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9,810,810 | 13 | 14 | 13. The process to describe vertical sequences of rocks using gestures according to claim 1 , wherein the insertion of data in the Organic Matter Content ( 15 ), Bioturbated Index ( 14 ) and Hydrocarbon Level ( 16 ) columns include touching and dragging an interval area in a desired column and selecting a desired value on a scale. | 13. The process to describe vertical sequences of rocks using gestures according to claim 1 , wherein the insertion of data in the Organic Matter Content ( 15 ), Bioturbated Index ( 14 ) and Hydrocarbon Level ( 16 ) columns include touching and dragging an interval area in a desired column and selecting a desired value on a scale. 14. The process to describe vertical sequences of rocks using gestures according to claim 13 , wherein the scale comprises an interval from 0% to 100%. | 0.958788 |
9,726,267 | 1 | 2 | 1. A relative translation system, comprising: a relative translation assembly, having a fixed support member, a translatable member supported by the fixed support member, and a translation guide portion to facilitate translation of the translatable member relative to the fixed support member, the translation guide portion having a fixed translation member and a movable translation member, the movable translation member fixedly coupled to a swing arm, the swing arm rotatably coupled to the fixed support member to provide a rotation of the movable translation member about an axis, the fixed translation member and the movable translation member operate together to constrain movement of the translatable member in a translational degree of freedom, wherein, the movable translation member is configured to maintain preload on the fixed and movable translation members and accommodate thermal expansion; and a drive mechanism configured to cause translation of the translatable member relative to the fixed support member. | 1. A relative translation system, comprising: a relative translation assembly, having a fixed support member, a translatable member supported by the fixed support member, and a translation guide portion to facilitate translation of the translatable member relative to the fixed support member, the translation guide portion having a fixed translation member and a movable translation member, the movable translation member fixedly coupled to a swing arm, the swing arm rotatably coupled to the fixed support member to provide a rotation of the movable translation member about an axis, the fixed translation member and the movable translation member operate together to constrain movement of the translatable member in a translational degree of freedom, wherein, the movable translation member is configured to maintain preload on the fixed and movable translation members and accommodate thermal expansion; and a drive mechanism configured to cause translation of the translatable member relative to the fixed support member. 2. The system of claim 1 , wherein the drive mechanism comprises: a drive shaft having a threaded portion; a first bearing to facilitate rotation of the drive shaft, the bearing being configured to support the drive shaft and interface with the fixed support member; and a drive member engaged with the threaded portion of the drive shaft and configured to be fixed to the translatable member to facilitate translation relative to the threaded portion upon rotation of the drive shaft, wherein an angle of misalignment of the bearing compensates for drive shaft rotational misalignment, and wherein a position of the drive member is adjustable upon assembly to compensate for drive axis translational misalignment. | 0.500699 |
9,235,978 | 1 | 3 | 1. A computer-implemented method comprising: generating a suggested alert definition for a notification application, the notification application configured to maintain active alert definitions for a user, wherein an active alert definition of the notification application specifies data to monitor and an alert trigger condition to cause the notification application to generate a corresponding alert notification for the user, wherein providing the suggested alert definition comprises: accessing a first data set of captured user interactions with a client computing device from electronic memory storage, wherein the first data set comprises information regarding user interaction with an application of the client computing device that is independent of the notification application, and using a processor to analyze the first data set, and generate a suggested alert definition for the user based on the analysis of the first data set, the suggested alert definition specifying data to monitor and a trigger condition for suggested conversion to an active alert of the notification application; and providing computer-readable code to display the suggested alert definition on a computing device display. | 1. A computer-implemented method comprising: generating a suggested alert definition for a notification application, the notification application configured to maintain active alert definitions for a user, wherein an active alert definition of the notification application specifies data to monitor and an alert trigger condition to cause the notification application to generate a corresponding alert notification for the user, wherein providing the suggested alert definition comprises: accessing a first data set of captured user interactions with a client computing device from electronic memory storage, wherein the first data set comprises information regarding user interaction with an application of the client computing device that is independent of the notification application, and using a processor to analyze the first data set, and generate a suggested alert definition for the user based on the analysis of the first data set, the suggested alert definition specifying data to monitor and a trigger condition for suggested conversion to an active alert of the notification application; and providing computer-readable code to display the suggested alert definition on a computing device display. 3. The method of claim 1 , wherein the first data set of captured user interactions comprises information regarding an action initiated by the user, selected from a group consisting of: a selection by the user to visit to a web site; a selection by the user to like content on a web site; a selection by the user to follow content on a web site; and a selection by the user to retrieve a document. | 0.79515 |
7,761,399 | 1 | 4 | 1. A system, comprising: a server configured to generate, in response to a first input provided by a user source, a recommendation container configured to receive content recommendations from at least one recommender source that is within a social network of the user source, and wherein the recommendation container is user definable by the user source, assign a user-defined topic to the recommendation container, wherein the user-defined topic is defined by a second input from the user source, associate, in response to a third input from the user source, the at least one recommender source with the recommendation container, assign a trust rating in response to a fourth input from the user source, to the at least one recommender source specifically for the user-defined topic, wherein the trust rating represents a degree of trust that the user source has in the at least one recommender source, as a recommendation source, to provide content recommendations of value specifically for the user-defined topic, detect a set of content recommendations provided by the at least one recommender source, wherein the set of content recommendations are on a plurality of topics, and wherein at least one of the plurality of topics includes the user-defined topic; filter the set of content recommendations using the user-defined topic forming a subset of content recommendations that are classified by the user-defined topic, determine individual recommendation ratings for each content recommendation in the subset of content recommendations, wherein the individual recommendation ratings are set by the at least one recommender source and represent individual degrees of preference that the at least one recommender source has for each content recommendation in the subset of content recommendations calculate individual ranking scores for each content recommendation in the subset of content recommendations by computing each individual recommendation rating with the trust rating, and rank the subset of content recommendations into a ranked list based on the individual ranking scores for each content recommendation in the subset of content recommendations; and a client device configured to receive the first, second, third, and fourth inputs from the user source, provide the first, second, third, and fourth inputs to the server, receive the ranked list from the server, and present the ranked list on a display associated with the client device. | 1. A system, comprising: a server configured to generate, in response to a first input provided by a user source, a recommendation container configured to receive content recommendations from at least one recommender source that is within a social network of the user source, and wherein the recommendation container is user definable by the user source, assign a user-defined topic to the recommendation container, wherein the user-defined topic is defined by a second input from the user source, associate, in response to a third input from the user source, the at least one recommender source with the recommendation container, assign a trust rating in response to a fourth input from the user source, to the at least one recommender source specifically for the user-defined topic, wherein the trust rating represents a degree of trust that the user source has in the at least one recommender source, as a recommendation source, to provide content recommendations of value specifically for the user-defined topic, detect a set of content recommendations provided by the at least one recommender source, wherein the set of content recommendations are on a plurality of topics, and wherein at least one of the plurality of topics includes the user-defined topic; filter the set of content recommendations using the user-defined topic forming a subset of content recommendations that are classified by the user-defined topic, determine individual recommendation ratings for each content recommendation in the subset of content recommendations, wherein the individual recommendation ratings are set by the at least one recommender source and represent individual degrees of preference that the at least one recommender source has for each content recommendation in the subset of content recommendations calculate individual ranking scores for each content recommendation in the subset of content recommendations by computing each individual recommendation rating with the trust rating, and rank the subset of content recommendations into a ranked list based on the individual ranking scores for each content recommendation in the subset of content recommendations; and a client device configured to receive the first, second, third, and fourth inputs from the user source, provide the first, second, third, and fourth inputs to the server, receive the ranked list from the server, and present the ranked list on a display associated with the client device. 4. The system of claim 1 , wherein the server is further configured to provide an instance of the recommendation container to at least one additional user source, receive at least one additional trust rating from the at least one additional user source, wherein the at least one additional trust rating represents a degree of trust that the at least one additional user source has in the recommendation container, as an additional recommendation source, specifically for the user-defined topic, and rank the subset of content recommendations in at least by computing the individual ranking scores with the at least one additional trust rating. | 0.739676 |
9,201,923 | 6 | 9 | 6. A method comprising: receiving a first query from a first user; defining a default order of processing constraints identified in the first query, each constraint representing a characteristic of an object or action in the first query; categorizing each constraint by constraint type, wherein the constraint type is selected from the group consisting of: string, binary, scalar, and ontology constraint types, and wherein each constraint type dictates how a corresponding constraint is modified by a modification strategy; defining an optimum value range specifying an optimum number of results returned in response to the first query; applying a first selected modification strategy to one or more constraints in accordance with the default order to generate a modified constraint if a number of results returned in response to the first query is not within the optimum value range, the first selected modification strategy comprising at least one of: relaxing a constraint, removing a constraint, tightening a constraint, and adding a constraint, wherein the first selected modification strategy is selected based on factors comprising at least one of: the number of results for the first query, ontological information of the first query, prosodic information of the first query, and information from a first user model associated with the first user; processing the first query to obtain a number of results for the query; processing a first re-query based on the modified constraint to obtain a second number of results; applying one of a different modification strategy to a same constraint or a second modification strategy to a subsequent constraint in the default order if the number of results for the first re-query is not within the defined value range; receiving a second query from a second user, different from the first user; consulting information from a second user model associated with the second user to select a third modification strategy to be applied to the second query, wherein the second query is the same as the first query, and the third selected modification strategy is different from the first selected modification strategy because the information from the second user model is different from the information from the first user model. | 6. A method comprising: receiving a first query from a first user; defining a default order of processing constraints identified in the first query, each constraint representing a characteristic of an object or action in the first query; categorizing each constraint by constraint type, wherein the constraint type is selected from the group consisting of: string, binary, scalar, and ontology constraint types, and wherein each constraint type dictates how a corresponding constraint is modified by a modification strategy; defining an optimum value range specifying an optimum number of results returned in response to the first query; applying a first selected modification strategy to one or more constraints in accordance with the default order to generate a modified constraint if a number of results returned in response to the first query is not within the optimum value range, the first selected modification strategy comprising at least one of: relaxing a constraint, removing a constraint, tightening a constraint, and adding a constraint, wherein the first selected modification strategy is selected based on factors comprising at least one of: the number of results for the first query, ontological information of the first query, prosodic information of the first query, and information from a first user model associated with the first user; processing the first query to obtain a number of results for the query; processing a first re-query based on the modified constraint to obtain a second number of results; applying one of a different modification strategy to a same constraint or a second modification strategy to a subsequent constraint in the default order if the number of results for the first re-query is not within the defined value range; receiving a second query from a second user, different from the first user; consulting information from a second user model associated with the second user to select a third modification strategy to be applied to the second query, wherein the second query is the same as the first query, and the third selected modification strategy is different from the first selected modification strategy because the information from the second user model is different from the information from the first user model. 9. The method of claim 6 comprising: updating the information from the first user model based on input from the first user. | 0.938684 |
9,002,817 | 10 | 11 | 10. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving in a search engine system a query, the query comprising query text submitted by a user; searching a first collection of resources to obtain one or more first search results, wherein each of the one or more first search results has a respective first search result score; searching a second collection of web resources to obtain one or more second search results, wherein each of the one or more second search results has a respective second search result score, wherein the resources of the first collection of resources are different from the resources of the second collection of web resources; determining from historical user click data that resources from the first collection of resources are more likely to be selected by users than resources from other collections of data when presented by the search engine in a response to the query text; generating enhanced first search result scores for the first search results as a consequence of the determining, the enhanced first search result scores being greater than the respective first search result scores for the first search results; generating a presentation order of first search results and second search results in order of the enhanced first search result scores and the second search result scores; generating a presentation of highest-ranked first search results and second search results in the presentation order; and providing the presentation in a response to the query. | 10. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving in a search engine system a query, the query comprising query text submitted by a user; searching a first collection of resources to obtain one or more first search results, wherein each of the one or more first search results has a respective first search result score; searching a second collection of web resources to obtain one or more second search results, wherein each of the one or more second search results has a respective second search result score, wherein the resources of the first collection of resources are different from the resources of the second collection of web resources; determining from historical user click data that resources from the first collection of resources are more likely to be selected by users than resources from other collections of data when presented by the search engine in a response to the query text; generating enhanced first search result scores for the first search results as a consequence of the determining, the enhanced first search result scores being greater than the respective first search result scores for the first search results; generating a presentation order of first search results and second search results in order of the enhanced first search result scores and the second search result scores; generating a presentation of highest-ranked first search results and second search results in the presentation order; and providing the presentation in a response to the query. 11. The system of claim 10 , wherein the historical click data represents resource collections of search results selected by users after submitting the query. | 0.856102 |
9,805,006 | 1 | 4 | 1. A method of loading a web page, comprising: providing, via a computer network and to a computing device having one or more processors, a script configured for loading with a web page, the web page configured for display on the computing device, the script having a plurality of function definitions and configured for asynchronous loading such that the web page is operable while the script is loaded; receiving an indication of a user interaction with the web page prior to complete loading of the plurality of function definitions on the web page; determining that the user interaction corresponds to a function definition of the plurality of function definitions that has not been loaded; subsequent to determining that the user interaction corresponds to the function definition that has not been loaded: instructing, using a variable, the computing device to queue a command string corresponding to the function definition; determining that the function has been loaded and instructing the computing device to retrieve the command string from the variable; and instructing the computing device to execute the function definition corresponding to the command string. | 1. A method of loading a web page, comprising: providing, via a computer network and to a computing device having one or more processors, a script configured for loading with a web page, the web page configured for display on the computing device, the script having a plurality of function definitions and configured for asynchronous loading such that the web page is operable while the script is loaded; receiving an indication of a user interaction with the web page prior to complete loading of the plurality of function definitions on the web page; determining that the user interaction corresponds to a function definition of the plurality of function definitions that has not been loaded; subsequent to determining that the user interaction corresponds to the function definition that has not been loaded: instructing, using a variable, the computing device to queue a command string corresponding to the function definition; determining that the function has been loaded and instructing the computing device to retrieve the command string from the variable; and instructing the computing device to execute the function definition corresponding to the command string. 4. The method of claim 1 , further comprising: identifying an event on the web page. | 0.82996 |
8,862,698 | 1 | 5 | 1. A method for deploying a process to a distributed network environment, wherein the process comprises a plurality of processing steps to be performed by a plurality of computing components of the distributed network environment, the method comprising: a. generating an Extensible Markup Language (XML) process package that defines information needed to execute the process; and b. deploying the XML process package to the plurality of computing components; c. wherein the XML process package comprises: a control flow definition, comprising a definition of the plurality of processing steps and at least one connection between the plurality of processing steps; and a data flow definition, comprising a definition of at least one dataflow between the plurality of processing components. | 1. A method for deploying a process to a distributed network environment, wherein the process comprises a plurality of processing steps to be performed by a plurality of computing components of the distributed network environment, the method comprising: a. generating an Extensible Markup Language (XML) process package that defines information needed to execute the process; and b. deploying the XML process package to the plurality of computing components; c. wherein the XML process package comprises: a control flow definition, comprising a definition of the plurality of processing steps and at least one connection between the plurality of processing steps; and a data flow definition, comprising a definition of at least one dataflow between the plurality of processing components. 5. The method of claim 1 , wherein the plurality of processing steps comprises a human task activity and wherein the control flow definition comprises a definition of a workflow form, the workflow form comprising at least one input element for inputting data into the workflow form to execute the human task activity. | 0.682365 |
8,947,355 | 25 | 26 | 25. A non-transitory computer-readable storage medium storing instructions for enabling a user to provide input to a computing device, the instructions when executed by a processor causing the processor to: determine a default relative orientation of the computing device using at least in part the at least one imaging element, wherein the default relative orientation of the computing device comprises a relative orientation of the computing device with respect to an aspect of a user of the computing device; detect a change in the relative orientation of the computing device with respect to the default relative orientation, wherein the change in the relative orientation of the electronic device is with respect to the aspect of the user and is caused, at least in part, by a movement of the electronic device by the user, wherein the change in the relative orientation of the computing device is detected using at least in part the at least one imaging element, and wherein the computing device displays a plurality of selectable elements in a graphical user interface; move a selection element of the graphical user interface in a direction corresponding to a direction of the change in relative orientation at a rate determined at least in part by an amount of the detected change in relative orientation, wherein a position of the selection element with respect to one of the plurality of selectable elements currently associated with the selection element is maintained in response to the detected relative orientation being different from the default relative orientation and the change in relative orientation being less than a fine threshold; and in response to receiving a selection action, provide the selectable element currently associated with the position of the selection element as input to the computing device. | 25. A non-transitory computer-readable storage medium storing instructions for enabling a user to provide input to a computing device, the instructions when executed by a processor causing the processor to: determine a default relative orientation of the computing device using at least in part the at least one imaging element, wherein the default relative orientation of the computing device comprises a relative orientation of the computing device with respect to an aspect of a user of the computing device; detect a change in the relative orientation of the computing device with respect to the default relative orientation, wherein the change in the relative orientation of the electronic device is with respect to the aspect of the user and is caused, at least in part, by a movement of the electronic device by the user, wherein the change in the relative orientation of the computing device is detected using at least in part the at least one imaging element, and wherein the computing device displays a plurality of selectable elements in a graphical user interface; move a selection element of the graphical user interface in a direction corresponding to a direction of the change in relative orientation at a rate determined at least in part by an amount of the detected change in relative orientation, wherein a position of the selection element with respect to one of the plurality of selectable elements currently associated with the selection element is maintained in response to the detected relative orientation being different from the default relative orientation and the change in relative orientation being less than a fine threshold; and in response to receiving a selection action, provide the selectable element currently associated with the position of the selection element as input to the computing device. 26. The non-transitory computer-readable storage medium of claim 25 , wherein the default relative orientation of the electronic device comprises a relative orientation of the electronic device with respect to an aspect of a user of the electronic device, the default relative orientation being determined at least in part using at least one imaging element of the electronic device. | 0.662257 |
9,973,488 | 1 | 4 | 1. A system, comprising: one or more processors; a memory device including instructions that, when executed by the one or more processors, cause the computing system to: receive a first request to cause temporary password information to be added to a set of password information comprising a plurality of instances of password information, the first request received in response to a login to a multi-tenant computing environment, the set of password information associated with the user and including at least a password known to the user, the set of temporary password information available for generating a ticket granting ticket (TGT); receive a second request for a security credential to be provided to a target component; determine, based at least in part on the second request, that the target component to receive the security credential is not configured to accept the TGT; and generate a response to the second request including at least a subset of the set of password information when the target component is determined as not being configured to accept the TGT. | 1. A system, comprising: one or more processors; a memory device including instructions that, when executed by the one or more processors, cause the computing system to: receive a first request to cause temporary password information to be added to a set of password information comprising a plurality of instances of password information, the first request received in response to a login to a multi-tenant computing environment, the set of password information associated with the user and including at least a password known to the user, the set of temporary password information available for generating a ticket granting ticket (TGT); receive a second request for a security credential to be provided to a target component; determine, based at least in part on the second request, that the target component to receive the security credential is not configured to accept the TGT; and generate a response to the second request including at least a subset of the set of password information when the target component is determined as not being configured to accept the TGT. 4. The system of claim 1 , wherein the instructions when executed further cause the computing system to determine which password information to use to generate the response based at least in part on a pre-authentication field in the second request. | 0.804416 |
9,619,488 | 11 | 16 | 11. A method for operating an image recognition program on a computing device having adaptable image search, the method comprising: executing the image recognition program on a processor of the computing device, the computing device being a user computing device; receiving a query from a user, the query comprising text that is typed or converted from speech; receiving a target image within which a search based on the query is to be performed; ranking a plurality of image recognition models by confidence level for performing the search based on at least a comparison between the query and respective text descriptions of the image recognition models, wherein the image recognition models are stored in non-volatile memory of the computing device; determining whether the confidence level of any of the image recognition models is above a confidence threshold; and upon determining that at least one confidence level of the image recognition models is above the confidence threshold, selecting at least one of the image recognition models whose confidence level is above the confidence threshold; performing the search within the target image for a target region of the target image using at least one selected image recognition model locally on the processor; and returning a search result to the user. | 11. A method for operating an image recognition program on a computing device having adaptable image search, the method comprising: executing the image recognition program on a processor of the computing device, the computing device being a user computing device; receiving a query from a user, the query comprising text that is typed or converted from speech; receiving a target image within which a search based on the query is to be performed; ranking a plurality of image recognition models by confidence level for performing the search based on at least a comparison between the query and respective text descriptions of the image recognition models, wherein the image recognition models are stored in non-volatile memory of the computing device; determining whether the confidence level of any of the image recognition models is above a confidence threshold; and upon determining that at least one confidence level of the image recognition models is above the confidence threshold, selecting at least one of the image recognition models whose confidence level is above the confidence threshold; performing the search within the target image for a target region of the target image using at least one selected image recognition model locally on the processor; and returning a search result to the user. 16. The method of claim 11 , wherein the computing device is a smartphone or tablet. | 0.961219 |
7,958,103 | 19 | 20 | 19. A computer system, comprising: a processor configured to receive one or more search criteria and an indication that a search result based content associated with the search criteria is to be included in a web page; and generate automatically for the web page a computer script or code configured to enable the search result based content to be retrieved in accordance with the search criteria; wherein the search result based content includes content from pages that: 1) satisfy the search criteria, 2) are associated with a natural language with which the web page is associated, and 3) match a life cycle state of the web page, wherein the life cycle state describes a stage in a content management system approval process; wherein the natural language comprises a primary natural language associated with the web page; wherein to generate automatically includes inserting in the search result based content a specific content from a specific page that satisfies: 1) the search criteria and 2) is associated with a secondary or default natural language associated with the web page, in the event a corresponding page associated with the primary natural language is not found; and a storage configured to store one or more of the search criteria and the computer script or code. | 19. A computer system, comprising: a processor configured to receive one or more search criteria and an indication that a search result based content associated with the search criteria is to be included in a web page; and generate automatically for the web page a computer script or code configured to enable the search result based content to be retrieved in accordance with the search criteria; wherein the search result based content includes content from pages that: 1) satisfy the search criteria, 2) are associated with a natural language with which the web page is associated, and 3) match a life cycle state of the web page, wherein the life cycle state describes a stage in a content management system approval process; wherein the natural language comprises a primary natural language associated with the web page; wherein to generate automatically includes inserting in the search result based content a specific content from a specific page that satisfies: 1) the search criteria and 2) is associated with a secondary or default natural language associated with the web page, in the event a corresponding page associated with the primary natural language is not found; and a storage configured to store one or more of the search criteria and the computer script or code. 20. A computer system as recited in claim 19 , wherein the indication comprises an update indication that a time or the end of an update interval specified by the schedule associated with the web page has arrived. | 0.674312 |
9,870,124 | 5 | 6 | 5. The method of claim 4 , wherein the graphical element associated with the conversation comprises an icon indicating roll-up information. | 5. The method of claim 4 , wherein the graphical element associated with the conversation comprises an icon indicating roll-up information. 6. The method of claim 5 , wherein the icon indicating roll-up information indicates that at least one message in the conversation has an attachment. | 0.957622 |
9,014,982 | 8 | 9 | 8. The method of claim 7 , wherein the computation of the derived measure uses entropy as the base measure. | 8. The method of claim 7 , wherein the computation of the derived measure uses entropy as the base measure. 9. The method of claim 8 , wherein the entropy measure is Shannon's entropy. | 0.946629 |
8,667,007 | 1 | 2 | 1. A system for providing recommendations to improve a query, comprising: a processor; and storage coupled to the processor, wherein the storage stores a computer program, and wherein the processor executes the computer program to perform operations, operations comprising: receiving a query with query keywords and selected categories; and in response to determining that the selected categories are ranked high with reference to query relevance indicator values for each of the selected categories, determining whether a lowest category level has been reached in the selected categories; in response to determining that the lowest category level has been reached, ranking individual services that are at the lowest category levels: and providing one or more high ranked services from the ranked individual services; and in response to determining that the lowest category level has not been reached, calculating a keyword relevance indicator of each keyword in the query for each subcategory of each of the selected categories, wherein the keyword relevance indicator for a keyword is calculated using a keyword frequency of the keyword and an inverse service frequency of a subcategory; calculating a query relevance indicator of the query with each subcategory using the retrieved keyword relevance indicators, wherein the query relevance indicator is generated based on a keyword relevance indicator of a keyword specified in the query and a keyword relevance indicator of a keyword in the subcategory that is not specified in the query; ranking each subcategory based on the query relevance indicators; and providing the ranked subcategories for use in selecting new categories to be submitted with the query. | 1. A system for providing recommendations to improve a query, comprising: a processor; and storage coupled to the processor, wherein the storage stores a computer program, and wherein the processor executes the computer program to perform operations, operations comprising: receiving a query with query keywords and selected categories; and in response to determining that the selected categories are ranked high with reference to query relevance indicator values for each of the selected categories, determining whether a lowest category level has been reached in the selected categories; in response to determining that the lowest category level has been reached, ranking individual services that are at the lowest category levels: and providing one or more high ranked services from the ranked individual services; and in response to determining that the lowest category level has not been reached, calculating a keyword relevance indicator of each keyword in the query for each subcategory of each of the selected categories, wherein the keyword relevance indicator for a keyword is calculated using a keyword frequency of the keyword and an inverse service frequency of a subcategory; calculating a query relevance indicator of the query with each subcategory using the retrieved keyword relevance indicators, wherein the query relevance indicator is generated based on a keyword relevance indicator of a keyword specified in the query and a keyword relevance indicator of a keyword in the subcategory that is not specified in the query; ranking each subcategory based on the query relevance indicators; and providing the ranked subcategories for use in selecting new categories to be submitted with the query. 2. The system of claim 1 , wherein the operations further comprise: in response to determining that at least one of the selected categories is ranked low with reference to the query relevance indicator values for each of the selected categories, identifying a pair of synonyms with a first one of the synonyms associated with a query keyword and a second one of the synonyms associated with a category keyword; and providing a recommendation that the query keyword be replaced with a synonym from the pair of synonyms. | 0.61743 |
9,984,053 | 13 | 16 | 13. A non-transitory computer program product having instructions encoded thereon that when executed by one or more processors cause a process to be carried out, the process comprising: receiving, by the one or more processors, input data representing a fixed layout digital publication in a first page layout format, the fixed layout digital publication including a plurality of words, each word being formed by a series of glyphs, each glyph having an effective width associated with the first page layout format and a default width associated with a second page layout format that is different than the first page layout format; computing, by the one or more processors, a letter spacing adjustment value for each word individually based on the number of glyphs in the respective word, the effective width of each glyph in the respective word in the first page layout format, and the default width of each glyph in the second page layout format; and generating, by the one or more processors, output data representing the fixed layout digital publication in the second page layout format by assigning the letter spacing adjustment value to a Cascading Style Sheet (CSS) ‘letter-spacing’ property associated with all of the glyphs in each respective word, such that the spacing between each glyph is the default width associated with the second page layout format adjusted by the letter spacing adjustment value on a word-by-word basis. | 13. A non-transitory computer program product having instructions encoded thereon that when executed by one or more processors cause a process to be carried out, the process comprising: receiving, by the one or more processors, input data representing a fixed layout digital publication in a first page layout format, the fixed layout digital publication including a plurality of words, each word being formed by a series of glyphs, each glyph having an effective width associated with the first page layout format and a default width associated with a second page layout format that is different than the first page layout format; computing, by the one or more processors, a letter spacing adjustment value for each word individually based on the number of glyphs in the respective word, the effective width of each glyph in the respective word in the first page layout format, and the default width of each glyph in the second page layout format; and generating, by the one or more processors, output data representing the fixed layout digital publication in the second page layout format by assigning the letter spacing adjustment value to a Cascading Style Sheet (CSS) ‘letter-spacing’ property associated with all of the glyphs in each respective word, such that the spacing between each glyph is the default width associated with the second page layout format adjusted by the letter spacing adjustment value on a word-by-word basis. 16. The non-transitory computer program product of claim 13 , further comprising generating a <span> tag associated with each word, wherein the output data includes the <span> tag. | 0.749304 |
9,836,450 | 10 | 13 | 10. A natural language platform configured to classify a document in natural language processing using a natural language model stored in one or more data files, the natural language platform comprising: a memory configured to store the one or more data files; and a processor coupled to the memory and configured to: access one or more feature types from the one or more data files, the one or more feature types each defining a data structure configured to access a tokenized sequence of the document and generate linguistic features from content within the tokenized sequence; perform a tokenizing operation of the document, the tokenizing operation configured to generate one or more tokenized sequences from the content within the document; generate a plurality of features for the document from the one or more tokenized sequences, based on parameters defined by the one or more feature types and on parameters defined in task configuration data in the one or more data files, the task configuration data associated with a type of task analysis that the natural language model is configured to classify the document into; access a plurality of probabilities stored in the one or more data files, each probability among the plurality of probabilities associated with a feature among the plurality of features and defining a pre-computed likelihood that said feature predicts a presence or absence of a label that the document is to be classified into; wherein: the plurality of probabilities are pre-computed during a model training process configured to train the natural language model to classify documents according to at least said label and said task analysis; the one or more data files is configured to store each probability in a logarithmic scale that is converted to said probability by the processor; the one or more data files is configured to store a table of rows and columns, wherein a first column comprises the plurality of features, a second column comprises a first category of probabilities among the plurality of probabilities that describes a first likelihood that a feature in the first column belonging to the same row satisfies a first attribute of said label, and a third column comprises a second category of probabilities among the plurality of probabilities that describes a second likelihood that said feature in the first column belonging to the same row satisfies a second attribute of said label; and the first attribute of said label represents a likelihood that said feature in the same row appears at a beginning of a span of the document, the second attribute of said label represents a likelihood that said feature in the same row appears inside said span of the document, and a fourth column comprises a third category of probabilities among the plurality of probabilities that represents a third likelihood that said feature in the same row appears outside said span of the document; compute a prediction score indicating how likely the document is to be classified into said label, based on the plurality or probabilities; classify the document into said label based on comparing the prediction score to a threshold; and train the natural language model at least based on the classified document. | 10. A natural language platform configured to classify a document in natural language processing using a natural language model stored in one or more data files, the natural language platform comprising: a memory configured to store the one or more data files; and a processor coupled to the memory and configured to: access one or more feature types from the one or more data files, the one or more feature types each defining a data structure configured to access a tokenized sequence of the document and generate linguistic features from content within the tokenized sequence; perform a tokenizing operation of the document, the tokenizing operation configured to generate one or more tokenized sequences from the content within the document; generate a plurality of features for the document from the one or more tokenized sequences, based on parameters defined by the one or more feature types and on parameters defined in task configuration data in the one or more data files, the task configuration data associated with a type of task analysis that the natural language model is configured to classify the document into; access a plurality of probabilities stored in the one or more data files, each probability among the plurality of probabilities associated with a feature among the plurality of features and defining a pre-computed likelihood that said feature predicts a presence or absence of a label that the document is to be classified into; wherein: the plurality of probabilities are pre-computed during a model training process configured to train the natural language model to classify documents according to at least said label and said task analysis; the one or more data files is configured to store each probability in a logarithmic scale that is converted to said probability by the processor; the one or more data files is configured to store a table of rows and columns, wherein a first column comprises the plurality of features, a second column comprises a first category of probabilities among the plurality of probabilities that describes a first likelihood that a feature in the first column belonging to the same row satisfies a first attribute of said label, and a third column comprises a second category of probabilities among the plurality of probabilities that describes a second likelihood that said feature in the first column belonging to the same row satisfies a second attribute of said label; and the first attribute of said label represents a likelihood that said feature in the same row appears at a beginning of a span of the document, the second attribute of said label represents a likelihood that said feature in the same row appears inside said span of the document, and a fourth column comprises a third category of probabilities among the plurality of probabilities that represents a third likelihood that said feature in the same row appears outside said span of the document; compute a prediction score indicating how likely the document is to be classified into said label, based on the plurality or probabilities; classify the document into said label based on comparing the prediction score to a threshold; and train the natural language model at least based on the classified document. 13. The natural language platform of claim 10 , wherein each feature among the generated plurality of features comprises a first array storing integer indices of every label in the natural language model having a non-zero probability. | 0.810373 |
8,316,019 | 7 | 11 | 7. A non-transitory computer-readable medium having instructions stored thereon, the instructions, when executed by one or more processors, cause the one or more processors to perform operations comprising: receiving a search query, the search query associated with a user identifier; receiving a ranked list of related search queries for the received search query, the related search queries being suggested alternate queries for the search query and ranked according to a first order; accessing a profile tree associated with the user identifier and including a hierarchy of nodes, the hierarchy of nodes including a root node and a plurality of child nodes, each child node descending from the root node or another child node, the profile tree defining a plurality of levels, each level including child nodes that descend from the root node at a same depth, and each node of the profile tree representing a respective topic that is derived from search history data associated with the user identifier, and each node of the profile tree corresponding to at least one of a term or a phrase, and wherein the terms and phrases of the profile tree corresponds to the nodes of the profile tree according to the respective topics to which the search terms and phrases belong; for each of the related search queries: identifying in the profile tree one or more nodes that match the related search query; determining the respective levels of the one or more nodes that match the related search query; determining a respective child count for each of the one or more nodes that match the related search query, the child count for each node being proportional to a number of child nodes descending directly from the node and a number of child nodes descending indirectly from the node; and deriving a respective relevance score for the related search query based on the respective levels of the one or more nodes that match the related search query and the respective child counts of the one or more nodes that match the related search query, wherein the relevance score is directly proportional to depths of the respective levels of the one or more nodes that match the related search query, and is inversely proportional to the respective child counts of the one or more nodes that match the related search query; adjusting the rank of at least one of the related search queries in the list based on the respective relevance scores of the related search queries so that the search queries are ranked according to a second order different from the first order; and providing suggested query data to a client device associated with the user identifier, the suggested query data operable to cause the client device to present a plurality of top-ranked related search queries according to the second order. | 7. A non-transitory computer-readable medium having instructions stored thereon, the instructions, when executed by one or more processors, cause the one or more processors to perform operations comprising: receiving a search query, the search query associated with a user identifier; receiving a ranked list of related search queries for the received search query, the related search queries being suggested alternate queries for the search query and ranked according to a first order; accessing a profile tree associated with the user identifier and including a hierarchy of nodes, the hierarchy of nodes including a root node and a plurality of child nodes, each child node descending from the root node or another child node, the profile tree defining a plurality of levels, each level including child nodes that descend from the root node at a same depth, and each node of the profile tree representing a respective topic that is derived from search history data associated with the user identifier, and each node of the profile tree corresponding to at least one of a term or a phrase, and wherein the terms and phrases of the profile tree corresponds to the nodes of the profile tree according to the respective topics to which the search terms and phrases belong; for each of the related search queries: identifying in the profile tree one or more nodes that match the related search query; determining the respective levels of the one or more nodes that match the related search query; determining a respective child count for each of the one or more nodes that match the related search query, the child count for each node being proportional to a number of child nodes descending directly from the node and a number of child nodes descending indirectly from the node; and deriving a respective relevance score for the related search query based on the respective levels of the one or more nodes that match the related search query and the respective child counts of the one or more nodes that match the related search query, wherein the relevance score is directly proportional to depths of the respective levels of the one or more nodes that match the related search query, and is inversely proportional to the respective child counts of the one or more nodes that match the related search query; adjusting the rank of at least one of the related search queries in the list based on the respective relevance scores of the related search queries so that the search queries are ranked according to a second order different from the first order; and providing suggested query data to a client device associated with the user identifier, the suggested query data operable to cause the client device to present a plurality of top-ranked related search queries according to the second order. 11. The non-transitory computer-readable medium of claim 7 , wherein the terms and phrases are terms and phrases extracted from result documents that have been previously selected by a user during search sessions associated with the user identifier. | 0.566202 |
9,712,588 | 17 | 24 | 17. A system comprising: one or more processors; and a memory storing instructions that, when executed, cause the system to: identify a channel category of a channel for a user based on one of a historical trend and a user activity; receive a request to customize a stream of content for the channel category; responsive to the request to customize, query new content items based on the channel category and a channel attribute; receive candidate content items that include the channel category and the channel attribute; determine a user-independent score for each of the candidate content items to approximate popularity of each candidate content item within the stream of content that produced it; compute a global score for each of the candidate content items by normalizing the user-independent score for each candidate content item across a plurality of streams of content, the global score identifying a popularity of each candidate content item within the plurality of streams of content; customize the stream of content for the channel by adding the candidate content items to the stream of content based on the global score of each candidate content item; and provide the customized stream of content. | 17. A system comprising: one or more processors; and a memory storing instructions that, when executed, cause the system to: identify a channel category of a channel for a user based on one of a historical trend and a user activity; receive a request to customize a stream of content for the channel category; responsive to the request to customize, query new content items based on the channel category and a channel attribute; receive candidate content items that include the channel category and the channel attribute; determine a user-independent score for each of the candidate content items to approximate popularity of each candidate content item within the stream of content that produced it; compute a global score for each of the candidate content items by normalizing the user-independent score for each candidate content item across a plurality of streams of content, the global score identifying a popularity of each candidate content item within the plurality of streams of content; customize the stream of content for the channel by adding the candidate content items to the stream of content based on the global score of each candidate content item; and provide the customized stream of content. 24. The system of claim 17 wherein the user activity is an interaction of the user with an application, wherein the interaction of the user with the application includes providing at least one of a user preference, a user interest, a comment, a tag, and a search. | 0.731084 |
8,560,531 | 1 | 13 | 1. A method for providing proximate dataset recommendations comprising: creating of a plurality of metadata records that correspond to a plurality of datasets representing scientific data by a scientific dataset search tool, wherein said plurality of metadata records conform to a standardized structural definition, wherein values for data elements of a metadata record are contained within a corresponding dataset; identifying at least one metadata record from the plurality of metadata records having a value that is proximate to one or more user-entered search parameters, wherein one of the search parameters is a temporal parameter, wherein proximity is determined with respect to a range represented by the corresponding user-entered search parameters; calculating a proximity score for each identified metadata record, wherein said proximity score expresses a relevance of the corresponding dataset to the user-entered search parameters, wherein calculating the proximity score comprises calculating a temporal proximity score, wherein calculating the temporal proximity score further comprises: determining a temporal distance, d Tdist , from a central point of the user-entered temporal search parameter for the dataset using the following formula or a variation or derivative thereof: d Tdist = { 0 d Tmin ≥ Q Tmin , d Tmax ≤ Q Tmax ( d Rmax - 1 ) 2 2 d Rmax - d Rmin d Tmin ≥ Q Tmin , d Tmax > Q Tmax ( d Rmin - 1 ) 2 2 d Rmax - d Rmin d Tmin < Q Tmin , d Tmax ≤ Q Tmax ( d Rmax - 1 ) 2 + ( d Rmax - 1 ) 2 2 d Rmax - d Rmin d Tmin < Q Tmin , d Tmax > Q Tmax ( d Rmin + d Rmax / 2 ) - 1 d Tmin > Q Tmin or d Tmax < Q Tmax , wherein Q Tmin and Q Tmax represent the minimum and maximum bounds of the temporal search parameter range, d Tmin and d Tmax represent the minimum and maximum time values of the dataset, and d Rmin and d Rmax represent the distance of d Tmin and d Tmax from the central point of the range; and using the proximity score to filter or order metadata records to create a listing of dataset results. | 1. A method for providing proximate dataset recommendations comprising: creating of a plurality of metadata records that correspond to a plurality of datasets representing scientific data by a scientific dataset search tool, wherein said plurality of metadata records conform to a standardized structural definition, wherein values for data elements of a metadata record are contained within a corresponding dataset; identifying at least one metadata record from the plurality of metadata records having a value that is proximate to one or more user-entered search parameters, wherein one of the search parameters is a temporal parameter, wherein proximity is determined with respect to a range represented by the corresponding user-entered search parameters; calculating a proximity score for each identified metadata record, wherein said proximity score expresses a relevance of the corresponding dataset to the user-entered search parameters, wherein calculating the proximity score comprises calculating a temporal proximity score, wherein calculating the temporal proximity score further comprises: determining a temporal distance, d Tdist , from a central point of the user-entered temporal search parameter for the dataset using the following formula or a variation or derivative thereof: d Tdist = { 0 d Tmin ≥ Q Tmin , d Tmax ≤ Q Tmax ( d Rmax - 1 ) 2 2 d Rmax - d Rmin d Tmin ≥ Q Tmin , d Tmax > Q Tmax ( d Rmin - 1 ) 2 2 d Rmax - d Rmin d Tmin < Q Tmin , d Tmax ≤ Q Tmax ( d Rmax - 1 ) 2 + ( d Rmax - 1 ) 2 2 d Rmax - d Rmin d Tmin < Q Tmin , d Tmax > Q Tmax ( d Rmin + d Rmax / 2 ) - 1 d Tmin > Q Tmin or d Tmax < Q Tmax , wherein Q Tmin and Q Tmax represent the minimum and maximum bounds of the temporal search parameter range, d Tmin and d Tmax represent the minimum and maximum time values of the dataset, and d Rmin and d Rmax represent the distance of d Tmin and d Tmax from the central point of the range; and using the proximity score to filter or order metadata records to create a listing of dataset results. 13. The method of claim 1 , wherein the scientific dataset search tool is a component of a data analysis system. | 0.919192 |
9,495,415 | 62 | 68 | 62. A user device as recited in claim 43 wherein search results module generates search results in response to suggestion data. | 62. A user device as recited in claim 43 wherein search results module generates search results in response to suggestion data. 68. A user device as recited in claim 62 wherein the user device generates the suggestion data based on series recording data. | 0.964123 |
9,632,985 | 77 | 81 | 77. The system of claim 74 , wherein the one or more interactive content presentation objects and one or more interactive assessment objects includes a manipulable image object. | 77. The system of claim 74 , wherein the one or more interactive content presentation objects and one or more interactive assessment objects includes a manipulable image object. 81. The system of claim 77 , wherein the one or more interactive content presentation objects and one or more interactive assessment objects includes a manipulable image object and a poptip, the poptip displayed responsive to a user selection. | 0.953555 |
9,373,086 | 12 | 14 | 12. The computer program product of claim 10 , wherein the computer readable program further causes the data processing system to analyze the natural language content of the supporting evidence to identify reasoning key words or reasoning key phrases and associated reasoning criteria at least by performing a search of text of the supporting evidence for reasoning key terms or reasoning key phrases indicative of a natural language reasoning statement in the text of the supporting evidence linking at least one reasoning criterion to the answer. | 12. The computer program product of claim 10 , wherein the computer readable program further causes the data processing system to analyze the natural language content of the supporting evidence to identify reasoning key words or reasoning key phrases and associated reasoning criteria at least by performing a search of text of the supporting evidence for reasoning key terms or reasoning key phrases indicative of a natural language reasoning statement in the text of the supporting evidence linking at least one reasoning criterion to the answer. 14. The computer program product of claim 12 , wherein the computer readable program further causes the data processing system to analyze the natural language content of the supporting evidence to identify reasoning key words or reasoning key phrases and associated reasoning criteria further at least by, for each instance of a reasoning key term or reasoning key phrase found in the text of the supporting evidence: identifying reasoning criteria specified in association with the reasoning key term or reasoning key phrase; and generating a distribution of reasoning criteria indicative of reasoning for the answer to the input question. | 0.814922 |
9,979,748 | 1 | 11 | 1. A computer-implemented method, comprising: at a domain name system (DNS) computing system that is in network communication with one or more clients that submit DNS requests and in network communication with one or more servers associated with respective domains: performing an analysis of one or more substrings associated with a target domain name relative to a database of malicious substrings; when the analysis indicates a correspondence with one or more malicious substrings, automatically retrieving content associated with the target domain name and generating one or more vectors based on the content; comparing the one or more vectors with a corpus of vectors associated with malicious content, wherein comparing includes determining a similarity score for the target domain name relative to a first document in the corpus and the similarity score is based on a distance between the one or more vectors for the target domain name and one or more vectors in the corpus for the first document; and automatically generating a domain classification based on comparing the one or more vectors with the corpus of vectors, wherein automatically generating includes automatically generating domain name information for the target domain name indicating an association with malware if the similarity score is above a threshold. | 1. A computer-implemented method, comprising: at a domain name system (DNS) computing system that is in network communication with one or more clients that submit DNS requests and in network communication with one or more servers associated with respective domains: performing an analysis of one or more substrings associated with a target domain name relative to a database of malicious substrings; when the analysis indicates a correspondence with one or more malicious substrings, automatically retrieving content associated with the target domain name and generating one or more vectors based on the content; comparing the one or more vectors with a corpus of vectors associated with malicious content, wherein comparing includes determining a similarity score for the target domain name relative to a first document in the corpus and the similarity score is based on a distance between the one or more vectors for the target domain name and one or more vectors in the corpus for the first document; and automatically generating a domain classification based on comparing the one or more vectors with the corpus of vectors, wherein automatically generating includes automatically generating domain name information for the target domain name indicating an association with malware if the similarity score is above a threshold. 11. The computer-implemented method of claim 1 , further comprising: receiving a plurality of domain name system (DNS) requests from a plurality of clients for the target domain name; and generating a plurality of DNS replies for the plurality of DNS requests based on the domain classification for the target domain name. | 0.627315 |
9,311,361 | 14 | 16 | 14. One or more non-transitory computer-readable storage media having computer-executable instructions embodied thereon, wherein when executed by at least one processor coupled to a memory device, the computer-executable instructions cause the processor to: store a plurality of software implemented algorithms in the memory device, wherein each algorithm includes one or more rules representing expert knowledge for subject matter of online content items, the rules are capable of recognizing graphic content parameters, recognizing textual content parameters, and relating the graphic content parameters and the textual content parameters to the set of desired parameters accessible to the rules based on the expert knowledge, the parameters relating to the appearance of the graphic content and the textual content, each algorithm pertains to a different aspect of online content; receive one or more generated items of online content from a content provider computing device; determine graphic content parameters and textual content parameters of the received items of online content, by parsing the online content using the plurality of algorithms according to the different rules included in each algorithm, wherein determining the graphic content parameters and textual content parameters include determining a relative size of a font with respect to other textual content, a location of the textual content within the content item, a location of breaks used in text wrapping in the textual content, a relative alignment of the textual content, a readability of the textual content based on font colors and background colors, and an orientation of graphic objects within the content item; compare the determined parameters to the set of desired parameters by determining whether each aspect meets a respective predefined threshold value; rank the items of online content based on the comparisons; and provide guidance for improving a quality of the items of online content by outputting the ranked items of online content to the content provider computing device. | 14. One or more non-transitory computer-readable storage media having computer-executable instructions embodied thereon, wherein when executed by at least one processor coupled to a memory device, the computer-executable instructions cause the processor to: store a plurality of software implemented algorithms in the memory device, wherein each algorithm includes one or more rules representing expert knowledge for subject matter of online content items, the rules are capable of recognizing graphic content parameters, recognizing textual content parameters, and relating the graphic content parameters and the textual content parameters to the set of desired parameters accessible to the rules based on the expert knowledge, the parameters relating to the appearance of the graphic content and the textual content, each algorithm pertains to a different aspect of online content; receive one or more generated items of online content from a content provider computing device; determine graphic content parameters and textual content parameters of the received items of online content, by parsing the online content using the plurality of algorithms according to the different rules included in each algorithm, wherein determining the graphic content parameters and textual content parameters include determining a relative size of a font with respect to other textual content, a location of the textual content within the content item, a location of breaks used in text wrapping in the textual content, a relative alignment of the textual content, a readability of the textual content based on font colors and background colors, and an orientation of graphic objects within the content item; compare the determined parameters to the set of desired parameters by determining whether each aspect meets a respective predefined threshold value; rank the items of online content based on the comparisons; and provide guidance for improving a quality of the items of online content by outputting the ranked items of online content to the content provider computing device. 16. The non-transitory computer-readable storage media of claim 14 , wherein the computer readable instructions when executed by the at least one processor cause the at least one processor to determine parameters that relate to the semantics of the textual content, where semantics include meaning, emotion, feeling, and memories. | 0.789541 |
8,266,524 | 8 | 9 | 8. A computer storage medium having computer executable instructions stored thereon which, when executed by a computer, cause the computer to: display a markup language document in a window generated by a web browser; detect a placement of an insertion pointer at a position in the window; upon detecting the placement of an insertion pointer, determine a text portion of the document displayed in the window at the position of the insertion pointer; create an editing surface overlaying the text portion of the document in the window and copy the text portion of the document to the editing surface, the editing surface created by adding a markup language element to the document having size and position attributes that cause the editing surface, when rendered by the web browser, to be displayed in the window at the position and of the size of the text portion of the document; detect input in the window; upon detecting input in the window, determine whether the editing surface will process the input; upon determining that the editing surface will process the input, pass the input to the editing surface to allow the editing surface to accept changes to the text portion of the document and perform a reflow operation of the editing surface; and upon determining that the editing surface will not process the input, update the text portion of the document with the changes from the editing surface and destroy the editing surface. | 8. A computer storage medium having computer executable instructions stored thereon which, when executed by a computer, cause the computer to: display a markup language document in a window generated by a web browser; detect a placement of an insertion pointer at a position in the window; upon detecting the placement of an insertion pointer, determine a text portion of the document displayed in the window at the position of the insertion pointer; create an editing surface overlaying the text portion of the document in the window and copy the text portion of the document to the editing surface, the editing surface created by adding a markup language element to the document having size and position attributes that cause the editing surface, when rendered by the web browser, to be displayed in the window at the position and of the size of the text portion of the document; detect input in the window; upon detecting input in the window, determine whether the editing surface will process the input; upon determining that the editing surface will process the input, pass the input to the editing surface to allow the editing surface to accept changes to the text portion of the document and perform a reflow operation of the editing surface; and upon determining that the editing surface will not process the input, update the text portion of the document with the changes from the editing surface and destroy the editing surface. 9. The computer storage medium of claim 8 , wherein creating an editing surface overlaying the text portion of the document in the window comprises: determining a current position and a current size of the portion of the document as displayed in the window; determining a character position within the text portion of the document corresponding to the position of the insertion pointer; causing the text portion of the document to be rendered by the web browser as invisible in the window; copying the text portion of the document into the editing surface; and positioning a cursor at the character position in the text portion of the document within the editing surface. | 0.701512 |
9,864,767 | 8 | 14 | 8. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining a resource that includes a first term that includes at least a first word and a second word; identifying a second term that (i) includes at least a third word and a fourth word, and (ii) that is indicated as a substitute term for the first term; storing, as a first entry in a search index, (i) data referencing the first word included in the first term, and (ii) data referencing the resource; storing, as a second entry in the search index, (i) data referencing the second word included in the first term, and (ii) data referencing the resource; storing, as a third entry in the search index, (i) data referencing the third word included in a second term that is indicated as a substitute term of the first term, (ii) data indicating that the third word included in the second term is a part of a substitute term and does not actually occur in the resource, (iii) data relating to a quantity of words in the first term, (iv) data relating an order of the third word within the second term, and (v) data referencing the resource; and storing, as a fourth entry in a search index, (i) data referencing the fourth word included in a second term that is indicated as a substitute term of the first term, (ii) data indicating that the fourth word included in the second term is a part of a substitute term and does not actually occur in the resource, (iii) data relating to a quantity of words in the first term, (iv) data relating an order of the fourth word within the second term, and (v) data referencing the resource. | 8. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining a resource that includes a first term that includes at least a first word and a second word; identifying a second term that (i) includes at least a third word and a fourth word, and (ii) that is indicated as a substitute term for the first term; storing, as a first entry in a search index, (i) data referencing the first word included in the first term, and (ii) data referencing the resource; storing, as a second entry in the search index, (i) data referencing the second word included in the first term, and (ii) data referencing the resource; storing, as a third entry in the search index, (i) data referencing the third word included in a second term that is indicated as a substitute term of the first term, (ii) data indicating that the third word included in the second term is a part of a substitute term and does not actually occur in the resource, (iii) data relating to a quantity of words in the first term, (iv) data relating an order of the third word within the second term, and (v) data referencing the resource; and storing, as a fourth entry in a search index, (i) data referencing the fourth word included in a second term that is indicated as a substitute term of the first term, (ii) data indicating that the fourth word included in the second term is a part of a substitute term and does not actually occur in the resource, (iii) data relating to a quantity of words in the first term, (iv) data relating an order of the fourth word within the second term, and (v) data referencing the resource. 14. The system of claim 8 , wherein the resource comprises a web page. | 0.794118 |
9,785,327 | 6 | 10 | 6. Non-transitory computer-readable storage media storing instructions executable by one or more processors to perform operations comprising: displaying an electronic document on a touch screen of a portable computing device; defining at least a first region, a second region, and a third region associated with the touch screen; associating with the first region a previous page command to display a previous page of the electronic document; associating with the second region a command to display or hide a control object; associating with the third region a next page command to display a next page of the electronic document; detecting a first touch input in the second region; displaying the control object overlaid in front of the electronic document based at least in part on the first touch input, the control object displayed with an opacity set to a last used opacity level; detecting a second touch input representing a swiping movement on the touch screen; and controlling, by a processor of the portable computing device, a perceived visible brightness of the electronic document by increasing or decreasing the opacity of the control object based at least in part on a current opacity level of the control object and in part on a characteristic of the second touch input. | 6. Non-transitory computer-readable storage media storing instructions executable by one or more processors to perform operations comprising: displaying an electronic document on a touch screen of a portable computing device; defining at least a first region, a second region, and a third region associated with the touch screen; associating with the first region a previous page command to display a previous page of the electronic document; associating with the second region a command to display or hide a control object; associating with the third region a next page command to display a next page of the electronic document; detecting a first touch input in the second region; displaying the control object overlaid in front of the electronic document based at least in part on the first touch input, the control object displayed with an opacity set to a last used opacity level; detecting a second touch input representing a swiping movement on the touch screen; and controlling, by a processor of the portable computing device, a perceived visible brightness of the electronic document by increasing or decreasing the opacity of the control object based at least in part on a current opacity level of the control object and in part on a characteristic of the second touch input. 10. The non-transitory computer-readable storage media of claim 6 , wherein the control object is displayed in front of the electronic document. | 0.820449 |
10,013,454 | 26 | 27 | 26. One or more non-transitory computer-storage media storing computer-useable instructions that, when executed by a computing device, perform a method, the method comprising: causing display of a set of events that are search results of a search query that specifies a plurality of commands, each event corresponding to a portion of raw machine data associated with a timestamp extracted from the portion of raw machine data, the display of the set of events being in a table format that includes: one or more columns, each column comprising data items of an event attribute, the data items being of the set of events; and a plurality of rows forming cells with the one or more columns, each cell displaying a textual representation of at least one of the data items of the event attribute of a corresponding column, the textual representation being selectable by a user, the textual representation including at least some of the portion of raw machine data of a corresponding event; based on a user selection of a text portion of the textual representation in a corresponding cell: causing display of a list of options corresponding to the selected text portion of the textual representation in the corresponding cell; and causing one or more commands to be added to the plurality of commands specified in the search query, wherein the one or more commands are based on an option that is selected from the list of options and the selected text portion of the textual representation in the corresponding cell. | 26. One or more non-transitory computer-storage media storing computer-useable instructions that, when executed by a computing device, perform a method, the method comprising: causing display of a set of events that are search results of a search query that specifies a plurality of commands, each event corresponding to a portion of raw machine data associated with a timestamp extracted from the portion of raw machine data, the display of the set of events being in a table format that includes: one or more columns, each column comprising data items of an event attribute, the data items being of the set of events; and a plurality of rows forming cells with the one or more columns, each cell displaying a textual representation of at least one of the data items of the event attribute of a corresponding column, the textual representation being selectable by a user, the textual representation including at least some of the portion of raw machine data of a corresponding event; based on a user selection of a text portion of the textual representation in a corresponding cell: causing display of a list of options corresponding to the selected text portion of the textual representation in the corresponding cell; and causing one or more commands to be added to the plurality of commands specified in the search query, wherein the one or more commands are based on an option that is selected from the list of options and the selected text portion of the textual representation in the corresponding cell. 27. The one or more computer-storage media of claim 26 , the method comprising: further based on the user selection of the text portion of the textual representation in the corresponding cell: causing the search query comprising the one or more commands to be automatically updated; causing the set of events to be updated to correspond to the executed search query; and causing the displayed search interface to be updated to correspond to the updated set of events. | 0.567593 |
8,762,469 | 1 | 12 | 1. A method for operating an automated assistant, comprising: at a server computer system comprising a processor and memory storing instructions for execution by the processor: receiving, from a speech recognition service operated separately from the server computer system, a text string corresponding to a voice command received at a portable electronic device; receiving contextual information from the portable electronic device; processing the text string and the contextual information; and transmitting results associated with processing the text string and the contextual information to the portable electronic device. | 1. A method for operating an automated assistant, comprising: at a server computer system comprising a processor and memory storing instructions for execution by the processor: receiving, from a speech recognition service operated separately from the server computer system, a text string corresponding to a voice command received at a portable electronic device; receiving contextual information from the portable electronic device; processing the text string and the contextual information; and transmitting results associated with processing the text string and the contextual information to the portable electronic device. 12. The method of claim 1 , wherein the contextual information is information from a software application running on the portable electronic device. | 0.848671 |
9,076,039 | 16 | 17 | 16. The system of claim 14 , wherein the probability determiner is further configured to determine a background expected value associated with the model search space. | 16. The system of claim 14 , wherein the probability determiner is further configured to determine a background expected value associated with the model search space. 17. The system of claim 16 , wherein the material identifier is further configured to determine a spectral fit between the first spectral signature and each spectral signature of a plurality of spectral signatures from the library, wherein each of the spectral fits corresponds to a correlation coefficient between the background suppressed signature and each of the plurality of spectral signatures. | 0.849624 |
9,224,396 | 1 | 9 | 1. A method comprising: establishing a call connection between at least a first and a second terminal; monitoring, by at least the first terminal, a conversation during the call in order to detect at least one predetermined context-related keyword received in one of the first or the second terminal and repeated in the other of the first or the second terminal; and in response to detecting at least one repeated predetermined context-related keyword, providing an indication about the detected context-related keyword to a user of at least the first terminal, said indication enabling opening an application linked to said context-related keyword. | 1. A method comprising: establishing a call connection between at least a first and a second terminal; monitoring, by at least the first terminal, a conversation during the call in order to detect at least one predetermined context-related keyword received in one of the first or the second terminal and repeated in the other of the first or the second terminal; and in response to detecting at least one repeated predetermined context-related keyword, providing an indication about the detected context-related keyword to a user of at least the first terminal, said indication enabling opening an application linked to said context-related keyword. 9. The method according to claim 1 , further comprising: sharing the keywords recognised by the first and the second terminal between each other during the call in order to enhance the operation of the speech recognition on the opposite terminal. | 0.834232 |
7,747,608 | 13 | 16 | 13. The method of claim 10 , wherein the first query language is SQL and the at least one additional query language is MDX. | 13. The method of claim 10 , wherein the first query language is SQL and the at least one additional query language is MDX. 16. The method of claim 13 , wherein the specified percentage is 20% and the specified number is 3 . | 0.967846 |
9,530,012 | 1 | 7 | 1. A method for constructing a post-transform template for use with a markup language security message in a light weight data model, comprising: a computer receiving an input byte array associated with the markup language security message, wherein the markup language security message includes a security element and encrypted message data; the computer determining whether a template corresponding to all of the markup language security message or a portion of the markup language security message is located in an automaton; responsive to a determination the template corresponding to all of the markup language security message or a portion of the markup language security message is located in the automaton: the computer retrieving a cached lightweight data model corresponding to the markup language security message and a transition sequence that represents all of the markup language security message; the computer parsing the transition sequence using a delta parsing engine, to create a first result; the computer generating the post-transform template using the first result of the delta parsing engine with cached transforms; and the computer storing the post-transform template in the automaton; and responsive to a determination the template corresponding to all of the markup language security message or a portion of the markup language security message is not located in the automaton: the computer calling transformers corresponding to transform information stored in the cached lightweight data model to construct the post-transform template, wherein a first process calling a transform using an expression conforming to Xpath produces a first transform result and a second process calling a canonicalization transform using the first transform result produces the post-transform template; the computer storing the post-transform template in the automaton; the computer populating the post-transform template with corresponding actual variable values of the input byte array; and the computer performing a serialization operation using the post transform template as populated to form a serialized byte array. | 1. A method for constructing a post-transform template for use with a markup language security message in a light weight data model, comprising: a computer receiving an input byte array associated with the markup language security message, wherein the markup language security message includes a security element and encrypted message data; the computer determining whether a template corresponding to all of the markup language security message or a portion of the markup language security message is located in an automaton; responsive to a determination the template corresponding to all of the markup language security message or a portion of the markup language security message is located in the automaton: the computer retrieving a cached lightweight data model corresponding to the markup language security message and a transition sequence that represents all of the markup language security message; the computer parsing the transition sequence using a delta parsing engine, to create a first result; the computer generating the post-transform template using the first result of the delta parsing engine with cached transforms; and the computer storing the post-transform template in the automaton; and responsive to a determination the template corresponding to all of the markup language security message or a portion of the markup language security message is not located in the automaton: the computer calling transformers corresponding to transform information stored in the cached lightweight data model to construct the post-transform template, wherein a first process calling a transform using an expression conforming to Xpath produces a first transform result and a second process calling a canonicalization transform using the first transform result produces the post-transform template; the computer storing the post-transform template in the automaton; the computer populating the post-transform template with corresponding actual variable values of the input byte array; and the computer performing a serialization operation using the post transform template as populated to form a serialized byte array. 7. The method of claim 1 , further comprising: the computer, in response to receiving a second markup language security message, determining that a result of a transformation of a previous markup language security message stored in the automaton is a match with the second markup language security message; and the computer, in response to determining that the result of the transformation of the previous markup language security message stored in the automaton is the match with the second markup language security message, skipping a second transformation of the second markup language security message. | 0.500824 |
9,405,841 | 15 | 19 | 15. A system for providing dynamic and category-specific search suggestions to a user, comprising: a processor; and a memory device including instructions that, when executed by the processor, cause the processor to: in response to receiving one or more characters associated with a partial search query to be executed against a set of data, determine a plurality of search queries relevant to the one or more characters; associate at least one search category with each of the plurality of relevant search query suggestions; select a subset of the at least one associated search category based at least in part a relevance value for each category meeting a threshold relevance value, the relevance value indicating a strength of an association of each category in the subset of the at least one associated search category with the plurality of relevant search query suggestions; provide for display at least the subset of the at least one associated search category and the plurality of relevant search query suggestions, the plurality of relevant search query suggestions including the one or more characters of the partial search query; determine an ordered set of some of the plurality of relevant search query suggestions and the subset of the at least one associated search category based at least in part on the relevance value of each category; and provide for display, within an allowable deviation from being simultaneous to receiving the one or more characters, a search suggestion window including the ordered set, wherein the some of the plurality of relevant search query suggestions and the subset of the at least one associated search category in the ordered set are displayed concurrently in the search suggestion window, the some of the plurality of relevant search query suggestions selectable to be executed against the set of data in the at least one associated search category. | 15. A system for providing dynamic and category-specific search suggestions to a user, comprising: a processor; and a memory device including instructions that, when executed by the processor, cause the processor to: in response to receiving one or more characters associated with a partial search query to be executed against a set of data, determine a plurality of search queries relevant to the one or more characters; associate at least one search category with each of the plurality of relevant search query suggestions; select a subset of the at least one associated search category based at least in part a relevance value for each category meeting a threshold relevance value, the relevance value indicating a strength of an association of each category in the subset of the at least one associated search category with the plurality of relevant search query suggestions; provide for display at least the subset of the at least one associated search category and the plurality of relevant search query suggestions, the plurality of relevant search query suggestions including the one or more characters of the partial search query; determine an ordered set of some of the plurality of relevant search query suggestions and the subset of the at least one associated search category based at least in part on the relevance value of each category; and provide for display, within an allowable deviation from being simultaneous to receiving the one or more characters, a search suggestion window including the ordered set, wherein the some of the plurality of relevant search query suggestions and the subset of the at least one associated search category in the ordered set are displayed concurrently in the search suggestion window, the some of the plurality of relevant search query suggestions selectable to be executed against the set of data in the at least one associated search category. 19. The system of claim 15 , wherein the memory device further includes instructions that, when executed by the processor, cause the processor to: provide a selection element adjacent to the display of each search query in the ordered set of search queries so as to enable selection of the associated search categories. | 0.805725 |
7,499,913 | 1 | 6 | 1. A method being executable in a computer for processing anchor text, comprising: forming a set of anchors that point to a target document, wherein each anchor is a path from a source document to the target document; grouping together anchors with same anchor text, wherein each anchor is associated with anchor text; computing a relevance score for each group, wherein computing the relevance score includes computing a linguistic score for each group; and generating context information for the target document based on the computed relevance score, wherein a title is composed from text of a group with a highest relevance score and a summary of the target document is composed from anchor texts of a number of groups with highest relevance scores. | 1. A method being executable in a computer for processing anchor text, comprising: forming a set of anchors that point to a target document, wherein each anchor is a path from a source document to the target document; grouping together anchors with same anchor text, wherein each anchor is associated with anchor text; computing a relevance score for each group, wherein computing the relevance score includes computing a linguistic score for each group; and generating context information for the target document based on the computed relevance score, wherein a title is composed from text of a group with a highest relevance score and a summary of the target document is composed from anchor texts of a number of groups with highest relevance scores. 6. The method of claim 1 , wherein computing the relevance score further comprises: computing a weighted sum of occurrences for anchor text for anchors in each group, wherein a weight of each individual occurrence of the anchor text is determined by a proximity class of an anchor and a weight associated with that proximity class. | 0.538997 |
9,053,703 | 1 | 6 | 1. A system comprising: one or more computer processors; and one or more non-transitory computer readable devices that include instructions that, when executed by the one or more computer processors, cause the one or more processors to perform operations, the operations comprising: receiving, at a computer system, a request to generate or modify a target acoustic model for a target language; accessing, by the computer system, a source acoustic model for a source language, wherein the source acoustic model includes information that maps acoustic features of the source language to phonemes in a transformed feature space; aligning, using the source acoustic model in the transformed feature space, untransformed voice data in the target language with phonemes in a corresponding textual transcript to obtain aligned voice data, wherein the untransformed voice data is in an untransformed feature space; transforming the aligned voice data according to a particular transform operation using the source acoustic model to obtain transformed voice data; adapting the source acoustic model to the target language, using the untransformed voice data in the target language, to obtain an adapted acoustic model; and training, by the computer system, a target acoustic model for the target language using the transformed voice data and the adapted acoustic model; and providing the target acoustic model in association with the target language. | 1. A system comprising: one or more computer processors; and one or more non-transitory computer readable devices that include instructions that, when executed by the one or more computer processors, cause the one or more processors to perform operations, the operations comprising: receiving, at a computer system, a request to generate or modify a target acoustic model for a target language; accessing, by the computer system, a source acoustic model for a source language, wherein the source acoustic model includes information that maps acoustic features of the source language to phonemes in a transformed feature space; aligning, using the source acoustic model in the transformed feature space, untransformed voice data in the target language with phonemes in a corresponding textual transcript to obtain aligned voice data, wherein the untransformed voice data is in an untransformed feature space; transforming the aligned voice data according to a particular transform operation using the source acoustic model to obtain transformed voice data; adapting the source acoustic model to the target language, using the untransformed voice data in the target language, to obtain an adapted acoustic model; and training, by the computer system, a target acoustic model for the target language using the transformed voice data and the adapted acoustic model; and providing the target acoustic model in association with the target language. 6. The system of claim 1 , wherein training the target acoustic model comprises performing a CMLLR transform operation and a maximum mutual information (MMI) transform operation using the transformed voice data and the adapted acoustic model. | 0.693671 |
8,799,000 | 17 | 18 | 17. The system of claim 11 , wherein the one or more differences include two or more alternative selection domains for the respective constrained selection tasks. | 17. The system of claim 11 , wherein the one or more differences include two or more alternative selection domains for the respective constrained selection tasks. 18. The system of claim 17 , wherein the two or more alternative selection domains includes a movie domain and a restaurant domain. | 0.930467 |
8,370,361 | 15 | 17 | 15. The method of claim 14 , wherein the connected component includes strings that represent vertices and edges between the vertices which are present only if the strings are sufficiently similar. | 15. The method of claim 14 , wherein the connected component includes strings that represent vertices and edges between the vertices which are present only if the strings are sufficiently similar. 17. The method of claim 15 , wherein the similarity is based on semantic similarity. | 0.983594 |
6,069,622 | 1 | 4 | 1. In a network including a plurality of data processing systems each having an associated display device, a method comprising: (a) receiving at each of the data processing systems an interaction event generated by any of the data processing systems; (b) automatically generating a comic panel based on the received interaction event, the comic panel providing a graphical representation of an instance in time of a sequential course of events; (c) displaying the generated comic panel on each of the display devices associated with the data processing systems; (d) when an input associated with a graphical representation of a character is received, automatically generating a balloon that includes text that corresponds to the received input associated with the character and automatically generating a tail that is positioned between a position of the balloon and another position for the graphical representation of the character in a current comic panel, the balloon, tail and graphical representation of the character being automatically disposed at positions that are non-overlapping of any other positions for balloons, tails and graphical representations of characters that were previously positioned for display in the current comic panel; and (e) when the input associated with the character is received and non-overlapping positions for displaying the balloon, tail and graphical representation of the character in the current comic panels are unavailable, automatically displaying a new comic panel that includes the balloon, tail and graphical representation of the character, wherein the balloon, tail and graphical representation of the character are disposed at separate positions that are non-overlapping in the display of the new comic panel. | 1. In a network including a plurality of data processing systems each having an associated display device, a method comprising: (a) receiving at each of the data processing systems an interaction event generated by any of the data processing systems; (b) automatically generating a comic panel based on the received interaction event, the comic panel providing a graphical representation of an instance in time of a sequential course of events; (c) displaying the generated comic panel on each of the display devices associated with the data processing systems; (d) when an input associated with a graphical representation of a character is received, automatically generating a balloon that includes text that corresponds to the received input associated with the character and automatically generating a tail that is positioned between a position of the balloon and another position for the graphical representation of the character in a current comic panel, the balloon, tail and graphical representation of the character being automatically disposed at positions that are non-overlapping of any other positions for balloons, tails and graphical representations of characters that were previously positioned for display in the current comic panel; and (e) when the input associated with the character is received and non-overlapping positions for displaying the balloon, tail and graphical representation of the character in the current comic panels are unavailable, automatically displaying a new comic panel that includes the balloon, tail and graphical representation of the character, wherein the balloon, tail and graphical representation of the character are disposed at separate positions that are non-overlapping in the display of the new comic panel. 4. The method of claim 1, wherein each character has a body portion with at least one body feature and wherein the interaction event provides a gesture indicating a modification of a body feature of one of the characters. | 0.913197 |
7,734,627 | 17 | 20 | 17. One or more memory devices comprising program instructions executable by least one processor, the one or more memory devices comprising: one or more instructions to randomly sample pairs of ordered terms from a particular document of a set of documents, to generate a cluster of pairs of ordered terms for the particular document, where the pairs of ordered terms include a first term and a second term and where, in at least some of the pairs of ordered terms, the second term occurs after one or more intervening terms occurring after the first term in the particular document, and where the random sampling is biased to have a higher chance of including a first ordered pair in the cluster than a second ordered pair, if the first ordered pair has fewer intervening terms that the second ordered pair; one or more instructions to build a similarity model that includes the cluster of pairs; one or more instructions to compare pairs of ordered terms from a target document to clusters of pairs of ordered terms from the similarity model; one or more instructions to generate similarity metrics that measure similarity between the target document and particular documents in the set of documents based on the comparing; and one or more instructions to output the generated similarity metrics. | 17. One or more memory devices comprising program instructions executable by least one processor, the one or more memory devices comprising: one or more instructions to randomly sample pairs of ordered terms from a particular document of a set of documents, to generate a cluster of pairs of ordered terms for the particular document, where the pairs of ordered terms include a first term and a second term and where, in at least some of the pairs of ordered terms, the second term occurs after one or more intervening terms occurring after the first term in the particular document, and where the random sampling is biased to have a higher chance of including a first ordered pair in the cluster than a second ordered pair, if the first ordered pair has fewer intervening terms that the second ordered pair; one or more instructions to build a similarity model that includes the cluster of pairs; one or more instructions to compare pairs of ordered terms from a target document to clusters of pairs of ordered terms from the similarity model; one or more instructions to generate similarity metrics that measure similarity between the target document and particular documents in the set of documents based on the comparing; and one or more instructions to output the generated similarity metrics. 20. The one or more memory devices of claim 17 , further comprising: one or more instructions to determine whether to categorize the target document as spam, based on the generated similarity metrics. | 0.768519 |
8,978,989 | 19 | 20 | 19. The apparatus according to claim 17 , wherein the processing unit is further configured to select cells from the free cells as selected cells, wherein the selected cells are cells which are selected from the free cells readable to provide a specified message or a specified part of a message. | 19. The apparatus according to claim 17 , wherein the processing unit is further configured to select cells from the free cells as selected cells, wherein the selected cells are cells which are selected from the free cells readable to provide a specified message or a specified part of a message. 20. The apparatus according to claim 19 , wherein the processing unit is configured to assign decode input values to the selected cells such that the encoded message includes a URL of a network resource. | 0.916735 |
9,860,076 | 5 | 6 | 5. The apparatus of claim 1 , wherein the instructions are executable by the processor to: deliver a request for clarification of the spoken command. | 5. The apparatus of claim 1 , wherein the instructions are executable by the processor to: deliver a request for clarification of the spoken command. 6. The apparatus of claim 5 , wherein the request for clarification includes an audible message. | 0.966736 |
8,145,660 | 1 | 5 | 1. A computer-implemented method, comprising: receiving, by one or more processors, a search query generated by a user; determining, by the one or more processors, a type of expansion to apply to the search query; automatically generating, by the one or more processors, a plurality of different expanded search queries according to the determined expansion type without intervention from the user; executing, by the one or more processors, a separate search on each one of the plurality of different expanded search queries to retrieve search results; and providing, by the one or more processors, the search results of the separate searches on each of the plurality of different expanded search queries for presentation to the user in a plurality of different modules, wherein each module comprises search results for one of the expanded search queries. | 1. A computer-implemented method, comprising: receiving, by one or more processors, a search query generated by a user; determining, by the one or more processors, a type of expansion to apply to the search query; automatically generating, by the one or more processors, a plurality of different expanded search queries according to the determined expansion type without intervention from the user; executing, by the one or more processors, a separate search on each one of the plurality of different expanded search queries to retrieve search results; and providing, by the one or more processors, the search results of the separate searches on each of the plurality of different expanded search queries for presentation to the user in a plurality of different modules, wherein each module comprises search results for one of the expanded search queries. 5. The method of claim 1 , wherein the search results are provided to the user asynchronously. | 0.825279 |
8,782,073 | 14 | 20 | 14. One or more computer-storage devices with computer-executable instructions embodied thereon, that when executed by a computing device performs a method for automatically presenting a search interface facility on a display, the method comprising: receiving a search criteria; determining that a first plurality of files within a first file location of a computer system match the search criteria; determining that a second file location of a computer system includes a second plurality of files that include the textual characters; and outputting for display a search interface that communicates that additional files in the second file location match the search criteria; wherein determining that a first plurality of files within a first file location of a computer system match the search criteria comprises performing deep file searching or searching on file attributes. | 14. One or more computer-storage devices with computer-executable instructions embodied thereon, that when executed by a computing device performs a method for automatically presenting a search interface facility on a display, the method comprising: receiving a search criteria; determining that a first plurality of files within a first file location of a computer system match the search criteria; determining that a second file location of a computer system includes a second plurality of files that include the textual characters; and outputting for display a search interface that communicates that additional files in the second file location match the search criteria; wherein determining that a first plurality of files within a first file location of a computer system match the search criteria comprises performing deep file searching or searching on file attributes. 20. The media of claim 14 , wherein the search criteria specifies the first file location. | 0.869942 |
8,056,049 | 8 | 12 | 8. A computer program product having instructions stored on volatile or non-volatile media readable by a computer system for reconciling computer application model conflicts, wherein the computer application models include i) an initial source computer application model, ii) an initial target computer application model generated by applying at least one transformation rule to the initial source computer application model, iii) a post-change target model produced by at least one change to the initial target model, and iv) a post-change source model produced by at least one change to the initial source model, said computer program product instructions being for execution by a computer, which, when executed by the computer, cause the computer to implement a method comprising: automatically dividing the initial source and target models and the post-change source and target models into segments responsive to at least one segmentation rule, wherein the at least one segmentation rule is defined responsive to the at least one transformation rule such that use of the at least one segmentation rule divides the initial source and target models into corresponding, isomorphic segments, wherein the initial source and target models have an isomorphic structure in common on which to mark changes; automatically identifying change statuses of the initial segments relative to the post-change segments of the respective models responsive to comparing initial segments to post-change segments of the source model and initial segments to post-change segments of the target model; and automatically generating, on a data structure representing the in-common isomorphic structure, an indication of conflicts between the post-change source model and post-change target model for presentation to a user or to a computer automated conflict settlement process, wherein the generating is responsive to comparing the identified change statuses of the corresponding, isomorphic segments of the initial source model and initial target model, wherein at least part of the identifying and generating occurs after changes to both the initial source model and the initial target model. | 8. A computer program product having instructions stored on volatile or non-volatile media readable by a computer system for reconciling computer application model conflicts, wherein the computer application models include i) an initial source computer application model, ii) an initial target computer application model generated by applying at least one transformation rule to the initial source computer application model, iii) a post-change target model produced by at least one change to the initial target model, and iv) a post-change source model produced by at least one change to the initial source model, said computer program product instructions being for execution by a computer, which, when executed by the computer, cause the computer to implement a method comprising: automatically dividing the initial source and target models and the post-change source and target models into segments responsive to at least one segmentation rule, wherein the at least one segmentation rule is defined responsive to the at least one transformation rule such that use of the at least one segmentation rule divides the initial source and target models into corresponding, isomorphic segments, wherein the initial source and target models have an isomorphic structure in common on which to mark changes; automatically identifying change statuses of the initial segments relative to the post-change segments of the respective models responsive to comparing initial segments to post-change segments of the source model and initial segments to post-change segments of the target model; and automatically generating, on a data structure representing the in-common isomorphic structure, an indication of conflicts between the post-change source model and post-change target model for presentation to a user or to a computer automated conflict settlement process, wherein the generating is responsive to comparing the identified change statuses of the corresponding, isomorphic segments of the initial source model and initial target model, wherein at least part of the identifying and generating occurs after changes to both the initial source model and the initial target model. 12. The computer program product of claim 8 , wherein dividing the initial source and target models and the post-change source and target models into segments is further responsive to at least one segment relating rule. | 0.807218 |
9,754,593 | 1 | 4 | 1. A method of identifying at least one speaker from a speech segment obtained by a computer by determining one or more words of the speech segment by identifying one or more portions of a sound wave having a sound wave contour between silences, the method comprising the steps of: the computer analyzing the sound wave contour of at least a portion of the sound wave to determine one or more variations within the sound wave contour; the computer assigning one or more features to the one or more variations by selecting a feature from a plurality of features based on slope characteristics of the sound wave contour representing the one or more portions of the sound wave having the sound wave contour between silences; the computer mapping one or more assigned features to one or more sound constructs, wherein the one or more sound constructs are at least part of a word; the computer determining parameters of the assigned features and order in which the parameters occur within the sound wave contour to indicate the start of a vowel in the speech segment; the computer grouping the parameters into predefined characteristics; the computer combining the predefined characteristics into a voice characteristic group; and the computer comparing the voice characteristic group to a plurality of existing voice characteristic groups each of the plurality of voice characteristic groups being attributed to one of the plurality of single speakers and, if the predefined characteristics of the voice characteristic group match the predefined characteristics of one of the plurality of existing voice characteristic groups, the computer assigning the sound construct to a speaker identified by the existing voice characteristic group matching the voice characteristic group. | 1. A method of identifying at least one speaker from a speech segment obtained by a computer by determining one or more words of the speech segment by identifying one or more portions of a sound wave having a sound wave contour between silences, the method comprising the steps of: the computer analyzing the sound wave contour of at least a portion of the sound wave to determine one or more variations within the sound wave contour; the computer assigning one or more features to the one or more variations by selecting a feature from a plurality of features based on slope characteristics of the sound wave contour representing the one or more portions of the sound wave having the sound wave contour between silences; the computer mapping one or more assigned features to one or more sound constructs, wherein the one or more sound constructs are at least part of a word; the computer determining parameters of the assigned features and order in which the parameters occur within the sound wave contour to indicate the start of a vowel in the speech segment; the computer grouping the parameters into predefined characteristics; the computer combining the predefined characteristics into a voice characteristic group; and the computer comparing the voice characteristic group to a plurality of existing voice characteristic groups each of the plurality of voice characteristic groups being attributed to one of the plurality of single speakers and, if the predefined characteristics of the voice characteristic group match the predefined characteristics of one of the plurality of existing voice characteristic groups, the computer assigning the sound construct to a speaker identified by the existing voice characteristic group matching the voice characteristic group. 4. The method of claim 1 , wherein the step of the computer determining one or more words further comprises the steps of the computer identifying a specified period of silence to indicate termination of a word within the speech segment. | 0.926617 |
7,778,875 | 1 | 2 | 1. A method for allowing targeted advertisements to be recommended by users of workflow software, the method comprising: (a) transmitting by a server, to a client, data representing a screen providing an input for a user of the client to recommend a potential advertiser corresponding to a first or second step in the workflow; (b) receiving at the server, from the client, input corresponding to at least one recommended advertiser for the first or second step in the workflow; and (c) storing in a memory element provided by the server the at least one recommended advertiser in association with the first or second step in the workflow. | 1. A method for allowing targeted advertisements to be recommended by users of workflow software, the method comprising: (a) transmitting by a server, to a client, data representing a screen providing an input for a user of the client to recommend a potential advertiser corresponding to a first or second step in the workflow; (b) receiving at the server, from the client, input corresponding to at least one recommended advertiser for the first or second step in the workflow; and (c) storing in a memory element provided by the server the at least one recommended advertiser in association with the first or second step in the workflow. 2. The method of claim 1 , wherein step (a) comprises transmitting by a server, to a client, data representing a screen corresponding to the first or second step in the workflow, the screen providing an input for the user to recommend a potential advertiser corresponding to the first or second step in the workflow. | 0.800253 |
9,645,700 | 15 | 24 | 15. A mobile device comprises: a processor; a memory coupled to the processor storing a computer program product that configures the processor to: launch a player application to playback visual items of playable content in one or more player windows; receive in the player application information feeds, the information feeds including web pages including web folders of images, text, and video data and ad hoc feeds including syndication feeds and podcast feeds; convert information content from the information feeds into a specified mark-up language format; apply parsing rules to parse the converted information content from the one or more feeds into code functions and data elements to provide one or more datasets comprising one or more of image, text, audio and video portions of the one or more feeds; load a first one of the one or more data elements and code functions into a player window of a player application to render the one or more datasets into one or more of the produced visual items of playable content playable in the player application, where the visual items of playable content comprise one or more components that are text, audio, video, and/or images parsed from the information feeds; store in a queue, the produced visual items of playable content; render produced visual items of playable content during a playback mode of the player application; apply one or more user focus operation tools by a user to one or more of the rendered visual items of playable content, with the one or more user focus operation tools applied being based on at least one of device context, characteristics of the one or more visual items of playable content, and user preferences specified for user focus operations; store new content resulting from the application of the one or more user focus operation tools to the one or more visual items of playable content; and render in a new player window the new content from applying the one or more user focus operation tools to the visual items of playable content. | 15. A mobile device comprises: a processor; a memory coupled to the processor storing a computer program product that configures the processor to: launch a player application to playback visual items of playable content in one or more player windows; receive in the player application information feeds, the information feeds including web pages including web folders of images, text, and video data and ad hoc feeds including syndication feeds and podcast feeds; convert information content from the information feeds into a specified mark-up language format; apply parsing rules to parse the converted information content from the one or more feeds into code functions and data elements to provide one or more datasets comprising one or more of image, text, audio and video portions of the one or more feeds; load a first one of the one or more data elements and code functions into a player window of a player application to render the one or more datasets into one or more of the produced visual items of playable content playable in the player application, where the visual items of playable content comprise one or more components that are text, audio, video, and/or images parsed from the information feeds; store in a queue, the produced visual items of playable content; render produced visual items of playable content during a playback mode of the player application; apply one or more user focus operation tools by a user to one or more of the rendered visual items of playable content, with the one or more user focus operation tools applied being based on at least one of device context, characteristics of the one or more visual items of playable content, and user preferences specified for user focus operations; store new content resulting from the application of the one or more user focus operation tools to the one or more visual items of playable content; and render in a new player window the new content from applying the one or more user focus operation tools to the visual items of playable content. 24. The device of claim 15 wherein the computer program further configures the processor to: repeatedly play the stored visual items of playable content in the queue for playback in a single player window. | 0.674603 |
9,176,944 | 7 | 8 | 7. A system comprising: one or more computers; and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by a computing system, multiple portions of text that were input into different types of fields associated with a resource; selecting (i) a first randomness threshold value for portions of text that are input into a text entry field of a first type, and (ii) a second randomness threshold value for portions of text that are input into a text entry field of a second type; for each of the multiple portions of text: determining, for the portion of text, a randomness value that reflects a level of entropy associated with a sequence of characters in the portion of text; determining a type of text entry field into which the portion of text was input, from among the text entry field of the first type and the text entry field of the second type, determining a randomness threshold value associated with the determined type of text entry field, from among the first randomness threshold value and the second randomness threshold value, where the randomness threshold value associated with the determined type of text entry field reflects a level of entropy permitted in a sequence of characters both input into a text entry field of the determined type and used to adapt a text processing system, and determining whether the randomness value for the portion of text satisfies the determined randomness threshold value; providing the one or more portions of text whose respective randomness values are determined to not satisfy the respective randomness threshold value determined for the portions of text, to adapt a text processing system; and preventing the one or more portions of text whose respective randomness values are determined to satisfy the respective randomness threshold value determined for the portions of text, from being used to adapt the text processing system. | 7. A system comprising: one or more computers; and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: receiving, by a computing system, multiple portions of text that were input into different types of fields associated with a resource; selecting (i) a first randomness threshold value for portions of text that are input into a text entry field of a first type, and (ii) a second randomness threshold value for portions of text that are input into a text entry field of a second type; for each of the multiple portions of text: determining, for the portion of text, a randomness value that reflects a level of entropy associated with a sequence of characters in the portion of text; determining a type of text entry field into which the portion of text was input, from among the text entry field of the first type and the text entry field of the second type, determining a randomness threshold value associated with the determined type of text entry field, from among the first randomness threshold value and the second randomness threshold value, where the randomness threshold value associated with the determined type of text entry field reflects a level of entropy permitted in a sequence of characters both input into a text entry field of the determined type and used to adapt a text processing system, and determining whether the randomness value for the portion of text satisfies the determined randomness threshold value; providing the one or more portions of text whose respective randomness values are determined to not satisfy the respective randomness threshold value determined for the portions of text, to adapt a text processing system; and preventing the one or more portions of text whose respective randomness values are determined to satisfy the respective randomness threshold value determined for the portions of text, from being used to adapt the text processing system. 8. The system of claim 7 , wherein the text entry field of the first type is a password entry field and the text entry field of the second type is a document body entry field. | 0.858414 |
9,268,820 | 22 | 28 | 22. A system comprising: a data store for storing content items; and one or more processors configured to interact with the data store, the one or more processors being further configured to perform operations comprising: identifying one or more queries that were received with a reference to a given factual entity, wherein the one or more queries identified for the given factual entity are different from one or more queries identified for one or more other factual entities; identifying one or more resources related to the given query; obtaining search results that are responsive to a received query; determining that the given factual entity is referenced by the received query; identifying a type of entity for the given factual entity; identifying, from a set of different knowledge panel templates, a knowledge panel template specified for the type of entity, the identified knowledge panel template including placeholders for content relevant to the type of entity; selecting, from the one or more resources related to the given factual entity, content for display in a knowledge panel for the given factual entity, the selected content including a first content item obtained from a first resource and a second content item obtained from a second resource different than the first resource, each given content item of the selected content being selected based on a number of the one or more received queries that reference both (i) the given factual entity and (ii) information presented by the given content item; generating the knowledge panel for the given factual entity by populating the placeholders of the identified knowledge panel template with the selected content; and providing data that causes the identified search results and the knowledge panel to be presented on a search results page, the knowledge panel presenting the selected content in a knowledge panel area alongside at least a portion of the search results. | 22. A system comprising: a data store for storing content items; and one or more processors configured to interact with the data store, the one or more processors being further configured to perform operations comprising: identifying one or more queries that were received with a reference to a given factual entity, wherein the one or more queries identified for the given factual entity are different from one or more queries identified for one or more other factual entities; identifying one or more resources related to the given query; obtaining search results that are responsive to a received query; determining that the given factual entity is referenced by the received query; identifying a type of entity for the given factual entity; identifying, from a set of different knowledge panel templates, a knowledge panel template specified for the type of entity, the identified knowledge panel template including placeholders for content relevant to the type of entity; selecting, from the one or more resources related to the given factual entity, content for display in a knowledge panel for the given factual entity, the selected content including a first content item obtained from a first resource and a second content item obtained from a second resource different than the first resource, each given content item of the selected content being selected based on a number of the one or more received queries that reference both (i) the given factual entity and (ii) information presented by the given content item; generating the knowledge panel for the given factual entity by populating the placeholders of the identified knowledge panel template with the selected content; and providing data that causes the identified search results and the knowledge panel to be presented on a search results page, the knowledge panel presenting the selected content in a knowledge panel area alongside at least a portion of the search results. 28. The system of claim 22 , wherein selecting content for display in the knowledge panel for the given factual entity comprises identifying types of content items specified by the identified knowledge panel template. | 0.836842 |
8,793,235 | 9 | 10 | 9. The method of claim 7 , further comprising: storing metrics associated with a selection of a selected search result from the set of search result; and transmitting the metrics to provide statistical data to improve selection of prerendering candidates in response to subsequent search queries. | 9. The method of claim 7 , further comprising: storing metrics associated with a selection of a selected search result from the set of search result; and transmitting the metrics to provide statistical data to improve selection of prerendering candidates in response to subsequent search queries. 10. The method of claim 9 , wherein the metrics are at least one of the selected search result, whether the selected search result is the at least one search result, and a page load time to access the selected search result. | 0.917037 |
7,633,535 | 1 | 13 | 1. An apparatus for adding user-supplied text to a digital still image comprising: (a) a card having a surface and image manipulation instructions printed on said surface in encoded form, at least one of said image manipulation instructions comprising instructions for adding user-supplied text to a digital still image; (b) a text entry device comprising: (i) a user interface adapted to receive text from a user; (ii) a memory adapted to store character set information including character set information defining at least one character set in a non-roman font; and (iii) camera communication means adapted to communicate said user-supplied text and said character set information to a digital still camera; and (c) a digital still camera comprising: (i) a sensor adapted to sense an original digital still image; (ii) a card reader adapted to read said image manipulation instructions stored on said card; (iii) text entry device communication means adapted to receive said user-supplied text and said character set information from said text entry device; (iv) image manipulation means adapted to manipulate said original digital still image in accordance with said image manipulation instructions to form a manipulated digital still image which includes said user-supplied text; and (v) a printer device adapted to print said manipulated digital still image. | 1. An apparatus for adding user-supplied text to a digital still image comprising: (a) a card having a surface and image manipulation instructions printed on said surface in encoded form, at least one of said image manipulation instructions comprising instructions for adding user-supplied text to a digital still image; (b) a text entry device comprising: (i) a user interface adapted to receive text from a user; (ii) a memory adapted to store character set information including character set information defining at least one character set in a non-roman font; and (iii) camera communication means adapted to communicate said user-supplied text and said character set information to a digital still camera; and (c) a digital still camera comprising: (i) a sensor adapted to sense an original digital still image; (ii) a card reader adapted to read said image manipulation instructions stored on said card; (iii) text entry device communication means adapted to receive said user-supplied text and said character set information from said text entry device; (iv) image manipulation means adapted to manipulate said original digital still image in accordance with said image manipulation instructions to form a manipulated digital still image which includes said user-supplied text; and (v) a printer device adapted to print said manipulated digital still image. 13. The apparatus as claimed in claim 1 wherein said printer device of said digital still camera is adapted to print said manipulated digital still image in less than 10 seconds. | 0.759459 |
6,028,604 | 1 | 4 | 1. A computer system comprising: a storage for storing a list of menu options corresponding to functions and for storing a description of said menu options; an input for receiving a first user input indicating a designation of one of said list of menu options and for receiving a second user input indicating a selection of said one of said list of menu options; a processor for determining in response to said input which of said menu options is currently designated by said user, for retrieving and providing to a user said description of said currently designated menu option prior to receipt of said second user input, and for executing said function based on the receipt of said second user input relating to said selection of said one of said list, wherein said description is stored apart from said function. | 1. A computer system comprising: a storage for storing a list of menu options corresponding to functions and for storing a description of said menu options; an input for receiving a first user input indicating a designation of one of said list of menu options and for receiving a second user input indicating a selection of said one of said list of menu options; a processor for determining in response to said input which of said menu options is currently designated by said user, for retrieving and providing to a user said description of said currently designated menu option prior to receipt of said second user input, and for executing said function based on the receipt of said second user input relating to said selection of said one of said list, wherein said description is stored apart from said function. 4. The computer system of claim 1, wherein said description includes sound files. | 0.815909 |
10,049,362 | 13 | 15 | 13. A voice biometric system comprising a processor and a memory, wherein the memory includes a non-transitory computer readable storage medium including executable instructions, which when executed by the processor, cause the processor to: obtain a user voiceprint based on a voice input from the user received through a network connection coupled to the processor; receive a request for authentication associated with a financial transaction from a requestor; obtain a spoken message from the user, the spoken message including word content and the word content including a financial transaction detail for the financial transaction; authenticate the word content included in the spoken message as spoken by the user based on the user voiceprint and the word content of the spoken message; and provide a result of the authentication, including the authenticated word content, to the requestor when the user is authenticated, thereby permitting the requestor to compare the authenticated word content to information related to the financial transaction to provide a degree of confidence that the financial transaction is not fraudulent. | 13. A voice biometric system comprising a processor and a memory, wherein the memory includes a non-transitory computer readable storage medium including executable instructions, which when executed by the processor, cause the processor to: obtain a user voiceprint based on a voice input from the user received through a network connection coupled to the processor; receive a request for authentication associated with a financial transaction from a requestor; obtain a spoken message from the user, the spoken message including word content and the word content including a financial transaction detail for the financial transaction; authenticate the word content included in the spoken message as spoken by the user based on the user voiceprint and the word content of the spoken message; and provide a result of the authentication, including the authenticated word content, to the requestor when the user is authenticated, thereby permitting the requestor to compare the authenticated word content to information related to the financial transaction to provide a degree of confidence that the financial transaction is not fraudulent. 15. The voice biometric system as claimed in claim 13 , wherein the requestor is an issuer of an account to which the financial transaction associated with the user is directed. | 0.844737 |
6,064,961 | 4 | 6 | 4. The method of claim 1, further comprising the step of audibly playing said displayed text responsive to a user request. | 4. The method of claim 1, further comprising the step of audibly playing said displayed text responsive to a user request. 6. The method of claim 4, further comprising the steps of: playing an audio recording of said displayed text if an original audio recording of said displayed text as dictated is available; and, playing said displayed text with a text-to-speech engine if said original audio recording is not available. | 0.836413 |
9,251,221 | 1 | 20 | 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. 20. The method of claim 1 , wherein executing the search query comprises using an extraction rule or regular expression to the portion of machine data in an event to derive a value for a field. | 0.85108 |
8,479,007 | 1 | 5 | 1. A method of creating and authenticating a document, the method comprising: registering a user of a document creation system as a document creator, the registering including recording user identification data, user biometric data, and contact information for the user, and allocating a unique user identity code to the user; creating a document having a user discernable portion and an encoded portion, the encoded portion including identification data identifying the registered user, contents data corresponding to at least part of the user discernable portion of the document, and authentication data; creating a central record of the document in a central database, the central record comprising data corresponding at least partially to the data in the encoded portion of the document; wherein at least one of the encoded portion of the document or the respective central record in the central database includes instructions for contacting the registered user as part of a document authentication process; receiving an image of the encoded portion of the document during the document authentication process; decoding the image to extract the data contained therein; and authenticating the document by contacting the respective registered user of the document creation system using the instructions, transmitting at least a portion of the instructions to the registered user, receiving current identification data from the registered user in accordance with the transmitted instructions, and comparing the received current identification data with data in the central record and the data extracted from the encoded portion of the document to verify the respective registered user as the document creator. | 1. A method of creating and authenticating a document, the method comprising: registering a user of a document creation system as a document creator, the registering including recording user identification data, user biometric data, and contact information for the user, and allocating a unique user identity code to the user; creating a document having a user discernable portion and an encoded portion, the encoded portion including identification data identifying the registered user, contents data corresponding to at least part of the user discernable portion of the document, and authentication data; creating a central record of the document in a central database, the central record comprising data corresponding at least partially to the data in the encoded portion of the document; wherein at least one of the encoded portion of the document or the respective central record in the central database includes instructions for contacting the registered user as part of a document authentication process; receiving an image of the encoded portion of the document during the document authentication process; decoding the image to extract the data contained therein; and authenticating the document by contacting the respective registered user of the document creation system using the instructions, transmitting at least a portion of the instructions to the registered user, receiving current identification data from the registered user in accordance with the transmitted instructions, and comparing the received current identification data with data in the central record and the data extracted from the encoded portion of the document to verify the respective registered user as the document creator. 5. A method according to claim 1 wherein the identification data identifying the user of the document creation system comprises a unique user identity code. | 0.747573 |
8,412,512 | 1 | 2 | 1. A computer-implemented method for translating a first social feed, the method comprising: receiving, with a processor, social feed data and a request from a first user for a translation, the social feed data configured to cause a client to display the first social feed in a first language; determining, with the processor, a social context for the translation, the social context including which relationships are associated with the social feed data using a social graph, wherein the social graph comprises relationships between the first user and at least one second user; receiving, with the processor, a user input from the first user specifying a particular relationship for which the social feed data should be translated; determining, with the processor, a relationship between the first user and the second user based at least in part on the social context for the translation and whether the relationship matches the particular relationship specified by the user input; determining, with the processor, a first portion of the first social feed for translation based at least in part on whether the relationship between the first user and the second user matches the particular relationship, the first portion including one or more portions of the social feed data associated with the second user; translating, with the processor, the social feed data that is associated with the first portion of the first social feed so that the translated social feed data causes the client to display the first portion translated into one or more second languages based at least in part on the request and the social context; and transmitting, with the processor, the translated social feed data to the client for the first user to view. | 1. A computer-implemented method for translating a first social feed, the method comprising: receiving, with a processor, social feed data and a request from a first user for a translation, the social feed data configured to cause a client to display the first social feed in a first language; determining, with the processor, a social context for the translation, the social context including which relationships are associated with the social feed data using a social graph, wherein the social graph comprises relationships between the first user and at least one second user; receiving, with the processor, a user input from the first user specifying a particular relationship for which the social feed data should be translated; determining, with the processor, a relationship between the first user and the second user based at least in part on the social context for the translation and whether the relationship matches the particular relationship specified by the user input; determining, with the processor, a first portion of the first social feed for translation based at least in part on whether the relationship between the first user and the second user matches the particular relationship, the first portion including one or more portions of the social feed data associated with the second user; translating, with the processor, the social feed data that is associated with the first portion of the first social feed so that the translated social feed data causes the client to display the first portion translated into one or more second languages based at least in part on the request and the social context; and transmitting, with the processor, the translated social feed data to the client for the first user to view. 2. The method of claim 1 , further comprising: identifying a second portion of the first social feed that is associated with a third user, the third user having a different relationship with the first user than the particular relationship; and excluding the second portion from translation based at least in part on the different relationship. | 0.848899 |
8,046,370 | 6 | 7 | 6. The computer-implemented method of claim 1 , wherein the ranking of the individual elements is indicated by graphic indicators. | 6. The computer-implemented method of claim 1 , wherein the ranking of the individual elements is indicated by graphic indicators. 7. The computer-implemented method of claim 6 , wherein the graphic indicators are asterisks. | 0.978148 |
10,127,902 | 2 | 3 | 2. The method of claim 1 , wherein the score of each generated token is the sum of a cumulative score of that token from the previous frame, the weight of the corresponding arc, and the best acoustic score of the current frame. | 2. The method of claim 1 , wherein the score of each generated token is the sum of a cumulative score of that token from the previous frame, the weight of the corresponding arc, and the best acoustic score of the current frame. 3. The method of claim 2 , wherein the score threshold is a sum of the best score from a previous frame, a best acoustic score of a current frame and a predefined constant. | 0.929043 |
7,574,433 | 7 | 8 | 7. A system for the indexing and retrieval of classified documents, the system comprising, at least one server computer, at least one document collection, said document collection comprising at least one document(s), said document(s) having been classified according to a predefined classification scheme, said predefined classification scheme comprising classification codes, said classification codes comprising title(s) and definition(s), said document(s) further comprising at least one retrieval key, wherein said retrieval key corresponds with at least one term of at least one of said classification code title(s) or classification code definition(s); at least one server web application; and at least one search engine system, wherein said server computer is connected to said search engine, and wherein said server web application communicates document(s) from said document collection to said search engine; and a means for dynamically inserting said term into said document(s) to create a tagged document, wherein said insertion is in response to a request from said search engine, and wherein said tagged document is communicated to said search engine. | 7. A system for the indexing and retrieval of classified documents, the system comprising, at least one server computer, at least one document collection, said document collection comprising at least one document(s), said document(s) having been classified according to a predefined classification scheme, said predefined classification scheme comprising classification codes, said classification codes comprising title(s) and definition(s), said document(s) further comprising at least one retrieval key, wherein said retrieval key corresponds with at least one term of at least one of said classification code title(s) or classification code definition(s); at least one server web application; and at least one search engine system, wherein said server computer is connected to said search engine, and wherein said server web application communicates document(s) from said document collection to said search engine; and a means for dynamically inserting said term into said document(s) to create a tagged document, wherein said insertion is in response to a request from said search engine, and wherein said tagged document is communicated to said search engine. 8. The system for the indexing and retrieval of classified documents of claim 7 , wherein the document(s) is in a format, said format selected from the group consisting of: HTML, XML, PDF, and MSWord. | 0.541284 |
8,706,478 | 1 | 3 | 1. A method for transforming a natural language request for modifying a set of subscriptions for a publish/subscribe topic string, the method comprising: receiving, at a processing device, a natural language request for modifying a set of subscriptions for one or more topics in a publish/subscribe topic hierarchy, the natural language request comprising a topic in the hierarchy and a predetermined natural language element; transforming the natural language request into a publish/subscribe topic string, wherein the predetermined natural language element is transformed into a publish/subscribe symbol, the symbol identifying a hierarchical relationship between the topic in the natural language request and one or more other topics in the topic hierarchy; and modifying one or more subscriptions to include one or more topics having the identified hierarchical relationship to the topic in the natural language request based on the transformed topic string. | 1. A method for transforming a natural language request for modifying a set of subscriptions for a publish/subscribe topic string, the method comprising: receiving, at a processing device, a natural language request for modifying a set of subscriptions for one or more topics in a publish/subscribe topic hierarchy, the natural language request comprising a topic in the hierarchy and a predetermined natural language element; transforming the natural language request into a publish/subscribe topic string, wherein the predetermined natural language element is transformed into a publish/subscribe symbol, the symbol identifying a hierarchical relationship between the topic in the natural language request and one or more other topics in the topic hierarchy; and modifying one or more subscriptions to include one or more topics having the identified hierarchical relationship to the topic in the natural language request based on the transformed topic string. 3. The method according to claim 1 , where a given predetermined natural language element used in the natural language request in relation to a given topic is selectively transformable into a plurality of publish/subscribe symbols. | 0.706107 |
9,996,537 | 1 | 2 | 1. A system for transforming media elements into a narrative comprising: a processor; a memory in communication with the processor; a clustering module in communication with the processor and the memory, the clustering module configured to: receive a dataset comprising a plurality of media elements each comprising metadata; and organize the plurality of media elements into a plurality of clusters based on the metadata, the plurality of clusters being organized into a clustering tree; and a narrative module in communication with the processor and the memory, the narrative module configured to create a narrative comprising a plurality of the media elements arranged into a narrative sequence, the narrative sequence being structured according to the clustering tree and for a predetermined duration, the narrative sequence comprising a story introduction for introducing the narrative, a geographic introduction for contextualizing a cluster, a time introduction for identifying a cluster time period, a show of media elements for representing the media elements, and a story end, wherein the narrative module is configured to create the narrative sequence according to an algorithm comprising specific durations for at least the following entries: story introduction (SI), geographic introduction (GI), time introduction (TI), show of photos, with a minimum duration for photo representation (P min ), and story end, given (SE guess ), where T is a total duration of the narrative, N is a total number of media elements in the dataset, and the algorithm produces the following result:
T>SI+GI+TI+P min +SE guess . | 1. A system for transforming media elements into a narrative comprising: a processor; a memory in communication with the processor; a clustering module in communication with the processor and the memory, the clustering module configured to: receive a dataset comprising a plurality of media elements each comprising metadata; and organize the plurality of media elements into a plurality of clusters based on the metadata, the plurality of clusters being organized into a clustering tree; and a narrative module in communication with the processor and the memory, the narrative module configured to create a narrative comprising a plurality of the media elements arranged into a narrative sequence, the narrative sequence being structured according to the clustering tree and for a predetermined duration, the narrative sequence comprising a story introduction for introducing the narrative, a geographic introduction for contextualizing a cluster, a time introduction for identifying a cluster time period, a show of media elements for representing the media elements, and a story end, wherein the narrative module is configured to create the narrative sequence according to an algorithm comprising specific durations for at least the following entries: story introduction (SI), geographic introduction (GI), time introduction (TI), show of photos, with a minimum duration for photo representation (P min ), and story end, given (SE guess ), where T is a total duration of the narrative, N is a total number of media elements in the dataset, and the algorithm produces the following result:
T>SI+GI+TI+P min +SE guess . 2. The system of claim 1 , wherein: the metadata for each media element comprises information about a time at which the media element was created, information about a location at which the media element was created, or a combination thereof; and the clustering module is configured to organize the plurality of media elements into the plurality of clusters based on: time, wherein the produced clusters are isolated in time but not in space; space, wherein the produced clusters are isolated in space but not in time; space/time, wherein the produced clusters comprise a sequence of clusters organized so that consecutive clusters are isolated in space and time; or a combination thereof. | 0.566751 |
9,002,848 | 10 | 17 | 10. A system comprising: a non-transitory storage device configured to store a set of documents, the set of documents including a first plurality of previously clustered documents and a second plurality of documents, each of the first plurality of previously clustered documents having at least one label identifying a topic to which content of the document relates; a clustering engine configured to: partition documents from the set of documents into multiple clusters; and determine that a dominant topic exists within a first cluster of said multiple clusters; determine (i) a purity score representing a first ratio of a number of documents having a label identifying the dominant topic in the first cluster to a total number of previously clustered documents within the first cluster and (ii) a confidence measure representing a second ratio of the total number of previously clustered documents in the first cluster to a size of the first cluster, wherein the size of the first cluster equals a total number od documents included within the first cluster; and a labeling engine configured to assign a label identifying the dominant topic to at least documents from the second plurality of documents within said one of the multiple clusters when the purity score exceeds a first predetermined threshold and the confidence score exceeds a second predetermined threshold. | 10. A system comprising: a non-transitory storage device configured to store a set of documents, the set of documents including a first plurality of previously clustered documents and a second plurality of documents, each of the first plurality of previously clustered documents having at least one label identifying a topic to which content of the document relates; a clustering engine configured to: partition documents from the set of documents into multiple clusters; and determine that a dominant topic exists within a first cluster of said multiple clusters; determine (i) a purity score representing a first ratio of a number of documents having a label identifying the dominant topic in the first cluster to a total number of previously clustered documents within the first cluster and (ii) a confidence measure representing a second ratio of the total number of previously clustered documents in the first cluster to a size of the first cluster, wherein the size of the first cluster equals a total number od documents included within the first cluster; and a labeling engine configured to assign a label identifying the dominant topic to at least documents from the second plurality of documents within said one of the multiple clusters when the purity score exceeds a first predetermined threshold and the confidence score exceeds a second predetermined threshold. 17. The system of claim 10 , wherein the at least one label is a plurality of labels, said system is further configured to: assign a respective weight to each label in the plurality of labels; and determine the dominant topic based at least in part on the respective weights. | 0.708068 |
8,891,908 | 1 | 4 | 1. An image retrieval method, comprising: learning multiple object category classifiers with a processor offline and generating classifications scores of images as the semantic attributes; and performing vocabulary tree based image retrieval using local features with semantic-aware co-indexing to jointly embed two distinct cues offline for near-duplicate image retrieval; and identifying top similar or dissimilar images using multiple semantic attributes; performing semantic-aware online querying; determining: sim ( q , d ) = . 1 S q S d ∑ v i ∈ T ( x i ) , v j ∈ T ( x j ) w v ( v i , v j ) , w v ( v i , v j ) = . idf 2 ( v ) 1 ( v i = v j ) = log 2 ( M M v ) , where i and j are indices, x is tree node, S is a bag of local descriptions, q a query image, d a database image, T is a vocabulary tree, w is word, idf is an inverse document frequency of node v, M is a total number of database images and M v is a number of images containing at least one descriptor that quantizes to a node v. | 1. An image retrieval method, comprising: learning multiple object category classifiers with a processor offline and generating classifications scores of images as the semantic attributes; and performing vocabulary tree based image retrieval using local features with semantic-aware co-indexing to jointly embed two distinct cues offline for near-duplicate image retrieval; and identifying top similar or dissimilar images using multiple semantic attributes; performing semantic-aware online querying; determining: sim ( q , d ) = . 1 S q S d ∑ v i ∈ T ( x i ) , v j ∈ T ( x j ) w v ( v i , v j ) , w v ( v i , v j ) = . idf 2 ( v ) 1 ( v i = v j ) = log 2 ( M M v ) , where i and j are indices, x is tree node, S is a bag of local descriptions, q a query image, d a database image, T is a vocabulary tree, w is word, idf is an inverse document frequency of node v, M is a total number of database images and M v is a number of images containing at least one descriptor that quantizes to a node v. 4. The method of claim 1 , comprising co-indexing local features and semantic attributes offline in inverted indexes for near-duplicate image retrieval. | 0.816867 |
8,051,045 | 1 | 7 | 1. A method comprising: identifying a data record for deletion from a database and storage in a data archive, the data record comprising a plurality of data record attributes, each of the plurality of data record attributes comprising a value that comprises at least one term; creating an archive record that comprises a first subset of attribute values of the plurality of data record attributes and an index record that comprises a second subset of attribute values of the plurality of data record attributes; storing the archive record in a data archive that is stored separately from the database; adding a reference to a location of the archive record in the data archive to the new index record; adding the new index record to a dictionary-based archive index that is stored separately from the database, the dictionary-based archive index comprising a plurality of index records and a dictionary, the adding of the index record to the dictionary-based archive index comprising identifying every term of the second subset of attribute values of the plurality of data record attributes and adding each of the terms to the dictionary except for those terms that are already in the dictionary, wherein at least one index record of the plurality of index records in the dictionary-based archive index comprises one term from terms stored in the dictionary, references to locations of multiple archive records in the data archive that contain the one term, and information regarding locations of the one term within the referenced multiple archive records, the location information including indications, for each of the multiple of archive records referenced by the at least one index record, respective attributes of the each of the multiple archive records in which the one term is found; deleting the data record from the database; determining whether an attribute value of the plurality of attribute values is required for frequent user read access; and if the attribute value is not required for frequent user read access, deleting the attribute value from the dictionary-based archive index. | 1. A method comprising: identifying a data record for deletion from a database and storage in a data archive, the data record comprising a plurality of data record attributes, each of the plurality of data record attributes comprising a value that comprises at least one term; creating an archive record that comprises a first subset of attribute values of the plurality of data record attributes and an index record that comprises a second subset of attribute values of the plurality of data record attributes; storing the archive record in a data archive that is stored separately from the database; adding a reference to a location of the archive record in the data archive to the new index record; adding the new index record to a dictionary-based archive index that is stored separately from the database, the dictionary-based archive index comprising a plurality of index records and a dictionary, the adding of the index record to the dictionary-based archive index comprising identifying every term of the second subset of attribute values of the plurality of data record attributes and adding each of the terms to the dictionary except for those terms that are already in the dictionary, wherein at least one index record of the plurality of index records in the dictionary-based archive index comprises one term from terms stored in the dictionary, references to locations of multiple archive records in the data archive that contain the one term, and information regarding locations of the one term within the referenced multiple archive records, the location information including indications, for each of the multiple of archive records referenced by the at least one index record, respective attributes of the each of the multiple archive records in which the one term is found; deleting the data record from the database; determining whether an attribute value of the plurality of attribute values is required for frequent user read access; and if the attribute value is not required for frequent user read access, deleting the attribute value from the dictionary-based archive index. 7. The method of claim 1 , wherein: the second subset of attribute values at least includes the first subset of attribute values; and accepting a query for a desired archive record comprises accepting a query to find the desired data record in the dictionary-based archive index based on the values for the second subset of attribute values; the method further comprising: accepting a query from a user for a desired archive record; performing a search of the archive index to find the desired archive record; and returning as a response to the query a responsive subset of the values for the second subset of attribute values for the desired data record. | 0.500762 |
9,053,421 | 14 | 17 | 14. A method of constructing a organizational chart, the method comprising: gathering data regarding a plurality of captured communicative acts occurring between two parties, the two parties defining a sender and receiver pair; using a processor and predefined behavior based patterns stored in at least one database to score each of the plurality of captured communicative acts to determine a plurality of social perception scores for the sender and receiver pair, each one of the plurality of social perception scores representing a perceived social difference between the sender and receiver pair for a respective one of the plurality of captured communicative acts based at least in part on behaviors used during the respective one of the plurality of captured communicative acts; and combining the plurality of social perception scores for the captured communicative acts occurring between the sender and receiver pair to construct a combined social perception score for the sender and receiver pair indicating the perceived social difference between the sender and receiver pair based on all of the plurality of captured communicative acts between the sender and receiver pair; wherein: the sender and receiver pair is one of a plurality of sender and receiver pairs in a group, and the processor determines a different combined social perception score for each one of the of plurality of sender and receiver pairs, and the method further comprises using an aggregating hardware engine to aggregate the different combined social perception scores for each of the plurality of sender and receiver pairs to construct the organizational chart for the group, the organizational chart for the group indicating relative social perceptions between all individuals in the group that form part of the plurality of sender and receiver pairs. | 14. A method of constructing a organizational chart, the method comprising: gathering data regarding a plurality of captured communicative acts occurring between two parties, the two parties defining a sender and receiver pair; using a processor and predefined behavior based patterns stored in at least one database to score each of the plurality of captured communicative acts to determine a plurality of social perception scores for the sender and receiver pair, each one of the plurality of social perception scores representing a perceived social difference between the sender and receiver pair for a respective one of the plurality of captured communicative acts based at least in part on behaviors used during the respective one of the plurality of captured communicative acts; and combining the plurality of social perception scores for the captured communicative acts occurring between the sender and receiver pair to construct a combined social perception score for the sender and receiver pair indicating the perceived social difference between the sender and receiver pair based on all of the plurality of captured communicative acts between the sender and receiver pair; wherein: the sender and receiver pair is one of a plurality of sender and receiver pairs in a group, and the processor determines a different combined social perception score for each one of the of plurality of sender and receiver pairs, and the method further comprises using an aggregating hardware engine to aggregate the different combined social perception scores for each of the plurality of sender and receiver pairs to construct the organizational chart for the group, the organizational chart for the group indicating relative social perceptions between all individuals in the group that form part of the plurality of sender and receiver pairs. 17. The method of claim 14 , wherein a hardware engine performs the combining the social perception scores operation. | 0.937633 |
7,788,134 | 10 | 13 | 10. The method of claim 1 , wherein associating the identified geographic attributes with the items includes storing the identified geographic attributes in a searchable field of a data structure for the items. | 10. The method of claim 1 , wherein associating the identified geographic attributes with the items includes storing the identified geographic attributes in a searchable field of a data structure for the items. 13. The method of claim 10 , further comprising providing the data structure to a user for local access and searching by the user. | 0.947197 |
7,570,661 | 1 | 2 | 1. A method of analyzing a network data stream comprising: capturing frames from a network data stream; parsing said captured frames using a protocol parser having a data structure, stored on a computer-readable medium, that includes a data type that identifies the protocol to generate parsed frames, wherein the protocol parser is created by interpreting a script that describes the format of the protocol and that is written in a language describing network protocols; organizing said parsed frames into conversations; and substituting a data structure size in said protocol parser for a selected data structure. | 1. A method of analyzing a network data stream comprising: capturing frames from a network data stream; parsing said captured frames using a protocol parser having a data structure, stored on a computer-readable medium, that includes a data type that identifies the protocol to generate parsed frames, wherein the protocol parser is created by interpreting a script that describes the format of the protocol and that is written in a language describing network protocols; organizing said parsed frames into conversations; and substituting a data structure size in said protocol parser for a selected data structure. 2. The method of analyzing a network data stream claimed in claim 1 wherein said protocol parser is stored in memory. | 0.892066 |
9,484,020 | 17 | 18 | 17. The computer-readable storage device of claim 15 , the computer-readable storage medium having additional instructions stored which result in operations comprising inserting an edit tag in the annotated data. | 17. The computer-readable storage device of claim 15 , the computer-readable storage medium having additional instructions stored which result in operations comprising inserting an edit tag in the annotated data. 18. The computer-readable storage device of claim 17 , wherein the edit tag identifies a portion of the speech utterance text to be removed based on repeated words which do not contribute to language understanding. | 0.867901 |
8,458,111 | 18 | 19 | 18. A computer system comprising the following: one or more processors; system memory; one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by the one or more processors, causes the computing system to perform a method for interpreting declarative program types at runtime without compiling, the method comprising the following: an act of accessing at least a portion of a declarative program that defines a parent activity using a declarative language, the declarative program written in XAML markup, the parent activity including a fully modeled activity type that includes one or more members which define a data flow for the fully modeled activity type, each member being defined within a XAML tag in the XAML markup and including a name and a type of input for the member, wherein the XAML markup also includes an identification of a schema to be used to determine how the fully modeled activity type is to be interpreted at runtime by a continuation-based runtime; an act of dynamically constructing a dynamic activity type based on the fully modeled activity type of the declarative program, the dynamic activity type being configured for interpretive execution by the continuation-based runtime without compilation, dynamically constructing the dynamic activity type comprising: generating, based on the schema defined in the declarative program, a type in memory without creating a common language runtime type to represent the fully modeled activity type, and mapping, based on the schema defined in the declarative program, each member of the fully modeled activity type to a property of the in-memory type; an act of interpretively executing the dynamically constructed dynamic activity type such that the dynamic activity is executed without compilation; an act of receiving a modification to the declarative program that modifies the schema; an act of dynamically constructing another dynamic activity type based on the fully modeled activity type of the declarative program, the other dynamic activity type being configured for interpretive execution without compilation, dynamically constructing the other dynamic activity type comprising: generating, based on the modified schema defined in the declarative program, a type in memory without creating a common language runtime type to represent the fully modeled activity type, and mapping, based on the modified schema defined in the declarative program, each member of the fully modeled activity type to a property of the in-memory type; an act of interpretively executing the dynamically constructed other dynamic activity type within the continuation-based runtime at a first process, such that the other dynamic activity type is executed without compilation, and during execution of the dynamically constructed dynamic activity type: pausing execution of the dynamically constructed dynamic activity type at the first process; and resuming execution of the dynamically constructed dynamic activity type at a second, different process. | 18. A computer system comprising the following: one or more processors; system memory; one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by the one or more processors, causes the computing system to perform a method for interpreting declarative program types at runtime without compiling, the method comprising the following: an act of accessing at least a portion of a declarative program that defines a parent activity using a declarative language, the declarative program written in XAML markup, the parent activity including a fully modeled activity type that includes one or more members which define a data flow for the fully modeled activity type, each member being defined within a XAML tag in the XAML markup and including a name and a type of input for the member, wherein the XAML markup also includes an identification of a schema to be used to determine how the fully modeled activity type is to be interpreted at runtime by a continuation-based runtime; an act of dynamically constructing a dynamic activity type based on the fully modeled activity type of the declarative program, the dynamic activity type being configured for interpretive execution by the continuation-based runtime without compilation, dynamically constructing the dynamic activity type comprising: generating, based on the schema defined in the declarative program, a type in memory without creating a common language runtime type to represent the fully modeled activity type, and mapping, based on the schema defined in the declarative program, each member of the fully modeled activity type to a property of the in-memory type; an act of interpretively executing the dynamically constructed dynamic activity type such that the dynamic activity is executed without compilation; an act of receiving a modification to the declarative program that modifies the schema; an act of dynamically constructing another dynamic activity type based on the fully modeled activity type of the declarative program, the other dynamic activity type being configured for interpretive execution without compilation, dynamically constructing the other dynamic activity type comprising: generating, based on the modified schema defined in the declarative program, a type in memory without creating a common language runtime type to represent the fully modeled activity type, and mapping, based on the modified schema defined in the declarative program, each member of the fully modeled activity type to a property of the in-memory type; an act of interpretively executing the dynamically constructed other dynamic activity type within the continuation-based runtime at a first process, such that the other dynamic activity type is executed without compilation, and during execution of the dynamically constructed dynamic activity type: pausing execution of the dynamically constructed dynamic activity type at the first process; and resuming execution of the dynamically constructed dynamic activity type at a second, different process. 19. The computer system of claim 18 , wherein mapping each member of the fully modeled activity type to a property of the dynamic activity type and the other dynamic activity type includes assigning the name of the member to the name of the property. | 0.501992 |
9,582,554 | 8 | 11 | 8. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions for: receiving a table containing a plurality of entries, each entry storing plain text; receiving an entity database containing an entity collection, the entity collection including a plurality of entity tags that belong to a category, wherein an entity tag from the plurality of entity tags is linked with metadata information from an open access database; determining that a set of entries from the plurality of entries belong to the category; matching an entry in the set of entries to the entity tag; linking the entity tag to the entry; searching an available resource other than the open access database to link additional data related to the entry according to the entity tag; selecting the additional data from a canvas overlying the available resource; and enriching the table to include the additional data in a new column. | 8. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions for: receiving a table containing a plurality of entries, each entry storing plain text; receiving an entity database containing an entity collection, the entity collection including a plurality of entity tags that belong to a category, wherein an entity tag from the plurality of entity tags is linked with metadata information from an open access database; determining that a set of entries from the plurality of entries belong to the category; matching an entry in the set of entries to the entity tag; linking the entity tag to the entry; searching an available resource other than the open access database to link additional data related to the entry according to the entity tag; selecting the additional data from a canvas overlying the available resource; and enriching the table to include the additional data in a new column. 11. The non-transitory computer readable storage medium of claim 8 , wherein the entity tag is configured to provide context to the plain text of the entry. | 0.815603 |
8,996,513 | 8 | 9 | 8. A system, which includes a processor and computer readable media, that constructs a search-result snippet of a website the system comprising: a search engine that receives a search query; a search-engine index that is leveraged by the search engine to determine that a plurality of websites are relevant to the search query, wherein the website is included among the plurality of websites, and wherein the search-engine index includes website instructions, which indicate that the website includes a website tool accessible at a landing page of the website; a snippet builder that constructs a plurality of search-result snippets, wherein each search-result snippet of the plurality of search-result snippets is tailored to summarize a respective website of the plurality of websites, wherein the snippet builder receives the website instructions and transforms the website instructions into an interface that provides access to the website tool and that is included in a search-result snippet summarizing the website, and wherein the interface includes a service-call instruction that provides access to the website tool without navigating to the landing page of the website; and a search-engine response page that provides the plurality of search-result snippets in response to the search query, wherein the search-result snippet of the website is included among the plurality of search-result snippets. | 8. A system, which includes a processor and computer readable media, that constructs a search-result snippet of a website the system comprising: a search engine that receives a search query; a search-engine index that is leveraged by the search engine to determine that a plurality of websites are relevant to the search query, wherein the website is included among the plurality of websites, and wherein the search-engine index includes website instructions, which indicate that the website includes a website tool accessible at a landing page of the website; a snippet builder that constructs a plurality of search-result snippets, wherein each search-result snippet of the plurality of search-result snippets is tailored to summarize a respective website of the plurality of websites, wherein the snippet builder receives the website instructions and transforms the website instructions into an interface that provides access to the website tool and that is included in a search-result snippet summarizing the website, and wherein the interface includes a service-call instruction that provides access to the website tool without navigating to the landing page of the website; and a search-engine response page that provides the plurality of search-result snippets in response to the search query, wherein the search-result snippet of the website is included among the plurality of search-result snippets. 9. The system of claim 8 further comprising, a crawler that retrieves the website instructions from the website and that recognizes a website-tool format, which indicates that the website includes the website tool. | 0.627178 |
9,646,082 | 16 | 19 | 16. A method comprising: identifying a first set of documents from a first database using a query for legal information; automatically identifying metadata associated with one or more of the identified first set of documents by executing the query against a plurality of additional databases comprising at least a legal classification code database, a legal headnotes database, and a secondary legal documents database; automatically identifying, based on the identified metadata, a set of key classification codes associated with the metadata and the identified first set of documents; automatically identifying a second set of two or more documents based on the metadata associated with one or more of the identified first set of documents and the identified set of key classification codes; automatically ranking the second set of documents based at least in part on identification of the second set of documents; and automatically outputting a list of one or more of the ranked documents to a client access device. | 16. A method comprising: identifying a first set of documents from a first database using a query for legal information; automatically identifying metadata associated with one or more of the identified first set of documents by executing the query against a plurality of additional databases comprising at least a legal classification code database, a legal headnotes database, and a secondary legal documents database; automatically identifying, based on the identified metadata, a set of key classification codes associated with the metadata and the identified first set of documents; automatically identifying a second set of two or more documents based on the metadata associated with one or more of the identified first set of documents and the identified set of key classification codes; automatically ranking the second set of documents based at least in part on identification of the second set of documents; and automatically outputting a list of one or more of the ranked documents to a client access device. 19. The method of claim 16 , wherein the ranking the second set of documents includes using a learning machine to process a plurality of feature vectors, with each feature vector including a feature based on at least one from the group consisting of number of shared legal classification codes and number of shared legal citations. | 0.731331 |
9,495,542 | 10 | 12 | 10. A non-transient computer program product comprising computer code for execution on a host computer processor, the computer code for implementing a method of scanning an item of target code prepared from a program written in a programming language having a security specification, the method employing a model checking system, the code comprising: computer code for receiving the item of target code, the target code comprising an item of executable binary code; code for preparing a data structure corresponding to the item target code by parsing the target code to extract executable elements; code for providing a language definition file corresponding to the programming language, the language definition file comprising rules defining the format of instructions in the programming language; code for providing a static model corresponding to the programming language, the static model comprising rules defined from the security specification of the programming language; code for creating a composite model of the target code by supplementing the data structure with information from the language definition file, and with information from the static model, the composite model having a format for processing by the model checking system; code for segmenting the composite model into a plurality of segments including at least a first segment; and code for changing a distribution of instructions among the segments by, for each segment after the first segment, assessing at least the first instruction in each segment, and moving the at least first instruction to an immediately preceding segment if that at least first instruction is not a transfer instruction; code for providing the composite model to the model checker; code for engaging the model checker to analyze the composite model, the code for engaging the model checker comprising: code for analyzing each of the plurality of segments individually; and code for analyzing boundaries of the segments; the model checker producing a result; and code for generating an output based on the result produced by the model checker, the output indicating a measure of whether the model checker identified an indication that the target contains malware. | 10. A non-transient computer program product comprising computer code for execution on a host computer processor, the computer code for implementing a method of scanning an item of target code prepared from a program written in a programming language having a security specification, the method employing a model checking system, the code comprising: computer code for receiving the item of target code, the target code comprising an item of executable binary code; code for preparing a data structure corresponding to the item target code by parsing the target code to extract executable elements; code for providing a language definition file corresponding to the programming language, the language definition file comprising rules defining the format of instructions in the programming language; code for providing a static model corresponding to the programming language, the static model comprising rules defined from the security specification of the programming language; code for creating a composite model of the target code by supplementing the data structure with information from the language definition file, and with information from the static model, the composite model having a format for processing by the model checking system; code for segmenting the composite model into a plurality of segments including at least a first segment; and code for changing a distribution of instructions among the segments by, for each segment after the first segment, assessing at least the first instruction in each segment, and moving the at least first instruction to an immediately preceding segment if that at least first instruction is not a transfer instruction; code for providing the composite model to the model checker; code for engaging the model checker to analyze the composite model, the code for engaging the model checker comprising: code for analyzing each of the plurality of segments individually; and code for analyzing boundaries of the segments; the model checker producing a result; and code for generating an output based on the result produced by the model checker, the output indicating a measure of whether the model checker identified an indication that the target contains malware. 12. The non-transient computer program product according to claim 10 , wherein code for segmenting the composite model into a plurality of segments comprises: code for segmenting the composite model into a plurality of segments according to language rule, and wherein code for providing the composite model to the model checker comprises code for providing the plurality of segments to a plurality of model checking systems. | 0.759091 |
8,078,633 | 1 | 9 | 1. A computer-implemented method, comprising: receiving, at a computer system, a string of characters that includes no word-delineating breaks; generating, by the computer system from the string of characters, a plurality of candidate word groups that are portions of the string of characters; determining, by the computer system, frequencies with which all or a portion of each of the candidate word groups occur in a corpus; and selecting, by the computer system using the determined frequencies, one or more of the candidate word groups for submission to an entity, wherein the one or more candidate word groups are selected based on each of the one or more candidate word groups having a determined frequency that is greater than determined frequencies for at least a threshold number of other candidate word groups. | 1. A computer-implemented method, comprising: receiving, at a computer system, a string of characters that includes no word-delineating breaks; generating, by the computer system from the string of characters, a plurality of candidate word groups that are portions of the string of characters; determining, by the computer system, frequencies with which all or a portion of each of the candidate word groups occur in a corpus; and selecting, by the computer system using the determined frequencies, one or more of the candidate word groups for submission to an entity, wherein the one or more candidate word groups are selected based on each of the one or more candidate word groups having a determined frequency that is greater than determined frequencies for at least a threshold number of other candidate word groups. 9. The method of claim 1 , wherein the selected one or more of the candidate word groups have the greatest determined frequencies among the generated candidate word groups. | 0.688406 |
4,508,447 | 5 | 7 | 5. The automatic document handling system of claim 3 wherein if said documents are simplex documents and duplex copying thereof is selected said control means automatically causes said first circulation of said document set to be a non copying circulation and then initiates a special initial copying circulation of only the document sheets in only one of said two trays in a second circulation of said document set, and then automatically initiates alternately sequentially feeding from both of said two trays in subsequent circulations of said document set. | 5. The automatic document handling system of claim 3 wherein if said documents are simplex documents and duplex copying thereof is selected said control means automatically causes said first circulation of said document set to be a non copying circulation and then initiates a special initial copying circulation of only the document sheets in only one of said two trays in a second circulation of said document set, and then automatically initiates alternately sequentially feeding from both of said two trays in subsequent circulations of said document set. 7. The automatic document handling system of claim 5 wherein said automatic alternate document sheet cooperative feeding means automatically acquires and begins feeding a sheet from one said tray simultaneously with the feeding of another sheet out of the other said tray to said copier. | 0.886292 |
10,102,847 | 13 | 19 | 13. One or more non-transitory computer-readable storage media storing instructions that, when executed by one or more processors, communicatively coupled to a communication network, configure the one or more processors to perform acts comprising: receiving, by a computer-based speech recognition system, a speech input including one or more words or phrases, wherein the speech input is from a call to a call center via the communication network; determining, by the computer-based speech recognition system, to provide the speech input to a human; receiving a response from the human that identifies a first task for the speech input, the first task including a first transcription of the speech input; processing the speech input to identify a second task for the speech input, the processing using a set of internal representations of the computer-based speech recognition system, the set of internal representations comprising one or more machine-readable parameters for recognizing speech in a speech utterance, the second task including a second transcription of the speech input; comparing the speech input and the first transcription of the speech input included in the first task with the second transcription of the speech input included in the second task, the set of internal representations comprising one or more machine-readable parameters for recognizing speech in a speech utterance; modifying the set of internal representations of the computer-based speech recognition system based at least in part on the comparing the first transcription with the second transcription to create a modified set of internal representations, wherein the modifying includes adjusting at least a portion of the set of internal representations; checking the performance of the modified set of internal representations to prevent the modification from degrading the set internal representations, wherein the checking comprises determining that a performance difference between the set of internal representations before and after modification is within a margin of error; receiving, by the computer-based speech recognition system, another input; and processing, by the one or more processors and based at least in part on the modified set of internal representations, the other input to identify a third task for the other input. | 13. One or more non-transitory computer-readable storage media storing instructions that, when executed by one or more processors, communicatively coupled to a communication network, configure the one or more processors to perform acts comprising: receiving, by a computer-based speech recognition system, a speech input including one or more words or phrases, wherein the speech input is from a call to a call center via the communication network; determining, by the computer-based speech recognition system, to provide the speech input to a human; receiving a response from the human that identifies a first task for the speech input, the first task including a first transcription of the speech input; processing the speech input to identify a second task for the speech input, the processing using a set of internal representations of the computer-based speech recognition system, the set of internal representations comprising one or more machine-readable parameters for recognizing speech in a speech utterance, the second task including a second transcription of the speech input; comparing the speech input and the first transcription of the speech input included in the first task with the second transcription of the speech input included in the second task, the set of internal representations comprising one or more machine-readable parameters for recognizing speech in a speech utterance; modifying the set of internal representations of the computer-based speech recognition system based at least in part on the comparing the first transcription with the second transcription to create a modified set of internal representations, wherein the modifying includes adjusting at least a portion of the set of internal representations; checking the performance of the modified set of internal representations to prevent the modification from degrading the set internal representations, wherein the checking comprises determining that a performance difference between the set of internal representations before and after modification is within a margin of error; receiving, by the computer-based speech recognition system, another input; and processing, by the one or more processors and based at least in part on the modified set of internal representations, the other input to identify a third task for the other input. 19. The computer-based speech recognition system of claim 13 , the acts further comprising performing the first task that is identified by the human for the speech input, wherein at least a portion of the first task that is identified by the human is performed by the human. | 0.704741 |
6,014,665 | 6 | 10 | 6. A method for organizing information comprising: (a) providing an index of key terms, the index associating each key term with at least one other key term to form key term groupings, the index further associating a key term matching score with each key term grouping; (b) accepting a first search query containing at least two key terms from a first user, with key terms of the first search query defining at least one key term grouping that contains at least two of the key terms of the first search query; storing the at least one key term grouping within the index; and storing a key term matching score with the at least one key term grouping; (c) altering the index such that the key term matching score for the key term grouping that contains at least two of the key terms of the first search query is altered relative to other key term matching scores; (d) accepting a second search query containing a first key term from a second user; (e) suggesting at least a second key term to the second user from one of the key term groupings defined by the first user that contains the first key term in accordance with the superiority of the key term matching scores of the key term groupings that contain the first key term. | 6. A method for organizing information comprising: (a) providing an index of key terms, the index associating each key term with at least one other key term to form key term groupings, the index further associating a key term matching score with each key term grouping; (b) accepting a first search query containing at least two key terms from a first user, with key terms of the first search query defining at least one key term grouping that contains at least two of the key terms of the first search query; storing the at least one key term grouping within the index; and storing a key term matching score with the at least one key term grouping; (c) altering the index such that the key term matching score for the key term grouping that contains at least two of the key terms of the first search query is altered relative to other key term matching scores; (d) accepting a second search query containing a first key term from a second user; (e) suggesting at least a second key term to the second user from one of the key term groupings defined by the first user that contains the first key term in accordance with the superiority of the key term matching scores of the key term groupings that contain the first key term. 10. The method for organizing information of claim 6, wherein step (d) comprises: (d2) accepting a second search query containing a first key term from a second user, and searching for articles related to the second search query. | 0.926461 |
9,235,635 | 6 | 8 | 6. Non-transitory machine readable media comprising program code that when executed by a programmable processor causes execution of a method for generating search results, the machine readable media including: program code for identifying a set of words in a fixed size data stream based on a subword cache; program code for determining at least one story trend associated with the set of words and generating a story hash associated with the set of words; program code for storing the story hash in a story trend cache and updating the story trend cache according to the story hash; and program code for retrieving one or more popular story topics according to the story trend cache for presentation to a user. | 6. Non-transitory machine readable media comprising program code that when executed by a programmable processor causes execution of a method for generating search results, the machine readable media including: program code for identifying a set of words in a fixed size data stream based on a subword cache; program code for determining at least one story trend associated with the set of words and generating a story hash associated with the set of words; program code for storing the story hash in a story trend cache and updating the story trend cache according to the story hash; and program code for retrieving one or more popular story topics according to the story trend cache for presentation to a user. 8. The machine readable media of claim 6 , wherein generating a story hash associated with the set of words comprises generating a SimHash based on the set of words. | 0.795285 |
8,239,820 | 6 | 12 | 6. A compliance system for web services, comprising: an artifact repository, said artifact repository having a memory for storing a set of artifacts; and a runtime engine coupled to said artifact repository, wherein said runtime engine asserts to said set of artifacts a set of conformance requirements that include at least one rule having a combination of (1) descriptive meta data and (2) functional code fragments to produce a result output, wherein said descriptive meta data includes a designation of a level of severity for non-conformance of said rule and said functional code fragments include a query and a match script, wherein said runtime engine executes said query for each of said set of artifacts to identify a portion of an artifact to be processed by said match script and invokes said match script to determine whether said artifact conforms to said rule, and wherein, if said artifact causes a non-conformance, said runtime engine generates and includes in said result output at least one result message containing (1) a result pointer that links to a location of a cause of said non-conformance in said artifact and (2) a result meta data that includes (i) a text description of said non-conformance, (ii) date and time of a run resulting in said non-conformance, (iii) an identity of a system executing said run, and (iv) input provided for said run. | 6. A compliance system for web services, comprising: an artifact repository, said artifact repository having a memory for storing a set of artifacts; and a runtime engine coupled to said artifact repository, wherein said runtime engine asserts to said set of artifacts a set of conformance requirements that include at least one rule having a combination of (1) descriptive meta data and (2) functional code fragments to produce a result output, wherein said descriptive meta data includes a designation of a level of severity for non-conformance of said rule and said functional code fragments include a query and a match script, wherein said runtime engine executes said query for each of said set of artifacts to identify a portion of an artifact to be processed by said match script and invokes said match script to determine whether said artifact conforms to said rule, and wherein, if said artifact causes a non-conformance, said runtime engine generates and includes in said result output at least one result message containing (1) a result pointer that links to a location of a cause of said non-conformance in said artifact and (2) a result meta data that includes (i) a text description of said non-conformance, (ii) date and time of a run resulting in said non-conformance, (iii) an identity of a system executing said run, and (iv) input provided for said run. 12. The compliance system according to claim 6 , wherein said set of artifacts include data from at least one of the group consisting of contracts, messages, and rules. | 0.718121 |
9,135,370 | 1 | 4 | 1. A method of generating updating parameters, the method comprising: obtaining one or more related keywords associated with a primary keyword, one or more co-search frequencies of the primary keyword and the one or more related keywords, and a search frequency of the primary keyword; computing one or more correlation levels based at least in part on the one or more co-search frequencies; computing a first feature value based at least in part on the search frequency of the primary keyword; and computing one or more second feature values based at least in part on the first feature value, the one or more correlation levels and the one or more co-search frequencies, a second feature value of the one or more second feature values being served as a parameter for determining whether a corresponding related keyword of the one or more related keywords is to be displayed constantly or in a rotating manner. | 1. A method of generating updating parameters, the method comprising: obtaining one or more related keywords associated with a primary keyword, one or more co-search frequencies of the primary keyword and the one or more related keywords, and a search frequency of the primary keyword; computing one or more correlation levels based at least in part on the one or more co-search frequencies; computing a first feature value based at least in part on the search frequency of the primary keyword; and computing one or more second feature values based at least in part on the first feature value, the one or more correlation levels and the one or more co-search frequencies, a second feature value of the one or more second feature values being served as a parameter for determining whether a corresponding related keyword of the one or more related keywords is to be displayed constantly or in a rotating manner. 4. The method as recited in claim 1 , wherein prior to computing the first feature value, the method further comprises filtering out a plurality of related keywords that satisfy a filtering rule. | 0.875 |
9,058,580 | 1 | 6 | 1. A method, comprising: receiving or capturing an image comprising an identity document (ID) using a mobile device; classifying the ID; wherein the classifying comprises: generating a reduced-resolution representation of the ID, determining the ID corresponds to a particular state; and identifying the particular state to which the ID corresponds; and extracting data from the ID based at least in part on the ID classification; and driving at least a portion of a workflow based on the extracted data, wherein the classifying is based on the image characteristics corresponding to the reduced-resolution representation of the identity document. | 1. A method, comprising: receiving or capturing an image comprising an identity document (ID) using a mobile device; classifying the ID; wherein the classifying comprises: generating a reduced-resolution representation of the ID, determining the ID corresponds to a particular state; and identifying the particular state to which the ID corresponds; and extracting data from the ID based at least in part on the ID classification; and driving at least a portion of a workflow based on the extracted data, wherein the classifying is based on the image characteristics corresponding to the reduced-resolution representation of the identity document. 6. The method as recited in claim 1 , wherein the ID comprises a multi-paged document, and the method further comprising: receiving or capturing one or more additional images using the mobile device, each additional image comprising at least a portion of at least one page of the ID, classifying each page of the ID; comparing each page classification to a classification of one or more other pages; and classifying the ID based on the comparison wherein the data are extracted from at least two pages of the ID. | 0.612708 |
8,015,543 | 20 | 30 | 20. A computer-readable medium comprising instructions, which when executed by a computer system causes the computer system to perform operations for a generating code based on a graphical model, the computer-readable medium comprising: instructions for translating the graphical model into a graphical model code, the graphical model code being compilable into an executable program and including a first graphical model code function, the first graphical model code function being a member of a group of graphical model code functions; instructions for receiving a selection of a first hardware specific library from a plurality of hardware specific libraries, the hardware specific libraries corresponding to one of at least a first target environment and a second target environment, the first hardware specific library corresponding to the first target environment; the hardware specific libraries comprising a plurality of relationships between the group of graphical model code functions and hardware specific functions, the hardware specific functions being compilable into object code for execution in the first target environment, and instructions for performing a lookup of the first graphical model code function in the first hardware specific library; instructions for obtaining a matched hardware specific function based on the lookup, the matched hardware specific function matching at least one property of the graphical model code function and being one of the hardware specific functions from the first hardware specific library; and instructions for modifying the graphical model code based on the matched hardware specific function. | 20. A computer-readable medium comprising instructions, which when executed by a computer system causes the computer system to perform operations for a generating code based on a graphical model, the computer-readable medium comprising: instructions for translating the graphical model into a graphical model code, the graphical model code being compilable into an executable program and including a first graphical model code function, the first graphical model code function being a member of a group of graphical model code functions; instructions for receiving a selection of a first hardware specific library from a plurality of hardware specific libraries, the hardware specific libraries corresponding to one of at least a first target environment and a second target environment, the first hardware specific library corresponding to the first target environment; the hardware specific libraries comprising a plurality of relationships between the group of graphical model code functions and hardware specific functions, the hardware specific functions being compilable into object code for execution in the first target environment, and instructions for performing a lookup of the first graphical model code function in the first hardware specific library; instructions for obtaining a matched hardware specific function based on the lookup, the matched hardware specific function matching at least one property of the graphical model code function and being one of the hardware specific functions from the first hardware specific library; and instructions for modifying the graphical model code based on the matched hardware specific function. 30. The computer-readable medium of claim 20 , further comprising: instructions for providing a listing of blocks used in the graphical model, wherein the blocks contain at least one graphical model code function having a hardware specific function replacement in the at least one hardware specific library. | 0.760156 |
10,109,278 | 11 | 13 | 11. A system for aligning content, the system comprising: an electronic data store configured to store: a transcription of an item of content comprising audio content; and a companion item of textual content, wherein the companion item of textual content comprises: a plurality of paragraphs of body text, and matter other than body text; and a physical computing device in communication with the electronic data store, the physical computing device configured to: identify, in the transcription, a portion of the transcription that includes text also included in a portion of the companion item of textual content; determine a level of correlation between words in the portion of the companion item of textual content and words in the portion of the transcription; determine that the level of correlation satisfies a threshold value; in response to determining that the level of correlation satisfies a threshold value, identify the portion of the companion item of content as body text; identify a second portion of the companion item of textual content that does not satisfy the threshold value with respect to any portion of the transcription; determine that the second portion of the companion item of textual content that does not satisfy the threshold value is back matter based at least in part on a determination that the second portion of the companion item of textual content that does not satisfy the threshold value appears within the companion item of textual content after a last portion of the companion item of textual content for which a corresponding portion of the transcription is identified; and generate content synchronization information that identifies (a) portions of the audio content that correspond to body text of the companion item of textual content and (b) further identifies the matter other than body text in the companion item, wherein the content synchronization information indicates that the matter other than body text in the companion item does not correspond to the audio content, wherein the matter other than body text includes the second portion of the companion item of textual content determined to be back matter, wherein the content synchronization information indicates that the portion of the companion item of textual content, excluding the matter other than body text, should be presented in synchronization with a portion of the audio content that corresponds to the portion of the transcription. | 11. A system for aligning content, the system comprising: an electronic data store configured to store: a transcription of an item of content comprising audio content; and a companion item of textual content, wherein the companion item of textual content comprises: a plurality of paragraphs of body text, and matter other than body text; and a physical computing device in communication with the electronic data store, the physical computing device configured to: identify, in the transcription, a portion of the transcription that includes text also included in a portion of the companion item of textual content; determine a level of correlation between words in the portion of the companion item of textual content and words in the portion of the transcription; determine that the level of correlation satisfies a threshold value; in response to determining that the level of correlation satisfies a threshold value, identify the portion of the companion item of content as body text; identify a second portion of the companion item of textual content that does not satisfy the threshold value with respect to any portion of the transcription; determine that the second portion of the companion item of textual content that does not satisfy the threshold value is back matter based at least in part on a determination that the second portion of the companion item of textual content that does not satisfy the threshold value appears within the companion item of textual content after a last portion of the companion item of textual content for which a corresponding portion of the transcription is identified; and generate content synchronization information that identifies (a) portions of the audio content that correspond to body text of the companion item of textual content and (b) further identifies the matter other than body text in the companion item, wherein the content synchronization information indicates that the matter other than body text in the companion item does not correspond to the audio content, wherein the matter other than body text includes the second portion of the companion item of textual content determined to be back matter, wherein the content synchronization information indicates that the portion of the companion item of textual content, excluding the matter other than body text, should be presented in synchronization with a portion of the audio content that corresponds to the portion of the transcription. 13. The system of claim 11 , wherein the level of correlation is determined based at least in part on input received from a human interaction task system. | 0.890157 |
9,966,075 | 12 | 14 | 12. An augmented reality system comprising: a first augmented reality device, comprising: a microphone; a communication module; a first processor; a first head-mounted display worn by a user of the first augmented reality device; and a memory communicatively coupled with and readable by the first processor and having stored therein a first set of processor-readable instructions which, when executed by the first processor, cause the first processor to: capture, from the microphone, speech spoken by a person while the person is in a real-world scene within a field of view of the user of the first augmented reality device; determine who, in the real-world scene, spoke the speech by tracking the speech and recognizing the face of the person; generate an indication of the person that spoke the speech based on the determination of who spoke the speech; determine a second augmented reality device comprising a second head-mounted display to receive text corresponding to the speech; and cause the text corresponding to the speech and the indication of the person that spoke the speech to be transmitted to the second augmented reality device via the communication module. | 12. An augmented reality system comprising: a first augmented reality device, comprising: a microphone; a communication module; a first processor; a first head-mounted display worn by a user of the first augmented reality device; and a memory communicatively coupled with and readable by the first processor and having stored therein a first set of processor-readable instructions which, when executed by the first processor, cause the first processor to: capture, from the microphone, speech spoken by a person while the person is in a real-world scene within a field of view of the user of the first augmented reality device; determine who, in the real-world scene, spoke the speech by tracking the speech and recognizing the face of the person; generate an indication of the person that spoke the speech based on the determination of who spoke the speech; determine a second augmented reality device comprising a second head-mounted display to receive text corresponding to the speech; and cause the text corresponding to the speech and the indication of the person that spoke the speech to be transmitted to the second augmented reality device via the communication module. 14. The augmented reality system of claim 12 , wherein the second augmented reality device comprises: the second head-mounted display; a second processor; and a second memory communicatively coupled with and readable by the second processor and having stored therein a second set of processor-readable instructions which, when executed by the second processor, cause the second processor to: cause the second head-mounted display to display the text corresponding to the speech by the person such that the text is graphically attributed to the person by superimposing the text on the real-world scene. | 0.660835 |
10,034,099 | 13 | 17 | 13. A method for using an apparatus for differentiating between vowels and consonants in a spoken sound, the method comprising: passing a spoken sound longitudinally through a set of carbon nanotube bundles, wherein each carbon nanotube having different lengths and thickness from other carbon nanotube provides an output for differentiating the spoken sound as vowels and consonants; detecting variations on a set of characteristic parameters of the set of carbon nanotube bundles; and processing a plurality of signals associated with the set of characteristic parameters. | 13. A method for using an apparatus for differentiating between vowels and consonants in a spoken sound, the method comprising: passing a spoken sound longitudinally through a set of carbon nanotube bundles, wherein each carbon nanotube having different lengths and thickness from other carbon nanotube provides an output for differentiating the spoken sound as vowels and consonants; detecting variations on a set of characteristic parameters of the set of carbon nanotube bundles; and processing a plurality of signals associated with the set of characteristic parameters. 17. The method of claim 13 , further comprising: detecting variations on a set of dynamic characteristics of the spoken sound, wherein the set of dynamic characteristics is selected from the group consisting of: (i) sound loudness; (ii) sound pitch; and (iii) sound quality including timbre and richness. | 0.853846 |
7,978,267 | 1 | 3 | 1. A broadcasting receiver comprising: a broadcasting reception unit which receives caption data comprising information on an edge shape of a caption window and caption text to be displayed in the caption window; and a caption processor which processes the received caption data, determines the edge shape of the caption window corresponding to the caption data, and generates the caption window and the caption text according to the edge shape and the caption text, wherein the caption data further comprises at least one of tail location information and tail direction information of a tail attached to an edge of the caption window, and the caption processor generates the caption window based on the at least one of the tail location information and the tail direction information. | 1. A broadcasting receiver comprising: a broadcasting reception unit which receives caption data comprising information on an edge shape of a caption window and caption text to be displayed in the caption window; and a caption processor which processes the received caption data, determines the edge shape of the caption window corresponding to the caption data, and generates the caption window and the caption text according to the edge shape and the caption text, wherein the caption data further comprises at least one of tail location information and tail direction information of a tail attached to an edge of the caption window, and the caption processor generates the caption window based on the at least one of the tail location information and the tail direction information. 3. The broadcasting receiver according to claim 1 , wherein the caption data further comprises display position information and display size information of the caption window in which the caption text is displayed, and the caption processor generates the caption window according to the display position information and the display size information of the caption window. | 0.653271 |
9,760,931 | 8 | 9 | 8. A system for processing a specification, the system comprising: a computing device; and a computer-readable storage medium in communication with the computing device, the computer-readable storage medium comprising one or more programming instructions for: receiving information regarding a search of at least one good or service, using the received information to automatically generate a specification that comprises a digital signature and defines the good or service, wherein automatically generating the specification comprises: automatically generating a command block of the specification that comprises one or more instructions that define the search and one or more instructions that define one or more actions to perform with respect to results of the search, automatically generating an origin block of the specification that comprises a verification uniform resource locator, and automatically generating a routing block of the specification that comprises information identifying one or more destination marketplaces and one or more instructions for forwarding the specification to one or more of the destination marketplaces, and transmitting the specification to one of the destination marketplaces for processing by the destination marketplace. | 8. A system for processing a specification, the system comprising: a computing device; and a computer-readable storage medium in communication with the computing device, the computer-readable storage medium comprising one or more programming instructions for: receiving information regarding a search of at least one good or service, using the received information to automatically generate a specification that comprises a digital signature and defines the good or service, wherein automatically generating the specification comprises: automatically generating a command block of the specification that comprises one or more instructions that define the search and one or more instructions that define one or more actions to perform with respect to results of the search, automatically generating an origin block of the specification that comprises a verification uniform resource locator, and automatically generating a routing block of the specification that comprises information identifying one or more destination marketplaces and one or more instructions for forwarding the specification to one or more of the destination marketplaces, and transmitting the specification to one of the destination marketplaces for processing by the destination marketplace. 9. The system of claim 8 , wherein the one or more programming instructions for generating a specification comprises one or more programming instructions for generating a specification comprising at least one command block comprising a key corresponding to a domain-specific language instruction and a value corresponding to a parameter of the instruction. | 0.755158 |
8,407,805 | 21 | 22 | 21. The system of claim 12 , wherein the computer readable instructions further cause the at least one processor to automatically redact and distribute by using two threads in a multicore processor environment. | 21. The system of claim 12 , wherein the computer readable instructions further cause the at least one processor to automatically redact and distribute by using two threads in a multicore processor environment. 22. The system of claim 21 , wherein the computer readable instructions further cause the at least one processor to automatically analyze by using yet another thread in the multicore processor environment. | 0.953324 |
8,489,601 | 4 | 5 | 4. A method of extracting data from service repair verbatims in a vehicle service reporting system, the method comprising: collecting the service repair verbatims from the vehicle service reporting system, each service repair verbatim including to an identified problem with at least one vehicle part, a technician's comments concerning the at least one vehicle part, a symptom associated with the at least one vehicle part, and a repair action associated with the symptom; providing a diagnostic and prognostic ontology database that is structured by a vehicle part classification, a vehicle part sub-class classification, and a relationship classification, wherein the relationship classification includes symptom relationships and action relationships; reconstructing each of the service repair verbatims utilizing the diagnostic and prognostic ontology database; extracting combinations of information from the reconstructed service repair verbatims as a function of user input criteria by a processor; determining a frequency of appearance of each combination extracted in the reconstructed service repair verbatims by the processor, and; clustering the reconstructed service repair verbatims for each combination based on the frequency of appearance by the processor. | 4. A method of extracting data from service repair verbatims in a vehicle service reporting system, the method comprising: collecting the service repair verbatims from the vehicle service reporting system, each service repair verbatim including to an identified problem with at least one vehicle part, a technician's comments concerning the at least one vehicle part, a symptom associated with the at least one vehicle part, and a repair action associated with the symptom; providing a diagnostic and prognostic ontology database that is structured by a vehicle part classification, a vehicle part sub-class classification, and a relationship classification, wherein the relationship classification includes symptom relationships and action relationships; reconstructing each of the service repair verbatims utilizing the diagnostic and prognostic ontology database; extracting combinations of information from the reconstructed service repair verbatims as a function of user input criteria by a processor; determining a frequency of appearance of each combination extracted in the reconstructed service repair verbatims by the processor, and; clustering the reconstructed service repair verbatims for each combination based on the frequency of appearance by the processor. 5. The method of claim 4 , wherein the step of reconstructing each service repair verbatim includes segregating each respective service repair verbatim into one or more sentences. | 0.961472 |
9,368,108 | 4 | 5 | 4. A speech recognition method, comprising: acquiring a text file and extracting a command word from the text file according to a predetermined rule, to obtain a command word list; comparing the command word list with a command word library, to confirm whether the command word list comprises a new command word, wherein the new command word is a command word that is comprised in the command word list but not comprised in the command word library; if the command word list comprises the new command word, generating a corresponding new pronunciation dictionary according to the new command word and performing training to obtain a new language model; merging the new language model into a language model library corresponding to the command word library; receiving speech and performing speech recognition on the speech according to an acoustic model, a phonation dictionary, and the merged language model library; determining whether the text file changes; and if the text file changes, acquiring a changed text file. | 4. A speech recognition method, comprising: acquiring a text file and extracting a command word from the text file according to a predetermined rule, to obtain a command word list; comparing the command word list with a command word library, to confirm whether the command word list comprises a new command word, wherein the new command word is a command word that is comprised in the command word list but not comprised in the command word library; if the command word list comprises the new command word, generating a corresponding new pronunciation dictionary according to the new command word and performing training to obtain a new language model; merging the new language model into a language model library corresponding to the command word library; receiving speech and performing speech recognition on the speech according to an acoustic model, a phonation dictionary, and the merged language model library; determining whether the text file changes; and if the text file changes, acquiring a changed text file. 5. The method according to claim 4 , wherein acquiring a text file comprises: acquiring the text file from a specified address. | 0.917853 |
7,747,638 | 6 | 7 | 6. The method of claim 1 , wherein: each query in the first set of search queries is associated with one or more users from a first set of users, the first set of users including at least the first user; and each query in the second set of search queries is associated with one or more users from a second set of users, the second set of users including at least the second user. | 6. The method of claim 1 , wherein: each query in the first set of search queries is associated with one or more users from a first set of users, the first set of users including at least the first user; and each query in the second set of search queries is associated with one or more users from a second set of users, the second set of users including at least the second user. 7. The method of claim 6 , wherein: the first set of queries is a set of persistent queries issued by the first set of users prior to the first particular time; and the second set of queries is a set of persistent queries issued by the second set of users between the first particular time and the second particular time. | 0.958698 |
9,483,530 | 1 | 6 | 1. A method comprising: receiving, by a processor in a computer system, information indicating that a pair of queries is associated with a threshold quantity of search results that are common between the pair of queries, a first query, in the pair of queries, including an extra term that is not included in a second query in the pair of queries; identifying, by a processor in the computer system and based on receiving the information indicating that the pair of queries is associated with the threshold quantity of search results that are common between the pair of queries, the extra term as not significant; receiving, by a processor in the computer system, information indicating that another pair of queries is not associated with the threshold quantity of search results that are common between the other pair of queries, a first query, in the other pair of queries, including the extra term and a second query, in the other pair of queries, not including the extra term; identifying, by a processor in the computer system, a context in which the extra term is significant, the context in which the extra term is significant being based on the information indicating that the pair of queries is associated with the threshold quantity of search results that are common between the pair of queries; and storing, by a processor in the computer system, information including the extra term, an indication that the extra term is not significant, and the context in which the extra term is significant. | 1. A method comprising: receiving, by a processor in a computer system, information indicating that a pair of queries is associated with a threshold quantity of search results that are common between the pair of queries, a first query, in the pair of queries, including an extra term that is not included in a second query in the pair of queries; identifying, by a processor in the computer system and based on receiving the information indicating that the pair of queries is associated with the threshold quantity of search results that are common between the pair of queries, the extra term as not significant; receiving, by a processor in the computer system, information indicating that another pair of queries is not associated with the threshold quantity of search results that are common between the other pair of queries, a first query, in the other pair of queries, including the extra term and a second query, in the other pair of queries, not including the extra term; identifying, by a processor in the computer system, a context in which the extra term is significant, the context in which the extra term is significant being based on the information indicating that the pair of queries is associated with the threshold quantity of search results that are common between the pair of queries; and storing, by a processor in the computer system, information including the extra term, an indication that the extra term is not significant, and the context in which the extra term is significant. 6. The method of claim 1 , further comprising: identifying, based on identifying the extra term as not significant, a plurality of documents based on the first query; associating a first weight to the extra term; associating a second weight to one or more other terms in the first query; and scoring, based on the associated first weight and the associated second weight, the plurality of documents. | 0.685827 |
8,291,374 | 14 | 15 | 14. A method of altering a computer game program, comprising the steps of: providing existing source code for a computer game program; testing said existing source code for functionality to create tested source code; applying mark-up language to said tested source code to create application templates; creating abstracted representations of a possible set of changes for said tested source code; producing generalized implementations of source code changes using said application templates; mapping said generalized implementations to produce mapped sections of code; selectively transforming sections of code from said tested source code, said abstracted representations, said generalized implementations, and said mapped sections to produce new source code. | 14. A method of altering a computer game program, comprising the steps of: providing existing source code for a computer game program; testing said existing source code for functionality to create tested source code; applying mark-up language to said tested source code to create application templates; creating abstracted representations of a possible set of changes for said tested source code; producing generalized implementations of source code changes using said application templates; mapping said generalized implementations to produce mapped sections of code; selectively transforming sections of code from said tested source code, said abstracted representations, said generalized implementations, and said mapped sections to produce new source code. 15. The method according to claim 14 , further including the step of utilizing said application templates to map said generalized implementations to sections of said working source code. | 0.883166 |
9,760,562 | 11 | 14 | 11. A method for monitoring a synchronous computer-mediated communication in which a text transcript is generated by at least two chat participants including a first chat participant and a second chat participant, the method comprising: setting up and maintaining a synchronous computer-mediated communication system between a plurality of chat participants; checking for potential frustration including checking the text transcript for use of a text-based signal in a list of text-based signals; and taking a responsive action based at least in part upon a potential cause of the potential frustration determined by performing a text analytics analysis on the text transcript; wherein: at least the checking step is performed by computer software running on computer hardware; the responsive action is designed to alleviate frustration of the second chat participant; the list of text-based signals is recorded in a user-specific dictionary being customizable by the first chat participant to include participant-specific text-based signals corresponding to the second chat participant; and the user-specific dictionary being customizable to indicate a participant-specific potential frustration precondition corresponding to the second chat participant during a chat session between the first chat participant and the second chat participant. | 11. A method for monitoring a synchronous computer-mediated communication in which a text transcript is generated by at least two chat participants including a first chat participant and a second chat participant, the method comprising: setting up and maintaining a synchronous computer-mediated communication system between a plurality of chat participants; checking for potential frustration including checking the text transcript for use of a text-based signal in a list of text-based signals; and taking a responsive action based at least in part upon a potential cause of the potential frustration determined by performing a text analytics analysis on the text transcript; wherein: at least the checking step is performed by computer software running on computer hardware; the responsive action is designed to alleviate frustration of the second chat participant; the list of text-based signals is recorded in a user-specific dictionary being customizable by the first chat participant to include participant-specific text-based signals corresponding to the second chat participant; and the user-specific dictionary being customizable to indicate a participant-specific potential frustration precondition corresponding to the second chat participant during a chat session between the first chat participant and the second chat participant. 14. The method of claim 11 wherein the responsive action includes automatically, and under software control, taking direct action. | 0.902402 |
8,954,940 | 1 | 3 | 1. A computer-implemented method comprising: identifying, by one or more computing devices, software code text, wherein the software code text includes one or more preprocessor statements; translating, by the one or more computing devices, the software code text including the one or more preprocessor statements into a preprocessor output using, at least in part, one or more preprocessors associated with the software code text, the preprocessor output including one or more transformations of the one or more preprocessor statements into a set of expressions that represent intended functionality of the preprocessor statements and that are expressed using standard language and syntax of a relevant programming language of the software code text; identifying, by the one or more computing devices, the one or more transformations of the software code text, including one or more transformations of the one or more preprocessor statements, based upon, at least in part, comparing the preprocessor output with the software code text; identifying, by the one or more computing devices, one or more locations in the software code text associated with the one or more transformations, based upon, at least in part, comparing the preprocessor output with the software code text; and parsing the software code text, by the one or more computing devices, based upon, at least in part, lexing the software code text to generate an integrated token stream model, wherein the integrated token stream model includes a representation of a first token stream representing the software code text and one or more representations of one or more other token streams representing the one or more transformations of the software code text. | 1. A computer-implemented method comprising: identifying, by one or more computing devices, software code text, wherein the software code text includes one or more preprocessor statements; translating, by the one or more computing devices, the software code text including the one or more preprocessor statements into a preprocessor output using, at least in part, one or more preprocessors associated with the software code text, the preprocessor output including one or more transformations of the one or more preprocessor statements into a set of expressions that represent intended functionality of the preprocessor statements and that are expressed using standard language and syntax of a relevant programming language of the software code text; identifying, by the one or more computing devices, the one or more transformations of the software code text, including one or more transformations of the one or more preprocessor statements, based upon, at least in part, comparing the preprocessor output with the software code text; identifying, by the one or more computing devices, one or more locations in the software code text associated with the one or more transformations, based upon, at least in part, comparing the preprocessor output with the software code text; and parsing the software code text, by the one or more computing devices, based upon, at least in part, lexing the software code text to generate an integrated token stream model, wherein the integrated token stream model includes a representation of a first token stream representing the software code text and one or more representations of one or more other token streams representing the one or more transformations of the software code text. 3. The method of claim 1 wherein parsing the software code text comprises: generating a representative model of the software code text based upon, at least in part, the integrated token stream model, wherein the representative model represents one or more syntactic structures associated with the preprocessor output and wherein the one or more syntactic structures are mapped, based upon, at least in part, the integrated token stream model, to one or more corresponding locations in the software code text. | 0.691373 |
8,892,423 | 1 | 5 | 1. A computer-implemented method for generating examples for electronic dictionaries to serve as an aid to translation between languages performed by one or more processors, the method comprising: creating an electronic dictionary example by: acquiring at least one dictionary entry comprising a headword W j in a source language and at least one translation T j1 , T j2 , . . . T jn for the headword W j in a target language; generating a first set comprising possible forms for the headword W j in the source language and a second set comprising possible forms for each translation T j1 , T j2 , . . . T jn in the target language; searching a corpus of translations, where the corpus of translations is a preexisting corpus of translation sentence pairs, each translation sentence pair comprising a first sentence in the source language and a second sentence in the target language, where the first sentence is a translation of the second sentence, and the searching includes searching at least one first sentence in the source language included in the corpus of translations and searching at least one second sentence in the target language in the corpus of translations; identifying in the corpus of translations at least one translation sentence pair, from either the searching of the at least one first sentence in the source language or the searching of the at least one second sentence in the target language, that consists of the first sentence that incorporates the headword W j , or one of its generated forms, and the second sentence that incorporates the translation T jn or one of its generated forms; and providing the at least one translation sentence pair to a user. | 1. A computer-implemented method for generating examples for electronic dictionaries to serve as an aid to translation between languages performed by one or more processors, the method comprising: creating an electronic dictionary example by: acquiring at least one dictionary entry comprising a headword W j in a source language and at least one translation T j1 , T j2 , . . . T jn for the headword W j in a target language; generating a first set comprising possible forms for the headword W j in the source language and a second set comprising possible forms for each translation T j1 , T j2 , . . . T jn in the target language; searching a corpus of translations, where the corpus of translations is a preexisting corpus of translation sentence pairs, each translation sentence pair comprising a first sentence in the source language and a second sentence in the target language, where the first sentence is a translation of the second sentence, and the searching includes searching at least one first sentence in the source language included in the corpus of translations and searching at least one second sentence in the target language in the corpus of translations; identifying in the corpus of translations at least one translation sentence pair, from either the searching of the at least one first sentence in the source language or the searching of the at least one second sentence in the target language, that consists of the first sentence that incorporates the headword W j , or one of its generated forms, and the second sentence that incorporates the translation T jn or one of its generated forms; and providing the at least one translation sentence pair to a user. 5. The computer-implemented method of claim 1 , wherein the method is performed for each dictionary entry of a bilingual or multilingual dictionary. | 0.813602 |
7,593,846 | 7 | 8 | 7. The method of claim 6 wherein providing the set of semantic solutions comprises ranking the semantic solutions relative to each other. | 7. The method of claim 6 wherein providing the set of semantic solutions comprises ranking the semantic solutions relative to each other. 8. The method of claim 7 wherein ranking is based on the extent of the input text present in each semantic solution. | 0.960705 |
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