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4,773,099 | 6 | 7 | 6. The method of claim 2 wherein a confidence region contains at most relatively few reference feature vectors not of said associated class. | 6. The method of claim 2 wherein a confidence region contains at most relatively few reference feature vectors not of said associated class. 7. The method of claim 6 wherein said relatively few reference feature vectors not of said associated class represent patterns similar to those of said associated class. | 0.951961 |
8,156,134 | 1 | 2 | 1. An article of manufacture comprising a computer readable storage medium having code executed to perform operations, the operations comprising: providing a module mapping associating a plurality of first type query translator modules with a first data store type to which the first query translator modules apply and associating a plurality of second query translator modules with a second data store type to which the second query translator modules apply, wherein the first and second query translator modules for the first and second data store types include database specific operations to implement query optimization for the first and second data store types to which the first and second query translator modules respectively apply and include first and second resolve modules, respectively; receiving a query to query a target data store; determining whether the target data store is of the first data store type or the second data store type; determining from the module mapping the first query translators to use in response to determining that the target data store is of the first data store type and the second query translator modules to use in response to determining that the target data store is of the second data store type; generating a parse tree of nodes; grouping the nodes according to query parts to produce a query graph; forwarding the query graph to the first or second resolve module from the determined first or second query translator modules to validate that the query attributes are valid attributes in the target data store; and in response to validating the query parts, performing: using the first query translator modules to translate the received query to a query execution plan in response to determining that the target data store is of the first data store type; and using the second query translator modules to translate the received query to a query execution plan in response to determining that the target data store is of the second data store type. | 1. An article of manufacture comprising a computer readable storage medium having code executed to perform operations, the operations comprising: providing a module mapping associating a plurality of first type query translator modules with a first data store type to which the first query translator modules apply and associating a plurality of second query translator modules with a second data store type to which the second query translator modules apply, wherein the first and second query translator modules for the first and second data store types include database specific operations to implement query optimization for the first and second data store types to which the first and second query translator modules respectively apply and include first and second resolve modules, respectively; receiving a query to query a target data store; determining whether the target data store is of the first data store type or the second data store type; determining from the module mapping the first query translators to use in response to determining that the target data store is of the first data store type and the second query translator modules to use in response to determining that the target data store is of the second data store type; generating a parse tree of nodes; grouping the nodes according to query parts to produce a query graph; forwarding the query graph to the first or second resolve module from the determined first or second query translator modules to validate that the query attributes are valid attributes in the target data store; and in response to validating the query parts, performing: using the first query translator modules to translate the received query to a query execution plan in response to determining that the target data store is of the first data store type; and using the second query translator modules to translate the received query to a query execution plan in response to determining that the target data store is of the second data store type. 2. The article of manufacture of claim 1 , wherein the first and second resolve modules perform different resolve validation operations specific to their data store type. | 0.754335 |
7,492,949 | 1 | 3 | 1. A process for semantically selecting a document template, comprising: (a) acquiring an input sentence, and (b) a processor for performing the following steps: looking up corresponding sentential proposition(s) to said sentence in a mapping table created by domain experts and, (c) looking up corresponding sentence(s) to said sentential proposition(s) in said mapping table and, (c) retrieving document templates from a template document collection that contain one or more of said sentences, Whereby a partial solution set of document templates for each said sentential proposition is returned. | 1. A process for semantically selecting a document template, comprising: (a) acquiring an input sentence, and (b) a processor for performing the following steps: looking up corresponding sentential proposition(s) to said sentence in a mapping table created by domain experts and, (c) looking up corresponding sentence(s) to said sentential proposition(s) in said mapping table and, (c) retrieving document templates from a template document collection that contain one or more of said sentences, Whereby a partial solution set of document templates for each said sentential proposition is returned. 3. The method according to claim 1 where the input sentence is acquired through a word processor. | 0.834471 |
9,811,321 | 19 | 20 | 19. The non-transitory computer-readable storage medium of claim 16 , wherein the first set of computer-executable instructions further cause the script chunking service to: calculate a second portion hash based at least in part on the second portion; retrieve, from a data store, one or more chunk hashes corresponding to chunks of computer-executable instructions; and determine that none of the one or more chunk hashes correspond to the second portion hash. | 19. The non-transitory computer-readable storage medium of claim 16 , wherein the first set of computer-executable instructions further cause the script chunking service to: calculate a second portion hash based at least in part on the second portion; retrieve, from a data store, one or more chunk hashes corresponding to chunks of computer-executable instructions; and determine that none of the one or more chunk hashes correspond to the second portion hash. 20. The non-transitory computer-readable storage medium of claim 19 , wherein the first set of computer-executable instructions further cause the script chunking service to: transmit, to a compiler, the second portion; and receive, from the compiler, the second chunk of computer-executable instructions. | 0.92607 |
8,868,403 | 9 | 10 | 9. A method of enabling disambiguation of an input into a handheld electronic device, the handheld electronic device including an input apparatus, an output apparatus, and a memory for storing a plurality of language objects, the handheld electronic device having a number of received messages available thereon, the method comprising: detecting a replying input with respect to a first received message of the number of received messages available on the handheld electronic device, the first received message having at least a sender; initiating a second message identifying the sender as a recipient of a number of recipients, and storing in the memory a first language object from the first received message, the first language object corresponding to the sender of the first received message; associating a frequency value with the first language object from the first received message; and outputting at least a portion of the first language object for the second message based on the associated frequency value. | 9. A method of enabling disambiguation of an input into a handheld electronic device, the handheld electronic device including an input apparatus, an output apparatus, and a memory for storing a plurality of language objects, the handheld electronic device having a number of received messages available thereon, the method comprising: detecting a replying input with respect to a first received message of the number of received messages available on the handheld electronic device, the first received message having at least a sender; initiating a second message identifying the sender as a recipient of a number of recipients, and storing in the memory a first language object from the first received message, the first language object corresponding to the sender of the first received message; associating a frequency value with the first language object from the first received message; and outputting at least a portion of the first language object for the second message based on the associated frequency value. 10. The method of claim 9 , wherein the outputting comprises: detecting an ambiguous input for the second message, the ambiguous input being at least a portion of a salutation of the second message; determining that the first language object stored in the memory corresponds with the ambiguous input for the second message; and outputting the at least a portion of the first language object as a first proposed disambiguation of the ambiguous input. | 0.501111 |
8,984,012 | 2 | 12 | 2. A system, comprising: one or more processors; one or more computer-storage media; and executable instructions stored on the one or more computer-storage media and executable by the one or more processors to receive a search query and generate an optimal list of search results in response, comprising: (1) a candidate generator that determines one or more candidate search queries, each comprising variant terms corresponding to search terms of the search query, (2) a probability generator to determine probabilities that including results stemming from searches of the one or more candidate search queries in the optimal list of search results will result in a user interaction with corresponding online resources, wherein the probabilities determined by the probability generator are based on interaction scores and candidate scores for the one or more candidate search queries, wherein the interaction scores are based on user interactions with at least one of the results stemming from the one or more candidate search queries, and wherein the candidate scores correspond to probabilities that the one or more candidate search queries are effective replacements for the search query, and (3) a blending module to determine the search results for the optimal list of search results based on the probabilities determined by the probability generator. | 2. A system, comprising: one or more processors; one or more computer-storage media; and executable instructions stored on the one or more computer-storage media and executable by the one or more processors to receive a search query and generate an optimal list of search results in response, comprising: (1) a candidate generator that determines one or more candidate search queries, each comprising variant terms corresponding to search terms of the search query, (2) a probability generator to determine probabilities that including results stemming from searches of the one or more candidate search queries in the optimal list of search results will result in a user interaction with corresponding online resources, wherein the probabilities determined by the probability generator are based on interaction scores and candidate scores for the one or more candidate search queries, wherein the interaction scores are based on user interactions with at least one of the results stemming from the one or more candidate search queries, and wherein the candidate scores correspond to probabilities that the one or more candidate search queries are effective replacements for the search query, and (3) a blending module to determine the search results for the optimal list of search results based on the probabilities determined by the probability generator. 12. The system of claim 2 , further comprising: a vertical module that generates a first set of candidate search queries refined to one or more verticals, the one or more verticals corresponding to media types comprising one or more of the following: an image, a video, and an audio file; and a geographic module that generates a second set of candidate search queries refined to a particular geographic location. | 0.581136 |
9,495,424 | 13 | 15 | 13. A computing device comprising: one or more processors; and a memory coupled to the one or more processors, the memory storing computer readable instructions that, when executed by the one or more processors, cause the one or more processors to: determine a user-defined parameter for named entity recognition, wherein the user-defined parameter comprises a beginning position and one of a length or an ending position to define a section of a written work on which the named entity recognition is to be performed, wherein an individual position or the length are measured in one of chapters, pages, paragraphs, or words; recognize, based at least in part on the user-defined parameter, one or more textual strings within the section of the written work, wherein a textual string of the one or more textual strings is associated with a named entity of a plurality of named entities within the section of the written work; calculate a significance value based at least in part on a number of the one or more textual strings; select a primary textual string from the one or more textual strings; and provide an ordered list of at least a portion of the plurality of named entities, wherein a position of the primary textual string within the ordered list is based at least in part on the significance value. | 13. A computing device comprising: one or more processors; and a memory coupled to the one or more processors, the memory storing computer readable instructions that, when executed by the one or more processors, cause the one or more processors to: determine a user-defined parameter for named entity recognition, wherein the user-defined parameter comprises a beginning position and one of a length or an ending position to define a section of a written work on which the named entity recognition is to be performed, wherein an individual position or the length are measured in one of chapters, pages, paragraphs, or words; recognize, based at least in part on the user-defined parameter, one or more textual strings within the section of the written work, wherein a textual string of the one or more textual strings is associated with a named entity of a plurality of named entities within the section of the written work; calculate a significance value based at least in part on a number of the one or more textual strings; select a primary textual string from the one or more textual strings; and provide an ordered list of at least a portion of the plurality of named entities, wherein a position of the primary textual string within the ordered list is based at least in part on the significance value. 15. The computing device of claim 13 , wherein the computer readable instructions further cause the one or more processors to provide the ordered list of the at least the portion of the plurality of named entities to a catalog that lists additional named entities associated with additional written works. | 0.669913 |
8,952,961 | 21 | 24 | 21. A method for servicing photon map queries, comprising: accepting photon queries from one or more code modules or shaders, each of the photon queries defining a spatially located volume and criteria for photons that are responsive to that photon query, at least some of the photon queries defining a locus and a number of photons (k) closest to the locus as the criteria, wherein k>=1; associating each of the accepted queries with a collection of photon queries that is associated with a node of an acceleration structure, the acceleration structure including nodes that respectively define surfaces that each spatially bound a respective selection of photons located in a 3-D scene, the selections of varying relative granularity, and the nodes arranged in a graph with edges connecting pairs of nodes; traversing the acceleration structure with collections of photon queries from the accepted photon queries, wherein the traversal is performed, collection-by-collection, by testing, in an acceleration structure resource comprising one or more processors, each of a plurality of child nodes of the node associated with a selected collection of photon queries for overlap with each of the spatially located volumes of the photon queries of that collection, and updating a status of collections maintained in a memory by referencing each photon query in a respective collection associated with each child node found to overlap with the spatially located volume of that photon query; and returning, for each of the photon queries, identifiers for photons satisfying the criteria specified for that photon query. | 21. A method for servicing photon map queries, comprising: accepting photon queries from one or more code modules or shaders, each of the photon queries defining a spatially located volume and criteria for photons that are responsive to that photon query, at least some of the photon queries defining a locus and a number of photons (k) closest to the locus as the criteria, wherein k>=1; associating each of the accepted queries with a collection of photon queries that is associated with a node of an acceleration structure, the acceleration structure including nodes that respectively define surfaces that each spatially bound a respective selection of photons located in a 3-D scene, the selections of varying relative granularity, and the nodes arranged in a graph with edges connecting pairs of nodes; traversing the acceleration structure with collections of photon queries from the accepted photon queries, wherein the traversal is performed, collection-by-collection, by testing, in an acceleration structure resource comprising one or more processors, each of a plurality of child nodes of the node associated with a selected collection of photon queries for overlap with each of the spatially located volumes of the photon queries of that collection, and updating a status of collections maintained in a memory by referencing each photon query in a respective collection associated with each child node found to overlap with the spatially located volume of that photon query; and returning, for each of the photon queries, identifiers for photons satisfying the criteria specified for that photon query. 24. The method of claim 21 for servicing photon map queries, further comprising producing a respective identifier for each photon query, and using the identifiers to reference the photon queries in the collections of photon queries. | 0.864802 |
7,475,145 | 5 | 6 | 5. A method for dynamically invoking a Web service comprising the steps of: assembling a collection of references to remote implementations of the Web service based upon a common port type; identifying a plurality of ports bound to said remote implementations of the Web service; applying a set of port selection rules to said identified ports to select a particular one of said ports; and, invoking the Web service through said selected port. | 5. A method for dynamically invoking a Web service comprising the steps of: assembling a collection of references to remote implementations of the Web service based upon a common port type; identifying a plurality of ports bound to said remote implementations of the Web service; applying a set of port selection rules to said identified ports to select a particular one of said ports; and, invoking the Web service through said selected port. 6. The method of claim 5 , wherein said identifying step comprises the step of parsing a Web service implementation document for each referenced remote implementation in said collection, said parsing producing a list of ports through which said remote implementations can be invoked. | 0.760575 |
8,874,443 | 17 | 18 | 17. The method of claim 12 further comprising performing a generalization process to obtain sentence templates as a back-off model to enable processing of units in a sentence that come from either a phrase or a sentence uttered by the first user; wherein the generalization process identifies constraint-sets present in the past conversation sessions but having different values, and wherein the back-off model utilizes the lexicalized constraints to align system variability due to the different values, with the original phrase data. | 17. The method of claim 12 further comprising performing a generalization process to obtain sentence templates as a back-off model to enable processing of units in a sentence that come from either a phrase or a sentence uttered by the first user; wherein the generalization process identifies constraint-sets present in the past conversation sessions but having different values, and wherein the back-off model utilizes the lexicalized constraints to align system variability due to the different values, with the original phrase data. 18. The method of claim 17 further comprising: utilizing a chunking-based approach to extract phrases used by the first user in a constraint specification; and updating the extracted phrases with values retrieved from the response database. | 0.932242 |
9,324,104 | 1 | 6 | 1. A computer-based recommendation system for generating recommendations of unique items, the recommendation system comprising: one or more computer readable storage devices configured to store: a plurality of computer executable instructions; an items information database containing data relating to a plurality of unique items; one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the plurality of computer executable instructions in order to cause the computer system to: receive an input from a user that comprises user-expressed preferences associated with the plurality of unique items; calculate a customization score for each unique item in the plurality of unique items, the customization score representing an estimated preference impact based on at least one customization attribute that may affect the user's preference for the unique item; calculate a condition score for each unique item in the plurality of unique items, the condition score representing an estimated preference impact based on at least one condition attribute that may affect the user's preference for the unique item; generate a dissimilarity penalty for each unique item in the plurality of unique items by combining the customization score and the condition score, the dissimilarity penalty at least partially generated based on a magnitude of dissimilarity between the unique item and the user-expressed preferences; and generate a recommendation of unique items by ranking at least a portion of the plurality of the unique items based at least partially on the calculated dissimilarity penalties. | 1. A computer-based recommendation system for generating recommendations of unique items, the recommendation system comprising: one or more computer readable storage devices configured to store: a plurality of computer executable instructions; an items information database containing data relating to a plurality of unique items; one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the plurality of computer executable instructions in order to cause the computer system to: receive an input from a user that comprises user-expressed preferences associated with the plurality of unique items; calculate a customization score for each unique item in the plurality of unique items, the customization score representing an estimated preference impact based on at least one customization attribute that may affect the user's preference for the unique item; calculate a condition score for each unique item in the plurality of unique items, the condition score representing an estimated preference impact based on at least one condition attribute that may affect the user's preference for the unique item; generate a dissimilarity penalty for each unique item in the plurality of unique items by combining the customization score and the condition score, the dissimilarity penalty at least partially generated based on a magnitude of dissimilarity between the unique item and the user-expressed preferences; and generate a recommendation of unique items by ranking at least a portion of the plurality of the unique items based at least partially on the calculated dissimilarity penalties. 6. The computer-based recommendation system of claim 1 , wherein the at least one customization attribute describes at least one of the following: an engine size, a type of material used for an interior of an automobile, a color of an automobile. | 0.814199 |
9,361,293 | 1 | 5 | 1. A method, in a data processing system comprising a processor and a memory, for generating a lexical resource for linguistic analysis, the method comprising: receiving, by the data processing system, a document data structure comprising a renaming directive in natural language textual content of the document data structure, wherein the renaming directive is a statement that specifies a correspondence between a full expression and a moniker that is stand-in text for the full expression; applying, by the data processing system, filter logic to the document data structure to identify the renaming directive within the natural language textual content of the document data structure; analyzing, by the data processing system, the renaming directive to identify a relationship between semantic concepts represented by the renaming directive that are to be used to update a lexical resource based on the renaming directive; updating, by the data processing system, the lexical resource based on results of analyzing the renaming directive; and outputting, by the data processing system, the updated lexical resource to a linguistic analysis system, wherein the linguistic analysis system performs linguistic analysis of a portion of textual content based on the updated lexical resource. | 1. A method, in a data processing system comprising a processor and a memory, for generating a lexical resource for linguistic analysis, the method comprising: receiving, by the data processing system, a document data structure comprising a renaming directive in natural language textual content of the document data structure, wherein the renaming directive is a statement that specifies a correspondence between a full expression and a moniker that is stand-in text for the full expression; applying, by the data processing system, filter logic to the document data structure to identify the renaming directive within the natural language textual content of the document data structure; analyzing, by the data processing system, the renaming directive to identify a relationship between semantic concepts represented by the renaming directive that are to be used to update a lexical resource based on the renaming directive; updating, by the data processing system, the lexical resource based on results of analyzing the renaming directive; and outputting, by the data processing system, the updated lexical resource to a linguistic analysis system, wherein the linguistic analysis system performs linguistic analysis of a portion of textual content based on the updated lexical resource. 5. The method of claim 1 , wherein the filter logic comprises patterns or rules for identifying a full expression and a moniker that refers to the full expression. | 0.744514 |
9,672,381 | 15 | 19 | 15. A non-transitory computer-readable medium having computer-executable instructions for execution by at least one processor, that, when executed, cause the at least one processor to: receive a privacy preference specification relative to an indication of at least one user identity of a plurality of user identities for a single user; and generate at least one privacy preference relative to the at least one indication of at least one user identity; associate the at least one privacy preference to at least one information card; wherein the at least one information card is related to the one or more of the selected user identities; and retrieve and determine which of the at least one information card satisfy identity requirements of a security policy, enables the user to select one of the at least one information card determined to satisfy the security policy, and requests an issuance of a security token in reference to the at least one information card selected by the user. | 15. A non-transitory computer-readable medium having computer-executable instructions for execution by at least one processor, that, when executed, cause the at least one processor to: receive a privacy preference specification relative to an indication of at least one user identity of a plurality of user identities for a single user; and generate at least one privacy preference relative to the at least one indication of at least one user identity; associate the at least one privacy preference to at least one information card; wherein the at least one information card is related to the one or more of the selected user identities; and retrieve and determine which of the at least one information card satisfy identity requirements of a security policy, enables the user to select one of the at least one information card determined to satisfy the security policy, and requests an issuance of a security token in reference to the at least one information card selected by the user. 19. The non-transitory computer-readable medium of claim 15 , wherein each user identity having a respective plurality of user identity attributes wherein the privacy preference indicates how the privacy of at least one user attribute of at least one of the plurality of user identity attributes is treated when the at least one user attribute is provided to a third party. | 0.680651 |
7,809,568 | 1 | 8 | 1. A method of indexing a spoken document comprising speech data and text meta-data, the method comprising: using a processor to generate information pertaining to recognized speech from the speech data, the recognized speech comprising a sequence of textual words, the information comprising probabilities utilizing both a sum of length based probabilities and a word position probability to determine the words in the first sequence of words in the recognized speech and a position of each of the words in the first sequence of words; using the processor to generate information pertaining to a second sequence of words in the text meta-data the text meta-data comprising a sequence of textual words, the information including at least positional information of a position of each of the words in the second sequence of words in the text meta-data with the same format as the positional information of the position of each of the words in the first sequence of words in the recognized speech; using the processor to build an index based on processing text and the information pertaining to recognized speech including both the sum of length based probabilities and the word position probability and the information pertaining to the text meta-data wherein the index comprises position specific posterior lattices and wherein the position specific probability equals one for the text meta-data; using the processor to output the index. | 1. A method of indexing a spoken document comprising speech data and text meta-data, the method comprising: using a processor to generate information pertaining to recognized speech from the speech data, the recognized speech comprising a sequence of textual words, the information comprising probabilities utilizing both a sum of length based probabilities and a word position probability to determine the words in the first sequence of words in the recognized speech and a position of each of the words in the first sequence of words; using the processor to generate information pertaining to a second sequence of words in the text meta-data the text meta-data comprising a sequence of textual words, the information including at least positional information of a position of each of the words in the second sequence of words in the text meta-data with the same format as the positional information of the position of each of the words in the first sequence of words in the recognized speech; using the processor to build an index based on processing text and the information pertaining to recognized speech including both the sum of length based probabilities and the word position probability and the information pertaining to the text meta-data wherein the index comprises position specific posterior lattices and wherein the position specific probability equals one for the text meta-data; using the processor to output the index. 8. The method of claim 1 wherein generating information pertaining to recognized speech from the speech data includes identifying at least two alternative speech unit sequences based on the same portion of speech data; and wherein building an index based on the information pertaining to recognized speech includes for each speech unit in the at least two alternative speech unit sequences, placing information in an entry in the index that indicates a position of the speech unit in at least one of the two alternative speech unit sequences. | 0.500921 |
8,521,723 | 17 | 20 | 17. A method comprising: receiving a first query; transforming the first query, comprising an outer query that includes a selection of a subquery that (a) returns at most one row and (b) includes a first predicate that references a database object that is from the outer query and outside the subquery, to a second query that includes: a second predicate that corresponds to the first predicate, wherein the second predicate references an outer join, wherein the second query does not select any subquery having the first predicate or the second predicate, and wherein the second query is semantically equivalent to the first query; generating an execution plan for executing the second query instead of the first query; wherein the method is performed by one or more computing devices. | 17. A method comprising: receiving a first query; transforming the first query, comprising an outer query that includes a selection of a subquery that (a) returns at most one row and (b) includes a first predicate that references a database object that is from the outer query and outside the subquery, to a second query that includes: a second predicate that corresponds to the first predicate, wherein the second predicate references an outer join, wherein the second query does not select any subquery having the first predicate or the second predicate, and wherein the second query is semantically equivalent to the first query; generating an execution plan for executing the second query instead of the first query; wherein the method is performed by one or more computing devices. 20. The method of claim 17 , wherein the subquery includes an aggregation operator, wherein transforming the first query to the second query comprises adding a view, wherein the view includes an added GROUP BY clause, and wherein the second predicate references the view. | 0.720619 |
9,411,713 | 4 | 6 | 4. The non-transitory computer-readable recording medium according to claim 1 , the process further comprising: displaying a necessity of the first requirement together with the degree of difficulty. | 4. The non-transitory computer-readable recording medium according to claim 1 , the process further comprising: displaying a necessity of the first requirement together with the degree of difficulty. 6. The non-transitory computer-readable recording medium according to claim 4 , wherein a relation between the degree of difficulty and the necessity is displayed in graph form. | 0.95 |
7,523,076 | 2 | 3 | 2. The method of claim 1 , further comprising: obtaining a measured diffraction signal from an optical metrology device; and analyzing the simulated diffraction signal and the measured diffraction signal. | 2. The method of claim 1 , further comprising: obtaining a measured diffraction signal from an optical metrology device; and analyzing the simulated diffraction signal and the measured diffraction signal. 3. The method of claim 2 , wherein the one or more termination criteria includes a cost function value determined based on the analysis of the simulated and measured diffraction signals. | 0.926014 |
8,774,392 | 11 | 15 | 11. A computer-implemented method for processing calls in a call center, comprising: receiving within a call center, a call comprising an inquiry from a caller; assigning the call to a human agent; executing via an automated voice response system, a script in response to the inquiry, wherein the script is selected by the human agent; altering a flow of the script via a sliding control that varies a level of participation by the automated voice response system and the human agent by receiving input from the human agent; and providing the altered script and input from the human agent as a response to the caller inquiry. | 11. A computer-implemented method for processing calls in a call center, comprising: receiving within a call center, a call comprising an inquiry from a caller; assigning the call to a human agent; executing via an automated voice response system, a script in response to the inquiry, wherein the script is selected by the human agent; altering a flow of the script via a sliding control that varies a level of participation by the automated voice response system and the human agent by receiving input from the human agent; and providing the altered script and input from the human agent as a response to the caller inquiry. 15. A method according to claim 11 , further comprising: selecting the human agent, comprising: determining all agents signed into the call center; and identifying one of the agents signed into the call center with availability to accept the call. | 0.690476 |
8,667,021 | 1 | 6 | 1. An intelligent system for retrieval and presentation of data to a user of an organization, comprising: a storage device that stores the data; an input device for the user to input at least one of a user initiated free-form inquiry and a user initiated structured inquiry; a computing device that receives the user initiated free-form inquiry and the user initiated structured inquiry, the computing device also structures a system initiated related knowledge search that is related to the free-form inquiry, wherein the related knowledge search is based upon sensory information, the sensory information including information associated with the user, a behavior of the user, a role of the user within the organization, previous free-form inquiries and previous structured inquiries by the user, wherein the related knowledge search is associated with, but not the same as, the free-form inquiry; and displaying the results of the user initiated free-form inquiry, the user initiated structured inquiry and the related knowledge search to a display device. | 1. An intelligent system for retrieval and presentation of data to a user of an organization, comprising: a storage device that stores the data; an input device for the user to input at least one of a user initiated free-form inquiry and a user initiated structured inquiry; a computing device that receives the user initiated free-form inquiry and the user initiated structured inquiry, the computing device also structures a system initiated related knowledge search that is related to the free-form inquiry, wherein the related knowledge search is based upon sensory information, the sensory information including information associated with the user, a behavior of the user, a role of the user within the organization, previous free-form inquiries and previous structured inquiries by the user, wherein the related knowledge search is associated with, but not the same as, the free-form inquiry; and displaying the results of the user initiated free-form inquiry, the user initiated structured inquiry and the related knowledge search to a display device. 6. The intelligent system of claim 1 , wherein the related knowledge search is based upon previous behavior of the user. | 0.813084 |
7,783,474 | 1 | 4 | 1. A method in a computer system for adding phrase pronunciations to a language model, the method comprising steps of: receiving at least one phrase to be added to the language model, the at least one phrase comprising a first phrase, the first phrase comprising a plurality of tokens including a first token; generating, using the computer system, a phrase pronunciation for the first phrase comprising a token pronunciation for the first token in the first phrase, wherein generating the phrase pronunciation for the first phrase comprises determining if the first token is represented in a pron component list, and, if so, selecting as the token pronunciation for the first token in the first phrase a component pronunciation from the pron component list, wherein the pron component list comprises a list of one or more component pronunciations for at least the first token as pronounced in one or more phrases, wherein the list of one or more component pronunciations is different from any list of one or more language model pronunciations in the language model for the first token; and adding the phrase pronunciation for the first phrase to the language model; wherein the step of generating the phrase pronunciation for the first phrase further comprises; if the first token is not represented in the pron component list, determining if the first token is represented in the language model, and, if so, selecting a language model pronunciation from the language model as the token pronunciation for the first token in the first phrase. | 1. A method in a computer system for adding phrase pronunciations to a language model, the method comprising steps of: receiving at least one phrase to be added to the language model, the at least one phrase comprising a first phrase, the first phrase comprising a plurality of tokens including a first token; generating, using the computer system, a phrase pronunciation for the first phrase comprising a token pronunciation for the first token in the first phrase, wherein generating the phrase pronunciation for the first phrase comprises determining if the first token is represented in a pron component list, and, if so, selecting as the token pronunciation for the first token in the first phrase a component pronunciation from the pron component list, wherein the pron component list comprises a list of one or more component pronunciations for at least the first token as pronounced in one or more phrases, wherein the list of one or more component pronunciations is different from any list of one or more language model pronunciations in the language model for the first token; and adding the phrase pronunciation for the first phrase to the language model; wherein the step of generating the phrase pronunciation for the first phrase further comprises; if the first token is not represented in the pron component list, determining if the first token is represented in the language model, and, if so, selecting a language model pronunciation from the language model as the token pronunciation for the first token in the first phrase. 4. A method for adding phrase pronunciations to a language model, in accordance with claim 1 , wherein the first token is parsed from the first phrase based on word boundaries. | 0.779449 |
9,329,874 | 1 | 4 | 1. One or more computer-readable hardware memory devices comprising a module having instructions that are executable on a client to perform operations comprising: retrieving a menu document that specifies one or more menu items corresponding with one or more actions that are performable by the module to be represented in the user interface, wherein at least one action is associated with a behavior that specifies whether the at least one action is to be represented in the user interface; retrieving a separate string document that specifies one or more strings that are to be utilized to represent respective said actions, wherein the string document is configurable to allow a user to specify a user-defined, customized name, representing an action that is performable by the module, to be displayed; and generating a user interface having customizable elements comprising the one or more actions matched with the one or more strings, wherein a determination to output at least one customizable element is based on an associated behavior of a device that is to display the user interface, wherein the menu document and string document are each generated by a network operator that streams television content to the client. | 1. One or more computer-readable hardware memory devices comprising a module having instructions that are executable on a client to perform operations comprising: retrieving a menu document that specifies one or more menu items corresponding with one or more actions that are performable by the module to be represented in the user interface, wherein at least one action is associated with a behavior that specifies whether the at least one action is to be represented in the user interface; retrieving a separate string document that specifies one or more strings that are to be utilized to represent respective said actions, wherein the string document is configurable to allow a user to specify a user-defined, customized name, representing an action that is performable by the module, to be displayed; and generating a user interface having customizable elements comprising the one or more actions matched with the one or more strings, wherein a determination to output at least one customizable element is based on an associated behavior of a device that is to display the user interface, wherein the menu document and string document are each generated by a network operator that streams television content to the client. 4. One or more computer-readable hardware memory devices as described in claim 1 , wherein the menu document and the string document use extensible markup language (XML). | 0.595238 |
8,977,952 | 1 | 9 | 1. A method of maintaining annotations across versions of an electronic book comprising: receiving at an access device a version of an electronic book and a signal instructing the access device to correlate a set of annotations associated with a different version of the electronic book with the received version of the electronic book, the received and different versions of the electronic books each including at least one document file, wherein each annotation in the set of annotations includes a document file indicator corresponding to the at least one document file with which the annotation is associated; using the document file indicator to compare each annotation of the set of annotations with the received version of the electronic book in order to determine where the annotation should be inserted into the received version of the electronic book, wherein if the received version of the electronic book does not include a document file indicator that matches a document file indicator of the different version of the electronic book, the annotation associated with the document file indicator of the different version is inserted at the beginning of the received version of the electronic book; and, inserting each annotation of the set of annotations into a location of the received version based on the comparing. | 1. A method of maintaining annotations across versions of an electronic book comprising: receiving at an access device a version of an electronic book and a signal instructing the access device to correlate a set of annotations associated with a different version of the electronic book with the received version of the electronic book, the received and different versions of the electronic books each including at least one document file, wherein each annotation in the set of annotations includes a document file indicator corresponding to the at least one document file with which the annotation is associated; using the document file indicator to compare each annotation of the set of annotations with the received version of the electronic book in order to determine where the annotation should be inserted into the received version of the electronic book, wherein if the received version of the electronic book does not include a document file indicator that matches a document file indicator of the different version of the electronic book, the annotation associated with the document file indicator of the different version is inserted at the beginning of the received version of the electronic book; and, inserting each annotation of the set of annotations into a location of the received version based on the comparing. 9. The method of claim 1 , further comprising: storing the different version of the electronic book in memory of the access device. | 0.816011 |
9,911,052 | 1 | 8 | 1. A non-transitory computer readable medium having a computer readable program code embodied therein, said computer readable program code adapted to be executed to implement a method for providing handwriting recognition for superimposed stroke input, said method comprising: creating, with a segmentation expert, a segmentation graph based on a plurality of input strokes, at least two of the strokes being at least partially superimposed on one another, wherein the segmentation graph consists of nodes and paths corresponding to character hypotheses formed by segmenting the input strokes to take into account the at least partially superimposed strokes; assigning, with a recognition expert, a recognition score to each node of the segmentation graph based on language recognition information; generating, with a language expert, linguistic meaning of the input strokes by optimizing the recognition scores of the node paths of the segmentation graph based on a language model; and providing an output based on the collaborative analysis of the segmentation graph, the recognition score, and the language model by the segmentation, recognition and language experts. | 1. A non-transitory computer readable medium having a computer readable program code embodied therein, said computer readable program code adapted to be executed to implement a method for providing handwriting recognition for superimposed stroke input, said method comprising: creating, with a segmentation expert, a segmentation graph based on a plurality of input strokes, at least two of the strokes being at least partially superimposed on one another, wherein the segmentation graph consists of nodes and paths corresponding to character hypotheses formed by segmenting the input strokes to take into account the at least partially superimposed strokes; assigning, with a recognition expert, a recognition score to each node of the segmentation graph based on language recognition information; generating, with a language expert, linguistic meaning of the input strokes by optimizing the recognition scores of the node paths of the segmentation graph based on a language model; and providing an output based on the collaborative analysis of the segmentation graph, the recognition score, and the language model by the segmentation, recognition and language experts. 8. A non-transitory computer readable medium according to claim 1 , wherein the generation of the linguistic meaning includes recognizing word boundaries in the superimposed input based on the language model. | 0.502392 |
10,025,848 | 1 | 2 | 1. A communication device, comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: receiving, from a server, information associated with a voicemail message, wherein the information includes a transcript and a transcript index that are generated from the voicemail message, and wherein each respective word in the voicemail message is indexed relative to an occurrence in time of the respective word in the voicemail message to yield the transcript index; displaying, at a graphical user interface, the information associated with the voicemail message; receiving a selection of a portion of the information via the graphical user interface, wherein the selection of the portion of the information includes selection of a portion of the transcript; and transmitting the portion of the information to an intended recipient, wherein the portion of the information is identified based on the transcript index. | 1. A communication device, comprising: a processor; and a memory that stores executable instructions that, when executed by the processor, facilitate performance of operations, comprising: receiving, from a server, information associated with a voicemail message, wherein the information includes a transcript and a transcript index that are generated from the voicemail message, and wherein each respective word in the voicemail message is indexed relative to an occurrence in time of the respective word in the voicemail message to yield the transcript index; displaying, at a graphical user interface, the information associated with the voicemail message; receiving a selection of a portion of the information via the graphical user interface, wherein the selection of the portion of the information includes selection of a portion of the transcript; and transmitting the portion of the information to an intended recipient, wherein the portion of the information is identified based on the transcript index. 2. The communication device of claim 1 , wherein the processor comprises a plurality of processors operating in a distributed processing environment, and wherein the operations further comprise receiving a second selection of the intended recipient via the graphical user interface. | 0.680272 |
7,949,676 | 8 | 9 | 8. A computer readable storage medium encoded with a computer program that is operable with a data processing system for causing the data processing system to execute: first processing for inputting a natural language sentence and performing morpheme analysis on the natural language sentence; second processing for performing syntactic analysis on the natural language sentence after morpheme analysis and further performing semantic analysis on the natural language sentence; and third processing for converting the natural language sentence after syntactic analysis and semantic analysis into an inquiry sentence described in an ontology description language by referring to a case frame ontology dictionary in which are stored information indicating to which property in an ontology does a relationship among a predicate, a subject and an object in the natural language sentence correspond, wherein said third processing includes: processing for examining, on the basis of said case frame ontology dictionary, a property to which a predicate of said natural language sentence processed by the syntactic analysis and the semantic analysis corresponds and a case frame to which the natural language sentence corresponds; and processing for generating said inquiry sentence by describing the obtained property and case frame in said ontology description language. | 8. A computer readable storage medium encoded with a computer program that is operable with a data processing system for causing the data processing system to execute: first processing for inputting a natural language sentence and performing morpheme analysis on the natural language sentence; second processing for performing syntactic analysis on the natural language sentence after morpheme analysis and further performing semantic analysis on the natural language sentence; and third processing for converting the natural language sentence after syntactic analysis and semantic analysis into an inquiry sentence described in an ontology description language by referring to a case frame ontology dictionary in which are stored information indicating to which property in an ontology does a relationship among a predicate, a subject and an object in the natural language sentence correspond, wherein said third processing includes: processing for examining, on the basis of said case frame ontology dictionary, a property to which a predicate of said natural language sentence processed by the syntactic analysis and the semantic analysis corresponds and a case frame to which the natural language sentence corresponds; and processing for generating said inquiry sentence by describing the obtained property and case frame in said ontology description language. 9. The computer readable storage medium encoded with the computer program according to claim 8 , wherein, in said second processing, the computer is made to execute processing for decomposing the natural language sentence according to dependence relationships between single words of said natural language sentence based on a case frame defined in correspondence with the ontology. | 0.681438 |
8,150,924 | 4 | 6 | 4. The method of claim 1 , wherein the first display information includes information enabling the client system to display as part of the user interface, a plurality of respective label affordances for respective labels, wherein each respective label affordance is configured to, in response to selection of the respective label affordance, cause a respective predefined request for conversations having messages associated with the respective label to be transmitted from the client system to the server system. | 4. The method of claim 1 , wherein the first display information includes information enabling the client system to display as part of the user interface, a plurality of respective label affordances for respective labels, wherein each respective label affordance is configured to, in response to selection of the respective label affordance, cause a respective predefined request for conversations having messages associated with the respective label to be transmitted from the client system to the server system. 6. The method of claim 4 , wherein the plurality of respective label affordances includes a second label affordance associated with a second predefined request for messages associated with a second label, and the method further comprises: after sending the first display information to the client system, receiving the second predefined request from the client system; and in response to the second predefined request: producing a second list of conversations in accordance with a criterion that all conversations in the second list of conversations include at least one message associated with the second label, wherein a plurality of the conversations in the second list each include a plurality of messages; and sending, to the client system, third display information enabling the client system to display the second list of conversations. | 0.790819 |
9,563,627 | 21 | 22 | 21. The method of claim 5 , wherein the type of device employed to select the embedded video link includes one of a smart phone and a tablet, and the content serving webpage serves a mobile version of the webpage. | 21. The method of claim 5 , wherein the type of device employed to select the embedded video link includes one of a smart phone and a tablet, and the content serving webpage serves a mobile version of the webpage. 22. The method of claim 21 , wherein the mobile version of the webpage includes playing the first video using an application installed on the smart phone or tablet and the post-play section recommends the third video within the application. | 0.938017 |
9,658,735 | 3 | 4 | 3. The system of claim 1 , wherein the aspects of the user interface pertain to one or more of a language syntax of the user interface, the language syntax including any of grammar, spelling, usage, punctuation, and style; security; and layout. | 3. The system of claim 1 , wherein the aspects of the user interface pertain to one or more of a language syntax of the user interface, the language syntax including any of grammar, spelling, usage, punctuation, and style; security; and layout. 4. The system of claim 3 , wherein one or more of the aspects of the user interface pertain to tool tips provided with one or more fields of the user interface. | 0.975324 |
7,606,785 | 22 | 23 | 22. An apparatus for generating a knowledge system, comprising: one or more processors; a memory; connected to the processors by a bus; and one or more stored sequences of instructions which, when executed by the one or more processors, cause the one or more processors to carry out the steps of: receiving a set of rules, specifying actions to be taken in response to finding specific types of input data and a format of an output t-box; receiving a first set of input information, in a format satisfying the rules; wherein the input information has sufficient structure to enable rules to be applied to the input information to determine individual fields therefrom; generating from the first set of input information and the set of rules a t-box comprising categories and relationships about categories, and an a-box comprising assertions of individual instances of the categories of the t-box, wherein the a-box is generated by applying the set of rules to the first set of input information, and wherein the t-box and the a-box are generated concurrently such that the a-box is generated while the t-box is being generated; generating a Web Ontology Language (“OWL”) database using the a-box and the t-box; and generating a knowledge base based on OWL statements of the OWL database. | 22. An apparatus for generating a knowledge system, comprising: one or more processors; a memory; connected to the processors by a bus; and one or more stored sequences of instructions which, when executed by the one or more processors, cause the one or more processors to carry out the steps of: receiving a set of rules, specifying actions to be taken in response to finding specific types of input data and a format of an output t-box; receiving a first set of input information, in a format satisfying the rules; wherein the input information has sufficient structure to enable rules to be applied to the input information to determine individual fields therefrom; generating from the first set of input information and the set of rules a t-box comprising categories and relationships about categories, and an a-box comprising assertions of individual instances of the categories of the t-box, wherein the a-box is generated by applying the set of rules to the first set of input information, and wherein the t-box and the a-box are generated concurrently such that the a-box is generated while the t-box is being generated; generating a Web Ontology Language (“OWL”) database using the a-box and the t-box; and generating a knowledge base based on OWL statements of the OWL database. 23. The apparatus of claim 22 , wherein the one or more stored sequences of instructions further comprise instructions for carrying out the steps of: receiving a second set of input information, the second set of input information differing from the first set of input information; and generating a revised t-box and a revised a-box based upon the second set of input information and the set of rules; wherein the revised t-box includes at least one category or relationship not present in the t-box and correlating to data in the revised a-box. | 0.630759 |
7,603,413 | 14 | 15 | 14. The computer program product of claim 1 wherein the questions change periodically. | 14. The computer program product of claim 1 wherein the questions change periodically. 15. The computer program product of claim 14 wherein the questions change on a nightly basis or a weekly basis. | 0.974876 |
9,613,263 | 11 | 12 | 11. The information handling device of claim 8 , wherein the instructions are further executable by the processor to receive at least one handwriting ink stroke adjacent to a machine input. | 11. The information handling device of claim 8 , wherein the instructions are further executable by the processor to receive at least one handwriting ink stroke adjacent to a machine input. 12. The information handling device of claim 11 , wherein the at least one grouping comprises the machine input and the at least one handwriting stroke adjacent to the machine input. | 0.948761 |
10,127,927 | 1 | 10 | 1. A method, comprising: receiving one or more speech samples, wherein the one or more speech samples are characterized by one or more emotions or speaking styles from one or more speakers; generating a set of training data by extracting one or more acoustic features from every frame of the one or more sample speeches; and generating a model from the set of training data, wherein the model identifies emotion or speaking style dependent information in the set of training data, wherein the model includes the application of a Probabilistic Linear Discriminant Analysis (PLDA) to identify an emotion related subspace. | 1. A method, comprising: receiving one or more speech samples, wherein the one or more speech samples are characterized by one or more emotions or speaking styles from one or more speakers; generating a set of training data by extracting one or more acoustic features from every frame of the one or more sample speeches; and generating a model from the set of training data, wherein the model identifies emotion or speaking style dependent information in the set of training data, wherein the model includes the application of a Probabilistic Linear Discriminant Analysis (PLDA) to identify an emotion related subspace. 10. The method of claim 1 , wherein generating a set of training data includes model adaptation for modelling the extracted acoustic features as a Gaussian Mixture Model (GMM) and representing the set of training data with GMM mean supervectors. | 0.83945 |
8,977,575 | 8 | 10 | 8. A system comprising: a computer implemented Bayesian diagnostic system, wherein the diagnostic system includes an inferencing engine and a conditional probability table stored on a non-transitory storage device that forms the basis for Bayesian inferences once the diagnostic system is trained, each inference including a diagnosis and associated probability of the diagnosis, wherein training the diagnostic system includes providing the diagnostic system with historical input data and a corresponding diagnosis to be derived from the historical input data and providing new input data having a predetermined diagnosis, wherein the diagnostic system generates a conditional probability table of a new diagnosis using the new input data; and a confidence generator stored on a non-transitory storage device to receive the inferences, and generate a confidence measure for each inference, wherein the confidence indicator is generated on a per-inference basis and wherein the confidence generator further generates a cumulative confidence measure for multiple per-inference confidence intervals, and wherein the diagnostic system is trained when the confidence indicator of the new diagnosis is greater than a predetermined threshold. | 8. A system comprising: a computer implemented Bayesian diagnostic system, wherein the diagnostic system includes an inferencing engine and a conditional probability table stored on a non-transitory storage device that forms the basis for Bayesian inferences once the diagnostic system is trained, each inference including a diagnosis and associated probability of the diagnosis, wherein training the diagnostic system includes providing the diagnostic system with historical input data and a corresponding diagnosis to be derived from the historical input data and providing new input data having a predetermined diagnosis, wherein the diagnostic system generates a conditional probability table of a new diagnosis using the new input data; and a confidence generator stored on a non-transitory storage device to receive the inferences, and generate a confidence measure for each inference, wherein the confidence indicator is generated on a per-inference basis and wherein the confidence generator further generates a cumulative confidence measure for multiple per-inference confidence intervals, and wherein the diagnostic system is trained when the confidence indicator of the new diagnosis is greater than a predetermined threshold. 10. The system of claim 8 wherein the confidence generator to generate the cumulative confidence measure for multiple inference confidence indicators included the confidence generator to generate the cumulative confidence measure, wherein given a set of failed tests T={T 1 , T 2 , . . . , T t }, the cumulative confidence measure is defined as: C k = 1 t ∑ j = 0 t c kj for each component B k , where t is the number of tests that failed, and c kj is the confidence level of B k with respect to test T j . | 0.500978 |
10,146,766 | 18 | 19 | 18. The computer-implemented method according to claim 17 , wherein the receiving identity information during the second transaction comprises: receiving input data associated with the second transaction; generating one or more suggested first text portions based on the input data; outputting at least one of the suggested first text portions; and receiving an indication of a selection of a first text portion. | 18. The computer-implemented method according to claim 17 , wherein the receiving identity information during the second transaction comprises: receiving input data associated with the second transaction; generating one or more suggested first text portions based on the input data; outputting at least one of the suggested first text portions; and receiving an indication of a selection of a first text portion. 19. The computer-implemented method according to claim 18 , wherein the receiving identity information during the second transaction further comprises: generating one or more suggested second text portions based on the input data; outputting at least one of the suggested second text portions; receiving an indication of a selection of a second text portion; and generating a user identifier based on the selected first text portion and the selected second text portion. | 0.894808 |
8,290,950 | 9 | 10 | 9. The non-transitory computer readable storage medium of claim 8 , further comprising executable instructions to: extract the second language from the second target locale in response to failing to match the second target locale to the list of supplied locales; and identify the substitute locale within the list of supplied locales based on the total ordering of all of the supported locales, wherein the substitute locale includes the second language in response to the list of supplied locales includes at least one locale with the second language. | 9. The non-transitory computer readable storage medium of claim 8 , further comprising executable instructions to: extract the second language from the second target locale in response to failing to match the second target locale to the list of supplied locales; and identify the substitute locale within the list of supplied locales based on the total ordering of all of the supported locales, wherein the substitute locale includes the second language in response to the list of supplied locales includes at least one locale with the second language. 10. The non-transitory computer readable storage medium of claim 9 , wherein the second target locale is a locale associated with at least one of a document, a report, a site, a group, and a division. | 0.932432 |
7,584,181 | 1 | 2 | 1. A computer-readable storage medium having stored and encoded thereon computer-executable instructions for performing on a computing device an enhanced local search of web sites and intranets by mining user access logs, comprising: segmenting the user access log into different browsing sessions; generating ordered pairs of pages from the browsing sessions to find implicit links by using a gliding window to move over explicit paths of the browsing sessions to generate the ordered pairs of pages; determining a frequency of each of the ordered pairs; defining a minimum support threshold; applying the minimum support threshold to the frequency of each of the ordered pairs; filtering the ordered pairs to remove any ordered pairs that are infrequently occurring; constructing an implicit links graph from the implicit links; generating two-item sequential patterns from the ordered pairs; updating the implicit links graph using the two-item sequential patterns; re-ranking search results obtained from a search engine to enhance the local searching to produce updated search results; and displaying the updated search results to a user. | 1. A computer-readable storage medium having stored and encoded thereon computer-executable instructions for performing on a computing device an enhanced local search of web sites and intranets by mining user access logs, comprising: segmenting the user access log into different browsing sessions; generating ordered pairs of pages from the browsing sessions to find implicit links by using a gliding window to move over explicit paths of the browsing sessions to generate the ordered pairs of pages; determining a frequency of each of the ordered pairs; defining a minimum support threshold; applying the minimum support threshold to the frequency of each of the ordered pairs; filtering the ordered pairs to remove any ordered pairs that are infrequently occurring; constructing an implicit links graph from the implicit links; generating two-item sequential patterns from the ordered pairs; updating the implicit links graph using the two-item sequential patterns; re-ranking search results obtained from a search engine to enhance the local searching to produce updated search results; and displaying the updated search results to a user. 2. The computer-readable storage medium of claim 1 , further comprising pre-processing the user access log using at least one of: (a) data cleaning; (b) browsing session identification; (c) consecutive repetition elimination. | 0.502212 |
7,856,446 | 9 | 10 | 9. The method of claim 1 , the observing step further, comprising: observing an implicit user action taken on an asset to enable easy, efficient future recovery of, and reference to the asset by the user; and based upon the observing, detecting a virtual bookmark. | 9. The method of claim 1 , the observing step further, comprising: observing an implicit user action taken on an asset to enable easy, efficient future recovery of, and reference to the asset by the user; and based upon the observing, detecting a virtual bookmark. 10. The method of claim 9 , further comprising: considering an asset left open in “a user display foreground or background for a significant period of time to be virtually bookmarked. | 0.948159 |
7,645,294 | 4 | 5 | 4. The spinal fixation system of claim 3 , wherein the connecting plate defines an opening at an end and a spanning portion extending from the end, and wherein the set screw or the cap extend through the opening when the connecting plate is fixed to the bone anchor. | 4. The spinal fixation system of claim 3 , wherein the connecting plate defines an opening at an end and a spanning portion extending from the end, and wherein the set screw or the cap extend through the opening when the connecting plate is fixed to the bone anchor. 5. The spinal fixation system of claim 4 , wherein the connecting plate includes a buttress at a distal side of the spanning portion. | 0.923739 |
7,580,931 | 9 | 14 | 9. A computer-readable storage device containing instructions for controlling a computer system to identify web pages for a search result for a query, the web pages being organized into web sites, the web pages of a web site being hierarchically organized wherein the web pages of the web site have ancestor/descendant relationships, each web page of a web site being a root web page of a subsite of the web site, a subsite includes the root web page of the subsite and its descendant web pages, each web page having a feature, comprising: receiving from a user a query; identifying web pages that are related to the received query; and for each identified web page, calculating a subsite feature for the subsite with the identified web page being the root web page of the subsite based on a contribution from the feature of the identified web page and a contribution from the features of the descendant web pages of the identified web page, such that the contribution of the features of a descendant web page decreases as an ancestral distance between the identified web page and the descendant web page increases; and determining relevance of the identified web page to the query based on the calculated subsite feature of the subsite; and presenting to the user an indication of the identified web pages in an order that is based at least in part on the determined relevance of the identified web pages wherein the subsite feature is represented by the following: F [ S ( p s ) ] = α ( 0 ) f ( p s ) + 1 R ( p s ) ∑ u = 1 h ( p s ) - 1 [ α ( u ) ∑ p i 1 ∈ R ( p s ) ∑ p i 2 ∈ R ( p i 1 ) ⋯ ∑ p i u ∈ R ( p i u - 1 ) f ( p i u ) ∏ k = 1 u R ( p i k ) ] where F[S(p s )] represents the feature of the subsites with root web page p s , h(p s ) represents height of a subtree with the root web page of p s , R(p s ) represents the child documents of p s , ∥a∥ represents the number of elements of a, f(p iu ) represents the feature of web page p iu , and where α is represented as follows:
α( Δl )=λ Δl where Δl represents the ancestral distance between the root web page and a descendant web page and λ represents a parameter to control the amount of decrease. | 9. A computer-readable storage device containing instructions for controlling a computer system to identify web pages for a search result for a query, the web pages being organized into web sites, the web pages of a web site being hierarchically organized wherein the web pages of the web site have ancestor/descendant relationships, each web page of a web site being a root web page of a subsite of the web site, a subsite includes the root web page of the subsite and its descendant web pages, each web page having a feature, comprising: receiving from a user a query; identifying web pages that are related to the received query; and for each identified web page, calculating a subsite feature for the subsite with the identified web page being the root web page of the subsite based on a contribution from the feature of the identified web page and a contribution from the features of the descendant web pages of the identified web page, such that the contribution of the features of a descendant web page decreases as an ancestral distance between the identified web page and the descendant web page increases; and determining relevance of the identified web page to the query based on the calculated subsite feature of the subsite; and presenting to the user an indication of the identified web pages in an order that is based at least in part on the determined relevance of the identified web pages wherein the subsite feature is represented by the following: F [ S ( p s ) ] = α ( 0 ) f ( p s ) + 1 R ( p s ) ∑ u = 1 h ( p s ) - 1 [ α ( u ) ∑ p i 1 ∈ R ( p s ) ∑ p i 2 ∈ R ( p i 1 ) ⋯ ∑ p i u ∈ R ( p i u - 1 ) f ( p i u ) ∏ k = 1 u R ( p i k ) ] where F[S(p s )] represents the feature of the subsites with root web page p s , h(p s ) represents height of a subtree with the root web page of p s , R(p s ) represents the child documents of p s , ∥a∥ represents the number of elements of a, f(p iu ) represents the feature of web page p iu , and where α is represented as follows:
α( Δl )=λ Δl where Δl represents the ancestral distance between the root web page and a descendant web page and λ represents a parameter to control the amount of decrease. 14. The computer-readable storage device of claim 9 wherein the subsite features are calculated based on initial search results of a query. | 0.748188 |
8,260,785 | 1 | 11 | 1. A computer implemented method comprising: at a computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: storing a plurality of objects in a fact repository, wherein the objects are associated with facts, each fact having one or more terms; modifying one or more of the facts in the fact repository, including automatically, without user intervention: establishing a list of object names of objects in the fact repository, wherein the list of object names is stored as a hash table; for a respective fact having multiple terms, comparing a respective phrase-identification metric for each of a plurality of different combinations of terms in the respective fact to identify one or more candidate phrases; checking at least a subset of the candidate phrases against the list of object names, wherein checking the candidate phrases against the list of object names includes determining, for each respective candidate phrase whether a hash of the respective candidate phrase collides with a value in the hash table; and for each fact in of a plurality of respective candidate phrases that match respective object names in the list of object names, constructing a respective search link for a respective fact corresponding to the respective candidate phrase, and storing the respective search link at a location associated with the respective fact in the fact repository, wherein selection of a representation of the respective search link invokes performance of a search query against the fact repository, the search query including one or more search criteria that include the respective object name corresponding to the respective candidate phrase; and after modifying the facts in the fact repository, in accordance with a determination that one or more predefined criteria have been met, automatically repeating, without user intervention, the steps of establishing a list of object names from a plurality of name facts, identifying candidate phrases, checking candidate phrases against the list of object names and constructing and storing search links in the fact repository. | 1. A computer implemented method comprising: at a computer system including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: storing a plurality of objects in a fact repository, wherein the objects are associated with facts, each fact having one or more terms; modifying one or more of the facts in the fact repository, including automatically, without user intervention: establishing a list of object names of objects in the fact repository, wherein the list of object names is stored as a hash table; for a respective fact having multiple terms, comparing a respective phrase-identification metric for each of a plurality of different combinations of terms in the respective fact to identify one or more candidate phrases; checking at least a subset of the candidate phrases against the list of object names, wherein checking the candidate phrases against the list of object names includes determining, for each respective candidate phrase whether a hash of the respective candidate phrase collides with a value in the hash table; and for each fact in of a plurality of respective candidate phrases that match respective object names in the list of object names, constructing a respective search link for a respective fact corresponding to the respective candidate phrase, and storing the respective search link at a location associated with the respective fact in the fact repository, wherein selection of a representation of the respective search link invokes performance of a search query against the fact repository, the search query including one or more search criteria that include the respective object name corresponding to the respective candidate phrase; and after modifying the facts in the fact repository, in accordance with a determination that one or more predefined criteria have been met, automatically repeating, without user intervention, the steps of establishing a list of object names from a plurality of name facts, identifying candidate phrases, checking candidate phrases against the list of object names and constructing and storing search links in the fact repository. 11. The method of claim 1 , wherein the one or more predefined criteria are met when a predetermined number of new facts in the fact repository have been created. | 0.881232 |
8,301,450 | 7 | 13 | 7. A method of dialogue speech recognition using topic domain detection, comprising: performing a forward search to create a word lattice based on a feature vector, which is extracted from an input voice signal, with reference to a global language model database, a pronunciation dictionary database and an acoustic model database, which have been previously established; detecting a topic domain during run-time of a speech recognition procedure from among one or more candidate topic domains, by inferring a topic based on meanings of vocabularies contained in the word lattice using information of the word lattice created as a result of the forward search; and performing a backward decoding relative to the detected topic domain with reference to a specific topic domain language model database, which has been previously established, thereby outputting a speech recognition result for an input voice signal in the form of a text, wherein, the detecting a topic domain further comprises determining whether one of the one or more candidate topic domains is the same as a topic domain which is the previous topic domain detected during run-time, relative to a previous output text obtained as a result of a previous backward decoding of a previous dialogue, using history information which includes the previous topic domain detected, wherein detecting the topic domain includes: removing stop words, which have no concern with the topic, among vocabularies forming the word lattice; calculating a distance for each of the one or more candidate topic domains based on the vocabularies contained in the word lattice by receiving the word lattice, in which the stop words have been removed, wherein the calculating the distance for each of the one or more candidate topic domains comprises receiving history information including the previous output text, to calculate the distance for each of the one or more candidate topic domains, and calculating the distance for each of the one or more candidate topic domains according to a plurality of probability factors, wherein for a first factor, a higher probability weight is given to a candidate topic domain if it is the same as the previous topic domain detected, and a lower probability weight is given to a candidate topic domain if it is different from the previous topic domain detected, for a second factor, a higher probability weight is given to a candidate topic domain in accordance with an increase in a frequency of topic words supporting the candidate topic domain among vocabularies forming the word lattice, and the first factor and second factor are obtained during run-time of the speech recognition procedure. | 7. A method of dialogue speech recognition using topic domain detection, comprising: performing a forward search to create a word lattice based on a feature vector, which is extracted from an input voice signal, with reference to a global language model database, a pronunciation dictionary database and an acoustic model database, which have been previously established; detecting a topic domain during run-time of a speech recognition procedure from among one or more candidate topic domains, by inferring a topic based on meanings of vocabularies contained in the word lattice using information of the word lattice created as a result of the forward search; and performing a backward decoding relative to the detected topic domain with reference to a specific topic domain language model database, which has been previously established, thereby outputting a speech recognition result for an input voice signal in the form of a text, wherein, the detecting a topic domain further comprises determining whether one of the one or more candidate topic domains is the same as a topic domain which is the previous topic domain detected during run-time, relative to a previous output text obtained as a result of a previous backward decoding of a previous dialogue, using history information which includes the previous topic domain detected, wherein detecting the topic domain includes: removing stop words, which have no concern with the topic, among vocabularies forming the word lattice; calculating a distance for each of the one or more candidate topic domains based on the vocabularies contained in the word lattice by receiving the word lattice, in which the stop words have been removed, wherein the calculating the distance for each of the one or more candidate topic domains comprises receiving history information including the previous output text, to calculate the distance for each of the one or more candidate topic domains, and calculating the distance for each of the one or more candidate topic domains according to a plurality of probability factors, wherein for a first factor, a higher probability weight is given to a candidate topic domain if it is the same as the previous topic domain detected, and a lower probability weight is given to a candidate topic domain if it is different from the previous topic domain detected, for a second factor, a higher probability weight is given to a candidate topic domain in accordance with an increase in a frequency of topic words supporting the candidate topic domain among vocabularies forming the word lattice, and the first factor and second factor are obtained during run-time of the speech recognition procedure. 13. The method of claim 7 , further comprising: storing and managing information, including information related to the topic domain of the output text which is output by the backward-decoding, and history information which includes the previous topic domain detected relative to the previous output text obtained as a result of the previous backward decoding of the previous dialogue. | 0.735901 |
8,051,061 | 14 | 16 | 14. A method for query suggestion performed by a processor executing computer-executable instructions stored on a memory device, the method comprising: receiving an input query in source language; providing a plurality of candidate queries in target language, at least part of the plurality of candidate queries in target language being selected from a query log of a search engine; evaluating the plurality of candidate queries in target language at least partly by deducing a monolingual similarity between the input query in source language and a translation of a respective candidate query from target language to source language; ranking the plurality of candidate queries in target language using a cross-lingual query similarity score, the cross-lingual query similarity score being based on a plurality of features and a weight of each feature in calculating the cross-lingual query similarity score; and from top ranking candidate queries in target language, suggesting a query in target language as a cross-lingual query at least partly based on click-through information of documents selected by users for the plurality of candidate queries in target language. | 14. A method for query suggestion performed by a processor executing computer-executable instructions stored on a memory device, the method comprising: receiving an input query in source language; providing a plurality of candidate queries in target language, at least part of the plurality of candidate queries in target language being selected from a query log of a search engine; evaluating the plurality of candidate queries in target language at least partly by deducing a monolingual similarity between the input query in source language and a translation of a respective candidate query from target language to source language; ranking the plurality of candidate queries in target language using a cross-lingual query similarity score, the cross-lingual query similarity score being based on a plurality of features and a weight of each feature in calculating the cross-lingual query similarity score; and from top ranking candidate queries in target language, suggesting a query in target language as a cross-lingual query at least partly based on click-through information of documents selected by users for the plurality of candidate queries in target language. 16. The method as recited in claim 14 , wherein the providing the plurality of candidate queries in target language comprises: ranking queries in the query log using a bidirectional translation probability derived from a parallel corpora of the source language and the target language; and selecting a set of top queries based on ranking result. | 0.696303 |
7,640,232 | 29 | 33 | 29. A search enhancement system implemented across a network, comprising: a search engine having access to a content source; an application module; at least one ratings service that is external to the application module, to the search engine, and to the content source, wherein the ratings service is accessible to the application module across the network, the ratings service comprising any of a secondary source and a supplementary source comprising rating information; a receipt at the application module from a user at a user terminal of a specification by the user of at least one of the ratings services; a receipt at the application module of a search query entered by the user at the user terminal, the search query comprising at least one search parameter specified by the user; a data query sent by the application module over the network, upon receipt of the specification by the user of the ratings services, to the user-specified ratings services; a receipt of rating information at the application module from at least one of the user-specified ratings services over the network in response to the sent data query, wherein the rating information is independently maintained by the at least one ratings service; a refined search provided through the application module, wherein the refinement comprises any of at the application module, using the received rating information from at least one of the user-specified ratings services in conjunction with the search parameters received from the user to perform the search at the search engine through retrieval of content from the content source, wherein search results received from the search engine at the application module comply with both the search parameters received from the user and the received rating information from the user-specified ratings services; performing the search at the search engine through retrieval of content from the content source with the search parameters received from the user and subsequently filtering search results received from the search engine at the application module with the received rating information from at least one of the user-specified ratings services, and performing the search at the search engine through retrieval of content from the content source with the search parameters received from the user and subsequently providing any of organizing and sorting of the search results received from the search engine at the application module with the received rating information from at least one of the user-specified ratings services; and a return of the results of the refined search from the application module to any of the user at the user terminal and a recipient at a recipient terminal, the recipient other than the user. | 29. A search enhancement system implemented across a network, comprising: a search engine having access to a content source; an application module; at least one ratings service that is external to the application module, to the search engine, and to the content source, wherein the ratings service is accessible to the application module across the network, the ratings service comprising any of a secondary source and a supplementary source comprising rating information; a receipt at the application module from a user at a user terminal of a specification by the user of at least one of the ratings services; a receipt at the application module of a search query entered by the user at the user terminal, the search query comprising at least one search parameter specified by the user; a data query sent by the application module over the network, upon receipt of the specification by the user of the ratings services, to the user-specified ratings services; a receipt of rating information at the application module from at least one of the user-specified ratings services over the network in response to the sent data query, wherein the rating information is independently maintained by the at least one ratings service; a refined search provided through the application module, wherein the refinement comprises any of at the application module, using the received rating information from at least one of the user-specified ratings services in conjunction with the search parameters received from the user to perform the search at the search engine through retrieval of content from the content source, wherein search results received from the search engine at the application module comply with both the search parameters received from the user and the received rating information from the user-specified ratings services; performing the search at the search engine through retrieval of content from the content source with the search parameters received from the user and subsequently filtering search results received from the search engine at the application module with the received rating information from at least one of the user-specified ratings services, and performing the search at the search engine through retrieval of content from the content source with the search parameters received from the user and subsequently providing any of organizing and sorting of the search results received from the search engine at the application module with the received rating information from at least one of the user-specified ratings services; and a return of the results of the refined search from the application module to any of the user at the user terminal and a recipient at a recipient terminal, the recipient other than the user. 33. The system of claim 29 , wherein the results of the refined search are returned to the recipient other than the user, and wherein the recipient is based on the results of the refined search. | 0.7657 |
9,990,639 | 1 | 17 | 1. A system for rental fraud detection, comprising: an input interface configured to: receive a set of training data, wherein the set of training data comprises a set of rental fraud indications; and receive a set of prediction data; a feature vector extractor configured to: extract a first training set of feature vectors from the set of training data, wherein the set of training data comprises real estate listings determined to be not fraudulent and real estate listings determined to be fraudulent; and extract a first test feature vector from the set of prediction data, wherein the set of prediction data comprises one or more real estate listings of undetermined fraudulence; a model builder configured to: build a first model using the first training set of feature vectors and the rental fraud indications; and a predictor configured to: predict whether the first test feature vector corresponds to fraudulent data using the first model. | 1. A system for rental fraud detection, comprising: an input interface configured to: receive a set of training data, wherein the set of training data comprises a set of rental fraud indications; and receive a set of prediction data; a feature vector extractor configured to: extract a first training set of feature vectors from the set of training data, wherein the set of training data comprises real estate listings determined to be not fraudulent and real estate listings determined to be fraudulent; and extract a first test feature vector from the set of prediction data, wherein the set of prediction data comprises one or more real estate listings of undetermined fraudulence; a model builder configured to: build a first model using the first training set of feature vectors and the rental fraud indications; and a predictor configured to: predict whether the first test feature vector corresponds to fraudulent data using the first model. 17. The system of claim 1 , wherein a feature of the first test feature vector comprises a property lister attribute. | 0.760246 |
9,268,873 | 1 | 5 | 1. A method for providing a search index, comprising: identifying a landing page uniform resource locator (URL) from among a plurality of mobile web page URLs that correspond to a plurality of mobile web pages accessible with a limited capability browser application of a limited capability computing device; associating the landing page URL with a web host based at least in part on a token determined from the landing page URL, wherein the web host includes web pages, the web pages being accessible with a browser application of a general purpose computing device but not accessible with a limited capability browser application of a limited capability mobile device; associating the landing page URL with a web category based at least in part on the web host, wherein the web category identifies a content topic shared by web pages, the web pages being accessible with a browser application of a general purpose computing device but not accessible with a limited capability browser application of a limited capability mobile device; and providing the landing page URL, the token, information associated with the web host, and the category to a search index that is used to associate a search term with the landing page URL based at least in part on at least one of the token, the web host, or the category. | 1. A method for providing a search index, comprising: identifying a landing page uniform resource locator (URL) from among a plurality of mobile web page URLs that correspond to a plurality of mobile web pages accessible with a limited capability browser application of a limited capability computing device; associating the landing page URL with a web host based at least in part on a token determined from the landing page URL, wherein the web host includes web pages, the web pages being accessible with a browser application of a general purpose computing device but not accessible with a limited capability browser application of a limited capability mobile device; associating the landing page URL with a web category based at least in part on the web host, wherein the web category identifies a content topic shared by web pages, the web pages being accessible with a browser application of a general purpose computing device but not accessible with a limited capability browser application of a limited capability mobile device; and providing the landing page URL, the token, information associated with the web host, and the category to a search index that is used to associate a search term with the landing page URL based at least in part on at least one of the token, the web host, or the category. 5. The method of claim 1 , wherein the landing page URL and the web host are associated with a same domain. | 0.947187 |
9,583,100 | 1 | 5 | 1. A method of providing hands-free services using a mobile device having wireless access to computer-based services, the method comprising the steps of: (a) receiving speech in a vehicle from a vehicle occupant using an audio user interface that is separate from the mobile device, wherein the audio user interface is communicatively linked directly to the mobile device via a short-range wireless connection; (b) recording the speech using the mobile device; (c) transmitting the recorded speech from the mobile device to a cloud speech service; (d) receiving automatic speech recognition (ASR) results from the cloud speech service at the mobile device; (e) determining that the received ASR results at the mobile device contain one or more error conditions; (f) obtaining a local speech recognition result, in response to the determination in step (e), by performing speech recognition on the speech received at the vehicle using a speech recognition resource that includes vehicle-related and/or user-related data that was not used by the cloud speech service in generating the ASR results; and (g) providing the local speech recognition result to the cloud speech service for use in improving subsequent recognition by the cloud speech service, wherein the local speech recognition result addresses the determined one or more error conditions. | 1. A method of providing hands-free services using a mobile device having wireless access to computer-based services, the method comprising the steps of: (a) receiving speech in a vehicle from a vehicle occupant using an audio user interface that is separate from the mobile device, wherein the audio user interface is communicatively linked directly to the mobile device via a short-range wireless connection; (b) recording the speech using the mobile device; (c) transmitting the recorded speech from the mobile device to a cloud speech service; (d) receiving automatic speech recognition (ASR) results from the cloud speech service at the mobile device; (e) determining that the received ASR results at the mobile device contain one or more error conditions; (f) obtaining a local speech recognition result, in response to the determination in step (e), by performing speech recognition on the speech received at the vehicle using a speech recognition resource that includes vehicle-related and/or user-related data that was not used by the cloud speech service in generating the ASR results; and (g) providing the local speech recognition result to the cloud speech service for use in improving subsequent recognition by the cloud speech service, wherein the local speech recognition result addresses the determined one or more error conditions. 5. The method of claim 1 , wherein the speech recognition resource includes a local speech recognition grammar. | 0.838192 |
7,860,855 | 17 | 18 | 17. The system of claim 1 further comprising: a user interface configured to receive requests for similar concept sets from a user; and a request manager configured to determine the similar concept sets based on one or more concept set similarity values. | 17. The system of claim 1 further comprising: a user interface configured to receive requests for similar concept sets from a user; and a request manager configured to determine the similar concept sets based on one or more concept set similarity values. 18. The system of claim 17 wherein: the user interface is configured to receive requests for similar web pages associated with concept sets from a user, and the request manager is configured to determine the similar web pages based on the concept sets associated with the similar web pages based on the one or more concept set similarity values. | 0.944941 |
8,689,285 | 6 | 8 | 6. A data processing system comprising: a hardware processor; and an accessible hardware memory, the data processing system particularly configured to receive a complex rule set corresponding to at least one electronic document, the complex rule set including a combination of granting rules, denying rules, and rule precedence; generate derived user groups according to the complex rule set; identify derived grant groups that correspond to members of original user groups that are granted access to the electronic document by a grant rule of the complex rule set, excluding members of the original user groups that were denied access to the electronic document by a higher-precedence deny rule of the complex rule set; derive grant rules for each electronic document according to the complex rule set to produce a derived grant rule set, wherein the derived grant rule set has a derived grant rule for each grant rule in the complex rule set, and does not have derived grant rules for any deny rule in the complex rule set; and store the derived grant rules as associated with the electronic document. | 6. A data processing system comprising: a hardware processor; and an accessible hardware memory, the data processing system particularly configured to receive a complex rule set corresponding to at least one electronic document, the complex rule set including a combination of granting rules, denying rules, and rule precedence; generate derived user groups according to the complex rule set; identify derived grant groups that correspond to members of original user groups that are granted access to the electronic document by a grant rule of the complex rule set, excluding members of the original user groups that were denied access to the electronic document by a higher-precedence deny rule of the complex rule set; derive grant rules for each electronic document according to the complex rule set to produce a derived grant rule set, wherein the derived grant rule set has a derived grant rule for each grant rule in the complex rule set, and does not have derived grant rules for any deny rule in the complex rule set; and store the derived grant rules as associated with the electronic document. 8. The data processing system of claim 6 , wherein the data processing system also responds to access requests for the electronic document from users based on the user, the user's membership in a derived grant group, and the grant rule. | 0.680217 |
7,516,145 | 14 | 17 | 14. A method comprising: producing a first rendering file of a hierarchical data file having first and second nodes by applying a full transformation file on the hierarchical data file; rendering the first rendering file to show a rendered form having a first data-entry field associated with the first node of the hierarchical data file and a second data-entry field associated with the second node of the hierarchical data file; enabling a user to input data into the first data-entry field; changing the hierarchical data file by retaining the data in the first node of the hierarchical data file; determining whether applying a partial transformation file on the changed hierarchical data file will produce a rendering file equivalent to a difference between the first rendering file and a second rendering file created by applying the full transformation on the changed hierarchical data file; producing a third rendering file of the changed hierarchical data file, the third rendering file comprising a partial rendering file based on the difference if it is determined that applying a partial transformation file on the changed hierarchical data file will produce a rendering file equivalent to the difference and the third rendering file comprising a full rendering file if it is determined that applying a partial transformation file on the changed hierarchical data file will not produce a rendering file equivalent to the difference; rendering the third rendering file to show a second rendered form reflecting the change to the hierarchical data file; and enabling the user to input data into the second data-entry field. | 14. A method comprising: producing a first rendering file of a hierarchical data file having first and second nodes by applying a full transformation file on the hierarchical data file; rendering the first rendering file to show a rendered form having a first data-entry field associated with the first node of the hierarchical data file and a second data-entry field associated with the second node of the hierarchical data file; enabling a user to input data into the first data-entry field; changing the hierarchical data file by retaining the data in the first node of the hierarchical data file; determining whether applying a partial transformation file on the changed hierarchical data file will produce a rendering file equivalent to a difference between the first rendering file and a second rendering file created by applying the full transformation on the changed hierarchical data file; producing a third rendering file of the changed hierarchical data file, the third rendering file comprising a partial rendering file based on the difference if it is determined that applying a partial transformation file on the changed hierarchical data file will produce a rendering file equivalent to the difference and the third rendering file comprising a full rendering file if it is determined that applying a partial transformation file on the changed hierarchical data file will not produce a rendering file equivalent to the difference; rendering the third rendering file to show a second rendered form reflecting the change to the hierarchical data file; and enabling the user to input data into the second data-entry field. 17. The method of claim 14 , wherein the hierarchical data file is written in XML. | 0.724832 |
9,317,605 | 15 | 16 | 15. A system comprising: a data processing apparatus; and a data store storing instructions executable by the data processing apparatus that upon execution by the data processing apparatus cause the data processing apparatus to perform operations comprising: receiving one or more characters from a user; transmitting the one or more characters to a forking engine; receiving, from the forking engine, data identifying (i) an auto-completion that corresponds to the one or more characters, and (ii) at least a first corpus, selected from a set of multiple corpora, that is associated with the auto-completion and to a first corpus score that satisfies a threshold and a universal search corpus that includes two or more of the multiple corpora and excludes the first corpus; and providing, for display in a drop down menu and to a user device, a first drop down entry that indicates a first representation of the auto-completion and that includes an icon representing the first corpus adjacent to the first representation of the auto-completion, and a second drop down entry that indicates a second representation of the auto-completion that corresponds to the universal search corpus and that excludes the icon representing the first corpus, wherein the universal search corpus includes two or more of a web search corpus, a places search corpus, a literature search corpus, a patent search corpus, an images search corpus, a videos search corpus, a news search corpus, a shopping search corpus, and a blogs search corpus. | 15. A system comprising: a data processing apparatus; and a data store storing instructions executable by the data processing apparatus that upon execution by the data processing apparatus cause the data processing apparatus to perform operations comprising: receiving one or more characters from a user; transmitting the one or more characters to a forking engine; receiving, from the forking engine, data identifying (i) an auto-completion that corresponds to the one or more characters, and (ii) at least a first corpus, selected from a set of multiple corpora, that is associated with the auto-completion and to a first corpus score that satisfies a threshold and a universal search corpus that includes two or more of the multiple corpora and excludes the first corpus; and providing, for display in a drop down menu and to a user device, a first drop down entry that indicates a first representation of the auto-completion and that includes an icon representing the first corpus adjacent to the first representation of the auto-completion, and a second drop down entry that indicates a second representation of the auto-completion that corresponds to the universal search corpus and that excludes the icon representing the first corpus, wherein the universal search corpus includes two or more of a web search corpus, a places search corpus, a literature search corpus, a patent search corpus, an images search corpus, a videos search corpus, a news search corpus, a shopping search corpus, and a blogs search corpus. 16. The system of claim 15 , wherein: the one or more characters are received through a search box; and the first drop down entry that indicates the first representation of the auto-completion and that includes the icon representing the first corpus, and the second drop down entry that indicates the second representation of the auto-completion that corresponds to the universal search corpus are displayed in the drop down menu beneath the search box. | 0.711832 |
8,542,195 | 1 | 6 | 1. A method comprising: selecting multiple languages for a keyboard; obtaining a text corpus for each of the multiple languages; and obtaining, for each of the multiple languages, a mean time to input each of a plurality of characters in the text corpus to the keyboard for one of the multiple languages; simultaneously optimizing the keyboard for the selected multiple languages by: analyzing the text corpus for each of the multiple languages to obtain a digram frequency table; selecting key positions for characters on the keyboard based on an average distance traveled to type one of the characters and a frequency of moving from one of the characters to another one of the characters; selecting constraints for the key positions for the characters on the keyboard; and using a Metropolis method to average the obtained mean times to input one of the characters to the keyboard for each of the multiple languages and determine placement for the positions of the characters on the keyboard for higher user input speed on the keyboard, based on the digram frequency table and additional constraints. | 1. A method comprising: selecting multiple languages for a keyboard; obtaining a text corpus for each of the multiple languages; and obtaining, for each of the multiple languages, a mean time to input each of a plurality of characters in the text corpus to the keyboard for one of the multiple languages; simultaneously optimizing the keyboard for the selected multiple languages by: analyzing the text corpus for each of the multiple languages to obtain a digram frequency table; selecting key positions for characters on the keyboard based on an average distance traveled to type one of the characters and a frequency of moving from one of the characters to another one of the characters; selecting constraints for the key positions for the characters on the keyboard; and using a Metropolis method to average the obtained mean times to input one of the characters to the keyboard for each of the multiple languages and determine placement for the positions of the characters on the keyboard for higher user input speed on the keyboard, based on the digram frequency table and additional constraints. 6. The method of claim 1 , wherein the method is simultaneously optimized for speed of user input. | 0.715116 |
8,024,733 | 57 | 58 | 57. A computer program product, for batch processing in a batch component model within a distributed object environment, the computer program product comprising: a computer readable recordable type media having computer executable instructions stored thereon, the computer executable instructions comprising: computer executable instructions for instantiating a batch component for use with a batch job within the distributed object environment; computer executable instructions for initializing the batch component with a set of deployment descriptors and an instance of a batch container to form a contractual relationship between the batch component and the batch container, wherein the set of deployment descriptors is a set of declarative policies for the batch component; computer executable instructions for wrapping the contractual relationship between the batch component and the batch container to form an adapter, wherein the adapter isolates the batch component from different implementations of the batch container; computer executable instructions for dynamically computing, by the batch container, a size of a checkpoint interval for the batch job using the set of deployment descriptors and other processing workloads, for each use of the checkpoint interval; computer executable instructions for managing operation of the batch component within the distributed object environment by the batch container in accordance with the set of deployment descriptors and the other processing workloads; and computer executable instructions for committing by the batch container on completion of the checkpoint interval, checkpoint cursors and data of the batch job that are updated during the batch processing to a storage of a data processing system, wherein context information including the size of the checkpoint interval and resource dependencies is persisted and passed to downstream batch containers. | 57. A computer program product, for batch processing in a batch component model within a distributed object environment, the computer program product comprising: a computer readable recordable type media having computer executable instructions stored thereon, the computer executable instructions comprising: computer executable instructions for instantiating a batch component for use with a batch job within the distributed object environment; computer executable instructions for initializing the batch component with a set of deployment descriptors and an instance of a batch container to form a contractual relationship between the batch component and the batch container, wherein the set of deployment descriptors is a set of declarative policies for the batch component; computer executable instructions for wrapping the contractual relationship between the batch component and the batch container to form an adapter, wherein the adapter isolates the batch component from different implementations of the batch container; computer executable instructions for dynamically computing, by the batch container, a size of a checkpoint interval for the batch job using the set of deployment descriptors and other processing workloads, for each use of the checkpoint interval; computer executable instructions for managing operation of the batch component within the distributed object environment by the batch container in accordance with the set of deployment descriptors and the other processing workloads; and computer executable instructions for committing by the batch container on completion of the checkpoint interval, checkpoint cursors and data of the batch job that are updated during the batch processing to a storage of a data processing system, wherein context information including the size of the checkpoint interval and resource dependencies is persisted and passed to downstream batch containers. 58. The computer program product, of claim 57 , wherein computer executable instructions for managing operation of the batch component further comprises: computer executable instructions for checkpointing a batch job in a distributed object environment by the batch container; computer executable instructions for determining a duration of a checkpoint interval for the batch component by the batch container; computer executable instructions for running the batch component within the checkpoint interval by the batch container; and computer executable instructions for storing at least one checkpoint cursor upon completion of the checkpoint interval duration by the batch container. | 0.500729 |
7,642,934 | 11 | 20 | 11. A handheld electronic device, comprising: a keyboard having a plurality of input members, a subset of said plurality of input members each having a first character assignment comprising a first set of letters; a display; a processor apparatus comprising a processor and a memory in electronic communication with one another, said processor apparatus having stored therein a number of routines, including a disambiguation routine, which, when executed on said processor, cause said handheld electronic device to perform operations comprising: detecting a predetermined first input; responsive to said detecting a predetermined first input, displaying a representation of a keypad comprising a plurality of keys wherein at least some of the keys each have a second character assignment comprising a second set of letters, wherein the at least some of said keys have a spatial position that corresponds to a spatial position of an input member in said subset; altering said first character assignments of at least some of said input members of said subset to each correspond with said second character assignment of a key having a corresponding spatial position; subsequent to said altering, detecting a second input; employing said disambiguation function to generate a linguistic interpretation of said second input; and outputting said linguistic interpretation. | 11. A handheld electronic device, comprising: a keyboard having a plurality of input members, a subset of said plurality of input members each having a first character assignment comprising a first set of letters; a display; a processor apparatus comprising a processor and a memory in electronic communication with one another, said processor apparatus having stored therein a number of routines, including a disambiguation routine, which, when executed on said processor, cause said handheld electronic device to perform operations comprising: detecting a predetermined first input; responsive to said detecting a predetermined first input, displaying a representation of a keypad comprising a plurality of keys wherein at least some of the keys each have a second character assignment comprising a second set of letters, wherein the at least some of said keys have a spatial position that corresponds to a spatial position of an input member in said subset; altering said first character assignments of at least some of said input members of said subset to each correspond with said second character assignment of a key having a corresponding spatial position; subsequent to said altering, detecting a second input; employing said disambiguation function to generate a linguistic interpretation of said second input; and outputting said linguistic interpretation. 20. The handheld electronic device according to claim 11 , wherein said second input is a vocal command that initiates a telephone routine. | 0.853376 |
8,527,500 | 16 | 18 | 16. The document processing system of claim 15 , wherein the preprocessing further comprises matching the prefix and the trailing context in the first document with the matching prefixes in the transformation database. | 16. The document processing system of claim 15 , wherein the preprocessing further comprises matching the prefix and the trailing context in the first document with the matching prefixes in the transformation database. 18. The document processing system of claim 16 , wherein the matching further comprises weighting the one or more matching prefixes, wherein the weighting is based on separate weights for matching the prefix and the trailing context. | 0.931672 |
8,086,960 | 10 | 11 | 10. A method, comprising: receiving an input to a body of an electronic markup language document that is being displayed in a browser; and in response to said receiving: generating a comment based on or including the input; marking a body section of a data structure for the electronic document with a tag based on the input, wherein the body section includes content for the body of the electronic markup language document; storing the comment in a comment section of the data structure for the electronic document, wherein said storing comprises storing the input using another tag to identify the comment, wherein the comment section of the data structure is separate from the body section of the data structure; and displaying the body of the electronic markup language document and an action user interface element, wherein the action user interface element is useable to cause the browser to parse the tag and the another tag to determine where the input can be applied to the electronic markup language document. | 10. A method, comprising: receiving an input to a body of an electronic markup language document that is being displayed in a browser; and in response to said receiving: generating a comment based on or including the input; marking a body section of a data structure for the electronic document with a tag based on the input, wherein the body section includes content for the body of the electronic markup language document; storing the comment in a comment section of the data structure for the electronic document, wherein said storing comprises storing the input using another tag to identify the comment, wherein the comment section of the data structure is separate from the body section of the data structure; and displaying the body of the electronic markup language document and an action user interface element, wherein the action user interface element is useable to cause the browser to parse the tag and the another tag to determine where the input can be applied to the electronic markup language document. 11. The method of claim 10 , further comprising the browser parsing the tag and the another tag to determine how to modify the document using the input. | 0.817746 |
7,693,738 | 1 | 5 | 1. A method of using a computer system to gather information about an organizational process or system, comprising: obtaining information about an organization to be assessed, wherein the information comprises information regarding assessors; the computer system preparing at least one question regarding the organizational process or system by analyzing the obtained information about the organization; the computer system displaying on a display device a first user adjustable icon and a second user adjustable icon and at least one question, the first user adjustable icon being adjustable within a first allowed range; the second user adjustable icon being adjustable within a second allowed range; and wherein the at least one question being adapted to prompt the assessor to input the assessor's perceptions of the organizational process or system; the computer system receiving a first quantitative input from a user, the first input corresponding to movement of the first user adjustable icon; the computer system determining a second allowed input range for a second user adjustable icon based on the first input, wherein the bottom of the determined second allowed input range for the second user adjustable icon is the value of the first quantitative input; the computer system displaying the second user adjustable icon such that the full width of the second user adjustable icon corresponds to the determined second allowed input range; and the computer system receiving a second quantitative input from the user, the second input corresponding to movement of the second user adjustable icon. | 1. A method of using a computer system to gather information about an organizational process or system, comprising: obtaining information about an organization to be assessed, wherein the information comprises information regarding assessors; the computer system preparing at least one question regarding the organizational process or system by analyzing the obtained information about the organization; the computer system displaying on a display device a first user adjustable icon and a second user adjustable icon and at least one question, the first user adjustable icon being adjustable within a first allowed range; the second user adjustable icon being adjustable within a second allowed range; and wherein the at least one question being adapted to prompt the assessor to input the assessor's perceptions of the organizational process or system; the computer system receiving a first quantitative input from a user, the first input corresponding to movement of the first user adjustable icon; the computer system determining a second allowed input range for a second user adjustable icon based on the first input, wherein the bottom of the determined second allowed input range for the second user adjustable icon is the value of the first quantitative input; the computer system displaying the second user adjustable icon such that the full width of the second user adjustable icon corresponds to the determined second allowed input range; and the computer system receiving a second quantitative input from the user, the second input corresponding to movement of the second user adjustable icon. 5. The method of claim 1 , wherein displaying comprises displaying across a global computer network. | 0.865591 |
8,554,761 | 1 | 5 | 1. A method comprising: transforming a first query to a transformed query; wherein the first query includes: a first outer join of a first database object and a second database object, and a first join predicate that specifies a first condition of the first database object for the first outer join, wherein the first join predicate does not reference the second database object; wherein the transformed query does not include the first join predicate but does include: a second predicate that specifies a second condition of the first database object, wherein the second predicate references the second database object; wherein the transformed query is semantically equivalent to the first query; causing execution of the transformed query instead of the first query; wherein the method is performed by one or more computing devices. | 1. A method comprising: transforming a first query to a transformed query; wherein the first query includes: a first outer join of a first database object and a second database object, and a first join predicate that specifies a first condition of the first database object for the first outer join, wherein the first join predicate does not reference the second database object; wherein the transformed query does not include the first join predicate but does include: a second predicate that specifies a second condition of the first database object, wherein the second predicate references the second database object; wherein the transformed query is semantically equivalent to the first query; causing execution of the transformed query instead of the first query; wherein the method is performed by one or more computing devices. 5. The method of claim 1 , wherein the second predicate is in a WHERE clause of the transformed query. | 0.930988 |
8,447,751 | 27 | 28 | 27. An apparatus comprising: a processor; and memory operatively coupled to the processor and storing computer readable instructions that, when executed, cause the apparatus to: receive an identifier for a network document; perform an on-demand analysis of the network document to determine a search engine score for the network document, wherein the on-demand analysis of the network document includes: determining a number of links included in the network document by analyzing a structure of the network document; determining a number of incoming links to the network document; and generating separate specific traffic-independent scoring analyses for each of the links included in the network document, wherein each of the separate specific traffic-independent scoring analyses are visually-navigable; and generate, based on the received identifier and independently of a user-specified search word or phrase, a display of the search engine score along with a first level of scoring detail for the network document, wherein the search engine score is determined by evaluating the network document using one or more traffic-independent scoring factors and wherein the network document is ranked based on the one or more traffic-independent scoring factors, and wherein the ranking is determined by combining the search engine score and a link flow distribution that indicates the likelihood that a user will access the network document relative to a second network document, wherein the network document and the second network document are within the same web site; receive a request to display details of the one or more traffic-independent scoring factors; in response to the request: generate the details of the one or more traffic-independent scoring factors by performing an on-demand analysis of the one or more traffic-independent scoring factors; and generate a display of a second level of scoring detail including the details of the one or more traffic-independent scoring factors, wherein the second level of scoring detail includes a plurality of non-traffic attributes. | 27. An apparatus comprising: a processor; and memory operatively coupled to the processor and storing computer readable instructions that, when executed, cause the apparatus to: receive an identifier for a network document; perform an on-demand analysis of the network document to determine a search engine score for the network document, wherein the on-demand analysis of the network document includes: determining a number of links included in the network document by analyzing a structure of the network document; determining a number of incoming links to the network document; and generating separate specific traffic-independent scoring analyses for each of the links included in the network document, wherein each of the separate specific traffic-independent scoring analyses are visually-navigable; and generate, based on the received identifier and independently of a user-specified search word or phrase, a display of the search engine score along with a first level of scoring detail for the network document, wherein the search engine score is determined by evaluating the network document using one or more traffic-independent scoring factors and wherein the network document is ranked based on the one or more traffic-independent scoring factors, and wherein the ranking is determined by combining the search engine score and a link flow distribution that indicates the likelihood that a user will access the network document relative to a second network document, wherein the network document and the second network document are within the same web site; receive a request to display details of the one or more traffic-independent scoring factors; in response to the request: generate the details of the one or more traffic-independent scoring factors by performing an on-demand analysis of the one or more traffic-independent scoring factors; and generate a display of a second level of scoring detail including the details of the one or more traffic-independent scoring factors, wherein the second level of scoring detail includes a plurality of non-traffic attributes. 28. The apparatus of claim 27 , wherein the network document is analyzed by a search engine separate from an optimization engine of the apparatus. | 0.853707 |
7,599,988 | 1 | 10 | 1. A method implemented by a client application running on a client computer, said method comprising: retrieving an address of a server that provides a geolocating service that analyzes received electronic documents containing unstructured text to discover spatial identifiers contained within the unstructured text and generates for those received electronic documents geolocation information, said geolocation information identifying all spatial identifiers discovered within the unstructured text of the received electronic documents and also including geospatial coordinates for all spatial identifiers discovered within the unstructured text of the received electronic documents; identifying at said client application a client document that includes unstructured text containing a plurality of unidentified spatial identifiers; electronically transferring the identified client document to the address of the server providing the geolocating service; and electronically receiving back from the server providing the geolocating service geolocation information for the client document, wherein the received geolocation information identifies all spatial identifiers among the plurality of unidentified spatial identifiers within the unstructured text including geographical coordinates for each of the identified spatial identifiers, wherein the geographical coordinates are not found at a specific location in the document but rather is derived from analyzing the content of the document, and wherein each of the identified spatial identifiers is assigned a corresponding spatial relevance level for the client document as a measure of the degree to which the document relates to the spatial location mentioned in its spatial information content. | 1. A method implemented by a client application running on a client computer, said method comprising: retrieving an address of a server that provides a geolocating service that analyzes received electronic documents containing unstructured text to discover spatial identifiers contained within the unstructured text and generates for those received electronic documents geolocation information, said geolocation information identifying all spatial identifiers discovered within the unstructured text of the received electronic documents and also including geospatial coordinates for all spatial identifiers discovered within the unstructured text of the received electronic documents; identifying at said client application a client document that includes unstructured text containing a plurality of unidentified spatial identifiers; electronically transferring the identified client document to the address of the server providing the geolocating service; and electronically receiving back from the server providing the geolocating service geolocation information for the client document, wherein the received geolocation information identifies all spatial identifiers among the plurality of unidentified spatial identifiers within the unstructured text including geographical coordinates for each of the identified spatial identifiers, wherein the geographical coordinates are not found at a specific location in the document but rather is derived from analyzing the content of the document, and wherein each of the identified spatial identifiers is assigned a corresponding spatial relevance level for the client document as a measure of the degree to which the document relates to the spatial location mentioned in its spatial information content. 10. The method of claim 1 wherein the received geolocation information also includes a spatial relevance level for the client document. | 0.937902 |
9,495,415 | 13 | 19 | 13. A method as recited in claim 1 further comprising weighting the search results with a relevance weight associated with a string object, wherein displaying the search results comprises displaying the search results in response to the relevance weight. | 13. A method as recited in claim 1 further comprising weighting the search results with a relevance weight associated with a string object, wherein displaying the search results comprises displaying the search results in response to the relevance weight. 19. A method as recited in claim 13 wherein when the relevance weight is equal, displaying comprises displaying the search results in alphabetical order. | 0.953039 |
9,946,772 | 1 | 8 | 1. A method comprising, by a computing device: receiving, from a client system of a first user, a text query inputted by the first user at a query field of a currently accessed interface of an online social network; generating a plurality of structured queries based on the text query, each structured query comprising one or more query tokens, wherein one or more of the query tokens are unique query tokens comprising references to one or more unique objects associated with the online social network, respectively; generating one or more search results corresponding to at least one of the structured queries; and sending, to the client system responsive to receiving the text query, instructions for displaying one or more suggested queries on the interface, wherein the one or more suggested queries correspond to one or more structured queries, respectively, at least one of the suggested queries being displayed with a preview of one or more search results matching the structured query corresponding to the suggested query, and wherein each suggested query that is displayed is selectable by the first user to retrieve search results matching the structured query corresponding to the selected suggested query. | 1. A method comprising, by a computing device: receiving, from a client system of a first user, a text query inputted by the first user at a query field of a currently accessed interface of an online social network; generating a plurality of structured queries based on the text query, each structured query comprising one or more query tokens, wherein one or more of the query tokens are unique query tokens comprising references to one or more unique objects associated with the online social network, respectively; generating one or more search results corresponding to at least one of the structured queries; and sending, to the client system responsive to receiving the text query, instructions for displaying one or more suggested queries on the interface, wherein the one or more suggested queries correspond to one or more structured queries, respectively, at least one of the suggested queries being displayed with a preview of one or more search results matching the structured query corresponding to the suggested query, and wherein each suggested query that is displayed is selectable by the first user to retrieve search results matching the structured query corresponding to the selected suggested query. 8. The method of claim 1 , wherein the sent structured queries are displayed in a drop-down menu on an interface currently accessed by the first user, wherein the drop-down menu enables the first user to select one of the structured queries. | 0.726757 |
10,140,980 | 3 | 4 | 3. The method of claim 1 , comprising: generating a convolutional filter with one or more real filter weights; and generating a frequency domain filter with one or more complex filter weights based on the convolutional filter, wherein processing the frequency domain data using complex linear projection comprises applying the frequency domain filter to the audio data. | 3. The method of claim 1 , comprising: generating a convolutional filter with one or more real filter weights; and generating a frequency domain filter with one or more complex filter weights based on the convolutional filter, wherein processing the frequency domain data using complex linear projection comprises applying the frequency domain filter to the audio data. 4. The method of claim 3 , comprising: receiving an additional input frame of audio data corresponding to the utterance; generating additional frequency domain data using the additional input frame of audio data; applying the frequency domain filter with the one or more complex filter weights to the additional frequency domain data; and providing the filtered additional frequency domain data to the neural network, wherein generating the transcription for the utterance comprises generating the transcription for the utterance based further on output that the neural network provides in response to receiving the filtered additional frequency domain data. | 0.623139 |
9,658,771 | 7 | 8 | 7. A computer implemented method for enabling a user to input alphabets in an Indian Language, via a user interface, said method comprising the following computer implemented steps: generating, based on a script-grammar corresponding to the Indian language, a default keypad layer comprising a plurality of alphabets represented as selectable vowels and consonants: generating, based on the script-grammar corresponding to the Indian language, a first keypad layer comprising the vowels and consonants and a plurality of modifiers; generating, based on the script-grammar corresponding to the Indian language, a second keypad layer comprising a plurality of matras, a plurality of halants, the vowels and the consonants, wherein said matins are formed by selectively combining the vowels and the consonants; generating, based on at least the script-grammar corresponding to the Indian language, a third keypad layer comprising the plurality of matras and the plural y of modifiers; integrating said default keypad layer, first keypad layer, second keypad layer and third keypad layer into a display enabled keypad layout; displaying said keypad layout on the user interface; providing the user with an access to at least said default keypad layer of the keypad layout; triggering a display of the first keypad layer subsequent to selection of a vowel on the default keypad layer, and triggering a display of the second keypad layer, in an event that a consonant has been selected from the default keypad layer; retriggering the display of the default keypad layer in an event that a modifier has been selected from the first keypad layer, and triggering a display of the third keypad layer in an event that a consonant has been selected from the first keypad layer, and generating a trigger to retain the display of the first keypad layer, in an event that a vowel has been selected via the first keypad layer; retriggering the display of the default keypad layer subsequent to selection of a halant from said second keypad layer, and retriggering te 6 display of the first keypad layer, in an event that a matra has been selected via said second keypad layer; and retriggering the display of the default keypad layer, subsequent to selection of a modifier from the third keypad layer, and retriggering the display of the default keypad layer, subsequent to selection of a matra from the third keypad layer. | 7. A computer implemented method for enabling a user to input alphabets in an Indian Language, via a user interface, said method comprising the following computer implemented steps: generating, based on a script-grammar corresponding to the Indian language, a default keypad layer comprising a plurality of alphabets represented as selectable vowels and consonants: generating, based on the script-grammar corresponding to the Indian language, a first keypad layer comprising the vowels and consonants and a plurality of modifiers; generating, based on the script-grammar corresponding to the Indian language, a second keypad layer comprising a plurality of matras, a plurality of halants, the vowels and the consonants, wherein said matins are formed by selectively combining the vowels and the consonants; generating, based on at least the script-grammar corresponding to the Indian language, a third keypad layer comprising the plurality of matras and the plural y of modifiers; integrating said default keypad layer, first keypad layer, second keypad layer and third keypad layer into a display enabled keypad layout; displaying said keypad layout on the user interface; providing the user with an access to at least said default keypad layer of the keypad layout; triggering a display of the first keypad layer subsequent to selection of a vowel on the default keypad layer, and triggering a display of the second keypad layer, in an event that a consonant has been selected from the default keypad layer; retriggering the display of the default keypad layer in an event that a modifier has been selected from the first keypad layer, and triggering a display of the third keypad layer in an event that a consonant has been selected from the first keypad layer, and generating a trigger to retain the display of the first keypad layer, in an event that a vowel has been selected via the first keypad layer; retriggering the display of the default keypad layer subsequent to selection of a halant from said second keypad layer, and retriggering te 6 display of the first keypad layer, in an event that a matra has been selected via said second keypad layer; and retriggering the display of the default keypad layer, subsequent to selection of a modifier from the third keypad layer, and retriggering the display of the default keypad layer, subsequent to selection of a matra from the third keypad layer. 8. The method as claimed in claim 7 , wherein the step of generating a default keypad layer further comprises the following steps: generating a default base layer comprising un-aspirated consonants; generating a default toggle layer aspirated consonants; and integrating said default base layer and default toggle layer onto the default keypad layer. | 0.905965 |
8,489,632 | 21 | 23 | 21. The computer-readable storage device of claim 19 , wherein determining the respective convergence status of each of the plurality of processes comprises: determining a difference between two or more training iterations and comparing the difference to a predetermined threshold value; and determining that the process is unlikely to converge if the difference exceeds the threshold value, and otherwise, determining that the process is likely to converge if the difference is less than the threshold value. | 21. The computer-readable storage device of claim 19 , wherein determining the respective convergence status of each of the plurality of processes comprises: determining a difference between two or more training iterations and comparing the difference to a predetermined threshold value; and determining that the process is unlikely to converge if the difference exceeds the threshold value, and otherwise, determining that the process is likely to converge if the difference is less than the threshold value. 23. The computer-readable storage device of claim 21 , wherein the difference is an absolute numerical value change between two iterations and the predetermined threshold value is expressed as a numerical value. | 0.955598 |
4,454,586 | 15 | 16 | 15. Apparatus for producing subunit speech patterns according to claim 14 wherein said means for detecting the first and second utterance time frames comprises means for producing a signal representative of the utterance time frame corresponding to the reference subunit begin frame responsive to said first signal and said best matching time frame path signals, and means for producing a signal representative of the utterance time frame corresponding to the reference subunit endframe responsive to said second signal and said best matching time frame path signals. | 15. Apparatus for producing subunit speech patterns according to claim 14 wherein said means for detecting the first and second utterance time frames comprises means for producing a signal representative of the utterance time frame corresponding to the reference subunit begin frame responsive to said first signal and said best matching time frame path signals, and means for producing a signal representative of the utterance time frame corresponding to the reference subunit endframe responsive to said second signal and said best matching time frame path signals. 16. Apparatus for producing subunit speech patterns according to claim 15 wherein said utterance time frame detecting means comprises means for comparing said first signal to the sequence of reference speech pattern time frames to generate a subunit begin frame signal, means for comparing said second signal to the sequence of reference speech pattern time frames to generate a subunit endframe signal, means responsive to said reference subunit begin frame signal and said best matching time frame path signals for producing a signal representative of the utterance time frame corresponding to the reference subunit begin frame, and means responsive to said reference word subunit endframe signal and said best matching time frame path signals for producing a signal representative of the utterance frame corresponding to the reference subunit endframe. | 0.656074 |
8,275,785 | 1 | 2 | 1. A method for using a computer system to provide additional material related to a concept within electronic text, comprising the steps of: a) identifying electronic text for display; b) packaging with said text computer-executable code, wherein: i. said code is formatted and designed to be executed in real-time without user action when said accompanying text is displayed; ii. when executed, said code submits a search request for additional information related to a concept represented within at least one text section of said identified text, said search request leading to a search of an index, said search of an index identifying additional material related to said concept; and iii. when executed, said code provides for display in the same presentation as said identified electronic text an indicator of said identified additional material, wherein said indicator comprises display material not derived from said electronic text; and c) in response to a request for said electronic text, providing said electronic text together with said computer-executable code; wherein said index contains a plurality of terms by which it may be searched; at least one term in said index is associated with at least one reference to a text section; and at least one term in said index is associated with a plurality of references, at least two of said plurality of references indicating different text sections. | 1. A method for using a computer system to provide additional material related to a concept within electronic text, comprising the steps of: a) identifying electronic text for display; b) packaging with said text computer-executable code, wherein: i. said code is formatted and designed to be executed in real-time without user action when said accompanying text is displayed; ii. when executed, said code submits a search request for additional information related to a concept represented within at least one text section of said identified text, said search request leading to a search of an index, said search of an index identifying additional material related to said concept; and iii. when executed, said code provides for display in the same presentation as said identified electronic text an indicator of said identified additional material, wherein said indicator comprises display material not derived from said electronic text; and c) in response to a request for said electronic text, providing said electronic text together with said computer-executable code; wherein said index contains a plurality of terms by which it may be searched; at least one term in said index is associated with at least one reference to a text section; and at least one term in said index is associated with a plurality of references, at least two of said plurality of references indicating different text sections. 2. The method of claim 1 , wherein said electronic text comprises non-text elements. | 0.7375 |
8,595,221 | 37 | 38 | 37. A method of identifying web pages in a world wide web having relevance to a first file, comprising: identifying a plurality of web pages within the world wide web, wherein the plurality of web pages each have a relationship with the first file, wherein the world wide web provides a platform for sharing web pages, and wherein each web page includes a document or information resource that is suitable for the world wide web and is accessible through a web browser; generating, by a system server, a first list of inquiries based on the plurality of web pages, wherein the list of inquiries includes search terms used in a search that identified the plurality of web pages; providing, by the system server, the first list of inquiries to at least one author of the first file; receiving from the at least one author of the plurality of web pages at least one first response to the first list of inquiries; generating, by the system server, a second list of inquiries based on the plurality of web pages; providing, by the system server, the second list of inquiries to at least one second author of the plurality of web pages; receiving from the at least one second author of the plurality of web pages at least one second response to the second list of inquiries; selecting a subset of the plurality of web pages based on the at least one first response and the at least one second response; storing information related to the selected subset of the plurality of web pages for access if the first file is selected; providing the selected subset of the plurality of web pages to a user that selects the first file; and identifying the at least one author or the at least one second author to the user. | 37. A method of identifying web pages in a world wide web having relevance to a first file, comprising: identifying a plurality of web pages within the world wide web, wherein the plurality of web pages each have a relationship with the first file, wherein the world wide web provides a platform for sharing web pages, and wherein each web page includes a document or information resource that is suitable for the world wide web and is accessible through a web browser; generating, by a system server, a first list of inquiries based on the plurality of web pages, wherein the list of inquiries includes search terms used in a search that identified the plurality of web pages; providing, by the system server, the first list of inquiries to at least one author of the first file; receiving from the at least one author of the plurality of web pages at least one first response to the first list of inquiries; generating, by the system server, a second list of inquiries based on the plurality of web pages; providing, by the system server, the second list of inquiries to at least one second author of the plurality of web pages; receiving from the at least one second author of the plurality of web pages at least one second response to the second list of inquiries; selecting a subset of the plurality of web pages based on the at least one first response and the at least one second response; storing information related to the selected subset of the plurality of web pages for access if the first file is selected; providing the selected subset of the plurality of web pages to a user that selects the first file; and identifying the at least one author or the at least one second author to the user. 38. The method of claim 37 , wherein the information related to the selected subset of the plurality of web pages comprises an opinion of the at least one author of either the first file or the plurality of web pages. | 0.502294 |
9,398,460 | 39 | 47 | 39. A mobile phone-based method for providing security escorts to a requester for a location, time, and duration by a security escort provider, the method comprising: a. receiving request data from at least one requester's mobile phone for at least one engagement in at least one location; b. creating a record in a database for each requester request; c. collecting request factor data relevant to at least one engagement in at least one location; d. creating at least one record in the database for request factor data; e. requesting availability from at least one security escort for at least one engagement in at least one location based request factor data; f. calculating cost information for the engagement based on data from g. providing requester with confirmation of escort availability for engagement and other factors; h. request factors; i. receiving payment from requester for at least one engagement in at least one location; j. transmitting authentication and confirmation information to mobile phone of the requester and the security escort; k. rendezvousing requester at the location with the security escort; l. exchanging authentications to verify the identity of requester and escort; m. providing the security service as requested by the requester in at least one location; n. completing the security escort's engagement; o. notifying the security escort's provider of the engagement termination making security escort available for new engagement; p. paying security escort for at least one engagement in at least one location based on request factors; q. creating at least one record in the database for review data; whereby a requester can request tailored security escorts for an engagement in a location, date, and time based on request factors wherein the cost is determined by the applicable adjustment factors. | 39. A mobile phone-based method for providing security escorts to a requester for a location, time, and duration by a security escort provider, the method comprising: a. receiving request data from at least one requester's mobile phone for at least one engagement in at least one location; b. creating a record in a database for each requester request; c. collecting request factor data relevant to at least one engagement in at least one location; d. creating at least one record in the database for request factor data; e. requesting availability from at least one security escort for at least one engagement in at least one location based request factor data; f. calculating cost information for the engagement based on data from g. providing requester with confirmation of escort availability for engagement and other factors; h. request factors; i. receiving payment from requester for at least one engagement in at least one location; j. transmitting authentication and confirmation information to mobile phone of the requester and the security escort; k. rendezvousing requester at the location with the security escort; l. exchanging authentications to verify the identity of requester and escort; m. providing the security service as requested by the requester in at least one location; n. completing the security escort's engagement; o. notifying the security escort's provider of the engagement termination making security escort available for new engagement; p. paying security escort for at least one engagement in at least one location based on request factors; q. creating at least one record in the database for review data; whereby a requester can request tailored security escorts for an engagement in a location, date, and time based on request factors wherein the cost is determined by the applicable adjustment factors. 47. The method of claim 39 , where the database is preloaded with at least one security escort data for at least one security escort for at least one engagement category. | 0.894932 |
9,558,276 | 29 | 31 | 29. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium of an agent device, including instructions configured to cause a data processing apparatus to: determine availability as an agent for topic data stored in a system, wherein agents are active or inactive and are relevant or irrelevant to the topic data, and wherein agents are relevant when a topic included in one or more profiles of one or more relevant agents matches the topic data; transmit availability as an active relevant agent for the topic data, wherein one or more real-time interaction options are associated with active relevant agents, wherein status data is generated and remotely stored according to the availability of active relevant agents associated with real-time interaction options, wherein the status data is transmitted by an agent search server to a search engine server operating remotely from the agent search server and in communication with the agent search server over a network, wherein an agent search request is generated using the topic data and includes the topic data, and wherein the agent search request is used to determine relevant agents associated with the topic data; detect data corresponding to a selection of an interactive element associated with search results generated by the search engine server, wherein the search results are generated in response to a search request including the topic data, wherein the search request does not include a request for an agent, wherein the search request is separate from the agent search request, wherein interactive elements are associated with the search results according to remotely received status data, wherein the interactive elements are separate from the search results, wherein an interactive element is displayed concurrently with a search result, and wherein the selection of an interactive element facilitates a real-time interaction option among two or more devices; and participate in a real-time interaction option as an active relevant agent associated with the topic data. | 29. A computer-program product tangibly embodied in a non-transitory machine-readable storage medium of an agent device, including instructions configured to cause a data processing apparatus to: determine availability as an agent for topic data stored in a system, wherein agents are active or inactive and are relevant or irrelevant to the topic data, and wherein agents are relevant when a topic included in one or more profiles of one or more relevant agents matches the topic data; transmit availability as an active relevant agent for the topic data, wherein one or more real-time interaction options are associated with active relevant agents, wherein status data is generated and remotely stored according to the availability of active relevant agents associated with real-time interaction options, wherein the status data is transmitted by an agent search server to a search engine server operating remotely from the agent search server and in communication with the agent search server over a network, wherein an agent search request is generated using the topic data and includes the topic data, and wherein the agent search request is used to determine relevant agents associated with the topic data; detect data corresponding to a selection of an interactive element associated with search results generated by the search engine server, wherein the search results are generated in response to a search request including the topic data, wherein the search request does not include a request for an agent, wherein the search request is separate from the agent search request, wherein interactive elements are associated with the search results according to remotely received status data, wherein the interactive elements are separate from the search results, wherein an interactive element is displayed concurrently with a search result, and wherein the selection of an interactive element facilitates a real-time interaction option among two or more devices; and participate in a real-time interaction option as an active relevant agent associated with the topic data. 31. The computer-program product of claim 29 , wherein status data is active or inactive, wherein status data is active when a relevant agent associated with the topic is active, and wherein status data is inactive when a relevant agent associated with the topic is inactive. | 0.546205 |
9,300,963 | 12 | 13 | 12. The method of claim 1 , wherein the flag is an implicit flag. | 12. The method of claim 1 , wherein the flag is an implicit flag. 13. The method of claim 12 , wherein the implicit flag is determined at a decoder based on information associated with intra period or Group of Picture (GOP) structure in the video bitstream. | 0.934634 |
7,920,714 | 13 | 19 | 13. Non-transitory computer readable media according to claim 11 whereby the texture feature is printed matter. | 13. Non-transitory computer readable media according to claim 11 whereby the texture feature is printed matter. 19. Non-transitory computer readable media according to claim 13 whereby the obtained data for the document comprises direction and contour changes of one or more portions of the printed matter of the texture feature of the obtained digital image. | 0.895781 |
8,397,157 | 9 | 12 | 9. The method of claim 1 , wherein the grammar rule item includes output control instructions, and wherein the generating of the portion of the markup language document representation is according to the output control instructions. | 9. The method of claim 1 , wherein the grammar rule item includes output control instructions, and wherein the generating of the portion of the markup language document representation is according to the output control instructions. 12. The method of claim 9 , wherein the output control instructions are implicit in the grammar rule item. | 0.980976 |
9,552,420 | 6 | 9 | 6. The method of claim 1 , further comprising generating the feature values from the surrogate document, the feature values comprising query-based features and term-based features, wherein the attributes are feature values. | 6. The method of claim 1 , further comprising generating the feature values from the surrogate document, the feature values comprising query-based features and term-based features, wherein the attributes are feature values. 9. The method of claim 6 , wherein the term-based features are weighted based on the user actions associated with the at least one document. | 0.949054 |
8,027,834 | 1 | 8 | 1. A method for testing a phonetic decision tree, the method comprising: testing a first phonetic decision tree, created using a first set of data, with a second set of data, the second set of data including at least one second term not in the first set of data, by phonetizing terms of the second set of data using the first phonetic decision tree; categorizing results of the testing into a set of correctly phonetized terms and a set of incorrectly phonetized terms; and operating at least one processor to create an exception dictionary including at least one term from the set of incorrectly phonetized terms and phonetization information related to the at least one term. | 1. A method for testing a phonetic decision tree, the method comprising: testing a first phonetic decision tree, created using a first set of data, with a second set of data, the second set of data including at least one second term not in the first set of data, by phonetizing terms of the second set of data using the first phonetic decision tree; categorizing results of the testing into a set of correctly phonetized terms and a set of incorrectly phonetized terms; and operating at least one processor to create an exception dictionary including at least one term from the set of incorrectly phonetized terms and phonetization information related to the at least one term. 8. The method of claim 1 , wherein the accepting comprises: following the categorizing, determining if one or more termination conditions are met by the first phonetic decision tree; and when the one or more termination conditions are met, accepting the first phonetic decision tree as a production decision tree to be used in the text-to-speech system. | 0.831905 |
7,827,153 | 1 | 3 | 1. A computer implemented method to perform bulk operation database cleanup comprising: extending a metamodel of a database in a data warehousing application including human readable descriptions of plurality of entities, fields and foreign key relationships; selecting attributes on which to group objects from the database, wherein the selecting is based on flags existing in the extended metamodel; grouping objects from a database based on selected attributes by performing a SELECT DISTINCT query on a selected attribute values, defining a number of subgroups less than a number of instances returned from the query, and allocating instances returned from the query among the subgroups; displaying a graphical user interface (GUI) to accept filter criteria from the human readable descriptions of entities, fields and foreign key relationships; filtering the grouped objects based on the accepted criteria to identify erroneous data; identifying whether a common attribute shared by all members of a group; dynamically generating structured query language (SQL) statements to directly correct the erroneous data within the database; and applying the SQL statements in a batch operation on the all members of the filtered grouped objects. | 1. A computer implemented method to perform bulk operation database cleanup comprising: extending a metamodel of a database in a data warehousing application including human readable descriptions of plurality of entities, fields and foreign key relationships; selecting attributes on which to group objects from the database, wherein the selecting is based on flags existing in the extended metamodel; grouping objects from a database based on selected attributes by performing a SELECT DISTINCT query on a selected attribute values, defining a number of subgroups less than a number of instances returned from the query, and allocating instances returned from the query among the subgroups; displaying a graphical user interface (GUI) to accept filter criteria from the human readable descriptions of entities, fields and foreign key relationships; filtering the grouped objects based on the accepted criteria to identify erroneous data; identifying whether a common attribute shared by all members of a group; dynamically generating structured query language (SQL) statements to directly correct the erroneous data within the database; and applying the SQL statements in a batch operation on the all members of the filtered grouped objects. 3. The method of claim 1 wherein selecting comprises: identifying a grouping suitability of an attribute field. | 0.838192 |
10,157,176 | 1 | 2 | 1. A method that is executed by a computer, the method comprising: accepting an input of text from an input device; detecting a string of characters from the text, the string of characters corresponding to an abbreviation, the abbreviation corresponding to a plurality of phrases, the plurality of phrases having different meanings respectively; acquiring record information that indicates a record corresponding to an identifier related to the text and background information that indicates an attribute of the identifier; generating the plurality of phrases for display on an interactive display window of a display device, the plurality of phrases being generated from a database storing correspondence information including the string of characters, the plurality of phrases, and a co-occurrence statistical value calculated for each of the plurality of phrases, the co-occurrence statistical value indicating probability of appearance in the record information and the background information; displaying the plurality of phrases on the interactive display window as candidates for an appropriate phrase corresponding to the abbreviation in the text, the interactive display window being configured to enable a user to select the appropriate phrase from among the plurality of phrases; updating the correspondence information when the appropriate phrase is selected; when an input of another text from the input device and the string of characters is detected from the another text, displaying the candidates determined based on the updated correspondence information; recalculating the co-occurrence statistical value based on the updated correspondence information; and updating the database based on the recalculated co-occurrence statistical value. | 1. A method that is executed by a computer, the method comprising: accepting an input of text from an input device; detecting a string of characters from the text, the string of characters corresponding to an abbreviation, the abbreviation corresponding to a plurality of phrases, the plurality of phrases having different meanings respectively; acquiring record information that indicates a record corresponding to an identifier related to the text and background information that indicates an attribute of the identifier; generating the plurality of phrases for display on an interactive display window of a display device, the plurality of phrases being generated from a database storing correspondence information including the string of characters, the plurality of phrases, and a co-occurrence statistical value calculated for each of the plurality of phrases, the co-occurrence statistical value indicating probability of appearance in the record information and the background information; displaying the plurality of phrases on the interactive display window as candidates for an appropriate phrase corresponding to the abbreviation in the text, the interactive display window being configured to enable a user to select the appropriate phrase from among the plurality of phrases; updating the correspondence information when the appropriate phrase is selected; when an input of another text from the input device and the string of characters is detected from the another text, displaying the candidates determined based on the updated correspondence information; recalculating the co-occurrence statistical value based on the updated correspondence information; and updating the database based on the recalculated co-occurrence statistical value. 2. The method according to claim 1 , the method further comprising: determining a display order of the plurality of phrases in the interactive display window based on the calculated statistical values. | 0.666113 |
7,543,189 | 1 | 5 | 1. A method of testing an application program using a test script containing test commands in a first language, the application program having a second language different from the first language, the method comprising the computer implemented steps of: employing translations used in the application program itself, comparing test commands in the first language to converted test commands in the second language by: determining a support file of the application program supporting program execution in various languages and having translations to the second language, the support file being a prior established file of the application program and the support file having resource name and URL for the second language; and accessing the determined support file and obtaining translations of the test commands in the second language. | 1. A method of testing an application program using a test script containing test commands in a first language, the application program having a second language different from the first language, the method comprising the computer implemented steps of: employing translations used in the application program itself, comparing test commands in the first language to converted test commands in the second language by: determining a support file of the application program supporting program execution in various languages and having translations to the second language, the support file being a prior established file of the application program and the support file having resource name and URL for the second language; and accessing the determined support file and obtaining translations of the test commands in the second language. 5. A method as claimed in claim 1 wherein the support file is any one of a property file, a resource bundle or resource file of the application program. | 0.845528 |
7,707,017 | 14 | 16 | 14. A system modeling facilitating apparatus, comprising: an input device for receiving information input by users, said information comprising entities and interactions among entities of a system; a storage device for storing information input by users and received from the input device, and diagram data formed by the system modeling facilitating apparatus; a display device for displaying information and diagram data; an abstract view editor for editing an abstract view, said view comprising entities and interactions among the entities; a module framework generator for building a sub-module for at least one of the entities, each sub-module being associated with a respective entity; an interface forming device for forming interfaces for each sub-module to other entities based on interactions of the respective entity associated with the sub-module; a module editor for forming, in each sub-module, representations of behaviors of the respective entity and logical relations among the behaviors, and building links between the interfaces to other entities and the representation of the behaviors; and wherein said model framework generator automatically builds a plurality of sub-modules and further comprising an integrated process assembler for integrating the plurality of sub-modules depicted in a local view based on the interactions described in said abstract view to automatically form a global view. | 14. A system modeling facilitating apparatus, comprising: an input device for receiving information input by users, said information comprising entities and interactions among entities of a system; a storage device for storing information input by users and received from the input device, and diagram data formed by the system modeling facilitating apparatus; a display device for displaying information and diagram data; an abstract view editor for editing an abstract view, said view comprising entities and interactions among the entities; a module framework generator for building a sub-module for at least one of the entities, each sub-module being associated with a respective entity; an interface forming device for forming interfaces for each sub-module to other entities based on interactions of the respective entity associated with the sub-module; a module editor for forming, in each sub-module, representations of behaviors of the respective entity and logical relations among the behaviors, and building links between the interfaces to other entities and the representation of the behaviors; and wherein said model framework generator automatically builds a plurality of sub-modules and further comprising an integrated process assembler for integrating the plurality of sub-modules depicted in a local view based on the interactions described in said abstract view to automatically form a global view. 16. The system modeling facilitating apparatus of claim 14 , further comprising an interface automatic updating device for, when a change is made to a part of said view, said interface automatic updating device automatically updates interfaces to other entities associated with the change. | 0.501724 |
9,953,265 | 16 | 17 | 16. The computer program product of claim 15 , further comprising: program instructions to determine a plurality of links to evidence, a plurality of definitions, and a plurality of activity related to each answer within the compiled set of answers. | 16. The computer program product of claim 15 , further comprising: program instructions to determine a plurality of links to evidence, a plurality of definitions, and a plurality of activity related to each answer within the compiled set of answers. 17. The computer program product of claim 16 , wherein the characterization summary for the compiled set of answers comprises at least one of the determined plurality of links to evidence, the determined plurality of definitions, and the determined plurality of activity related to each answer within the compiled set of answers. | 0.901732 |
8,850,401 | 1 | 4 | 1. A method of monitoring a software system, wherein the method comprises: monitoring the software system using an ontology driven approach based on a service oriented architecture (SOA) comprising components of the software system communicating with each other via exchanging messages, wherein said monitoring comprises: receiving a monitoring message by a monitoring component, wherein the monitoring message is sent from a component of the software system; providing an ontology comprising at least one interpretation rule for the monitoring message by the monitoring component, wherein the ontology comprises a model of at least a subset of the world, wherein the ontology models the at least a subset of the world by establishing concepts of objects and classes with properties and relations among each other, and wherein the at least one interpretation rule of the ontology is dynamically adaptable via changes to the ontology without requiring changes to the monitoring component; and reacting, by the monitoring component, in accordance with the at least one interpretation rule of the ontology. | 1. A method of monitoring a software system, wherein the method comprises: monitoring the software system using an ontology driven approach based on a service oriented architecture (SOA) comprising components of the software system communicating with each other via exchanging messages, wherein said monitoring comprises: receiving a monitoring message by a monitoring component, wherein the monitoring message is sent from a component of the software system; providing an ontology comprising at least one interpretation rule for the monitoring message by the monitoring component, wherein the ontology comprises a model of at least a subset of the world, wherein the ontology models the at least a subset of the world by establishing concepts of objects and classes with properties and relations among each other, and wherein the at least one interpretation rule of the ontology is dynamically adaptable via changes to the ontology without requiring changes to the monitoring component; and reacting, by the monitoring component, in accordance with the at least one interpretation rule of the ontology. 4. The method of claim 1 , wherein said reacting comprises modifying the ontology. | 0.895408 |
8,225,408 | 24 | 25 | 24. The method of claim 23 wherein said dynamically building comprises positioning nodes of the parse tree corresponding to rules as parent nodes, the children of which correspond to the tokens within the patterns that correspond to the rules. | 24. The method of claim 23 wherein said dynamically building comprises positioning nodes of the parse tree corresponding to rules as parent nodes, the children of which correspond to the tokens within the patterns that correspond to the rules. 25. The method of claim 24 wherein said dynamically building comprises adding a new parent node to the parse tree when a rule is matched. | 0.965211 |
8,161,066 | 2 | 38 | 2. A method for creating a semantic object to represent a target referent of an object type, the semantic object being stored on a computer readable medium, the method, comprising, creating the semantic object of a semantic object type to represent the target referent of the object type, the semantic object having multiple meta-tags that are each associable with metadata; wherein, the semantic object of the semantic object type is suitable to represent the object type of the target referent; associating a meta-tag of the multiple meta-tags with the metadata; wherein the meta-tag or the metadata is definable using an ontology; and extracting a portion of the content from the target referent for inclusion in the semantic object; subsequently determining that the target referent has been revised, updating metadata associated with one or more meta-taps of the multiple meta-taps of the semantic object based on the revision; wherein the extraction is part of a data mining performed on selected resources including the ontology or the Internet. sharing, with another user, the semantic object having included therein the portion of the content extracted from the target referent. | 2. A method for creating a semantic object to represent a target referent of an object type, the semantic object being stored on a computer readable medium, the method, comprising, creating the semantic object of a semantic object type to represent the target referent of the object type, the semantic object having multiple meta-tags that are each associable with metadata; wherein, the semantic object of the semantic object type is suitable to represent the object type of the target referent; associating a meta-tag of the multiple meta-tags with the metadata; wherein the meta-tag or the metadata is definable using an ontology; and extracting a portion of the content from the target referent for inclusion in the semantic object; subsequently determining that the target referent has been revised, updating metadata associated with one or more meta-taps of the multiple meta-taps of the semantic object based on the revision; wherein the extraction is part of a data mining performed on selected resources including the ontology or the Internet. sharing, with another user, the semantic object having included therein the portion of the content extracted from the target referent. 38. The method of claim 2 , further comprising, exchanging information about the ontology using the semantic object. | 0.892193 |
7,831,584 | 12 | 14 | 12. The method of claim 11 , further comprising: receiving, from the user, additional input to the partial search query, wherein said additional input further defines said partial search query; lexographically matching said further defined partial search query with said subset of said index to form a narrowed subset of said index; performing said step of ranking with said narrowed subset; and displaying said ranked list. | 12. The method of claim 11 , further comprising: receiving, from the user, additional input to the partial search query, wherein said additional input further defines said partial search query; lexographically matching said further defined partial search query with said subset of said index to form a narrowed subset of said index; performing said step of ranking with said narrowed subset; and displaying said ranked list. 14. The method of claim 12 , further comprising: reiterating said steps of receiving additional input, lexographically matching, ranking, and displaying until the user selects a product from said ranked list. | 0.884316 |
9,305,090 | 15 | 16 | 15. A system, comprising: at least one computing device comprising a processor and a memory; and an application executable in the at least one computing device, the application causing the at least one computing device to at least: request a plurality of suggested keywords from a server in response to user input submitted through a query form, wherein at least one of the plurality of suggested keywords is based at least in part on a shopping history associated with a user account corresponding to an electronic commerce application or a popularity of an item offered for sale through the electronic commerce application and at least one of the plurality of suggested keywords comprises at least one enhanced suggested keyword, the at least one enhanced suggested keyword including at least one spelling correction to the user input; determine a number of a plurality of speculative search queries, the number of the plurality of speculative search queries being determined based at least in part on a length of time that the user account has been associated with the electronic commerce application; provide the plurality of speculative search queries to the server, wherein individual ones of the plurality of speculative search queries comprise at least one of the plurality of suggested keywords, and wherein individual ones of the plurality of speculative search queries that include the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword are weighted higher than individual ones of the plurality of speculative search queries that fail to include any of the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword, wherein the weights of the suggested keywords are used to prefer the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword over individual ones of the plurality of speculative search queries that fail to include the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword when determining suggested keywords to include in the speculative search queries; render, in a hidden portion of a browser window, at least a portion of at least two of a plurality of speculative search results, the at least two of the plurality of speculative search results correspond to at least one of the plurality of speculative search queries; move the rendered portion of the at least two of the plurality of speculative search results from the hidden portion of the browser window to a visible portion of the browser window; render the portion of the at least two of the plurality of speculative search results in the visible portion of the browser window in response to receiving a user instruction to execute a committed search query that includes a suggested keyword from the at least one of the plurality of speculative queries; and render, in the visible portion of the browser window, a remaining portion of the plurality of speculative search results from at least one of the plurality of speculative search queries, in response to receiving the remaining portion of results from the server. | 15. A system, comprising: at least one computing device comprising a processor and a memory; and an application executable in the at least one computing device, the application causing the at least one computing device to at least: request a plurality of suggested keywords from a server in response to user input submitted through a query form, wherein at least one of the plurality of suggested keywords is based at least in part on a shopping history associated with a user account corresponding to an electronic commerce application or a popularity of an item offered for sale through the electronic commerce application and at least one of the plurality of suggested keywords comprises at least one enhanced suggested keyword, the at least one enhanced suggested keyword including at least one spelling correction to the user input; determine a number of a plurality of speculative search queries, the number of the plurality of speculative search queries being determined based at least in part on a length of time that the user account has been associated with the electronic commerce application; provide the plurality of speculative search queries to the server, wherein individual ones of the plurality of speculative search queries comprise at least one of the plurality of suggested keywords, and wherein individual ones of the plurality of speculative search queries that include the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword are weighted higher than individual ones of the plurality of speculative search queries that fail to include any of the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword, wherein the weights of the suggested keywords are used to prefer the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword over individual ones of the plurality of speculative search queries that fail to include the at least one of the plurality of suggested keywords that comprises the at least one enhanced suggested keyword when determining suggested keywords to include in the speculative search queries; render, in a hidden portion of a browser window, at least a portion of at least two of a plurality of speculative search results, the at least two of the plurality of speculative search results correspond to at least one of the plurality of speculative search queries; move the rendered portion of the at least two of the plurality of speculative search results from the hidden portion of the browser window to a visible portion of the browser window; render the portion of the at least two of the plurality of speculative search results in the visible portion of the browser window in response to receiving a user instruction to execute a committed search query that includes a suggested keyword from the at least one of the plurality of speculative queries; and render, in the visible portion of the browser window, a remaining portion of the plurality of speculative search results from at least one of the plurality of speculative search queries, in response to receiving the remaining portion of results from the server. 16. The system of claim 15 , wherein the application further causes the at least one computing device to at least request a remaining portion of at least one of the plurality of speculative search results. | 0.849486 |
8,150,694 | 15 | 17 | 15. The computer-readable storage medium of claim 13 , wherein the acoustic elements associated with the one or more syllable data objects divide the one or more syllable data objects into one or more core components. | 15. The computer-readable storage medium of claim 13 , wherein the acoustic elements associated with the one or more syllable data objects divide the one or more syllable data objects into one or more core components. 17. The computer-readable storage medium of claim 15 , wherein the acoustic elements associated with the one or more syllable data objects further divide the one or more core components associated with the one or more syllable data objects into one or more sub-categories. | 0.859067 |
9,330,138 | 15 | 20 | 15. A system, comprising: a processing module comprising a non-transitory computer readable medium storing instructions that, when executed, cause the system to: receive a first query that is associated with a first type of database; translate, using primitives, the first query into an edge query that is associated with a graph database storing a graph, wherein: the first type of database has a different data model than the graph database; the graph comprises nodes, edges between the nodes, and predicates to represent and store data with index-free adjacency; and the primitives include: a rule based on edges in the graph that expresses a relational schema in the first type of database, and information associated with a compound key that specifies a relationship between the nodes, the edges and the predicates in the graph corresponding to a table in the first type of database; execute the edge query against the graph database, wherein the edge query identifies an edge associated with a predicate that specifies one or more of the nodes in the graph; and receive a result in response to the edge query, wherein the result includes a subset of the graph. | 15. A system, comprising: a processing module comprising a non-transitory computer readable medium storing instructions that, when executed, cause the system to: receive a first query that is associated with a first type of database; translate, using primitives, the first query into an edge query that is associated with a graph database storing a graph, wherein: the first type of database has a different data model than the graph database; the graph comprises nodes, edges between the nodes, and predicates to represent and store data with index-free adjacency; and the primitives include: a rule based on edges in the graph that expresses a relational schema in the first type of database, and information associated with a compound key that specifies a relationship between the nodes, the edges and the predicates in the graph corresponding to a table in the first type of database; execute the edge query against the graph database, wherein the edge query identifies an edge associated with a predicate that specifies one or more of the nodes in the graph; and receive a result in response to the edge query, wherein the result includes a subset of the graph. 20. The system of claim 15 , wherein the non-transitory computer readable medium further stores instructions that, when executed, cause the system to determine the primitives. | 0.822874 |
9,990,191 | 4 | 5 | 4. A computer network system including one or more databases communicating over the computer network for translating software, the system comprising: one or more central processing units (CPU); a first database executing instructions in the one or more CPUs to store software for one or more applications and having a first buffer that stores content selected for translation, wherein the first database stores, from one or more third-party application developers, software applications that require translation, wherein one or more languages selected for translation are selected by the one or more third-party application developers; a second database executing instructions in the one or more CPUs to receive the content stored in the first buffer of the first database and to store profiles associated with one or more translators; a notification component executing instructions in the CPU to notify the one or more translators of content stored in the second database that matches a language stored in the profiles corresponding to the one or more translators; and a second buffer executing instructions in the one or more CPUs to receive translated content and to store the translated updated content for verification, wherein the second buffer is isolated from the first database that includes one or more software development files corresponding to the one or more applications. | 4. A computer network system including one or more databases communicating over the computer network for translating software, the system comprising: one or more central processing units (CPU); a first database executing instructions in the one or more CPUs to store software for one or more applications and having a first buffer that stores content selected for translation, wherein the first database stores, from one or more third-party application developers, software applications that require translation, wherein one or more languages selected for translation are selected by the one or more third-party application developers; a second database executing instructions in the one or more CPUs to receive the content stored in the first buffer of the first database and to store profiles associated with one or more translators; a notification component executing instructions in the CPU to notify the one or more translators of content stored in the second database that matches a language stored in the profiles corresponding to the one or more translators; and a second buffer executing instructions in the one or more CPUs to receive translated content and to store the translated updated content for verification, wherein the second buffer is isolated from the first database that includes one or more software development files corresponding to the one or more applications. 5. The computer network system of claim 4 , wherein the first database and the second database are one database. | 0.806228 |
9,552,349 | 5 | 7 | 5. The method of claim 2 , further comprising the steps of generating one or more distance one variants of said at least one candidate word and testing said distance one variants against one or more of said dictionary hash table and said at least one variant dictionary hash table, and accumulating matches. | 5. The method of claim 2 , further comprising the steps of generating one or more distance one variants of said at least one candidate word and testing said distance one variants against one or more of said dictionary hash table and said at least one variant dictionary hash table, and accumulating matches. 7. The method of claim 5 , wherein said one or more distance one variants comprises single character wild card replacements of said at least one candidate word obtained by generating variants of said at least one candidate word by replacing any one character in said at least one candidate word with a chosen wild card character and leaving other characters unchanged, thereby generating W variants of said at least one candidate word of length W. | 0.902188 |
9,271,130 | 10 | 11 | 10. The system of claim 1 , wherein at least one of the first profile and the second profile is accessible by the first user using any one of a plurality of devices. | 10. The system of claim 1 , wherein at least one of the first profile and the second profile is accessible by the first user using any one of a plurality of devices. 11. The system of claim 10 , wherein the processor is further configured to register at least one of the plurality of devices for use with the account. | 0.947313 |
9,411,802 | 7 | 11 | 7. The method of claim 1 , wherein the performance of the joint inference in step 4 produces an SRL result on a source side and an SRL result on a target side and the joint interference is based on: a correctness of the SRL result on the source side, a correctness of the SRL result on the target side, and an argument structure consistency between the SRL results on the source side and the target side. | 7. The method of claim 1 , wherein the performance of the joint inference in step 4 produces an SRL result on a source side and an SRL result on a target side and the joint interference is based on: a correctness of the SRL result on the source side, a correctness of the SRL result on the target side, and an argument structure consistency between the SRL results on the source side and the target side. 11. The method of claim 7 , wherein when considering the argument structure consistency between the SRL results on the source side and the target side, the objective is to maximize a number of correctly aligned arguments, and plurality of constraints comprise: 1) Conformity with bilingual SRL result: For all candidates on both source and target sides, only those that are chosen to be arguments on each side are aligned; 2) One-to-many alignment limit: An argument cannot align with more than three arguments; and 3) Complete argument alignment: Each argument on the source side is aligned with at least one argument on the target side, and vice versa, wherein a penalty is induced when this constraint is violated. | 0.812008 |
9,311,499 | 1 | 17 | 1. A computerized method of securing data in a plurality of security controlled data stores with access controls thereat, each data store having a defined security level, said data potentially having sensitive content defined as sensitive words, data objects, characters, images, data elements or icons, comprising: separately storing sensitive content in secure data stores of said plurality of security data stores at the respective defined security level for said sensitive content; permitting reconstruction of some or all of said data with appropriate access controls applied to respective secure data stores; and said storing or reconstruction based upon (i) territorial protocol and a geographic location signal or (ii) a triggering event; and at least one of: prior to storing, at least one or more of tagging, labeling, or classifying said sensitive content in said secure data stores; or concurrent with storing, at least one or more of tagging, labeling, or classifying said sensitive content in said secure data stores. | 1. A computerized method of securing data in a plurality of security controlled data stores with access controls thereat, each data store having a defined security level, said data potentially having sensitive content defined as sensitive words, data objects, characters, images, data elements or icons, comprising: separately storing sensitive content in secure data stores of said plurality of security data stores at the respective defined security level for said sensitive content; permitting reconstruction of some or all of said data with appropriate access controls applied to respective secure data stores; and said storing or reconstruction based upon (i) territorial protocol and a geographic location signal or (ii) a triggering event; and at least one of: prior to storing, at least one or more of tagging, labeling, or classifying said sensitive content in said secure data stores; or concurrent with storing, at least one or more of tagging, labeling, or classifying said sensitive content in said secure data stores. 17. A computerized method of securing data as claimed in claim 1 wherein said sensitive content is at least one or more of: select sensitive words, data objects, characters, images, data elements or icons; defined sensitive words, data objects, characters, images, data elements or icons; known sensitive words, data objects, characters, images, data elements or icons; certain sensitive words, data objects, characters, images, data elements or icons; a collection of sensitive words, data objects, characters, images, data elements or icons; a plurality of predetermined sensitive words, data objects, characters, images, data elements or icons; or a plurality of predetermined sensitive words, data objects, characters, images, data elements or icons having different hierarchal or orthogonal levels of sensitive content. | 0.500606 |
9,293,061 | 1 | 8 | 1. A method for creating a mnemonic experience for a user, which comprises: selecting a concentration of information to be remembered; gathering information on said concentration, said information being intended to be remembered by the user; providing a building; placing a display to be observed in said building, said display teaching said information when observed by the user; providing a character to interact with the user and said display, said character being contextually related to said display; interacting said character with the user with while the user observes said display; gathering further information on said concentration; determining an importance of said information relative to an importance of said further information; and not creating a display of said further information when said importance of said further information is less than the importance of said piece of information. | 1. A method for creating a mnemonic experience for a user, which comprises: selecting a concentration of information to be remembered; gathering information on said concentration, said information being intended to be remembered by the user; providing a building; placing a display to be observed in said building, said display teaching said information when observed by the user; providing a character to interact with the user and said display, said character being contextually related to said display; interacting said character with the user with while the user observes said display; gathering further information on said concentration; determining an importance of said information relative to an importance of said further information; and not creating a display of said further information when said importance of said further information is less than the importance of said piece of information. 8. The method according to claim 1 , which further comprises: providing a room within said building; and disposing said display in said room. | 0.905369 |
8,640,030 | 1 | 5 | 1. A method for creating tag information for synchronized presentation of a tag during playback of a video on a display screen, the method comprising: in response to receipt, during playback of the video, of a first signal indicating a first position of the tag with respect to the video, associating a first time with the first position, wherein the first time indicates a temporal point in playback of the video; in response to receipt, during playback of the video, of a second signal indicating a second position of the tag with respect to the video, associating a second time with the second position, wherein the second time indicates a temporal point in playback of the video; and creating one or more files that collectively include the first and second times and positions in association with tag design information, wherein the tag design information specifies a rendering of the tag when the tag is displayed in synchronization with subsequent playback of the video, wherein synchronization is according to the first and second times and positions so that the tag moves across the display screen from the first position to the second position during video playback. | 1. A method for creating tag information for synchronized presentation of a tag during playback of a video on a display screen, the method comprising: in response to receipt, during playback of the video, of a first signal indicating a first position of the tag with respect to the video, associating a first time with the first position, wherein the first time indicates a temporal point in playback of the video; in response to receipt, during playback of the video, of a second signal indicating a second position of the tag with respect to the video, associating a second time with the second position, wherein the second time indicates a temporal point in playback of the video; and creating one or more files that collectively include the first and second times and positions in association with tag design information, wherein the tag design information specifies a rendering of the tag when the tag is displayed in synchronization with subsequent playback of the video, wherein synchronization is according to the first and second times and positions so that the tag moves across the display screen from the first position to the second position during video playback. 5. The method of claim 1 , further comprising: causing display of one or more user controls to enable animating a tag. | 0.838356 |
8,484,024 | 13 | 17 | 13. A system, comprising: a memory; and a processor operatively coupled to the memory and configured to: obtain a first dictionary and a training data set associated with a speech recognition system; compute one or more support parameters from the training data set; transform the first dictionary into a second dictionary, wherein the second dictionary is a function of one or more phonetic labels of the first dictionary; and use the one or more support parameters to select one or more samples from the second dictionary to create a set of one or more exemplar-based class identification features for a pattern recognition task; and use the set of one or more exemplar-based class identification features to perform a pattern recognition task, said step comprising defining a sensitivity matrix to contain one or more exemplars from the training data set. | 13. A system, comprising: a memory; and a processor operatively coupled to the memory and configured to: obtain a first dictionary and a training data set associated with a speech recognition system; compute one or more support parameters from the training data set; transform the first dictionary into a second dictionary, wherein the second dictionary is a function of one or more phonetic labels of the first dictionary; and use the one or more support parameters to select one or more samples from the second dictionary to create a set of one or more exemplar-based class identification features for a pattern recognition task; and use the set of one or more exemplar-based class identification features to perform a pattern recognition task, said step comprising defining a sensitivity matrix to contain one or more exemplars from the training data set. 17. The system of claim 13 , wherein the using the set of one or more exemplar-based class identification features to perform a pattern recognition task step further comprises using the set of one or more exemplar-based class identification features for at least one of speech recognition, text classification and speaker recognition. | 0.659184 |
8,965,971 | 21 | 22 | 21. The system of claim 14 , wherein the input source corresponds to at least one metadata source and the processing comprises: extracting metadata from the metadata source; and processing the metadata to create extracted information based on the metadata source. | 21. The system of claim 14 , wherein the input source corresponds to at least one metadata source and the processing comprises: extracting metadata from the metadata source; and processing the metadata to create extracted information based on the metadata source. 22. The system of claim 21 , wherein the extracted information comprises GPS coordinates related to the metadata source. | 0.949367 |
9,053,489 | 1 | 4 | 1. A computer-implemented method comprising: as implemented by one or more computing devices configured with specific computer-executable instructions, receiving a message from a sender communication device, wherein the message is configured to be sent to a recipient communication device using an identifier of the recipient communication device; identifying a word, for which advertising is available, from the message; receiving geographical location information from the recipient communication device; determining temporal information pertaining to the recipient communication device based at least on the geographical location information received from the recipient communication device; sending the word identified from the message and the temporal information to a third party; obtaining a plurality of advertisements from the third party based at least in part on the word identified in the message and the temporal information, wherein each advertisement of the plurality of advertisements is associated with a respective payment level, and wherein each respective payment level is based at least in part on the temporal information pertaining to the recipient communication device; associating in a data store of the one or more computing devices the word identified in the message with the plurality of advertisements and the identifier of the recipient communication device, wherein the one or more computing devices are remote from the sender communication device and the recipient communication device; sending the message to the recipient communication device; receiving, from the recipient communication device, the identifier of the recipient communication device; receiving, from the recipient communication device, a transcribed utterance that includes the word identified in the message; selecting at least one advertisement of the plurality of advertisements, wherein the selecting is based at least in part on the respective payment level of the at least one advertisement; and based at least in part on the word identified in the message being present in the transcribed utterance and being associated with the plurality of advertisements and the identifier of the recipient communication device, sending the at least one advertisement to the recipient communication device using the identifier of the recipient communication device. | 1. A computer-implemented method comprising: as implemented by one or more computing devices configured with specific computer-executable instructions, receiving a message from a sender communication device, wherein the message is configured to be sent to a recipient communication device using an identifier of the recipient communication device; identifying a word, for which advertising is available, from the message; receiving geographical location information from the recipient communication device; determining temporal information pertaining to the recipient communication device based at least on the geographical location information received from the recipient communication device; sending the word identified from the message and the temporal information to a third party; obtaining a plurality of advertisements from the third party based at least in part on the word identified in the message and the temporal information, wherein each advertisement of the plurality of advertisements is associated with a respective payment level, and wherein each respective payment level is based at least in part on the temporal information pertaining to the recipient communication device; associating in a data store of the one or more computing devices the word identified in the message with the plurality of advertisements and the identifier of the recipient communication device, wherein the one or more computing devices are remote from the sender communication device and the recipient communication device; sending the message to the recipient communication device; receiving, from the recipient communication device, the identifier of the recipient communication device; receiving, from the recipient communication device, a transcribed utterance that includes the word identified in the message; selecting at least one advertisement of the plurality of advertisements, wherein the selecting is based at least in part on the respective payment level of the at least one advertisement; and based at least in part on the word identified in the message being present in the transcribed utterance and being associated with the plurality of advertisements and the identifier of the recipient communication device, sending the at least one advertisement to the recipient communication device using the identifier of the recipient communication device. 4. The computer-implemented method of claim 1 , wherein a content of the at least one advertisement is based at least in part on information about a user of the recipient communication device. | 0.764128 |
7,747,617 | 1 | 7 | 1. A method in a computing system for generating a dimensional model of a plurality of documents, comprising: initializing a dimensional model comprising a fact table and a plurality of dimension tables; for each of the plurality of documents, obtaining one or more attribute values associated with the document, each for a document attribute; adding a row for the document to the fact table; storing in the row added to the fact table a reference to the document; for each attribute for which an attribute value was extracted, storing in the row added to the fact table a reference to a row corresponding to the attribute value in a dimension table corresponding to the attribute; and in response to receiving a search request specifying a search request attribute value for one or more of the attributes, generating a search result by joining selected rows of the dimension tables corresponding to each attribute for which a search request attribute value is specified to the fact table to produce a join result, the search result including the document references contained by the rows of the join result. | 1. A method in a computing system for generating a dimensional model of a plurality of documents, comprising: initializing a dimensional model comprising a fact table and a plurality of dimension tables; for each of the plurality of documents, obtaining one or more attribute values associated with the document, each for a document attribute; adding a row for the document to the fact table; storing in the row added to the fact table a reference to the document; for each attribute for which an attribute value was extracted, storing in the row added to the fact table a reference to a row corresponding to the attribute value in a dimension table corresponding to the attribute; and in response to receiving a search request specifying a search request attribute value for one or more of the attributes, generating a search result by joining selected rows of the dimension tables corresponding to each attribute for which a search request attribute value is specified to the fact table to produce a join result, the search result including the document references contained by the rows of the join result. 7. The method of claim 1 wherein the each reference to a document stored in a row of the fact table is a description of how to retrieve the referenced document. | 0.897304 |
5,572,650 | 1 | 2 | 1. A method for displaying information about a relational database comprising the steps of: identifying each relation of a plurality of relations in the relational database; determining for each relation a respective number of occurrences of a specific data item contained therein; determining for each relation a key structural characteristic which can be used to access that relation; categorizing each relation of the plurality of relations according to key structural characteristics of the respective relation; visually displaying the plurality of relations in categories according to the key structural characteristics thereof; visually displaying for each relation of the plurality of relations a respective bar that is representative of the number of occurrences of the specific data item contained therein; coloring each display of each relation that has the same key structural characteristic with a common color that is different from the coloring of the relations of the other key structural characteristics; visually displaying a cursor that is operator controllable over the display area; and changing the coloring of a visual display of a relation with which the cursor is actively contacting to indicate a selection thereof for a display of further information. | 1. A method for displaying information about a relational database comprising the steps of: identifying each relation of a plurality of relations in the relational database; determining for each relation a respective number of occurrences of a specific data item contained therein; determining for each relation a key structural characteristic which can be used to access that relation; categorizing each relation of the plurality of relations according to key structural characteristics of the respective relation; visually displaying the plurality of relations in categories according to the key structural characteristics thereof; visually displaying for each relation of the plurality of relations a respective bar that is representative of the number of occurrences of the specific data item contained therein; coloring each display of each relation that has the same key structural characteristic with a common color that is different from the coloring of the relations of the other key structural characteristics; visually displaying a cursor that is operator controllable over the display area; and changing the coloring of a visual display of a relation with which the cursor is actively contacting to indicate a selection thereof for a display of further information. 2. The method as set forth in claim 1, further comprising the step of: displaying an additional view in an active window displaying further information about the cursor-selected relation. | 0.85961 |
8,903,924 | 15 | 16 | 15. A computer system, comprising: a processor; a memory; and a program comprising a plurality of instructions stored in the memory that are executed by the processor to: detect receipt of text-based electronic communications; identify first data of interest with a predetermined characteristic in the text-based electronic communications; extract, from a plurality of text-based electronic communications, a plurality of instances of the identified first data of interest from the text-based electronic communications, at least two of the text-based electronic communications sent to different intended recipients, wherein each text-based electronic communication includes first data of interest with a common predetermined characteristic, and wherein each text-based electronic communication includes first data or interest differing from first data of interest of other text-based electronic communications, the computer system associated with sending the one or more text-based electronic communications; obtain, for each identified first data of interest, a first set of associated data that is associated with the extracted first data of interest, each initial first set of associated data from at least one electronic resource; and display, independent of the text-based electronic communications and the at least one electronic resource, a plurality of instances of the extracted first data of interest, each instance of the extracted first data of interest displayed with the corresponding first set of associated data. | 15. A computer system, comprising: a processor; a memory; and a program comprising a plurality of instructions stored in the memory that are executed by the processor to: detect receipt of text-based electronic communications; identify first data of interest with a predetermined characteristic in the text-based electronic communications; extract, from a plurality of text-based electronic communications, a plurality of instances of the identified first data of interest from the text-based electronic communications, at least two of the text-based electronic communications sent to different intended recipients, wherein each text-based electronic communication includes first data of interest with a common predetermined characteristic, and wherein each text-based electronic communication includes first data or interest differing from first data of interest of other text-based electronic communications, the computer system associated with sending the one or more text-based electronic communications; obtain, for each identified first data of interest, a first set of associated data that is associated with the extracted first data of interest, each initial first set of associated data from at least one electronic resource; and display, independent of the text-based electronic communications and the at least one electronic resource, a plurality of instances of the extracted first data of interest, each instance of the extracted first data of interest displayed with the corresponding first set of associated data. 16. The computer system of claim 15 , wherein the plurality of instructions further comprises instructions that are executed by the processor to obtain, from at least one electronic resource, a first set of associated data that is associated with the extracted first data of interest, second data of interest comprises the common predetermined characteristic, and a second set of associated data that is associated with the second data of interest, and to display, independent of the text-based electronic communications and the at least one electronic resource, the extracted first data of interest, the obtained first set of associated data, the obtained second data of interest, and the obtained second set of associated data. | 0.695997 |
8,849,665 | 21 | 22 | 21. The computer-readable storage device of claim 19 , wherein the finite state acceptor comprises two nodes, wherein each of the two nodes is connected to another node with an edge that represents an n-gram. | 21. The computer-readable storage device of claim 19 , wherein the finite state acceptor comprises two nodes, wherein each of the two nodes is connected to another node with an edge that represents an n-gram. 22. The computer-readable storage device of claim 21 , wherein each of the two nodes represents an n−1 length word history, and wherein the edge is labeled with a word that follows the n−1 length word history. | 0.867386 |
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