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8,375,069 | 7 | 9 | 7. A user-interface system for presenting a collection of items in which the presentation is ordered at least in part based on navigation and selection behavior of a user learned over time, the system comprising: logic for providing access to a set of items; logic for associating an initial relevance weight with each of a plurality of the items of the set; logic for receiving input entered by the user for identifying desired items; logic, responsive to the input entered by the user, for selecting and presenting a subset of items to the user in a first presentation order of items browsable by the user wherein the arrangement of items within the first presentation order is based at least in part on the initial associated relevance weights associated with the items; logic for receiving input entered by the user for browsing through the first presentation order of items and for identifying and selecting the desired items; logic, responsive to a selection by the user of an item, for presenting said item to the user and for adjusting the associated relevance weight of said item; logic for selecting and presenting a subset of items to the user in a second presentation order subsequent to adjusting the associated relevance weight of any of the items, wherein the arrangement of items within the second presentation order is based at least in part on the adjusted associated relevance weights assigned to the items. | 7. A user-interface system for presenting a collection of items in which the presentation is ordered at least in part based on navigation and selection behavior of a user learned over time, the system comprising: logic for providing access to a set of items; logic for associating an initial relevance weight with each of a plurality of the items of the set; logic for receiving input entered by the user for identifying desired items; logic, responsive to the input entered by the user, for selecting and presenting a subset of items to the user in a first presentation order of items browsable by the user wherein the arrangement of items within the first presentation order is based at least in part on the initial associated relevance weights associated with the items; logic for receiving input entered by the user for browsing through the first presentation order of items and for identifying and selecting the desired items; logic, responsive to a selection by the user of an item, for presenting said item to the user and for adjusting the associated relevance weight of said item; logic for selecting and presenting a subset of items to the user in a second presentation order subsequent to adjusting the associated relevance weight of any of the items, wherein the arrangement of items within the second presentation order is based at least in part on the adjusted associated relevance weights assigned to the items. 9. The system of claim 7 , further comprising: logic for organizing the set of items into nodes based on the information content of the items; logic for associating an initial relevance weight with at least one of the nodes; and logic, responsive to the selection by the user of an item, for adjusting the relevance weight associated with the node containing the selected item; wherein the logic for selecting and presenting a subset of items to the user in a first presentation order of items includes logic for selecting and presenting a subset of nodes within the first presentation order, wherein the selection and arrangement of the nodes within the first presentation order is based at least in part on the initial relevance weights associated with the nodes; and wherein the logic for selecting and presenting a subset of items to the user in a second presentation order of items includes logic for selecting and presenting a subset of nodes within the second presentation order, wherein the selection and arrangement of the nodes within the second presentation order is based at least in part on the adjusted relevance weights associated with the nodes. | 0.5 |
7,539,854 | 22 | 26 | 22. The machine accessible storage medium as recited in claim 16 , wherein the instructions further cause the machine to: extend a language construct with a scripting language; parse the scripting language by a script engine; and if the script engine is not running, ignore scripting language elements. | 22. The machine accessible storage medium as recited in claim 16 , wherein the instructions further cause the machine to: extend a language construct with a scripting language; parse the scripting language by a script engine; and if the script engine is not running, ignore scripting language elements. 26. The machine accessible storage medium as recited in claim 22 , wherein the instructions further cause the machine to initiate a warm reset of the computer system in response to changing configuration settings. | 0.693966 |
9,336,295 | 1 | 2 | 1. A method for performing context inference in a mobile device, the method comprising: receiving, at a classifier implemented in one or more integrated circuits of the mobile device, sensor data from at least one data source associated with the mobile device, wherein the at least one data source comprises one or more sensors of the mobile device; determining, by the classifier implemented in the one or more integrated circuits, a first context class for the received sensor data, the first context class corresponding to a context state indicated by the received sensor data; determining, by the classifier implemented in the one or more integrated circuits, that a confidence value associated with the determination of the first context class is below a threshold value; creating, by the classifier implemented in the one or more integrated circuits, a fusion class for the received sensor data at least in part by fusing the first context class for the received sensor data and at least a second context class for the received sensor data, the at least the second context class being different from the first context class, wherein the fusion class semantically encompasses the first context class and the at least the second context class and further wherein the fusion class is broader than each of the first context class and the at least the second context class; substituting, by the classifier implemented in the one or more integrated circuits, the fusion class for the first context class; and outputting, by the classifier implemented in the one or more integrated circuits, the fusion class as the inferred context of the mobile device. | 1. A method for performing context inference in a mobile device, the method comprising: receiving, at a classifier implemented in one or more integrated circuits of the mobile device, sensor data from at least one data source associated with the mobile device, wherein the at least one data source comprises one or more sensors of the mobile device; determining, by the classifier implemented in the one or more integrated circuits, a first context class for the received sensor data, the first context class corresponding to a context state indicated by the received sensor data; determining, by the classifier implemented in the one or more integrated circuits, that a confidence value associated with the determination of the first context class is below a threshold value; creating, by the classifier implemented in the one or more integrated circuits, a fusion class for the received sensor data at least in part by fusing the first context class for the received sensor data and at least a second context class for the received sensor data, the at least the second context class being different from the first context class, wherein the fusion class semantically encompasses the first context class and the at least the second context class and further wherein the fusion class is broader than each of the first context class and the at least the second context class; substituting, by the classifier implemented in the one or more integrated circuits, the fusion class for the first context class; and outputting, by the classifier implemented in the one or more integrated circuits, the fusion class as the inferred context of the mobile device. 2. The method of claim 1 wherein the at least one data source comprises one or more of an audio sensor, a transceiver, a motion sensor, a clock, a device usage sensor, a light sensor, a camera, or a calendar. | 0.711911 |
4,438,505 | 7 | 11 | 7. An electronic word conversion device wherein a first word or words represented in a first language are entered to obtain a second word or words represented in a second language equivalent to the first word or words, comprising: input means operable for entering a partial word containing at least one character; memory means for storing a plurality of full-length words and their associated translated words; address means for accessing said memory means; activate means for enabling said address means; auto-search means selectively driving said activate means to repetitively drive said address means so that a plurality of full-length words having one or more characters common to the partial word, and their associated translated words corresponding to the full-length words may be selected, said continuous activation of said address means occurring in response to a single actuation of an auto-search key; auto-search enable flip-flop being set to selectively activate said auto-search means; said device, when said auto-search means is disabled by resetting said flip-flop to place said drive in a simple scanning mode, displaying only a single full-length word and its associated translation; and display means for displaying said full-length words and then associated translated words. | 7. An electronic word conversion device wherein a first word or words represented in a first language are entered to obtain a second word or words represented in a second language equivalent to the first word or words, comprising: input means operable for entering a partial word containing at least one character; memory means for storing a plurality of full-length words and their associated translated words; address means for accessing said memory means; activate means for enabling said address means; auto-search means selectively driving said activate means to repetitively drive said address means so that a plurality of full-length words having one or more characters common to the partial word, and their associated translated words corresponding to the full-length words may be selected, said continuous activation of said address means occurring in response to a single actuation of an auto-search key; auto-search enable flip-flop being set to selectively activate said auto-search means; said device, when said auto-search means is disabled by resetting said flip-flop to place said drive in a simple scanning mode, displaying only a single full-length word and its associated translation; and display means for displaying said full-length words and then associated translated words. 11. The device of claim 7 further comprising: translation enable means for selectively enabling the displaying of said associated translated words by said display means, the display of said associated translated words being enabled by actuation of a translation key. | 0.721174 |
8,176,413 | 1 | 6 | 1. A data processing method, comprising: receiving an electronically parseable document; and scanning the document according to at least one predefined rule to determine if the document is suspicious, wherein if the document is determined not to be suspicious, passing the document from a scanner to a first parser, and parsing the document with the first parser, and wherein if the document is determined to be suspicious, passing the document from the scanner to a second parser without passing the document from the scanner to the first parser, and parsing the document with the second parser, wherein the document is determined to be suspicious if the document includes a property that may cause a receiving computer system to fail, wherein the document is determined to be suspicious if the document comprises a well-formed document within a plurality of rules, but when the document is parsed, the document fails or slows down the receiving computer system to fail, and wherein the property includes at least one of a length of an attribute name, a number of an attribute per element, and a number of nested elements that exceeds a predetermined threshold. | 1. A data processing method, comprising: receiving an electronically parseable document; and scanning the document according to at least one predefined rule to determine if the document is suspicious, wherein if the document is determined not to be suspicious, passing the document from a scanner to a first parser, and parsing the document with the first parser, and wherein if the document is determined to be suspicious, passing the document from the scanner to a second parser without passing the document from the scanner to the first parser, and parsing the document with the second parser, wherein the document is determined to be suspicious if the document includes a property that may cause a receiving computer system to fail, wherein the document is determined to be suspicious if the document comprises a well-formed document within a plurality of rules, but when the document is parsed, the document fails or slows down the receiving computer system to fail, and wherein the property includes at least one of a length of an attribute name, a number of an attribute per element, and a number of nested elements that exceeds a predetermined threshold. 6. The method according to claim 1 , further comprising monitoring a performance of the second parser, and in a predefined circumstance, discarding another document prior to parsing, if said document is of a particular form. | 0.5 |
7,966,555 | 2 | 3 | 2. A method as recited in claim 1 , further comprising receiving an indication that a prescribed keyboard key associated with successively selecting a plurality of cells is selected. | 2. A method as recited in claim 1 , further comprising receiving an indication that a prescribed keyboard key associated with successively selecting a plurality of cells is selected. 3. A method as recited in claim 2 , wherein the prescribed keyboard key comprises a control key. | 0.5 |
7,523,126 | 1 | 8 | 1. A method of displaying data, comprising the steps of: (1) defining a set of documents, each document having a unique identification, the set being defined by selecting at least one starting document, with the set further comprising documents being included based on predetermined relationships to information derived from said at least one starting document; (2) generating a hierarchal tree representation of at least one subset of the set of documents, a subset inclusion and hierarchy thereof being defined by said predetermined relationships between documents within the set; and (3) selectively focusing on a node of said hierarchal tree, to define a graphic display representation of at least a portion thereof to emphasize the selected focus while depicting the hierarchal relationships. | 1. A method of displaying data, comprising the steps of: (1) defining a set of documents, each document having a unique identification, the set being defined by selecting at least one starting document, with the set further comprising documents being included based on predetermined relationships to information derived from said at least one starting document; (2) generating a hierarchal tree representation of at least one subset of the set of documents, a subset inclusion and hierarchy thereof being defined by said predetermined relationships between documents within the set; and (3) selectively focusing on a node of said hierarchal tree, to define a graphic display representation of at least a portion thereof to emphasize the selected focus while depicting the hierarchal relationships. 8. The method according to claim 1 , further comprising the step of using an intelligent agent as part of a human user interface. | 0.754753 |
10,127,569 | 1 | 5 | 1. A non-transitory computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to create a service instance based on a provider function for calculating a service order, the creating comprising: defining a structured set of metadata for the provider function, the structured set of metadata defining one or more variants that select a fulfillment pattern, the fulfillment pattern comprising a process flow declaration that includes one or more fulfillment functions of the fulfillment pattern and sets dependencies between pairs of fulfillment functions that impose an ordered priority of execution of the one or more fulfillment functions, and including metadata retrieved from a technical catalog; defining a transformation sequence, based on the metadata for the provider function, comprising customizable process logic for the provider function, wherein the customizable process logic is structured within one or more stages configured to generate the service order; dynamically generating a runtime process flow for the provider function based on the metadata and the transformation sequence, the dynamically generating including selecting at least one fulfillment pattern from the one or more fulfillment patterns based on at least one entity from one or more entities comprised in the metadata and at least one discriminator from one or more discriminators comprised in the metadata; and generating a fulfillment flow based on the at least one selected fulfillment pattern; calculating the service order with customer-facing service order line objects and referring to an entity as its subject based on the fulfillment flow, wherein the metadata comprises the entity that defines a capability that is provided, and wherein the entity comprises one or more child entities; designing a configuration for the entity, wherein the configuration comprises the entity, the one or more child entities, and one or more relationships between the entity and the one or more child entities; creating, for each child entity, a design context comprising a reference to both a parent entity and one or more sub-components, wherein each child entity is a subject for the design context and wherein each subject comprises either a customer order, service order or a technical order; and designing, for each child entity, an instance of the child entity using a corresponding design context. | 1. A non-transitory computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to create a service instance based on a provider function for calculating a service order, the creating comprising: defining a structured set of metadata for the provider function, the structured set of metadata defining one or more variants that select a fulfillment pattern, the fulfillment pattern comprising a process flow declaration that includes one or more fulfillment functions of the fulfillment pattern and sets dependencies between pairs of fulfillment functions that impose an ordered priority of execution of the one or more fulfillment functions, and including metadata retrieved from a technical catalog; defining a transformation sequence, based on the metadata for the provider function, comprising customizable process logic for the provider function, wherein the customizable process logic is structured within one or more stages configured to generate the service order; dynamically generating a runtime process flow for the provider function based on the metadata and the transformation sequence, the dynamically generating including selecting at least one fulfillment pattern from the one or more fulfillment patterns based on at least one entity from one or more entities comprised in the metadata and at least one discriminator from one or more discriminators comprised in the metadata; and generating a fulfillment flow based on the at least one selected fulfillment pattern; calculating the service order with customer-facing service order line objects and referring to an entity as its subject based on the fulfillment flow, wherein the metadata comprises the entity that defines a capability that is provided, and wherein the entity comprises one or more child entities; designing a configuration for the entity, wherein the configuration comprises the entity, the one or more child entities, and one or more relationships between the entity and the one or more child entities; creating, for each child entity, a design context comprising a reference to both a parent entity and one or more sub-components, wherein each child entity is a subject for the design context and wherein each subject comprises either a customer order, service order or a technical order; and designing, for each child entity, an instance of the child entity using a corresponding design context. 5. The non-transitory computer-readable medium of claim 1 , wherein the designing the instance of the child entity is performed recursively for each child entity. | 0.89875 |
9,152,672 | 1 | 2 | 1. A method for performing queries on a distributed time series data storage system having a time series database that stores data blocks containing time stamped data across a plurality of computing devices, and an index database that stores an index associated with the time stamped data in each data block, the method comprising: sending a query to a query layer running on a first computing device, the query specifying criteria that define a set of data retrieved from the time series data storage system and an analysis performed on the set of data; requesting from the index database the indices associated with the data blocks stored in the time series database needed to evaluate the query; returning the indices back to the query layer; preparing a sub-query that produces appropriate data matching the criteria, the sub-query including the criteria and a logical operation performed on the data matching the criteria; forwarding the sub-query to an evaluator running on each of the plurality of computing devices that are identified in the returned indices as holding data corresponding to the data blocks needed to evaluate the query; evaluating the criteria specified in the sub-query in each evaluator with respect to the data blocks stored on the same computing device on which the evaluator is running in order to select a subset of data; performing the logical operation specified in the sub-query in each evaluator on the subset of data generated in that evaluator in the evaluating step above to generate a sub-result; receiving each sub-result from each evaluator at an output handler; and combining the sub-result from each evaluator into a query result. | 1. A method for performing queries on a distributed time series data storage system having a time series database that stores data blocks containing time stamped data across a plurality of computing devices, and an index database that stores an index associated with the time stamped data in each data block, the method comprising: sending a query to a query layer running on a first computing device, the query specifying criteria that define a set of data retrieved from the time series data storage system and an analysis performed on the set of data; requesting from the index database the indices associated with the data blocks stored in the time series database needed to evaluate the query; returning the indices back to the query layer; preparing a sub-query that produces appropriate data matching the criteria, the sub-query including the criteria and a logical operation performed on the data matching the criteria; forwarding the sub-query to an evaluator running on each of the plurality of computing devices that are identified in the returned indices as holding data corresponding to the data blocks needed to evaluate the query; evaluating the criteria specified in the sub-query in each evaluator with respect to the data blocks stored on the same computing device on which the evaluator is running in order to select a subset of data; performing the logical operation specified in the sub-query in each evaluator on the subset of data generated in that evaluator in the evaluating step above to generate a sub-result; receiving each sub-result from each evaluator at an output handler; and combining the sub-result from each evaluator into a query result. 2. The method of claim 1 wherein the time series data storage system further comprises a data generator that produces the time stamped data and an ingester, and wherein the method further comprises: receiving the time-stamped data from the data generator by the ingester; creating the data block and the index from the time-stamped data; sending the data block to the time series database for storage; and sending the index to the index database for storage. | 0.5 |
7,673,295 | 1 | 7 | 1. A method for compile-time detection of non-concurrency in a parallel program having a base language and a parallel programming language, the method comprising: modeling a program control flow of a subroutine of the parallel program, utilizing at least one processing unit, in a control flow graph having plural phases, wherein each phase having plural nodes; modeling a program hierarchical loop structure of the subroutine of the base language and a parallel programming language constructs in a region tree of the subroutine, utilizing the at least one processing unit, wherein the region tree comprises at least one construct edge defining a cycle between at least one end construct directive node and at least one begin construct directive node, wherein the at least one construct edge does not reflect control transfer of a the subroutine; analyzing the control flow graph and the region tree, utilizing the at least one processing unit, to identify plural parallel regions; analyzing a parallel region, utilizing the at least one processing unit, to identify plural static phases, each static phases having one or more nodes; and comparing nodes of the control flow graph and nodes of the static phases, utilizing the at least one processing unit, to determine non-concurrency at compile time for nodes in the same phase. | 1. A method for compile-time detection of non-concurrency in a parallel program having a base language and a parallel programming language, the method comprising: modeling a program control flow of a subroutine of the parallel program, utilizing at least one processing unit, in a control flow graph having plural phases, wherein each phase having plural nodes; modeling a program hierarchical loop structure of the subroutine of the base language and a parallel programming language constructs in a region tree of the subroutine, utilizing the at least one processing unit, wherein the region tree comprises at least one construct edge defining a cycle between at least one end construct directive node and at least one begin construct directive node, wherein the at least one construct edge does not reflect control transfer of a the subroutine; analyzing the control flow graph and the region tree, utilizing the at least one processing unit, to identify plural parallel regions; analyzing a parallel region, utilizing the at least one processing unit, to identify plural static phases, each static phases having one or more nodes; and comparing nodes of the control flow graph and nodes of the static phases, utilizing the at least one processing unit, to determine non-concurrency at compile time for nodes in the same phase. 7. The method of claim 1 wherein comparing nodes of the control flow graph and nodes of the static phases further comprises: determining that two nodes are in the same phase and same single construct; and determining non-concurrency for the nodes if none barrier free path exists from the single construct end directive node to the header of the immediately enclosing loop. | 0.594565 |
9,195,744 | 8 | 9 | 8. A search apparatus implemented in a computer, said apparatus comprising a processor programmed to: receive a search query comprising a plurality of keywords; determine each mathematical combination of the plurality of keywords; divide the search query into a number of sub-queries, in which each sub-query comprising at least one of said keywords and in which each mathematical combination is represented as a separate sub-query; compare each sub-query to an inhibited combinations list; exclude sub-queries that are identified as inhibited combinations; after excluding sub-queries that are identified as inhibited combinations, submit remaining sub-queries to different search engines such that private information from the search query is less discernible at any one of said search engines than if more of the keywords of the search query were provided to that individual search engine; and re-search a plurality of search results returned from the different search engines in response to the submission of said sub-queries, said re-searching being performed using all the keywords of the search query. | 8. A search apparatus implemented in a computer, said apparatus comprising a processor programmed to: receive a search query comprising a plurality of keywords; determine each mathematical combination of the plurality of keywords; divide the search query into a number of sub-queries, in which each sub-query comprising at least one of said keywords and in which each mathematical combination is represented as a separate sub-query; compare each sub-query to an inhibited combinations list; exclude sub-queries that are identified as inhibited combinations; after excluding sub-queries that are identified as inhibited combinations, submit remaining sub-queries to different search engines such that private information from the search query is less discernible at any one of said search engines than if more of the keywords of the search query were provided to that individual search engine; and re-search a plurality of search results returned from the different search engines in response to the submission of said sub-queries, said re-searching being performed using all the keywords of the search query. 9. The search apparatus of claim 8 , in which said processor is further programmed to accept user input identifying at least one keyword or combination of said keywords that is not to be used as a sub-query. | 0.748786 |
9,569,431 | 13 | 14 | 13. The first computing device of claim 8 , wherein the first computing device is a mobile computing device. | 13. The first computing device of claim 8 , wherein the first computing device is a mobile computing device. 14. The first computing device of claim 13 , wherein the first computing device is executing a video conferencing application configured to generate and output the translation request and to receive and output the translated audio. | 0.5 |
8,935,151 | 2 | 7 | 2. A method, comprising: tagging a source-language sentence with non-lexical tags; parsing, utilizing one or more processors, the tagged source-language sentence using a source language lexicalized parser to generate a parse tree for the sentence, where the source language lexicalized parser has been trained using gold standard source-language data; tagging a target-language sentence with non-lexical tags, where the target-language sentence is a translation of the source-language sentence; parsing, utilizing one or more of the processors, the tagged target-language sentence with a delexicalized parser to generate a set of k-best parse trees for the target-language sentence; selecting the best target-language parse tree of the k-best parse trees that most closely aligns with the lexicalized parse tree of the source-language sentence; and updating a parameter vector of a target language lexicalized parser based upon the selected best target-language parse tree. | 2. A method, comprising: tagging a source-language sentence with non-lexical tags; parsing, utilizing one or more processors, the tagged source-language sentence using a source language lexicalized parser to generate a parse tree for the sentence, where the source language lexicalized parser has been trained using gold standard source-language data; tagging a target-language sentence with non-lexical tags, where the target-language sentence is a translation of the source-language sentence; parsing, utilizing one or more of the processors, the tagged target-language sentence with a delexicalized parser to generate a set of k-best parse trees for the target-language sentence; selecting the best target-language parse tree of the k-best parse trees that most closely aligns with the lexicalized parse tree of the source-language sentence; and updating a parameter vector of a target language lexicalized parser based upon the selected best target-language parse tree. 7. The method of claim 2 , wherein the delexicalized parser has been trained using concatenating gold standard data for each of a plurality of distinct languages. | 0.781081 |
7,856,446 | 1 | 5 | 1. A method for identifying, extracting using a processor, capturing, and leveraging expertise and knowledge comprising: observing, between and among peers and experts who show high affinity with regard to any of the users, assets, and topics/terms, a user heartbeat which comprises user activity, including mouse movement and stable pauses on an asset, while the asset is in a user display foreground; based upon the observing, detecting user think time for the asset; employing automatic techniques to extract patterns from at least the user think time; and learning affinities between and among any of the users, assets and topics/terms from the extracted patterns for any of: automatically determining each user's peer group, predicting a desired destination of the users in a navigation context, calculating an expert and peer impact factor, an asset impact factor, or rareness, determining importance of an asset and/or expertise that individuals possess, without asking the individuals directly, automatically disambiguating query terms in an online search, and/or effecting a predictive query by suggesting search terms to the users or automatically inserting search terms into user queries to expand a search, wherein learning affinities includes applying a formula to lower weights of the term as the terms become associated with more assets. | 1. A method for identifying, extracting using a processor, capturing, and leveraging expertise and knowledge comprising: observing, between and among peers and experts who show high affinity with regard to any of the users, assets, and topics/terms, a user heartbeat which comprises user activity, including mouse movement and stable pauses on an asset, while the asset is in a user display foreground; based upon the observing, detecting user think time for the asset; employing automatic techniques to extract patterns from at least the user think time; and learning affinities between and among any of the users, assets and topics/terms from the extracted patterns for any of: automatically determining each user's peer group, predicting a desired destination of the users in a navigation context, calculating an expert and peer impact factor, an asset impact factor, or rareness, determining importance of an asset and/or expertise that individuals possess, without asking the individuals directly, automatically disambiguating query terms in an online search, and/or effecting a predictive query by suggesting search terms to the users or automatically inserting search terms into user queries to expand a search, wherein learning affinities includes applying a formula to lower weights of the term as the terms become associated with more assets. 5. The method of claim 1 , further comprising: for a given user who may be anonymous, the user visiting a particular site, and a given context comprising any of what page the user is on and how the user got there, providing recommendations to the user that allow the user to navigate the site more efficiently. | 0.716636 |
8,172,882 | 1 | 4 | 1. An implant comprising: a first hook adapted to be hooked onto a first lateral border of a first superior articular facet of a vertebra; a second hook adapted to be hooked onto a second lateral border of a second superior articular facet of said same vertebra; a connector coupled to the first and second hooks, the connector configured to be positioned between the first hook and the second hook and superior to a spinous process of said same vertebra; and a first lock associated with the first hook and a second lock associated with the second hook; whereby the first hook is adapted to be hooked around the first lateral border of the first superior articular facet, the second hook is adapted to be hooked around the second lateral border of the second superior articular facet; and whereby the first hook and second hook are configured to be moved along said connector towards said spinous process, such that the first hook and second hook can then be locked in place relative to said connector thereby securing the implant to said vertebra; and whereby the first and second hooks each comprise: an upper portion that accepts the connector; a lower portion adapted to engage a lateral border of a superior articular facet; and a movable joint connecting the upper portion and the lower portion such that the lower portion can move relative to the upper portion. | 1. An implant comprising: a first hook adapted to be hooked onto a first lateral border of a first superior articular facet of a vertebra; a second hook adapted to be hooked onto a second lateral border of a second superior articular facet of said same vertebra; a connector coupled to the first and second hooks, the connector configured to be positioned between the first hook and the second hook and superior to a spinous process of said same vertebra; and a first lock associated with the first hook and a second lock associated with the second hook; whereby the first hook is adapted to be hooked around the first lateral border of the first superior articular facet, the second hook is adapted to be hooked around the second lateral border of the second superior articular facet; and whereby the first hook and second hook are configured to be moved along said connector towards said spinous process, such that the first hook and second hook can then be locked in place relative to said connector thereby securing the implant to said vertebra; and whereby the first and second hooks each comprise: an upper portion that accepts the connector; a lower portion adapted to engage a lateral border of a superior articular facet; and a movable joint connecting the upper portion and the lower portion such that the lower portion can move relative to the upper portion. 4. The implant of claim 1 , wherein the first and second hooks have several different radii to ensure the hooks match anatomy variations in the articular facets wherein said first radius is about 0.625 inches and the second radius is about 0.785 inches and the first radius describes a curve in a first plane and the second radius describes a curve that is in a second plane and wherein said first plane is about perpendicular to the second plane. | 0.5 |
9,489,350 | 3 | 26 | 3. A computer-implemented method for comparing content overlap between a target electronic document and at least one additional electronic document, comprising: receiving, at a computer, a search request from a user for documents containing one or more keywords; using the computer to access an electronic database and present to the user a first list of one or more documents in the electronic database based on the one or more keywords, the first list of one or more documents including a first hyperlink for the first electronic document; receiving at the computer a request for the first electronic document via the first hyperlink; determining, in response to the request for the first electronic document, a second list of documents in the electronic database that are similar to the first electronic document, the second list of documents including the second electronic document, and the determining comprising: using the computer to parse a text of each of the target and at least one additional document into constituent units; using the computer to identify named entities within each of the constituent units; using the computer to pair identified named entities which appear together within the same constituent units; and using the computer to assess a similarity between the target document and the at least one additional document based on a result of the paired entities; and using the computer to display to the user the contents of the first electronic document and a hyperlink to the second electronic document and a graphic indicating the similarity between the target document and the at least one additional document with an indication of similarity, wherein the graphic comprises: a measure of relationship overlap between the target document and the at least one additional document; a measure of relationship overlap between the target document and a selected portion of the at least one additional document; a measure of a size of the target document; a measure of a size of the at least one additional document; and a measure of a size of the textual overlap between the target document and the at least one additional document, wherein at least two of the measure of textual overlap between the target document and the at least one additional document; the measure of relationship overlap between the target document and the at least one additional document; and the measure of relationship overlap between the target document and a selected portion of the at least one additional document are displayed as bars having a length corresponding to a magnitude of the respective measure. | 3. A computer-implemented method for comparing content overlap between a target electronic document and at least one additional electronic document, comprising: receiving, at a computer, a search request from a user for documents containing one or more keywords; using the computer to access an electronic database and present to the user a first list of one or more documents in the electronic database based on the one or more keywords, the first list of one or more documents including a first hyperlink for the first electronic document; receiving at the computer a request for the first electronic document via the first hyperlink; determining, in response to the request for the first electronic document, a second list of documents in the electronic database that are similar to the first electronic document, the second list of documents including the second electronic document, and the determining comprising: using the computer to parse a text of each of the target and at least one additional document into constituent units; using the computer to identify named entities within each of the constituent units; using the computer to pair identified named entities which appear together within the same constituent units; and using the computer to assess a similarity between the target document and the at least one additional document based on a result of the paired entities; and using the computer to display to the user the contents of the first electronic document and a hyperlink to the second electronic document and a graphic indicating the similarity between the target document and the at least one additional document with an indication of similarity, wherein the graphic comprises: a measure of relationship overlap between the target document and the at least one additional document; a measure of relationship overlap between the target document and a selected portion of the at least one additional document; a measure of a size of the target document; a measure of a size of the at least one additional document; and a measure of a size of the textual overlap between the target document and the at least one additional document, wherein at least two of the measure of textual overlap between the target document and the at least one additional document; the measure of relationship overlap between the target document and the at least one additional document; and the measure of relationship overlap between the target document and a selected portion of the at least one additional document are displayed as bars having a length corresponding to a magnitude of the respective measure. 26. The method of claim 3 , wherein the indication of similarity comprises one or more indicators, the indicators comprising: an indication of like semantic pairs between the target document and the at least one additional document and an indication of the presence of original material in the target document, relative to the at least one additional document, for one or more of the identified named entities and/or the pair of named entities that appear together within the same constituent unit. | 0.5 |
9,946,794 | 8 | 9 | 8. The method of claim 1 , wherein: the second module score is determined by a metadata module executing at the computing device, the metadata module determines the second module score by matching the search query with metadata associated with application search results or synonyms of the metadata, and the metadata includes an associated metadata score. | 8. The method of claim 1 , wherein: the second module score is determined by a metadata module executing at the computing device, the metadata module determines the second module score by matching the search query with metadata associated with application search results or synonyms of the metadata, and the metadata includes an associated metadata score. 9. The method of claim 8 , further comprising receiving the metadata associated with application search results from the special purpose search system. | 0.5 |
8,862,577 | 2 | 3 | 2. The method of claim 1 , wherein providing the at least one visualization comprises providing a certainty calendar map having lines of graphical elements, where the graphical elements represent corresponding comments in the user feedback, where the lines correspond to respective different time intervals, and a particular one of the lines includes a plurality of graphical elements, at least one of the plurality of graphical elements assigned a first visual indicator to represent a particular user sentiment in the corresponding comment, and assigned a second visual indicator to represent a level of uncertainty of the particular user sentiment. | 2. The method of claim 1 , wherein providing the at least one visualization comprises providing a certainty calendar map having lines of graphical elements, where the graphical elements represent corresponding comments in the user feedback, where the lines correspond to respective different time intervals, and a particular one of the lines includes a plurality of graphical elements, at least one of the plurality of graphical elements assigned a first visual indicator to represent a particular user sentiment in the corresponding comment, and assigned a second visual indicator to represent a level of uncertainty of the particular user sentiment. 3. The method of claim 2 , wherein the first visual indicator of the at least one graphical element is one of plural different colors that represent different user sentiments. | 0.5 |
8,417,718 | 1 | 11 | 1. A method of selecting suggested query completions for a partial query, the method including: determining a prefix and a suffix of a partial query having multiple terms, the prefix including one or more terms occurring at a beginning of the partial query, the suffix including one or more terms occurring at an end of the partial query, wherein a last term in the prefix precedes a first term in the suffix; calculating suffix similarity scores for unique queries having prefixes which do not include the prefix of the partial query as a substring, the suffix similarity score for a unique query based at least in part on similarity of terms in the suffix of the partial query and terms in a suffix of the unique query; selecting one or more of the unique queries as candidate queries for completing the partial query based at least in part on the suffix similarity scores for the unique queries; calculating completion scores for unique suffixes among the suffixes of the candidate queries, the completion scores representing an extent to which the unique suffixes are potential query completions for the partial query; and using the completion scores to select one or more terms of the unique suffixes as suggested query completions for the partial query; wherein the method is performed by one or more computer processors. | 1. A method of selecting suggested query completions for a partial query, the method including: determining a prefix and a suffix of a partial query having multiple terms, the prefix including one or more terms occurring at a beginning of the partial query, the suffix including one or more terms occurring at an end of the partial query, wherein a last term in the prefix precedes a first term in the suffix; calculating suffix similarity scores for unique queries having prefixes which do not include the prefix of the partial query as a substring, the suffix similarity score for a unique query based at least in part on similarity of terms in the suffix of the partial query and terms in a suffix of the unique query; selecting one or more of the unique queries as candidate queries for completing the partial query based at least in part on the suffix similarity scores for the unique queries; calculating completion scores for unique suffixes among the suffixes of the candidate queries, the completion scores representing an extent to which the unique suffixes are potential query completions for the partial query; and using the completion scores to select one or more terms of the unique suffixes as suggested query completions for the partial query; wherein the method is performed by one or more computer processors. 11. The method of claim 1 , including: receiving the partial query; and sending one or more of the selected terms of the unique suffixes in response to receiving the partial query. | 0.863429 |
4,430,726 | 11 | 12 | 11. A dictation transcribing system comprising a plurality of dictation terminals each operable by a user for transmitting voice dictation signals to one or more remote locations, a plurality of transcriber terminals at remote locations each operable by a user for transcribing voice dictation signals received from the dictation terminal, means for switching voice dictation signals from said dictation terminal to said first or second transcriber terminals, and means for controlling said switching means characterized in that said system further comprises means connected to each dictation terminal for partitioning said voice dictation signals into time sequential voice dictation segments and said controlling means includes storing means responsive to a signal from each transcriber terminal for storing an entry identifying the time when each assigned transcriber terminal is no longer busy transcribing and means responsive to said partitioning means for assigning and transmitting each of said voice dictation segments to one of said transcriber terminals by selecting the transcriber terminal having the earliest time entry in said storing means. | 11. A dictation transcribing system comprising a plurality of dictation terminals each operable by a user for transmitting voice dictation signals to one or more remote locations, a plurality of transcriber terminals at remote locations each operable by a user for transcribing voice dictation signals received from the dictation terminal, means for switching voice dictation signals from said dictation terminal to said first or second transcriber terminals, and means for controlling said switching means characterized in that said system further comprises means connected to each dictation terminal for partitioning said voice dictation signals into time sequential voice dictation segments and said controlling means includes storing means responsive to a signal from each transcriber terminal for storing an entry identifying the time when each assigned transcriber terminal is no longer busy transcribing and means responsive to said partitioning means for assigning and transmitting each of said voice dictation segments to one of said transcriber terminals by selecting the transcriber terminal having the earliest time entry in said storing means. 12. The invention of claim 11 wherein said controlling means further includes an assignment table means for storing which transcriber terminals are assigned a voice dictation segment from which dictation terminals, means for determining the busy status of each transcriber terminal and means for assigning and transmitting a voice dictation segment from a dictation terminal to a non-busy transcriber terminal assigned to said dictation terminal. | 0.5 |
9,286,451 | 1 | 2 | 1. A password authentication method, comprising: generating a first virtual keyboard as a keyboard; generating a group of sequential candidate characters according to a user's operations to the keyboard, at least one key on the keyboard being associated with at least two characters, wherein the user's single operation of any one key results in characters associated with that key being selected as candidate characters with the same ranking; authenticating whether a character string formed by the sequential candidate characters matches a password of the user; generating a different second virtual keyboard in response to a character string formed by the sequential candidate characters matching the password of the user, at least one key on the second virtual keyboard being associated with at least two characters, the second virtual keyboard having a different character layout than the first virtual keyboard such that character combinations on keys of the second virtual keyboard are different from character combinations on keys of the first virtual keyboard, wherein each key on the second virtual keyboard is associated with a different number of characters; generating a second group of sequential candidate characters according to the user's operations to the second virtual keyboard, wherein the user's single operation of any one key on the second virtual keyboard results in characters associated with that key are selected as candidate characters having same ranking; and authenticating whether one of character strings formed by the second group of sequential candidate characters matches the password of the user. | 1. A password authentication method, comprising: generating a first virtual keyboard as a keyboard; generating a group of sequential candidate characters according to a user's operations to the keyboard, at least one key on the keyboard being associated with at least two characters, wherein the user's single operation of any one key results in characters associated with that key being selected as candidate characters with the same ranking; authenticating whether a character string formed by the sequential candidate characters matches a password of the user; generating a different second virtual keyboard in response to a character string formed by the sequential candidate characters matching the password of the user, at least one key on the second virtual keyboard being associated with at least two characters, the second virtual keyboard having a different character layout than the first virtual keyboard such that character combinations on keys of the second virtual keyboard are different from character combinations on keys of the first virtual keyboard, wherein each key on the second virtual keyboard is associated with a different number of characters; generating a second group of sequential candidate characters according to the user's operations to the second virtual keyboard, wherein the user's single operation of any one key on the second virtual keyboard results in characters associated with that key are selected as candidate characters having same ranking; and authenticating whether one of character strings formed by the second group of sequential candidate characters matches the password of the user. 2. The method according to claim 1 , wherein the step of generating a first virtual keyboard as the keyboard comprises at least one of: randomly generating associations between keys on the first virtual keyboard and characters; and randomly generating a key layout of the first virtual keyboard. | 0.63848 |
8,727,780 | 10 | 15 | 10. A mathematical research system comprising: two or more concept line items (CLIs) created from a plurality of mathematical concepts expressed in a plurality of documents, wherein a CLI is a textual expression of a mathematical concept, wherein the mathematical concepts are extracted from one or more algorithmic, linguistic, geometric, and graphic mathematical representations; a set of two or more defined interrelationships between the two or more CLIs, wherein the defined interrelationships include one or more of a prerequisite to another CLI, a dependency on another CLI, and a lack of relationship to another CLI; a computer processor operable to generate a mapping of the two or more CLIs and the interrelationships; one or more databases operable to store the two or more CLIs and the generated mapping, wherein the mapping is in the form of a directed graph, wherein the directed graph includes one or more prerequisite and dependency interrelationships; a database including the plurality of documents, wherein documents expressing one or more CLIs are tagged with one or more associated mathematical concept tags; an index that relates each CLI to the corresponding documents; and a search interface through which a user searches the database to identify documents related to one or more CLIs, wherein the identified documents are used to generate an educational curriculum, wherein the search interface accepts a search term provided by the user, wherein the search interface accepts all of the following forms of search terms: text-based phrases, mathematical expressions expressed in documents, interrelationships, and concept ranges. | 10. A mathematical research system comprising: two or more concept line items (CLIs) created from a plurality of mathematical concepts expressed in a plurality of documents, wherein a CLI is a textual expression of a mathematical concept, wherein the mathematical concepts are extracted from one or more algorithmic, linguistic, geometric, and graphic mathematical representations; a set of two or more defined interrelationships between the two or more CLIs, wherein the defined interrelationships include one or more of a prerequisite to another CLI, a dependency on another CLI, and a lack of relationship to another CLI; a computer processor operable to generate a mapping of the two or more CLIs and the interrelationships; one or more databases operable to store the two or more CLIs and the generated mapping, wherein the mapping is in the form of a directed graph, wherein the directed graph includes one or more prerequisite and dependency interrelationships; a database including the plurality of documents, wherein documents expressing one or more CLIs are tagged with one or more associated mathematical concept tags; an index that relates each CLI to the corresponding documents; and a search interface through which a user searches the database to identify documents related to one or more CLIs, wherein the identified documents are used to generate an educational curriculum, wherein the search interface accepts a search term provided by the user, wherein the search interface accepts all of the following forms of search terms: text-based phrases, mathematical expressions expressed in documents, interrelationships, and concept ranges. 15. The system of claim 10 wherein said computer processor is further operable to score a particular CLI, wherein said score of said CLI is a difficulty score, and wherein a difficulty score indicates said particular CLI's level of difficulty. | 0.786467 |
9,118,618 | 1 | 2 | 1. A method for modifying a data packet by a hardware-based packet editor comprising: receiving, by the packet editor, a packet editing script comprising one or more script entries indicating modifications to be applied to the data packet and a data block comprising data for the modified packet; for each given script entry in the packet editing script, copying, by the packet editor, data in the data block at a location and a size identified in the given script entry into a packet buffer; generating, by the packet editor, a modified data packet with the data in the packet buffer, wherein the copying comprises: retrieving the given script entry of the packet editing script; determining whether the given script entry is a first script entry for the modified data packet; in response to determining that the given script entry is the first script entry for the modified data packet, reserving the packet buffer for the modified data packet; copying the data in the data block at a block location and with a block length identified in the given script entry into the packet buffer; determining whether the given script entry is a last script entry for the modified data packet; and in response to determining that the given script entry is not the last script entry for the modified data packet, performing the copying the data in the data block at a block location and with a block length identified in the given script entry into the packet buffer and the determining whether the given script entry is a last script entry for the next given script entry of the packet editing script. | 1. A method for modifying a data packet by a hardware-based packet editor comprising: receiving, by the packet editor, a packet editing script comprising one or more script entries indicating modifications to be applied to the data packet and a data block comprising data for the modified packet; for each given script entry in the packet editing script, copying, by the packet editor, data in the data block at a location and a size identified in the given script entry into a packet buffer; generating, by the packet editor, a modified data packet with the data in the packet buffer, wherein the copying comprises: retrieving the given script entry of the packet editing script; determining whether the given script entry is a first script entry for the modified data packet; in response to determining that the given script entry is the first script entry for the modified data packet, reserving the packet buffer for the modified data packet; copying the data in the data block at a block location and with a block length identified in the given script entry into the packet buffer; determining whether the given script entry is a last script entry for the modified data packet; and in response to determining that the given script entry is not the last script entry for the modified data packet, performing the copying the data in the data block at a block location and with a block length identified in the given script entry into the packet buffer and the determining whether the given script entry is a last script entry for the next given script entry of the packet editing script. 2. The method of claim 1 wherein the determining whether the given script entry is the first script entry comprises: determining whether a start of packet (SOP) indicator in the given script entry indicates that the given script entry is the first script entry for the modified data packet. | 0.738739 |
8,050,918 | 7 | 8 | 7. A tangible computer-readable storage device encoded with instructions which, when executed by a computer, cause the computer to perform a method of evaluating grammars associated with a voice portal, the method comprising: generating, for a current grammar of the voice portal representing a valid input for a first menu of the voice portal, a test input, the test input for the current grammar including a test pattern; providing the test input to the voice portal; receiving at least one measure of how distinguishable the current grammar is from other grammars of a set of active grammars that are active when the current grammar is active, the set of active grammars including the current grammar and at least one grammar from a second menu of the voice portal, the at least one measure based at least in part on analysis of the test pattern with respect to the set of active grammars, the at least one measure comprising at least one measure of how distinguishable the current grammar is from the at least one grammar from the second menu of the voice portal; and determining, based at least in part on the at least one measure, whether to modify the current grammar from the first menu to be distinguishable from the at least one grammar from the second menu. | 7. A tangible computer-readable storage device encoded with instructions which, when executed by a computer, cause the computer to perform a method of evaluating grammars associated with a voice portal, the method comprising: generating, for a current grammar of the voice portal representing a valid input for a first menu of the voice portal, a test input, the test input for the current grammar including a test pattern; providing the test input to the voice portal; receiving at least one measure of how distinguishable the current grammar is from other grammars of a set of active grammars that are active when the current grammar is active, the set of active grammars including the current grammar and at least one grammar from a second menu of the voice portal, the at least one measure based at least in part on analysis of the test pattern with respect to the set of active grammars, the at least one measure comprising at least one measure of how distinguishable the current grammar is from the at least one grammar from the second menu of the voice portal; and determining, based at least in part on the at least one measure, whether to modify the current grammar from the first menu to be distinguishable from the at least one grammar from the second menu. 8. The tangible computer-readable storage device of claim 7 , wherein the at least one measure of how distinguishable the current grammar is from other grammars of the set of active grammars includes a confidence level and a set of n-best results for the test input, and wherein the method further comprises comparing the confidence level and set of n-best results for the test input with an expected value to assess the at least one measure of how distinguishable the current grammar is from other grammars of the set of active grammars. | 0.5 |
8,429,723 | 1 | 8 | 1. A computer system for distributed legal workflow security, the computer system providing central administration of legal workflow conducted by a plurality of distributed workflow participants, the system comprising a computer network including one or more computers operably programmed and configured to: permit an administrator to (i) create user accounts for each of the participants, (ii) associate one or more legal workflow role types with each of the accounts, and (iii) associate menu item permission privileges for a plurality of common menu items of a common legal workflow graphical interface with each of the types; provide the common interface to each of the participants, wherein the menu items are displayed to each of the participants via the common interface independent of the permission privileges associated with the type of the participant's account such that only the menu items for which the type of the participant's account has permission are active; and permit one of the participants to create another account of a same type as the one of the participant's account and with same or fewer permission privileges as the type of the one of the participant's account. | 1. A computer system for distributed legal workflow security, the computer system providing central administration of legal workflow conducted by a plurality of distributed workflow participants, the system comprising a computer network including one or more computers operably programmed and configured to: permit an administrator to (i) create user accounts for each of the participants, (ii) associate one or more legal workflow role types with each of the accounts, and (iii) associate menu item permission privileges for a plurality of common menu items of a common legal workflow graphical interface with each of the types; provide the common interface to each of the participants, wherein the menu items are displayed to each of the participants via the common interface independent of the permission privileges associated with the type of the participant's account such that only the menu items for which the type of the participant's account has permission are active; and permit one of the participants to create another account of a same type as the one of the participant's account and with same or fewer permission privileges as the type of the one of the participant's account. 8. The computer system of claim 1 wherein the permission privileges include active, inactive, hidden, greyed, edit, no edit, add, delete or grant. | 0.609626 |
9,275,554 | 33 | 36 | 33. The method according to claim 32 , wherein the at least one configuration setting for the selection of the one or more keywords is an automatic setting; and wherein the automatic setting causes the application to automatically select the one or more keywords of the textual information for testing based on one or more search criteria. | 33. The method according to claim 32 , wherein the at least one configuration setting for the selection of the one or more keywords is an automatic setting; and wherein the automatic setting causes the application to automatically select the one or more keywords of the textual information for testing based on one or more search criteria. 36. The method according to claim 33 , wherein the one or more search criteria comprises an emphasized text search; and wherein the emphasized text search causes the application to automatically select one or more emphasized text, such that the one or more emphasized text are the one or more selected keywords. | 0.592932 |
10,047,970 | 1 | 2 | 1. A thermostat configured to control one or more HVAC components of an HVAC system, the thermostat comprising: a housing, the housing configured to house: a control module configured to provide one or more control signals to control one or more HVAC components of an HVAC system in accordance with a thermostat control algorithm; a microphone; a speaker; a display; a voice recognition module, wherein the voice recognition module is configured to receive via the microphone a first distinct voice stream that includes a predetermined audible trigger followed by a help phrase, and to recognize the predetermined audible trigger and the help phrase in the first distinct voice stream; and wherein the control module is further configured to execute a help command that corresponds to the help phrase by entering a voice control mode and automatically providing one or more natural language audio clips via the speaker and/or one or more video clips via the display for assisting a user in operating the thermostat in response to the voice recognition module recognizing the predetermined audible trigger and the help phrase in the first distinct voice stream. | 1. A thermostat configured to control one or more HVAC components of an HVAC system, the thermostat comprising: a housing, the housing configured to house: a control module configured to provide one or more control signals to control one or more HVAC components of an HVAC system in accordance with a thermostat control algorithm; a microphone; a speaker; a display; a voice recognition module, wherein the voice recognition module is configured to receive via the microphone a first distinct voice stream that includes a predetermined audible trigger followed by a help phrase, and to recognize the predetermined audible trigger and the help phrase in the first distinct voice stream; and wherein the control module is further configured to execute a help command that corresponds to the help phrase by entering a voice control mode and automatically providing one or more natural language audio clips via the speaker and/or one or more video clips via the display for assisting a user in operating the thermostat in response to the voice recognition module recognizing the predetermined audible trigger and the help phrase in the first distinct voice stream. 2. The thermostat of claim 1 , wherein the voice recognition module, in response to recognizing the predetermined audible trigger and the help phrase, provides an audiovisual clip for assisting the user in operating the thermostat. | 0.838687 |
5,440,678 | 1 | 2 | 1. A method of creating a multi-media footnote control in an animated sequence of video images on-line in a computer system, comprising the steps of: identifying a relationship between a specific portion of an on-line animated sequence of video images and multi-media reference material pertinent thereto which is stored in a separate on-line source; entering identification data from said multi-media reference material in a create footnote window associated with said on-line images; automatically passing said entered data to said on-line images to create a footnote, wherein said specific portion of said on-line images and said multi-media reference material are linked together, and said footnote appears during viewing of said on-line images for a predetermined period of time on said specific portion of said on-line images; and automatically accessing said separate on-line source and displaying said multi-media reference material for viewing upon selection of said footnote. | 1. A method of creating a multi-media footnote control in an animated sequence of video images on-line in a computer system, comprising the steps of: identifying a relationship between a specific portion of an on-line animated sequence of video images and multi-media reference material pertinent thereto which is stored in a separate on-line source; entering identification data from said multi-media reference material in a create footnote window associated with said on-line images; automatically passing said entered data to said on-line images to create a footnote, wherein said specific portion of said on-line images and said multi-media reference material are linked together, and said footnote appears during viewing of said on-line images for a predetermined period of time on said specific portion of said on-line images; and automatically accessing said separate on-line source and displaying said multi-media reference material for viewing upon selection of said footnote. 2. The method of claim 1, further comprising the step of: automatically positioning said footnote in a footnote area of said on-line images. | 0.590643 |
9,361,531 | 34 | 35 | 34. The non-transitory computer-readable medium of claim 33 , wherein the LD and the LD/OCR-Key critical paths associated with the LD trellis and the LD/OCR-Key trellis are constructed concurrently. | 34. The non-transitory computer-readable medium of claim 33 , wherein the LD and the LD/OCR-Key critical paths associated with the LD trellis and the LD/OCR-Key trellis are constructed concurrently. 35. The non-transitory computer-readable medium of claim 34 , wherein the smallest set of errors is a function of the LD and LD/OCR-Key critical paths. | 0.5 |
8,280,823 | 249 | 251 | 249. The system of claim 242 , wherein to satisfy the search criteria, the parsed resume associated with each said at least one matching resume includes, for each said at least one job requirement, either the required skill or experience-related phrase, or an alternative required skill or experience-related phrase, and wherein the term of experience for either the required skill or experience-related phrase, or the alternative required skill or experience-related phrase, is greater than or equal to the required term of experience. | 249. The system of claim 242 , wherein to satisfy the search criteria, the parsed resume associated with each said at least one matching resume includes, for each said at least one job requirement, either the required skill or experience-related phrase, or an alternative required skill or experience-related phrase, and wherein the term of experience for either the required skill or experience-related phrase, or the alternative required skill or experience-related phrase, is greater than or equal to the required term of experience. 251. The system of claim 249 , wherein the required term of experience is rounded up to a unit of time. | 0.624088 |
9,552,830 | 1 | 5 | 1. A vehicle automatic language setting method, for use by a vehicle having an active language setting, to facilitate communication between a vehicle and a driver automatically, said driver having a preferred language and having a portable electronic device, comprising the steps of: connecting the vehicle to the portable electronic device for the purpose of at least language determination; determining the preferred language of the driver by scanning the portable electronic device for the purpose of at least one in-vehicle component language determination; associating in-vehicle components comprising of at least one climate control, at least one infotainment system, and at least the one vehicle safety sensors to said vehicle; setting the active language of the vehicle and/or at least one in-vehicle component to the preferred language automatically; and communicating data by the vehicle and/or at least one-in-vehicle component to the driver automatically in the preferred language, absent said data being communicated between the portable electronic device and the vehicle; and/or absent of the dependency of a navigation system, GPS or geographic location. | 1. A vehicle automatic language setting method, for use by a vehicle having an active language setting, to facilitate communication between a vehicle and a driver automatically, said driver having a preferred language and having a portable electronic device, comprising the steps of: connecting the vehicle to the portable electronic device for the purpose of at least language determination; determining the preferred language of the driver by scanning the portable electronic device for the purpose of at least one in-vehicle component language determination; associating in-vehicle components comprising of at least one climate control, at least one infotainment system, and at least the one vehicle safety sensors to said vehicle; setting the active language of the vehicle and/or at least one in-vehicle component to the preferred language automatically; and communicating data by the vehicle and/or at least one-in-vehicle component to the driver automatically in the preferred language, absent said data being communicated between the portable electronic device and the vehicle; and/or absent of the dependency of a navigation system, GPS or geographic location. 5. The vehicle language setting method as recited in claim 1 , wherein the portable electronic device is a smartphone. | 0.911411 |
10,067,937 | 16 | 20 | 16. A computer-implemented method, comprising: executing, by a first computing device comprising at least one hardware processor, an instance of a video messaging application to provide a live conference call between at least the first computing device and a second computing device, the conference call comprising audio and video communication generated through the first computing device and the second computing device; generating, by the first computing device or the second computing device, a data stream comprising audio data and video data during the live conference call, wherein the audio data embodies speech associated with a first language; causing, by the first computing device, a server to start performance of a language translation using the audio data where the speech associated with the first language is translated to a translation output associated with a second language by: determining a time delay needed for the server to complete the language translation where the speech made in the first language is translated to the translation output; imposing the time delay in a video signal for transmission to the first computing device and the second computing device; converting the speech made in the first language to text; and converting the text to the translation output made in the second language; determining, by the first computing device, that a predefined amount of the speech associated with the first language has been translated to the translation output associated with the second language sufficient to prevent a discontinuity in speech segments; and in response to the predefined amount of the speech having been translated to the translation output, rendering, by the first computing device, the translation output and the video data on the first computing device using the video signal, wherein the video data is rendered in a display associated with the first computing device after an elapse of the time delay and completion of the language translation, wherein the translation output is rendered as text in the display or played as audio on the first computing device. | 16. A computer-implemented method, comprising: executing, by a first computing device comprising at least one hardware processor, an instance of a video messaging application to provide a live conference call between at least the first computing device and a second computing device, the conference call comprising audio and video communication generated through the first computing device and the second computing device; generating, by the first computing device or the second computing device, a data stream comprising audio data and video data during the live conference call, wherein the audio data embodies speech associated with a first language; causing, by the first computing device, a server to start performance of a language translation using the audio data where the speech associated with the first language is translated to a translation output associated with a second language by: determining a time delay needed for the server to complete the language translation where the speech made in the first language is translated to the translation output; imposing the time delay in a video signal for transmission to the first computing device and the second computing device; converting the speech made in the first language to text; and converting the text to the translation output made in the second language; determining, by the first computing device, that a predefined amount of the speech associated with the first language has been translated to the translation output associated with the second language sufficient to prevent a discontinuity in speech segments; and in response to the predefined amount of the speech having been translated to the translation output, rendering, by the first computing device, the translation output and the video data on the first computing device using the video signal, wherein the video data is rendered in a display associated with the first computing device after an elapse of the time delay and completion of the language translation, wherein the translation output is rendered as text in the display or played as audio on the first computing device. 20. The computer-implemented method of claim 16 , further comprising placing, by the first computing device, the audio data and the video data into a buffer to await the language translation. | 0.67069 |
9,679,092 | 9 | 10 | 9. The method of claim 1 , wherein the constraint file comprises a parameterizable constraint evaluated at runtime, wherein the parameterizable constraint for a selected instance of a parameterizable module depends upon a parameter value from the selected instance of the parameterizable module. | 9. The method of claim 1 , wherein the constraint file comprises a parameterizable constraint evaluated at runtime, wherein the parameterizable constraint for a selected instance of a parameterizable module depends upon a parameter value from the selected instance of the parameterizable module. 10. The method of claim 9 , wherein the parameterizable constraint is specified using a scripting language. | 0.5 |
8,117,225 | 77 | 78 | 77. The computer program product of claim 15 , wherein the computer program product is operable such that each of the different online applications are capable of having associated login information for use in accessing user-specific information stored utilizing the different online applications. | 77. The computer program product of claim 15 , wherein the computer program product is operable such that each of the different online applications are capable of having associated login information for use in accessing user-specific information stored utilizing the different online applications. 78. The computer program product of claim 77 , wherein the user-specific information includes tags. | 0.524038 |
7,707,160 | 38 | 39 | 38. The computer system of claim 37 further comprising at least one web browser operable to display the factual knowledge and the new knowledge. | 38. The computer system of claim 37 further comprising at least one web browser operable to display the factual knowledge and the new knowledge. 39. The computer system of claim 38 wherein the web browser is operable to display a summary information screen providing general information on a named object using a portion of the factual knowledge retrieved from the knowledge base. | 0.5 |
9,141,403 | 10 | 11 | 10. The computer system of claim 9 , wherein the model object further comprises a second task mapped to a second command for performing the second task. | 10. The computer system of claim 9 , wherein the model object further comprises a second task mapped to a second command for performing the second task. 11. The computer system of claim 10 , wherein upon activating the at least one rendered UI element, the method comprises: executing the first task and the second task. | 0.5 |
8,380,521 | 4 | 6 | 4. The method of claim 3 , comprising determining if the speaker is authorized to invoke a conference feature associated with the second hot word. | 4. The method of claim 3 , comprising determining if the speaker is authorized to invoke a conference feature associated with the second hot word. 6. The method of claim 4 , wherein determining if the speaker is authorized comprises evaluating a record assigned to the speaker that specifies privileges allocated to the speaker. | 0.5 |
10,084,805 | 1 | 2 | 1. An apparatus, comprising: processing circuitry; and memory to store instructions that, when executed by the processing circuitry, cause the processing circuitry to: obtain scenario rules and data representing actions performed by entities; apply the scenario rules to a subset of the data to detect scenario violations based on the actions performed by the entities, the subset of the data associated with the entities of a particular entity type; group scenario violations into scenario clusters, each scenario cluster comprising one or more scenario violations associated with similar behavior performed by the entities indicated by similarity metrics, and each of the scenario clusters is one of a set of scenario clusters; determine predictive ability values for each of the scenario clusters, the predictive ability values to indicate relative significance between each of the scenario clusters to predict a target behavior; rank the scenario clusters based on the predictive ability values and remove scenario clusters from the set of scenario clusters having predictive ability values below a predictive threshold; generate combinations of scenario clusters from the set of scenario clusters, each of the combinations of scenario clusters including two or more scenario clusters; determine an effectiveness factor for each of the combinations of scenario clusters, each of the effectiveness factors based on a number of entities committing the targeted behavior as a percentage of all the entities that committed at least one scenario violation for a particular combination of scenario clusters of the combinations of scenario clusters; generate scores for each of the entities of the particular entity type using the combinations of scenario clusters having the effectiveness factor at or above an effectiveness threshold; and provide results to a system to enable presentation on a display device, the results indicating one or more of the entities that committed the targeted behavior based on the scores for each of the entities. | 1. An apparatus, comprising: processing circuitry; and memory to store instructions that, when executed by the processing circuitry, cause the processing circuitry to: obtain scenario rules and data representing actions performed by entities; apply the scenario rules to a subset of the data to detect scenario violations based on the actions performed by the entities, the subset of the data associated with the entities of a particular entity type; group scenario violations into scenario clusters, each scenario cluster comprising one or more scenario violations associated with similar behavior performed by the entities indicated by similarity metrics, and each of the scenario clusters is one of a set of scenario clusters; determine predictive ability values for each of the scenario clusters, the predictive ability values to indicate relative significance between each of the scenario clusters to predict a target behavior; rank the scenario clusters based on the predictive ability values and remove scenario clusters from the set of scenario clusters having predictive ability values below a predictive threshold; generate combinations of scenario clusters from the set of scenario clusters, each of the combinations of scenario clusters including two or more scenario clusters; determine an effectiveness factor for each of the combinations of scenario clusters, each of the effectiveness factors based on a number of entities committing the targeted behavior as a percentage of all the entities that committed at least one scenario violation for a particular combination of scenario clusters of the combinations of scenario clusters; generate scores for each of the entities of the particular entity type using the combinations of scenario clusters having the effectiveness factor at or above an effectiveness threshold; and provide results to a system to enable presentation on a display device, the results indicating one or more of the entities that committed the targeted behavior based on the scores for each of the entities. 2. The apparatus of claim 1 , wherein the similarity metrics to indicate correlation distances for the scenario violations, the scenario violations having a similarity metric below an eigen value threshold are grouped into a same scenario cluster. | 0.920013 |
8,856,153 | 11 | 18 | 11. A computer system comprising: one or more processors; one or more non-transitory computer-readable storage media storing instructions, which, when executed by the one or more processors, cause: storing a plurality of parser definitions, wherein each parser definition is associated with an object type, wherein a particular parser definition of the one or more parser definitions comprises two or more parser sub-definitions, wherein a first parser sub-definition of the two or more parser sub-definitions is associated with a first property type, and wherein a second parser sub-definition of the two or more parser sub-definitions is associated with a second property type; wherein at least the first property type is a composite type that includes two or more of a string component, a date component, or a number component; determining whether input data matches the particular parser definition; based at least in part on determining that the input data matches the particular parser definition: creating at least a first property instance of the first property type and a second property instance of the second property type; storing first data corresponding to a first portion of the input data in the first property instance, wherein the first portion of the input data and the corresponding first data each include two or more of string data, date data, or number data; storing second data based on a second portion of the input data in the second property instance. | 11. A computer system comprising: one or more processors; one or more non-transitory computer-readable storage media storing instructions, which, when executed by the one or more processors, cause: storing a plurality of parser definitions, wherein each parser definition is associated with an object type, wherein a particular parser definition of the one or more parser definitions comprises two or more parser sub-definitions, wherein a first parser sub-definition of the two or more parser sub-definitions is associated with a first property type, and wherein a second parser sub-definition of the two or more parser sub-definitions is associated with a second property type; wherein at least the first property type is a composite type that includes two or more of a string component, a date component, or a number component; determining whether input data matches the particular parser definition; based at least in part on determining that the input data matches the particular parser definition: creating at least a first property instance of the first property type and a second property instance of the second property type; storing first data corresponding to a first portion of the input data in the first property instance, wherein the first portion of the input data and the corresponding first data each include two or more of string data, date data, or number data; storing second data based on a second portion of the input data in the second property instance. 18. The computer system of claim 11 , wherein the composite type consists of a string component and a number component, and wherein the first portion of the input data and the corresponding first data each consist of string data and number data. | 0.72032 |
9,910,831 | 23 | 24 | 23. The display apparatus according to claim 22 , further comprising an inputter configured to receive a pinch operation from a user to decrease the size of the character and an expansion operation to increase the size of the character, wherein the controller is configured to, in response to the inputter receiving the pinch operation, decrease at least one of a size and a thickness of the font effect, and in response to the inputter receiving the expansion operation, increase at least one of the size and the thickness of font effect. | 23. The display apparatus according to claim 22 , further comprising an inputter configured to receive a pinch operation from a user to decrease the size of the character and an expansion operation to increase the size of the character, wherein the controller is configured to, in response to the inputter receiving the pinch operation, decrease at least one of a size and a thickness of the font effect, and in response to the inputter receiving the expansion operation, increase at least one of the size and the thickness of font effect. 24. The display apparatus according to claim 23 , the controller is configured to, in response to the inputter receiving the pinch operation, decrease at least one of the size and the thickness of the font effect in proportion to the decrease in the size of the character, and in response to the inputter receiving the expansion operation, increase at least one of the size and the thickness of font effect in proportion to the increase in the size of the character. | 0.5 |
10,146,933 | 5 | 6 | 5. The method as in claim 4 wherein selecting less that all of the individual words includes: identifying, as the first group of words, a predefined number of uncommon words from the individual words parsed from the phrase. | 5. The method as in claim 4 wherein selecting less that all of the individual words includes: identifying, as the first group of words, a predefined number of uncommon words from the individual words parsed from the phrase. 6. The method as in claim 5 wherein identifying the predefined number of uncommon words from the individual words parsed from the phrase includes: scoring each individual word parsed from the phrase based on a word preference database, and selecting, as the first group of words, four words from the individual words parsed from the phrase based on scoring each individual word. | 0.5 |
9,082,125 | 17 | 20 | 17. The method of claim 16 , wherein the analyzing the solicitee responses to the first script template from the first portion of the solicitees comprises: receiving communications over a network, each communication including a solicitee response indicator, wherein for a given communication the solicitee response indicator therein indicates whether a given solicitee has responded to a given solicitation by accepting or rejecting an offer, wherein the given solicitation is related to a given script template of the plurality of script templates; updating a solicitation response table, wherein the solicitation response table comprises a script template identifier having accumulated solicitee responses associated therewith, wherein responsive to the communication module receiving the given communication, the updating module uses the solicitee response indicator that is included therein to update the accumulated solicitee response associated with the given script template; and wherein the step of analyzing includes determining statistics related to accumulated solicitee responses for multiple script identifiers. | 17. The method of claim 16 , wherein the analyzing the solicitee responses to the first script template from the first portion of the solicitees comprises: receiving communications over a network, each communication including a solicitee response indicator, wherein for a given communication the solicitee response indicator therein indicates whether a given solicitee has responded to a given solicitation by accepting or rejecting an offer, wherein the given solicitation is related to a given script template of the plurality of script templates; updating a solicitation response table, wherein the solicitation response table comprises a script template identifier having accumulated solicitee responses associated therewith, wherein responsive to the communication module receiving the given communication, the updating module uses the solicitee response indicator that is included therein to update the accumulated solicitee response associated with the given script template; and wherein the step of analyzing includes determining statistics related to accumulated solicitee responses for multiple script identifiers. 20. The method of claim 17 , wherein the communications over the network employ an internet protocol. | 0.823427 |
9,760,838 | 18 | 19 | 18. The method of claim 13 , wherein the one or more factors further comprises a co-occurrence of two or more terms. | 18. The method of claim 13 , wherein the one or more factors further comprises a co-occurrence of two or more terms. 19. The method of claim 18 , which further comprises instructions that, when executed, identify a set of trending terms that comprises one or more sets based on a frequency of co-occurring terms from the comparison of terms. | 0.5 |
9,274,782 | 7 | 11 | 7. A system for analyzing workflows associated with a computer application, the computer application installed in a client environment, the system comprising: a memory; and at least one processor in communication with the memory, wherein the computer system is configured to perform a method, the method comprising: identifying first metadata describing an original workflow, the original workflow providing an original configuration of the computer application, the original configuration providing original functionality; identifying second metadata describing a customized workflow, wherein the customized workflow is a modified version of the original workflow, the customized workflow providing a customized configuration of the computer application, the customized configuration providing customized functionality different from the original functionality; comparing, by a computer processor, the first metadata and the second metadata; and generating, based on the comparing, analysis results representing the customized functionality; identifying third metadata describing an updated original workflow, wherein the updated original workflow is a second modified version of the original workflow, the updated original workflow providing updated configuration of an updated version of the computer application, the updated configuration providing updated functionality different from the original functionality and different from the customized functionality; further comparing, by the computer processor, the third metadata with the first metadata and the second metadata; generating, based on the further comparing, second analysis results representing customized updated functionality, the customized updated functionality including the customized functionality and the updated functionality; and creating a merged workflow based on the second analysis results, the merged workflow and the updated version of the computer application providing the customized updated functionality. | 7. A system for analyzing workflows associated with a computer application, the computer application installed in a client environment, the system comprising: a memory; and at least one processor in communication with the memory, wherein the computer system is configured to perform a method, the method comprising: identifying first metadata describing an original workflow, the original workflow providing an original configuration of the computer application, the original configuration providing original functionality; identifying second metadata describing a customized workflow, wherein the customized workflow is a modified version of the original workflow, the customized workflow providing a customized configuration of the computer application, the customized configuration providing customized functionality different from the original functionality; comparing, by a computer processor, the first metadata and the second metadata; and generating, based on the comparing, analysis results representing the customized functionality; identifying third metadata describing an updated original workflow, wherein the updated original workflow is a second modified version of the original workflow, the updated original workflow providing updated configuration of an updated version of the computer application, the updated configuration providing updated functionality different from the original functionality and different from the customized functionality; further comparing, by the computer processor, the third metadata with the first metadata and the second metadata; generating, based on the further comparing, second analysis results representing customized updated functionality, the customized updated functionality including the customized functionality and the updated functionality; and creating a merged workflow based on the second analysis results, the merged workflow and the updated version of the computer application providing the customized updated functionality. 11. The system of claim 7 , the method further comprising: retrieving at least one of the first metadata and the second metadata from a metadata store. | 0.797587 |
10,062,104 | 1 | 5 | 1. A method comprising: sending a connection request, from a seller application executing on a client machine, to a network-based transaction facility, the seller application being customizable and being customized by receiving configuration information from the network-based transaction facility, the configuration information including a hierarchal product category structure for generating a listing for a product for sale; receiving, by the seller application, a current version of the configuration information from the network-based transaction facility; sending, by the seller application, configuration confirmation to the network-based transaction facility, the configuration confirmation indicating the seller application is configured using the current version of the configuration information including the hierarchal product category structure; and sending a request for a transaction listing, the transaction listing being generated based on the current version of the configuration information. | 1. A method comprising: sending a connection request, from a seller application executing on a client machine, to a network-based transaction facility, the seller application being customizable and being customized by receiving configuration information from the network-based transaction facility, the configuration information including a hierarchal product category structure for generating a listing for a product for sale; receiving, by the seller application, a current version of the configuration information from the network-based transaction facility; sending, by the seller application, configuration confirmation to the network-based transaction facility, the configuration confirmation indicating the seller application is configured using the current version of the configuration information including the hierarchal product category structure; and sending a request for a transaction listing, the transaction listing being generated based on the current version of the configuration information. 5. The method of claim 1 , further comprises configuring the seller application based on the configuration information in response to the receiving of the configuration information. | 0.717188 |
9,229,800 | 4 | 5 | 4. The method according to claim 1 , wherein the performing phrase extraction comprises employing a compression algorithm to build a dictionary of phrases. | 4. The method according to claim 1 , wherein the performing phrase extraction comprises employing a compression algorithm to build a dictionary of phrases. 5. The method according to claim 4 , wherein the performing phrase extraction comprises performing a frequency estimation of a number of times the plurality of phrases appear in the plurality of documents. | 0.5 |
7,552,864 | 14 | 15 | 14. The method according to claim 13 , wherein information about the authenticity criteria determined on the basis of counterfeit documents is transferred from the control device to the test station. | 14. The method according to claim 13 , wherein information about the authenticity criteria determined on the basis of counterfeit documents is transferred from the control device to the test station. 15. The method according to claim 14 , wherein the information transferred from the control device to the test station relates to characteristic differences between a counterfeit and an authentic document. | 0.5 |
7,917,838 | 3 | 5 | 3. The computer implemented method of claim 2 , wherein data of the second data type is formatted according to a structured format of records and fields. | 3. The computer implemented method of claim 2 , wherein data of the second data type is formatted according to a structured format of records and fields. 5. The computer implemented method of claim 3 , wherein the records include at least one field followed by an ASCII 13 character and an ASCII 10 character in series. | 0.5 |
9,218,614 | 3 | 5 | 3. The computer implemented method of claim 1 , further including identifying a second element corresponding to the first element by searching at least one of the textual component or the graphical component based on the first element. | 3. The computer implemented method of claim 1 , further including identifying a second element corresponding to the first element by searching at least one of the textual component or the graphical component based on the first element. 5. The computer implemented method of claim 3 , further including linking the second element with the first element by receiving a linking designation. | 0.637019 |
9,236,047 | 15 | 16 | 15. A computer-readable storage device which stores a set of instructions which when executed performs a method for providing voice stream augmented note taking, the method executed by the set of instructions comprising: recording a voice stream into a buffer; converting the voice stream into a text stream, wherein the text stream includes at least one text chunk comprising a sentence or phrase, the at least one text chunk comprising content-laden text that is defined by logical breaks identifying phrase or sentence boundaries in the text; receiving a text input to an electronic document from a user; determining whether the text input at least partially matches the at least one text chunk; in response to determining that the text input at least partially matches the at least one text chunk, displaying the at least one text chunk to the user as a selectable element; receiving a selection of the displayed at least one text chunk from the user; and inserting the at least one text chunk into the electronic document. | 15. A computer-readable storage device which stores a set of instructions which when executed performs a method for providing voice stream augmented note taking, the method executed by the set of instructions comprising: recording a voice stream into a buffer; converting the voice stream into a text stream, wherein the text stream includes at least one text chunk comprising a sentence or phrase, the at least one text chunk comprising content-laden text that is defined by logical breaks identifying phrase or sentence boundaries in the text; receiving a text input to an electronic document from a user; determining whether the text input at least partially matches the at least one text chunk; in response to determining that the text input at least partially matches the at least one text chunk, displaying the at least one text chunk to the user as a selectable element; receiving a selection of the displayed at least one text chunk from the user; and inserting the at least one text chunk into the electronic document. 16. The computer-readable storage device of claim 15 , further comprising: identifying a plurality of text chunks associated with the text stream, wherein each of the plurality of text chunk is identified according to at least one boundary and wherein the at least one boundary comprises at least one of the following: a pause in the recorded voice stream, a sentence boundary, a conjunction word within the text stream, and a phrase boundary. | 0.5 |
5,537,628 | 8 | 11 | 8. A method for handling text using a code page that is different than a native code page used in a document into which the text is pasted, comprising the steps of: (a) producing a piece table by scanning characters comprising the document to develop an array of character positions and an array of data records, said characters in the document being referenced in the array of character positions by a sequence of character position coordinates, said array of character positions being divided into a plurality of pieces, each piece comprising characters of text that are disposed adjacent to each other in the document and which have common properties; (b) including in each record of the array of data records: (i) a file number for a corresponding piece of the array of character positions, said file number indicating a file in which the characters referenced in the piece are stored; and (ii) a file position in said file where said characters are to be found; (c) producing a file control block for any file that is opened to paste text into the document, said file control block including code page identifier data indicating a default code page for the text stored in said file, and thus, for the text referenced by any of the pieces; (d) providing a data block for each file that is opened to paste text into the document, said data block including a specifier for an exception code page to be used for any run of text in the file that has a different code page than the default code page for the file in which the run of text is stored, so that the default code page for the file in which the run of text is stored and the data block for the run of text are checked to determine the code page to be applied to all of the characters in said run of text; and (e) when the code page used by any run of text to be displayed is different than the native code page, translating the code page for the characters in the run of text to be displayed to the native code page using a closest available mapping, said code page for the run of text being retained if the document is saved to a file, thereby ensuring that a reference to the code page for any text pasted into the document is not omitted from the file to which the document is saved. | 8. A method for handling text using a code page that is different than a native code page used in a document into which the text is pasted, comprising the steps of: (a) producing a piece table by scanning characters comprising the document to develop an array of character positions and an array of data records, said characters in the document being referenced in the array of character positions by a sequence of character position coordinates, said array of character positions being divided into a plurality of pieces, each piece comprising characters of text that are disposed adjacent to each other in the document and which have common properties; (b) including in each record of the array of data records: (i) a file number for a corresponding piece of the array of character positions, said file number indicating a file in which the characters referenced in the piece are stored; and (ii) a file position in said file where said characters are to be found; (c) producing a file control block for any file that is opened to paste text into the document, said file control block including code page identifier data indicating a default code page for the text stored in said file, and thus, for the text referenced by any of the pieces; (d) providing a data block for each file that is opened to paste text into the document, said data block including a specifier for an exception code page to be used for any run of text in the file that has a different code page than the default code page for the file in which the run of text is stored, so that the default code page for the file in which the run of text is stored and the data block for the run of text are checked to determine the code page to be applied to all of the characters in said run of text; and (e) when the code page used by any run of text to be displayed is different than the native code page, translating the code page for the characters in the run of text to be displayed to the native code page using a closest available mapping, said code page for the run of text being retained if the document is saved to a file, thereby ensuring that a reference to the code page for any text pasted into the document is not omitted from the file to which the document is saved. 11. The method of claim 8, wherein the code page identifier data in the file control block of each file that is opened to paste text into the document comprises a plurality of bytes. | 0.930108 |
9,183,830 | 1 | 10 | 1. A method comprising: training an source hidden Markov model (HMM) based speech features generator implemented by one or more processors of a system using speech signals of a source speaker, wherein the source HMM based speech features generator comprises a configuration of source HMM state models, each of the source HMM state models having a set of generator-model functions; extracting speech features from speech signals of a target speaker to generate a target set of target-speaker vectors; for each given source HMM state model of the configuration, determining a particular target-speaker vector from among the target set that most closely matches parameters of the set of generator-model functions of the given source HMM; determining a fundamental frequency (F0) transform that speech-adapts F0 statistics of the source HMM based speech features generator to match F0 statistics of the speech of the target speaker; constructing a converted HMM based speech features generator implemented by one or more processors of the system to be the same as the source HMM based speech features generator, but wherein the parameters of the set of generator-model functions of each source HMM state model of the converted HMM based speech features generator are replaced with the determined particular most closely matching target-speaker vector from among the target set; and speech-adapting F0 statistics of the converted HMM based speech features generator using the F0 transform to thereby produce a speech-adapted converted HMM based speech features generator. | 1. A method comprising: training an source hidden Markov model (HMM) based speech features generator implemented by one or more processors of a system using speech signals of a source speaker, wherein the source HMM based speech features generator comprises a configuration of source HMM state models, each of the source HMM state models having a set of generator-model functions; extracting speech features from speech signals of a target speaker to generate a target set of target-speaker vectors; for each given source HMM state model of the configuration, determining a particular target-speaker vector from among the target set that most closely matches parameters of the set of generator-model functions of the given source HMM; determining a fundamental frequency (F0) transform that speech-adapts F0 statistics of the source HMM based speech features generator to match F0 statistics of the speech of the target speaker; constructing a converted HMM based speech features generator implemented by one or more processors of the system to be the same as the source HMM based speech features generator, but wherein the parameters of the set of generator-model functions of each source HMM state model of the converted HMM based speech features generator are replaced with the determined particular most closely matching target-speaker vector from among the target set; and speech-adapting F0 statistics of the converted HMM based speech features generator using the F0 transform to thereby produce a speech-adapted converted HMM based speech features generator. 10. The method of claim 1 , wherein constructing the converted HMM based speech features generator comprises transforming the source HMM based speech features generator into the converted HMM based speech features generator by replacing the parameters of the set of generator-model functions of each source HMM state model of the source HMM based speech features generator with the determined particular most closely matching target-speaker vector from among the target set, and wherein speech-adapting the F0 statistics of the converted HMM based speech features generator using the F0 transform comprises speech-adapting the F0 statistics of the transformed source HMM based speech features generator using the F0 transform. | 0.686799 |
9,860,262 | 27 | 40 | 27. A system for detecting a malicious program comprising: at least one computer; a sensor installed on the at least one computer, the sensor structured and arranged to collect information on resource utilization of the at least one computer; and a machine learning daemon structured and arranged to receive bundles of information from the sensor and determine a probability that the computer is infected with a malicious program, wherein the sensor and machine learning daemon are structured and arranged to: randomly sample a trace of system calls collected over a predetermined interval, each system call including context information and memory addresses for a function being monitored; compute system address differences from the trace of system calls and retaining computed values; form a group of n-grams (words) of retained differences of system addresses from the trace of system calls; form a series of process snippets, each process snippet including the context information and the retained differences of system addresses; transform each process snippet to form a compact representation (process dot) comprising a pair of elements (c, a), wherein c includes the context information and a is a sparse vector that encodes information derived from the group of n-grams; form clusters of compact representations; and compare the clusters formed to a library of malicious program samples. | 27. A system for detecting a malicious program comprising: at least one computer; a sensor installed on the at least one computer, the sensor structured and arranged to collect information on resource utilization of the at least one computer; and a machine learning daemon structured and arranged to receive bundles of information from the sensor and determine a probability that the computer is infected with a malicious program, wherein the sensor and machine learning daemon are structured and arranged to: randomly sample a trace of system calls collected over a predetermined interval, each system call including context information and memory addresses for a function being monitored; compute system address differences from the trace of system calls and retaining computed values; form a group of n-grams (words) of retained differences of system addresses from the trace of system calls; form a series of process snippets, each process snippet including the context information and the retained differences of system addresses; transform each process snippet to form a compact representation (process dot) comprising a pair of elements (c, a), wherein c includes the context information and a is a sparse vector that encodes information derived from the group of n-grams; form clusters of compact representations; and compare the clusters formed to a library of malicious program samples. 40. The system of claim 27 , wherein communication between the sensor and the machine learning daemon can be queued until later re-established. | 0.70332 |
10,073,913 | 18 | 19 | 18. A server comprising computer usable information storage medium that includes computer-readable instruction, the server configured to: receive a search query from an electronic device associated with a user; responsive to the search query, generate a search query result set, the search query result set including a vertical search result; determine a confidence level that the vertical search result is the most relevant to the search query; responsive to the confidence level being above a pre-determined threshold, cause the electronic device to display exclusively the vertical search result; responsive to the confidence level being below the pre-determined threshold, cause the electronic device to display a standard search result page (SERP); wherein to cause the electronic device to display the standard SERP, the server is configured to cause the electronic device to display both the general search results and the vertical search results; and wherein to cause the electronic device to display both the general search results and the vertical search results, the server is configured to cause the electronic device to display a widget application reflecting vertical search results. | 18. A server comprising computer usable information storage medium that includes computer-readable instruction, the server configured to: receive a search query from an electronic device associated with a user; responsive to the search query, generate a search query result set, the search query result set including a vertical search result; determine a confidence level that the vertical search result is the most relevant to the search query; responsive to the confidence level being above a pre-determined threshold, cause the electronic device to display exclusively the vertical search result; responsive to the confidence level being below the pre-determined threshold, cause the electronic device to display a standard search result page (SERP); wherein to cause the electronic device to display the standard SERP, the server is configured to cause the electronic device to display both the general search results and the vertical search results; and wherein to cause the electronic device to display both the general search results and the vertical search results, the server is configured to cause the electronic device to display a widget application reflecting vertical search results. 19. The server of claim 18 , wherein to generate a search query result set, the server is configured to transmit the search query to a search cluster and to receive ranked search result set therefrom, the search cluster having performed a general search. | 0.68408 |
9,256,795 | 6 | 7 | 6. The computer-implemented method of claim 5 , wherein analyzing the output to isolate the character string indicative of the text entity includes performing one or more heuristic tests. | 6. The computer-implemented method of claim 5 , wherein analyzing the output to isolate the character string indicative of the text entity includes performing one or more heuristic tests. 7. The computer-implemented method of claim 6 , further comprising: converting the output into text lines; and omitting characters that do not fit a pattern indicative of the text entity. | 0.5 |
8,432,368 | 1 | 14 | 1. A method for capturing user input on a computing device, comprising: receiving an electrical signal from a force sensitive sensor positioned on a case of the computing device; comparing the received electrical signal to each of a plurality of reference signal templates; calculating cross-correlation values of the received electrical signal and each of the plurality of reference signal templates; determining a best match reference signal template for the received electrical signal based on the cross-correlation values; identifying a functionality associated with the best match reference signal template; and implementing the identified functionality on the computing device. | 1. A method for capturing user input on a computing device, comprising: receiving an electrical signal from a force sensitive sensor positioned on a case of the computing device; comparing the received electrical signal to each of a plurality of reference signal templates; calculating cross-correlation values of the received electrical signal and each of the plurality of reference signal templates; determining a best match reference signal template for the received electrical signal based on the cross-correlation values; identifying a functionality associated with the best match reference signal template; and implementing the identified functionality on the computing device. 14. The method of claim 1 , wherein the computing device is a tablet computing device. | 0.924956 |
8,935,252 | 1 | 2 | 1. A method for rule generation, the method comprising: receiving, by a computer system, a plurality of classification rules; for a set of documents in a corpus, performing, by the computer system, for each document in the set, performing repeatedly: applying a plurality of rules from the plurality of classification rules applicable to the document by a) applying an applicable rule of the plurality of rules to the document to obtain a rule outcome, b) selecting another applicable rule of the plurality of rules according to the rule outcome, c) repeating a) and b) one or more times until a final rule outcome is reached; presenting the final rule outcome and the document to a rater; receiving a rating of the final rule outcome; and updating, for one or more of the applicable rules, quality metrics corresponding to the one or more of the applicable rules in accordance with the received rating, wherein updating quality metrics of the one or more applicable rules comprises, for each applicable rule, adjusting the quality metric corresponding to the each applicable rule by an amount that decreases with a number of intervening rules from the applicable rule that produced the final rule outcome; comparing the quality metrics of the plurality of rules to a rule threshold; determining that a first portion of the plurality of rules have quality metrics above the threshold; determining that a second portion of the plurality of rules have quality metrics above the threshold; adding the first portion to a production rule set and discarding the second portion; performing, by the computer system, production document classification in accordance with the production rule set. | 1. A method for rule generation, the method comprising: receiving, by a computer system, a plurality of classification rules; for a set of documents in a corpus, performing, by the computer system, for each document in the set, performing repeatedly: applying a plurality of rules from the plurality of classification rules applicable to the document by a) applying an applicable rule of the plurality of rules to the document to obtain a rule outcome, b) selecting another applicable rule of the plurality of rules according to the rule outcome, c) repeating a) and b) one or more times until a final rule outcome is reached; presenting the final rule outcome and the document to a rater; receiving a rating of the final rule outcome; and updating, for one or more of the applicable rules, quality metrics corresponding to the one or more of the applicable rules in accordance with the received rating, wherein updating quality metrics of the one or more applicable rules comprises, for each applicable rule, adjusting the quality metric corresponding to the each applicable rule by an amount that decreases with a number of intervening rules from the applicable rule that produced the final rule outcome; comparing the quality metrics of the plurality of rules to a rule threshold; determining that a first portion of the plurality of rules have quality metrics above the threshold; determining that a second portion of the plurality of rules have quality metrics above the threshold; adding the first portion to a production rule set and discarding the second portion; performing, by the computer system, production document classification in accordance with the production rule set. 2. The method of claim 1 , wherein receiving, by the computer system, the plurality of classification rules further comprises: selecting an element of the corpus; transmitting a rule request with the selected element to a rule generator; receiving a rule from the rule generator; and adding the received rule to the plurality of classification rules. | 0.5 |
9,350,561 | 9 | 11 | 9. A system for generating a computer visualization of data, comprising: a network computer, comprising: a transceiver that communicates over the network; a non-transitory memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: selecting a visualization model based on at least an allocation model, wherein the visualization model includes one or more visualization model items; mapping one or more allocation model items included in the allocation model to the one or more visualization model items; providing a resource value for each of the one or more visualization model items by at least aggregating an amount of resources corresponding to each of their one or more mapped allocation model items; storing the visualization model in the memory, wherein the visualization model includes one or more resource values for the one or more visualization model items; displaying one or more portions of the visualization model that overlays the allocation model in a user interface of the computer, wherein the allocation model underlies the visualization model; and when a visualization model item is selected using the user interface of the network computer, the one or more processors execute instructions that perform further actions, including: traversing the underlying allocation model to identify one or more source allocation model items and one or more target allocation model items that are associated with the selected visualization model item; providing one or more source visualization model items that provide resources to the selected visualization model item based on the one or more identified source allocation model items; providing one or more target visualization model items that receive resources from the selected visualization model item based on the one or more identified target allocation model items; displaying on the user interface one or more input flow lines that start from the one or more source visualization model items and end at the selected visualization model item; and displaying on the user interface one or more output flow lines that start from the selected visualization model item and end at the one or more target visualization model items; and a client computer, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and a processor device that executes instructions that perform actions, including: displaying the visualization model on a client user interface; and displaying the user-interface for interacting with the visualization model. | 9. A system for generating a computer visualization of data, comprising: a network computer, comprising: a transceiver that communicates over the network; a non-transitory memory that stores at least instructions; and one or more processor devices that execute instructions that perform actions, including: selecting a visualization model based on at least an allocation model, wherein the visualization model includes one or more visualization model items; mapping one or more allocation model items included in the allocation model to the one or more visualization model items; providing a resource value for each of the one or more visualization model items by at least aggregating an amount of resources corresponding to each of their one or more mapped allocation model items; storing the visualization model in the memory, wherein the visualization model includes one or more resource values for the one or more visualization model items; displaying one or more portions of the visualization model that overlays the allocation model in a user interface of the computer, wherein the allocation model underlies the visualization model; and when a visualization model item is selected using the user interface of the network computer, the one or more processors execute instructions that perform further actions, including: traversing the underlying allocation model to identify one or more source allocation model items and one or more target allocation model items that are associated with the selected visualization model item; providing one or more source visualization model items that provide resources to the selected visualization model item based on the one or more identified source allocation model items; providing one or more target visualization model items that receive resources from the selected visualization model item based on the one or more identified target allocation model items; displaying on the user interface one or more input flow lines that start from the one or more source visualization model items and end at the selected visualization model item; and displaying on the user interface one or more output flow lines that start from the selected visualization model item and end at the one or more target visualization model items; and a client computer, comprising: a transceiver that communicates over the network; a memory that stores at least instructions; and a processor device that executes instructions that perform actions, including: displaying the visualization model on a client user interface; and displaying the user-interface for interacting with the visualization model. 11. The system of claim 9 , wherein providing the one or more target visualization model items further comprises, providing the one or more target visualization model items based on the one or more target allocation model items that receive resources from the one or more source allocation model items that correspond to the selected visualization model item. | 0.754446 |
7,853,587 | 1 | 8 | 1. A system for providing a search result summary comprising: a search engine to generate chunks of data associated with a source; a snippet generator to generate a number of snippets using the chunks of data and at least one query term; a ranking component configured to rank the number of snippets based in part on a ranking algorithm and one or more ranking features to rank each snippet based in part on a number of words in each snippet, a number of punctuation symbols in each snippet, a number of numbers in each snippet, and a score of a proximity feature associated with each snippet, the proximity feature associated with a snippet span defined in part by one or more query terms; at least one filter configured to filter the number of snippets to reduce redundant snippets from being included in the search result summary; and, a summary generator to generate a summary which includes a number of ranked snippets that have passed through the one or more filters. | 1. A system for providing a search result summary comprising: a search engine to generate chunks of data associated with a source; a snippet generator to generate a number of snippets using the chunks of data and at least one query term; a ranking component configured to rank the number of snippets based in part on a ranking algorithm and one or more ranking features to rank each snippet based in part on a number of words in each snippet, a number of punctuation symbols in each snippet, a number of numbers in each snippet, and a score of a proximity feature associated with each snippet, the proximity feature associated with a snippet span defined in part by one or more query terms; at least one filter configured to filter the number of snippets to reduce redundant snippets from being included in the search result summary; and, a summary generator to generate a summary which includes a number of ranked snippets that have passed through the one or more filters. 8. The system of claim 1 , wherein the source includes one or more of a web page, document, and a file. | 0.920769 |
8,478,046 | 1 | 19 | 1. A method for detection of signature marks in a document, comprising: selecting candidate text objects for each of an ordered set of optical character recognition (OCR) processed document pages; providing for identifying sequences of elements in the candidate text objects, each detected element of an identified sequence occurring on a different page of the document, the sequence having a numbering pattern including an incremental part and optionally a fixed part, missing elements between two detected elements of the sequence being permitted; for an identified sequence: generating a model of the sequence, the model including: the numbering pattern of the sequence, an increment, which is computed based on the distance between pages on which consecutive elements of the sequence are identified, a valid sequence having an increment of greater than 1, and a first page, which corresponds to a page of the document on which the sequence starts; validating the sequence with the model; and for a valid sequence, identifying elements of the sequence in the pages of the document as signature marks. | 1. A method for detection of signature marks in a document, comprising: selecting candidate text objects for each of an ordered set of optical character recognition (OCR) processed document pages; providing for identifying sequences of elements in the candidate text objects, each detected element of an identified sequence occurring on a different page of the document, the sequence having a numbering pattern including an incremental part and optionally a fixed part, missing elements between two detected elements of the sequence being permitted; for an identified sequence: generating a model of the sequence, the model including: the numbering pattern of the sequence, an increment, which is computed based on the distance between pages on which consecutive elements of the sequence are identified, a valid sequence having an increment of greater than 1, and a first page, which corresponds to a page of the document on which the sequence starts; validating the sequence with the model; and for a valid sequence, identifying elements of the sequence in the pages of the document as signature marks. 19. A system for performing the method of claim 1 comprising memory which stores instructions for performing the method and a processor in communication with the memory for executing the instructions. | 0.772727 |
9,507,824 | 1 | 12 | 1. A method implemented on a computer system, the method comprising, the computer system: for each table of a plurality of database tables and for each column of a plurality of columns within the each table, creating a profile for the each column by accessing and analyzing a subset of values stored in the column; establishing a join graph of nodes, wherein each node represents one of the plurality of database tables; for each pair of a plurality of pairs of a first table and a second table from the plurality of database tables, wherein the first table is different than the second table and wherein no defined relationship exists between the first table and the second table: for each pair of a plurality of pairs of a first column from the first table and a second column from the second table, calculating a joinability score representative of a predicted level of success in performing a join from the first table on the first column to the second table on the second column, wherein the score is determined based upon the profile for the first column and the profile for the second column, and for one pair of the plurality of pairs of the first column from the first table and the second column from the second table, adding, based on the joinability score, a directed edge to the join graph from a node representing the first table to a node representing the second table; receiving a selection of a subset of the plurality of database tables; creating a join tree comprising a subset of edges in the join graph that spans a subset of nodes in the join graph corresponding to the selected subset of the plurality of database tables; extracting a set of joins represented by the subset of edges; and providing the extracted set of joins as a result, wherein creating a profile for the each column comprises: processing the each column to create a set of m observables, with m being a positive integer constant greater than one, wherein each observable is a function of a set of elements in the each column, independent of replications, and including the set of m observables in the profile for the each column, and wherein calculating the joinability score comprises: combining the set of m observables included in the profile for the first column and the set of m observables included in the profile for the second column to create a combined set of m observables, wherein each observable in the combined set of m observables is a function of a set of elements in a union between the first column and the second column, independent of replications, computing an estimated cardinality of a union between the first column and the second column based on the combined set of m observables without creating a union between the first column and the second column, computing an estimated cardinality of an intersection between the first column and the second column by subtracting the estimated cardinality of the union from the sum of an estimated cardinality of the first column and an estimated cardinality of the second column, and dividing the estimated cardinality of the intersection by the estimated cardinality of the first column. | 1. A method implemented on a computer system, the method comprising, the computer system: for each table of a plurality of database tables and for each column of a plurality of columns within the each table, creating a profile for the each column by accessing and analyzing a subset of values stored in the column; establishing a join graph of nodes, wherein each node represents one of the plurality of database tables; for each pair of a plurality of pairs of a first table and a second table from the plurality of database tables, wherein the first table is different than the second table and wherein no defined relationship exists between the first table and the second table: for each pair of a plurality of pairs of a first column from the first table and a second column from the second table, calculating a joinability score representative of a predicted level of success in performing a join from the first table on the first column to the second table on the second column, wherein the score is determined based upon the profile for the first column and the profile for the second column, and for one pair of the plurality of pairs of the first column from the first table and the second column from the second table, adding, based on the joinability score, a directed edge to the join graph from a node representing the first table to a node representing the second table; receiving a selection of a subset of the plurality of database tables; creating a join tree comprising a subset of edges in the join graph that spans a subset of nodes in the join graph corresponding to the selected subset of the plurality of database tables; extracting a set of joins represented by the subset of edges; and providing the extracted set of joins as a result, wherein creating a profile for the each column comprises: processing the each column to create a set of m observables, with m being a positive integer constant greater than one, wherein each observable is a function of a set of elements in the each column, independent of replications, and including the set of m observables in the profile for the each column, and wherein calculating the joinability score comprises: combining the set of m observables included in the profile for the first column and the set of m observables included in the profile for the second column to create a combined set of m observables, wherein each observable in the combined set of m observables is a function of a set of elements in a union between the first column and the second column, independent of replications, computing an estimated cardinality of a union between the first column and the second column based on the combined set of m observables without creating a union between the first column and the second column, computing an estimated cardinality of an intersection between the first column and the second column by subtracting the estimated cardinality of the union from the sum of an estimated cardinality of the first column and an estimated cardinality of the second column, and dividing the estimated cardinality of the intersection by the estimated cardinality of the first column. 12. The method of claim 1 , wherein the one pair of the plurality of pairs is selected based on the joinability score of the one pair exceeding the joinability scores for all others of the plurality of pairs. | 0.804511 |
8,010,547 | 9 | 10 | 9. A system for normalizing query words in web search, the system comprising: a communicator operably coupled with a search engine and to receive search queries from users; a memory to store computer instructions to be executed by a processor; a dictionary database coupled with the memory and the processor, and that is populated with a plurality of possible word normalizations from words located in query logs of the search engine, wherein the normalizations comprise candidates of splitting at least one query word and joining at least two query words; the processor operable to determine a confidence score with the split and join candidates based on a frequency of their occurrence in the query logs and to build three sub-dictionaries within the dictionary database comprising must-split, must-join, and normal based on the confidence scores; a reformulator coupled with the dictionary database and executable by the processor to reformulate one or more words of a query to generate based on the one or more words possible split candidates from the dictionary and possible candidates of join algorithmically; and a language modeler executable by the processor to apply at a language model to the possible split and loin candidates to: rank highest the candidates that match words in the must-split and must-join dictionaries; and rank the candidates that match words in the normal sub-dictionary according to a probability of being found in the query logs; wherein the communicator is operable to submit the highest ranked candidates as a reformulated query to the search engine to improve search results returned in response to the reformulated query. | 9. A system for normalizing query words in web search, the system comprising: a communicator operably coupled with a search engine and to receive search queries from users; a memory to store computer instructions to be executed by a processor; a dictionary database coupled with the memory and the processor, and that is populated with a plurality of possible word normalizations from words located in query logs of the search engine, wherein the normalizations comprise candidates of splitting at least one query word and joining at least two query words; the processor operable to determine a confidence score with the split and join candidates based on a frequency of their occurrence in the query logs and to build three sub-dictionaries within the dictionary database comprising must-split, must-join, and normal based on the confidence scores; a reformulator coupled with the dictionary database and executable by the processor to reformulate one or more words of a query to generate based on the one or more words possible split candidates from the dictionary and possible candidates of join algorithmically; and a language modeler executable by the processor to apply at a language model to the possible split and loin candidates to: rank highest the candidates that match words in the must-split and must-join dictionaries; and rank the candidates that match words in the normal sub-dictionary according to a probability of being found in the query logs; wherein the communicator is operable to submit the highest ranked candidates as a reformulated query to the search engine to improve search results returned in response to the reformulated query. 10. The system of claim 9 , wherein the reformulator is operable to generate hyphen and apostrophe candidates algorithmically. | 0.5 |
10,146,776 | 7 | 11 | 7. A computing system comprising: one or more computers; and a computer-readable medium having instructions stored thereon that, when executed by the one or more computers, cause performance of operations comprising: identifying, by the computing system, that a user input at a first computing device selected, from among a set of search results provided to the first computing device responsive to a first query, a search result that references a first electronic document; generating, by the computing system and in response to identifying that the user input at the first computing device selected the search result that references the first electronic document, an association between the first electronic document and one or more terms derived from the first query; after generating the association between the first electronic document and the one or more terms derived from the first query: receiving a second query specified by a user of a second computing device; determining a relevance of the first electronic document to the second query based at least in part on a level of similarity between (i) the one or more terms derived from the first query and associated with the first electronic document and (ii) one or more second terms derived from the second query; generating a second set of search results responsive to the second query, including selecting or ranking the first electronic document represented in the second set of search results based on the determined relevance; and transmitting the second set of search results to the second computing device. | 7. A computing system comprising: one or more computers; and a computer-readable medium having instructions stored thereon that, when executed by the one or more computers, cause performance of operations comprising: identifying, by the computing system, that a user input at a first computing device selected, from among a set of search results provided to the first computing device responsive to a first query, a search result that references a first electronic document; generating, by the computing system and in response to identifying that the user input at the first computing device selected the search result that references the first electronic document, an association between the first electronic document and one or more terms derived from the first query; after generating the association between the first electronic document and the one or more terms derived from the first query: receiving a second query specified by a user of a second computing device; determining a relevance of the first electronic document to the second query based at least in part on a level of similarity between (i) the one or more terms derived from the first query and associated with the first electronic document and (ii) one or more second terms derived from the second query; generating a second set of search results responsive to the second query, including selecting or ranking the first electronic document represented in the second set of search results based on the determined relevance; and transmitting the second set of search results to the second computing device. 11. The computing system of claim 7 , wherein generating the association between the first electronic document and the one or more terms derived from the first query comprises correlating the first electronic document with a concept expressed by the one or more terms. | 0.784912 |
4,771,401 | 1 | 6 | 1. A digital data processing apparatus for storing digitally encoded linguistic information, said apparatus comprising A. input means for accepting a signal representative of linguistic expression, B. database storage means for storing a linguistic expression database, said database storage means including master lexicon storage means for storing digitally encoded information representative of plural linguistic expressions and including plural addressable lexicon storage blocks, each said block storing one or more lexicon entries, each said lexicon entry storing signals representative of a linguistic expression, each said expression including at least one alphanumeric character, C. database access means connected with said input means and with said database storage means for accessing information stored in said linguistic expression database, said database access means including master lexicon access means for addressably accessing each said lexicon storage block according to its skeletal collation range, said skeletal collation range being defined by upper and lower bounds of a collation sequence of linguistically salient word skeletons of said one or more linguistic expressions represented within a lexicon storage block, and D. output means connected with said database access means for generating a signal representative of linguistic information. | 1. A digital data processing apparatus for storing digitally encoded linguistic information, said apparatus comprising A. input means for accepting a signal representative of linguistic expression, B. database storage means for storing a linguistic expression database, said database storage means including master lexicon storage means for storing digitally encoded information representative of plural linguistic expressions and including plural addressable lexicon storage blocks, each said block storing one or more lexicon entries, each said lexicon entry storing signals representative of a linguistic expression, each said expression including at least one alphanumeric character, C. database access means connected with said input means and with said database storage means for accessing information stored in said linguistic expression database, said database access means including master lexicon access means for addressably accessing each said lexicon storage block according to its skeletal collation range, said skeletal collation range being defined by upper and lower bounds of a collation sequence of linguistically salient word skeletons of said one or more linguistic expressions represented within a lexicon storage block, and D. output means connected with said database access means for generating a signal representative of linguistic information. 6. A digital data processing apparatus according to claim 1 wherein said linguistic expression database comprises common expression verification table means for storing digitally encoded information representative of plural commonly used linguistic expressions and including plural common-expression entries, each said common-expression entry including means for storing a first hash code of a first common linguistic expression, and wherein said database access means comprises means for addressably accessing each said common-expression entry according to a first selected index. | 0.532958 |
5,500,919 | 12 | 31 | 12. A text-to-speech controller, comprising: a text buffer for storing a text file comprised by text characters organized into words; a controller for controllably feeding text characters in the text file from said text buffer to a text-to-speech converter; and command means including a graphical user interface for accepting input commands to alter how said controller feeds text characters from said text buffer to the text-to-speech converter; wherein said controller sequentially feeds text characters from said text buffer to said text-to-speech converter in the absence of commands from said command means, and wherein said controller alters how text characters are fed from said text buffer to the text-to-speech converter in response to commands from said command means which are effectuated at interword text boundaries. | 12. A text-to-speech controller, comprising: a text buffer for storing a text file comprised by text characters organized into words; a controller for controllably feeding text characters in the text file from said text buffer to a text-to-speech converter; and command means including a graphical user interface for accepting input commands to alter how said controller feeds text characters from said text buffer to the text-to-speech converter; wherein said controller sequentially feeds text characters from said text buffer to said text-to-speech converter in the absence of commands from said command means, and wherein said controller alters how text characters are fed from said text buffer to the text-to-speech converter in response to commands from said command means which are effectuated at interword text boundaries. 31. A controller according to claim 12, further comprising a parser for parsing text in said text buffer. | 0.86875 |
9,600,460 | 21 | 22 | 21. The non-transitory computer-readable storage medium of claim 19 , wherein the attribute of each note specifies the location in the document with which the note is associated. | 21. The non-transitory computer-readable storage medium of claim 19 , wherein the attribute of each note specifies the location in the document with which the note is associated. 22. The non-transitory computer-readable storage medium of claim 21 , further comprising instructions for: determining a page order of the locations in the document associated with the notes in the aggregated set; determining an order of the notes in the aggregated set based on the locations in the document with which the notes are associated and the determined page order of the locations within the document; and displaying the notes in the aggregated set in the determined order. | 0.5 |
9,767,448 | 1 | 4 | 1. A system comprising: a non-transitory memory storing instructions; and one or more hardware processors coupled to the non-transitory memory and configured to read the instructions from the non-transitory memory to cause the system to perform operations comprising: displaying, on a graphical user interface (GUI) of the system, a list of contacts of a user; receiving a selection of a contact from the list of contacts; providing, via the GUI, available funding sources to the user; receiving a selection of a funding source from the available funding sources from the user; providing, via the GUI, a payment indicator; receiving, via the GUI, a touch input that is associated with the payment indicator; determining a transaction amount based on a time-dependent measurement of the touch input; and providing, for display via the GUI, the transaction amount along with the payment indicator. | 1. A system comprising: a non-transitory memory storing instructions; and one or more hardware processors coupled to the non-transitory memory and configured to read the instructions from the non-transitory memory to cause the system to perform operations comprising: displaying, on a graphical user interface (GUI) of the system, a list of contacts of a user; receiving a selection of a contact from the list of contacts; providing, via the GUI, available funding sources to the user; receiving a selection of a funding source from the available funding sources from the user; providing, via the GUI, a payment indicator; receiving, via the GUI, a touch input that is associated with the payment indicator; determining a transaction amount based on a time-dependent measurement of the touch input; and providing, for display via the GUI, the transaction amount along with the payment indicator. 4. The system of claim 1 , wherein the time-dependent measurement of the touch input indicates a length of the touch input. | 0.598039 |
8,117,114 | 1 | 2 | 1. A method, comprising: performing, using a computer: assigning a unique identifier to each of one or more keyword-advertisement pairs used for implementing an advertising campaign; assigning particular portions of analytics data resulting from the implementing the advertising campaign to particular ones of the unique identifiers assigned to respective ones of the one or more keyword-advertisement pairs such that each particular portion of the analytics data shares a unique identifier with a keyword-advertisement pair of the one or more keyword-advertisement pairs; receiving, via a user interface, advertisement campaign information comprising: one or more keywords to be purchased; and one or more advertisements to be displayed in response to activation of one or more of the keywords; generating a plurality of keyword-advertisement pairs, wherein each of the keyword-advertisement pairs specify: at least one of the keywords to be purchased; and one of the advertisements to be displayed in response to activation of the at least one of the keywords to be purchased; receiving, via the user interface, a request for an estimate of performance of the advertisement campaign; determining, in response to receiving the request for an estimate of performance of the advertisement campaign, an estimate of one or more analytic metrics for the one or more keywords to be purchased, wherein the estimate of performance of one or more analytic metrics for the one or more keywords to be purchased is based at least in part on historical information, and the estimating further comprises reviewing metrics for ones of the one or more keyword-advertisement that are selected for re-use; and providing, for display via the user interface, the estimate of one or more analytic metrics for the one or more keywords to be purchased. | 1. A method, comprising: performing, using a computer: assigning a unique identifier to each of one or more keyword-advertisement pairs used for implementing an advertising campaign; assigning particular portions of analytics data resulting from the implementing the advertising campaign to particular ones of the unique identifiers assigned to respective ones of the one or more keyword-advertisement pairs such that each particular portion of the analytics data shares a unique identifier with a keyword-advertisement pair of the one or more keyword-advertisement pairs; receiving, via a user interface, advertisement campaign information comprising: one or more keywords to be purchased; and one or more advertisements to be displayed in response to activation of one or more of the keywords; generating a plurality of keyword-advertisement pairs, wherein each of the keyword-advertisement pairs specify: at least one of the keywords to be purchased; and one of the advertisements to be displayed in response to activation of the at least one of the keywords to be purchased; receiving, via the user interface, a request for an estimate of performance of the advertisement campaign; determining, in response to receiving the request for an estimate of performance of the advertisement campaign, an estimate of one or more analytic metrics for the one or more keywords to be purchased, wherein the estimate of performance of one or more analytic metrics for the one or more keywords to be purchased is based at least in part on historical information, and the estimating further comprises reviewing metrics for ones of the one or more keyword-advertisement that are selected for re-use; and providing, for display via the user interface, the estimate of one or more analytic metrics for the one or more keywords to be purchased. 2. The method of claim 1 , wherein the one or more analytic metrics comprise a cost of the advertising campaign associated with each of the one or more keywords. | 0.828723 |
8,630,847 | 1 | 7 | 1. A computer-implemented method, comprising: identifying a word corpus; determining a weight based on a type of the word corpus, the weight indicating a degree of reliability for updating an existing input method editor dictionary using the word corpus; associating a word probability value with each word in the word corpus; identifying a sentence; determining candidate segmentations of the sentence based on the word corpus; determining a segmentation probability value for each of the candidate segmentations, each candidate segmentation having one or more segments that define words forming the sentence; determining a weighted segmentation probability value for each segmentation probability value based on the weight; determining, in a data processing apparatus, a soft-count value for each word in the word corpus based on the weighted segmentation probability values of the candidate segmentations in which the word appears and a number of occurrences of the word in the candidate segmentations in which the word appears; iteratively adjusting the associated word probability value for each word in the word corpus based on the soft-count value for the word; and updating the existing input method editor dictionary by iteratively adding a plurality of words from the word corpus and their respective associated word probability values to the existing input method editor dictionary, wherein the plurality of words from the word corpus are words having the highest associated word probability values. | 1. A computer-implemented method, comprising: identifying a word corpus; determining a weight based on a type of the word corpus, the weight indicating a degree of reliability for updating an existing input method editor dictionary using the word corpus; associating a word probability value with each word in the word corpus; identifying a sentence; determining candidate segmentations of the sentence based on the word corpus; determining a segmentation probability value for each of the candidate segmentations, each candidate segmentation having one or more segments that define words forming the sentence; determining a weighted segmentation probability value for each segmentation probability value based on the weight; determining, in a data processing apparatus, a soft-count value for each word in the word corpus based on the weighted segmentation probability values of the candidate segmentations in which the word appears and a number of occurrences of the word in the candidate segmentations in which the word appears; iteratively adjusting the associated word probability value for each word in the word corpus based on the soft-count value for the word; and updating the existing input method editor dictionary by iteratively adding a plurality of words from the word corpus and their respective associated word probability values to the existing input method editor dictionary, wherein the plurality of words from the word corpus are words having the highest associated word probability values. 7. The method of claim 1 wherein determining a soft-count value of a word in the sentence comprises multiplying a sum of the weighted segmentation probability values of candidate segmentations of a substring before the word, the probability value of the word, and a sum of the weighted segmentation probability values of candidate segmentations of a substring after the word. | 0.632353 |
9,392,084 | 13 | 16 | 13. A system comprising: a CPU, a computer readable memory and a computer readable storage medium; program instructions to capture data and ecology information about an entire existing network infrastructure; program instructions to generate a first generalized descriptive language for the captured data and ecology information; program instructions to capture capabilities and configuration data from a plurality of target devices on an existing network infrastructure; program instructions to generate a second generalized descriptive language for the captured capabilities and configuration data; program instructions to match nodal attributes of the first generalized descriptive language and the second generalized descriptive language to generate a heteromophic map of a replacement network infrastructure; and program instructions to reconstruct an entirety of the existing network infrastructure using the heteromorphic map by introducing functionally equivalent hardware components that correspond to the second generalized descriptive language, wherein the program instructions are stored on the computer readable storage medium for execution by the CPU via the computer readable memory. | 13. A system comprising: a CPU, a computer readable memory and a computer readable storage medium; program instructions to capture data and ecology information about an entire existing network infrastructure; program instructions to generate a first generalized descriptive language for the captured data and ecology information; program instructions to capture capabilities and configuration data from a plurality of target devices on an existing network infrastructure; program instructions to generate a second generalized descriptive language for the captured capabilities and configuration data; program instructions to match nodal attributes of the first generalized descriptive language and the second generalized descriptive language to generate a heteromophic map of a replacement network infrastructure; and program instructions to reconstruct an entirety of the existing network infrastructure using the heteromorphic map by introducing functionally equivalent hardware components that correspond to the second generalized descriptive language, wherein the program instructions are stored on the computer readable storage medium for execution by the CPU via the computer readable memory. 16. The system of claim 13 , wherein the reconstructing the entirety of the existing network infrastructure further comprises: provisioning hardware of the determined functionally equivalent components; and provisioning software on the hardware of the determined functionally equivalent components. | 0.5 |
8,423,576 | 1 | 3 | 1. A method to process data, comprising: parsing input from a requestor, the input comprising at least one of a query or a command, expressed in a natural human language, that is parsed using action extractors and named entity extractors into a structured stream query language query comprising an indication of at least one data stream or set of data streams and at least one action to be performed on the, at least one, data stream or set of data streams; mapping the structured stream query language query into a graph of processing elements that are selected and interconnected so as to execute the structured stream query language query comprising at least one action and at least one named entity; instantiating the graph of processing elements and connecting and initializing the instantiated graph of processing elements with an identified, at least one, data stream or set of data streams to receive data from the identified at least one data stream or set of data streams; and outputting a result of the structured stream query language query to the requestor. | 1. A method to process data, comprising: parsing input from a requestor, the input comprising at least one of a query or a command, expressed in a natural human language, that is parsed using action extractors and named entity extractors into a structured stream query language query comprising an indication of at least one data stream or set of data streams and at least one action to be performed on the, at least one, data stream or set of data streams; mapping the structured stream query language query into a graph of processing elements that are selected and interconnected so as to execute the structured stream query language query comprising at least one action and at least one named entity; instantiating the graph of processing elements and connecting and initializing the instantiated graph of processing elements with an identified, at least one, data stream or set of data streams to receive data from the identified at least one data stream or set of data streams; and outputting a result of the structured stream query language query to the requestor. 3. The method of claim 1 , where the requestor is one of a user or a software application. | 0.925125 |
9,524,650 | 1 | 4 | 1. An automated training system comprising: a database containing audio files and a training script that defines a sequence of the audio files making up a training call; a training engine that automatically makes a call to an external system via a first communications connection, executes the training script and outputs audio data contained in the audio files to the external system via the first communications connection in accordance with the training script; a response receiver that receives: a) voice data from the external system, the voice data representing voice responses of a user of the external system to the training call, the response receiver comprising an automated speech recognition system that receives and interprets the voice data and a speech analysis component that receives the voice data and determines the tone of the voice of the user of the external system based on the voice data, and b) receives external system response data representing the responses of the user of the external system to the training call via the external system, the responses being made via one or more input devices, wherein the received external system response data comprises data representing a screen displayed to the user of the external system; and an analysis engine that: receives data representing the voice responses from the automated speech recognition system, determines the number of words in the voice responses that were not understood by the automated speech recognition system, compares the voice responses of the user of the external system to stored expected voice responses, compares the external system responses of the user of the external system to stored correct external system responses, receives data representing the tone of the voice of the user of the external system from the speech analysis component, and generates a scoring report for the user based on the determined number of words in the voice responses that were not understood, the comparison of the voice responses, the tone, and the comparison of the external system responses. | 1. An automated training system comprising: a database containing audio files and a training script that defines a sequence of the audio files making up a training call; a training engine that automatically makes a call to an external system via a first communications connection, executes the training script and outputs audio data contained in the audio files to the external system via the first communications connection in accordance with the training script; a response receiver that receives: a) voice data from the external system, the voice data representing voice responses of a user of the external system to the training call, the response receiver comprising an automated speech recognition system that receives and interprets the voice data and a speech analysis component that receives the voice data and determines the tone of the voice of the user of the external system based on the voice data, and b) receives external system response data representing the responses of the user of the external system to the training call via the external system, the responses being made via one or more input devices, wherein the received external system response data comprises data representing a screen displayed to the user of the external system; and an analysis engine that: receives data representing the voice responses from the automated speech recognition system, determines the number of words in the voice responses that were not understood by the automated speech recognition system, compares the voice responses of the user of the external system to stored expected voice responses, compares the external system responses of the user of the external system to stored correct external system responses, receives data representing the tone of the voice of the user of the external system from the speech analysis component, and generates a scoring report for the user based on the determined number of words in the voice responses that were not understood, the comparison of the voice responses, the tone, and the comparison of the external system responses. 4. The automated training system according to claim 1 , wherein the analysis engine measures the total time of the training call, and further generates the scoring report for the user based on the measured total time. | 0.796816 |
8,069,046 | 5 | 7 | 5. A system for interpreting natural language utterances using out-of-vocabulary and noise toleration capabilities, comprising: an input device configured to receive an utterance; and a speech interpretation engine configured to: recognize a phoneme stream contained in the received utterance; map the recognized phoneme stream to a syllable series that includes one or more syllables that an acoustic grammar phonemically represents in accordance with an acoustic speech model; and generate an interpretation of the utterance, wherein the generated interpretation includes the one or more syllables in the syllable series mapped to the recognized phoneme stream. | 5. A system for interpreting natural language utterances using out-of-vocabulary and noise toleration capabilities, comprising: an input device configured to receive an utterance; and a speech interpretation engine configured to: recognize a phoneme stream contained in the received utterance; map the recognized phoneme stream to a syllable series that includes one or more syllables that an acoustic grammar phonemically represents in accordance with an acoustic speech model; and generate an interpretation of the utterance, wherein the generated interpretation includes the one or more syllables in the syllable series mapped to the recognized phoneme stream. 7. The system of claim 5 , wherein the acoustic speech model includes an unstressed central vowel that links sequential phonemic elements in the acoustic speech model. | 0.508824 |
9,251,221 | 1 | 22 | 1. A method, comprising: accessing, by one or more processing devices, a set of events, wherein each event in the set of events is associated with a time stamp and includes a portion of machine data indicative of performance or operation of an information technology environment; accessing an object-scoring rule that (i) includes a search query that determines when events meet a triggering condition; (ii) identifies an object representing a component of the information technology environment, an application running in the information technology environment, or a person using a component in the information technology environment, and (iii) specifies a numerical contribution to a score for the object, the numerical contribution to be applied to the score based at least on part on a determination that the triggering condition is met; executing the search query of the object-scoring rule against the set of events to determine if the triggering condition of the object-scoring rule is met; based on determining that the triggering condition is met, generating a record of the numerical contribution specified in the object-scoring rule, the record associating the numerical contribution with a time indicator and indicating the object whose score should be affected by the contribution; identifying, using one or more records of numerical contributions, a set of numerical contributions having associated time indicators falling within a defined time period; and calculating the score for the object based on the set of numerical contributions, wherein the score indicates at least one of: an indication of a security risk posed by the component or person that the object represents, an indication of performance of the component of the information technology environment that the object represents, or an indication of performance of the application that the object represents. | 1. A method, comprising: accessing, by one or more processing devices, a set of events, wherein each event in the set of events is associated with a time stamp and includes a portion of machine data indicative of performance or operation of an information technology environment; accessing an object-scoring rule that (i) includes a search query that determines when events meet a triggering condition; (ii) identifies an object representing a component of the information technology environment, an application running in the information technology environment, or a person using a component in the information technology environment, and (iii) specifies a numerical contribution to a score for the object, the numerical contribution to be applied to the score based at least on part on a determination that the triggering condition is met; executing the search query of the object-scoring rule against the set of events to determine if the triggering condition of the object-scoring rule is met; based on determining that the triggering condition is met, generating a record of the numerical contribution specified in the object-scoring rule, the record associating the numerical contribution with a time indicator and indicating the object whose score should be affected by the contribution; identifying, using one or more records of numerical contributions, a set of numerical contributions having associated time indicators falling within a defined time period; and calculating the score for the object based on the set of numerical contributions, wherein the score indicates at least one of: an indication of a security risk posed by the component or person that the object represents, an indication of performance of the component of the information technology environment that the object represents, or an indication of performance of the application that the object represents. 22. The method of claim 1 , wherein the numerical contribution is proportional to a number of occurrences of the triggering condition. | 0.896445 |
8,069,130 | 8 | 12 | 8. The method of claim 1 , wherein defining a first semiconductor testing rule comprises defining a parameter associated with said rule. | 8. The method of claim 1 , wherein defining a first semiconductor testing rule comprises defining a parameter associated with said rule. 12. The method of claim 8 , wherein defining a parameter comprises defining a rule action to be taken if rule criteria are met. | 0.584967 |
8,965,129 | 1 | 3 | 1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: cropping a frame of the real-time video feed of one or more words of the first language to fit inside a bounding box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments while determining at least a shape score for at least one merged character segment; performing character recognition on the merged character segments by utilizing at least the shape score of the at least one merged character segment to produce a plurality of recognized characters with high scores; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language. | 1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: cropping a frame of the real-time video feed of one or more words of the first language to fit inside a bounding box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments while determining at least a shape score for at least one merged character segment; performing character recognition on the merged character segments by utilizing at least the shape score of the at least one merged character segment to produce a plurality of recognized characters with high scores; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language. 3. The method of claim 1 , wherein two or more lines of the first language is being translated. | 0.91578 |
8,594,468 | 1 | 4 | 1. A method of annotating a personal image comprising: compiling visual features and textual information from a plurality of images; hashing the visual features; clustering the plurality of images based at least in part on a hash value, the clustering creating clustered images; building one or more statistical language models based at least in part on the clustered images; and annotating the personal image by selecting words with a maximum joint probability between the personal image and the clustered images. | 1. A method of annotating a personal image comprising: compiling visual features and textual information from a plurality of images; hashing the visual features; clustering the plurality of images based at least in part on a hash value, the clustering creating clustered images; building one or more statistical language models based at least in part on the clustered images; and annotating the personal image by selecting words with a maximum joint probability between the personal image and the clustered images. 4. A method as recited in claim 1 , wherein the one or more statistical language models is a unigram model that calculates a probability that a word is associated with the personal image based at least in part on a visual similarity between the personal image and the clustered images and a prior probability of the clustered images. | 0.5 |
8,595,268 | 6 | 8 | 6. A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for compressing objects, the method comprising: receiving a request to write a first object including a first key and a first value, wherein the first object is of a given type; receiving a request to write a second object including a second key and a second value, wherein the second object is of the given type; classifying the first object to a compression dictionary according to at least one rule based on a value of the first object and/or the key of the first object; classifying the second object to the compression dictionary according to at least one rule based on a value of the second object and/or the key of the second object; and compressing the first object and the second object based on the compression dictionary; identifying first matching patterns in a pair of objects; determining if the number of first matching patterns exceeds a first threshold; when the number of first matching patterns is determined to exceed the first threshold, selecting an object from the pair of objects and identifying second matching patterns in the selected object and the compression dictionary; determining if the number of second matching patterns exceeds a second threshold; and when the number of second matching patterns is determined to exceed the second threshold, assigning the pair of objects to the compression dictionary. | 6. A non-transitory computer-readable medium containing computer-executable instructions that, when executed by a processor, cause the processor to perform a method for compressing objects, the method comprising: receiving a request to write a first object including a first key and a first value, wherein the first object is of a given type; receiving a request to write a second object including a second key and a second value, wherein the second object is of the given type; classifying the first object to a compression dictionary according to at least one rule based on a value of the first object and/or the key of the first object; classifying the second object to the compression dictionary according to at least one rule based on a value of the second object and/or the key of the second object; and compressing the first object and the second object based on the compression dictionary; identifying first matching patterns in a pair of objects; determining if the number of first matching patterns exceeds a first threshold; when the number of first matching patterns is determined to exceed the first threshold, selecting an object from the pair of objects and identifying second matching patterns in the selected object and the compression dictionary; determining if the number of second matching patterns exceeds a second threshold; and when the number of second matching patterns is determined to exceed the second threshold, assigning the pair of objects to the compression dictionary. 8. The non-transitory medium of claim 6 , the method further comprising writing the first object to an in-memory, non-relational data store as an uncompressed object before the first object is compressed, and overwriting the uncompressed object with a compressed form of the first objected object when the first object is compressed. | 0.5 |
8,027,948 | 14 | 17 | 14. A system for generating an ontology, comprising: a concept determining module for determining plural concepts from a data set by using a first predetermined pattern, said determining plural concepts comprising generating a plurality of web service ontologies; a relationship determining module for using a second predetermined pattern to determine a relationship between said plural concepts, and between a concept and a concept token in said plural concepts; and a computer processor comprising an ontology generator for generating said ontology based on said relationship. | 14. A system for generating an ontology, comprising: a concept determining module for determining plural concepts from a data set by using a first predetermined pattern, said determining plural concepts comprising generating a plurality of web service ontologies; a relationship determining module for using a second predetermined pattern to determine a relationship between said plural concepts, and between a concept and a concept token in said plural concepts; and a computer processor comprising an ontology generator for generating said ontology based on said relationship. 17. The system of claim 14 , wherein said concept determining module comprises a source ontology generator for generating a source ontology from a source web service collection, and a target ontology generator for generating a target ontology from a target web service collection. | 0.5 |
8,566,790 | 2 | 3 | 2. The system of claim 1 , wherein a type definition of the data representation language schema is used to interpret the script. | 2. The system of claim 1 , wherein a type definition of the data representation language schema is used to interpret the script. 3. The system of claim 2 , wherein at least one of the type definitions is a complex type definition. | 0.667763 |
8,756,252 | 1 | 4 | 1. A method, comprising: determining categories and an associated category graph for a parsing framework associated with execution of an automated software build tool; determining a plurality of types, wherein each type implements at least one category; automatically determining, by a processor, a set of types for each category, wherein a type is included in a set for a particular category when that type implements that category or any descendant of that category in the category graph; automatically defining, by the processor, namespaces for the categories based at least in part on sets of types associated with each category, wherein the categories and namespaces are associated with a description; simultaneously determining, using reflection of a single Java bean and associated Java bean method, both: (i) a name of a parameter in accordance a method name, and (ii) a category and said associated automatically defined namespace in accordance with a parameter type; automatically parsing two nesting levels using both (i) the name of the parameter and (ii) the category and said associated namespace, wherein the category and said associated namespace are identified by a first nested element level and the parameter type is identified by a second nested element level within the first nested element level; executing the automated software build tool in accordance with the defined namespaces such that (i) a first parameter name at a first location in the automated software build tool refers to first namespace and is resolved to a first parameter type and (ii) the first parameter name at a second location in the automated software build tool refers to a second namespace and is resolved to a second parameter type; and creating a graph structure based on the description in accordance with parsing by the parsing framework. | 1. A method, comprising: determining categories and an associated category graph for a parsing framework associated with execution of an automated software build tool; determining a plurality of types, wherein each type implements at least one category; automatically determining, by a processor, a set of types for each category, wherein a type is included in a set for a particular category when that type implements that category or any descendant of that category in the category graph; automatically defining, by the processor, namespaces for the categories based at least in part on sets of types associated with each category, wherein the categories and namespaces are associated with a description; simultaneously determining, using reflection of a single Java bean and associated Java bean method, both: (i) a name of a parameter in accordance a method name, and (ii) a category and said associated automatically defined namespace in accordance with a parameter type; automatically parsing two nesting levels using both (i) the name of the parameter and (ii) the category and said associated namespace, wherein the category and said associated namespace are identified by a first nested element level and the parameter type is identified by a second nested element level within the first nested element level; executing the automated software build tool in accordance with the defined namespaces such that (i) a first parameter name at a first location in the automated software build tool refers to first namespace and is resolved to a first parameter type and (ii) the first parameter name at a second location in the automated software build tool refers to a second namespace and is resolved to a second parameter type; and creating a graph structure based on the description in accordance with parsing by the parsing framework. 4. The method of claim 1 , wherein a first tag is associated with a first namespace and a second tag, nested with respect to the first tag and having the same name as the first tag, is associated with a second namespace separate from the first namespace. | 0.51711 |
9,672,819 | 19 | 20 | 19. A linguistic recognition method, the method comprising: building a database; receiving a language input by a user; recognizing a character from the input language; and recognizing a word by stochastically inferring the word or a sentence based on stored common linguistic model data and individual linguistic model data from the recognized character, wherein the database comprises: the common linguistic model data configured to stochastically infer the word or the sentence from the character acquired by recognizing a language input by the user, and the individual linguistic model data configured to stochastically infer an individual use word or an individual use sentence related to the user by collecting recognition-related information through one or more client devices used by the user after storing the common linguistic data and analyzing the collected recognition-related information, and wherein the individual use word is excluded from the common linguistic model data. | 19. A linguistic recognition method, the method comprising: building a database; receiving a language input by a user; recognizing a character from the input language; and recognizing a word by stochastically inferring the word or a sentence based on stored common linguistic model data and individual linguistic model data from the recognized character, wherein the database comprises: the common linguistic model data configured to stochastically infer the word or the sentence from the character acquired by recognizing a language input by the user, and the individual linguistic model data configured to stochastically infer an individual use word or an individual use sentence related to the user by collecting recognition-related information through one or more client devices used by the user after storing the common linguistic data and analyzing the collected recognition-related information, and wherein the individual use word is excluded from the common linguistic model data. 20. The method according to claim 19 , wherein the individual linguistic model data is acquired by at least one of analyzing an individual unique language pattern, analyzing user member group language pattern, and analyzing a real-time word on the World Wide Web. | 0.5 |
8,180,795 | 3 | 4 | 3. The computer readable medium of claim 1 wherein the executable instructions to update include executable instructions to initially deliver the custom values to a web service. | 3. The computer readable medium of claim 1 wherein the executable instructions to update include executable instructions to initially deliver the custom values to a web service. 4. The computer readable medium of claim 3 wherein the executable instructions to update include executable instructions to deliver the custom values from the web service to the data source. | 0.5 |
9,342,839 | 1 | 5 | 1. A computer-implemented method comprising: receiving a search query; identifying search results responsive to the query, including identifying a first search result in a top set of search results that is associated with a first brand; determining the first brand associated with the first search result; based at least in part on the query, identifying one or more eligible content items for delivery along with the search results responsive to the query; determining a second brand associated with at least one of the eligible content items; comparing the first and second brands, and when the first and second brands are the same, creating a combined content item, the combined content item being a single display unit including at least a portion of the first search result and at least a portion of content from the first eligible content item, wherein the respective portions are less than an entire portion of content and being presented along with other search results responsive to the search query, wherein creating further includes determining content sponsor preferences associated with a content sponsor of the first eligible content item, the content sponsor preferences including one or more specifications for how to combine the first eligible content item with the first search result, and wherein creating further includes generating the combined content item in accordance with the content sponsor preferences; and providing the combined content item as a search result responsive to the request. | 1. A computer-implemented method comprising: receiving a search query; identifying search results responsive to the query, including identifying a first search result in a top set of search results that is associated with a first brand; determining the first brand associated with the first search result; based at least in part on the query, identifying one or more eligible content items for delivery along with the search results responsive to the query; determining a second brand associated with at least one of the eligible content items; comparing the first and second brands, and when the first and second brands are the same, creating a combined content item, the combined content item being a single display unit including at least a portion of the first search result and at least a portion of content from the first eligible content item, wherein the respective portions are less than an entire portion of content and being presented along with other search results responsive to the search query, wherein creating further includes determining content sponsor preferences associated with a content sponsor of the first eligible content item, the content sponsor preferences including one or more specifications for how to combine the first eligible content item with the first search result, and wherein creating further includes generating the combined content item in accordance with the content sponsor preferences; and providing the combined content item as a search result responsive to the request. 5. The method of claim 1 further comprising combining other information associated with the brand in the combination content item. | 0.762774 |
9,092,303 | 14 | 17 | 14. The import manager of claim 12 , further comprising: an operation module configured to perform the operation on the first element; wherein the operation module is further configured to automatically perform the operation on the plurality of second elements, based on the first element being dependent on the plurality of second elements. | 14. The import manager of claim 12 , further comprising: an operation module configured to perform the operation on the first element; wherein the operation module is further configured to automatically perform the operation on the plurality of second elements, based on the first element being dependent on the plurality of second elements. 17. The import manager of claim 14 , wherein the consumption indicator module is further configured to interpret a second resource consumption indicator that specifies a second designated resource of the plurality of resources that the one or more second elements of the plurality of second elements consume; wherein the comparison module is further configured to compare the second resource consumption indicator to the plurality of indexes to match the second resource consumption indicator to an index of the plurality of indexes that corresponds to the second designated resource; wherein the dependency determination module is configured to determine that the one or more second elements depend on a third element that produces the second designated resource based on the index that corresponds to the second designated resource having a value that specifies that the third element produces the second designated resource; and wherein the import manager further comprises: an operation module configured to automatically perform the operation on the third element, based on the one or more second elements being dependent on the third element and further based on the third element being a hidden selectable element or a non-selectable element, in response to performance of the operation on the first element. | 0.643051 |
8,615,527 | 13 | 20 | 13. The computer readable storage medium of claim 12 , further comprising determining, based on the monitored queries, whether one or more of the referenced fields is a searchable field. | 13. The computer readable storage medium of claim 12 , further comprising determining, based on the monitored queries, whether one or more of the referenced fields is a searchable field. 20. The computer readable storage medium of claim 13 , wherein generating the abstract representations comprises generating an abstract representation for at least one of the fields returned as query results. | 0.5 |
8,782,042 | 31 | 32 | 31. The method of claim 25 , wherein each process in the plurality of processes further generates a relevancy score for each candidate identity attribute, the relevancy score representing a degree of correctness that the particular entity identified by the candidate identity attribute is the entity. | 31. The method of claim 25 , wherein each process in the plurality of processes further generates a relevancy score for each candidate identity attribute, the relevancy score representing a degree of correctness that the particular entity identified by the candidate identity attribute is the entity. 32. The method of claim 31 , wherein calculating the score for the particular candidate identity attribute further comprises calculating the score based on the particular candidate identity attribute's relevancy score. | 0.556911 |
9,015,284 | 5 | 8 | 5. The apparatus of claim 1 , wherein the apparatus further comprising a component configured to: receive over the second interface a request, the request comprising a domain name and a group identifier and optional parameters; resolve the members of the group; send the request to the members; receive response from the members; and send a response to the sender of the request. | 5. The apparatus of claim 1 , wherein the apparatus further comprising a component configured to: receive over the second interface a request, the request comprising a domain name and a group identifier and optional parameters; resolve the members of the group; send the request to the members; receive response from the members; and send a response to the sender of the request. 8. The apparatus of claim 5 , wherein the apparatus is configured to send the response to the sender of the request as a JavaScript Object Notation object comprising one or more arrays of responses. | 0.811429 |
5,539,861 | 7 | 9 | 7. The method of claim 1, wherein said step of using said bio-signal to produce said modified signal comprises using said bio-signal to modify a spectrum of said signal. | 7. The method of claim 1, wherein said step of using said bio-signal to produce said modified signal comprises using said bio-signal to modify a spectrum of said signal. 9. The method of claim 7, wherein a portion of said spectrum is amplified. | 0.506667 |
9,251,138 | 1 | 21 | 1. A computer system for analyzing natural language comprising: a phrase database configured to store phrases; and a phrase analysis engine coupled with the phrase database and configured to: obtain a corpus comprising a plurality of phrases; extract phrases from the corpus; determine a degree of similarity among the phrases based on phrase contexts associated with the phrases and on overlaps among phrase contexts determined by surrounding phrases in the corpus proximate to the phrases; and cluster the phrases into classes within the phrase database based on the degree of similarity among the phrase; and a user interface configured to present a response generated from phrases obtained from the phrase database to a user. | 1. A computer system for analyzing natural language comprising: a phrase database configured to store phrases; and a phrase analysis engine coupled with the phrase database and configured to: obtain a corpus comprising a plurality of phrases; extract phrases from the corpus; determine a degree of similarity among the phrases based on phrase contexts associated with the phrases and on overlaps among phrase contexts determined by surrounding phrases in the corpus proximate to the phrases; and cluster the phrases into classes within the phrase database based on the degree of similarity among the phrase; and a user interface configured to present a response generated from phrases obtained from the phrase database to a user. 21. The system of claim 1 , wherein the phrases relate to a request for help. | 0.757862 |
8,407,611 | 10 | 19 | 10. An apparatus comprising: at least one memory configured to store information defining a placeholder widget comprising a roughly drawn sketch, the placeholder widget having a text property; and at least one processor configured to: execute a widget editor configured to define the placeholder widget; execute a GUI editor configured to receive information defining a prototype graphical user interface (GUI) that comprises an instance of the placeholder widget, wherein the widget editor is separate from the GUI editor; present the prototype GUI to a user, an appearance of the instance of the placeholder widget based on the text property of the placeholder widget; in response to a user selection of the instance of the placeholder widget, present a list of second widgets to the user and receiving a user selection of one of the second widgets; and in response to the selection of the selected second widget, replace the instance of the placeholder widget with an instance of the selected second widget in the prototype GUI and transfer the text property of the placeholder widget to the instance of the selected second widget. | 10. An apparatus comprising: at least one memory configured to store information defining a placeholder widget comprising a roughly drawn sketch, the placeholder widget having a text property; and at least one processor configured to: execute a widget editor configured to define the placeholder widget; execute a GUI editor configured to receive information defining a prototype graphical user interface (GUI) that comprises an instance of the placeholder widget, wherein the widget editor is separate from the GUI editor; present the prototype GUI to a user, an appearance of the instance of the placeholder widget based on the text property of the placeholder widget; in response to a user selection of the instance of the placeholder widget, present a list of second widgets to the user and receiving a user selection of one of the second widgets; and in response to the selection of the selected second widget, replace the instance of the placeholder widget with an instance of the selected second widget in the prototype GUI and transfer the text property of the placeholder widget to the instance of the selected second widget. 19. The apparatus of claim 10 , wherein: the processor executes the widget editor based on first user input; the processor executes the GUI editor based on second user input; and the GUI editor is configured to invoke the widget editor in order to edit widgets contained in one or more prototype GUIs. | 0.5 |
7,546,529 | 1 | 14 | 1. A computer-implemented method for correcting text, comprising the steps of: receiving a text selection comprising a plurality of text components derived from different input sources, wherein at least one of the text components comprises a stochastic text component derived from a stochastic input source; receiving a command to display alternatives for the text selection; parsing the text selection into the text components; retrieving the stochastic model for the stochastic text component from the at least one stochastic input source; combining the stochastic model with other text components to produce a list of alternatives for the text selection, wherein the other text components include non-stochastic text components received from a non-stochastic input source; and displaying the list of alternatives for the text selection on a display device, wherein the text selection comprises a plurality of stochastic text components and one of the stochastic models comprises an “n-best” candidate list and another stochastic model comprises a lattice, and wherein the step of combining the stochastic models to produce a list of alternatives for the text selection further comprises the steps of: creating an “n-best” candidate list corresponding to the lattice; and producing the list of alternatives for the text selection by combining the “n-best” candidate lists for the text components. | 1. A computer-implemented method for correcting text, comprising the steps of: receiving a text selection comprising a plurality of text components derived from different input sources, wherein at least one of the text components comprises a stochastic text component derived from a stochastic input source; receiving a command to display alternatives for the text selection; parsing the text selection into the text components; retrieving the stochastic model for the stochastic text component from the at least one stochastic input source; combining the stochastic model with other text components to produce a list of alternatives for the text selection, wherein the other text components include non-stochastic text components received from a non-stochastic input source; and displaying the list of alternatives for the text selection on a display device, wherein the text selection comprises a plurality of stochastic text components and one of the stochastic models comprises an “n-best” candidate list and another stochastic model comprises a lattice, and wherein the step of combining the stochastic models to produce a list of alternatives for the text selection further comprises the steps of: creating an “n-best” candidate list corresponding to the lattice; and producing the list of alternatives for the text selection by combining the “n-best” candidate lists for the text components. 14. The method of claim 1 , wherein the stochastic text component is derived from at least two stochastic different input sources. | 0.917929 |
9,218,614 | 10 | 15 | 10. A system, comprising: a memory including machine executable instructions; and a processor to execute the instructions to implement a framework to build a visual representation of a product concept, the visual representation including at least one of a textual component or a graphical component, the processor to implement the framework by: designating a first element of the at least one of the textual component or the graphical component as a dynamic element; associating the dynamic element with a variant list including a first element variant; in response to a selection of the first element variant from the variant list and based on an undesirability of the first element variant and a second element variant simultaneously appearing in the visual representation together, suppress the second element variant; and generating a first instantiation of the visual representation including the first element variant as the dynamic element. | 10. A system, comprising: a memory including machine executable instructions; and a processor to execute the instructions to implement a framework to build a visual representation of a product concept, the visual representation including at least one of a textual component or a graphical component, the processor to implement the framework by: designating a first element of the at least one of the textual component or the graphical component as a dynamic element; associating the dynamic element with a variant list including a first element variant; in response to a selection of the first element variant from the variant list and based on an undesirability of the first element variant and a second element variant simultaneously appearing in the visual representation together, suppress the second element variant; and generating a first instantiation of the visual representation including the first element variant as the dynamic element. 15. The system of claim 10 , wherein the processor is to receive a user input including the first element variant. | 0.77907 |
9,659,012 | 1 | 3 | 1. A method for debugging data integration code, comprising: receiving data integration code at a debugger client which includes a plurality of language interfaces corresponding to a plurality of different programming languages, wherein the data integration code corresponds to a distributed data integration scenario executing across a plurality of different hosts in a user network and wherein the distributed data integration scenario includes a plurality of portions of data integration code written in one or more of the plurality of programming languages and wherein the distributed data integration scenario is implemented on an existing infrastructure of a user thereby enabling a user to customize the distributed data integration scenario and enabling execution of the distributed data integration code corresponding to the plurality of different programming languages; connecting to a first host based on the data integration code; executing a first portion of the data integration code in a debugging mode at the first host, wherein the first portion of the data integration code is written in a first programming language; sending debugging messages to the first host from the debugger client using a first language interface; receiving a message from the first host to invoke to a second host to debug a second portion of the data integration code; connecting to the second host based on the message from the first host; executing the second portion of the data integration code in a debugging mode at the second host, wherein the second portion of the data integration code is written in a second programming language; and sending debugging messages to the second host from the debugger client using a second language interface. | 1. A method for debugging data integration code, comprising: receiving data integration code at a debugger client which includes a plurality of language interfaces corresponding to a plurality of different programming languages, wherein the data integration code corresponds to a distributed data integration scenario executing across a plurality of different hosts in a user network and wherein the distributed data integration scenario includes a plurality of portions of data integration code written in one or more of the plurality of programming languages and wherein the distributed data integration scenario is implemented on an existing infrastructure of a user thereby enabling a user to customize the distributed data integration scenario and enabling execution of the distributed data integration code corresponding to the plurality of different programming languages; connecting to a first host based on the data integration code; executing a first portion of the data integration code in a debugging mode at the first host, wherein the first portion of the data integration code is written in a first programming language; sending debugging messages to the first host from the debugger client using a first language interface; receiving a message from the first host to invoke to a second host to debug a second portion of the data integration code; connecting to the second host based on the message from the first host; executing the second portion of the data integration code in a debugging mode at the second host, wherein the second portion of the data integration code is written in a second programming language; and sending debugging messages to the second host from the debugger client using a second language interface. 3. The method of claim 1 , wherein the debugging messages include one or more of: setting breakpoints; pausing execution; resuming execution; and requesting variable values. | 0.741791 |
9,189,197 | 5 | 8 | 5. A method for controlling a human computer interface, comprising: providing a user interface device for receiving natural language speech input; generating a graphic user interface comprising an array of facets arranged in a tiled configuration, at least one of the facets being associated with at least one application; and implementing a natural language speech parser configured to parse received natural language speech input according to instruction grammars to determine instructions and respective parameters of the determined instructions, wherein, upon receipt of natural language speech input comprising a first instruction and a first parameter of the first instruction, shifting a focus to a facet associated with a first application associated with the respective first parameter of the first instruction and to vary the first facet from a first size to a second size, the second size occupying substantially an entire viewable portion of the graphic user interface, and passing the first instruction and respective first parameter to the first application associated with the facet for processing, and upon subsequent receipt of natural language speech input comprising a second instruction, shifting a focus away from the facet associated with the first application associated with the first parameter and return the first facet to the first size, and wherein, upon receipt of natural language speech input comprising the first instruction and a second parameter, shifting the focus to a second facet associated with a second application associated with the second parameter of the first instruction, varying the second facet from a third size to the second size, and upon receipt of natural language speech input comprising the second instruction, shifting the focus from the second facet associated with the second parameter and returning the second facet to the third size. | 5. A method for controlling a human computer interface, comprising: providing a user interface device for receiving natural language speech input; generating a graphic user interface comprising an array of facets arranged in a tiled configuration, at least one of the facets being associated with at least one application; and implementing a natural language speech parser configured to parse received natural language speech input according to instruction grammars to determine instructions and respective parameters of the determined instructions, wherein, upon receipt of natural language speech input comprising a first instruction and a first parameter of the first instruction, shifting a focus to a facet associated with a first application associated with the respective first parameter of the first instruction and to vary the first facet from a first size to a second size, the second size occupying substantially an entire viewable portion of the graphic user interface, and passing the first instruction and respective first parameter to the first application associated with the facet for processing, and upon subsequent receipt of natural language speech input comprising a second instruction, shifting a focus away from the facet associated with the first application associated with the first parameter and return the first facet to the first size, and wherein, upon receipt of natural language speech input comprising the first instruction and a second parameter, shifting the focus to a second facet associated with a second application associated with the second parameter of the first instruction, varying the second facet from a third size to the second size, and upon receipt of natural language speech input comprising the second instruction, shifting the focus from the second facet associated with the second parameter and returning the second facet to the third size. 8. The method of claim 5 , wherein the array of facets represents multiple concurrently executing applications, further comprising causing cause the facets associated with respective applications automatically change shape in accordance with an activity of the respective application. | 0.572289 |
8,566,029 | 1 | 7 | 1. A computer-implemented method comprising: generating, at one or more processors, a first search engine results page which includes links to one or more points-of-interest that satisfy a query; receiving, at the one or more processors, one or more signals indicating that a link to a point-of-interest was selected by a user; responsive to receiving the one or more signals: selecting, at the one or more processors, a plurality of geographic areas, each geographic area being associated with a set of information, each set of information comprising one or more identifiers of points-of-interest and a score associated with each identifier, determining, at the one or more processors, for each of the selected geographic areas, an increment value, determining, at the one or more processors, for each of the selected geographic areas, a score associated with the selected point-of-interest, incrementing, at the one or more processors, for each of the selected geographic areas, the score by the increment value, and storing, by the one or more processors, for each of the selected geographic areas, the incremented score in the set of information associated with the respective geographic area, the incremented score being stored in association with an identifier of the selected point-of-interest; and using, at the one or more processors, the incremented scores stored in the sets of information associated with the selected geographic areas to generate a second search engine results page. | 1. A computer-implemented method comprising: generating, at one or more processors, a first search engine results page which includes links to one or more points-of-interest that satisfy a query; receiving, at the one or more processors, one or more signals indicating that a link to a point-of-interest was selected by a user; responsive to receiving the one or more signals: selecting, at the one or more processors, a plurality of geographic areas, each geographic area being associated with a set of information, each set of information comprising one or more identifiers of points-of-interest and a score associated with each identifier, determining, at the one or more processors, for each of the selected geographic areas, an increment value, determining, at the one or more processors, for each of the selected geographic areas, a score associated with the selected point-of-interest, incrementing, at the one or more processors, for each of the selected geographic areas, the score by the increment value, and storing, by the one or more processors, for each of the selected geographic areas, the incremented score in the set of information associated with the respective geographic area, the incremented score being stored in association with an identifier of the selected point-of-interest; and using, at the one or more processors, the incremented scores stored in the sets of information associated with the selected geographic areas to generate a second search engine results page. 7. The method of claim 1 , wherein using the incremented scores stored in the sets of information associated with the selected geographic areas to generate a second search engine results page further comprises: identifying candidate points-of-interest stored for a target geographic area in the sets of information, determining the score associated with each candidate point-of-interest; and selecting, as relevant points-of-interest, the candidate points-of-interest whose associated scores satisfy a threshold, wherein the second search engine results page includes links to the relevant points-of-interest. | 0.64593 |
9,866,645 | 19 | 20 | 19. A non-transitory computer-readable medium encoded with instructions for causing a processing system to execute steps for generating actionable push notifications, comprising: receiving, by a notification server, a trigger message from a third party server; determining, by the notification server, user information associated with a user in response to the trigger message from the third party server; evaluating, by the notification server, the user information to determine one or more notification rules defined by the user, wherein the one or more notification rules indicate one or more circumstances under which the user should receive actionable notification messages; based on the trigger message and the one or more notification rules defined by the user, determining, by the notification server, that an actionable notification message should be sent to the user; based on the user information, determining, by the notification server, a user device associated with the user; in response to the determination that the actionable notification message should be sent to the user, generating, by the notification server, the actionable notification message having one or more actionable options operatively related to the actionable notification message; and transmitting, by the notification server, the actionable notification message and the one or more associated actionable options to the user device associated with the user, wherein the actionable notification message causes the user device to display a graphical user interface including a notification message corresponding to the actionable notification message and one or more user interface components corresponding to the one or more actionable options. | 19. A non-transitory computer-readable medium encoded with instructions for causing a processing system to execute steps for generating actionable push notifications, comprising: receiving, by a notification server, a trigger message from a third party server; determining, by the notification server, user information associated with a user in response to the trigger message from the third party server; evaluating, by the notification server, the user information to determine one or more notification rules defined by the user, wherein the one or more notification rules indicate one or more circumstances under which the user should receive actionable notification messages; based on the trigger message and the one or more notification rules defined by the user, determining, by the notification server, that an actionable notification message should be sent to the user; based on the user information, determining, by the notification server, a user device associated with the user; in response to the determination that the actionable notification message should be sent to the user, generating, by the notification server, the actionable notification message having one or more actionable options operatively related to the actionable notification message; and transmitting, by the notification server, the actionable notification message and the one or more associated actionable options to the user device associated with the user, wherein the actionable notification message causes the user device to display a graphical user interface including a notification message corresponding to the actionable notification message and one or more user interface components corresponding to the one or more actionable options. 20. The non-transitory computer-readable medium of claim 19 , further comprising instructions for causing the processing system to execute steps, including: receiving, by the notification server, an enrollment request associated with the user, wherein the enrollment request includes the user information; and storing, by the notification server, the user information. | 0.577011 |
8,041,733 | 14 | 18 | 14. One or more non-transitory computer-readable storage media storing instructions, which when executed by one or more processors, cause the one or more processors to perform: determining that a first query is associated with a first query category; detecting a first entity text in the first query; mapping the first entity text to a first entity category at least partially in response to: (a) determining that the first entity text is among a plurality of entity texts that are mapped to an entity of a plurality of entities, wherein a plurality of other entity texts are mapped to a plurality of other entities of the plurality of entities, and (b) determining that the entity is mapped to the first entity category; determining a first keyword text that occurs in the first query in addition to the first entity text; determining that a second query comprises said first keyword text and a second entity text in said first entity category; based at least in part on said determining that the second query comprises said first keyword text and the second entity text in said first entity category, storing information that indicates that the second query is associated with said first query category; storing a plurality of annotated queries in association with a plurality of query categories, wherein each annotated query of the plurality of annotated queries comprises a pair of at least a keyword text and an entity category, and wherein each annotated query represents one or more queries of a set of queries; for each annotated query of the plurality of annotated queries, determining an accuracy value for the annotated query based at least in part on a frequency by which the annotated query refers to a query category associated with the annotated query relative to a total number of times the annotated query occurs in the set of queries; selecting one or more annotated queries of the plurality of annotated queries based at least in part on the accuracy value determined for the one or more annotated queries. | 14. One or more non-transitory computer-readable storage media storing instructions, which when executed by one or more processors, cause the one or more processors to perform: determining that a first query is associated with a first query category; detecting a first entity text in the first query; mapping the first entity text to a first entity category at least partially in response to: (a) determining that the first entity text is among a plurality of entity texts that are mapped to an entity of a plurality of entities, wherein a plurality of other entity texts are mapped to a plurality of other entities of the plurality of entities, and (b) determining that the entity is mapped to the first entity category; determining a first keyword text that occurs in the first query in addition to the first entity text; determining that a second query comprises said first keyword text and a second entity text in said first entity category; based at least in part on said determining that the second query comprises said first keyword text and the second entity text in said first entity category, storing information that indicates that the second query is associated with said first query category; storing a plurality of annotated queries in association with a plurality of query categories, wherein each annotated query of the plurality of annotated queries comprises a pair of at least a keyword text and an entity category, and wherein each annotated query represents one or more queries of a set of queries; for each annotated query of the plurality of annotated queries, determining an accuracy value for the annotated query based at least in part on a frequency by which the annotated query refers to a query category associated with the annotated query relative to a total number of times the annotated query occurs in the set of queries; selecting one or more annotated queries of the plurality of annotated queries based at least in part on the accuracy value determined for the one or more annotated queries. 18. The one or more non-transitory computer-readable storage media of claim 14 , wherein the instructions further cause the one or more processors to perform storing a particular annotated query by replacing the first entity text in the first query with a placeholder for any entity text in the first entity category. | 0.85886 |
8,285,706 | 10 | 12 | 10. A computer-readable storage medium having computer-readable instructions stored thereupon which, when executed by a computer, cause the computer to: display a page to two or more players via a multi-player game; when the page is displayed, receive first terms from a first player and receiving second terms from a second player, cause a search engine to return first candidate pages in response to performing a first query using the first terms, cause the search engine to return second candidate pages in response to performing a second query using the second terms, and assign points to the first player and the second player when the first player and the second player agree and correctly indicate that they are viewing the same or a different page as the other player; store one or more of the first terms and the second terms provided by the two or more players during play of the multi-player game and associated data; and utilize the one or more of the first terms and the second terms and the associated data to improve results returned by the search engine. | 10. A computer-readable storage medium having computer-readable instructions stored thereupon which, when executed by a computer, cause the computer to: display a page to two or more players via a multi-player game; when the page is displayed, receive first terms from a first player and receiving second terms from a second player, cause a search engine to return first candidate pages in response to performing a first query using the first terms, cause the search engine to return second candidate pages in response to performing a second query using the second terms, and assign points to the first player and the second player when the first player and the second player agree and correctly indicate that they are viewing the same or a different page as the other player; store one or more of the first terms and the second terms provided by the two or more players during play of the multi-player game and associated data; and utilize the one or more of the first terms and the second terms and the associated data to improve results returned by the search engine. 12. The computer-readable storage medium of claim 10 , having further computer-readable instructions stored thereupon which, when executed by the computer, cause the computer to: display a third page to the two or more players via a second multi-player game; when the third page is displayed, receive third terms from the first player and receiving fourth terms from the second player, cause the search engine to return third candidate pages in response to performing a third query using the third terms, cause the search engine to return fourth candidate pages in response to performing a fourth query using the fourth terms, assign points to the first player if the third candidate pages returned by the search engine include the third page displayed before the fourth candidate pages returned by the search engine include the third page displayed, and assign the points to the second player if the fourth candidate pages returned by the search engine include the third page displayed before the third candidate pages returned by the search engine include the third page displayed; store one or more of the third terms and the fourth terms provided by the two or more players during play of the second multi-player game and associated third data; and utilizing the one or more of the third terms and the fourth terms and the associated third data to improve results returned by the search engine. | 0.5 |
8,539,349 | 1 | 3 | 1. A method of splitting a Chinese character sequence into word segments, the method comprising: providing a synchronization list including a plurality of Chinese words at a system; receiving an input data string including a first Chinese character sequence at the system; identifying one of the plurality of Chinese words from the synchronization list in the first Chinese character sequence at the system, wherein the identifying includes, comparing the Chinese words in the synchronization list with characters in the first Chinese character sequence; detecting a first match between a first Chinese word in the synchronization list and a leftmost or rightmost unsegmented section of the first Chinese character sequence; continuing to compare the characters in the first Chinese character sequence against other Chinese words in the synchronization list that begin with the first Chinese word; and identifying a longest Chinese word in the synchronization list that matches the leftmost or rightmost unsegmented section of the first Chinese character sequence; defining the identified longest Chinese word as a word segment in the first Chinese character sequence at the system; identifying a first undefined character sequence in the first Chinese character sequence at the system; and segmenting the first undefined character sequence into at least one word segment at the system. | 1. A method of splitting a Chinese character sequence into word segments, the method comprising: providing a synchronization list including a plurality of Chinese words at a system; receiving an input data string including a first Chinese character sequence at the system; identifying one of the plurality of Chinese words from the synchronization list in the first Chinese character sequence at the system, wherein the identifying includes, comparing the Chinese words in the synchronization list with characters in the first Chinese character sequence; detecting a first match between a first Chinese word in the synchronization list and a leftmost or rightmost unsegmented section of the first Chinese character sequence; continuing to compare the characters in the first Chinese character sequence against other Chinese words in the synchronization list that begin with the first Chinese word; and identifying a longest Chinese word in the synchronization list that matches the leftmost or rightmost unsegmented section of the first Chinese character sequence; defining the identified longest Chinese word as a word segment in the first Chinese character sequence at the system; identifying a first undefined character sequence in the first Chinese character sequence at the system; and segmenting the first undefined character sequence into at least one word segment at the system. 3. The method of claim 1 , wherein providing a synchronization list including a plurality of Chinese words at a system comprises providing a synchronization list including a plurality of Chinese number words and a plurality of Chinese classifier words at the system, the method further comprising: identifying one of the plurality of Chinese classifier words in the first Chinese character sequence at the system; determining whether the identified classifier word follows one of the plurality of Chinese number words in the first Chinese character sequence at the system; and defining the identified Chinese classifier word as a word segment based on the determination at the system. | 0.753957 |
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