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6. The method of claim 1 further comprising: presenting the suggested personalized reaction to the first user; receiving input from the first user; determining whether the input is to send the suggested personalized reaction; and modifying a suggestion module based on the received input if the input was to send the suggested personalized reaction. | 6. The method of claim 1 further comprising: presenting the suggested personalized reaction to the first user; receiving input from the first user; determining whether the input is to send the suggested personalized reaction; and modifying a suggestion module based on the received input if the input was to send the suggested personalized reaction. 7. The method of claim 6 wherein modifying the suggestion module includes updating a decision tree based upon the suggested personalized reaction being sent. | 0.934579 |
1. A computer-implemented method for linking documents with multiple topics to related documents, implemented using a client/server network architecture, comprising: in advance of a user search request, searching in a seed source to identify seed documents having at least one discrete seed topic but lacking target document links, using the client/server network architecture, each seed document belonging to one of a plurality of collections of seed documents, each collection having a target source map defining a list of target sources to search to generate target document links for seed documents belonging in the collection, wherein the at least one seed topic corresponds to a topical classification assigned from a taxonomy for a specific subject area, and wherein the at least one seed topic is pre-defined in advance of a user search request; retrieving and formatting the identified seed documents, in advance of a user search request, using the client/server network architecture; extracting the at least one seed topic for each retrieved seed document, in advance of a user search request, using the client/server network architecture; for each retrieved seed document, retrieving the list of the target sources found in the target source map for the collection to which the seed document belongs, in advance of a user search request, using the client/server network architecture; and for each seed topic within each retrieved seed document, processing each target source within the list of target sources defined by the target source map for the collection to which the retrieved seed document belongs, to pre-establish a target document link for the seed topic using a natural language search constructed from the seed topic, in advance of a user search request, using the client/server network architecture. | 1. A computer-implemented method for linking documents with multiple topics to related documents, implemented using a client/server network architecture, comprising: in advance of a user search request, searching in a seed source to identify seed documents having at least one discrete seed topic but lacking target document links, using the client/server network architecture, each seed document belonging to one of a plurality of collections of seed documents, each collection having a target source map defining a list of target sources to search to generate target document links for seed documents belonging in the collection, wherein the at least one seed topic corresponds to a topical classification assigned from a taxonomy for a specific subject area, and wherein the at least one seed topic is pre-defined in advance of a user search request; retrieving and formatting the identified seed documents, in advance of a user search request, using the client/server network architecture; extracting the at least one seed topic for each retrieved seed document, in advance of a user search request, using the client/server network architecture; for each retrieved seed document, retrieving the list of the target sources found in the target source map for the collection to which the seed document belongs, in advance of a user search request, using the client/server network architecture; and for each seed topic within each retrieved seed document, processing each target source within the list of target sources defined by the target source map for the collection to which the retrieved seed document belongs, to pre-establish a target document link for the seed topic using a natural language search constructed from the seed topic, in advance of a user search request, using the client/server network architecture. 3. The method of claim 1 , further comprising the step of preparing a source to be a target source by preparing documents in the source to be target documents in the target source, by assigning basic definitions to the target source, wherein the basic definitions include a definition of a portion of each of the target documents suitable as a description of the target document for purposes of displaying a link to a user, and a definition for generating a term vector for the target document, prior to the searching step. | 0.621223 |
1. A system comprising: one or more processors; a database schema including a plurality of data sources, each data source including one or more fields for storing data, and metadata defining relationships amongst the fields within or between data sources; a schema parser executed by at least one of the processors and configured to determine one or more datasets of data stored within or referenced from the database schema, wherein a dataset includes one or more fields from the database schema and represents the data stored in the one or more fields; an input handler executed by at least one of the processors and configured to receive a user's selection of one or more of the datasets via a graphical user interface, wherein the input handler is configured to determine that a first graphical icon representing a first dataset is graphically associated within the graphical user interface with a second graphical icon representing a second dataset; a translation engine executed by at least one of the processors and configured to provide, responsive to the graphical association of the first and second icons, operations for refining the data of the selected datasets into a result set via a query, wherein the translation engine is configured to determine which operations to provide based on the relationships of the selected datasets as stored or derived from the metadata, wherein the translation engine is configured to provide the operations to a user via the interface, wherein the operations are provided in a natural language expression corresponding to the relationships as determined from the metadata, wherein the input handler is configured to receive a selection of one of the operations provided by the translation engine; a query engine executed by at least one of the processors and configured to provide a graphical depiction of the query via the interface, the graphical query including operational flow indicators indicating a directional flow of the query from the selected datasets with the selected operation resulting in the result set; and a logic engine executed by at least one of the processors and configured to assemble a machine readable structured query language (SQL) query based on the graphical depiction of the query, wherein the logic engine comprises a plurality of different subroutines, each different subroutine being configured to process a different type of operation represented by a particular type of element in the graphical query to generate a SQL substatement of the elements's operation wherein the logic engine is further configured to incorporate the SQL substatements into a complete machine readable SQL query. | 1. A system comprising: one or more processors; a database schema including a plurality of data sources, each data source including one or more fields for storing data, and metadata defining relationships amongst the fields within or between data sources; a schema parser executed by at least one of the processors and configured to determine one or more datasets of data stored within or referenced from the database schema, wherein a dataset includes one or more fields from the database schema and represents the data stored in the one or more fields; an input handler executed by at least one of the processors and configured to receive a user's selection of one or more of the datasets via a graphical user interface, wherein the input handler is configured to determine that a first graphical icon representing a first dataset is graphically associated within the graphical user interface with a second graphical icon representing a second dataset; a translation engine executed by at least one of the processors and configured to provide, responsive to the graphical association of the first and second icons, operations for refining the data of the selected datasets into a result set via a query, wherein the translation engine is configured to determine which operations to provide based on the relationships of the selected datasets as stored or derived from the metadata, wherein the translation engine is configured to provide the operations to a user via the interface, wherein the operations are provided in a natural language expression corresponding to the relationships as determined from the metadata, wherein the input handler is configured to receive a selection of one of the operations provided by the translation engine; a query engine executed by at least one of the processors and configured to provide a graphical depiction of the query via the interface, the graphical query including operational flow indicators indicating a directional flow of the query from the selected datasets with the selected operation resulting in the result set; and a logic engine executed by at least one of the processors and configured to assemble a machine readable structured query language (SQL) query based on the graphical depiction of the query, wherein the logic engine comprises a plurality of different subroutines, each different subroutine being configured to process a different type of operation represented by a particular type of element in the graphical query to generate a SQL substatement of the elements's operation wherein the logic engine is further configured to incorporate the SQL substatements into a complete machine readable SQL query. 5. The system of claim 1 , wherein, in response to the input handler receiving a selection of one of the provided operations, the query engine is configured to provide a graphical depiction of the query via the interface, the graphical query including a third icon representing a third dataset formed in response to the selected operation, the third icon being connected to the first and second icons by one or more operational flow indicators indicating a directional flow of the query from the first and second datasets to the third dataset. | 0.544686 |
11. A system for configuring knowledge sets and AI algorithms, useful in association with an automated messaging system, the system comprising: an AI trainer configured to: receive a at least one training message; select a subsection of text from the at least one training message; select a knowledge set from a plurality of knowledge sets for the selected subsection of text based upon user, industry, and service type, wherein each knowledge set includes probabilistic associations between a term and a category; select an insight from a plurality of insights for the selected subsection of text based upon associations of the terms within the subsection of text given the selected knowledge set; categorize the training message based upon the insight; receive one of approval or rejection of the categorization; and update the probabilistic associations in response to the received approval or rejection to improve classification accuracy. | 11. A system for configuring knowledge sets and AI algorithms, useful in association with an automated messaging system, the system comprising: an AI trainer configured to: receive a at least one training message; select a subsection of text from the at least one training message; select a knowledge set from a plurality of knowledge sets for the selected subsection of text based upon user, industry, and service type, wherein each knowledge set includes probabilistic associations between a term and a category; select an insight from a plurality of insights for the selected subsection of text based upon associations of the terms within the subsection of text given the selected knowledge set; categorize the training message based upon the insight; receive one of approval or rejection of the categorization; and update the probabilistic associations in response to the received approval or rejection to improve classification accuracy. 18. The system of claim 11 , further comprising a knowledge set manager configured to generate a new knowledge set in the plurality of knowledge sets. | 0.531657 |
1. A computer device including a processor, a memory coupled to the processor, and a program stored in the memory, wherein the computer is configured to execute the program and perform the steps of: providing a collection of documents, wherein said collection includes at least one document; receiving a word or word string query to be analyzed; searching by a processor, said collection of documents for the query to be analyzed and returning documents containing the query to be analyzed; determining a user-defined amount of words or word strings or both to the left of said query to be analyzed in said returned documents based on their frequency and creating a Left Signature List comprising each of said words and word strings to the left of said query to be analyzed in said returned documents; searching said collection of documents for the words and word strings on the Left Signature List and returning second documents containing said words and word strings on the Left Signature List; determining a user-defined amount of words or word strings or both to the right of each of said words and word strings comprising said Left Signature List in said second returned documents and creating Left Anchor Lists comprising each of said words and word strings to the right of each of said words and word strings on the Left Signature List based on their frequency in said second returned documents; determining a user-defined number of words or word strings or both to the right of said query to be analyzed in said returned documents and creating a Right Signature List comprising each of said words and word strings to the right of said query to be analyzed in said returned documents based on their frequency; searching said collection of documents for each of said words and word strings on the Right Signature List and returning third documents containing said words and word strings on the Right Signature List; determining a user-defined number of words or word strings or both to the left of each of said words and word strings comprising said Right Signature List in said third returned documents and creating Right Anchor Lists comprising each of said words and word strings to the left of each of said words and word strings on the Right Signature List based on their frequency in said third returned documents; and ranking results based on the number of different Anchor Lists on which the result appears so long as the result appears on at least one Left Anchor List and one Right Anchor List. | 1. A computer device including a processor, a memory coupled to the processor, and a program stored in the memory, wherein the computer is configured to execute the program and perform the steps of: providing a collection of documents, wherein said collection includes at least one document; receiving a word or word string query to be analyzed; searching by a processor, said collection of documents for the query to be analyzed and returning documents containing the query to be analyzed; determining a user-defined amount of words or word strings or both to the left of said query to be analyzed in said returned documents based on their frequency and creating a Left Signature List comprising each of said words and word strings to the left of said query to be analyzed in said returned documents; searching said collection of documents for the words and word strings on the Left Signature List and returning second documents containing said words and word strings on the Left Signature List; determining a user-defined amount of words or word strings or both to the right of each of said words and word strings comprising said Left Signature List in said second returned documents and creating Left Anchor Lists comprising each of said words and word strings to the right of each of said words and word strings on the Left Signature List based on their frequency in said second returned documents; determining a user-defined number of words or word strings or both to the right of said query to be analyzed in said returned documents and creating a Right Signature List comprising each of said words and word strings to the right of said query to be analyzed in said returned documents based on their frequency; searching said collection of documents for each of said words and word strings on the Right Signature List and returning third documents containing said words and word strings on the Right Signature List; determining a user-defined number of words or word strings or both to the left of each of said words and word strings comprising said Right Signature List in said third returned documents and creating Right Anchor Lists comprising each of said words and word strings to the left of each of said words and word strings on the Right Signature List based on their frequency in said third returned documents; and ranking results based on the number of different Anchor Lists on which the result appears so long as the result appears on at least one Left Anchor List and one Right Anchor List. 2. The computer device of claim 1 , wherein said ranking results includes multiplying a total frequency of each word or word string occurring in said Left Anchor Lists by a total frequency of said word or word string occurring in said Right Anchor Lists. | 0.536154 |
14. An article comprising: a storage medium comprising machine-readable instructions stored thereon which, are executable by a computing platform to: record user interactions from a plurality of users with one or more contextual shortcuts, said one or more contextual shortcuts to comprise one or more user-selectable keyword anchors; update an index to be based, at least in part, on said user interactions from said plurality of users, said update to at least add at least one previously non-indexed electronic document to said index at least partially in response to receipt of one or more user interactions with said one or more contextual shortcuts to be contained within said at least one previously non-indexed electronic document, wherein said index is to be searchable by said plurality of users; process a search query from a user to be based, at least in part, on a user selection of a given user-selectable keyword anchor to be associated with a contextual shortcut; and perform a search query on said indexed one or more electronic documents based, at least in part, on said user selection of said given user-selectable keyword anchor in an electronic document to determine a ranked list of said one or more electronic documents to be associated with sad search query, wherein said ranked list is determined based at least in part on the recorded said user interactions from the plurality of users. | 14. An article comprising: a storage medium comprising machine-readable instructions stored thereon which, are executable by a computing platform to: record user interactions from a plurality of users with one or more contextual shortcuts, said one or more contextual shortcuts to comprise one or more user-selectable keyword anchors; update an index to be based, at least in part, on said user interactions from said plurality of users, said update to at least add at least one previously non-indexed electronic document to said index at least partially in response to receipt of one or more user interactions with said one or more contextual shortcuts to be contained within said at least one previously non-indexed electronic document, wherein said index is to be searchable by said plurality of users; process a search query from a user to be based, at least in part, on a user selection of a given user-selectable keyword anchor to be associated with a contextual shortcut; and perform a search query on said indexed one or more electronic documents based, at least in part, on said user selection of said given user-selectable keyword anchor in an electronic document to determine a ranked list of said one or more electronic documents to be associated with sad search query, wherein said ranked list is determined based at least in part on the recorded said user interactions from the plurality of users. 16. The article of claim 14 , wherein said machine-readable instructions which are further executable by the computing platform to initiate transmission of said ranked list of the one or more electronic documents to said user via a contextual search interface to be based, at least in part, on a given contextual content to be associated with said given contextual shortcut. | 0.678017 |
15. A computer system comprising: a processor; and a non-transitory computer readable medium having stored thereon program code that causes the processor to, upon being executed: receive a query to be executed; assign a priority to the query, the priority being identical to priorities assigned to one or more previously received queries; divide the query into a plurality of sub-queries; assign a sub-priority to each sub-query in the plurality of sub-queries, wherein the sub-priority for each sub-query of the query is identical to each other, and wherein the sub-priority is based on a resource consumption metric of the query that reflects an amount of computing resources consumed due to execution of the query; select, from a plurality of sub-query pools, a sub-query pool that is associated with the priority of the query, the selected sub-query pool including sub-queries of the one or more previously received queries; and add the plurality of sub-queries to the selected sub-query pool. | 15. A computer system comprising: a processor; and a non-transitory computer readable medium having stored thereon program code that causes the processor to, upon being executed: receive a query to be executed; assign a priority to the query, the priority being identical to priorities assigned to one or more previously received queries; divide the query into a plurality of sub-queries; assign a sub-priority to each sub-query in the plurality of sub-queries, wherein the sub-priority for each sub-query of the query is identical to each other, and wherein the sub-priority is based on a resource consumption metric of the query that reflects an amount of computing resources consumed due to execution of the query; select, from a plurality of sub-query pools, a sub-query pool that is associated with the priority of the query, the selected sub-query pool including sub-queries of the one or more previously received queries; and add the plurality of sub-queries to the selected sub-query pool. 16. The computer system of claim 15 wherein the program code further causes the processor to, when a CPU is available for executing a sub-query: identify a sub-query pool from the plurality of sub-query pools that includes one or more unexecuted sub-queries and is associated with the highest priority; update the sub-priority for each sub-query in the identified sub-query pool; select a sub-query from the identified sub-query pool having the highest sub-priority; and schedule the selected sub-query for execution on the CPU. | 0.507524 |
9. The method of claim 1 , further comprising: receiving markup data stored in the electronic counterpart to the printed document, wherein the markup data comprises at least one of actions or rules for determining actions, and wherein the markup data is applied to perform one or more actions that involve the captured text. | 9. The method of claim 1 , further comprising: receiving markup data stored in the electronic counterpart to the printed document, wherein the markup data comprises at least one of actions or rules for determining actions, and wherein the markup data is applied to perform one or more actions that involve the captured text. 10. The method of claim 9 , wherein the context information is in the form of digital information associated with the printed document comprising multimedia data, reference materials, or a link to the online discussion forum. | 0.881477 |
1. A computer-implemented method for detecting scareware comprising: accessing, using a web crawler and without regard to a particular search query, one or more webpages to be evaluated, at least one of which being a landing page effective to automatically access one or more redirection pages; comparing, using a classifier, the features extracted with features of known scareware and non-scareware pages, the known scareware and non-scareware pages having been previously classified by the classifier, the comparing comprising determining features effective to determine a likelihood that the landing page and the one or more redirection pages is a scareware page based on the number of times the considered feature occurs in the known scareware pages, the number of times the considered feature does not occur in the known scareware pages, the number of times the considered feature occurs in the known non-scareware pages, and the number of times the considered feature does not occur in the known non-scareware pages; and in response to determining the landing page or at least one of the redirection pages is a scareware page, storing page data and pop-up data associated with the landing page and any associated redirection pages with a label indicating the page data and pop-up data are associated with a scareware page, and storing reference feature data for the scareware page locally. | 1. A computer-implemented method for detecting scareware comprising: accessing, using a web crawler and without regard to a particular search query, one or more webpages to be evaluated, at least one of which being a landing page effective to automatically access one or more redirection pages; comparing, using a classifier, the features extracted with features of known scareware and non-scareware pages, the known scareware and non-scareware pages having been previously classified by the classifier, the comparing comprising determining features effective to determine a likelihood that the landing page and the one or more redirection pages is a scareware page based on the number of times the considered feature occurs in the known scareware pages, the number of times the considered feature does not occur in the known scareware pages, the number of times the considered feature occurs in the known non-scareware pages, and the number of times the considered feature does not occur in the known non-scareware pages; and in response to determining the landing page or at least one of the redirection pages is a scareware page, storing page data and pop-up data associated with the landing page and any associated redirection pages with a label indicating the page data and pop-up data are associated with a scareware page, and storing reference feature data for the scareware page locally. 5. The method of claim 1 further comprising: constructing at least one feature vector for the one or more landing page and one or more redirection pages; comparing the at least one constructed feature vector with at least one feature vector of known scareware and non-scareware pages. | 0.679625 |
51. A method according to claim 50, wherein the parameters comprise information for modifying inputted characters. | 51. A method according to claim 50, wherein the parameters comprise information for modifying inputted characters. 52. A method according to claim 51, wherein the graphic patterns corresponding to the character patterns represent a variety of kinds of modifying information. | 0.951865 |
1. A document processing apparatus comprising: first word extracting means for extracting a first word from document data; preceding/subsequent word extracting means for extracting, from the document data, a second word that is one of a preceding word and a subsequent word of the first word; keyword extracting means for extracting a keyword of the document data, based on a frequency of occurrence of the first word, wherein said keyword extracting means includes word counting means for counting a number of occurrences of each word, other than unnecessary words which are pre-excluded from being keywords, in the document data, said keyword extracting means extracting a word having a high number of occurrences, counted by said word counting means, as the keyword; and translation means for translating the keyword into a predetermined language by referring to a dictionary in a process that considers a meaning of the first and second words existing together in the document data. | 1. A document processing apparatus comprising: first word extracting means for extracting a first word from document data; preceding/subsequent word extracting means for extracting, from the document data, a second word that is one of a preceding word and a subsequent word of the first word; keyword extracting means for extracting a keyword of the document data, based on a frequency of occurrence of the first word, wherein said keyword extracting means includes word counting means for counting a number of occurrences of each word, other than unnecessary words which are pre-excluded from being keywords, in the document data, said keyword extracting means extracting a word having a high number of occurrences, counted by said word counting means, as the keyword; and translation means for translating the keyword into a predetermined language by referring to a dictionary in a process that considers a meaning of the first and second words existing together in the document data. 2. A document processing apparatus according to claim 1, further comprising designation means for designating a language into which the translation is to be made by said translation means. | 0.852396 |
6. A system for providing contextual validation of synonyms in ontology driven natural language processing (NLP), the system comprising: a memory medium comprising instructions; a bus coupled to the memory medium; and a processor coupled to a NLP engine via the bus that when executing the instructions causes the system to: receive a user input of natural language text containing a token that identifies a unit of the natural language text; structure the user input into a semantic model comprising a set of classes each containing a set of related permutations of the token; designate the token as a synonym of one of the set of related permutations; annotate the token with a class from the set of classes corresponding to the one of the set of related permutations; quantify a linear distance as a number of words between the token and a contextual token within the user input; compare the quantified linear distance to a pre-specified limit to the number of words; when, based on the comparing, the quantified linear distance is within the pre-specified limit to the number of words, assign a high confidence level to the annotation, and validate the annotation based on the high confidence level; and when, based on the comparing, the quantified linear distance is not within the pre-specified limit to the number of words, assign a low confidence level to the annotation. | 6. A system for providing contextual validation of synonyms in ontology driven natural language processing (NLP), the system comprising: a memory medium comprising instructions; a bus coupled to the memory medium; and a processor coupled to a NLP engine via the bus that when executing the instructions causes the system to: receive a user input of natural language text containing a token that identifies a unit of the natural language text; structure the user input into a semantic model comprising a set of classes each containing a set of related permutations of the token; designate the token as a synonym of one of the set of related permutations; annotate the token with a class from the set of classes corresponding to the one of the set of related permutations; quantify a linear distance as a number of words between the token and a contextual token within the user input; compare the quantified linear distance to a pre-specified limit to the number of words; when, based on the comparing, the quantified linear distance is within the pre-specified limit to the number of words, assign a high confidence level to the annotation, and validate the annotation based on the high confidence level; and when, based on the comparing, the quantified linear distance is not within the pre-specified limit to the number of words, assign a low confidence level to the annotation. 8. The system according to claim 6 , further comprising instructions causing the system to restructure the semantic model to include a knowledge structure containing the contextual token, the quantified linear distance, the pre-specified linear distance limit, and the designation of the token as a synonym of the one of the set of related permutations. | 0.53839 |
2. The specific call detecting device according to claim 1 , wherein the voice recognition execution determining unit determines that the first voice is a target of voice recognition until a period in which the utterance ratio is higher than a predetermined threshold, reaches a first period, and determines that the first voice is not a target of voice recognition after the period in which the utterance ratio is higher than the threshold, reaches the first period. | 2. The specific call detecting device according to claim 1 , wherein the voice recognition execution determining unit determines that the first voice is a target of voice recognition until a period in which the utterance ratio is higher than a predetermined threshold, reaches a first period, and determines that the first voice is not a target of voice recognition after the period in which the utterance ratio is higher than the threshold, reaches the first period. 5. The specific call detecting device according to claim 2 , further comprising a psychological state determining unit which determines whether a psychological state of the first speaker is normal or not on the basis of the first voice, wherein the voice recognition execution determining unit sets the first period when it is determined that the psychological state of the first speaker is not normal to be longer than the first period when it is determined that the psychological state of the first speaker is normal. | 0.812003 |
1. A method for generating a publication, the method comprising: generating a template for one or more pages, the template including one or more address sable blocks; receiving base content, wherein the base content is content that remains the same for different versions of the publication; generating at least one structured document for the publication, each structured document including one or more entry fields corresponding to the one or more addressable blocks, wherein each structured document includes or refers to version information in the one or more entry fields, and wherein the version information is content that is different for different versions of the publication; receiving a plurality of structured documents, wherein each structured document is received from each of two or more entities; merging the plurality of structured documents into a master structured document; generating a design application version of the structured document from each of the two or more entities, the design application version compatible with a design application; and automatically generating a plurality of versions of the publication using the design application, wherein the generating of the plurality of versions of the publication is performed after the merging the plurality of structured documents from the two or more entities into the master structured document, wherein each version of the publication is generated using the template, the base content, and version information included in or referred to in at least one structured document received from the two or more of the entities, the version information inserted based on the one or more addressable blocks in a page of the version based on the one or more codes associated with the one or more entry fields; displaying the plurality of versions of the publication on one page, wherein the page includes a plurality of sections, wherein the sections include the same base content, wherein each section is associated with a different version, wherein each version is associated with a different entity of the two or more entities, wherein each section includes different version information that corresponds to a different entity, and wherein after all pages of the publication have been generated, the pages are changeable if needed; and after generating a structured document that includes a first page of the publication with multiple versions: determining if a second page of the publication is to include one or more versions; generating a template for the second page; and adding version information for the template for the second page to one of a structured document that is already created or a new structured document that is generated for the template for the second page. | 1. A method for generating a publication, the method comprising: generating a template for one or more pages, the template including one or more address sable blocks; receiving base content, wherein the base content is content that remains the same for different versions of the publication; generating at least one structured document for the publication, each structured document including one or more entry fields corresponding to the one or more addressable blocks, wherein each structured document includes or refers to version information in the one or more entry fields, and wherein the version information is content that is different for different versions of the publication; receiving a plurality of structured documents, wherein each structured document is received from each of two or more entities; merging the plurality of structured documents into a master structured document; generating a design application version of the structured document from each of the two or more entities, the design application version compatible with a design application; and automatically generating a plurality of versions of the publication using the design application, wherein the generating of the plurality of versions of the publication is performed after the merging the plurality of structured documents from the two or more entities into the master structured document, wherein each version of the publication is generated using the template, the base content, and version information included in or referred to in at least one structured document received from the two or more of the entities, the version information inserted based on the one or more addressable blocks in a page of the version based on the one or more codes associated with the one or more entry fields; displaying the plurality of versions of the publication on one page, wherein the page includes a plurality of sections, wherein the sections include the same base content, wherein each section is associated with a different version, wherein each version is associated with a different entity of the two or more entities, wherein each section includes different version information that corresponds to a different entity, and wherein after all pages of the publication have been generated, the pages are changeable if needed; and after generating a structured document that includes a first page of the publication with multiple versions: determining if a second page of the publication is to include one or more versions; generating a template for the second page; and adding version information for the template for the second page to one of a structured document that is already created or a new structured document that is generated for the template for the second page. 8. The method of claim 1 , wherein the page for the version is created using base content that is similar for each of the versions, and wherein each of the versions includes different version information. | 0.530424 |
1. A computer-implemented process, comprising: receiving a machine-learned facet model; the machine-learned facet model automatically generated by applying one or more automated machine-learning processes to a plurality of examples of training data to train the machine-learned facet model; the plurality of examples of training data comprising a plurality of automatically clustered and labeled instances of sentiment vocabulary extracted from sentiment bearing content; applying the machine-learned facet model to evaluate a plurality of samples of sentiment-bearing content to identify conversational topics and facets associated with one or more segments of that content; identifying one or more of the facets that have a consensus based on two or more samples of the sentiment-bearing content; generating a plurality of sentiment-based recommendations about one or more of the identified facets that have a consensus; and applying one or more of the sentiment-based recommendations to change a visual appearance of existing content to indicate a type of sentiment associated with one or more corresponding facets identified in the existing content. | 1. A computer-implemented process, comprising: receiving a machine-learned facet model; the machine-learned facet model automatically generated by applying one or more automated machine-learning processes to a plurality of examples of training data to train the machine-learned facet model; the plurality of examples of training data comprising a plurality of automatically clustered and labeled instances of sentiment vocabulary extracted from sentiment bearing content; applying the machine-learned facet model to evaluate a plurality of samples of sentiment-bearing content to identify conversational topics and facets associated with one or more segments of that content; identifying one or more of the facets that have a consensus based on two or more samples of the sentiment-bearing content; generating a plurality of sentiment-based recommendations about one or more of the identified facets that have a consensus; and applying one or more of the sentiment-based recommendations to change a visual appearance of existing content to indicate a type of sentiment associated with one or more corresponding facets identified in the existing content. 2. The computer-implemented process of claim 1 further comprising: generating a plurality of conversational utterances about one or more of the identified facets that have a consensus; and outputting one or more relevant conversational utterances via one or more output devices. | 0.622096 |
1. A computer-implemented method including steps for the improvement of storage and searching in at least one computer system by organizing files, data items, web site members, or web pages, the method comprising: automatically determining with a data processor user-defined metalabels for each of a plurality of electronic files, data items, web site members, or web pages; automatically organizing with a hardware data processor the user-defined metalabels for each of Rail the plurality of electronic files, data items, web site members, or web pages into a plurality of hierarchical structures for improving search functions in or across the at least one computer system, wherein the each of the electronic files, data items, web site members, or web pages is identifiable by a filename, file path, member identification, or domain name on a corresponding computer, and each of the plurality of user-defined metalabels in the plurality of hierarchical structures provides a computer location of the each of the plurality of electronic files, data items, web site members, or web pages; automatically and individually weighting each of the user-defined metalabels as a function of relevance; automatically associating the corresponding weighting with each of the user-defined metalabels; and automatically organizing and/or filtering searches of the metalabels using the weighting to improve or narrow search results for a query of the at least one computer system. | 1. A computer-implemented method including steps for the improvement of storage and searching in at least one computer system by organizing files, data items, web site members, or web pages, the method comprising: automatically determining with a data processor user-defined metalabels for each of a plurality of electronic files, data items, web site members, or web pages; automatically organizing with a hardware data processor the user-defined metalabels for each of Rail the plurality of electronic files, data items, web site members, or web pages into a plurality of hierarchical structures for improving search functions in or across the at least one computer system, wherein the each of the electronic files, data items, web site members, or web pages is identifiable by a filename, file path, member identification, or domain name on a corresponding computer, and each of the plurality of user-defined metalabels in the plurality of hierarchical structures provides a computer location of the each of the plurality of electronic files, data items, web site members, or web pages; automatically and individually weighting each of the user-defined metalabels as a function of relevance; automatically associating the corresponding weighting with each of the user-defined metalabels; and automatically organizing and/or filtering searches of the metalabels using the weighting to improve or narrow search results for a query of the at least one computer system. 10. The method of claim 1 , further comprising ordering a display of metalabels as a function of relevancy values. | 0.622947 |
11. A computer-implemented method that facilitates searching within an online classifieds site comprising: monitoring updated items posted to the online classifieds site; determining, by a processing unit, that a match is present between at least one updated item and at least a user's geo-tag preferences, wherein the user's geo-tag preferences include at least two separate locations, and wherein the match is based on a detailed location description associated with the at least one updated item; alerting the user that at least one match is determined; and presenting a filtered location description comprising a mapped portion of the detailed location description associated with the at least one updated item to the user, wherein the mapped portion of the detailed location description illustrates a neighborhood associated with the at least one updated item. | 11. A computer-implemented method that facilitates searching within an online classifieds site comprising: monitoring updated items posted to the online classifieds site; determining, by a processing unit, that a match is present between at least one updated item and at least a user's geo-tag preferences, wherein the user's geo-tag preferences include at least two separate locations, and wherein the match is based on a detailed location description associated with the at least one updated item; alerting the user that at least one match is determined; and presenting a filtered location description comprising a mapped portion of the detailed location description associated with the at least one updated item to the user, wherein the mapped portion of the detailed location description illustrates a neighborhood associated with the at least one updated item. 16. The method of claim 11 , further comprising geo-tagging an item with its location information and posting it on the online classifieds site. | 0.688806 |
1. A method of performing translations between first and second natural languages comprising: a first step of sectioning a source text described by a first natural language word by word and storing the words in storage; a second step of deriving information regarding the parts-of-speech of the stored source words through retrieval of the parts-of-speech information from a lexical dictionary storage in which words are registered together with information regarding the parts-of-speech thereof; a third step of deriving target words in the second natural language which are equivalent in meaning to the respective stored source words in the first natural language; a fourth step of translating a first pattern of a string of parts-of-speech formed by gathering the parts-of-speech for each of the stored source words derived in said second step into a pattern in which the order of the parts-of-speech is in accordance with said first natural language, into a second pattern of a string-of-parts of speech with an order in accordance with said second natural language by referring to a translation pattern table which registers therein the correspondences between first patterns of parts-of-speech strings defining sequences of parts-of-speech of the first natural language and second patterns of parts-of-speech strings defining sequences of parts-of-speech of the second natural language; and a fifth step of generating a sentence in the second natural language by sequencing said target words in accordance with the sequential order of the parts-of-speech in said translated second pattern of the string of parts-of-speech of said second natural language. | 1. A method of performing translations between first and second natural languages comprising: a first step of sectioning a source text described by a first natural language word by word and storing the words in storage; a second step of deriving information regarding the parts-of-speech of the stored source words through retrieval of the parts-of-speech information from a lexical dictionary storage in which words are registered together with information regarding the parts-of-speech thereof; a third step of deriving target words in the second natural language which are equivalent in meaning to the respective stored source words in the first natural language; a fourth step of translating a first pattern of a string of parts-of-speech formed by gathering the parts-of-speech for each of the stored source words derived in said second step into a pattern in which the order of the parts-of-speech is in accordance with said first natural language, into a second pattern of a string-of-parts of speech with an order in accordance with said second natural language by referring to a translation pattern table which registers therein the correspondences between first patterns of parts-of-speech strings defining sequences of parts-of-speech of the first natural language and second patterns of parts-of-speech strings defining sequences of parts-of-speech of the second natural language; and a fifth step of generating a sentence in the second natural language by sequencing said target words in accordance with the sequential order of the parts-of-speech in said translated second pattern of the string of parts-of-speech of said second natural language. 2. A method of performing translation between natural languages according to claim 1, wherein the source words are extracted from the source text through a character-based examination with the aid of a space and/or a punctuation serving as a delimiter symbol at said first step. | 0.613573 |
34. A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for outputting data based on anomaly detection, the method comprising: receiving an input dataset; generating n-grams of different sizes from the input dataset; counting the number of distinct n-grams in the n-grams of different sizes that are not present in a binary anomaly detection model; computing an anomaly score based upon the number of distinct n-grams and a total count of the n-grams in the input dataset; using the anomaly score to determine whether an input dataset contains an anomaly; and outputting the input dataset based on whether the input dataset contains an anomaly. | 34. A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for outputting data based on anomaly detection, the method comprising: receiving an input dataset; generating n-grams of different sizes from the input dataset; counting the number of distinct n-grams in the n-grams of different sizes that are not present in a binary anomaly detection model; computing an anomaly score based upon the number of distinct n-grams and a total count of the n-grams in the input dataset; using the anomaly score to determine whether an input dataset contains an anomaly; and outputting the input dataset based on whether the input dataset contains an anomaly. 37. The medium of claim 34 , wherein the anomaly score is compared to a threshold level to determine whether the input dataset contains an anomaly. | 0.639797 |
15. The apparatus according to claim 14 , wherein the update unit executes the update using a Markov Chain Monte Carlo method. | 15. The apparatus according to claim 14 , wherein the update unit executes the update using a Markov Chain Monte Carlo method. 16. The apparatus according to claim 15 , wherein the update unit uses a filter structure of the weak classifier as a state of the weak classifier, and updates the state of the weak classifier by the Markov Chain Monte Carlo method using an evaluation function including the state of the weak classifier as vector elements. | 0.898241 |
1. A data processing method comprising: receiving, at a server computer, an electronic document comprising a plurality of unknown-language data elements each associated with one or more types; based on a document schema of the document, selecting one or more unknown-language data elements from the plurality of unknown-language data elements; assigning to each of the one or more unknown-language data elements a corresponding weight value based on a respective type of the unknown-language data element; comparing the one or more unknown-language data elements with a plurality of known-language data elements that are associated with the document schema; based on the comparing, determining a number of unknown-language data elements in the one or more unknown-language data elements that matched any in a subset of the plurality of known-language data elements, wherein the subset of known-language data elements corresponds to a particular language; based on the number of unknown-language data elements in the one or more unknown-language data elements that matched to the subset of known-language data elements and based on the corresponding weight value assigned to each unknown-language data element in the number of unknown-language data elements, determining a language confidence level value specifying a level of machine confidence that the document is expressed in the particular language; based on the language confidence level value for the particular language exceeding a language threshold value, automatically processing the document using the particular language. | 1. A data processing method comprising: receiving, at a server computer, an electronic document comprising a plurality of unknown-language data elements each associated with one or more types; based on a document schema of the document, selecting one or more unknown-language data elements from the plurality of unknown-language data elements; assigning to each of the one or more unknown-language data elements a corresponding weight value based on a respective type of the unknown-language data element; comparing the one or more unknown-language data elements with a plurality of known-language data elements that are associated with the document schema; based on the comparing, determining a number of unknown-language data elements in the one or more unknown-language data elements that matched any in a subset of the plurality of known-language data elements, wherein the subset of known-language data elements corresponds to a particular language; based on the number of unknown-language data elements in the one or more unknown-language data elements that matched to the subset of known-language data elements and based on the corresponding weight value assigned to each unknown-language data element in the number of unknown-language data elements, determining a language confidence level value specifying a level of machine confidence that the document is expressed in the particular language; based on the language confidence level value for the particular language exceeding a language threshold value, automatically processing the document using the particular language. 13. The method of claim 1 , further comprising: automatically determining that the document is encrypted; in response to automatically determining that the document is encrypted, automatically decrypting the document. | 0.695247 |
21. The system of claim 19 , wherein the update handler code generates an overlay display object which is part of the web page, and displays the supplemental content in the overlay display object, such that the overlay display object and supplemental content are displayed without opening a new browser window. | 21. The system of claim 19 , wherein the update handler code generates an overlay display object which is part of the web page, and displays the supplemental content in the overlay display object, such that the overlay display object and supplemental content are displayed without opening a new browser window. 22. The system of claim 21 , wherein the supplemental content includes functionality for the user to select the product for purchase or rental. | 0.87847 |
1. A non-transitory computer-readable medium for remotely executing operations of an application that is provided through a computing device, the non-transitory computer-readable medium carrying instructions, that when executed by one or more processors, cause performance of operations comprising: (a) accessing a schema that logically represents a nodal hierarchy relating to execution of an application on a processing device, the nodal hierarchy including multiple nodes, including one or more category nodes and one or more content nodes; (b) providing, with the schema, an executable script that is associated with at least one node of the hierarchy; (c) processing, using the schema, a user input from the computing device, the user input being selective of one or more nodes of the hierarchy, and providing user interface content to the computing device, the user interface content corresponding to one of (i) one or more nodes, or (ii) a script content, generated as an output of an executed script that is associated with a selected node; and (d) executing, using the schema, the application on the processing device. | 1. A non-transitory computer-readable medium for remotely executing operations of an application that is provided through a computing device, the non-transitory computer-readable medium carrying instructions, that when executed by one or more processors, cause performance of operations comprising: (a) accessing a schema that logically represents a nodal hierarchy relating to execution of an application on a processing device, the nodal hierarchy including multiple nodes, including one or more category nodes and one or more content nodes; (b) providing, with the schema, an executable script that is associated with at least one node of the hierarchy; (c) processing, using the schema, a user input from the computing device, the user input being selective of one or more nodes of the hierarchy, and providing user interface content to the computing device, the user interface content corresponding to one of (i) one or more nodes, or (ii) a script content, generated as an output of an executed script that is associated with a selected node; and (d) executing, using the schema, the application on the processing device. 5. The non-transitory computer-readable medium of claim 1 , wherein the schema is generated from input by an application developer. | 0.565485 |
14. A method of selecting BIOS components for inclusion within a BIOS project, comprising: retrieving a script file corresponding to a project type; searching the script file for a component category and component category selection criteria, wherein the component category selection criteria comprises a requirement indicator as to whether a BIOS component from the BIOS component category is required to be included in the BIOS project and a unicity indicator as to whether more than one BIOS component from the BIOS component category may be included in the BIOS project; retrieving identifiers from a component storage medium of all BIOS components characterized by a component category matching the component category from the script file; requesting user selection of any component identifiers corresponding to BIOS components to be included within the BIOS project; receiving the user selection component identifiers according to the component category selection criteria; and identifying the BIOS components corresponding to the user selection as BIOS project components. | 14. A method of selecting BIOS components for inclusion within a BIOS project, comprising: retrieving a script file corresponding to a project type; searching the script file for a component category and component category selection criteria, wherein the component category selection criteria comprises a requirement indicator as to whether a BIOS component from the BIOS component category is required to be included in the BIOS project and a unicity indicator as to whether more than one BIOS component from the BIOS component category may be included in the BIOS project; retrieving identifiers from a component storage medium of all BIOS components characterized by a component category matching the component category from the script file; requesting user selection of any component identifiers corresponding to BIOS components to be included within the BIOS project; receiving the user selection component identifiers according to the component category selection criteria; and identifying the BIOS components corresponding to the user selection as BIOS project components. 16. The method of claim 14 , wherein the script file comprises a plurality of component category entries, wherein each component category entry is characterized by a component category, a component category description, a directory location within the BIOS project for storing BIOS components within the component category, and the component category selection criteria. | 0.721994 |
1. A method comprising: a) creating a set of text descriptions, wherein the set of text descriptions comprises, for each category in a category set, a corresponding text description for the category; b) accepting the set of text descriptions; c) identifying each word from a lexical data source which is related to a word in the set of text descriptions by less than a threshold number of semantic relations; d) creating a build time set of word pairs, each word pair from the build time set of word pairs comprising a word from the identified words from the lexical data source and a word from the set of text descriptions; e) using, without human intervention, a processor to assign lexical chaining confidence scores to each word pair from the build time set of word pairs; f) accepting a text statement from an input source; g) creating a run time set of word pairs, each word pair from the run time set of word pairs comprising a word from the accepted text statement, and a word from the set of text descriptions; and h) determining at least one category corresponding to the accepted text statement based, at least in part, on said assigned lexical chaining confidence scores for word pairs from the build time set of word pairs corresponding to word pairs from the run time set of word pairs. | 1. A method comprising: a) creating a set of text descriptions, wherein the set of text descriptions comprises, for each category in a category set, a corresponding text description for the category; b) accepting the set of text descriptions; c) identifying each word from a lexical data source which is related to a word in the set of text descriptions by less than a threshold number of semantic relations; d) creating a build time set of word pairs, each word pair from the build time set of word pairs comprising a word from the identified words from the lexical data source and a word from the set of text descriptions; e) using, without human intervention, a processor to assign lexical chaining confidence scores to each word pair from the build time set of word pairs; f) accepting a text statement from an input source; g) creating a run time set of word pairs, each word pair from the run time set of word pairs comprising a word from the accepted text statement, and a word from the set of text descriptions; and h) determining at least one category corresponding to the accepted text statement based, at least in part, on said assigned lexical chaining confidence scores for word pairs from the build time set of word pairs corresponding to word pairs from the run time set of word pairs. 6. The method of claim 1 wherein said text statement is derived from an audio response using automatically generated statistical language models (SLMs). | 0.82776 |
3. The method of claim 2 , the method further comprising: initializing an input FST based on the first token and the semantic structure; and composing the input FST based on the first FST path and the second FST path, wherein the first FST path and the second FST path are integrated with the input FST, and wherein the first FST is selected from the input FST. | 3. The method of claim 2 , the method further comprising: initializing an input FST based on the first token and the semantic structure; and composing the input FST based on the first FST path and the second FST path, wherein the first FST path and the second FST path are integrated with the input FST, and wherein the first FST is selected from the input FST. 5. The method of claim 3 , wherein comparing the plurality of domain tokens with the first input token comprises: performing fuzzy or exact matching between the plurality of domain tokens from the information domain and the first token, wherein the plurality of domain tokens comprises fuzzy or exact matches to the first token. | 0.913826 |
9. The system of claim 5 , wherein the computation component determines a fifth conditional probability, P(T|R), of the domain topic given the result. | 9. The system of claim 5 , wherein the computation component determines a fifth conditional probability, P(T|R), of the domain topic given the result. 12. The system of claim 9 , wherein the computation component determines the P(T|R) based upon a topicality score for the domain topic received by the computation component. | 0.882101 |
12. A tangible computer-readable medium storing computer-executable instructions for causing a computer to perform a method, the method comprising: receiving at least one first parallel processing request at a parallel programming interface, the at least one first parallel processing request comprising at least one evaluation request of one or more parallel operations on one or more input arrays; building an expression graph in response to receiving the at least one first parallel processing request at the parallel programming interface, the expression graph comprising nodes representing the one or more parallel operations; and evaluating the one or more parallel operations in response to determining that a second parallel processing request received at the parallel programming interface subsequent to receiving the at least one first parallel processing request at the parallel programming interface requires evaluation of at least one of the one or more parallel operations, the determining occurring in response to receiving the second parallel processing request at the parallel programming interface, the evaluation comprising: constructing one or more shader programs formed according to resource constraints of a graphics environment; the constructing comprising at least one of: responsive to determining that a path of nodes of parallel operations through the expression graph comprises multiple texture coordinate operations, inserting a first shader break annotation in the determined path; responsive to determining that appending shader code of a first child node to a parent node of the first child node will exceed a resource constraint of the graphics environment, inserting a second shader break annotation in the expression graph; and breaking a second child node into a separate shader program, responsive to identifying an output texture from the second child node with a size constraint inconsistent with an input texture of a parent node of the second child node; invoking the one or more shader programs on a graphics processor; and returning an output of the one or more shader programs invoked on the graphics processor; and wherein the at least one first parallel processing request and the second parallel processing request are received from an application program executing on a computer system. | 12. A tangible computer-readable medium storing computer-executable instructions for causing a computer to perform a method, the method comprising: receiving at least one first parallel processing request at a parallel programming interface, the at least one first parallel processing request comprising at least one evaluation request of one or more parallel operations on one or more input arrays; building an expression graph in response to receiving the at least one first parallel processing request at the parallel programming interface, the expression graph comprising nodes representing the one or more parallel operations; and evaluating the one or more parallel operations in response to determining that a second parallel processing request received at the parallel programming interface subsequent to receiving the at least one first parallel processing request at the parallel programming interface requires evaluation of at least one of the one or more parallel operations, the determining occurring in response to receiving the second parallel processing request at the parallel programming interface, the evaluation comprising: constructing one or more shader programs formed according to resource constraints of a graphics environment; the constructing comprising at least one of: responsive to determining that a path of nodes of parallel operations through the expression graph comprises multiple texture coordinate operations, inserting a first shader break annotation in the determined path; responsive to determining that appending shader code of a first child node to a parent node of the first child node will exceed a resource constraint of the graphics environment, inserting a second shader break annotation in the expression graph; and breaking a second child node into a separate shader program, responsive to identifying an output texture from the second child node with a size constraint inconsistent with an input texture of a parent node of the second child node; invoking the one or more shader programs on a graphics processor; and returning an output of the one or more shader programs invoked on the graphics processor; and wherein the at least one first parallel processing request and the second parallel processing request are received from an application program executing on a computer system. 14. The tangible computer-readable medium of claim 12 , wherein the resource constraints of the graphics environment comprise a constraint on the number of instructions in a shader program. | 0.512158 |
5. The system according to claim 1 , wherein the document destruction apparatus further includes a destruction operator authentication section that identifies a destruction operator who is to destruct the document. | 5. The system according to claim 1 , wherein the document destruction apparatus further includes a destruction operator authentication section that identifies a destruction operator who is to destruct the document. 6. The system according to claim 5 , wherein the document destruction apparatus further includes: a document administration information storage section that stores the administration information containing a destruction authority for the document, a first identification section that identifies a destruction authority of the destruction operator authenticated by the destruction operator authentication section, a second identification section that identifies the destruction authority for the document based on the document identification information and the administration information, a third determination section that determines as to whether or not the destruction operator has the destruction authority for the document, based on the destruction authority of the destruction operator identified by the first identification section and the destruction authority for the document determined by the second identification section, a document destruction member, and a controller that controls the document destruction member to destruct the document if the destruction operator has the destruction authority for the document. | 0.660625 |
29. A computer program product comprising a computer readable storage medium having executable code, when executed by a computer, causes the computer to execute a process for processing of a design that is based upon multiple programming languages, the design comprising a first language portion and a second language portion, the method comprising: performing a first process on the second language portion of the design to cause an interruption of processing for the first language portion of the design, wherein the processing for the first language portion is interrupted to process the second language portion, and the first language portion receives a plurality of requests for the processing, for the first language portion from a programming interface when the first language portion is not interrupted; determining whether there are one or more of the plurality of requests, which are identified by and sent to a processing module to perform the first process on the second language portion by the programming interface, waiting for the processing of the first language portion and indicating a need for the processing module to call a request processing module at the first language portion; handling the one or more of the plurality of requests, which are identified by and sent to the processing module by the programming interface, for the processing of the first language portion by having the processing module call a request processing function at the first language portion that has been interrupted, at least one of the one or more of the plurality of requests for the processing of the first language portion; executing the request processing function at the first language portion to process the one or more of the plurality of requests, wherein the act of executing the request processing function is performed by a processor; providing continued access to the first language portion while performing the first process on the second portion, by using the processing module; and generating processing results based upon executing the request processing function and storing the processing results in a computer-readable storage medium or a storage device or displaying the processing results on a display apparatus. | 29. A computer program product comprising a computer readable storage medium having executable code, when executed by a computer, causes the computer to execute a process for processing of a design that is based upon multiple programming languages, the design comprising a first language portion and a second language portion, the method comprising: performing a first process on the second language portion of the design to cause an interruption of processing for the first language portion of the design, wherein the processing for the first language portion is interrupted to process the second language portion, and the first language portion receives a plurality of requests for the processing, for the first language portion from a programming interface when the first language portion is not interrupted; determining whether there are one or more of the plurality of requests, which are identified by and sent to a processing module to perform the first process on the second language portion by the programming interface, waiting for the processing of the first language portion and indicating a need for the processing module to call a request processing module at the first language portion; handling the one or more of the plurality of requests, which are identified by and sent to the processing module by the programming interface, for the processing of the first language portion by having the processing module call a request processing function at the first language portion that has been interrupted, at least one of the one or more of the plurality of requests for the processing of the first language portion; executing the request processing function at the first language portion to process the one or more of the plurality of requests, wherein the act of executing the request processing function is performed by a processor; providing continued access to the first language portion while performing the first process on the second portion, by using the processing module; and generating processing results based upon executing the request processing function and storing the processing results in a computer-readable storage medium or a storage device or displaying the processing results on a display apparatus. 35. The computer program product of claim 29 , wherein the request processing function is called by a gdb debugger. | 0.50373 |
34. The system of claim 27 , wherein the dialog engine is further for: engaging in a dialog with the user including: receiving input from the user, producing a voice markup language script in response to the input, and executing the voice markup language script to generate an output for provision to the user. | 34. The system of claim 27 , wherein the dialog engine is further for: engaging in a dialog with the user including: receiving input from the user, producing a voice markup language script in response to the input, and executing the voice markup language script to generate an output for provision to the user. 38. The method of claim 34 , wherein the dialog engine is further for: transmitting an append prompt request to the media service provider module to add a second prompt to the output queue. | 0.838035 |
9. The computer program product of claim 7 further including defining a coding style template for each of a plurality of program element types defined in a syntax of a target programming language corresponding to the program, and mapping each of the program elements to a corresponding abstract coding style. | 9. The computer program product of claim 7 further including defining a coding style template for each of a plurality of program element types defined in a syntax of a target programming language corresponding to the program, and mapping each of the program elements to a corresponding abstract coding style. 10. The computer program product of claim 9 wherein each coding style template is defined with a target syntax element type, one or more coding style placeholders, and a coding style-abstraction function. | 0.887036 |
2. The computer-implemented method of claim 1 wherein said determining said word based on said plurality of strokes comprises: inputting said plurality of strokes into a statistical classifier trained to identify said word; and indexing an output of said statistical classifier to a dictionary determining said word. | 2. The computer-implemented method of claim 1 wherein said determining said word based on said plurality of strokes comprises: inputting said plurality of strokes into a statistical classifier trained to identify said word; and indexing an output of said statistical classifier to a dictionary determining said word. 6. The computer-implemented method of claim 2 wherein said dictionary comprises a predetermined limited set of words. | 0.913781 |
3. A computer-implemented method for assessing compliance with the HIPAA, in a context management system, the method comprising: (A) collecting context data from a plurality of applications that use the context management system; (B) storing data corresponding to the collected context data on a centralized storage location; and (C) extracting audit information by processing at least a subset of the data stored on the centralized storage location, the audit information suitable for making an assessment of compliance with a provision of the HIPAA; wherein any of the plurality of applications supports the CCOW standard set. | 3. A computer-implemented method for assessing compliance with the HIPAA, in a context management system, the method comprising: (A) collecting context data from a plurality of applications that use the context management system; (B) storing data corresponding to the collected context data on a centralized storage location; and (C) extracting audit information by processing at least a subset of the data stored on the centralized storage location, the audit information suitable for making an assessment of compliance with a provision of the HIPAA; wherein any of the plurality of applications supports the CCOW standard set. 9. The method of claim 3 , wherein at least a first application executes on a first machine at the point-of-use and at least a second application executes on a second machine. | 0.673664 |
13. The method of claim 10 , wherein the object is an audio file. | 13. The method of claim 10 , wherein the object is an audio file. 14. The method of claim 13 , wherein the audio file is selected from the group consisting of a *.wav file and a u-law file. | 0.939036 |
1. A computer-implemented method comprising: selecting a predetermined voice command which, when spoken by a user during a conversation with another person, informs a wearable computer device that an event is occurring, and that prompts the wearable computer device to store an audio clip surrounding the event in a memory for later retrieval; using audio signals received through an environmental microphone of an audio-only user interface of the wearable computer device to generate digital audio data; buffering the digital audio data in a scrolling audio buffer of the wearable computer device for a predetermined period of time; using audio signals received through a personal microphone of the audio-only user interface of the wearable computer device to determine that the user has spoken the predetermined voice command; and responsive to determining that the user has spoken the predetermined voice command, storing the audio clip in the memory for later retrieval, the audio clip including at least a portion of the digital audio data buffered in the scrolling audio buffer before the predetermined voice command was spoken, and at least a portion of the digital audio data buffered in the scrolling audio buffer after the predetermined voice command was spoken. | 1. A computer-implemented method comprising: selecting a predetermined voice command which, when spoken by a user during a conversation with another person, informs a wearable computer device that an event is occurring, and that prompts the wearable computer device to store an audio clip surrounding the event in a memory for later retrieval; using audio signals received through an environmental microphone of an audio-only user interface of the wearable computer device to generate digital audio data; buffering the digital audio data in a scrolling audio buffer of the wearable computer device for a predetermined period of time; using audio signals received through a personal microphone of the audio-only user interface of the wearable computer device to determine that the user has spoken the predetermined voice command; and responsive to determining that the user has spoken the predetermined voice command, storing the audio clip in the memory for later retrieval, the audio clip including at least a portion of the digital audio data buffered in the scrolling audio buffer before the predetermined voice command was spoken, and at least a portion of the digital audio data buffered in the scrolling audio buffer after the predetermined voice command was spoken. 3. The method of claim 1 , wherein the event comprises an introduction event or a greeting event, in which the user is being introduced to or is greeting the other person, respectively. | 0.607683 |
13. A voice-enabled computing system comprising: a disambiguation engine configured to differentiate between different types of abstractions based upon voice commands, wherein the disambiguation engine supports a plurality of different abstraction types, wherein each of the plurality of different abstraction types is associated with an indication of whether any particular sequencing and/or timing is to be imposed. | 13. A voice-enabled computing system comprising: a disambiguation engine configured to differentiate between different types of abstractions based upon voice commands, wherein the disambiguation engine supports a plurality of different abstraction types, wherein each of the plurality of different abstraction types is associated with an indication of whether any particular sequencing and/or timing is to be imposed. 15. The system of claim 13 , wherein the at least one processor, executes the processor-executable instructions in the at least one computer-readable memory to perform (A), (B), and (C), in response to a request from a remotely located system. | 0.78062 |
26. A method implemented by a provider in a broadcasting system for updating metadata related to multimedia program content scheduled for broadcast in the broadcasting system, the method comprising: receiving by the provider a request from a client device in the broadcasting system for an updated version of a lower fragment in the metadata related to the scheduled multimedia program content, the client device storing an earlier version of the metadata, wherein the metadata has a hierarchical structure based on a prescribed syntax and the hierarchical structure includes an upper fragment above the lower fragment, and wherein the earlier version is identified by a version identifier; and in response to the request, sending from the provider to the client device an update document having a structure based on the prescribed syntax, the update document including the upper fragment and an invalid element, wherein the invalid element specifies that information in the lower fragment of the earlier version of the metadata is invalid. | 26. A method implemented by a provider in a broadcasting system for updating metadata related to multimedia program content scheduled for broadcast in the broadcasting system, the method comprising: receiving by the provider a request from a client device in the broadcasting system for an updated version of a lower fragment in the metadata related to the scheduled multimedia program content, the client device storing an earlier version of the metadata, wherein the metadata has a hierarchical structure based on a prescribed syntax and the hierarchical structure includes an upper fragment above the lower fragment, and wherein the earlier version is identified by a version identifier; and in response to the request, sending from the provider to the client device an update document having a structure based on the prescribed syntax, the update document including the upper fragment and an invalid element, wherein the invalid element specifies that information in the lower fragment of the earlier version of the metadata is invalid. 28. The method of claim 26 , wherein the version identifier is a numerical representation of a calendar date on which the earlier version was created. | 0.595594 |
14. The method of claim 1 : the instructions further configured to, upon receiving a document, index the document in a document index according to, for respective nodes, the node path; and identifying the at least one matching document comprising: for respective query node identifiers, examine the document index to identify the matching documents having at least one matching node comprising, for respective query node identifiers, at least one query node in the node path of the matching node that matches the query node identifier. | 14. The method of claim 1 : the instructions further configured to, upon receiving a document, index the document in a document index according to, for respective nodes, the node path; and identifying the at least one matching document comprising: for respective query node identifiers, examine the document index to identify the matching documents having at least one matching node comprising, for respective query node identifiers, at least one query node in the node path of the matching node that matches the query node identifier. 16. The method of claim 14 , the document index comprising a reverse index indicating, for respective query node paths, the at least one matching documents having at least one matching node comprising, for respective query node identifiers, at least one query node in the node path of the matching node that matches the query node identifier. | 0.778814 |
1. Server apparatus, comprising: a processor; a communications interface in data communication with the processor; and a storage device in data communication with the processor, the storage device comprising a storage medium, the storage medium comprising at least one computer program with a plurality of instructions, said at least one program being configured to: receive a first remotely generated input via said communications interface, said first input relating to a first location; receive a second remotely generated input via said communications interface, said second input relating to a second location, the first and second locations being part of a common journey; identify a first entity associated with the first location; identify a second entity associated with the second location; cause first advertising content related to the first entity to be forwarded via said communication interface to a remotely disposed computerized device which generated said first and second remotely generated inputs; and cause second advertising content related to the second entity to be forwarded via said communication interface to said remotely disposed computerized device. | 1. Server apparatus, comprising: a processor; a communications interface in data communication with the processor; and a storage device in data communication with the processor, the storage device comprising a storage medium, the storage medium comprising at least one computer program with a plurality of instructions, said at least one program being configured to: receive a first remotely generated input via said communications interface, said first input relating to a first location; receive a second remotely generated input via said communications interface, said second input relating to a second location, the first and second locations being part of a common journey; identify a first entity associated with the first location; identify a second entity associated with the second location; cause first advertising content related to the first entity to be forwarded via said communication interface to a remotely disposed computerized device which generated said first and second remotely generated inputs; and cause second advertising content related to the second entity to be forwarded via said communication interface to said remotely disposed computerized device. 2. The server apparatus of claim 1 , wherein the first advertising content and the second advertising content are configured to be presented substantially in an order corresponding to the order in which the first location and second location are to be encountered during said journey. | 0.667585 |
14. The computing system of claim 13 , wherein the memory includes further instructions when executed by the processor cause the processor to determine the current page within the website hierarchy from which the search request is received. | 14. The computing system of claim 13 , wherein the memory includes further instructions when executed by the processor cause the processor to determine the current page within the website hierarchy from which the search request is received. 15. The computing system of claim 14 , wherein the memory includes further instructions when executed by the processor cause the processor to acquire one or more children pages of the current page, including the child page, wherein identifying the location of the first search template page includes identifying a location of the plurality of search template pages within the one or more children pages. | 0.873411 |
1. A computer-implemented method, comprising: in response to receiving a new document, generating an assigned-doc-ID for the new document; identifying, for the assigned-doc-ID, a virtual-index-epoch from a virtual-index-epoch map that includes virtual-index-epochs that are each assigned a range of assign-doc-IDs; applying a first function to a virtual-index-epoch value of the identified virtual-index-epoch to identify a logical partition; applying a second function to the identified logical partition to identify a physical partition; and placing the new document into the identified physical partition associated with the identified virtual-index-epoch. | 1. A computer-implemented method, comprising: in response to receiving a new document, generating an assigned-doc-ID for the new document; identifying, for the assigned-doc-ID, a virtual-index-epoch from a virtual-index-epoch map that includes virtual-index-epochs that are each assigned a range of assign-doc-IDs; applying a first function to a virtual-index-epoch value of the identified virtual-index-epoch to identify a logical partition; applying a second function to the identified logical partition to identify a physical partition; and placing the new document into the identified physical partition associated with the identified virtual-index-epoch. 8. The method of claim 1 , wherein the first function and the second function are one of system determined and user specified, and wherein the system determined functions are based on one of system capacity, modeled performance of a physical partition, and actual performance of the physical partition. | 0.603617 |
10. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to implement a context aware abbreviation detection and annotation (CAADA) system that operates to: identify, in received content, an instance of a full name of an entity; perform analysis of a context window associated with the instance of the full name of the entity to identify a presence of a pattern of content representative of an abbreviation; identify an abbreviation being present in association with the instance of the full name of the entity based on results of the analysis of the context window; generate a mapping data structure that maps the full name of the entity to the abbreviation; analyze the received content to identify other instances of the abbreviation that match the abbreviation and the pattern of content representative of the abbreviation; generate a global abbreviation list data structure comprising each instance of the abbreviation within the received content; compare the abbreviation in the mapping data structure to the abbreviation in the global abbreviation list data structure to identify matches between entries in the mapping data structure to entries in the global abbreviations list data structure; responsive to matching an abbreviation in the global abbreviation list-data structure to an abbreviation in the mapping data structure, generate annotations in an annotation data structure for each instance of the abbreviation in received content along with the full name of the entity associated with the abbreviation; annotate the received content based on the annotation data structure to thereby generate abbreviation annotations for each instance of the abbreviation in the received content; and output the annotated received content along with the annotation data structure for use by a cognitive system to perform a cognitive operation based on the annotated received content and the annotation data structure. | 10. A computer program product comprising a non-transitory computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to implement a context aware abbreviation detection and annotation (CAADA) system that operates to: identify, in received content, an instance of a full name of an entity; perform analysis of a context window associated with the instance of the full name of the entity to identify a presence of a pattern of content representative of an abbreviation; identify an abbreviation being present in association with the instance of the full name of the entity based on results of the analysis of the context window; generate a mapping data structure that maps the full name of the entity to the abbreviation; analyze the received content to identify other instances of the abbreviation that match the abbreviation and the pattern of content representative of the abbreviation; generate a global abbreviation list data structure comprising each instance of the abbreviation within the received content; compare the abbreviation in the mapping data structure to the abbreviation in the global abbreviation list data structure to identify matches between entries in the mapping data structure to entries in the global abbreviations list data structure; responsive to matching an abbreviation in the global abbreviation list-data structure to an abbreviation in the mapping data structure, generate annotations in an annotation data structure for each instance of the abbreviation in received content along with the full name of the entity associated with the abbreviation; annotate the received content based on the annotation data structure to thereby generate abbreviation annotations for each instance of the abbreviation in the received content; and output the annotated received content along with the annotation data structure for use by a cognitive system to perform a cognitive operation based on the annotated received content and the annotation data structure. 17. The computer program product of claim 10 , wherein the CAADA system performs the operation as part of an ingestion operation for ingesting a corpus of information upon which a natural language processing operation is performed by a natural language processing system, wherein the received content is a portion of the corpus of information. | 0.57883 |
4. The computer program product of claim 3 , wherein the method further comprises: scheduling transmission of another portion of the set of fill-in messages based on the conversational cadence of the user; transmitting the other portion of the set of fill-in messages in the social network according to a schedule based on the conversational cadence of the user to create the appearance of no reduction in the conversational cadence; and discontinuing transmission of the other portion of the set of fill-in messages in response to one of detecting return of the user to the social network or detecting another action. | 4. The computer program product of claim 3 , wherein the method further comprises: scheduling transmission of another portion of the set of fill-in messages based on the conversational cadence of the user; transmitting the other portion of the set of fill-in messages in the social network according to a schedule based on the conversational cadence of the user to create the appearance of no reduction in the conversational cadence; and discontinuing transmission of the other portion of the set of fill-in messages in response to one of detecting return of the user to the social network or detecting another action. 5. The computer program product of claim 4 , wherein detecting return of the user to the social network comprises detecting an increase in the conversational cadence of the user by the user personally transmitting a series of new message in the social network, and wherein detecting another action comprises receiving a command from the user to cancel transmission of the set of fill-in messages in the social network. | 0.830411 |
1. A document processing system comprising: one or more document guide components defining a path of travel of documents, the path of travel of documents including an intersection portion that separates a first portion from a second portion; and a component reposition element at the intersection portion of the path of travel of one or more documents, the component reposition element arranged to align a document processing component with a first portion of the path of travel when a first side of one of the documents is closer to the document processing component than a second side of one of the documents and a second portion of the path of travel when the second side of one of the documents is closer to the document processing component than the first side of one of the documents; wherein the component repositioning element is configured to move the image scanner between first and second positions, wherein in the first position the image scanner is oriented to scan a first side of the document and in the second position the image scanner is oriented to scan a second side of the document; and wherein the path of travel includes a turn-around loop. | 1. A document processing system comprising: one or more document guide components defining a path of travel of documents, the path of travel of documents including an intersection portion that separates a first portion from a second portion; and a component reposition element at the intersection portion of the path of travel of one or more documents, the component reposition element arranged to align a document processing component with a first portion of the path of travel when a first side of one of the documents is closer to the document processing component than a second side of one of the documents and a second portion of the path of travel when the second side of one of the documents is closer to the document processing component than the first side of one of the documents; wherein the component repositioning element is configured to move the image scanner between first and second positions, wherein in the first position the image scanner is oriented to scan a first side of the document and in the second position the image scanner is oriented to scan a second side of the document; and wherein the path of travel includes a turn-around loop. 5. The document processing system of claim 1 , further comprising one or more document recovery bins. | 0.579604 |
2. The method for packet classification in claim 1 , wherein the step of filtering includes: generating one or more hashing indices for each of the particular tuples; and accessing Bloom filter entries indicated by the one or more hashing indices to identify bit values of the Bloom filter entries. | 2. The method for packet classification in claim 1 , wherein the step of filtering includes: generating one or more hashing indices for each of the particular tuples; and accessing Bloom filter entries indicated by the one or more hashing indices to identify bit values of the Bloom filter entries. 4. The method for packet classification in claim 2 , wherein the one or more hashing indices are generated from a string generated through extracting from each of the fields higher order bits corresponding to the matching length represented by the particular tuple followed by a concatenation of the extracted bits. | 0.885091 |
1. A method of retrieving media, comprising: (a) defining a probabilistic framework organizing media with respect to concepts represented in the respective media comprising at least one hidden layer; (b) automatically mapping elements of a set of media to the probabilistic framework, using at least one processor, based on implicit concepts represented within each element of the set of media, the probabilistic framework comprising at least one joint probability distribution which models a probability that a symbol belonging to a respective concept is an annotation symbol of respective media; (c) automatically determining, using at least one processor, at least one implicit concept represented in a received query; (d) automatically determining, using at least one processor, a probabilistic correspondence of elements of the set of media with the determined at least one implicit concept; and (e) outputting at least one representation or identifier of at least one element of the set of media selectively in dependence on at least the determined probabilistic correspondence. | 1. A method of retrieving media, comprising: (a) defining a probabilistic framework organizing media with respect to concepts represented in the respective media comprising at least one hidden layer; (b) automatically mapping elements of a set of media to the probabilistic framework, using at least one processor, based on implicit concepts represented within each element of the set of media, the probabilistic framework comprising at least one joint probability distribution which models a probability that a symbol belonging to a respective concept is an annotation symbol of respective media; (c) automatically determining, using at least one processor, at least one implicit concept represented in a received query; (d) automatically determining, using at least one processor, a probabilistic correspondence of elements of the set of media with the determined at least one implicit concept; and (e) outputting at least one representation or identifier of at least one element of the set of media selectively in dependence on at least the determined probabilistic correspondence. 6. The method according to claim 1 , wherein the query comprises an image, and said automatically determining comprises associating words with the image using a Bayesian model comprising a hidden concept layer which connects a visual feature layer and a word layer, which is discovered by fitting a generative model to a training set comprising images and annotation words, wherein the conditional probabilities of the visual features and the annotation words given a hidden concept class are determined based on an Expectation-Maximization (EM) based iterative learning procedure. | 0.835891 |
15. The system of claim 14 , wherein each of the semantic grouping of the concepts is identified by a semantic type. | 15. The system of claim 14 , wherein each of the semantic grouping of the concepts is identified by a semantic type. 16. The system of claim 15 , wherein the semantic type is a category name. | 0.98025 |
28. The computer system of claim 19 , wherein the instructions further include instructions to: add the identified document to a spam list that includes a list of spam documents. | 28. The computer system of claim 19 , wherein the instructions further include instructions to: add the identified document to a spam list that includes a list of spam documents. 29. The computer program product of claim 28 , wherein the instructions further include instructions to: add the identified document to a spam list that includes a list of spam documents associated with the most significant phrase; and for each related phrase of the most significant phrase, add the identified document to a list of spam documents associated with the related phrase. | 0.926211 |
1. A method executed by one or more processors of a computing system, the method for instantiating a database having a database schema corresponding to a unified modeling language (UML) specification, the method comprising: extracting at least one model element from a unified modeling language (UML) specification, the unified modeling language (UML) specification being defined by a first model comprising a plurality of model elements, the plurality of model elements of the first model being usable to describe software system structure, software system behavior, and software system architecture for one or more particular software systems; generating a first set of one or more declarative language coding patterns based on first predetermined criteria and the at least one model element, the declarative language coding patterns defining a database having a database schema representing the first model and the at least one model element; translating the generated first set of one or more declarative language coding patterns into a first set of one or more Structured Query Language (SQL) statements that when executed, can instantiate at least a portion of a database having the database schema representing the first model and the at least one model element; and instantiating within a data storage system, by executing the first set of one or more SQL statements, the at least a portion of the database having the database schema representing the first model and the at least one model element of the unified modeling language (UML) specification. | 1. A method executed by one or more processors of a computing system, the method for instantiating a database having a database schema corresponding to a unified modeling language (UML) specification, the method comprising: extracting at least one model element from a unified modeling language (UML) specification, the unified modeling language (UML) specification being defined by a first model comprising a plurality of model elements, the plurality of model elements of the first model being usable to describe software system structure, software system behavior, and software system architecture for one or more particular software systems; generating a first set of one or more declarative language coding patterns based on first predetermined criteria and the at least one model element, the declarative language coding patterns defining a database having a database schema representing the first model and the at least one model element; translating the generated first set of one or more declarative language coding patterns into a first set of one or more Structured Query Language (SQL) statements that when executed, can instantiate at least a portion of a database having the database schema representing the first model and the at least one model element; and instantiating within a data storage system, by executing the first set of one or more SQL statements, the at least a portion of the database having the database schema representing the first model and the at least one model element of the unified modeling language (UML) specification. 2. The method as in claim 1 , wherein the first predetermined criteria comprises a plurality of transform directives. | 0.599178 |
1. A computer-implemented method, comprising: receiving, by a computing system, a first search query that was typed by a first user input at a computing device into a search input box of a mapping application program at the computing device; parsing, by the computing system, the first search query in order to determine that one or more words in the first search query name a particular geographical location; conducting, by the computing system, a search for first search results that: (i) are responsive to the first search query, and (ii) identify respective first businesses that are geographically located around the particular geographical location that is named by the one or more words in the first search query; sending, by the computing system and for receipt by the computing device, information that identifies the first search results, so as to cause the computing device to present a display of a first geographical area of a map with first graphical interface elements that identify the first search results overlaying the map at locations that correspond to locations on the map of the first businesses; receiving, by the computing system, a second search query that was typed by a second user input at the computing device into the search input box of the mapping application program into which the first search query was typed, wherein the second search query does not include one or more words that name any geographical location; parsing, by the computing system, the second search query in order to identify whether the second search query includes one or more words that name any geographical location; receiving, by the computing system, an indication of a geographical location that is indicated by a presently-displayed geographical area of the map that is being presented by the computing device; conducting, by the computing system, a search for second search results that: (i) are responsive to the second search query, and (ii) identify respective second businesses that are geographically located around the geographical location that is indicated by the presently-displayed geographical area of the map that is being presented by the computing device; and sending, by the computing system and for receipt by the computing device, information that identifies the second search results, so as to cause the computing device to present a display of a second geographical area of the map with second graphical interface elements that identify the second search results overlaying the map at locations that correspond to locations on the map of the second businesses. | 1. A computer-implemented method, comprising: receiving, by a computing system, a first search query that was typed by a first user input at a computing device into a search input box of a mapping application program at the computing device; parsing, by the computing system, the first search query in order to determine that one or more words in the first search query name a particular geographical location; conducting, by the computing system, a search for first search results that: (i) are responsive to the first search query, and (ii) identify respective first businesses that are geographically located around the particular geographical location that is named by the one or more words in the first search query; sending, by the computing system and for receipt by the computing device, information that identifies the first search results, so as to cause the computing device to present a display of a first geographical area of a map with first graphical interface elements that identify the first search results overlaying the map at locations that correspond to locations on the map of the first businesses; receiving, by the computing system, a second search query that was typed by a second user input at the computing device into the search input box of the mapping application program into which the first search query was typed, wherein the second search query does not include one or more words that name any geographical location; parsing, by the computing system, the second search query in order to identify whether the second search query includes one or more words that name any geographical location; receiving, by the computing system, an indication of a geographical location that is indicated by a presently-displayed geographical area of the map that is being presented by the computing device; conducting, by the computing system, a search for second search results that: (i) are responsive to the second search query, and (ii) identify respective second businesses that are geographically located around the geographical location that is indicated by the presently-displayed geographical area of the map that is being presented by the computing device; and sending, by the computing system and for receipt by the computing device, information that identifies the second search results, so as to cause the computing device to present a display of a second geographical area of the map with second graphical interface elements that identify the second search results overlaying the map at locations that correspond to locations on the map of the second businesses. 6. The computer-implemented method of claim 1 , wherein the indication of the geographical location that is indicated by the presently-displayed geographical area of the map was appended to the second search query. | 0.830174 |
17. The system of claim 1 , wherein the system is further configured to: evaluate search results from the rerun query and to select search results that meet predefined search result selection criteria; and wherein the search results sent to the computer associated with the particular individual computer user correspond to at least some of the selected search results. | 17. The system of claim 1 , wherein the system is further configured to: evaluate search results from the rerun query and to select search results that meet predefined search result selection criteria; and wherein the search results sent to the computer associated with the particular individual computer user correspond to at least some of the selected search results. 23. The system of claim 17 , wherein at least one of the predefined search result selection criteria used to evaluate a search result from the rerun query is based on the search result being the only new search result in the top N search results returned for the rerun query, where N is an integer. | 0.858663 |
8. The apparatus according to claim 7 , wherein there are a plurality of levels of accentuation corresponding to different rating levels, each level having a different, corresponding display format. | 8. The apparatus according to claim 7 , wherein there are a plurality of levels of accentuation corresponding to different rating levels, each level having a different, corresponding display format. 10. The apparatus according to claim 8 , further including: a means for concurrently changing an accentuation of a displayed accentuated symbol and a rating of the corresponding keyword. | 0.908869 |
1. A method of creating a requirement description for testing an embedded system, comprising: storing a vocabulary of natural-language, selectable text segments in a data processing system, each of said text segments being combinable only with a deterministically selected subset of said text segments to form at least one natural-language sentence including a condition and a response to a condition, and storing a requirements metamodel in the data processing system, each text segment being linked to an instance in the requirements metamodel such that when a text segment is selected a machine readable description of the text segment is created and such that said condition is assigned a value placeable at an input of the embedded system and the response to the condition is assigned a value placeable at an output of the embedded system. | 1. A method of creating a requirement description for testing an embedded system, comprising: storing a vocabulary of natural-language, selectable text segments in a data processing system, each of said text segments being combinable only with a deterministically selected subset of said text segments to form at least one natural-language sentence including a condition and a response to a condition, and storing a requirements metamodel in the data processing system, each text segment being linked to an instance in the requirements metamodel such that when a text segment is selected a machine readable description of the text segment is created and such that said condition is assigned a value placeable at an input of the embedded system and the response to the condition is assigned a value placeable at an output of the embedded system. 2. The method according to claim 1 , further comprising assigning the text segments to classes of a stored requirement metamodel. | 0.697566 |
5. The one or more computer readable media of claim 1 , wherein the cross-lingual query generative probability between the search query (q c ) and a document (d e ) based on query translation is expressed in terms comprising: ∑ i , j μ ij f i ( q e , d e ) g j ( q c , q e ) , where q e is a translation of the search query q c in the second language, ƒ i (q e ,d e ) is a monolingual relevancy feature function used for estimating relevancy between q e as a search query in the second language and the document d e , g j (q c ,q e ) is a feature function associated with query translation between the search query q c and the translation search query q e , and μ ij is corresponding weight parameter, and i is a first index that represents at least one ƒ i (q e ,d e ), and j is a second index that represents at least one g j (q c ,q e ). | 5. The one or more computer readable media of claim 1 , wherein the cross-lingual query generative probability between the search query (q c ) and a document (d e ) based on query translation is expressed in terms comprising: ∑ i , j μ ij f i ( q e , d e ) g j ( q c , q e ) , where q e is a translation of the search query q c in the second language, ƒ i (q e ,d e ) is a monolingual relevancy feature function used for estimating relevancy between q e as a search query in the second language and the document d e , g j (q c ,q e ) is a feature function associated with query translation between the search query q c and the translation search query q e , and μ ij is corresponding weight parameter, and i is a first index that represents at least one ƒ i (q e ,d e ), and j is a second index that represents at least one g j (q c ,q e ). 6. The one or more computer readable media of claim 5 , wherein the weight parameter μ ij is determined using a learning model having a training corpus. | 0.895453 |
11. A non-transitory computer-readable storage medium comprising a plurality of instructions configured to execute on at least one computer processor to enable the computer processor to control a system for assessing sentiment of text, comprising an input device and a display, to perform operations comprising: receive text input via the input device, the text associated with a review relating to a particular topic; and as the text is being inputted, determine, based on respective scores calculated for each of one or more words included in the received text, a real-time orientation value reflecting a sentiment of the received text; and modify an appearance of a visual display element on the display based on the determined real-time orientation value. | 11. A non-transitory computer-readable storage medium comprising a plurality of instructions configured to execute on at least one computer processor to enable the computer processor to control a system for assessing sentiment of text, comprising an input device and a display, to perform operations comprising: receive text input via the input device, the text associated with a review relating to a particular topic; and as the text is being inputted, determine, based on respective scores calculated for each of one or more words included in the received text, a real-time orientation value reflecting a sentiment of the received text; and modify an appearance of a visual display element on the display based on the determined real-time orientation value. 18. The non-transitory computer-readable storage medium according to claim 11 , wherein the real-time orientation value is determined by extracting one or more words from the received text; accessing a training corpus to identify probability scores associated with the words; performing a central tendency calculation for the received text by evaluating the probability scores associated with the words; and assigning the orientation value to the received text based at least on the central tendency calculation. | 0.554717 |
7. A method comprising: receiving a selection of a compressed file object within a page description language document file, the selection received on a computing device performing the method, the compressed file object including a compressed file within a compressed archive included in the page description language document file, the compressed file object further including an object definition identifier within a header of the compressed file; reading, from a memory device, data of the page description language document file following the object definition identifier of the compressed file object until an end-of-object identifier is reached; and opening, through execution of instructions on at least one processor, the compressed file object from the page description language document file. | 7. A method comprising: receiving a selection of a compressed file object within a page description language document file, the selection received on a computing device performing the method, the compressed file object including a compressed file within a compressed archive included in the page description language document file, the compressed file object further including an object definition identifier within a header of the compressed file; reading, from a memory device, data of the page description language document file following the object definition identifier of the compressed file object until an end-of-object identifier is reached; and opening, through execution of instructions on at least one processor, the compressed file object from the page description language document file. 9. The method of claim 7 , wherein opening the compressed file object includes: sending a file open request to an operating system with reference to the compressed file. | 0.594737 |
1. A method for generating an assent indication in a document approval and review function for collaborative document editing, the method comprising: loading into a memory of a computer a document for editing in a document editor; determining, by the processor of the computer, a set of authors for the document; modifying a file name of the document by the processor of the computer, by appending an identity of each author in the determined set author to the file name of the document; and, responsive to one of the authors in the determined set of authors assenting to a publication of the document, changing a visual appearance in the modified file name of an identity of the assenting author by removing the identity of the assenting author from the modified file name of the document resulting in leaving the identity of each author in the determined set of authors that has yet to assent to the publication of the document in the modified file name of the document. | 1. A method for generating an assent indication in a document approval and review function for collaborative document editing, the method comprising: loading into a memory of a computer a document for editing in a document editor; determining, by the processor of the computer, a set of authors for the document; modifying a file name of the document by the processor of the computer, by appending an identity of each author in the determined set author to the file name of the document; and, responsive to one of the authors in the determined set of authors assenting to a publication of the document, changing a visual appearance in the modified file name of an identity of the assenting author by removing the identity of the assenting author from the modified file name of the document resulting in leaving the identity of each author in the determined set of authors that has yet to assent to the publication of the document in the modified file name of the document. 3. The method of claim 1 , wherein changing a visual appearance in the file name of an identity of the assenting author, comprises decorating the identity of the assenting author in the file name with an icon. | 0.80663 |
17. An apparatus for automatically evaluating Bayesian network models for decision support, the apparatus comprising a computer system including a processor, a memory coupled with the processor, an input coupled with the processor for receiving user input and data input, and an output coupled with the processor for outputting display data, wherein the computer system further comprises means, residing in its processor and memory, for: receiving a Bayesian Network (BN) model including evidence nodes and conclusion nodes, where the conclusion nodes are linked with the evidence nodes by causal dependency links, and where the evidence nodes have evidence states and the conclusion nodes have conclusion states; setting the states of the conclusion nodes to desired conclusion states and determining, by propagating down the causal dependency links, a corresponding probability of occurrence of evidence states of the evidence nodes and producing, from the probability of occurrence, a plurality of samples of most likely states of the evidence nodes; setting the states of the evidence nodes to states corresponding to the plurality of samples of the evidence states, and propagating the evidence states back up the causal dependency links to the conclusion nodes, to obtain a plurality of probabilities of the resulting states of the conclusion nodes; and outputting a representation of the plurality of the probabilities of the resulting states of the conclusion nodes. | 17. An apparatus for automatically evaluating Bayesian network models for decision support, the apparatus comprising a computer system including a processor, a memory coupled with the processor, an input coupled with the processor for receiving user input and data input, and an output coupled with the processor for outputting display data, wherein the computer system further comprises means, residing in its processor and memory, for: receiving a Bayesian Network (BN) model including evidence nodes and conclusion nodes, where the conclusion nodes are linked with the evidence nodes by causal dependency links, and where the evidence nodes have evidence states and the conclusion nodes have conclusion states; setting the states of the conclusion nodes to desired conclusion states and determining, by propagating down the causal dependency links, a corresponding probability of occurrence of evidence states of the evidence nodes and producing, from the probability of occurrence, a plurality of samples of most likely states of the evidence nodes; setting the states of the evidence nodes to states corresponding to the plurality of samples of the evidence states, and propagating the evidence states back up the causal dependency links to the conclusion nodes, to obtain a plurality of probabilities of the resulting states of the conclusion nodes; and outputting a representation of the plurality of the probabilities of the resulting states of the conclusion nodes. 27. An apparatus for automatically evaluating Bayesian network models for decision support, as set forth in claim 17 , wherein the outputted representation is a complete representation of probabilities of states for all conclusions given a particular set of combinations of conclusion states. | 0.54793 |
6. A method, comprising: receiving, by at least one server communicatively coupled to a network, a request to identify a plurality of candidate domain names for registration from a requester; identifying, by the at least one server, the plurality of candidate domain names relevant to the request; calculating, by the at least one server, a reputation rating for each one of the plurality of candidate domain names, wherein the reputation rating is calculated based on historical data associated with each one of the plurality of candidate domain names and the historical data is accumulated by at least one of determining a length of time that the each one of the plurality of candidate domain names has been registered; determining an amount of spam, viruses, or phishing email messages that originated from email accounts or websites of the each one of the plurality of candidate domain names; determining a number of complaints about the each one of the plurality of candidate domain names; determining whether website content of the each one of the plurality of candidate domain names relates to illegal content; determining whether the each one of the plurality of candidate domain names has been issued a certified security certificate; and determining whether a registering entity has validated contact information of a registrant of the each one of the plurality of candidate domain names; and displaying, by the at least one server, a user interface depicting the plurality of candidate domain names and an indication of the reputation rating of the each one of the plurality of candidate domain names. | 6. A method, comprising: receiving, by at least one server communicatively coupled to a network, a request to identify a plurality of candidate domain names for registration from a requester; identifying, by the at least one server, the plurality of candidate domain names relevant to the request; calculating, by the at least one server, a reputation rating for each one of the plurality of candidate domain names, wherein the reputation rating is calculated based on historical data associated with each one of the plurality of candidate domain names and the historical data is accumulated by at least one of determining a length of time that the each one of the plurality of candidate domain names has been registered; determining an amount of spam, viruses, or phishing email messages that originated from email accounts or websites of the each one of the plurality of candidate domain names; determining a number of complaints about the each one of the plurality of candidate domain names; determining whether website content of the each one of the plurality of candidate domain names relates to illegal content; determining whether the each one of the plurality of candidate domain names has been issued a certified security certificate; and determining whether a registering entity has validated contact information of a registrant of the each one of the plurality of candidate domain names; and displaying, by the at least one server, a user interface depicting the plurality of candidate domain names and an indication of the reputation rating of the each one of the plurality of candidate domain names. 14. The method of claim 6 , wherein the request for the domain name includes keywords. | 0.549292 |
1. A method for parsing business card information text from electronically derived text representing an electronically scanned business card, comprising: (a) electronically ordering, using an electronic device, lines of text linearly left-to-right, top-to-bottom; (b) generating, for each line of text having a keyword therein, a terminal symbol corresponding to the keyword therein, the terminal symbol being a member of a pre-defined set of terminal symbols; (c) generating, for each line of text not having a keyword therein and absent of numeric characters, an alphabetic terminal symbol; (d) generating, for each line of text not having a keyword therein and having a numeric character therein, an alphanumeric terminal symbol; (e) generating a string of terminal symbols from the generated terminal symbols; (f) electronically determining, using an electronic device, a probable parsing of the generated string of terminal symbols; (g) labeling each text line, according to a determined function, with non-terminal symbols; and (h) electronically parsing, using an electronic device, the business card information text into fields of business card information text based upon the non-terminal symbol of each text line and the determined probable parsing of the generated string of terminal symbols. | 1. A method for parsing business card information text from electronically derived text representing an electronically scanned business card, comprising: (a) electronically ordering, using an electronic device, lines of text linearly left-to-right, top-to-bottom; (b) generating, for each line of text having a keyword therein, a terminal symbol corresponding to the keyword therein, the terminal symbol being a member of a pre-defined set of terminal symbols; (c) generating, for each line of text not having a keyword therein and absent of numeric characters, an alphabetic terminal symbol; (d) generating, for each line of text not having a keyword therein and having a numeric character therein, an alphanumeric terminal symbol; (e) generating a string of terminal symbols from the generated terminal symbols; (f) electronically determining, using an electronic device, a probable parsing of the generated string of terminal symbols; (g) labeling each text line, according to a determined function, with non-terminal symbols; and (h) electronically parsing, using an electronic device, the business card information text into fields of business card information text based upon the non-terminal symbol of each text line and the determined probable parsing of the generated string of terminal symbols. 9. The method as claimed in claim 1 , wherein the probable parsing of the generated string of terminal symbols is determined using a Cocke-Younger-Kasami algorithm and probabilistic context free grammar. | 0.555977 |
11. A computing system for autosuggesting related objects to a user, comprising: one or more processors; and one or more memory devices, the one or more memory devices storing instructions that when executed by the one or more processors cause the one or more processors to perform operations, the operations comprising: receiving data indicative of a user input that comprises an n-gram of one or more characters; identifying one or more autocomplete suggestions for the user input; identifying one or more ontologies based at least in part on at least one of the n-gram of one or more characters and the autocomplete suggestions for the user input, wherein each ontology is associated with a category that is related to at least one of the user input and the autocomplete suggestions for the user input, and wherein each ontology comprises a plurality of object types, each object type comprises one or more terms; determining one or more suggested related objects based at least in part on one or more of the plurality of object types, wherein the one or more suggested related objects comprise one or more of the terms that are related to at least one of the user input and the autocomplete suggestions; and providing data indicative of the suggested related objects for display on a user interface via a display device. | 11. A computing system for autosuggesting related objects to a user, comprising: one or more processors; and one or more memory devices, the one or more memory devices storing instructions that when executed by the one or more processors cause the one or more processors to perform operations, the operations comprising: receiving data indicative of a user input that comprises an n-gram of one or more characters; identifying one or more autocomplete suggestions for the user input; identifying one or more ontologies based at least in part on at least one of the n-gram of one or more characters and the autocomplete suggestions for the user input, wherein each ontology is associated with a category that is related to at least one of the user input and the autocomplete suggestions for the user input, and wherein each ontology comprises a plurality of object types, each object type comprises one or more terms; determining one or more suggested related objects based at least in part on one or more of the plurality of object types, wherein the one or more suggested related objects comprise one or more of the terms that are related to at least one of the user input and the autocomplete suggestions; and providing data indicative of the suggested related objects for display on a user interface via a display device. 15. The computing system of claim 11 , wherein the terms of the suggested related objects are displayed on the user interface with at least one of the user input and the autocomplete suggestions for the user input. | 0.643864 |
16. A non-transitory computer readable storage medium having stored therein instructions, which when executed by one or more processors in a computer system, cause the computer system to: maintain a plurality of conversations, each having an identified set of participants; maintain for each respective participant in one or more of the conversations, a respective participant-specific inverse index of terms in conversations for which the respective participant is an identified participant; respond to receiving a search query from a first participant of a first conversation in the plurality of conversations by: using the participant-specific inverse index corresponding to the first participant to identify a second conversation in the plurality of conversations as relevant to the search query, and format all or a portion of the second conversation for display to the first participant; wherein the plurality of conversations are instant messaging conversations, and participants in each conversation in the plurality of conversations are instant messaging participants. | 16. A non-transitory computer readable storage medium having stored therein instructions, which when executed by one or more processors in a computer system, cause the computer system to: maintain a plurality of conversations, each having an identified set of participants; maintain for each respective participant in one or more of the conversations, a respective participant-specific inverse index of terms in conversations for which the respective participant is an identified participant; respond to receiving a search query from a first participant of a first conversation in the plurality of conversations by: using the participant-specific inverse index corresponding to the first participant to identify a second conversation in the plurality of conversations as relevant to the search query, and format all or a portion of the second conversation for display to the first participant; wherein the plurality of conversations are instant messaging conversations, and participants in each conversation in the plurality of conversations are instant messaging participants. 18. The computer readable storage medium of claim 16 , wherein the set of participants of a respective conversation include one or more subscribers of the computer system and an email participant identified by an email address. | 0.818182 |
1. A system comprising: a third-party corpus database electronically storing various third-party content that are available to be incorporated into an electronic document, wherein the various third-party content are indexed in the third-party corpus database according to one or more parameters; a distributed computing system including a set of multiple computing devices that are interconnected and electronically access the third-party corpus database to evaluate the various third-party content, based at least in part on the one or more parameters, and transmit digital data corresponding to a set of the various third-party content to a user device, wherein: the digital data includes machine readable instructions that configure the user device to incorporate the set of various third-party content into a presentation of a given electronic document at the user device; the distributed computing system selects the set of various third-party content and formatting for the at least some of the various third-party content in the set based on multiple evaluation processes including performing: a first evaluation process that provides the distributed computing system with a separate cost-prominence relationship for each third-party content in the set, wherein performance of the first evaluation process by the distributed combing system includes performance of operations comprising: identifying, for each location among the various locations of the given electronic document, an aggregate performance of multiple different third-party content when presented in that location of the given electronic document; for each third-party content: determining a bid amount required for that third-party content to be presented in each of the various locations of the given electronic document; and fitting a cost-prominence curve to points each representing an intersection of the aggregate performance at one of the various locations of the given document and the bid amount required for that third-party content to be presented in that location of the given document; and a second evaluation process that identifies, independent of the cost-prominence relationship, a winning third-party content for each of one or more locations of the electronic document, including at least a first location; wherein: the digital data include instructions that present the winning third-party content at the user device according to a given format that is automatically selected by the distributed computing system based on the cost-prominence relationship of the first evaluation process. | 1. A system comprising: a third-party corpus database electronically storing various third-party content that are available to be incorporated into an electronic document, wherein the various third-party content are indexed in the third-party corpus database according to one or more parameters; a distributed computing system including a set of multiple computing devices that are interconnected and electronically access the third-party corpus database to evaluate the various third-party content, based at least in part on the one or more parameters, and transmit digital data corresponding to a set of the various third-party content to a user device, wherein: the digital data includes machine readable instructions that configure the user device to incorporate the set of various third-party content into a presentation of a given electronic document at the user device; the distributed computing system selects the set of various third-party content and formatting for the at least some of the various third-party content in the set based on multiple evaluation processes including performing: a first evaluation process that provides the distributed computing system with a separate cost-prominence relationship for each third-party content in the set, wherein performance of the first evaluation process by the distributed combing system includes performance of operations comprising: identifying, for each location among the various locations of the given electronic document, an aggregate performance of multiple different third-party content when presented in that location of the given electronic document; for each third-party content: determining a bid amount required for that third-party content to be presented in each of the various locations of the given electronic document; and fitting a cost-prominence curve to points each representing an intersection of the aggregate performance at one of the various locations of the given document and the bid amount required for that third-party content to be presented in that location of the given document; and a second evaluation process that identifies, independent of the cost-prominence relationship, a winning third-party content for each of one or more locations of the electronic document, including at least a first location; wherein: the digital data include instructions that present the winning third-party content at the user device according to a given format that is automatically selected by the distributed computing system based on the cost-prominence relationship of the first evaluation process. 5. The system of claim 1 , wherein performance of the first evaluation process includes, for each given third-party content, creating in a memory structure, the cost-prominence relationship for the given third-party content. | 0.555019 |
1. A method of enhancing speech, comprising: receiving noisy speech comprising a clean speech component and a non-stationary noise component; providing a speech model; providing a noise model having at least one shape and a gain; dynamically modifying the at least one shape and the gain of the noise model based at least in part on the speech model and the received noisy speech using a processor; and enhancing the noisy speech at least based on the modified noise model. | 1. A method of enhancing speech, comprising: receiving noisy speech comprising a clean speech component and a non-stationary noise component; providing a speech model; providing a noise model having at least one shape and a gain; dynamically modifying the at least one shape and the gain of the noise model based at least in part on the speech model and the received noisy speech using a processor; and enhancing the noisy speech at least based on the modified noise model. 4. The method of claim 1 , wherein the noisy speech enhancement is further based on the speech model. | 0.616044 |
1. A multi-lingual text-to-speech system, comprising: an acoustic-prosodic model selection module, for an inputted text to be synthesized and containing a second-language (L2) portion, and an L2 phonetic unit transcription corresponding to the L2 portion of the inputted text, sequentially finds a second acoustic-prosodic model corresponding to each phonetic unit of the L2 phonetic unit transcription in an L2 acoustic-prosodic model set, searches an L2-to-L1 phonetic unit transformation table, L1 being a first language, and uses at least a controllable accent weighting parameter to determine a transformation combination to select a corresponding L1 phonetic unit transcription and sequentially find a first acoustic-prosodic model corresponding to each phonetic unit of said L1 phonetic unit transcription in an L1 acoustic-prosodic model set; an acoustic-prosodic model mergence module that merges said first and said second acoustic-prosodic models into a merged acoustic-prosodic model according to said at least a controllable accent weighting parameter, sequentially processes all the transformations in said transformation combination, then sequentially arranges each merged acoustic-prosodic model to generate a merged acoustic-prosodic model sequence; and a speech synthesizer, wherein said merged acoustic-prosodic model sequence is applied to said speech synthesizer to synthesize said inputted text into an L2 speech with an L1 accent based at least partly on the transformation combination determined by the controllable accent weighting parameter. | 1. A multi-lingual text-to-speech system, comprising: an acoustic-prosodic model selection module, for an inputted text to be synthesized and containing a second-language (L2) portion, and an L2 phonetic unit transcription corresponding to the L2 portion of the inputted text, sequentially finds a second acoustic-prosodic model corresponding to each phonetic unit of the L2 phonetic unit transcription in an L2 acoustic-prosodic model set, searches an L2-to-L1 phonetic unit transformation table, L1 being a first language, and uses at least a controllable accent weighting parameter to determine a transformation combination to select a corresponding L1 phonetic unit transcription and sequentially find a first acoustic-prosodic model corresponding to each phonetic unit of said L1 phonetic unit transcription in an L1 acoustic-prosodic model set; an acoustic-prosodic model mergence module that merges said first and said second acoustic-prosodic models into a merged acoustic-prosodic model according to said at least a controllable accent weighting parameter, sequentially processes all the transformations in said transformation combination, then sequentially arranges each merged acoustic-prosodic model to generate a merged acoustic-prosodic model sequence; and a speech synthesizer, wherein said merged acoustic-prosodic model sequence is applied to said speech synthesizer to synthesize said inputted text into an L2 speech with an L1 accent based at least partly on the transformation combination determined by the controllable accent weighting parameter. 4. The system as claimed in claim 1 , wherein said second acoustic-prosodic model and said first acoustic-prosodic model at least comprise an acoustic parameter. | 0.654473 |
1. A method comprising: receiving a first request, wherein the first request is a request to provide a requested service, the requested service is one of a plurality of services, the first request conforms to a request format defined in a first language, the first request is received by a module configured to receive the first request from a plurality of source types, and the plurality of source types comprises an applet executing on a first remote network node, and a control module executing on a second remote network node; parsing the first request by providing the first request to a language parser, wherein the language parser is configured to parse the first language; obtaining results of parsing the first request from the language parser; in response to the obtaining the results, selecting a first device, wherein the selecting comprises determining whether the first device is coupled to the language parser, and in response to a determination that the first device is not coupled to the language parser, adding the first device to a plurality of devices coupled to the language parser; and coupling the first device to the language parser, wherein the first device is configured to provide the requested service, each of the plurality of devices is configured to provide a corresponding service of the plurality of services, and at least two devices among the plurality of devices are configured to provide the requested service; and converting the first request to a second request, wherein the second request conforms to a request format defined in a second language, the first device is configured to provide the requested service in response to receiving the second request, a language-specific interface of each device of the plurality of devices is incompatible with a language-specific interface of each other device of the plurality of devices, and the each other device of the plurality of devices are those devices of the plurality of devices other than the each device. | 1. A method comprising: receiving a first request, wherein the first request is a request to provide a requested service, the requested service is one of a plurality of services, the first request conforms to a request format defined in a first language, the first request is received by a module configured to receive the first request from a plurality of source types, and the plurality of source types comprises an applet executing on a first remote network node, and a control module executing on a second remote network node; parsing the first request by providing the first request to a language parser, wherein the language parser is configured to parse the first language; obtaining results of parsing the first request from the language parser; in response to the obtaining the results, selecting a first device, wherein the selecting comprises determining whether the first device is coupled to the language parser, and in response to a determination that the first device is not coupled to the language parser, adding the first device to a plurality of devices coupled to the language parser; and coupling the first device to the language parser, wherein the first device is configured to provide the requested service, each of the plurality of devices is configured to provide a corresponding service of the plurality of services, and at least two devices among the plurality of devices are configured to provide the requested service; and converting the first request to a second request, wherein the second request conforms to a request format defined in a second language, the first device is configured to provide the requested service in response to receiving the second request, a language-specific interface of each device of the plurality of devices is incompatible with a language-specific interface of each other device of the plurality of devices, and the each other device of the plurality of devices are those devices of the plurality of devices other than the each device. 13. The method of claim 1 , wherein at least one of the plurality of devices is configured to receive requests conforming only to another request format, the another request format is defined in a third language, and the second language and the third language are incompatible with one another. | 0.625596 |
23. A computer-readable medium having computer-executable instructions, when executed by a computer configured to: receive an input schema, the input schema specifying how to represent one or more elements in one or more documents; receive one or more rules; analyze the input schema for conformance to the one or more rules; if the input schema does not conform to the one or more rules, generate a modified schema based on the input schema, the modified schema specifying how to represent the one or more elements in the one or more documents in conformance with the one or more rules; validate a document against the modified schema; and generate a report if the document is not properly validated against the modified schema. | 23. A computer-readable medium having computer-executable instructions, when executed by a computer configured to: receive an input schema, the input schema specifying how to represent one or more elements in one or more documents; receive one or more rules; analyze the input schema for conformance to the one or more rules; if the input schema does not conform to the one or more rules, generate a modified schema based on the input schema, the modified schema specifying how to represent the one or more elements in the one or more documents in conformance with the one or more rules; validate a document against the modified schema; and generate a report if the document is not properly validated against the modified schema. 25. The computer-readable medium of claim 23 , the instructions when executed are further operable to: compile a plurality of reports, the plurality of reports corresponding to a plurality of documents that failed to properly validate; and further modify the modified schema based on the plurality of reports. | 0.544444 |
21. The computer program product of claim 14 , wherein the method further comprises: engaging in a dialog with the user, including: receiving input from the user, producing a voice markup language script in response to the input, and executing the voice markup language script to generate an output for provision to the user. | 21. The computer program product of claim 14 , wherein the method further comprises: engaging in a dialog with the user, including: receiving input from the user, producing a voice markup language script in response to the input, and executing the voice markup language script to generate an output for provision to the user. 22. The computer program product of claim 21 , wherein executing the voice markup language script comprises: interpreting the voice markup language script to produce an audio output. | 0.834395 |
1. A method comprising: receiving, by one or more computer processors, a scanned image of a source text comprising a first glyph and a second glyph, wherein the first glyph and the second glyph correspond to a first instance and a second instance of a character in the source text, respectively, and wherein the first instance of the character appears in a first word of the source text and the second instance of the character appears in a second word of the source text, the first word including a first group of characters and the second word including a second group of characters; generating, by the one or more computer processors, a vector image representative of each of the first glyph and the second glyph; determining, by the one or more computer processors, a first horizontal reference line indicative of a default vertical alignment of the first instance of the character with respect to the first group of characters, wherein the first horizontal reference line indicates an origin of the first instance of the character; determining, by the one or more computer processors, a second horizontal reference line indicative of a vertical alignment of the first group of characters and a third horizontal reference line indicative of a vertical alignment of the second group of characters; determining, by the one or more computer processors, a first vertical distance value between the first horizontal reference line and the second horizontal reference line; assigning, by the one or more computer processors, a first numerical identifier to the first glyph; generating, by the one or more computer processors, first glyph data associated with the first glyph, the first glyph data comprising the first numerical identifier and the first vertical distance value; determining, by the one or more computer processors, a second vertical distance value for the second glyph by determining a second vertical distance between the first horizontal reference line and the third horizontal reference line; determining, by the one or more computer processors, that the second vertical distance value is different than the first vertical distance value; assigning, by the one or more computer processors, a second numerical identifier to the second glyph, wherein the second numerical identifier is different from the first numerical identifier; generating, by the one or more computer processors, second glyph data associated with the second glyph, the second glyph data comprising the second vertical distance value; generating, by the one or more computer processors, a font file configured to be executed by a renderer to render the source text, the font file comprising the vector image, the first glyph data, and the second glyph data; and generating, by the one or more computer processors, a digitally renderable format for the source text based at least in part on the font file and the scanned image. | 1. A method comprising: receiving, by one or more computer processors, a scanned image of a source text comprising a first glyph and a second glyph, wherein the first glyph and the second glyph correspond to a first instance and a second instance of a character in the source text, respectively, and wherein the first instance of the character appears in a first word of the source text and the second instance of the character appears in a second word of the source text, the first word including a first group of characters and the second word including a second group of characters; generating, by the one or more computer processors, a vector image representative of each of the first glyph and the second glyph; determining, by the one or more computer processors, a first horizontal reference line indicative of a default vertical alignment of the first instance of the character with respect to the first group of characters, wherein the first horizontal reference line indicates an origin of the first instance of the character; determining, by the one or more computer processors, a second horizontal reference line indicative of a vertical alignment of the first group of characters and a third horizontal reference line indicative of a vertical alignment of the second group of characters; determining, by the one or more computer processors, a first vertical distance value between the first horizontal reference line and the second horizontal reference line; assigning, by the one or more computer processors, a first numerical identifier to the first glyph; generating, by the one or more computer processors, first glyph data associated with the first glyph, the first glyph data comprising the first numerical identifier and the first vertical distance value; determining, by the one or more computer processors, a second vertical distance value for the second glyph by determining a second vertical distance between the first horizontal reference line and the third horizontal reference line; determining, by the one or more computer processors, that the second vertical distance value is different than the first vertical distance value; assigning, by the one or more computer processors, a second numerical identifier to the second glyph, wherein the second numerical identifier is different from the first numerical identifier; generating, by the one or more computer processors, second glyph data associated with the second glyph, the second glyph data comprising the second vertical distance value; generating, by the one or more computer processors, a font file configured to be executed by a renderer to render the source text, the font file comprising the vector image, the first glyph data, and the second glyph data; and generating, by the one or more computer processors, a digitally renderable format for the source text based at least in part on the font file and the scanned image. 2. The method of claim 1 , wherein the character is a first character, the method further comprising: identifying, by the one or more computer processors, a third glyph corresponding to an instance of a second character adjacent to the first instance of the first character in the first word and a fourth glyph corresponding to an instance of a third character adjacent to the second instance of the first character in the second word; determining, by the one or more computer processors, that the second character and the third character are a same character; determining, by the one or more computer processors, a first vertical reference line indicative of a default horizontal alignment of the first instance of the first character on the second horizontal reference line with respect to the first group of characters, wherein the first vertical reference line indicates an origin of the first instance of the first character; determining, by the one or more computer processors, a second vertical reference line indicative of a horizontal alignment of the second instance of the first character on the third horizontal reference line with respect to the second group of characters, and a third vertical reference line indicative of a default horizontal alignment of the second group of characters; determining, by the one or more computer processors, a first horizontal distance value for the third glyph by determining a horizontal distance between the first vertical reference line and the second vertical reference line; assigning, by the one or more computer processors, a third numerical identifier to the third glyph; generating, by the one or more computer processors, third glyph data associated with the third glyph, the third glyph data comprising the third numerical identifier and the first horizontal distance value; determining, by the one or more computer processors, a second horizontal distance value for the fourth glyph by determining a second horizontal distance between the second vertical reference line and the third vertical reference line; determining, by the one or more computer processors, that the second horizontal distance value is different than the first horizontal distance value; assigning, by the one or more computer processors, a fourth numerical identifier to the fourth glyph, wherein the fourth numerical identifier is different from the third numerical identifier; and generating, by the one or more computer processors, fourth glyph data associated with the fourth glyph, the fourth glyph data comprising the second horizontal distance value; wherein the font file further comprises the third glyph data and the fourth glyph data. | 0.5 |
39. The non-transitory computer-readable medium of claim 38 , further comprising program code for causing a computer to perform a method comprising: displaying a list of the audio messages in an audio message queue; and allowing the teacher to browse and select one of the audio messages in the audio message queue. | 39. The non-transitory computer-readable medium of claim 38 , further comprising program code for causing a computer to perform a method comprising: displaying a list of the audio messages in an audio message queue; and allowing the teacher to browse and select one of the audio messages in the audio message queue. 41. The non-transitory computer-readable medium of claim 39 , further comprising program code for causing a computer to perform a method comprising: allowing the teacher to establish a private audio communication channel with the selected learner. | 0.878825 |
45. The machine-readable storage medium of claim 39 , further comprising instructions which, when executed by the one or more processors, cause the one or more processors to carry out the step of: when the reputation score is better than a second predefined threshold, performing a second specified action associated with responding to messages that are not unsolicited, wherein the first predefined threshold is different from the second predefined threshold. | 45. The machine-readable storage medium of claim 39 , further comprising instructions which, when executed by the one or more processors, cause the one or more processors to carry out the step of: when the reputation score is better than a second predefined threshold, performing a second specified action associated with responding to messages that are not unsolicited, wherein the first predefined threshold is different from the second predefined threshold. 47. The machine-readable storage medium of claim 45 , wherein the message is associated with a message recipient, and wherein the step of performing the second specified action comprises sending the message to the message recipient. | 0.855443 |
23. A method for conducting an expert conversation, the method comprising: using a dialogue runtime system running on a computing system to select a sequence of nodes derived from a dialogue containing a plurality of nodes and edges between the nodes that is stored in a knowledge database in communication with the dialogue runtime system, wherein each node in the dialogue comprises one or more child nodes and at least one node in the dialogue comprises two or more parent nodes; presenting a sequence of questions to a user in a web-based browser, each question derived from a node in the selected sequence of nodes; selecting each subsequent node in the sequence based upon answers provided from the user in response to the present sequence of questions; displaying a conversation thread to the user, the conversation thread comprising the selected sequence of nodes, and the expert conversation comprising the conversation thread; wherein the conversation thread comprises a directed acyclic graph. | 23. A method for conducting an expert conversation, the method comprising: using a dialogue runtime system running on a computing system to select a sequence of nodes derived from a dialogue containing a plurality of nodes and edges between the nodes that is stored in a knowledge database in communication with the dialogue runtime system, wherein each node in the dialogue comprises one or more child nodes and at least one node in the dialogue comprises two or more parent nodes; presenting a sequence of questions to a user in a web-based browser, each question derived from a node in the selected sequence of nodes; selecting each subsequent node in the sequence based upon answers provided from the user in response to the present sequence of questions; displaying a conversation thread to the user, the conversation thread comprising the selected sequence of nodes, and the expert conversation comprising the conversation thread; wherein the conversation thread comprises a directed acyclic graph. 24. The method of claim 23 , wherein at least one selected subsequent node in the selected sequence of nodes comprises a first previously traversed node that is a parent node of a second previously traversed node in the selected sequence, the first previously traversed node comprising an intermediate node in the dialogue between start nodes and end nodes in the dialogue. | 0.568878 |
38. A method for building and utilizing tax preparation system related models using biometric data comprising: providing a tax preparation system; defining biometric data to be obtained and analyzed; providing one or more biometric data collection systems to obtain the defined biometric data; monitoring two or more users' interaction with the tax preparation system and obtaining user interaction activity data indicating the users' interaction with the tax preparation system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the users at defined times as the users interact with the tax preparation system; correlating the biometric data associated with the users with the users' interaction activity data at the defined times; obtaining baseline data associated with the users, the baseline data including data indicating when the baseline data was obtained; analyzing the biometric data associated with the users and correlated to the users' interaction activity data and the baseline data from the users, to generate emotional pattern predictive model data representing an emotional pattern predictive model associated with each of the users; analyzing the emotional pattern predictive model data representing the emotional pattern predictive models associated with each of the users to identify one or more user categories; identifying one or more user categories; for each user category identified, aggregating and analyzing the emotional pattern predictive model data associated with each of the users of that identified user category to generate user category emotional pattern profile data for that user category; determining that a current user of the tax preparation system is a user of one of the identified user categories and associating that user category with the current user; monitoring the current user's interaction with the tax preparation system and obtaining current user interaction activity data indicating the current user's interaction with the tax preparation system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the current user at defined times as the current user interacts with the tax preparation system; correlating the biometric data associated with the current user with the current user's location and/or activity within the tax preparation system; comparing the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user; and if a deviation is found between the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user, modifying one or more features and/or supporting systems associated with the tax preparation system to customize an tax preparation system user experience to the current user; and presenting the customized tax preparation system user experience to the current user. | 38. A method for building and utilizing tax preparation system related models using biometric data comprising: providing a tax preparation system; defining biometric data to be obtained and analyzed; providing one or more biometric data collection systems to obtain the defined biometric data; monitoring two or more users' interaction with the tax preparation system and obtaining user interaction activity data indicating the users' interaction with the tax preparation system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the users at defined times as the users interact with the tax preparation system; correlating the biometric data associated with the users with the users' interaction activity data at the defined times; obtaining baseline data associated with the users, the baseline data including data indicating when the baseline data was obtained; analyzing the biometric data associated with the users and correlated to the users' interaction activity data and the baseline data from the users, to generate emotional pattern predictive model data representing an emotional pattern predictive model associated with each of the users; analyzing the emotional pattern predictive model data representing the emotional pattern predictive models associated with each of the users to identify one or more user categories; identifying one or more user categories; for each user category identified, aggregating and analyzing the emotional pattern predictive model data associated with each of the users of that identified user category to generate user category emotional pattern profile data for that user category; determining that a current user of the tax preparation system is a user of one of the identified user categories and associating that user category with the current user; monitoring the current user's interaction with the tax preparation system and obtaining current user interaction activity data indicating the current user's interaction with the tax preparation system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the current user at defined times as the current user interacts with the tax preparation system; correlating the biometric data associated with the current user with the current user's location and/or activity within the tax preparation system; comparing the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user; and if a deviation is found between the biometric data associated with the current user correlated to the current user's interaction activity data with the user category emotional pattern profile data for the user category associated with the current user, modifying one or more features and/or supporting systems associated with the tax preparation system to customize an tax preparation system user experience to the current user; and presenting the customized tax preparation system user experience to the current user. 40. The method for building and utilizing tax preparation system related models using biometric data of claim 38 , wherein the biometric data includes at least one of the biometric data selected from the group of biometric data consisting of: data acquired from measuring the user's heart beat; data acquired from measuring the user's eye rotation; data acquired from measuring the user's eye dilation; data acquired from measuring the user's skin color; data acquired from measuring the user's perspiration; data acquired from measuring the user's respiration; data acquired from measuring the user's oxygen saturation; data acquired from measuring the user's blood pressure data acquired from measuring the user's skin temperature; data acquired from measuring the user's muscle tension; data acquired from measuring the user's neural activity; data acquired from measuring the user's eye blinking; data acquired from measuring the user's facial expression; data acquired from measuring the user's voice and/or speech; and data acquired from measuring the user's interactions with hardware associated with the user's interaction with the tax preparation system. | 0.546091 |
17. A computerized method of analyzing a plurality of documents, comprising: collecting and filtering terms from a plurality of documents; identifying a term-frequency vector for each of the documents; identifying a term-frequency matrix using the term-frequency vector, wherein rows of the matrix comprise values for the term-frequency vectors; projecting the term-frequency matrix onto a lower dimensional space using latent semantic analysis, to create a transformed term matrix; developing a correlation matrix comprising columns and rows corresponding, to terms of the transformed term matrix, and a plurality of elements each having a correlation value indicating a statistical relationship exclusively between two of the terms; creating a dendrogram of related concepts using a function of the correlation matrix; identifying branches of the dendrogram corresponding to related concepts; and clustering documents that contain concept term sets together. | 17. A computerized method of analyzing a plurality of documents, comprising: collecting and filtering terms from a plurality of documents; identifying a term-frequency vector for each of the documents; identifying a term-frequency matrix using the term-frequency vector, wherein rows of the matrix comprise values for the term-frequency vectors; projecting the term-frequency matrix onto a lower dimensional space using latent semantic analysis, to create a transformed term matrix; developing a correlation matrix comprising columns and rows corresponding, to terms of the transformed term matrix, and a plurality of elements each having a correlation value indicating a statistical relationship exclusively between two of the terms; creating a dendrogram of related concepts using a function of the correlation matrix; identifying branches of the dendrogram corresponding to related concepts; and clustering documents that contain concept term sets together. 18. The method of claim 17 , wherein the filtering is performed with reference to a set of stop words. | 0.625305 |
12. A mobile communication device process comprising: sending a first request outside said mobile communication device to display a document stored outside said mobile communication device; receiving and parsing output data from outside said mobile communication device corresponding to a first segment of said document, said output data comprising commands containing content and document characteristics; parsing said output data and executing each of said commands to thereby display the content of said first segment of the document according to said document characteristics comprising any navigational entities contained within said first segment; in response to user selection of a navigational entity sending a further request outside said mobile communication device containing an identifier and index value corresponding to said navigational entity; receiving and parsing a further segment of output data from outside said mobile communication device corresponding to a further segment of said document; parsing said further segment of output data and executing each command therein to thereby display the content of said further segment of the document according to said document characteristics; detecting within said mobile communication device any skipped content between said first and further segment and providing a visual indication of said skipped content, wherein said visual indication of said skipped content includes a horizontal bar indicator between said first and further segment; and, calculating and displaying size of said skipped content within said horizontal bar indicator. | 12. A mobile communication device process comprising: sending a first request outside said mobile communication device to display a document stored outside said mobile communication device; receiving and parsing output data from outside said mobile communication device corresponding to a first segment of said document, said output data comprising commands containing content and document characteristics; parsing said output data and executing each of said commands to thereby display the content of said first segment of the document according to said document characteristics comprising any navigational entities contained within said first segment; in response to user selection of a navigational entity sending a further request outside said mobile communication device containing an identifier and index value corresponding to said navigational entity; receiving and parsing a further segment of output data from outside said mobile communication device corresponding to a further segment of said document; parsing said further segment of output data and executing each command therein to thereby display the content of said further segment of the document according to said document characteristics; detecting within said mobile communication device any skipped content between said first and further segment and providing a visual indication of said skipped content, wherein said visual indication of said skipped content includes a horizontal bar indicator between said first and further segment; and, calculating and displaying size of said skipped content within said horizontal bar indicator. 14. The mobile communication device process of claim 12 , wherein each of said navigation entities includes at least one of a table of content, hyperlinks, and bookmarks. | 0.706006 |
13. The information handling system of claim 11 , wherein the a priori classification engine, the a posteriori classification engine, and the heuristics engine are each operable to classify a communication. | 13. The information handling system of claim 11 , wherein the a priori classification engine, the a posteriori classification engine, and the heuristics engine are each operable to classify a communication. 18. The information handling system of claim 13 , wherein the heuristics engine is operable to determine whether the communication should be classified as a personal message. | 0.939429 |
7. The method of claim 6 wherein applying the illumination model comprises generating a feature map for the volume from the three-dimensional data set. | 7. The method of claim 6 wherein applying the illumination model comprises generating a feature map for the volume from the three-dimensional data set. 8. The method of claim 7 wherein generating a feature map comprises generating a hot spot map. | 0.948537 |
10. An apparatus for generating a suggested personalized reaction, the apparatus comprising: a first module for determining interaction items associated with a first user of an electronic communication system, for determining interaction items associated with at least one other user, the first module coupled to receive interaction items from the electronic communication system, the interaction items associated with the first user including an online user post and the electronic communication system including an online service; a suggestion module for generating a suggested personalized reaction using interaction items associated with the first user and interaction items associated with at least one other user using a decision tree based on the content of the interaction items associated with the at least one other user, the suggestion module coupled to the first module to receive determined interaction items, the suggestion module configured to process user input associated with the suggested personalized reaction to update the decision tree; and a user interface module for presenting the suggested personalized reaction and related information and for receiving input from the first user, the user interface module coupled to receive the suggested personalized reaction from the suggestion module, the user interface module configured to receive input from the first user. | 10. An apparatus for generating a suggested personalized reaction, the apparatus comprising: a first module for determining interaction items associated with a first user of an electronic communication system, for determining interaction items associated with at least one other user, the first module coupled to receive interaction items from the electronic communication system, the interaction items associated with the first user including an online user post and the electronic communication system including an online service; a suggestion module for generating a suggested personalized reaction using interaction items associated with the first user and interaction items associated with at least one other user using a decision tree based on the content of the interaction items associated with the at least one other user, the suggestion module coupled to the first module to receive determined interaction items, the suggestion module configured to process user input associated with the suggested personalized reaction to update the decision tree; and a user interface module for presenting the suggested personalized reaction and related information and for receiving input from the first user, the user interface module coupled to receive the suggested personalized reaction from the suggestion module, the user interface module configured to receive input from the first user. 14. The apparatus of claim 10 wherein the first module is adapted to retrieve any information in the electronic communication system accessible to the first user whether the information is private or public. | 0.542416 |
9. 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: classifying a received phrase as an incomplete phrase for performing a voice action based at least on determining that (i) the voice action requires a parameter, and (ii) that no term of the phrase corresponds to the parameter; in response to classifying the phrase as an incomplete phrase, generating a prompt for entry of the parameter; in response to the prompt, receiving data indicating an entered parameter; and providing, for output, a suggested complete phrase for performing the voice action using the entered parameter, the suggested complete phrase comprising a phrase that when subsequently received causes the voice action to be performed without prompting for the entry of the parameter after determining that the suggested complete phrase includes one or more terms that correspond to the voice action. | 9. 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: classifying a received phrase as an incomplete phrase for performing a voice action based at least on determining that (i) the voice action requires a parameter, and (ii) that no term of the phrase corresponds to the parameter; in response to classifying the phrase as an incomplete phrase, generating a prompt for entry of the parameter; in response to the prompt, receiving data indicating an entered parameter; and providing, for output, a suggested complete phrase for performing the voice action using the entered parameter, the suggested complete phrase comprising a phrase that when subsequently received causes the voice action to be performed without prompting for the entry of the parameter after determining that the suggested complete phrase includes one or more terms that correspond to the voice action. 11. The system of claim 9 , wherein generating a prompt for entry of the parameter comprises at least one of: generating a user interface for display that includes fields for entry of the parameter; and synthesizing speech that requests the user speak the parameter. | 0.689891 |
4. The system of claim 1 , wherein said model builder transforms trajectory data in real-time for each of plural application contexts by aggregating and summarizing scores obtained from a user defined set of intention detection functions and user assigned criticality weights of application specific target areas to an application specific context aware representation, wherein the application specific context aware representation is a semantic representation of time stamped events corresponding to each sample point of a motion trajectory and a set of the semantic events is decided by a specific application context. | 4. The system of claim 1 , wherein said model builder transforms trajectory data in real-time for each of plural application contexts by aggregating and summarizing scores obtained from a user defined set of intention detection functions and user assigned criticality weights of application specific target areas to an application specific context aware representation, wherein the application specific context aware representation is a semantic representation of time stamped events corresponding to each sample point of a motion trajectory and a set of the semantic events is decided by a specific application context. 5. The system of claim 4 , wherein said model builder utilizes observations from different sensors by applying error bounds for obtaining a decreased measurement error. | 0.89038 |
48. The method of claim 47 , further comprising: using a formula to calculate a score for each programming code matching a search wherein the score is used to sort the display of resulting programming code from the search query to an end user; and displaying the programming code that score higher with a higher ranking if: (1) the programming code have been reused by developers previously, (2) the programming code contain a definition for an entity which is referenced by other projects, and/or (3) the programming code have a high frequency of matching terms specified in the search. | 48. The method of claim 47 , further comprising: using a formula to calculate a score for each programming code matching a search wherein the score is used to sort the display of resulting programming code from the search query to an end user; and displaying the programming code that score higher with a higher ranking if: (1) the programming code have been reused by developers previously, (2) the programming code contain a definition for an entity which is referenced by other projects, and/or (3) the programming code have a high frequency of matching terms specified in the search. 49. The method of claim 48 , wherein: the matching terms are selected from the set consisting of: a reuse score that indicates the number of times a file has been downloaded or a line of programming instruction of the file has been copied; a referenced entity count that indicates the number of references to the entities in the file from other files within the project and within an entire index; a word frequency count that indicates the number of times a search term is found divided by the number of words in the file multiplied by 100; a score that is defined by a mathematical expression that generates a score based on reuse count, referenced entity count, and word frequency count; and the use of this process ensures that files that have been reused are displayed first, followed by files that have many external references to the entities defined within are listed later, followed by files that have a high frequency of the search terms contained within the content. | 0.65062 |
19. A device control method, comprising: performing, in a computer: a speech recognition step of acquiring speech data representing a speech and specifying words candidates included in the speech by performing speech recognition on the speech data and calculating a likelihood of each of the specified words candidates; a specifying step of specifying words included in the speech based on likelihoods specified in the speech recognition step and specifying a content of the speech uttered by an utterer based on the specified words; and a process execution step of specifying content of a subsequent control to be performed on an external device to be a control target based on a currently executed control, a predetermined subsequent control, a weighting factor associated with the currently executed control, and the specified content of the uttered speech, and performing the subsequent control, wherein the process execution step obtains the weighting factor by calculating a product of transition constants defined on routes from the currently executed control to the subsequent control associated with the currently executed control, and, among the subsequent controls associated with the currently executed control, identifies a control in which a product is a largest product of the weighting factor and the calculated likelihood. | 19. A device control method, comprising: performing, in a computer: a speech recognition step of acquiring speech data representing a speech and specifying words candidates included in the speech by performing speech recognition on the speech data and calculating a likelihood of each of the specified words candidates; a specifying step of specifying words included in the speech based on likelihoods specified in the speech recognition step and specifying a content of the speech uttered by an utterer based on the specified words; and a process execution step of specifying content of a subsequent control to be performed on an external device to be a control target based on a currently executed control, a predetermined subsequent control, a weighting factor associated with the currently executed control, and the specified content of the uttered speech, and performing the subsequent control, wherein the process execution step obtains the weighting factor by calculating a product of transition constants defined on routes from the currently executed control to the subsequent control associated with the currently executed control, and, among the subsequent controls associated with the currently executed control, identifies a control in which a product is a largest product of the weighting factor and the calculated likelihood. 20. The device control method according to claim 19 , further comprising: an information acquisition step of acquiring information via a predetermined communication device; and a speech output step of outputting a speech based on the information acquired in the information acquisition step, whereby when the control specified in the process execution step is to output the information acquired in the information acquisition step, a speech is output based on the information in the speech output step. | 0.575549 |
7. A method, comprising: detecting a change in position of a body member of a performer relative to a performance element of a performance object with which an event is to be performed; generating a signal dependent on the detected change in position of the body member; and recording the signal so that a first sensory cue can be determined to indicate the change in position of the body member relative to the performance element of the performance object during a learning session; determining the first sensory cue dependent on the recorded signal; and applying the first sensory cue to indicate to a user learning session the learning session the change in position of the body member of the performer during the performance of the event,the first sensory cue being effective for stimulating a first processing center of the user; wherein the first sensory cue is one of a haptic, auditory and visual sensory cue effective for stimulating a first processing center of a brain of the user; and generating a visual sensory cue capable of being displayed to the user on a video display device, the visual sensory cue providing a virtual visual indication to the user of the change in position of the body member of the performer during the performance, the visual sensory cue being effective for stimulating the visual processing center of the brain of the user, the visual sensory cue being synchronized with the first sensory cue so that the change in position of body member of the performer is virtually visually indicated in synchronization with the first sensory cue and so that the visual processing center is stimulated with a visual sensory cue in synchronization, stimulating the first processing center, wherein thesnthat 5 iDimuiatio of the first processing center and the visual processing center is effective for teaching the user to perform a version of the event. | 7. A method, comprising: detecting a change in position of a body member of a performer relative to a performance element of a performance object with which an event is to be performed; generating a signal dependent on the detected change in position of the body member; and recording the signal so that a first sensory cue can be determined to indicate the change in position of the body member relative to the performance element of the performance object during a learning session; determining the first sensory cue dependent on the recorded signal; and applying the first sensory cue to indicate to a user learning session the learning session the change in position of the body member of the performer during the performance of the event,the first sensory cue being effective for stimulating a first processing center of the user; wherein the first sensory cue is one of a haptic, auditory and visual sensory cue effective for stimulating a first processing center of a brain of the user; and generating a visual sensory cue capable of being displayed to the user on a video display device, the visual sensory cue providing a virtual visual indication to the user of the change in position of the body member of the performer during the performance, the visual sensory cue being effective for stimulating the visual processing center of the brain of the user, the visual sensory cue being synchronized with the first sensory cue so that the change in position of body member of the performer is virtually visually indicated in synchronization with the first sensory cue and so that the visual processing center is stimulated with a visual sensory cue in synchronization, stimulating the first processing center, wherein thesnthat 5 iDimuiatio of the first processing center and the visual processing center is effective for teaching the user to perform a version of the event. 10. A method according to claim 7 : wherein the applied electrical signal causes a sensation or contraction in the muscles of the user. | 0.781181 |
21. A method for enabling a developer of a steering application to associate semantic tags with user responses, the method comprising: obtaining user responses to an open-ended steering question posed by an interactive response system; selecting a subset of user responses; automatically grouping the user responses within the subset into groups, wherein each group is a set of sentences that are semantically related; automatically assigning preliminary semantic tags to each of the groups; providing a computer user interface that enables a user to validate the content of the groups to ensure that all sentences within a group have the same semantic meaning and to view and edit the preliminary semantic tags associated with the groups, wherein the computer user interface includes: a groups view that displays a list of the groups and corresponding semantic tags for each group, wherein the groups view enables a user to edit the preliminary semantic tags associated with each of the groups, a sentence view that displays, for a selected group in the groups view, a list of unique sentences associated with the selected group, wherein in the sentence view a user is able to verify whether or not a sentence belongs to the group selected in the groups view, and a related-groups view that displays, for a selected sentence in the sentence view, a plurality of groups most closely-related to the selected sentence, wherein the computer user interface enables the user to apply semantic clustering to unverified sentences, and wherein applying semantic clustering to unverified sentences re-distributes the unverified sentences into groups based at least in part on the group memberships of verified sentences; and iteratively repeating the selecting, grouping, assigning, and providing steps with different subsets of user responses until all user responses have been processed, wherein each iteration uses data from previously validated and tagged groups to increase the accuracy of the clustering and assigning steps. | 21. A method for enabling a developer of a steering application to associate semantic tags with user responses, the method comprising: obtaining user responses to an open-ended steering question posed by an interactive response system; selecting a subset of user responses; automatically grouping the user responses within the subset into groups, wherein each group is a set of sentences that are semantically related; automatically assigning preliminary semantic tags to each of the groups; providing a computer user interface that enables a user to validate the content of the groups to ensure that all sentences within a group have the same semantic meaning and to view and edit the preliminary semantic tags associated with the groups, wherein the computer user interface includes: a groups view that displays a list of the groups and corresponding semantic tags for each group, wherein the groups view enables a user to edit the preliminary semantic tags associated with each of the groups, a sentence view that displays, for a selected group in the groups view, a list of unique sentences associated with the selected group, wherein in the sentence view a user is able to verify whether or not a sentence belongs to the group selected in the groups view, and a related-groups view that displays, for a selected sentence in the sentence view, a plurality of groups most closely-related to the selected sentence, wherein the computer user interface enables the user to apply semantic clustering to unverified sentences, and wherein applying semantic clustering to unverified sentences re-distributes the unverified sentences into groups based at least in part on the group memberships of verified sentences; and iteratively repeating the selecting, grouping, assigning, and providing steps with different subsets of user responses until all user responses have been processed, wherein each iteration uses data from previously validated and tagged groups to increase the accuracy of the clustering and assigning steps. 25. The method of claim 21 , wherein the user responses are written responses. | 0.53083 |
3. A system configured to process an automation script used for testing a page, comprising: at least one hardware processor configured to initiate the following executable operations: executing the automation script; searching for an element on the page according to locating information contained within an instruction of the automation script; collecting, responsive to finding the element on the page according to the locating information, element-related information; associating the collected element-related information of the element with the instruction of the automation script; saving the collected element-related information; determining whether a better instruction for searching for the element exists according to the collected element-related information; and updating, responsive to the determining that the better instruction exists, the automation script with the better instruction. | 3. A system configured to process an automation script used for testing a page, comprising: at least one hardware processor configured to initiate the following executable operations: executing the automation script; searching for an element on the page according to locating information contained within an instruction of the automation script; collecting, responsive to finding the element on the page according to the locating information, element-related information; associating the collected element-related information of the element with the instruction of the automation script; saving the collected element-related information; determining whether a better instruction for searching for the element exists according to the collected element-related information; and updating, responsive to the determining that the better instruction exists, the automation script with the better instruction. 4. The system of claim 3 , wherein the element-related information includes at least one of full attribute, text, and location. | 0.651125 |
8. A computer system, comprising: a processor; and a storage device connected to the processor, wherein the storage device has stored thereon a program, and wherein the processor is configured to execute instructions of the program to perform operations, wherein the operations comprise: dynamically generating an environment dictionary for a document that is being viewed based on information from one or more social networks associated with the user; and in response to receiving a portion of a word for the document, receiving a list of words for use in completing the portion of the word, wherein each word in the list of words has an associated weight; for at least one word in the list of words, obtaining an environment weight from the dynamically created environment dictionary; updating the associated weight of the at least one word using the obtained environment weight; and ordering the words in the list of words based on the updated, associated weight of each of the words. | 8. A computer system, comprising: a processor; and a storage device connected to the processor, wherein the storage device has stored thereon a program, and wherein the processor is configured to execute instructions of the program to perform operations, wherein the operations comprise: dynamically generating an environment dictionary for a document that is being viewed based on information from one or more social networks associated with the user; and in response to receiving a portion of a word for the document, receiving a list of words for use in completing the portion of the word, wherein each word in the list of words has an associated weight; for at least one word in the list of words, obtaining an environment weight from the dynamically created environment dictionary; updating the associated weight of the at least one word using the obtained environment weight; and ordering the words in the list of words based on the updated, associated weight of each of the words. 11. The computer system of claim 8 , wherein the operations further comprise: updating the environment dictionary based on new information collected from at least one of an environment of the user and the one or more social networks associated with the user. | 0.638268 |
1. One or more computer-readable storage media having computer-executable instructions embodied thereon, that when executed, cause a computing device to perform a method of presenting on a search results page a plurality of preview videos that have been algorithmically determined to be most relevant to various informational items and that are played in succession without user intervention, the method comprising: determining from a database a first informational item and a second informational item that have associated preview videos; algorithmically determining a first video associated with the first informational item and a second video associated with the second informational item, wherein the first and the second videos are determined by a ranking system; algorithmically extracting a first important portion of the first video to form a first preview video and a second important portion of the second video to form a second preview video; combining the first preview video and the second preview video into a single video file such that the second preview video is sequentially played after the first preview video has been played; communicating for display on the search results page the first informational item and the second informational item and the single video file that includes at least the first and the second preview videos; determining a first set of related content associated with the first preview video, wherein the first set of related content is different from the first informational item and the first preview video; determining a second set of related content associated with the second preview video, wherein the second set of related content is different from the second informational item and the second preview video; receiving an indication to initiate play of the single video file: and upon receiving the indication to initiate play of the single video file, automatically and sequentially displaying the first set of related content and the second set of related content such that: (1) only one set of related content is displayed at any one time, and (2) the first set of related content is displayed simultaneously with the first preview video and the second set of related content is displayed simultaneously with the second preview video. | 1. One or more computer-readable storage media having computer-executable instructions embodied thereon, that when executed, cause a computing device to perform a method of presenting on a search results page a plurality of preview videos that have been algorithmically determined to be most relevant to various informational items and that are played in succession without user intervention, the method comprising: determining from a database a first informational item and a second informational item that have associated preview videos; algorithmically determining a first video associated with the first informational item and a second video associated with the second informational item, wherein the first and the second videos are determined by a ranking system; algorithmically extracting a first important portion of the first video to form a first preview video and a second important portion of the second video to form a second preview video; combining the first preview video and the second preview video into a single video file such that the second preview video is sequentially played after the first preview video has been played; communicating for display on the search results page the first informational item and the second informational item and the single video file that includes at least the first and the second preview videos; determining a first set of related content associated with the first preview video, wherein the first set of related content is different from the first informational item and the first preview video; determining a second set of related content associated with the second preview video, wherein the second set of related content is different from the second informational item and the second preview video; receiving an indication to initiate play of the single video file: and upon receiving the indication to initiate play of the single video file, automatically and sequentially displaying the first set of related content and the second set of related content such that: (1) only one set of related content is displayed at any one time, and (2) the first set of related content is displayed simultaneously with the first preview video and the second set of related content is displayed simultaneously with the second preview video. 6. The media of claim 1 , wherein the first and second set of related content include one or more of an article, a video, an image, or an audio clip. | 0.578746 |
10. The method of acquiring rules for a computer-based expert system, said rules being characterized by a predetermined grammar and conditions involving queries having more than one possible answer, said method comprising, serially receiving portions of a sentence input from an expert, in response to an already received portion of sentence input, generating alternatives for a next portion of a sentence permitted by said predetermined grammar, accepting a further portion of said sentence input from said expert as matches one of said alternatives, as said further sentence portion is accepted, continuing to generate allowable alternatives and accept matching input for following sentence portions from said expert until a statement is completed according to said predetermined grammar, and transforming the completed statement into the form of a diagnostic rule. | 10. The method of acquiring rules for a computer-based expert system, said rules being characterized by a predetermined grammar and conditions involving queries having more than one possible answer, said method comprising, serially receiving portions of a sentence input from an expert, in response to an already received portion of sentence input, generating alternatives for a next portion of a sentence permitted by said predetermined grammar, accepting a further portion of said sentence input from said expert as matches one of said alternatives, as said further sentence portion is accepted, continuing to generate allowable alternatives and accept matching input for following sentence portions from said expert until a statement is completed according to said predetermined grammar, and transforming the completed statement into the form of a diagnostic rule. 14. The method according to claim 10, wherein transforming the completed statement into the form of a diagnostic rule comprises: constructing functional description equations from fragments of said statement, combining functional equations to form functional structures, and converting said functional structures to rule clauses. | 0.5 |
1. A method comprising: identifying, via a processor, an identifier in a text, wherein the identifier identifies an element of a figure in a first language, wherein the figure comprises a reference and a first line, wherein the first line extends between the element and the reference; accessing, via the processor, a data structure referencing between the first language and a second language; translating, via the processor, the identifier from the first language to the second language based at least in part on the data structure; modifying, via the processor, the figure based at least in part on the translating, wherein the modifying comprises at least one of: placing, via the processor, the identifier recited in the second language onto the figure adjacent to the reference without overlying the reference; placing, via the processor, a second line and the identifier recited in the second language onto the figure such that the reference is positioned between the first line and the second line and such that the second line is positioned between the reference and the identifier recited in the second language; replacing, via the processor, the reference in the figure with the identifier recited in the second language; placing, via the processor, the identifier recited in the second language onto the figure such that the identifier recited in the second language is positioned within the element; or placing, via the processor, a shape and the identifier recited in the second language onto the figure such that the shape encloses the reference and the identifier recited in the second language. | 1. A method comprising: identifying, via a processor, an identifier in a text, wherein the identifier identifies an element of a figure in a first language, wherein the figure comprises a reference and a first line, wherein the first line extends between the element and the reference; accessing, via the processor, a data structure referencing between the first language and a second language; translating, via the processor, the identifier from the first language to the second language based at least in part on the data structure; modifying, via the processor, the figure based at least in part on the translating, wherein the modifying comprises at least one of: placing, via the processor, the identifier recited in the second language onto the figure adjacent to the reference without overlying the reference; placing, via the processor, a second line and the identifier recited in the second language onto the figure such that the reference is positioned between the first line and the second line and such that the second line is positioned between the reference and the identifier recited in the second language; replacing, via the processor, the reference in the figure with the identifier recited in the second language; placing, via the processor, the identifier recited in the second language onto the figure such that the identifier recited in the second language is positioned within the element; or placing, via the processor, a shape and the identifier recited in the second language onto the figure such that the shape encloses the reference and the identifier recited in the second language. 7. The method of claim 1 , wherein the data structure is hosted on a data source remote from the processor. | 0.568591 |
13. A computer readable medium for storing a program that causes a computer to: execute a pre-scan of a document, on which document the user has marked a plurality of document blocks, and creating pre-scan image data from which pre-scan image data the plurality of document blocks that is marked by the user are detected; extract the plurality of document blocks that are digital image data representing a portion of the scanned document, the scanned document having document images and a background, the plurality of document blocks include document image data and background image data, the document image data represents some of the document images on the scanned document, wherein all the document image data in the extracted plurality of document blocks represents fewer document images than are present in the scanned document; generate character code data for character image data within the plurality of document blocks; reconstruct the plurality of document blocks into a single document block in a specific shape based on the plurality of extracted document blocks; and laying out the generated character code data within the reconstructed document block to create a layout image. | 13. A computer readable medium for storing a program that causes a computer to: execute a pre-scan of a document, on which document the user has marked a plurality of document blocks, and creating pre-scan image data from which pre-scan image data the plurality of document blocks that is marked by the user are detected; extract the plurality of document blocks that are digital image data representing a portion of the scanned document, the scanned document having document images and a background, the plurality of document blocks include document image data and background image data, the document image data represents some of the document images on the scanned document, wherein all the document image data in the extracted plurality of document blocks represents fewer document images than are present in the scanned document; generate character code data for character image data within the plurality of document blocks; reconstruct the plurality of document blocks into a single document block in a specific shape based on the plurality of extracted document blocks; and laying out the generated character code data within the reconstructed document block to create a layout image. 18. The computer readable medium as claimed in claim 13 , wherein the plurality of document blocks also includes a photographic image area that is extracted and laid out with the character code data. | 0.761324 |
15. A non-transitory computer-readable medium containing instructions that, when executed by a computer processor, cause the computer processor to: receive data identifying a set of seed content items and a sequential order for the set of seed content items, wherein the set of seed content items includes at least one seed content item included in a first content item playlist, and the sequential order indicates an order in which seed content items from the set of seed content items are ordered to be performed in the first content item playlist; generate a seed content attribute sequence based on attributes of at least a first seed content item of the set of seed content items and the sequential order for the set of seed content items; generate a recommended content attribute sequence that is likely to follow the seed content attribute sequence, the recommended content attribute sequence determined from the seed content attribute sequence and a statistical language model based on an analysis of a set of reference content attribute sequences, wherein the set of reference content attribute sequences were generated from a set of user created content playlists; and select a set of recommended content items to be added to the first content item playlist and performed sequentially after the set of seed content items in a recommended sequential order, the set of recommended content item and the recommended sequential order selected based on content attributes of the set of recommended content items and the recommended content attribute sequence. | 15. A non-transitory computer-readable medium containing instructions that, when executed by a computer processor, cause the computer processor to: receive data identifying a set of seed content items and a sequential order for the set of seed content items, wherein the set of seed content items includes at least one seed content item included in a first content item playlist, and the sequential order indicates an order in which seed content items from the set of seed content items are ordered to be performed in the first content item playlist; generate a seed content attribute sequence based on attributes of at least a first seed content item of the set of seed content items and the sequential order for the set of seed content items; generate a recommended content attribute sequence that is likely to follow the seed content attribute sequence, the recommended content attribute sequence determined from the seed content attribute sequence and a statistical language model based on an analysis of a set of reference content attribute sequences, wherein the set of reference content attribute sequences were generated from a set of user created content playlists; and select a set of recommended content items to be added to the first content item playlist and performed sequentially after the set of seed content items in a recommended sequential order, the set of recommended content item and the recommended sequential order selected based on content attributes of the set of recommended content items and the recommended content attribute sequence. 19. The non-transitory computer-readable medium of claim 15 , wherein the instructions further cause the computer processor to: receive a denial message indicating that a human user has denied at least a first recommended content item of the set of recommended content items; and generate an updated set of recommend content items, the updated set of recommended content item including an updated recommended content item in place of the first recommend content item, wherein the updated content item is not included in the set of recommended content items. | 0.512694 |
9. A computer program product for use at computer system, the computer system including a display device, the computer program product for implementing a method for visually representing a query of multi-source data, the computer program product comprising one or more computer storage devices having stored thereon computer-executable instructions that, when executed a processor, cause the computer system to perform the method, including the following: access a data set, the data set including data combined from a plurality of different sources; supplement presentation of data contained in a portion of the data set on the display device by using a visual cue to visually indicate any occurrences of a query term within the data contained in the portion of the data set on the display device, visually indicating occurrences of the query term highlighting the volume of the query term within the data contained in the portion of the data set; receive a command to query a larger portion of the data set for the query term, the larger portion of the data set including the portion of the data set; determine that data contained in the data set is not to be displayed on the display device in response to the command; and present the visual cue in an arrangement of locations on the display device to visually indicate occurrences of the query term in the data contained in the larger portion of the data set, each location in the arrangement of locations indicating where the query term would have be presented on the display device had the data contained in the larger portion of the data set been presented at the display device, presenting the arrangement of locations permitting insight into the volume of the query term in the data contained in the larger portion of the data set without consuming presentation space on the display device to present the data contained in the larger portion of the data set. | 9. A computer program product for use at computer system, the computer system including a display device, the computer program product for implementing a method for visually representing a query of multi-source data, the computer program product comprising one or more computer storage devices having stored thereon computer-executable instructions that, when executed a processor, cause the computer system to perform the method, including the following: access a data set, the data set including data combined from a plurality of different sources; supplement presentation of data contained in a portion of the data set on the display device by using a visual cue to visually indicate any occurrences of a query term within the data contained in the portion of the data set on the display device, visually indicating occurrences of the query term highlighting the volume of the query term within the data contained in the portion of the data set; receive a command to query a larger portion of the data set for the query term, the larger portion of the data set including the portion of the data set; determine that data contained in the data set is not to be displayed on the display device in response to the command; and present the visual cue in an arrangement of locations on the display device to visually indicate occurrences of the query term in the data contained in the larger portion of the data set, each location in the arrangement of locations indicating where the query term would have be presented on the display device had the data contained in the larger portion of the data set been presented at the display device, presenting the arrangement of locations permitting insight into the volume of the query term in the data contained in the larger portion of the data set without consuming presentation space on the display device to present the data contained in the larger portion of the data set. 16. The computer program product of claim 9 , wherein the data contained in the data set comprises real time messaging data from a plurality of messaging users; and further comprising computer-executable instructions that, when executed, cause the computer system to derive a possible trend for the query term within the real time messaging data based on the arrangement of locations of the visual cue. | 0.636997 |
14. A computer-implemented method of evaluating an access request against an attribute-based access control (ABAC) policy, wherein the method is implemented in a policy decision point (PDP), which is communicatively coupled over a communication link to at least one remote attribute source (RAS), and wherein the ABAC policy comprises hierarchically ordered functional expressions, each functional expression having at least one other functional expression and/or at least one attribute as a subordinate, the value of each attribute being either locally available at the PDP or remotely available in response to a query submitted from the PDP to one of said at least one RAS, the method comprising: i) a processor in the PDP receiving an access request intended for an ABAC policy; ii) the processor in the PDP obtaining a transformed ABAC policy equivalent to said ABAC policy, the transformed ABAC policy comprising at least one functional expression representing a remote query to one of said at least one RAS; and iii) the processor in the PDP initiating evaluation of the access request against the transformed ABAC policy, including generating, in response to encountering said functional expression, the remote query to said one RAS, executing the query and receiving output data resulting from the execution, wherein the received output data are propagated into the subsequent evaluation of the access request. | 14. A computer-implemented method of evaluating an access request against an attribute-based access control (ABAC) policy, wherein the method is implemented in a policy decision point (PDP), which is communicatively coupled over a communication link to at least one remote attribute source (RAS), and wherein the ABAC policy comprises hierarchically ordered functional expressions, each functional expression having at least one other functional expression and/or at least one attribute as a subordinate, the value of each attribute being either locally available at the PDP or remotely available in response to a query submitted from the PDP to one of said at least one RAS, the method comprising: i) a processor in the PDP receiving an access request intended for an ABAC policy; ii) the processor in the PDP obtaining a transformed ABAC policy equivalent to said ABAC policy, the transformed ABAC policy comprising at least one functional expression representing a remote query to one of said at least one RAS; and iii) the processor in the PDP initiating evaluation of the access request against the transformed ABAC policy, including generating, in response to encountering said functional expression, the remote query to said one RAS, executing the query and receiving output data resulting from the execution, wherein the received output data are propagated into the subsequent evaluation of the access request. 22. A computer program product comprising a non-transitory computer-readable medium with instructions for causing a programmable computer to perform the method of claim 14 . | 0.586825 |
42. A system for facilitating a display of markup document content retrieved from a host server on a computer network, the computer network including a client system and a server system, the system comprising: at least one processor; at least one interface configured or designed to provide a communication link to at least one other network device in the data network; and memory including instructions that, when executed by the processor, cause the system to: track interaction of a user with the markup document; store user activity tracking information for the user with respect to the markup document, the user activity tracking information relating to at least one relative position within content associated with the markup document that indicates a first portion of the content associated with a previous version of the markup document that was previously displayed to the user; receive a request in response to an action by a user of the client system, the action triggering the request corresponding to the markup document; retrieve content associated with the markup document, wherein at least a portion of the content was previously displayed to the user on the client system; identify, based at least in part of the user activity tracking information, intra page bookmark information that enables display of the retrieved content associated with the markup document according to the relative position such that said at least a portion of the markup document that was previously displayed to the user is distinguished from another portion of the retrieved content that has yet to be displayed to the user, said another portion that has yet to be displayed to the user being capable of including content that was part of the markup document when said at least a portion of the markup document was previously displayed to the user; modify, based at least in part on the intra page bookmark information, display information for the markup document such that the portion of the markup document that was previously displayed to the user is distinguished from said another portion in a manner enabling the user to locate a beginning of the second portion; enable the user to manually insert intra page bookmarks to bookmark a desired location within the markup document, the bookmark allowing the user to start at the desired location after closing the markup document; and enabling the user to selectively choose to display the intra page bookmarks. | 42. A system for facilitating a display of markup document content retrieved from a host server on a computer network, the computer network including a client system and a server system, the system comprising: at least one processor; at least one interface configured or designed to provide a communication link to at least one other network device in the data network; and memory including instructions that, when executed by the processor, cause the system to: track interaction of a user with the markup document; store user activity tracking information for the user with respect to the markup document, the user activity tracking information relating to at least one relative position within content associated with the markup document that indicates a first portion of the content associated with a previous version of the markup document that was previously displayed to the user; receive a request in response to an action by a user of the client system, the action triggering the request corresponding to the markup document; retrieve content associated with the markup document, wherein at least a portion of the content was previously displayed to the user on the client system; identify, based at least in part of the user activity tracking information, intra page bookmark information that enables display of the retrieved content associated with the markup document according to the relative position such that said at least a portion of the markup document that was previously displayed to the user is distinguished from another portion of the retrieved content that has yet to be displayed to the user, said another portion that has yet to be displayed to the user being capable of including content that was part of the markup document when said at least a portion of the markup document was previously displayed to the user; modify, based at least in part on the intra page bookmark information, display information for the markup document such that the portion of the markup document that was previously displayed to the user is distinguished from said another portion in a manner enabling the user to locate a beginning of the second portion; enable the user to manually insert intra page bookmarks to bookmark a desired location within the markup document, the bookmark allowing the user to start at the desired location after closing the markup document; and enabling the user to selectively choose to display the intra page bookmarks. 45. The system of claim 42 , wherein the markup document corresponds to a weblog page. | 0.587722 |
5. A method according to claim 4, wherein: said step of copying the fourth reference to the third reference occurs only when the second user dictionary has been modified or created by the content portion of the subsequent hierarchical level. | 5. A method according to claim 4, wherein: said step of copying the fourth reference to the third reference occurs only when the second user dictionary has been modified or created by the content portion of the subsequent hierarchical level. 6. A method according to claim 5, wherein: said step of copying the fourth reference to the third reference occurs only when a setup procedure SPDL element has been processed. | 0.952326 |
1. An apparatus comprising a processor and a memory storing executable instructions that in response to execution by the processor cause the apparatus to at least perform the following: intercepting a communication from a sender to a receiver, the communication being formatted in a structured mark-up language, the mark-up language including at least one protocol primitive for an application that sends and receives communications, each protocol primitive including one or more protocol information elements that carry information about a communication, each protocol information element including lawful interception (LI) attributes that include at least one of a type of content and a level of interception; comparing a protocol primitive in the intercepted communication with a document type definition (DTD) for the mark-up language, to identify the LI attributes of the protocol information elements in the intercepted communication, the DTD specifying the LI attributes of the protocol information elements; and preparing one or more of the protocol information elements in the intercepted communication for transmission to an interception monitoring facility according to the LI attributes of the protocol information elements. | 1. An apparatus comprising a processor and a memory storing executable instructions that in response to execution by the processor cause the apparatus to at least perform the following: intercepting a communication from a sender to a receiver, the communication being formatted in a structured mark-up language, the mark-up language including at least one protocol primitive for an application that sends and receives communications, each protocol primitive including one or more protocol information elements that carry information about a communication, each protocol information element including lawful interception (LI) attributes that include at least one of a type of content and a level of interception; comparing a protocol primitive in the intercepted communication with a document type definition (DTD) for the mark-up language, to identify the LI attributes of the protocol information elements in the intercepted communication, the DTD specifying the LI attributes of the protocol information elements; and preparing one or more of the protocol information elements in the intercepted communication for transmission to an interception monitoring facility according to the LI attributes of the protocol information elements. 3. The apparatus of claim 1 , wherein the executable instructions cause the apparatus to further perform the following: receiving a preliminary DTD including the protocol information elements of the mark-up language, without their LI attributes; and augmenting the preliminary DTD to include the LI attributes of the protocol information elements, wherein the LI attributes include (i) a type of content selected from a group of types including content of communication, interception-related information, and a combination of content of communication and interception-related information, and (ii) a level of interception selected from a group of levels representing different amounts of information to be transmitted to the interception monitoring facility. | 0.617626 |
13. The system of claim 12 , wherein automatically generating the one or more sentences comprises automatically generating the one or more sentences using one or more regular expressions. | 13. The system of claim 12 , wherein automatically generating the one or more sentences comprises automatically generating the one or more sentences using one or more regular expressions. 14. The system of claim 13 , wherein the instructions, when executed by the one or more processors, further cause: selecting a particular regular expression from among a plurality of regular expressions; wherein the one or more regular expressions includes the particular regular expression and are fewer than the plurality of regular expressions. | 0.75266 |
1. A method of providing a visualization graph on a computer with memory, a processor, and a display device, the method comprising: storing data in the memory corresponding to a plurality of entities having a particular type, wherein a semantic net includes the entities and wherein the entities are linked to each other by a plurality of relations; providing, by executing a process in the processor, a visualization graph on the display device in response to a query with respect to an entity selected from the plurality of entities, wherein the visualization graph includes: a first of the entities, representing results of the query, displayed because it is a focus entity defined by the user or the query a second of the entities, representing the results of the query, displayed because it is directly related to the focus entity, wherein a third of the entities, representing the results of the query, is not displayed because it is indirectly related to the focus entity; a fourth of the entities, representing the results of the query, that is indirectly related to the focus entity, wherein context information is used to determine that the fourth entity be displayed; a plurality of sectors representing the results of the query, the plurality of sectors being subdivisions of a screen area with boundaries; a plurality of sub-sectors being subdivisions inside the boundaries of the plurality of sectors, the subsectors also having boundaries, wherein a size of a predetermined one of the plurality of sub-sectors depends on a number of the entities allocated to the predetermined sub-sector, wherein a predetermined one of the plurality of sectors has a size that depends on a number of the entities allocated to the predetermined sector and the number of the entities allocated to the predetermined sub-sector; displaying the entities inside the boundaries of the predetermined sector and the boundaries of the predetermined sub-sector of the visualization graph depending on an entity type and entity sub-type of the allocated entities, respectively; and providing an invisible attractor in the predetermined sector, which attracts a subset of the entities to the predetermined sector depending on the entity type of the subset of entities, wherein the invisible attractor remains invisible during user interaction with the visualization graph. | 1. A method of providing a visualization graph on a computer with memory, a processor, and a display device, the method comprising: storing data in the memory corresponding to a plurality of entities having a particular type, wherein a semantic net includes the entities and wherein the entities are linked to each other by a plurality of relations; providing, by executing a process in the processor, a visualization graph on the display device in response to a query with respect to an entity selected from the plurality of entities, wherein the visualization graph includes: a first of the entities, representing results of the query, displayed because it is a focus entity defined by the user or the query a second of the entities, representing the results of the query, displayed because it is directly related to the focus entity, wherein a third of the entities, representing the results of the query, is not displayed because it is indirectly related to the focus entity; a fourth of the entities, representing the results of the query, that is indirectly related to the focus entity, wherein context information is used to determine that the fourth entity be displayed; a plurality of sectors representing the results of the query, the plurality of sectors being subdivisions of a screen area with boundaries; a plurality of sub-sectors being subdivisions inside the boundaries of the plurality of sectors, the subsectors also having boundaries, wherein a size of a predetermined one of the plurality of sub-sectors depends on a number of the entities allocated to the predetermined sub-sector, wherein a predetermined one of the plurality of sectors has a size that depends on a number of the entities allocated to the predetermined sector and the number of the entities allocated to the predetermined sub-sector; displaying the entities inside the boundaries of the predetermined sector and the boundaries of the predetermined sub-sector of the visualization graph depending on an entity type and entity sub-type of the allocated entities, respectively; and providing an invisible attractor in the predetermined sector, which attracts a subset of the entities to the predetermined sector depending on the entity type of the subset of entities, wherein the invisible attractor remains invisible during user interaction with the visualization graph. 4. The method according to claim 1 , wherein the location of an entity on the graph is determined by a sum of the influence exerted on the entity by the attractor and the repulsors. | 0.553579 |
10. The method of claim 1 further comprising: receiving one or more facets selected by a user from the selected number of facets; refining the search result set based on the one or more facets selected by the user. | 10. The method of claim 1 further comprising: receiving one or more facets selected by a user from the selected number of facets; refining the search result set based on the one or more facets selected by the user. 12. The method of claim 10 , wherein the refining the search result set comprises refining the search result set based on a single facet selected by the user. | 0.893478 |
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