associate the annotation structure with at least one of the plurality of applications; allow a user to define roles configured to determine the type of information captured or viewed in an annotation created for a given data object of a given application; and associate annotation structures defined by the user with combinations of the user defined roles and annotatable data objects, whereby a subsequent request to annotate a given annotatable data object results in a selection of one or more of the associated annotation structures based on a match between a role of a user making the subsequent request and the role associated with the one or more of the associated annotation structures.
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6. A computer-readable storage medium containing an executable component for configuring an annotation system for managing annotations created for data objects manipulated by one or more applications on a network which, when executed by a processor, performs operations comprising: identifying a plurality of annotatable heterogeneous data objects, each manipulated by a corresponding one of a plurality of applications on the network, wherein each of the plurality of applications specifies an indexing mechanism for indexing data objects associated with a representative application, and wherein the indexing mechanism for each of the plurality of applications is different from one another; and providing a set of one or more configuration tools configured to: allow a user to define an annotation structure containing one or more annotation fields for annotations created for a respective application, and wherein one or more of the annotation fields are used to store metadata included in a given annotation and wherein one or more of the annotation fields store metadata used to index an annotation according to the indexing mechanism and mapping function associated with the respective application; associate the annotation structure with at least one of the plurality of applications; allow a user to define roles configured to determine the type of information captured or viewed in an annotation created for a given data object of a given application; and associate annotation structures defined by the user with combinations of the user defined roles and annotatable data objects, whereby a subsequent request to annotate a given annotatable data object results in a selection of one or more of the associated annotation structures based on a match between a role of a user making the subsequent request and the role associated with the one or more of the associated annotation structures. 9. The computer readable storage medium of claim 6 , wherein the configuration tools allow a user to specify one or more filters specifying how annotation fields contained in an annotation structure can be manipulated based on user roles.
| 0.555762 |
11. A non-transitory computer readable medium comprising code that, when loaded into a computing device, adapts the device to manage spam within an email message stream directed from a server to a communications device, the non-transitory computer readable medium including: code for defining a plurality of anti-spam filter levels with at least one anti-spam filter level at each one of the server and the communications device and including at least one anti-spam module configurable for filtering spam messages; code for generating in response to a selection an anti-spam request at the communications device, the anti-spam request including a preferred anti-spam filter level; code for communicating the anti-spam request to the preferred anti-spam filter level from the communication device; code for implementing the anti-spam request on at least one anti-spam module in the preferred anti-spam filter level based on at least one predetermined criterion; and code for determining if the anti-spam request cannot be implemented at the preferred anti-spam filter level and, if it is determined that the anti-spam request cannot be implemented at the preferred anti-spam level, implementing the anti-spam request at the uppermost anti-spam filter level having at least one anti-spam module with available processing capacity.
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11. A non-transitory computer readable medium comprising code that, when loaded into a computing device, adapts the device to manage spam within an email message stream directed from a server to a communications device, the non-transitory computer readable medium including: code for defining a plurality of anti-spam filter levels with at least one anti-spam filter level at each one of the server and the communications device and including at least one anti-spam module configurable for filtering spam messages; code for generating in response to a selection an anti-spam request at the communications device, the anti-spam request including a preferred anti-spam filter level; code for communicating the anti-spam request to the preferred anti-spam filter level from the communication device; code for implementing the anti-spam request on at least one anti-spam module in the preferred anti-spam filter level based on at least one predetermined criterion; and code for determining if the anti-spam request cannot be implemented at the preferred anti-spam filter level and, if it is determined that the anti-spam request cannot be implemented at the preferred anti-spam level, implementing the anti-spam request at the uppermost anti-spam filter level having at least one anti-spam module with available processing capacity. 15. The non-transitory computer readable medium of claim 11 , further including: code for comparing anti-spam addresses and any anti-spam subjects from at least two anti-spam requests at a given anti-spam filter level; code for determining if any anti-spam addresses or any anti-spam subjects have common portions of minimal length; code for proposing consolidation of the relevant anti-spam requests at a higher anti-spam filter level if there are any common portions of minimal length in at least one of the anti-spam addresses or anti-spam subjects.
| 0.5 |
22. The computer program product of claim 18 , wherein the step of determining frequent itemsets comprises the steps of: generating an array of counts of occurrences of multiple types of items or events in the same data entry.
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22. The computer program product of claim 18 , wherein the step of determining frequent itemsets comprises the steps of: generating an array of counts of occurrences of multiple types of items or events in the same data entry. 23. The computer program product of claim 22 , wherein the array of counts of occurrences of multiple types of items or events in the same data entry includes only a portion of the occurrences, wherein the occurrences included in the portion occur more frequently than do the occurrences not included in the portion.
| 0.877455 |
1. A computer-implemented method for identifying data files that have a common characteristic, the method comprising: receiving a plurality of data files including one or more data files having the common characteristic; generating a list of key terms from the plurality of data files; classifying each data file of the plurality of data files within a hierarchical structure, the hierarchical structure including upper nodes and lower nodes configured to group data files having similar characteristics, wherein a data file is classified within a lower node of the hierarchical structure based on a psychological characteristic of the classified data file, wherein the psychological characteristic indicates a psychological state of the creator of the classified data file; identifying data files from the plurality of data files having an association with a social community, the social community being a homogenous sub-group of a larger population defined by one or more features, wherein the identified data files having the association with the social community are classified within a particular node of the hierarchical structure that is defined by the one or more features; updating the list of key terms based on an analysis of the identified data files; and using the updated list of key terms to identify other data files that have the common characteristic.
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1. A computer-implemented method for identifying data files that have a common characteristic, the method comprising: receiving a plurality of data files including one or more data files having the common characteristic; generating a list of key terms from the plurality of data files; classifying each data file of the plurality of data files within a hierarchical structure, the hierarchical structure including upper nodes and lower nodes configured to group data files having similar characteristics, wherein a data file is classified within a lower node of the hierarchical structure based on a psychological characteristic of the classified data file, wherein the psychological characteristic indicates a psychological state of the creator of the classified data file; identifying data files from the plurality of data files having an association with a social community, the social community being a homogenous sub-group of a larger population defined by one or more features, wherein the identified data files having the association with the social community are classified within a particular node of the hierarchical structure that is defined by the one or more features; updating the list of key terms based on an analysis of the identified data files; and using the updated list of key terms to identify other data files that have the common characteristic. 27. The method of claim 1 , further comprising: receiving the plurality of data files, wherein the plurality of data files are text documents; and generating the list of key terms, the key terms being words, phrases, sentences, or symbols that are associated with the common characteristic.
| 0.607089 |
5. The computer-implemented method for building a dynamic classification dictionary of claim 1 , further comprising: analyzing the aggregate set of taxonomic nouns identified for all documents; and creating a term table based upon the analyzed aggregate set of taxonomic nouns.
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5. The computer-implemented method for building a dynamic classification dictionary of claim 1 , further comprising: analyzing the aggregate set of taxonomic nouns identified for all documents; and creating a term table based upon the analyzed aggregate set of taxonomic nouns. 13. The computer-implemented method for building a dynamic classification dictionary of claim 5 , further comprising: identifying candidate terms to add to the dynamic classification dictionary based upon the analyzed aggregate set of taxonomic nouns.
| 0.895904 |
1. A method, in a data processing system comprising a processor and a memory, the memory comprising instructions which are executed by the processor to configure the data processing system to implement a natural language content (NLC) disambiguation engine, the method comprising: identifying, by the NLC disambiguation engine, in a corpus of natural language content, a portion of natural language content (NLC) that is determined to be ambiguous with regard to a context of the portion of NLC, thereby identifying an ambiguous content portion; comparing, by the NLC disambiguation engine, the ambiguous content portion to private content information associated with a source of the ambiguous content portion, wherein the private content information is content information accessible to users and resources associated with the source and is not accessible to users or resources that are not associated with the source; identifying, by the NLC disambiguation engine, a domain of the ambiguous content portion based on a domain of a matching portion of the private content information; and performing, by the NLC disambiguation engine, a clarifying operation that clarifies the ambiguous content portion based on the identified domain of the ambiguous content portion to thereby generate a clarified content portion for processing by a cognitive operation of a cognitive system.
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1. A method, in a data processing system comprising a processor and a memory, the memory comprising instructions which are executed by the processor to configure the data processing system to implement a natural language content (NLC) disambiguation engine, the method comprising: identifying, by the NLC disambiguation engine, in a corpus of natural language content, a portion of natural language content (NLC) that is determined to be ambiguous with regard to a context of the portion of NLC, thereby identifying an ambiguous content portion; comparing, by the NLC disambiguation engine, the ambiguous content portion to private content information associated with a source of the ambiguous content portion, wherein the private content information is content information accessible to users and resources associated with the source and is not accessible to users or resources that are not associated with the source; identifying, by the NLC disambiguation engine, a domain of the ambiguous content portion based on a domain of a matching portion of the private content information; and performing, by the NLC disambiguation engine, a clarifying operation that clarifies the ambiguous content portion based on the identified domain of the ambiguous content portion to thereby generate a clarified content portion for processing by a cognitive operation of a cognitive system. 6. The method of claim 1 , wherein the domain of the matching portion of the private content information comprises a domain, in a taxonomy data structure specifying domains corresponding to private content information associated with the source, which is indicated by the source to be able to be used by the NLC disambiguation engine to disambiguate ambiguous content.
| 0.566667 |
4. The method of claim 3 wherein an inter-sample relationship is time of a scene.
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4. The method of claim 3 wherein an inter-sample relationship is time of a scene. 5. The method of claim 4 wherein the classification is whether a scene represents a commercial.
| 0.972951 |
16. A system for providing thematic information to provide a visual theme for documents, comprising: a computer readable storage medium encoded with a theme object for conveying thematic information for visual display of documents; wherein the theme object is defined using a markup language and is stored in a theme file; wherein the definition of the theme object is maintained separately within the theme file from other objects that define the document and that are each maintained separately; and wherein a schema defines and enforces rules for displaying the theme object; an operating system executed on a processor; wherein the operating system provides an application programming interface (API) to the theme object; an application suite executed on a processor; wherein the application suite comprises a first application for authoring a first kind of document using the API to the theme object, and comprising a second application that is different from the first application for authoring a second kind of document using the API to the theme object; wherein the first kind of document is associated with a first file format that includes modular parts that are associated together; wherein the theme object is a modular part that is associated with the first file format; wherein the second kind of document is associated with a second file format that includes modular parts that are associated together; wherein the theme object is a modular part that is associated with the second file format; wherein the theme object provides a common appearance for the first kind of document and the second kind of document.
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16. A system for providing thematic information to provide a visual theme for documents, comprising: a computer readable storage medium encoded with a theme object for conveying thematic information for visual display of documents; wherein the theme object is defined using a markup language and is stored in a theme file; wherein the definition of the theme object is maintained separately within the theme file from other objects that define the document and that are each maintained separately; and wherein a schema defines and enforces rules for displaying the theme object; an operating system executed on a processor; wherein the operating system provides an application programming interface (API) to the theme object; an application suite executed on a processor; wherein the application suite comprises a first application for authoring a first kind of document using the API to the theme object, and comprising a second application that is different from the first application for authoring a second kind of document using the API to the theme object; wherein the first kind of document is associated with a first file format that includes modular parts that are associated together; wherein the theme object is a modular part that is associated with the first file format; wherein the second kind of document is associated with a second file format that includes modular parts that are associated together; wherein the theme object is a modular part that is associated with the second file format; wherein the theme object provides a common appearance for the first kind of document and the second kind of document. 17. The system of claim 16 wherein the first application is a spreadsheet application and the second application is a word processing application.
| 0.584403 |
1. A method, in a data processing system, for deploying a web service, comprising: retrieving a deployment descriptor for the web service; determining, by a processor unit, a location type for the web service from the deployment descriptor, wherein the location type identifies whether a description of a real implementation of the web service supporting a portType comprises at least one of WSDL and JavaBean; and responsive to a determination that the location type for the web service indicates that the web service is defined by both a JavaBean and a web service description language document, deploying the web service based on the location type for the web service, wherein the deployment descriptor describes how the web service is deployed in the data processing system.
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1. A method, in a data processing system, for deploying a web service, comprising: retrieving a deployment descriptor for the web service; determining, by a processor unit, a location type for the web service from the deployment descriptor, wherein the location type identifies whether a description of a real implementation of the web service supporting a portType comprises at least one of WSDL and JavaBean; and responsive to a determination that the location type for the web service indicates that the web service is defined by both a JavaBean and a web service description language document, deploying the web service based on the location type for the web service, wherein the deployment descriptor describes how the web service is deployed in the data processing system. 5. The method of claim 1 , wherein if the location type is determined to indicate that the web service is defined by a web services description language (WSDL) document only, deploying the web service includes: generating an internal definition of the web service based on the WSDL document.
| 0.614224 |
8. A non-transitory computer-readable storage medium having stored thereon instructions, which when executed by a processor result in one or more operations configured for use in a text-to-speech (TTS) system, the operations comprising: identifying, using one or more processors, a word or phrase as a named entity; identifying a language of origin associated with the named entity; transliterating the named entity to a script associated with the language of origin; if the TTS system is operating in the language of origin, passing the transliterated script to the TTS system; and if the TTS system is not operating in the language of origin, generating a phoneme sequence in the language of origin using a grapheme to phoneme (G2P) converter.
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8. A non-transitory computer-readable storage medium having stored thereon instructions, which when executed by a processor result in one or more operations configured for use in a text-to-speech (TTS) system, the operations comprising: identifying, using one or more processors, a word or phrase as a named entity; identifying a language of origin associated with the named entity; transliterating the named entity to a script associated with the language of origin; if the TTS system is operating in the language of origin, passing the transliterated script to the TTS system; and if the TTS system is not operating in the language of origin, generating a phoneme sequence in the language of origin using a grapheme to phoneme (G2P) converter. 9. The non-transitory computer-readable storage medium of claim 8 , further comprising: if the TTS system is not operating in the language of origin, mapping the phoneme sequence to a sequence of target language phonemes.
| 0.511765 |
1. A method of replicating IP address assignment changes in a distributed database having a plurality of nodes, comprising: receiving a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database, wherein a change request to modify the distributed database is expressed as the semantic command, the semantic command being expressed as one of a predefined set of commands, wherein the receiving of the semantic command at the first node comprises: receiving credentials of a user; and determining whether to authorize the user based on the received credentials, the user being authorized in the event that the user has not been previously authorized within a predetermined time period; and provisionally applying the semantic command to the first local version of the database using a processor before sending the semantic command to the master node, wherein the provisional applying the semantic command to the first local version of the database comprises modifying the first local version of the database before reconciling the modification with the master node, wherein the reconciling of the modification with the master comprises: forwarding the received credentials to the master; determining whether the modification would cause a conflict on the master, comprising: determining whether the same user has been authorized on a second node within the predetermined time period; and in the event that the modification would not cause a conflict, performing the modification on the master node.
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1. A method of replicating IP address assignment changes in a distributed database having a plurality of nodes, comprising: receiving a semantic command at a first node having a first local version of the database, wherein the semantic command comprises a semantically expressed request to modify one or more IP address assignments in the database that allows for provisional modification of the first local version of the database before sending the semantic command to a master node having a master version of the database, wherein a change request to modify the distributed database is expressed as the semantic command, the semantic command being expressed as one of a predefined set of commands, wherein the receiving of the semantic command at the first node comprises: receiving credentials of a user; and determining whether to authorize the user based on the received credentials, the user being authorized in the event that the user has not been previously authorized within a predetermined time period; and provisionally applying the semantic command to the first local version of the database using a processor before sending the semantic command to the master node, wherein the provisional applying the semantic command to the first local version of the database comprises modifying the first local version of the database before reconciling the modification with the master node, wherein the reconciling of the modification with the master comprises: forwarding the received credentials to the master; determining whether the modification would cause a conflict on the master, comprising: determining whether the same user has been authorized on a second node within the predetermined time period; and in the event that the modification would not cause a conflict, performing the modification on the master node. 2. A method as recited in claim 1 , wherein if the semantic command includes any IP address assignment changes that would result in an IP address assignment conflict with IP address assignment data stored in the master version of the database on the master node, then the semantic command is not applied to the master node.
| 0.751152 |
1. A method for providing a document comprising: processing, by one or more processors, a graphical document to identify one or more ideas associated with the graphical document including processing documents that are linked to the graphical document to derive at least one of the one or more ideas; receiving, by the one or more processors, a request for a document where the document is associated with a concept; comparing, by the one or more processors, the one or more ideas with the concept; and responsive to the request, delivering, by the one or more processors, the graphical document based on the comparison if the one or more ideas match the concept.
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1. A method for providing a document comprising: processing, by one or more processors, a graphical document to identify one or more ideas associated with the graphical document including processing documents that are linked to the graphical document to derive at least one of the one or more ideas; receiving, by the one or more processors, a request for a document where the document is associated with a concept; comparing, by the one or more processors, the one or more ideas with the concept; and responsive to the request, delivering, by the one or more processors, the graphical document based on the comparison if the one or more ideas match the concept. 2. The method of claim 1 , wherein processing the graphical document to identify one or more ideas associated with the graphical document comprises: identifying one or more documents similar to the graphical document; and identifying that the one or more ideas are associated with the one or more similar documents.
| 0.602691 |
1. A method for automatically marking a document to be read by a text-to-speech reader with voice type identifiers, said method comprising: identifying two or more voice types available to the text-to-speech reader, each voice type having a corresponding voice type identifier; identifying text elements within the document, wherein identifying text elements comprises marking gross structural subdivisions of text with a first set of sequenced tags, marking individual paragraphs of the text with a second set of sequenced tags, and marking text elements with a third set of sequenced tags to generate a hierarchical tree identifying the text elements; grouping similar text elements together, wherein the step of grouping comprises generating one or more clusters according to each identifiable topic of the document, syntactically parsing the document and subsequently performing text mining to determine which text elements in the document are similar, wherein similarity is based upon lexical affinities among the text elements; classifying the grouped text elements according to voice types available to the text-to-speech reader; and marking the classified grouped text elements within the document with corresponding voice type identifiers.
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1. A method for automatically marking a document to be read by a text-to-speech reader with voice type identifiers, said method comprising: identifying two or more voice types available to the text-to-speech reader, each voice type having a corresponding voice type identifier; identifying text elements within the document, wherein identifying text elements comprises marking gross structural subdivisions of text with a first set of sequenced tags, marking individual paragraphs of the text with a second set of sequenced tags, and marking text elements with a third set of sequenced tags to generate a hierarchical tree identifying the text elements; grouping similar text elements together, wherein the step of grouping comprises generating one or more clusters according to each identifiable topic of the document, syntactically parsing the document and subsequently performing text mining to determine which text elements in the document are similar, wherein similarity is based upon lexical affinities among the text elements; classifying the grouped text elements according to voice types available to the text-to-speech reader; and marking the classified grouped text elements within the document with corresponding voice type identifiers. 2. The method as claimed in claim 1 , wherein the step of identifying text elements comprises breaking down the document into elements and separating out the text elements.
| 0.524528 |
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