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9,549,227 | 1 | 2 | 1. A method comprising: by one or more computer systems of a social-networking system, providing social content for display in a mobile application running on a mobile device of a user of the social-networking system, the mobile application configured to display an interface for selecting media content to view on a display device of the user that is separate from the mobile device, wherein: the social content is determined from a social graph of the social-networking system, the social graph comprising a plurality of nodes and edges connecting the nodes, the nodes and edges comprising: device nodes that each correspond to a respective mobile device; user nodes that are each associated with a particular user of the social-networking system; concept nodes that are each associated with particular media content; and a plurality of ownership edges connecting the user nodes and the device nodes, each particular ownership edge indicating that a particular user corresponding to a particular user node owns a particular device corresponding to a particular device node; the mobile device of the user is determined by analyzing the device nodes and the ownership edges of the social graph; and the interface of the mobile application is configured to display, proximate to each particular media content that is displayed for selection, particular social content that is connected to both the user and the particular media content in the social graph, the particular social content comprising: an identification of at least one friend of the user who has previously liked the particular media content; and an identification of at least one friend of the user who is currently watching the particular media content; by the one or more computer systems of the social-networking system, receiving an indication from the mobile application that an option to view particular media content has been selected by the user using the interface of the mobile application running on the mobile device; and by the one or more computer systems of the social-networking system, in response to the selection by the user on the mobile device, providing one or more instructions to display the selected particular media content on the display device of the user that is separate from the mobile device. | 1. A method comprising: by one or more computer systems of a social-networking system, providing social content for display in a mobile application running on a mobile device of a user of the social-networking system, the mobile application configured to display an interface for selecting media content to view on a display device of the user that is separate from the mobile device, wherein: the social content is determined from a social graph of the social-networking system, the social graph comprising a plurality of nodes and edges connecting the nodes, the nodes and edges comprising: device nodes that each correspond to a respective mobile device; user nodes that are each associated with a particular user of the social-networking system; concept nodes that are each associated with particular media content; and a plurality of ownership edges connecting the user nodes and the device nodes, each particular ownership edge indicating that a particular user corresponding to a particular user node owns a particular device corresponding to a particular device node; the mobile device of the user is determined by analyzing the device nodes and the ownership edges of the social graph; and the interface of the mobile application is configured to display, proximate to each particular media content that is displayed for selection, particular social content that is connected to both the user and the particular media content in the social graph, the particular social content comprising: an identification of at least one friend of the user who has previously liked the particular media content; and an identification of at least one friend of the user who is currently watching the particular media content; by the one or more computer systems of the social-networking system, receiving an indication from the mobile application that an option to view particular media content has been selected by the user using the interface of the mobile application running on the mobile device; and by the one or more computer systems of the social-networking system, in response to the selection by the user on the mobile device, providing one or more instructions to display the selected particular media content on the display device of the user that is separate from the mobile device. 2. The method of claim 1 , wherein the one or more computer systems comprise a dongle of the social-networking system, the dongle comprising: a first interface operable to communicate with a content source; a second interface operable to communicate with the display device; and one or more transceivers operable to communicate with the social-networking system and the mobile device. | 0.550351 |
9,489,374 | 2 | 3 | 2. The computer readable storage medium according to claim 1 , wherein the program causes the computer to perform further operations comprising: receiving a transmit instruction to transmit text to another information processing apparatus; and when the transmit instruction is received, transmitting, to the other information processing apparatus, transmission data that contains text that only includes the fixed character string. | 2. The computer readable storage medium according to claim 1 , wherein the program causes the computer to perform further operations comprising: receiving a transmit instruction to transmit text to another information processing apparatus; and when the transmit instruction is received, transmitting, to the other information processing apparatus, transmission data that contains text that only includes the fixed character string. 3. The computer readable storage medium according to claim 2 , wherein the received one or more characters is stored in the storage as one or more unfixed characters, and the program causes the computer to perform further operations comprising: when the transmit instruction is received, deleting the one or more unfixed characters from the storage prior to transmitting the transmission data. | 0.5 |
6,137,906 | 3 | 4 | 3. The computer program as recited in conjunction with claim 2 wherein if the coordinate is determined to be to the left of the at least one word's right side, the program chooses the at least one word of the line. | 3. The computer program as recited in conjunction with claim 2 wherein if the coordinate is determined to be to the left of the at least one word's right side, the program chooses the at least one word of the line. 4. The computer program as recited in conjunction with claim 3 wherein the program includes instructions that causes the computer to: determine whether the coordinate is to the left of the at least one word's right side, and if it is determined not to be at the left, select the next word on the line to determine whether the next word is to the left of the line. | 0.5 |
8,594,023 | 1 | 7 | 1. A method comprising: receiving information about an expected use of a spectrum band in a radio frequency spectrum, the expected use by a primary user and the receiving at a mobile device; classifying the expected use of the spectrum band into at least two working modes, the classifying responsive to the information about the expected use; sensing the spectrum band to determine a current access pattern of the primary user; selecting one of the working modes as a current working mode of the primary user, the selecting responsive to the classifying and to the current access pattern of the primary user; scheduling transmissions on the spectrum band using a current schedule that is responsive to the current working mode of the primary user, the scheduling as a secondary user of the spectrum band; determining whether the current working mode of the primary user has changed; if the current working mode of the primary user has changed, re-performing the sensing, selecting, scheduling, and determining; and if the current working mode of the primary user has not changed, re-performing the scheduling and determining. | 1. A method comprising: receiving information about an expected use of a spectrum band in a radio frequency spectrum, the expected use by a primary user and the receiving at a mobile device; classifying the expected use of the spectrum band into at least two working modes, the classifying responsive to the information about the expected use; sensing the spectrum band to determine a current access pattern of the primary user; selecting one of the working modes as a current working mode of the primary user, the selecting responsive to the classifying and to the current access pattern of the primary user; scheduling transmissions on the spectrum band using a current schedule that is responsive to the current working mode of the primary user, the scheduling as a secondary user of the spectrum band; determining whether the current working mode of the primary user has changed; if the current working mode of the primary user has changed, re-performing the sensing, selecting, scheduling, and determining; and if the current working mode of the primary user has not changed, re-performing the scheduling and determining. 7. The method of claim 1 , wherein the receiving, classifying, sensing, and selecting are performed in response to the mobile device being powered on. | 0.776786 |
8,219,539 | 1 | 3 | 1. A computer-implemented method for returning temporally aware results for a query, comprising: identifying a first set of results for a query, the first set of results non-temporally based; classifying whether the query is temporally based by inputting one or more features of the query into a trained classifier to assign a classification to the query; if the query is classified as temporally based, determining an alternate set of results for the query different than the first set of results; and updating the classification based upon user interaction with the alternate set of results, comprising: representing the one or more features of the query as a vector of coordinates in feature space, the vector of coordinates assigned a temporally based label if the query is classified as temporally based; and if the user interaction with the alternate set of results indicates the query is non-temporally based and the vector of coordinates is assigned the temporally based label, then: modifying the temporally based label assigned to the vector of coordinates to a non-temporally based label; and updating a margin separating a temporally-based query region and a non-temporally based query region in the feature space, at least some of at least one of the identifying, the classifying, the determining, and the updating the classification implemented at least in part via a processor. | 1. A computer-implemented method for returning temporally aware results for a query, comprising: identifying a first set of results for a query, the first set of results non-temporally based; classifying whether the query is temporally based by inputting one or more features of the query into a trained classifier to assign a classification to the query; if the query is classified as temporally based, determining an alternate set of results for the query different than the first set of results; and updating the classification based upon user interaction with the alternate set of results, comprising: representing the one or more features of the query as a vector of coordinates in feature space, the vector of coordinates assigned a temporally based label if the query is classified as temporally based; and if the user interaction with the alternate set of results indicates the query is non-temporally based and the vector of coordinates is assigned the temporally based label, then: modifying the temporally based label assigned to the vector of coordinates to a non-temporally based label; and updating a margin separating a temporally-based query region and a non-temporally based query region in the feature space, at least some of at least one of the identifying, the classifying, the determining, and the updating the classification implemented at least in part via a processor. 3. The method of claim 1 , comprising: assigning the non-temporally based label to the vector of coordinates if the vector of coordinates is within the non-temporally based query region of the feature space. | 0.847794 |
7,882,437 | 3 | 5 | 3. The method of claim 2 wherein: listing the at least one presentation document includes storing a location of the presentation document in the data structure representing a presentation; and storing each presentation grammar includes retrieving a presentation grammar of the presentation document in dependence upon the location of the presentation document. | 3. The method of claim 2 wherein: listing the at least one presentation document includes storing a location of the presentation document in the data structure representing a presentation; and storing each presentation grammar includes retrieving a presentation grammar of the presentation document in dependence upon the location of the presentation document. 5. The method of claim 3 wherein: the presentation document comprises an instance of an object oriented class on a content server, the presentation document having a presentation document name; the presentation grammar comprises a member data element of the instance; storing a location of the presentation document in the data structure representing a presentation includes storing the presentation document name and a network location of the content server; and retrieving a presentation grammar further comprises: requesting the presentation grammar from the content server, including communicating the presentation document name as a request parameter; and receiving the presentation grammar in response from the content server. | 0.5 |
6,023,691 | 11 | 16 | 11. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a component that includes data, calculations required for the simulation and communication information to provide a goal based educational environment, comprising: (a) a code segment that accesses the information in the component of the rule-based expert system to retrieve presentation information indicative of a goal; (b) a code segment that utilizes the information in the component of the rule-based expert system to integrate goal-based learning information in a structured, dynamic business simulation designed by a profiling component to motivate accomplishment of the goal; (c) a code segment that monitors answers to questions posed to evaluate progress toward the goal utilizing the component of the rule-based expert system and that provides goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages that further motivates accomplishment of the goal; and (d) a code segment that analyzes progress towards the goal and stores student progress in memory. | 11. A computer program embodied on a computer-readable medium that creates a business simulation utilizing a rule-based expert system with a component that includes data, calculations required for the simulation and communication information to provide a goal based educational environment, comprising: (a) a code segment that accesses the information in the component of the rule-based expert system to retrieve presentation information indicative of a goal; (b) a code segment that utilizes the information in the component of the rule-based expert system to integrate goal-based learning information in a structured, dynamic business simulation designed by a profiling component to motivate accomplishment of the goal; (c) a code segment that monitors answers to questions posed to evaluate progress toward the goal utilizing the component of the rule-based expert system and that provides goal-based, remediation learning information feedback from a remediation object component including a knowledge system and a software tutor comprising an artificial intelligence engine which generates individualized coaching messages that further motivates accomplishment of the goal; and (d) a code segment that analyzes progress towards the goal and stores student progress in memory. 16. A computer program embodied on a computer-readable medium as recited in claim 11, including a code segment that organizes the simulation into states and utilizes the states to alter the simulation. | 0.598 |
8,347,266 | 1 | 2 | 1. A system comprising: a memory that stores code associated with a computer program; and a component coupled to the memory, the component configured to access the code, to identify a variable in the code and a modifier associated with the variable, the modifier designating that the variable is to be used for determining the identity of an object associated with the variable and for determining whether the object is equal to another object based on value semantics, and, responsive to identifying the variable and the modifier associated with the variable, to use the variable to determine the identity of the object associated with the variable and to determine whether the object is equal to the other object based on value semantics, the component being configured to use the variable to determine the identity of the object and to determine whether the object is equal to the other object based on value semantics by automatically overriding an Equals virtual method and a GetHashCode virtual method such that the overridden Equals virtual method and the overridden GetHashCode virtual method are implemented using the variable and satisfy a required contract associated with the virtual methods. | 1. A system comprising: a memory that stores code associated with a computer program; and a component coupled to the memory, the component configured to access the code, to identify a variable in the code and a modifier associated with the variable, the modifier designating that the variable is to be used for determining the identity of an object associated with the variable and for determining whether the object is equal to another object based on value semantics, and, responsive to identifying the variable and the modifier associated with the variable, to use the variable to determine the identity of the object associated with the variable and to determine whether the object is equal to the other object based on value semantics, the component being configured to use the variable to determine the identity of the object and to determine whether the object is equal to the other object based on value semantics by automatically overriding an Equals virtual method and a GetHashCode virtual method such that the overridden Equals virtual method and the overridden GetHashCode virtual method are implemented using the variable and satisfy a required contract associated with the virtual methods. 2. The system of claim 1 , wherein the component is configured to identify a class declaration in the code that includes the variable and the modifier associated with the variable. | 0.5 |
8,065,605 | 1 | 11 | 1. A system comprising: a user interface device; and one or more server computers operable to interact with the user interface device and to: apply a pre-defined rule set to a plurality of versions of a first document in a plurality of structured documents to extract one or more index values, the pre-defined rule set including a plurality of rules, each rule having a distinct rule identifier, each extracted index value being extracted by a rule in the pre-defined rule set, wherein one or more versions of the first document is concurrently accessible to a plurality of users for collaborative authoring; and for each extracted index value, store in an index-value data structure the extracted index-value, the rule identifier of the rule that extracted the index value, and information identifying the first document and the respective version of the first document from which the index-value was extracted. | 1. A system comprising: a user interface device; and one or more server computers operable to interact with the user interface device and to: apply a pre-defined rule set to a plurality of versions of a first document in a plurality of structured documents to extract one or more index values, the pre-defined rule set including a plurality of rules, each rule having a distinct rule identifier, each extracted index value being extracted by a rule in the pre-defined rule set, wherein one or more versions of the first document is concurrently accessible to a plurality of users for collaborative authoring; and for each extracted index value, store in an index-value data structure the extracted index-value, the rule identifier of the rule that extracted the index value, and information identifying the first document and the respective version of the first document from which the index-value was extracted. 11. The system of claim 1 , wherein the one or more server computers are further operable to: identify a plurality of additional documents in the plurality of structured documents; and repeat the applying and the storing for each of the plurality of additional documents. | 0.5 |
8,358,703 | 21 | 22 | 21. A method comprising: accessing, without initially decoding, an arithmetically coded bitstream that includes at least a first coded portion and a second coded portion, wherein the first coded portion and the second coded portion have been coded with a code having memory, such that decoding the second coded portion relies on an output from decoding the first coded portion; and replacing the first coded portion with a replacement arithmetically coded portion to produce a modified coded bitstream for which a decoding of the second coded portion will produce a common result based on either an output from decoding the first coded portion or an output from decoding the replacement arithmetically coded portion, wherein the replacement arithmetically coded portion generates a Context-based Adaptive Binary Arithmetic Coding (CABAC) state value that is the same as a CABAC state value generated by the first coded portion. | 21. A method comprising: accessing, without initially decoding, an arithmetically coded bitstream that includes at least a first coded portion and a second coded portion, wherein the first coded portion and the second coded portion have been coded with a code having memory, such that decoding the second coded portion relies on an output from decoding the first coded portion; and replacing the first coded portion with a replacement arithmetically coded portion to produce a modified coded bitstream for which a decoding of the second coded portion will produce a common result based on either an output from decoding the first coded portion or an output from decoding the replacement arithmetically coded portion, wherein the replacement arithmetically coded portion generates a Context-based Adaptive Binary Arithmetic Coding (CABAC) state value that is the same as a CABAC state value generated by the first coded portion. 22. The method of claim 21 further comprising: accessing an indicator of a location of the first coded portion. | 0.899091 |
8,612,369 | 1 | 12 | 1. A computer-implemented method to apply a query to a set of documents, comprising: by a computer: reconstructing a document term matrix XεR N×M where N is a number of documents and M is a number of words, by minimizing reconstruction errors with min ∥X−UA∥, where A is a fixed projection matrix and U is a column orthogonal matrix; determining a loss function and parameter gradients to generate U; fixing U while determining the loss function and sparse regularization constraints on the projection matrix A; generating parameter coefficients and generating a sparse projection matrix A; and generating a Sparse Latent Semantic Analysis (Sparse SLA) model and applying the model to a set of documents and displaying documents matching a query. | 1. A computer-implemented method to apply a query to a set of documents, comprising: by a computer: reconstructing a document term matrix XεR N×M where N is a number of documents and M is a number of words, by minimizing reconstruction errors with min ∥X−UA∥, where A is a fixed projection matrix and U is a column orthogonal matrix; determining a loss function and parameter gradients to generate U; fixing U while determining the loss function and sparse regularization constraints on the projection matrix A; generating parameter coefficients and generating a sparse projection matrix A; and generating a Sparse Latent Semantic Analysis (Sparse SLA) model and applying the model to a set of documents and displaying documents matching a query. 12. The method of claim 1 , comprising projecting X onto a latent space V=XA T . | 0.904306 |
9,875,298 | 6 | 8 | 6. The method of claim 4 , wherein said at least one operation comprises determining whether said second portion is associated with a predetermined part of speech, and wherein said generating is performed responsive to determining that said second portion is associated with said predetermined part of speech. | 6. The method of claim 4 , wherein said at least one operation comprises determining whether said second portion is associated with a predetermined part of speech, and wherein said generating is performed responsive to determining that said second portion is associated with said predetermined part of speech. 8. The method of claim 6 , wherein said second search query is free of said first portion and said second portion. | 0.683333 |
8,266,153 | 2 | 3 | 2. The computer program product of claim 1 wherein the set of objects is deployed to an application server framework, and the set of metadata sources are within the application server framework. | 2. The computer program product of claim 1 wherein the set of objects is deployed to an application server framework, and the set of metadata sources are within the application server framework. 3. The computer program product of claim 2 wherein the application server framework is a J2EE framework, and the set of metadata sources comprises database descriptors, application data framework (ADF) entity descriptors, runtime configuration descriptors, and source code. | 0.5 |
9,282,289 | 18 | 20 | 18. A non-transitory computer-readable medium comprising computer-readable instructions thereon for generating a summary document of an online meeting, the computer-readable medium comprising: instructions to store, in computer memory, at least a portion of screen data representing a previously presented portion of an ongoing online meeting; instructions to capture a plurality of screenshots in response to trigger events, each screenshot i) being based at least in part on the stored screen data and ii) being representable as an image thumbnail, and wherein the instructions to capture the plurality of screenshots are operable to capture each screenshot of the screen data by, at least in part, associating a timestamp with the screenshot, the timestamp indicating a point in time in the previously presented portion of the meeting; instructions to combine the plurality of screenshots, thereby dynamically generating a summary document summarizing the ongoing online meeting, wherein the image thumbnails representing the plurality of screenshots are for facilitating navigating through the summary document while the ongoing online meeting is still ongoing; and instructions to signal for presenting, at a viewer computing device attending the meeting, simultaneously and while the ongoing online meeting is still ongoing, first screen data corresponding to a currently presented portion of the ongoing online meeting and second screen data corresponding to one of the plurality of screenshots in the summary document, wherein the second screen data includes stored screen data from a previously presented portion of the ongoing online meeting, wherein the first screen data is presented picture-in-picture inside the second screen data or the second screen data is presented picture-in-picture inside the first screen data, wherein presenting the first screen data corresponding to the currently presented portion of the ongoing online meeting includes presenting live screen and audio data of the ongoing online meeting, and wherein presenting the second screen data corresponding to the screenshot includes displaying screen data from the previously presented portion of the online meeting corresponding to the point in time in the previously presented portion of the meeting indicated by the timestamp associated with the one of the plurality of screenshots in the summary document. | 18. A non-transitory computer-readable medium comprising computer-readable instructions thereon for generating a summary document of an online meeting, the computer-readable medium comprising: instructions to store, in computer memory, at least a portion of screen data representing a previously presented portion of an ongoing online meeting; instructions to capture a plurality of screenshots in response to trigger events, each screenshot i) being based at least in part on the stored screen data and ii) being representable as an image thumbnail, and wherein the instructions to capture the plurality of screenshots are operable to capture each screenshot of the screen data by, at least in part, associating a timestamp with the screenshot, the timestamp indicating a point in time in the previously presented portion of the meeting; instructions to combine the plurality of screenshots, thereby dynamically generating a summary document summarizing the ongoing online meeting, wherein the image thumbnails representing the plurality of screenshots are for facilitating navigating through the summary document while the ongoing online meeting is still ongoing; and instructions to signal for presenting, at a viewer computing device attending the meeting, simultaneously and while the ongoing online meeting is still ongoing, first screen data corresponding to a currently presented portion of the ongoing online meeting and second screen data corresponding to one of the plurality of screenshots in the summary document, wherein the second screen data includes stored screen data from a previously presented portion of the ongoing online meeting, wherein the first screen data is presented picture-in-picture inside the second screen data or the second screen data is presented picture-in-picture inside the first screen data, wherein presenting the first screen data corresponding to the currently presented portion of the ongoing online meeting includes presenting live screen and audio data of the ongoing online meeting, and wherein presenting the second screen data corresponding to the screenshot includes displaying screen data from the previously presented portion of the online meeting corresponding to the point in time in the previously presented portion of the meeting indicated by the timestamp associated with the one of the plurality of screenshots in the summary document. 20. The computer-readable medium of claim 18 , further comprising: instructions to receive an annotation from the viewer computing device attending the meeting; and instructions to add the annotation to the summary document. | 0.5 |
8,725,756 | 9 | 10 | 9. The method of claim 1 , further comprising: initiating the current search session in response to receiving the first search query from the user device, the current search session being associated with the user device; and determining that the additional search query was received during the current search session based, at least in part, on the additional search query being received from the user device. | 9. The method of claim 1 , further comprising: initiating the current search session in response to receiving the first search query from the user device, the current search session being associated with the user device; and determining that the additional search query was received during the current search session based, at least in part, on the additional search query being received from the user device. 10. The method of claim 9 , wherein determining that the additional search query was received during the current search session comprises determining that the additional search query was received from the user device within a threshold period of time after receipt of the first search query from the user device. | 0.790885 |
7,774,386 | 5 | 6 | 5. A computer-implemented method of applying abstraction by a validating parser, comprising: using, by a validating parser, a first schema definition for validating syntax elements when parsing syntax of an input document, wherein the first schema definition is identified in the input document; and omitting, by the validating parser when generating output from the parsed syntax of the input document, each of at least one of the validated syntax elements which is valid according to the first schema definition but is not valid according to a second schema definition for which the output is generated, wherein: the first schema definition is an extended schema; the second schema definition is a base schema from which the extended schema is extended, such that the extended schema defines at least one syntax element that is not defined in the base schema; and the second schema definition is dynamically requested, to the validating parser, by an application program for which the output is being generated. | 5. A computer-implemented method of applying abstraction by a validating parser, comprising: using, by a validating parser, a first schema definition for validating syntax elements when parsing syntax of an input document, wherein the first schema definition is identified in the input document; and omitting, by the validating parser when generating output from the parsed syntax of the input document, each of at least one of the validated syntax elements which is valid according to the first schema definition but is not valid according to a second schema definition for which the output is generated, wherein: the first schema definition is an extended schema; the second schema definition is a base schema from which the extended schema is extended, such that the extended schema defines at least one syntax element that is not defined in the base schema; and the second schema definition is dynamically requested, to the validating parser, by an application program for which the output is being generated. 6. The method according to claim 5 , wherein the input document is a structured document. | 0.914587 |
8,606,778 | 2 | 3 | 2. The method of claim 1 , where the tree structure includes a hierarchical tag markup structure of HyperText Markup Language (HTML) code. | 2. The method of claim 1 , where the tree structure includes a hierarchical tag markup structure of HyperText Markup Language (HTML) code. 3. The method of claim 2 , where the one or more tags include a line break tag and a bold tag, the line break tag and the bold tag being repeated for each item, of the plurality of items, in the HTML code. | 0.5 |
8,862,602 | 11 | 19 | 11. A computer-implemented method comprising: receiving a search query at a processing circuit from a client device, the search query comprising a text string; parsing the search query at the processing circuit using parsing criteria based on one or more dictionaries to determine keywords associated with the search query, wherein the keywords associated with the search query include one or more portions of the text string searching a database using the keywords associated with the search query to obtain a search result comprising a universal resource locator; identifying a plurality of the keywords in the universal resource locator; modifying the universal resource locator by inserting previously non-existing space between at least two of the plurality of identified keywords in the universal resource locator; generating display data comprising the modified universal resource locator having the plurality of identified keywords and the inserted space therebetween; and sending the display data to the client device; wherein inserting the space in the universal resource locator comprises inserting a HTML tar between characters of the universal resource locator before sending the display data to the client device, wherein the HTML tag comprises at least one of a div tag, an italics tag, and a span tag. | 11. A computer-implemented method comprising: receiving a search query at a processing circuit from a client device, the search query comprising a text string; parsing the search query at the processing circuit using parsing criteria based on one or more dictionaries to determine keywords associated with the search query, wherein the keywords associated with the search query include one or more portions of the text string searching a database using the keywords associated with the search query to obtain a search result comprising a universal resource locator; identifying a plurality of the keywords in the universal resource locator; modifying the universal resource locator by inserting previously non-existing space between at least two of the plurality of identified keywords in the universal resource locator; generating display data comprising the modified universal resource locator having the plurality of identified keywords and the inserted space therebetween; and sending the display data to the client device; wherein inserting the space in the universal resource locator comprises inserting a HTML tar between characters of the universal resource locator before sending the display data to the client device, wherein the HTML tag comprises at least one of a div tag, an italics tag, and a span tag. 19. The method of claim 11 , wherein the display data comprises selectable characters which can be pasted into a web browser. | 0.794408 |
8,775,409 | 16 | 23 | 16. A computer-readable medium storing software having thereon instructions, which, when executed by one or more computers, cause the one or more computers to perform operations of: receiving a request to identify trending search queries in a search system; grouping a plurality of search queries into a plurality of clusters of search queries; associating each cluster of search queries with a respective representative category; determining, by one or more computers and for each cluster of search queries, a cluster score based on a cluster performance score or a category popularity score, wherein the category popularity score of a particular category is a score whose value correlates with the number of clusters associated with the particular category, and wherein the cluster performance score of a particular cluster is a score whose value correlates with a respective rank of one or more pages that are identified for one or more of search queries that are grouped into the particular cluster; generating a ranking of the clusters of search queries based on the cluster scores; and presenting, as a representation of the trending search queries in the search system, information identifying a subset of the clusters of search queries as ranked according to the ranking. | 16. A computer-readable medium storing software having thereon instructions, which, when executed by one or more computers, cause the one or more computers to perform operations of: receiving a request to identify trending search queries in a search system; grouping a plurality of search queries into a plurality of clusters of search queries; associating each cluster of search queries with a respective representative category; determining, by one or more computers and for each cluster of search queries, a cluster score based on a cluster performance score or a category popularity score, wherein the category popularity score of a particular category is a score whose value correlates with the number of clusters associated with the particular category, and wherein the cluster performance score of a particular cluster is a score whose value correlates with a respective rank of one or more pages that are identified for one or more of search queries that are grouped into the particular cluster; generating a ranking of the clusters of search queries based on the cluster scores; and presenting, as a representation of the trending search queries in the search system, information identifying a subset of the clusters of search queries as ranked according to the ranking. 23. The computer-readable medium of claim 16 , wherein associating each cluster of search queries with a respective representative category further comprises: for each cluster: associating each search query in the cluster with one or more categories based on a respective set of result documents responsive to the search query; and associating the cluster with a respective representative category based on the category associations of the cluster's search queries. | 0.5 |
9,483,500 | 2 | 11 | 2. A method to display landmark information comprising: receiving, by one or more computers, a user query; identifying one or more trigger words in the user query; selecting one or more tags from a landmark database, the tags corresponding to the one or more trigger words; supplementing the user query with the one or more tags to generate a supplemented user query; retrieving, based on the supplemented user query, one or more visual clusters of landmark images; generating a user interface including the one or more visual clusters of retrieved landmark images; and causing one or more summary lists of visual clusters of landmark images to be displayed on the user interface, wherein each of the one or more summary lists includes descriptive information and access information for each visual cluster in the one or more summary lists displayed. | 2. A method to display landmark information comprising: receiving, by one or more computers, a user query; identifying one or more trigger words in the user query; selecting one or more tags from a landmark database, the tags corresponding to the one or more trigger words; supplementing the user query with the one or more tags to generate a supplemented user query; retrieving, based on the supplemented user query, one or more visual clusters of landmark images; generating a user interface including the one or more visual clusters of retrieved landmark images; and causing one or more summary lists of visual clusters of landmark images to be displayed on the user interface, wherein each of the one or more summary lists includes descriptive information and access information for each visual cluster in the one or more summary lists displayed. 11. The method of claim 2 , further comprising providing a user interface element to receive user input corresponding to each visual cluster. | 0.818299 |
8,594,468 | 9 | 11 | 9. A computer readable storage device comprising computer executable instructions that when executed by one or more processors cause one or more computing devices to perform a method comprising: compiling visual information and textual information from a plurality of images; extracting the visual information from the plurality of images by using a gray block methodology; reducing the visual information by employing a projection matrix; hashing the reduced visual information; clustering the plurality of images based at least in part on a hash value to create image clusters; building one or more statistical language models based at least in part on the image clusters; and annotating a personal image by selecting words with a maximum joint probability with the personal image. | 9. A computer readable storage device comprising computer executable instructions that when executed by one or more processors cause one or more computing devices to perform a method comprising: compiling visual information and textual information from a plurality of images; extracting the visual information from the plurality of images by using a gray block methodology; reducing the visual information by employing a projection matrix; hashing the reduced visual information; clustering the plurality of images based at least in part on a hash value to create image clusters; building one or more statistical language models based at least in part on the image clusters; and annotating a personal image by selecting words with a maximum joint probability with the personal image. 11. A computer readable storage device as recited in claim 9 , wherein the plurality of images with a same hash value are grouped into a same image cluster. | 0.780899 |
8,738,666 | 1 | 2 | 1. A computer processor implemented method for the correlation of conceptual and relational information, comprising: receiving structure information relating to metadata types from a user, by receiving a type of metadata to manage from the user, displaying at least one field corresponding to the type of metadata to the user, and receiving information from the user for entry into said at least one field; receiving context information to establish context for the correlation of conceptual and relational information from said user, by receiving a selection of an existing item of context information or a new item of context information from the user, receiving a selection of an existing source or item of content or a new source or item of content associated with the context information from the user, and an association between at least one item of context information and at least one source or item of content from the user; receiving ontology information for the correlation of conceptual and relational information from said user, by receiving a selection of an existing item of ontology information or a new item of ontology information from the user and an association between at least one item of ontology information and at least one item of context information; receiving concept information for the correlation of conceptual and relational information from said user, by receiving a selection of a concept type and corresponding concept from the user, displaying a plurality of attributes associable with the concept, and receiving information from the user corresponding to the plurality of attributes; recording relationships between conceptual and relational information, by receiving a selection of a concept from the user, receiving a selection of an ontology information from the user, displaying attributes associated with the concept to the user, displaying associations associated with the ontology information to the user, and receiving selections of concepts, ontology information, attributes, associations, or combinations thereof from the user to define said relationships; and displaying said relationships between conceptual and relational information to said user. | 1. A computer processor implemented method for the correlation of conceptual and relational information, comprising: receiving structure information relating to metadata types from a user, by receiving a type of metadata to manage from the user, displaying at least one field corresponding to the type of metadata to the user, and receiving information from the user for entry into said at least one field; receiving context information to establish context for the correlation of conceptual and relational information from said user, by receiving a selection of an existing item of context information or a new item of context information from the user, receiving a selection of an existing source or item of content or a new source or item of content associated with the context information from the user, and an association between at least one item of context information and at least one source or item of content from the user; receiving ontology information for the correlation of conceptual and relational information from said user, by receiving a selection of an existing item of ontology information or a new item of ontology information from the user and an association between at least one item of ontology information and at least one item of context information; receiving concept information for the correlation of conceptual and relational information from said user, by receiving a selection of a concept type and corresponding concept from the user, displaying a plurality of attributes associable with the concept, and receiving information from the user corresponding to the plurality of attributes; recording relationships between conceptual and relational information, by receiving a selection of a concept from the user, receiving a selection of an ontology information from the user, displaying attributes associated with the concept to the user, displaying associations associated with the ontology information to the user, and receiving selections of concepts, ontology information, attributes, associations, or combinations thereof from the user to define said relationships; and displaying said relationships between conceptual and relational information to said user. 2. The method of claim 1 , wherein the step of receiving structure information relating to metadata types from the user comprises receiving a selection of data previously entered or ingested into a non-transitory computer readable medium in communication with the computer processor. | 0.799859 |
8,508,787 | 10 | 16 | 10. A system for translating documents having a multifunctional printer machine, the system comprising: a processor; a computer-readable storage medium in communication with the processor, the computer-readable storage medium comprising one or more programming instructions for: capturing an image of a document; determining regions of the document captured that include original text; performing optical character recognition of the regions of the document captured that include the original text; determining a source language corresponding to the original text directly on the multifunctional printer machine; displaying a plurality of target languages on the multifunctional printer machine; receiving a selected target language from a user in response to the displaying the plurality of target languages on the multifunctional printer machine, wherein the selected target language is selected from the plurality of target languages; performing language translation of the regions of the document captured that include the original text into translated text in accordance with the source language and the selected target language; displaying a plurality of page layout templates on the multifunctional printer machine; receiving one or more page layout templates from the user in response to the displaying the plurality of page layout templates on the multifunctional printer machine, wherein the one or more page layout templates are selected from the plurality of page layout templates, the one or more page layout templates having multiple pre designated areas for receiving the original text and the translated text; and outputting one or more printouts in accordance with the one or more page layout templates, the one or more printouts comprising (i) the original text in the source language and (ii) the translated text in the selected target language. | 10. A system for translating documents having a multifunctional printer machine, the system comprising: a processor; a computer-readable storage medium in communication with the processor, the computer-readable storage medium comprising one or more programming instructions for: capturing an image of a document; determining regions of the document captured that include original text; performing optical character recognition of the regions of the document captured that include the original text; determining a source language corresponding to the original text directly on the multifunctional printer machine; displaying a plurality of target languages on the multifunctional printer machine; receiving a selected target language from a user in response to the displaying the plurality of target languages on the multifunctional printer machine, wherein the selected target language is selected from the plurality of target languages; performing language translation of the regions of the document captured that include the original text into translated text in accordance with the source language and the selected target language; displaying a plurality of page layout templates on the multifunctional printer machine; receiving one or more page layout templates from the user in response to the displaying the plurality of page layout templates on the multifunctional printer machine, wherein the one or more page layout templates are selected from the plurality of page layout templates, the one or more page layout templates having multiple pre designated areas for receiving the original text and the translated text; and outputting one or more printouts in accordance with the one or more page layout templates, the one or more printouts comprising (i) the original text in the source language and (ii) the translated text in the selected target language. 16. The system according to claim 10 , wherein performing language translation of the regions of the document captured comprises executing optical character recognition to select text portions of the document captured. | 0.70137 |
9,715,492 | 1 | 7 | 1. A method, determining a message sentiment, comprising: selecting, by a processor, a message; selecting, by the processor, a context associated with the selected message; determining, by the processor, a sentiment of the context; assigning, by the processor, the determined sentiment to the selected message; and wherein the determining the sentiment of the context further comprises, determining the sentiment in accord with an attribute of the context. | 1. A method, determining a message sentiment, comprising: selecting, by a processor, a message; selecting, by the processor, a context associated with the selected message; determining, by the processor, a sentiment of the context; assigning, by the processor, the determined sentiment to the selected message; and wherein the determining the sentiment of the context further comprises, determining the sentiment in accord with an attribute of the context. 7. The method of claim 1 , wherein the context is an implied endorsement by a viewer of the message. | 0.788136 |
9,607,030 | 1 | 12 | 1. A method, comprising: extracting, ranking, and annotating, by a processor, content in (i) one or more forms used on websites, (ii) a source code of open source software available in a source management system, and (iii) one or more existing data design projects that include mappings between logical data model objects and physical data model objects, the content selected from the group consisting of terms and abbreviations for the terms, wherein an extracted term is annotated using an abbreviation for the extracted term, and an extracted abbreviation is annotated using a term for the extracted abbreviation; storing, in a knowledge base, the content, respective annotations for the content, and respective ranks for the content; and given an input data structure that lacks identifiers of a given type for data objects therein, automatically generating, by the processor, suggested identifiers of the given type for the data objects based on the content, the respective annotations for the content, and the respective ranks for the content stored in the knowledge base, wherein the suggested identifiers of the given type are selected from the group consisting of the terms and the abbreviations for the terms. | 1. A method, comprising: extracting, ranking, and annotating, by a processor, content in (i) one or more forms used on websites, (ii) a source code of open source software available in a source management system, and (iii) one or more existing data design projects that include mappings between logical data model objects and physical data model objects, the content selected from the group consisting of terms and abbreviations for the terms, wherein an extracted term is annotated using an abbreviation for the extracted term, and an extracted abbreviation is annotated using a term for the extracted abbreviation; storing, in a knowledge base, the content, respective annotations for the content, and respective ranks for the content; and given an input data structure that lacks identifiers of a given type for data objects therein, automatically generating, by the processor, suggested identifiers of the given type for the data objects based on the content, the respective annotations for the content, and the respective ranks for the content stored in the knowledge base, wherein the suggested identifiers of the given type are selected from the group consisting of the terms and the abbreviations for the terms. 12. The method of claim 1 , further comprising forming existing projects triples to store in the knowledge base, where each of the existing projects triples includes (i) an abbreviation used in a physical data model, (ii) a term for the abbreviation used in a logical data model, and (iii) an occurrence value indicating a number of occurrences of the abbreviation in the physical data model. | 0.5 |
7,827,029 | 1 | 2 | 1. A method comprising the steps of: determining a user selected passage by highlighting, marking, or cut and pasting a block of text using a computer operable input device; determining user interest information; determining a parsing grammar and a generation grammar; determining a meaning structure based on the selected passage; transforming the user selected passage and the user interest information into condensation transformations comprised of rewrite rules which delete, merge and change elements of the meaning structure; determining meaning distortion constraints beyond which the meaning structure is identified as being distorted after the condensation transformations are applied; determining a packed meaning structure based on the selected passage and the determined parsing grammar; determining a reduced meaning structure based on the condensation transformations, the packed meaning structure, the user information, and the meaning distortion constraints; determining at least one candidate condensation structure based on the reduced meaning structure and a predictive model or a statistical disambiguation model; and determining a user-interest note based on the candidate condensation structures and the determined generation grammar. | 1. A method comprising the steps of: determining a user selected passage by highlighting, marking, or cut and pasting a block of text using a computer operable input device; determining user interest information; determining a parsing grammar and a generation grammar; determining a meaning structure based on the selected passage; transforming the user selected passage and the user interest information into condensation transformations comprised of rewrite rules which delete, merge and change elements of the meaning structure; determining meaning distortion constraints beyond which the meaning structure is identified as being distorted after the condensation transformations are applied; determining a packed meaning structure based on the selected passage and the determined parsing grammar; determining a reduced meaning structure based on the condensation transformations, the packed meaning structure, the user information, and the meaning distortion constraints; determining at least one candidate condensation structure based on the reduced meaning structure and a predictive model or a statistical disambiguation model; and determining a user-interest note based on the candidate condensation structures and the determined generation grammar. 2. The method of claim 1 , in which determining the note further comprises the step of prioritizing the retention of the elements of the passage that match elements of the user interest information. | 0.740157 |
8,504,353 | 1 | 4 | 1. A method of translating two languages using statistical machine translation (SMT) and a generalized asymmetric traveling salesman problem (GTSP) graph, comprising: defining a SMT problem as a GTSP; translating blocks of an input sentence using bi-phrases corresponding to nodes in a GTSP graph that represents the GTSP; solving the GTSP; and outputting the translated blocks in an order defined by the GTSP solution; and further comprising: generating an optimal tour of the GSTP graph; computing a true cost C t of the optimal tour; computing an apparent cost C a of the optimal tour; determining a difference D between a true cost C t and an apparent cost C a of the optimal tour; determining whether the difference D is less than a predetermined threshold ε; outputting the optimal tour as a solution to the GSTP if D is less than the predetermined threshold ε; and translating the input sentence from a first language to a second language using the output GSTP solution; wherein the true cost C t of the optimal tour is computed using n-gram costs, where n is an integer greater than or equal to 3. | 1. A method of translating two languages using statistical machine translation (SMT) and a generalized asymmetric traveling salesman problem (GTSP) graph, comprising: defining a SMT problem as a GTSP; translating blocks of an input sentence using bi-phrases corresponding to nodes in a GTSP graph that represents the GTSP; solving the GTSP; and outputting the translated blocks in an order defined by the GTSP solution; and further comprising: generating an optimal tour of the GSTP graph; computing a true cost C t of the optimal tour; computing an apparent cost C a of the optimal tour; determining a difference D between a true cost C t and an apparent cost C a of the optimal tour; determining whether the difference D is less than a predetermined threshold ε; outputting the optimal tour as a solution to the GSTP if D is less than the predetermined threshold ε; and translating the input sentence from a first language to a second language using the output GSTP solution; wherein the true cost C t of the optimal tour is computed using n-gram costs, where n is an integer greater than or equal to 3. 4. The method of claim 1 , further comprising: refining at least one node in the graph if D is greater than or equal to the predetermined threshold c, and generating a refined graph comprising the refined node; and iteratively computing the true cost C t and apparent cost C a for one or more refined graphs, determining the difference D there between, and comparing the difference D to the predetermined threshold ε until D is less than c. | 0.5 |
9,396,232 | 4 | 5 | 4. The method of claim 1 , wherein requesting at least one business grammar rule based on a user information associated with the user further comprises: querying at least one descriptive business grammar configured string based on the user information; extracting at least one token from the descriptive business grammar configured string; and accessing the at least one rule based on the at least one token. | 4. The method of claim 1 , wherein requesting at least one business grammar rule based on a user information associated with the user further comprises: querying at least one descriptive business grammar configured string based on the user information; extracting at least one token from the descriptive business grammar configured string; and accessing the at least one rule based on the at least one token. 5. The method of claim 4 , wherein the descriptive business grammar configured string comprises a department code. | 0.5 |
7,716,218 | 1 | 11 | 1. A method for enhanced tuning of search engine parameters to obtain at least one optimal search result, comprising: receiving a search parameter at a search engine equipped with a plurality of tunable knobs set at an initial setting; generating a search result for the search parameter based on the received search parameter and the initial setting of the plurality of tunable knobs, the search result including a plurality of result objects, each of the plurality of tunable knobs associated with a weighting factor; associating a relevancy score for each of the plurality of result objects generated by the search engine, the relevancy score associated with a tunable knob setting; presenting the result objects from the search result; identifying one or more of the presented result objects not selected over time, the non-selection of the result objects identifying the associated tunable knob settings; dynamically adjusting the relevancy score of the identified one or more result objects not selected over time; tuning the plurality of tunable knobs using one or more search algorithms to obtain an optimal search result, the tuning allowing adjustment of the tunable knobs based on the adjusted relevancy score and the non-selected result objects over time, wherein the relevancy score and the non-selected result objects identify the one or more tunable knob settings to be adjusted for obtaining an optimal search result; and further dynamically adjusting the previously dynamically adjusted one or more result objects not selected. | 1. A method for enhanced tuning of search engine parameters to obtain at least one optimal search result, comprising: receiving a search parameter at a search engine equipped with a plurality of tunable knobs set at an initial setting; generating a search result for the search parameter based on the received search parameter and the initial setting of the plurality of tunable knobs, the search result including a plurality of result objects, each of the plurality of tunable knobs associated with a weighting factor; associating a relevancy score for each of the plurality of result objects generated by the search engine, the relevancy score associated with a tunable knob setting; presenting the result objects from the search result; identifying one or more of the presented result objects not selected over time, the non-selection of the result objects identifying the associated tunable knob settings; dynamically adjusting the relevancy score of the identified one or more result objects not selected over time; tuning the plurality of tunable knobs using one or more search algorithms to obtain an optimal search result, the tuning allowing adjustment of the tunable knobs based on the adjusted relevancy score and the non-selected result objects over time, wherein the relevancy score and the non-selected result objects identify the one or more tunable knob settings to be adjusted for obtaining an optimal search result; and further dynamically adjusting the previously dynamically adjusted one or more result objects not selected. 11. The method for enhanced tuning of search engine parameters to obtain optimal search result of claim 1 , wherein tuning the plurality of tunable knobs is by choosing a plurality of tunable knobs at a time and adjusting the plurality of tunable knobs to obtain a more optimal search result. | 0.806878 |
10,142,708 | 18 | 24 | 18. A content delivery platform system, comprising: at least one processor-based component; and at least one nontransitory processor-readable medium communicatively coupled to the at least one processor-based component and which stores at least one of data or processor-executable instructions, that when executed by the at least one processor-based component, cause the at least one processor-based component to: for each presentation of each of a plurality of narratives to a user, an entirety each narrative comprised of a set of a plurality of narrative segments, at least two of the narrative segments of each of the narratives having a distinct temporal order within a time sequence of events of the respective narrative: cause a successive presentation of ones of the narrative segments of the respective narrative to the user; and prevent the presentation of entirety of the respective narrative to the user before all of the narrative segments of the respective narrative have been presented to the user at least until an occurrence of at least one social media sharing action. | 18. A content delivery platform system, comprising: at least one processor-based component; and at least one nontransitory processor-readable medium communicatively coupled to the at least one processor-based component and which stores at least one of data or processor-executable instructions, that when executed by the at least one processor-based component, cause the at least one processor-based component to: for each presentation of each of a plurality of narratives to a user, an entirety each narrative comprised of a set of a plurality of narrative segments, at least two of the narrative segments of each of the narratives having a distinct temporal order within a time sequence of events of the respective narrative: cause a successive presentation of ones of the narrative segments of the respective narrative to the user; and prevent the presentation of entirety of the respective narrative to the user before all of the narrative segments of the respective narrative have been presented to the user at least until an occurrence of at least one social media sharing action. 24. The system of claim 18 , where in the processor-executable instructions further cause the at least one processor-based component to: provide the user access to at least one piece of bonus material which was not otherwise available to the user responsive to the occurrence of the at least one social media sharing action. | 0.781081 |
8,326,826 | 24 | 59 | 24. A computer program product, encoded on a computer readable medium, operable to cause a data processing apparatus to perform operations comprising: selecting a candidate query in a query sequence stored in a query log, the query sequence including an initial query and one or more revised queries and defining an order in which the queries were submitted for a search session; selecting a revised query subsequent to the candidate query in the order; determining a quality score for the revised query; determining a navigation score for the revised query; and determining that the quality score for the revised query is greater than a quality score threshold and that the navigation score for the revised query is greater than a navigation score threshold, and in response: identifying a navigational resource for the revised query; and associating the navigational resource with the candidate query, the association specifying the navigational resource as being relevant to the candidate query in a search operation. | 24. A computer program product, encoded on a computer readable medium, operable to cause a data processing apparatus to perform operations comprising: selecting a candidate query in a query sequence stored in a query log, the query sequence including an initial query and one or more revised queries and defining an order in which the queries were submitted for a search session; selecting a revised query subsequent to the candidate query in the order; determining a quality score for the revised query; determining a navigation score for the revised query; and determining that the quality score for the revised query is greater than a quality score threshold and that the navigation score for the revised query is greater than a navigation score threshold, and in response: identifying a navigational resource for the revised query; and associating the navigational resource with the candidate query, the association specifying the navigational resource as being relevant to the candidate query in a search operation. 59. The computer program product of claim 24 , wherein the search operation, responsive to receiving an input query, generates a corresponding relevance score for each of a plurality of resources, each relevance score measuring a relevance of the resource to the input query, and wherein the operations further comprise: receiving from a search session an input query for the search operation; determining that the input query matches the candidate query and in response increasing the relevance score of the navigational resource associated with the candidate query; generating a set of search results, each search result including a corresponding resource locator that specifies the location of a corresponding resource, at least one of the corresponding resources being the navigational resource; ordering the search results according to the relevance scores of the corresponding resources; and providing the search results for the search session. | 0.5 |
9,031,929 | 25 | 30 | 25. A non-transitory computer storage medium encoded with instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: determining a first count of user selections, received by a search engine, of search results that were presented in response to queries that are categorized as referring include a reference to a particular site; determining a second count of user selections, received by the search engine, of search results that identify resources in the particular site; and determining a site quality score for the particular site including computing a ratio of a numerator based on the first count and a denominator based on the second count, wherein (i) the numerator is based on the first count reduced by a threshold value which is a predetermined threshold value, (ii) the denominator is based on the second count raised to a power that is greater than zero and less than one, or (iii) both. | 25. A non-transitory computer storage medium encoded with instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: determining a first count of user selections, received by a search engine, of search results that were presented in response to queries that are categorized as referring include a reference to a particular site; determining a second count of user selections, received by the search engine, of search results that identify resources in the particular site; and determining a site quality score for the particular site including computing a ratio of a numerator based on the first count and a denominator based on the second count, wherein (i) the numerator is based on the first count reduced by a threshold value which is a predetermined threshold value, (ii) the denominator is based on the second count raised to a power that is greater than zero and less than one, or (iii) both. 30. The computer storage medium of claim 25 , wherein the numerator is a maximum of (a) a lower-bound value and (b) the first count reduced by a threshold value. | 0.65 |
9,836,453 | 7 | 13 | 7. The method of claim 6 , wherein the document-specific features include at least three of the features in the group. | 7. The method of claim 6 , wherein the document-specific features include at least three of the features in the group. 13. The method of claim 7 , wherein the document-specific features further include features for gazetteer entries generated from links to other entries, the links being identified from a knowledge base entry corresponding to one of the document-level entity tags. | 0.5 |
8,301,632 | 6 | 8 | 6. The method of claim 1 further comprising associating the media information with at least one search term in a database of search terms. | 6. The method of claim 1 further comprising associating the media information with at least one search term in a database of search terms. 8. The method of claim 6 further comprising editorially associating the media information with at least one of the search terms. | 0.507692 |
9,886,496 | 9 | 13 | 9. A computing device comprising: a processor; a memory configured to be in communication with the processor, and effective to store instructions; and the processor effective to, in accordance with the instructions: identify contents of a database, wherein the contents of the database are categorized into intelligence fields, wherein the intelligence fields relate to particular types of information among the contents of the database, and wherein the database is stored in a first data structure stored in a memory; receive a selection of a particular intelligence field in the database; search a first data file in the database for matching data among the particular types of information, wherein the particular types of information are categorized within the selected particular intelligence field; identify a match between a first piece of data of the particular type of information and a second piece of data of the particular type of information, wherein the first piece of data is in the first data file and related to a first entity, the first piece of data includes a first link to a first source stored in the memory, the first source is stored in a second data structure different from the first data structure, and wherein the second piece of data is related to a second entity in a second data file, the second piece of data includes a second link to a second source stored in the memory, the second source is different from the first source, and the second source is stored in a third data structure different from the first data structure and the second data structure; determine that the first entity and the second entity are related based on the match; and update the first data file to produce an updated first data file, wherein the updated first data file indicates a relationship between the first entity and the second entity; wherein the memory is further effective to store the updated first data file; and wherein the processor is further effective to cause at least some of the contents of the first data file related to the first entity and the second entity to be displayed on a display. | 9. A computing device comprising: a processor; a memory configured to be in communication with the processor, and effective to store instructions; and the processor effective to, in accordance with the instructions: identify contents of a database, wherein the contents of the database are categorized into intelligence fields, wherein the intelligence fields relate to particular types of information among the contents of the database, and wherein the database is stored in a first data structure stored in a memory; receive a selection of a particular intelligence field in the database; search a first data file in the database for matching data among the particular types of information, wherein the particular types of information are categorized within the selected particular intelligence field; identify a match between a first piece of data of the particular type of information and a second piece of data of the particular type of information, wherein the first piece of data is in the first data file and related to a first entity, the first piece of data includes a first link to a first source stored in the memory, the first source is stored in a second data structure different from the first data structure, and wherein the second piece of data is related to a second entity in a second data file, the second piece of data includes a second link to a second source stored in the memory, the second source is different from the first source, and the second source is stored in a third data structure different from the first data structure and the second data structure; determine that the first entity and the second entity are related based on the match; and update the first data file to produce an updated first data file, wherein the updated first data file indicates a relationship between the first entity and the second entity; wherein the memory is further effective to store the updated first data file; and wherein the processor is further effective to cause at least some of the contents of the first data file related to the first entity and the second entity to be displayed on a display. 13. The computing device of claim 9 , wherein the relationship between the first entity and the second entity includes a strength rating, wherein the processor is effective to determine the strength rating based on a number of times the match between the first piece of data and the second piece of data is identified by the processor. | 0.714651 |
8,885,927 | 4 | 5 | 4. The user emotion detection method according to claim 1 , wherein the user emotion parameter comprises at least one or any combination of: a user emotion rating parameter and a user emotion category parameter. | 4. The user emotion detection method according to claim 1 , wherein the user emotion parameter comprises at least one or any combination of: a user emotion rating parameter and a user emotion category parameter. 5. The user emotion detection method according to claim 4 , wherein the user emotion category parameter is obtained according to the user emotion rating parameter. | 0.5 |
7,539,938 | 1 | 2 | 1. A computer implemented method for validating use of the scientific method in an unpublished article by peer review of the unpublished article over a communications network, comprising: receiving an article from an author via a data communications network, the article comprising a title and a body; parsing the title and body of the article to generate a list of keywords; ranking the list of keywords according to their relative weight in describing the article; querying a database containing profiles of potential reviewers to determine a plurality of qualified reviewers based on the ranked list of keywords; ranking the plurality of qualified reviewers; contacting each qualified reviewer via the data communications network and requesting that the qualified reviewer agree to review the article; receiving an agreement from one or more qualified reviewers; providing the article to an accepting qualified reviewer; providing an evaluation form to the accepting qualified reviewer; receiving a completed evaluation form from the accepting qualified reviewer; providing the accepting qualified reviewer with access to completed evaluation forms of other reviewers for the same article after receiving the completed evaluation form from the accepting qualified reviewer; providing the author with the completed evaluation form; receiving a response from the author directly in the completed evaluation form; providing the completed evaluation form with author responses to an editor; receiving a publication decision from the editor; and providing the publication decision to the author and the reviewer. | 1. A computer implemented method for validating use of the scientific method in an unpublished article by peer review of the unpublished article over a communications network, comprising: receiving an article from an author via a data communications network, the article comprising a title and a body; parsing the title and body of the article to generate a list of keywords; ranking the list of keywords according to their relative weight in describing the article; querying a database containing profiles of potential reviewers to determine a plurality of qualified reviewers based on the ranked list of keywords; ranking the plurality of qualified reviewers; contacting each qualified reviewer via the data communications network and requesting that the qualified reviewer agree to review the article; receiving an agreement from one or more qualified reviewers; providing the article to an accepting qualified reviewer; providing an evaluation form to the accepting qualified reviewer; receiving a completed evaluation form from the accepting qualified reviewer; providing the accepting qualified reviewer with access to completed evaluation forms of other reviewers for the same article after receiving the completed evaluation form from the accepting qualified reviewer; providing the author with the completed evaluation form; receiving a response from the author directly in the completed evaluation form; providing the completed evaluation form with author responses to an editor; receiving a publication decision from the editor; and providing the publication decision to the author and the reviewer. 2. The method of claim 1 , wherein the providing the article to an accepting qualified reviewer step further comprises providing the article to a predetermined maximum number of accepting qualified reviewers. | 0.5 |
8,538,960 | 10 | 12 | 10. A method of providing search results, the method comprising: using a processor to perform acts comprising: receiving a query from a user; determining that the query is answerable with subjective information; obtaining objective results from a corpus of information; using a social graph to identify one or more people who are friends of said user in said social graph, and who have an aspect of relevance to said query; creating person results that comprise said one or more people and, for each of said one or more people, an explanation of each person's relevance to said query; providing, to said user, a set of results that comprise said objective results and said person results, each of said person results being actionable to initiate contact between said user and a person identified in a given result; and training a classifier to identify queries that call for subjective information using training data that comprises: a plurality of positive examples of queries for which people were provided as search results and in which users who requested the results clicked on the people in the results; and a plurality of negative examples of queries for which people were provided as search results and in which users who requested the results did not click on the people in the results; said determining that said query calls for subjective information being performed using said classifier, with said classifier having been trained on said training data. | 10. A method of providing search results, the method comprising: using a processor to perform acts comprising: receiving a query from a user; determining that the query is answerable with subjective information; obtaining objective results from a corpus of information; using a social graph to identify one or more people who are friends of said user in said social graph, and who have an aspect of relevance to said query; creating person results that comprise said one or more people and, for each of said one or more people, an explanation of each person's relevance to said query; providing, to said user, a set of results that comprise said objective results and said person results, each of said person results being actionable to initiate contact between said user and a person identified in a given result; and training a classifier to identify queries that call for subjective information using training data that comprises: a plurality of positive examples of queries for which people were provided as search results and in which users who requested the results clicked on the people in the results; and a plurality of negative examples of queries for which people were provided as search results and in which users who requested the results did not click on the people in the results; said determining that said query calls for subjective information being performed using said classifier, with said classifier having been trained on said training data. 12. The method of claim 10 , said aspect of relevance being based on a comparison of words in said query with Uniform Resource Locators that people in said social graph have entered. | 0.80131 |
9,483,530 | 8 | 13 | 8. A device comprising: a memory to store instructions; and a processor to execute the instructions to: receive first 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; receive, based on receiving the first information indicating that the pair of queries is associated with the threshold quantity of search results that are common between the pair of queries, second information indicating that the extra term is not significant; receive third 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; receive, based on receiving the third information indicating that the other pair of queries is not associated with the threshold quantity of search results that are common between the other pair of queries, fourth information indicating 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 store information including the extra term, an indication that the extra term is not significant, and the context in which the extra term is significant. | 8. A device comprising: a memory to store instructions; and a processor to execute the instructions to: receive first 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; receive, based on receiving the first information indicating that the pair of queries is associated with the threshold quantity of search results that are common between the pair of queries, second information indicating that the extra term is not significant; receive third 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; receive, based on receiving the third information indicating that the other pair of queries is not associated with the threshold quantity of search results that are common between the other pair of queries, fourth information indicating 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 store information including the extra term, an indication that the extra term is not significant, and the context in which the extra term is significant. 13. The device of claim 8 , where the processor is further to: identify, based on the second information and using the extra term as optional, a plurality of documents based on the first query; and provide, for presentation, information regarding the plurality of documents. | 0.690045 |
10,019,991 | 3 | 5 | 3. The apparatus of claim 1 , wherein the display device classifies a domain and displays the domain classified in a layer according to a speech recognition level. | 3. The apparatus of claim 1 , wherein the display device classifies a domain and displays the domain classified in a layer according to a speech recognition level. 5. The apparatus of claim 3 , wherein the layer according to the speech recognition level classifies a general region providing a basic speech recognition region according to a generation situation of the speech and a location. | 0.5 |
7,493,347 | 1 | 11 | 1. A method of generating condensed reports of checkpoint log data, the method comprising: reading a log record comprising a plurality of log entries that report on the status of, and events occurring in, a software application that generates the log entries, wherein status and event information in the plurality of log entries is relevant to a determination of errors and inefficiencies in the software application; reading a log entry count and a log entry size from a header of the log record; demarcating log entries within the log record with information from the log entry count and the log entry size; parsing the log record into log entries; receiving a query expression; applying the query expression against each parsed log entry; and generating a condensed log report comprising only log entries that satisfy the query expression. | 1. A method of generating condensed reports of checkpoint log data, the method comprising: reading a log record comprising a plurality of log entries that report on the status of, and events occurring in, a software application that generates the log entries, wherein status and event information in the plurality of log entries is relevant to a determination of errors and inefficiencies in the software application; reading a log entry count and a log entry size from a header of the log record; demarcating log entries within the log record with information from the log entry count and the log entry size; parsing the log record into log entries; receiving a query expression; applying the query expression against each parsed log entry; and generating a condensed log report comprising only log entries that satisfy the query expression. 11. The method of claim 1 , further comprising accessing log records within a set of log records based on a time stamp. | 0.748945 |
9,390,161 | 8 | 9 | 8. The method of claim 1 , characterized in that it further comprises: applying the one or more phrase separators to split the natural text based on heuristic rules; and generating the one or more phrases. | 8. The method of claim 1 , characterized in that it further comprises: applying the one or more phrase separators to split the natural text based on heuristic rules; and generating the one or more phrases. 9. The method of claim 8 , characterized in that it further comprises calculating the frequency of each of the one or more phrases as it occurs within the one or more generated phrases. | 0.5 |
8,756,207 | 28 | 29 | 28. The system of claim 27 , wherein identifying matches amongst the records is such that: each of the identified matches is between records in one of the evaluated groupings; and for each of the records, being grouped with any other of the records is a condition precedent for being identified as matching that record. | 28. The system of claim 27 , wherein identifying matches amongst the records is such that: each of the identified matches is between records in one of the evaluated groupings; and for each of the records, being grouped with any other of the records is a condition precedent for being identified as matching that record. 29. The system of claim 28 , wherein the phonetic reduction includes all original consonants from the respective substring and does not include any vowels. | 0.5 |
4,464,731 | 13 | 14 | 13. An electronic translator according to claim 12, wherein the first character of the first word or words entered in the input means is transferred immediately to a register in the access means enabling the access means to address those locations in the memory means where first words starting with the first character are stored. | 13. An electronic translator according to claim 12, wherein the first character of the first word or words entered in the input means is transferred immediately to a register in the access means enabling the access means to address those locations in the memory means where first words starting with the first character are stored. 14. An electronic translator according to claim 13, wherein the predetermined order is alphabetical. | 0.5 |
8,942,973 | 1 | 5 | 1. A method for translating a content locator, the method comprising: determining at least one segment of the content locator; generating a plurality of possible transformations of the at least one segment; calculating a context score for each of the plurality of possible transformations by comparing each of the possible transformations to subject matter included in a document associated with the content locator; ranking each of the plurality of possible transformations by comparing the context scores of the plurality of possible transformations to one another; transforming the at least one segment from a source language into a target language by at least one of translation or transliteration; and transmitting the transformed at least one segment in the target language for display on a network browser of a client device. | 1. A method for translating a content locator, the method comprising: determining at least one segment of the content locator; generating a plurality of possible transformations of the at least one segment; calculating a context score for each of the plurality of possible transformations by comparing each of the possible transformations to subject matter included in a document associated with the content locator; ranking each of the plurality of possible transformations by comparing the context scores of the plurality of possible transformations to one another; transforming the at least one segment from a source language into a target language by at least one of translation or transliteration; and transmitting the transformed at least one segment in the target language for display on a network browser of a client device. 5. The method according to claim 1 , wherein transformation comprises: generating a trust value for the transformation of the at least one segment, the trust value including an accuracy for the transformation; and utilizing the transformation of the at least one segment if the trust value for the at least one segment meets or exceeds a threshold value. | 0.628151 |
8,768,708 | 18 | 28 | 18. A specifically programmed computer system, comprising: a non-transient computer memory having at least one region for storing computer executable program code; and at least one processor for executing the program code stored in the memory, wherein the program code performs at least the following: receiving data indicative of speech from the speaker; storing the received data in at least one database; calculating, based upon the received data, an average intensity value for each of a plurality of frequencies, wherein the calculation of the average intensity value for each frequency is based on: i) dividing the received data into a number of time periods; ii) obtaining an intensity of the speaker's speech for each frequency during each time period; iii) obtaining a sum of intensity values for each frequency during all time periods; and iv) dividing the sum of intensity values for each frequency by the number of time periods; calculating, based upon the received data, a maximum intensity value for each of the plurality of frequencies, wherein the maximum intensity value for each frequency is the highest intensity of the speaker's speech for each frequency during all time periods; calculating a level of a survival element of a personality profile of the speaker based upon at least one of: (a) a rapid change in the average intensity value between at least a portion of the plurality of frequencies and (b) a rapid change in the maximum intensity value between at least a portion of the plurality of frequencies; calculating a level of a homeostasis element of the personality profile of the speaker by measuring a distance between the average intensity value and the maximum intensity for each frequency of at least a portion of the plurality of frequencies; calculating a level of a growth element of the personality profile of the speaker based upon at least one of: (a) determining a frequency range within at least a portion of the plurality of frequencies in which the average intensity value of each frequency within the frequency range is higher than a value that is equal to a predetermined percent of the highest average intensity value within the frequency range of the at least a portion of the plurality of frequencies, (b) determining at least one frequency within at least a portion of the plurality of frequencies that has the highest maximum intensity value among the at least a portion of the plurality of frequencies, and (c) determining a level of correlation between changes in intensity values during the time periods of a first frequency and changes in intensity values during the time periods of a second frequency; and outputting an indicator of the personality profile of the speaker based upon a combination of the calculated level of the survival element of the speaker, the calculated level of the homeostasis element of the speaker, and the calculated level of the growth element of the speaker, wherein the indicator of the personal profile at least inform that the speaker exhibits at least one the following personality characteristics: i) a strive to innovate when the calculated level of the growth element is high, ii) a strive for personal enrichment when the calculated level of the growth element is high, iii) a tendency to seek isolation when the calculated level of the growth element is low, iv) a tendency for mental depression when the calculated level of the growth element is low, v) a tendency to engage in high-risk behavior when the calculated level of the survival element is high, vi) a tendency for aggressiveness when the calculated level of the survival element is high, vii) a tendency for possessiveness when the calculated level of the survival element is high, viii) a tendency for being indecisive when the calculated level of the survival element is low, ix) a tendency for being resistant to changing opinions when the calculated level of the homeostasis element is high, x) a tendency for being resistant to changing habits when the calculated level of the homeostasis element is high, xi) a tendency to frequently change opinions when the calculated level of the homeostasis element is low, and xii) a tendency to frequently change habits when the calculated level of the homeostasis element is low. | 18. A specifically programmed computer system, comprising: a non-transient computer memory having at least one region for storing computer executable program code; and at least one processor for executing the program code stored in the memory, wherein the program code performs at least the following: receiving data indicative of speech from the speaker; storing the received data in at least one database; calculating, based upon the received data, an average intensity value for each of a plurality of frequencies, wherein the calculation of the average intensity value for each frequency is based on: i) dividing the received data into a number of time periods; ii) obtaining an intensity of the speaker's speech for each frequency during each time period; iii) obtaining a sum of intensity values for each frequency during all time periods; and iv) dividing the sum of intensity values for each frequency by the number of time periods; calculating, based upon the received data, a maximum intensity value for each of the plurality of frequencies, wherein the maximum intensity value for each frequency is the highest intensity of the speaker's speech for each frequency during all time periods; calculating a level of a survival element of a personality profile of the speaker based upon at least one of: (a) a rapid change in the average intensity value between at least a portion of the plurality of frequencies and (b) a rapid change in the maximum intensity value between at least a portion of the plurality of frequencies; calculating a level of a homeostasis element of the personality profile of the speaker by measuring a distance between the average intensity value and the maximum intensity for each frequency of at least a portion of the plurality of frequencies; calculating a level of a growth element of the personality profile of the speaker based upon at least one of: (a) determining a frequency range within at least a portion of the plurality of frequencies in which the average intensity value of each frequency within the frequency range is higher than a value that is equal to a predetermined percent of the highest average intensity value within the frequency range of the at least a portion of the plurality of frequencies, (b) determining at least one frequency within at least a portion of the plurality of frequencies that has the highest maximum intensity value among the at least a portion of the plurality of frequencies, and (c) determining a level of correlation between changes in intensity values during the time periods of a first frequency and changes in intensity values during the time periods of a second frequency; and outputting an indicator of the personality profile of the speaker based upon a combination of the calculated level of the survival element of the speaker, the calculated level of the homeostasis element of the speaker, and the calculated level of the growth element of the speaker, wherein the indicator of the personal profile at least inform that the speaker exhibits at least one the following personality characteristics: i) a strive to innovate when the calculated level of the growth element is high, ii) a strive for personal enrichment when the calculated level of the growth element is high, iii) a tendency to seek isolation when the calculated level of the growth element is low, iv) a tendency for mental depression when the calculated level of the growth element is low, v) a tendency to engage in high-risk behavior when the calculated level of the survival element is high, vi) a tendency for aggressiveness when the calculated level of the survival element is high, vii) a tendency for possessiveness when the calculated level of the survival element is high, viii) a tendency for being indecisive when the calculated level of the survival element is low, ix) a tendency for being resistant to changing opinions when the calculated level of the homeostasis element is high, x) a tendency for being resistant to changing habits when the calculated level of the homeostasis element is high, xi) a tendency to frequently change opinions when the calculated level of the homeostasis element is low, and xii) a tendency to frequently change habits when the calculated level of the homeostasis element is low. 28. The system of claim 18 , wherein the indicator of the personality profile of the speaker is associated with at least one personality profile from a plurality of personal profiles which are calculated based at least in part on all possible mathematical permutations among levels of grading for at least two of: a) the survival element, b) the homeostasis element, and c) the growth element. | 0.610891 |
8,655,761 | 12 | 13 | 12. The method of claim 1 , wherein submitting the keyword context and geographic context comprises submitting multiple related queries to a remote server, and wherein displaying an interactive application comprises rendering query results incrementally and at least in part substantially concurrently with the submission of one or more of the multiple queries. | 12. The method of claim 1 , wherein submitting the keyword context and geographic context comprises submitting multiple related queries to a remote server, and wherein displaying an interactive application comprises rendering query results incrementally and at least in part substantially concurrently with the submission of one or more of the multiple queries. 13. The method of claim 12 , wherein the multiple related queries comprise queries to refine prior results for updated display. | 0.5 |
9,092,420 | 12 | 17 | 12. A method for automatically generating grammar for use in the processing of natural language, the method comprising: setting one domain as a target domain to be processed by an intention analysis system using a setting processor; extracting a corpus relevant to the target domain from a collection of corpora using an extractor, dividing the corpus into sentences and tagging the sentences; classifying the extracted corpus into a domain action among one or more domain actions that correspond to the target domain; converting one or more words included in the extracted corpus into classes; and generating a grammar based on the converted classes of the extracted corpus using a generator wherein one or more ungrammatical words or sentences are removed from the corpus. | 12. A method for automatically generating grammar for use in the processing of natural language, the method comprising: setting one domain as a target domain to be processed by an intention analysis system using a setting processor; extracting a corpus relevant to the target domain from a collection of corpora using an extractor, dividing the corpus into sentences and tagging the sentences; classifying the extracted corpus into a domain action among one or more domain actions that correspond to the target domain; converting one or more words included in the extracted corpus into classes; and generating a grammar based on the converted classes of the extracted corpus using a generator wherein one or more ungrammatical words or sentences are removed from the corpus. 17. The method of claim 12 , wherein the collection of corpora include text corpus that is collected from one or more of novels, magazines, dictionaries, and text available on the World Wide Web, and the collection of corpora further includes speech corpus that is collected from one or more of conversations, interviews, and speeches. | 0.5 |
8,762,156 | 18 | 19 | 18. The data processing system of claim 17 wherein the context includes a history of user inputs and wherein the set of interpreters use the context in a process of determining whether to repair one or more words in the first text output and wherein the processor is capable of recognizing text using an acoustic model and a language model. | 18. The data processing system of claim 17 wherein the context includes a history of user inputs and wherein the set of interpreters use the context in a process of determining whether to repair one or more words in the first text output and wherein the processor is capable of recognizing text using an acoustic model and a language model. 19. The data processing system of claim 18 wherein the set of interpreters search the one or more databases to compare words in the first text output with one or more items in the one or more databases when determining whether to repair one or more words in the first text output. | 0.5 |
5,509,103 | 1 | 10 | 1. A method of training a neural network used in a speech-recognition system, said neural network comprising a plurality of neurons, said method comprising the following steps: receiving an example spoken word; performing analog-to-digital conversion of said example spoken word to produce a digitized signal; performing cepstral analysis of said digitized signal to produce a sequence of data frames; generating a plurality of data blocks from said sequence of data frames; determining if said neural network is to recognize said example spoken word; (i) if so, equating neural network output to one; (ii) if not, equating said neural network output to zero; and training said neural network by calculating a plurality of weight values for said neural network, wherein if the number of said neurons is equal to the number of said data blocks, a matrix-inversion technique is used to calculate said weight values, otherwise, a least-squares estimation technique is used to calculate said weight values. | 1. A method of training a neural network used in a speech-recognition system, said neural network comprising a plurality of neurons, said method comprising the following steps: receiving an example spoken word; performing analog-to-digital conversion of said example spoken word to produce a digitized signal; performing cepstral analysis of said digitized signal to produce a sequence of data frames; generating a plurality of data blocks from said sequence of data frames; determining if said neural network is to recognize said example spoken word; (i) if so, equating neural network output to one; (ii) if not, equating said neural network output to zero; and training said neural network by calculating a plurality of weight values for said neural network, wherein if the number of said neurons is equal to the number of said data blocks, a matrix-inversion technique is used to calculate said weight values, otherwise, a least-squares estimation technique is used to calculate said weight values. 10. The method recited in claim 1, wherein said neural network computes a discriminant function based upon an orthogonal function. | 0.9521 |
8,285,744 | 1 | 27 | 1. A system that facilitates searching manufacturing process information, comprising: a memory that stores computer-executable components; a processor, communicatively coupled to the memory, that facilitates execution of the computer-executable components, the computer-executable components including: a plurality of indexing agents, specific to a plurality of disparate types of manufacturing information, that are configured to access the plurality of disparate types of manufacturing information from a manufacturing process within an industrial automation system and configured to create searchable sub-indices for the plurality of disparate types of manufacturing information, wherein a number of the plurality of indexing agents employed is at least one of expanded or reduced based in part on a change in a number of the plurality of disparate types of manufacturing information; and a manufacturing process search engine configured to employ the at least a portion of the searchable sub-indices to facilitate in responding to a manufacturing process information search query, wherein the manufacturing process search engine includes at least one data broker configured to access at least one of real-time data from an industrial automation device or historical data associated with a data storage. | 1. A system that facilitates searching manufacturing process information, comprising: a memory that stores computer-executable components; a processor, communicatively coupled to the memory, that facilitates execution of the computer-executable components, the computer-executable components including: a plurality of indexing agents, specific to a plurality of disparate types of manufacturing information, that are configured to access the plurality of disparate types of manufacturing information from a manufacturing process within an industrial automation system and configured to create searchable sub-indices for the plurality of disparate types of manufacturing information, wherein a number of the plurality of indexing agents employed is at least one of expanded or reduced based in part on a change in a number of the plurality of disparate types of manufacturing information; and a manufacturing process search engine configured to employ the at least a portion of the searchable sub-indices to facilitate in responding to a manufacturing process information search query, wherein the manufacturing process search engine includes at least one data broker configured to access at least one of real-time data from an industrial automation device or historical data associated with a data storage. 27. The system of claim 1 , wherein the plurality of indexing agents are remotely coupled to the manufacturing process indexing component. | 0.744444 |
8,296,354 | 24 | 27 | 24. A computer-implemented method for converting typed application data into a Simple Object Access Protocol (SOAP) format, the method comprising: an act of storing by a first computer system a typed data object, wherein the typed data object defines a method associated with a first portion of a distributed application, wherein the typed data object comprises: typed application data comprising at least one typed object parameter for invoking the method, wherein the at least one typed object parameter is in a format compatible with the first portion of the distributed application and with a second portion of the distributed application on a second computer system; and at least one message contract attribute of a message contract model, wherein the at least one message contract attribute annotates the typed data object such that the at least one message contract attribute is adjacent to the at least one typed object parameter, wherein the at least one message contract attribute defines a mapping between the at least one typed object parameter and a corresponding SOAP element, and wherein the at least one message contract attribute specifies a location within a SOAP envelope for inserting the corresponding SOAP element; an act of accessing the typed data object; an act of mapping the at least one typed object parameter to the corresponding SOAP element by referring to the at least one message contract attribute that annotates the accessed typed data object; an act of inserting the corresponding SOAP element into the location within the SOAP envelope in accordance with the at least one message contract attribute; and an act of transmitting the SOAP envelope to the second portion of the distributed application on the second computer system. | 24. A computer-implemented method for converting typed application data into a Simple Object Access Protocol (SOAP) format, the method comprising: an act of storing by a first computer system a typed data object, wherein the typed data object defines a method associated with a first portion of a distributed application, wherein the typed data object comprises: typed application data comprising at least one typed object parameter for invoking the method, wherein the at least one typed object parameter is in a format compatible with the first portion of the distributed application and with a second portion of the distributed application on a second computer system; and at least one message contract attribute of a message contract model, wherein the at least one message contract attribute annotates the typed data object such that the at least one message contract attribute is adjacent to the at least one typed object parameter, wherein the at least one message contract attribute defines a mapping between the at least one typed object parameter and a corresponding SOAP element, and wherein the at least one message contract attribute specifies a location within a SOAP envelope for inserting the corresponding SOAP element; an act of accessing the typed data object; an act of mapping the at least one typed object parameter to the corresponding SOAP element by referring to the at least one message contract attribute that annotates the accessed typed data object; an act of inserting the corresponding SOAP element into the location within the SOAP envelope in accordance with the at least one message contract attribute; and an act of transmitting the SOAP envelope to the second portion of the distributed application on the second computer system. 27. The computer-implemented method as recited in claim 24 , wherein the act of mapping the typed object parameter to the corresponding SOAP element comprises serializing the typed object parameter to the corresponding SOAP element. | 0.743929 |
7,840,577 | 1 | 7 | 1. A system for processing search query submissions, the system comprising: a data set that maps individual terms to sets of related terms, said data set stored in a computer memory and being based at least partly on a term co-occurrence analysis, said data set comprising a plurality of entries, each of which maps an individual term to a respective set of related terms; and a query processing system that uses the data set to identify alternative spellings of misspelled search terms of multiple-term search queries, said query processing system comprising computer hardware that executes software. | 1. A system for processing search query submissions, the system comprising: a data set that maps individual terms to sets of related terms, said data set stored in a computer memory and being based at least partly on a term co-occurrence analysis, said data set comprising a plurality of entries, each of which maps an individual term to a respective set of related terms; and a query processing system that uses the data set to identify alternative spellings of misspelled search terms of multiple-term search queries, said query processing system comprising computer hardware that executes software. 7. The system as in claim 1 , wherein the data set reflects a result of a term co-occurrence analysis of a database searched by the query processing system. | 0.797403 |
7,505,894 | 16 | 18 | 16. The system of claim 15 wherein each of the nodes in the target language dependency tree represent a word in a target language text fragment, and wherein the order model is configured to assign a score to an order for each node, in turn, at each level of the target language dependency tree. | 16. The system of claim 15 wherein each of the nodes in the target language dependency tree represent a word in a target language text fragment, and wherein the order model is configured to assign a score to an order for each node, in turn, at each level of the target language dependency tree. 18. The system of claim 16 wherein the source language dependency structure has nodes aligned with the nodes in the target language dependency tree, and wherein the order model is configured to compute a score indicative of whether a selected node in the target language dependency tree will switch from being a pre or post modifier of a parent node in the source language text fragment to being a post or pre modifier of the parent node in the target language text fragment. | 0.5 |
8,180,630 | 2 | 3 | 2. The method of automated dictionary population, as recited in claim 1 , further comprising linking the words of the identified phrases. | 2. The method of automated dictionary population, as recited in claim 1 , further comprising linking the words of the identified phrases. 3. The method of automated dictionary population, as recited in claim 2 , further comprising storing the linking of the words of the identified phrases. | 0.5 |
7,546,288 | 7 | 8 | 7. The method of claim 1 , wherein searching the database produces an unranked list of items of media content. | 7. The method of claim 1 , wherein searching the database produces an unranked list of items of media content. 8. The method of claim 7 , further comprising sending the unranked list of items of media content to the second computing device. | 0.772085 |
8,606,757 | 1 | 5 | 1. A method comprising: receiving, on a computing device, a plurality of execution results corresponding to a plurality of query language expressions, the plurality of query language expressions being concurrently executed against a document, and the receiving being contemporaneous with interleaved production of the plurality of execution results; creating, on the computing device, a plurality of result handles correspondingly associated with the plurality of query language expressions; storing, on the computing device, at least a first received portion of one of the plurality of execution results in one of the plurality of result handles associated with a corresponding one of the plurality of query language expressions, wherein said storing is contemporaneous with further production of at least a second portion of the one of the plurality of execution results; upon receiving the second portion of the one of the execution results, and in response to a determination of insufficient space for the second received portion, reserving a new memory block, on the computing device, setting a most recently reserved memory block to point to the new memory block, thereby creating a linked list of reserved memory blocks associated with the one of the plurality of results handles, and storing, the second portion of the one of the execution results in the new memory block; and storing metadata associated with the corresponding one of the plurality of query language expressions and references to the linked list of reserved memory blocks in the one of the plurality of result handles wherein said metadata includes at least an indication of whether result items of the corresponding one of the plurality of query language expressions are homogenous or heterogeneous. | 1. A method comprising: receiving, on a computing device, a plurality of execution results corresponding to a plurality of query language expressions, the plurality of query language expressions being concurrently executed against a document, and the receiving being contemporaneous with interleaved production of the plurality of execution results; creating, on the computing device, a plurality of result handles correspondingly associated with the plurality of query language expressions; storing, on the computing device, at least a first received portion of one of the plurality of execution results in one of the plurality of result handles associated with a corresponding one of the plurality of query language expressions, wherein said storing is contemporaneous with further production of at least a second portion of the one of the plurality of execution results; upon receiving the second portion of the one of the execution results, and in response to a determination of insufficient space for the second received portion, reserving a new memory block, on the computing device, setting a most recently reserved memory block to point to the new memory block, thereby creating a linked list of reserved memory blocks associated with the one of the plurality of results handles, and storing, the second portion of the one of the execution results in the new memory block; and storing metadata associated with the corresponding one of the plurality of query language expressions and references to the linked list of reserved memory blocks in the one of the plurality of result handles wherein said metadata includes at least an indication of whether result items of the corresponding one of the plurality of query language expressions are homogenous or heterogeneous. 5. The method of claim 1 , further comprising: determining whether the memory block storing the second portion of the one of the plurality of execution results includes space to store another portion of the one of the plurality of execution results; and in response to a determination of insufficient space in the memory block, linking another memory block. | 0.806399 |
9,870,572 | 5 | 6 | 5. The method of claim 1 , wherein the geographic location comprises a street address. | 5. The method of claim 1 , wherein the geographic location comprises a street address. 6. The method of claim 5 , wherein the listing pertains to a business that is located at the geographic location. | 0.5 |
8,565,537 | 19 | 21 | 19. A processing system comprising: at least one processor; a non-transitory machine-accessible medium responsive to the processor; and instructions in the machine-accessible medium, wherein the instructions, when executed by the processor, enable the processing system to perform operations comprising: receiving an example image for use in querying a collection of digital images; using a local feature descriptor representing a portion of the contents of a digital image and a global feature descriptor representing substantially all of the contents of the digital image to perform a content-based image comparison of the collection of digital images with the example image, to automatically rank the collection of digital images with respect to similarity to the example image, wherein the global feature descriptor is content based; using a final classifier and multiple different intermediate classifiers to perform the automatic ranking, comprising: generating, by the different intermediate classifiers, intermediate relevance metrics with respect to different modalities; and generating, by the final classifier, results from the intermediate classifiers into a final relevance metric to display images in ranked order; after generating the final relevance metric, receiving input identifying a second example image for use in querying the collection of digital images; automatically determining at least one new intermediate classifier, based at least in part on the example images; automatically determining a new final classifier, based at least in part on the example images; and using the new intermediate classifier and the new final classifier to automatically re-rank the digital images in the collection with respect to similarity to the example images. | 19. A processing system comprising: at least one processor; a non-transitory machine-accessible medium responsive to the processor; and instructions in the machine-accessible medium, wherein the instructions, when executed by the processor, enable the processing system to perform operations comprising: receiving an example image for use in querying a collection of digital images; using a local feature descriptor representing a portion of the contents of a digital image and a global feature descriptor representing substantially all of the contents of the digital image to perform a content-based image comparison of the collection of digital images with the example image, to automatically rank the collection of digital images with respect to similarity to the example image, wherein the global feature descriptor is content based; using a final classifier and multiple different intermediate classifiers to perform the automatic ranking, comprising: generating, by the different intermediate classifiers, intermediate relevance metrics with respect to different modalities; and generating, by the final classifier, results from the intermediate classifiers into a final relevance metric to display images in ranked order; after generating the final relevance metric, receiving input identifying a second example image for use in querying the collection of digital images; automatically determining at least one new intermediate classifier, based at least in part on the example images; automatically determining a new final classifier, based at least in part on the example images; and using the new intermediate classifier and the new final classifier to automatically re-rank the digital images in the collection with respect to similarity to the example images. 21. A processing system according to claim 19 , wherein: each digital image comprises a set of pixel values; and the operation of using local and global feature descriptors to perform the content-based image comparison of the collection of digital images with the example image comprises: using a first local feature descriptor and a second local feature descriptor to perform the content-based image comparison, wherein: the first local feature descriptor represents pixel values from a first portion of the digital image; and the second local feature descriptor represents pixel values from a second portion of the digital image. | 0.5 |
7,788,089 | 1 | 3 | 1. A computer-implemented method for classifying an end-of-line hyphen as either a soft-hyphen that has been inserted into the word for typesetting purposes or a hard-hyphen that belongs in the word, comprising: performing in a computer programmed to perform particular functions pursuant to instructions from program software operations comprising: searching a document for a word that contains an end-of-line hyphen; creating a solution set for the word containing the end-of-line hyphen, wherein each solution in the solution set is obtained by identifying the end-of-line hyphen as either a soft-hyphen that has been inserted into the word for typesetting purposes or a hard-hyphen that belongs in the word, wherein the solution set is stored in memory of a computer system; searching a dictionary for each solution in the solution set; and using the results from the dictionary search to identify the end-of-line hyphen as either a soft-hyphen or a hard-hyphen. | 1. A computer-implemented method for classifying an end-of-line hyphen as either a soft-hyphen that has been inserted into the word for typesetting purposes or a hard-hyphen that belongs in the word, comprising: performing in a computer programmed to perform particular functions pursuant to instructions from program software operations comprising: searching a document for a word that contains an end-of-line hyphen; creating a solution set for the word containing the end-of-line hyphen, wherein each solution in the solution set is obtained by identifying the end-of-line hyphen as either a soft-hyphen that has been inserted into the word for typesetting purposes or a hard-hyphen that belongs in the word, wherein the solution set is stored in memory of a computer system; searching a dictionary for each solution in the solution set; and using the results from the dictionary search to identify the end-of-line hyphen as either a soft-hyphen or a hard-hyphen. 3. The computer-implemented method of claim 1 , wherein the result of the dictionary search is to find none of the solutions in the solution set, the method further comprising: prompting a user to manually identify the end-of-line hyphen as either a soft-hyphen or a hard-hyphen. | 0.5 |
9,466,294 | 3 | 9 | 3. A computer-implemented method for facilitating a transaction, comprising: receiving input initiating the transaction; generating one or more queries from the input, each of the queries including one or more variables representing unknown information required for the transaction to proceed, the one or more variables of the one or more queries including a first variable, a second variable, and a third variable; for each variable in each query, determining whether the unknown information represented by the variable can be obtained from a first information source, the first information source comprising a knowledge base including structured data having a format compatible with the one or more queries; for each variable for which the unknown information cannot be obtained from the first information source, determining whether the unknown information represented by the variable can be obtained from one or more of a plurality of alternate information sources, the alternate information sources including a user by whom the input was entered, and a remote information source that is remote from and independent of the knowledge base; transmitting a first request for information to the remote information source; receiving a response to the first request; transmitting a second request for information to the device associated with the user; receiving a response to the second request from the device, the response to the second request including input from the user; determining the unknown information represented by each variable, including determining the unknown information represented by the first variable using the response to the first request, determining the unknown information represented by the second variable using the response to the second request, and determining the unknown information represented by the third variable using the knowledge base; and proceeding with the transaction. | 3. A computer-implemented method for facilitating a transaction, comprising: receiving input initiating the transaction; generating one or more queries from the input, each of the queries including one or more variables representing unknown information required for the transaction to proceed, the one or more variables of the one or more queries including a first variable, a second variable, and a third variable; for each variable in each query, determining whether the unknown information represented by the variable can be obtained from a first information source, the first information source comprising a knowledge base including structured data having a format compatible with the one or more queries; for each variable for which the unknown information cannot be obtained from the first information source, determining whether the unknown information represented by the variable can be obtained from one or more of a plurality of alternate information sources, the alternate information sources including a user by whom the input was entered, and a remote information source that is remote from and independent of the knowledge base; transmitting a first request for information to the remote information source; receiving a response to the first request; transmitting a second request for information to the device associated with the user; receiving a response to the second request from the device, the response to the second request including input from the user; determining the unknown information represented by each variable, including determining the unknown information represented by the first variable using the response to the first request, determining the unknown information represented by the second variable using the response to the second request, and determining the unknown information represented by the third variable using the knowledge base; and proceeding with the transaction. 9. The method of claim 3 , wherein when execution of a first one of the one or more queries fails, re-executing the first query after adding to contextual information generated with reference to one or more of the alternate information sources. | 0.691919 |
9,189,473 | 7 | 13 | 7. The method of claim 1 , wherein the computing of the similarity comprises inputting at least one socio-temporal feature for the pair of the candidate named entities into a classifier trained to output a similarity score, the at least one socio-temporal feature being based on a similarity between the event profiles of the candidate named entities in the pair. | 7. The method of claim 1 , wherein the computing of the similarity comprises inputting at least one socio-temporal feature for the pair of the candidate named entities into a classifier trained to output a similarity score, the at least one socio-temporal feature being based on a similarity between the event profiles of the candidate named entities in the pair. 13. The method of claim 7 , wherein the providing for merging the candidate named entities into a common real named entity, based on the computed similarity comprises merging a pair of candidate named entities when the classifier score meets a predefined threshold. | 0.5 |
7,711,550 | 16 | 20 | 16. A computer readable medium containing instructions which when executed by a computer perform the steps of: receiving a previously generated text string; passing the text string to a name recognizer application; determining whether a particular spoken language is associated with the text string; applying a set of name rules of the spoken language associated with the text string to a plurality of individual words comprising the text string, the set of name rules comprising grammatical rules and sentence structure rules of the spoken language; determining whether any of the plurality of individual words comprise a name according to the set of name rules of the spoken language associated with the text string; generating a list of user actions that may be performed on the name, wherein generating the list of actions that may be performed on the name comprises analyzing the language associated with the text string and determining if the name exists in a user contacts database; associating the list of user actions with the name; if any of the plurality of individual words comprise a name, returning the name and the list of user actions associated with the name to a host application with which the text string was previously generated for providing the list of user actions associated with the name, marking the name in the text string to indicate the list of user actions are available in association with the name, and providing to a user the list of user actions in association with the name. | 16. A computer readable medium containing instructions which when executed by a computer perform the steps of: receiving a previously generated text string; passing the text string to a name recognizer application; determining whether a particular spoken language is associated with the text string; applying a set of name rules of the spoken language associated with the text string to a plurality of individual words comprising the text string, the set of name rules comprising grammatical rules and sentence structure rules of the spoken language; determining whether any of the plurality of individual words comprise a name according to the set of name rules of the spoken language associated with the text string; generating a list of user actions that may be performed on the name, wherein generating the list of actions that may be performed on the name comprises analyzing the language associated with the text string and determining if the name exists in a user contacts database; associating the list of user actions with the name; if any of the plurality of individual words comprise a name, returning the name and the list of user actions associated with the name to a host application with which the text string was previously generated for providing the list of user actions associated with the name, marking the name in the text string to indicate the list of user actions are available in association with the name, and providing to a user the list of user actions in association with the name. 20. The computer readable medium of claim 16 , further comprising upon selection of the marked name in the text string, providing the list of actions associated with the name. | 0.680657 |
8,195,648 | 1 | 2 | 1. A computer system, comprising: a processor; and a memory communicatively coupled to the processor, the memory having computer-executable instructions that when executed by the processor provide one or more modules, the one or more modules further comprising: an execution module configured to: partition a plurality of events into one or more groups based on a partitioning operator; instantiate a query application module for each of the one or more groups, wherein each particular query application module for a particular group includes data associated with the query and group-specific data associated with the particular group, and is configured to apply the query to events of the particular group to generate results, and wherein each query application module for a group comprises logic to execute a plurality of complex event processing (CEP) operators and wherein the logic of each query application module is configured for execution at a separate execution thread of the computer system; and merge results of each of the query application modules. | 1. A computer system, comprising: a processor; and a memory communicatively coupled to the processor, the memory having computer-executable instructions that when executed by the processor provide one or more modules, the one or more modules further comprising: an execution module configured to: partition a plurality of events into one or more groups based on a partitioning operator; instantiate a query application module for each of the one or more groups, wherein each particular query application module for a particular group includes data associated with the query and group-specific data associated with the particular group, and is configured to apply the query to events of the particular group to generate results, and wherein each query application module for a group comprises logic to execute a plurality of complex event processing (CEP) operators and wherein the logic of each query application module is configured for execution at a separate execution thread of the computer system; and merge results of each of the query application modules. 2. The computer system of claim 1 , further comprising: a planning module configured to generate a query application plan based on a query that includes a partitioning operator, wherein the planning module executes during a compile-time of the computer system and wherein the execution module executes during a run-time of the computer system. | 0.5 |
8,782,595 | 7 | 8 | 7. A build system comprising: one or more processors; a computer-readable medium coupled to the one or more processors having instructions stored thereon that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: receiving one or more attribute rules and one or more extra action rules, wherein the one or more attribute rules correspond to one or more predefined default actions of the build system, wherein the extra action rules specify additional actions that are to be added to the build system; generating a graph that represents a relationship between files specified as attributes in the attribute rules and said one or more predefined default actions that correspond to the attribute rules; receiving a request to enable at least one of the extra action rules; receiving action listener rules, wherein the action listener rules indicate one or more default actions and corresponding one or more extra action rules; checking the graph to determine whether said graph includes a particular one of the default actions indicated in the action listener rules; and in response to a determination that the graph includes said particular one of the default actions, adding additional actions to the graph for one or more of the extra action rules corresponding to the particular one of the default actions. | 7. A build system comprising: one or more processors; a computer-readable medium coupled to the one or more processors having instructions stored thereon that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: receiving one or more attribute rules and one or more extra action rules, wherein the one or more attribute rules correspond to one or more predefined default actions of the build system, wherein the extra action rules specify additional actions that are to be added to the build system; generating a graph that represents a relationship between files specified as attributes in the attribute rules and said one or more predefined default actions that correspond to the attribute rules; receiving a request to enable at least one of the extra action rules; receiving action listener rules, wherein the action listener rules indicate one or more default actions and corresponding one or more extra action rules; checking the graph to determine whether said graph includes a particular one of the default actions indicated in the action listener rules; and in response to a determination that the graph includes said particular one of the default actions, adding additional actions to the graph for one or more of the extra action rules corresponding to the particular one of the default actions. 8. The build system of claim 7 , further comprising analyzing the graph and executing those actions in the graph that need updating. | 0.666667 |
8,290,961 | 1 | 5 | 1. A computer implemented method of information retrieval, comprising: parsing a corpus to identify instances of wordforms within each document of the corpus; performing a morphological tokenization on the wordforms to convert the wordforms into morphemes by separating affixes from their stems; generating a morpheme-by-document matrix based at least in part on a number of instances of the affixes and the stems within each document of the corpus, wherein the morpheme-by-document matrix accounts for information related to past tense and present tense inflections by separately enumerating the instances of the affixes from the instances of the stems; applying a weighting function to attribute-values within the morpheme-by-document matrix to generate a weighted morpheme-by-document matrix, wherein applying the weighting function includes: applying the weighting function to the attribute-values of the stems; and applying the weighting function to the attribute-values of the affixes separately from the attribute-values of the stems to separately account for relative importance of the affixes; generating at least one lower rank approximation matrix by factorizing the weighted morpheme-by-document matrix; and retrieving information with reference to the at least one lower rank approximation matrix. | 1. A computer implemented method of information retrieval, comprising: parsing a corpus to identify instances of wordforms within each document of the corpus; performing a morphological tokenization on the wordforms to convert the wordforms into morphemes by separating affixes from their stems; generating a morpheme-by-document matrix based at least in part on a number of instances of the affixes and the stems within each document of the corpus, wherein the morpheme-by-document matrix accounts for information related to past tense and present tense inflections by separately enumerating the instances of the affixes from the instances of the stems; applying a weighting function to attribute-values within the morpheme-by-document matrix to generate a weighted morpheme-by-document matrix, wherein applying the weighting function includes: applying the weighting function to the attribute-values of the stems; and applying the weighting function to the attribute-values of the affixes separately from the attribute-values of the stems to separately account for relative importance of the affixes; generating at least one lower rank approximation matrix by factorizing the weighted morpheme-by-document matrix; and retrieving information with reference to the at least one lower rank approximation matrix. 5. The computer implemented method of claim 1 , further comprising: generating a term-by-term alignment matrix based on the morpheme-by-document matrix; and applying a second weighting function to the term-by-term alignment matrix to generate a weighted term-by-term alignment matrix. | 0.784522 |
7,950,064 | 12 | 14 | 12. A computer program product stored in a non-transitory computer readable medium, comprising functional descriptive material that, when executed by an information handling system, causes the information handling system to perform actions that include: opening a word processing document that includes document content and a plurality of comments inserted at a plurality of insertion points within the document content, wherein the opening occurs during a word processing application currently assigned to a user identifier, and wherein one or more of the plurality of comments includes one or more recipient identifiers; selecting a first set of comments from the plurality of comments where the user identifier is included in the recipient identifiers of the corresponding comments; identifying a first set of one or more encrypted comments included in the first set of comments; retrieving a user encryption key corresponding to the user identifier; decrypting the first set of encrypted comments using the retrieved user encryption key; selecting a second set of comments from the plurality of comments where the user identifier is not included in the recipient identifiers of the corresponding comments; displaying the first set of comments, each of the first set of comments being displayed at their respective insertion points within the document content; and inhibiting display of the second set of comments. | 12. A computer program product stored in a non-transitory computer readable medium, comprising functional descriptive material that, when executed by an information handling system, causes the information handling system to perform actions that include: opening a word processing document that includes document content and a plurality of comments inserted at a plurality of insertion points within the document content, wherein the opening occurs during a word processing application currently assigned to a user identifier, and wherein one or more of the plurality of comments includes one or more recipient identifiers; selecting a first set of comments from the plurality of comments where the user identifier is included in the recipient identifiers of the corresponding comments; identifying a first set of one or more encrypted comments included in the first set of comments; retrieving a user encryption key corresponding to the user identifier; decrypting the first set of encrypted comments using the retrieved user encryption key; selecting a second set of comments from the plurality of comments where the user identifier is not included in the recipient identifiers of the corresponding comments; displaying the first set of comments, each of the first set of comments being displayed at their respective insertion points within the document content; and inhibiting display of the second set of comments. 14. The computer program product of claim 12 wherein a group comment is included in the first set of comments, wherein the group comment includes a group recipient identifier and wherein the selecting of the first set of comments further comprises additional functional descriptive material that causes the data processing system to perform additional actions that include: determining that the user identifier is included in a list of identifiers corresponding to the group recipient identifier. | 0.5 |
9,225,745 | 1 | 5 | 1. A method comprising: receiving a message via a communications interface in a computing device, the message including a request to perform an action within a proposal system, the proposal system being operable to create a request for proposals based on user input, the request for proposals describing a business need associated with a business entity, the proposal system being further operable to process a plurality of proposal documents received in response to the request for proposals, the request being associated with a user account, wherein the plurality of proposal documents correspond to plans addressing the business need associated with the business entity; determining, via a processor in the computing device, whether the requested action complies with an access policy, wherein the requested action comprises a request to create a designated proposal document in response to the request for proposals; and performing the requested action via the processor when it is determined that the requested action complies with the access policy, wherein performing the requested action comprises creating the designated proposal document based on user input and suggested content, the suggested content being determined by the proposal system, wherein the user account is a member of a first user account group, wherein the access policy identifies a first one or more permitted actions associated with the first user account group, and wherein determining whether the requested action complies with the access policy comprises determining whether the first one or more permitted actions includes the requested action, wherein the user account is a member of a second user account group, and wherein the access policy identifies a second one or more permitted actions associated with the second user account group, wherein determining whether the requested action complies with the access policy further comprises determining whether the second one or more permitted actions includes the requested action, and wherein the requested action is performed when either the first or second one or more permitted actions includes the requested action. | 1. A method comprising: receiving a message via a communications interface in a computing device, the message including a request to perform an action within a proposal system, the proposal system being operable to create a request for proposals based on user input, the request for proposals describing a business need associated with a business entity, the proposal system being further operable to process a plurality of proposal documents received in response to the request for proposals, the request being associated with a user account, wherein the plurality of proposal documents correspond to plans addressing the business need associated with the business entity; determining, via a processor in the computing device, whether the requested action complies with an access policy, wherein the requested action comprises a request to create a designated proposal document in response to the request for proposals; and performing the requested action via the processor when it is determined that the requested action complies with the access policy, wherein performing the requested action comprises creating the designated proposal document based on user input and suggested content, the suggested content being determined by the proposal system, wherein the user account is a member of a first user account group, wherein the access policy identifies a first one or more permitted actions associated with the first user account group, and wherein determining whether the requested action complies with the access policy comprises determining whether the first one or more permitted actions includes the requested action, wherein the user account is a member of a second user account group, and wherein the access policy identifies a second one or more permitted actions associated with the second user account group, wherein determining whether the requested action complies with the access policy further comprises determining whether the second one or more permitted actions includes the requested action, and wherein the requested action is performed when either the first or second one or more permitted actions includes the requested action. 5. The method recited in claim 1 , wherein the request for an action is generated automatically. | 0.88785 |
9,524,081 | 1 | 11 | 1. A method for synchronizing performance of a virtual object to performance of a person, comprising: capturing a first audio signal associated with sounds made by the person during a first time period; detecting that a first utterance has been spoken by the person using the captured first audio signal; determining a speed at which the person spoke the first utterance; capturing a second audio signal associated with sounds made by the person during a second time period subsequent to the first time period; detecting that a portion of a second utterance has been spoken by the person using the captured second audio signal; and displaying, using a display, a sequence of images of the virtual object at a rate corresponding with the determined speed of the first utterance in response to detecting that the portion of the second utterance has been spoken by the person, the sequence of images including a sequence of mouth shape images displayed such that the virtual object appears to speak the second utterance at the determined speed of the first utterance. | 1. A method for synchronizing performance of a virtual object to performance of a person, comprising: capturing a first audio signal associated with sounds made by the person during a first time period; detecting that a first utterance has been spoken by the person using the captured first audio signal; determining a speed at which the person spoke the first utterance; capturing a second audio signal associated with sounds made by the person during a second time period subsequent to the first time period; detecting that a portion of a second utterance has been spoken by the person using the captured second audio signal; and displaying, using a display, a sequence of images of the virtual object at a rate corresponding with the determined speed of the first utterance in response to detecting that the portion of the second utterance has been spoken by the person, the sequence of images including a sequence of mouth shape images displayed such that the virtual object appears to speak the second utterance at the determined speed of the first utterance. 11. The method of claim 1 , wherein: the determining a speed at which the person spoke the first utterance includes determining an amount of time that the person took to speak a plurality of words corresponding with the first utterance. | 0.77176 |
7,546,527 | 1 | 2 | 1. A method for extracting data from a document formatted using a first markup language and presenting the extracted data using a second, different markup language, the method comprising: providing a content converter system operating as an interface between a client and a server, the content converter system including one or more templates for extracting data from documents, a template table associating each template with a network location identifier of a particular document and a particular target markup language, and a markup language application for reformatting the extracted data using a different markup language; receiving a content request from the client by the content converter system, said content request specifying a network location from which a specified document including formatted content in the first markup language can be retrieved, said content request further indicating the second target markup language; responsive to the content request, identifying a template which corresponds to said specified document and said target markup language using the template table, said template providing at least one content marker, wherein the at least one content marker indicates a data offset for identifying within the specified document one or more data fields containing information corresponding to at least one among a type of data and a particular action, wherein the template further specifies at least one among markup language tags, code, and additional text to associate with the information contained in a particular data field when presented in said target markup language, and wherein said template can be customized by a user to extract in one or more different combinations from the specified document information based upon the at least one content marker; retrieving said specified document from said specified network location; applying said template to said specified document and extracting data from said formatted content based upon the template, by: identifying a presentation order of the at least one content marker in said template; and extracting the information in said data fields from said specified document in accordance with the presentation order; and formatting said information by the markup language application of the content converter system for presentation in said presentation order based upon said associated markup language tags, code, and additional text specified in the template, wherein said formatting produces a second document formatted for presentation according to the second target markup language. | 1. A method for extracting data from a document formatted using a first markup language and presenting the extracted data using a second, different markup language, the method comprising: providing a content converter system operating as an interface between a client and a server, the content converter system including one or more templates for extracting data from documents, a template table associating each template with a network location identifier of a particular document and a particular target markup language, and a markup language application for reformatting the extracted data using a different markup language; receiving a content request from the client by the content converter system, said content request specifying a network location from which a specified document including formatted content in the first markup language can be retrieved, said content request further indicating the second target markup language; responsive to the content request, identifying a template which corresponds to said specified document and said target markup language using the template table, said template providing at least one content marker, wherein the at least one content marker indicates a data offset for identifying within the specified document one or more data fields containing information corresponding to at least one among a type of data and a particular action, wherein the template further specifies at least one among markup language tags, code, and additional text to associate with the information contained in a particular data field when presented in said target markup language, and wherein said template can be customized by a user to extract in one or more different combinations from the specified document information based upon the at least one content marker; retrieving said specified document from said specified network location; applying said template to said specified document and extracting data from said formatted content based upon the template, by: identifying a presentation order of the at least one content marker in said template; and extracting the information in said data fields from said specified document in accordance with the presentation order; and formatting said information by the markup language application of the content converter system for presentation in said presentation order based upon said associated markup language tags, code, and additional text specified in the template, wherein said formatting produces a second document formatted for presentation according to the second target markup language. 2. The method of claim 1 , wherein said extracted information is unformatted data. | 0.877976 |
7,562,289 | 2 | 11 | 2. The method of claim 1 , further comprising: generating at least one annotation associated with non-graphic information; storing the at least one annotation in the at least one electronic graphics file, where the at least one annotation is associated with at least one geographic position in the at least one electronic graphic file; receiving at least one selection of the at least one annotation, and displaying the non-graphic information associated with the at least one geographic position. | 2. The method of claim 1 , further comprising: generating at least one annotation associated with non-graphic information; storing the at least one annotation in the at least one electronic graphics file, where the at least one annotation is associated with at least one geographic position in the at least one electronic graphic file; receiving at least one selection of the at least one annotation, and displaying the non-graphic information associated with the at least one geographic position. 11. The method of claim 2 , wherein the at least one annotation comprises: at least one hyperlink to at least one database in communication with at least one network, textual information associated with at least one geographical feature in the at least one electronic graphics file, or textual information associated with at least one object in the at least one electronic graphics file, or any combination thereof. | 0.5 |
8,086,460 | 12 | 14 | 12. A speech-enabled application served by a Web 2.0 server, wherein said speech-enabled application is stored in a non-transitory storage medium and is configured to be run by a browser, said speech enabled application comprising: a plurality of linked markup documents together comprising a speech-enabled application served by a Web 2.0 server, said plurality of linked markup documents conforming to an ATOM PUBLISHING PROTOCOL (APP) based protocol, said linked markup documents including an entry collection of documents and a resource collection of documents, wherein said entry collection comprise content of the speech-enabled application, and wherein the resource collection comprises computing resources used in conjunction with the content, wherein each entry of the entry collection specifies a set of resource entries of the resource collection, wherein each resources of the resource collection that correspond to content of the entry collection that are automatically activated when said content is activated, wherein said resource collection comprising at least one speech resource associated with a speech engine disposed in a speech processing system remotely located from the Web 2.0 server, wherein said speech resource adds a speech processing capability to the speech-enabled application. | 12. A speech-enabled application served by a Web 2.0 server, wherein said speech-enabled application is stored in a non-transitory storage medium and is configured to be run by a browser, said speech enabled application comprising: a plurality of linked markup documents together comprising a speech-enabled application served by a Web 2.0 server, said plurality of linked markup documents conforming to an ATOM PUBLISHING PROTOCOL (APP) based protocol, said linked markup documents including an entry collection of documents and a resource collection of documents, wherein said entry collection comprise content of the speech-enabled application, and wherein the resource collection comprises computing resources used in conjunction with the content, wherein each entry of the entry collection specifies a set of resource entries of the resource collection, wherein each resources of the resource collection that correspond to content of the entry collection that are automatically activated when said content is activated, wherein said resource collection comprising at least one speech resource associated with a speech engine disposed in a speech processing system remotely located from the Web 2.0 server, wherein said speech resource adds a speech processing capability to the speech-enabled application. 14. The speech-enabled application of claim 12 , wherein the Web 2.0 server is a WIKI server that includes a WIKI editor interface, which permits users to input WIKI syntax that a transformer of the WIKI server automatically converts to VoiceXML, wherein the WIKI server is able to access resources of the speech processing engine through use of a set of RESTful commands comprising GET, PUT, POST, and DELETE. | 0.602713 |
9,442,968 | 13 | 15 | 13. A non-transitory computer readable medium storing instructions that, when executed by a processor, perform a variant configuration method comprising: loading a dependency tree comprising Boolean expressions describing an input selection condition into memory in one of disjunctive normal form (DNF) and conjunctive normal form (CNF); joining concrete configuration values from input configuration data with the dependency tree, and comparing values of one or more literals; aggregating the comparison results and aggregating the aggregation results, using an AND-group with a minimum function and an OR-group with a maximum function in an alternating sequence ordered corresponding to the chosen normal form; and outputting the result of the selection condition evaluation for the concrete configuration; wherein each separate branch of the dependency tree comprises Boolean expressions selectively cast in one of DNF and CNF according to which normal form most reduces the number of Boolean expressions in each branch. | 13. A non-transitory computer readable medium storing instructions that, when executed by a processor, perform a variant configuration method comprising: loading a dependency tree comprising Boolean expressions describing an input selection condition into memory in one of disjunctive normal form (DNF) and conjunctive normal form (CNF); joining concrete configuration values from input configuration data with the dependency tree, and comparing values of one or more literals; aggregating the comparison results and aggregating the aggregation results, using an AND-group with a minimum function and an OR-group with a maximum function in an alternating sequence ordered corresponding to the chosen normal form; and outputting the result of the selection condition evaluation for the concrete configuration; wherein each separate branch of the dependency tree comprises Boolean expressions selectively cast in one of DNF and CNF according to which normal form most reduces the number of Boolean expressions in each branch. 15. The medium of claim 13 further comprising instructions for generalizing the dependency tree to evaluate added terms comprising at least one of a non-fixed-value literal, a multi-valued literal, an in-list, and a variant table, by translating and integrating each added term into the sequence of aggregations. | 0.5 |
7,613,602 | 5 | 8 | 5. A structured document search apparatus comprising: a connection unit connectable to a structured document processing apparatus that stores a structure model tree indicating a typical structure of a structured document, and frequency-of-occurrence information indicating locations of each of lexical items included in the structured document; a reception unit configured to receive query data which is described in a query language and is required to generate a new composite document formed of partial structures of a plurality of structured documents; a parsing unit configured to parse the query data including elements; a query graph generation unit configured to generate a query graph indicating a relationship among the elements based on the parsed query data; a selection unit configured to select, based on the frequency-of-occurrence information and the query graph, a similar structure similar to the structure model tree from the structured document processing apparatus; a storage unit configured to store similarities indicating similar levels between lexical items; a calculation unit configured to calculate a structure score value indicating a similar degree of the selected similar structure based on the similarities; a cost calculation unit configured to calculate a plurality of processing costs for selecting plans indicating processing orders of elements based on the frequency-of-occurrence information; a selection unit configured to select, from the plans, a plan which has a lowest processing cost of the calculated processing costs; a priority calculation unit configured to calculate processing priority levels of a plurality of processes for making the plan based on the lowest processing cost and the structure score values; a processing execution unit configured to execute the processes in descending order of the processing priority levels; and a result acquisition unit configured to acquire execution results of execution of the plurality of processes as search results. | 5. A structured document search apparatus comprising: a connection unit connectable to a structured document processing apparatus that stores a structure model tree indicating a typical structure of a structured document, and frequency-of-occurrence information indicating locations of each of lexical items included in the structured document; a reception unit configured to receive query data which is described in a query language and is required to generate a new composite document formed of partial structures of a plurality of structured documents; a parsing unit configured to parse the query data including elements; a query graph generation unit configured to generate a query graph indicating a relationship among the elements based on the parsed query data; a selection unit configured to select, based on the frequency-of-occurrence information and the query graph, a similar structure similar to the structure model tree from the structured document processing apparatus; a storage unit configured to store similarities indicating similar levels between lexical items; a calculation unit configured to calculate a structure score value indicating a similar degree of the selected similar structure based on the similarities; a cost calculation unit configured to calculate a plurality of processing costs for selecting plans indicating processing orders of elements based on the frequency-of-occurrence information; a selection unit configured to select, from the plans, a plan which has a lowest processing cost of the calculated processing costs; a priority calculation unit configured to calculate processing priority levels of a plurality of processes for making the plan based on the lowest processing cost and the structure score values; a processing execution unit configured to execute the processes in descending order of the processing priority levels; and a result acquisition unit configured to acquire execution results of execution of the plurality of processes as search results. 8. The apparatus according to claim 5 , wherein the structured document processing apparatus further stores respective relevant lexical identifiers of the lexical items, assigns structure model tree identifiers to a plurality of nodes of a structure model tree, and assigns a structure model tree identifier of a node where one of the relevant lexical identifiers occurs most frequently as a relevant structure model tree identifier, the structured document search apparatus further comprises a lexical score value assigning unit configured to assign a relative value of one of the lexical items to each of the lexical items as a lexical score value based on the relevant lexical identifiers and the relevant structure model tree identifiers, the value increasing with an increase of number of the lexical items having an identical relevant lexical identifier which matches with the lexical items having an identical relevant structure model tree identifier, and wherein when the query language conducts search processing including a plurality of keywords, and when combining processing of index information is executed in the search processing, the priority calculation unit calculates the priority processing levels of the processes for making the plan based on the lexical score values, the lowest processing cost, and the structure score values. | 0.5 |
7,831,911 | 1 | 11 | 1. A computer-implemented method of ranking replacement target strings for a misspelled source string, the computer-implemented method comprising: converting the misspelled source string into a source phoneme sequence using a letter-to-sound system; utilizing a computer processor that is a component of the computer to traverse at least one phoneme-based trie structure so as to select a plurality of different candidate phoneme sequences based on a comparison of phonemes in the phoneme-based trie structure to the source phoneme sequence but without doing a direct comparison of every component of the plurality of different candidate phoneme sequences to a component of the source phoneme sequence; generating a count for each different candidate phoneme sequence in said plurality of different candidate phoneme sequences, the count being indicative of a quantity of edit operations required to transform the candidate phoneme sequence into the source phoneme sequence; utilizing the computer processor to select a limited number of the plurality of different candidate phoneme sequences based at least in part on said counts, the limited number being less than all of the different candidate phoneme sequences included in said plurality of different candidate phoneme sequences; utilizing the computer processor to select a first set of replacement target strings, each replacement target string in the first set being selected based on direct correspondence to a candidate phoneme sequences in said limited number of different candidate phoneme sequences; utilizing the computer processor to traverse at least one letter-based trie structure so as to select a plurality of different candidate letter sequences, wherein selecting the plurality of different candidate letter sequences comprises traversing the letter-based trie structure so as to identify the plurality of different candidate letter sequences without doing a direct comparison of every component of the plurality of different candidate letter sequences with every component of the misspelled source string; utilizing the computer processor to select a limited number of the plurality of different candidate letter sequences based at least in part on a count of a quantity of edit operations required to transform each different candidate letter sequence included in the limited number of different candidate letter sequences into the misspelled source string, the limited number of different candidate letter sequences being less than all of the different candidate letter sequences included in said plurality of different candidate letter sequences; utilizing the computer processor to select a second set of replacement target strings, each replacement target string in the second set being one of the candidate letter sequences in said limited number of the plurality of different candidate letter sequences; and utilizing the computer processor to rank the replacement strings in the first and/or second sets based on a summation of the count of the quantity of edit operations required to transform a particular different candidate phoneme sequence included in the limited number of the plurality of different candidate phoneme sequences into the source phoneme sequence plus the count of the quantity of edit operations required to transform a particular different candidate letter sequence included in the limited number of the plurality of different candidate letter sequences into the misspelled source string. | 1. A computer-implemented method of ranking replacement target strings for a misspelled source string, the computer-implemented method comprising: converting the misspelled source string into a source phoneme sequence using a letter-to-sound system; utilizing a computer processor that is a component of the computer to traverse at least one phoneme-based trie structure so as to select a plurality of different candidate phoneme sequences based on a comparison of phonemes in the phoneme-based trie structure to the source phoneme sequence but without doing a direct comparison of every component of the plurality of different candidate phoneme sequences to a component of the source phoneme sequence; generating a count for each different candidate phoneme sequence in said plurality of different candidate phoneme sequences, the count being indicative of a quantity of edit operations required to transform the candidate phoneme sequence into the source phoneme sequence; utilizing the computer processor to select a limited number of the plurality of different candidate phoneme sequences based at least in part on said counts, the limited number being less than all of the different candidate phoneme sequences included in said plurality of different candidate phoneme sequences; utilizing the computer processor to select a first set of replacement target strings, each replacement target string in the first set being selected based on direct correspondence to a candidate phoneme sequences in said limited number of different candidate phoneme sequences; utilizing the computer processor to traverse at least one letter-based trie structure so as to select a plurality of different candidate letter sequences, wherein selecting the plurality of different candidate letter sequences comprises traversing the letter-based trie structure so as to identify the plurality of different candidate letter sequences without doing a direct comparison of every component of the plurality of different candidate letter sequences with every component of the misspelled source string; utilizing the computer processor to select a limited number of the plurality of different candidate letter sequences based at least in part on a count of a quantity of edit operations required to transform each different candidate letter sequence included in the limited number of different candidate letter sequences into the misspelled source string, the limited number of different candidate letter sequences being less than all of the different candidate letter sequences included in said plurality of different candidate letter sequences; utilizing the computer processor to select a second set of replacement target strings, each replacement target string in the second set being one of the candidate letter sequences in said limited number of the plurality of different candidate letter sequences; and utilizing the computer processor to rank the replacement strings in the first and/or second sets based on a summation of the count of the quantity of edit operations required to transform a particular different candidate phoneme sequence included in the limited number of the plurality of different candidate phoneme sequences into the source phoneme sequence plus the count of the quantity of edit operations required to transform a particular different candidate letter sequence included in the limited number of the plurality of different candidate letter sequences into the misspelled source string. 11. The method of claim 1 , wherein said particular different candidate phoneme sequence and said particular different candidate letter sequence correspond to a common replacement string, the common replacement string being included in both the first and second sets of replacement target strings. | 0.757749 |
8,914,395 | 14 | 15 | 14. The non-transitory computer-readable storage medium of claim 11 , wherein instructions for determining the respective ranking score, when the respective score is determined based on the search criterion, further comprise: instructions for determining a respective search factor that indicates frequency of appearance of the translation in the record of queries previously entered into the medical database; instructions for normalizing the respective search factor with respect to search factors determined for the other translations in the plurality of translations to produce a normalized search factor for the translation; and instructions for utilizing the normalized search factor for the translation as the ranking score for the translation. | 14. The non-transitory computer-readable storage medium of claim 11 , wherein instructions for determining the respective ranking score, when the respective score is determined based on the search criterion, further comprise: instructions for determining a respective search factor that indicates frequency of appearance of the translation in the record of queries previously entered into the medical database; instructions for normalizing the respective search factor with respect to search factors determined for the other translations in the plurality of translations to produce a normalized search factor for the translation; and instructions for utilizing the normalized search factor for the translation as the ranking score for the translation. 15. The non-transitory computer-readable storage medium of claim 14 , further comprising instructions for: requesting the user to provide feedback for the presented translation by indicating whether the translation is (i) adequate or (ii) not adequate; receiving the requested feedback from the user; and adjusting ranking scores for subsequent translations based on the received user feedback. | 0.5 |
8,787,702 | 4 | 7 | 4. The method of claim 3 , wherein determining if said page is inverted or non-inverted further includes: determining if additional lines of text of said page are to be processed; and following determining that no additional lines of text of said page are to be processed, making a decision as to whether said page is inverted or not inverted based on the value of said cumulative difference value. | 4. The method of claim 3 , wherein determining if said page is inverted or non-inverted further includes: determining if additional lines of text of said page are to be processed; and following determining that no additional lines of text of said page are to be processed, making a decision as to whether said page is inverted or not inverted based on the value of said cumulative difference value. 7. The method of claim 4 , further comprising: generating an estimate of the number of text characters that were processed in generating said cumulative difference value; and generating a confidence measure based on said estimate of the number of text characters that were processed. | 0.5 |
9,606,967 | 3 | 4 | 3. The method of claim 1 , further comprising providing said mark in a phantom document at a specific location with respect to borders and/or center of said phantom document. | 3. The method of claim 1 , further comprising providing said mark in a phantom document at a specific location with respect to borders and/or center of said phantom document. 4. The method of claim 3 , further comprising stretching said phantom document over said electronic document to delimit a border of the electronic document. | 0.5 |
9,576,242 | 1 | 20 | 1. A computer-based reasoning service platform comprising: an inquiry interface configured to receive an inquiry over a network, the inquiry associated with data objects of a data space; and at least one inference engine coupled with the inquiry interface and configured to: receive the inquiry from the inquiry interface; recognize at least two data objects of the data space based, at least in part, from the inquiry; select at least one reasoning rules set from available reasoning rules sets as a function of the data space and object attributes of the recognized at least two data objects; establish a hypothesized conclusion according to the at least one selected reasoning rules set, the hypothesized conclusion representing that the at least two data objects have a suspected correlation; and present the hypothesized conclusion and an associated advertisement to a user via a presentation module. | 1. A computer-based reasoning service platform comprising: an inquiry interface configured to receive an inquiry over a network, the inquiry associated with data objects of a data space; and at least one inference engine coupled with the inquiry interface and configured to: receive the inquiry from the inquiry interface; recognize at least two data objects of the data space based, at least in part, from the inquiry; select at least one reasoning rules set from available reasoning rules sets as a function of the data space and object attributes of the recognized at least two data objects; establish a hypothesized conclusion according to the at least one selected reasoning rules set, the hypothesized conclusion representing that the at least two data objects have a suspected correlation; and present the hypothesized conclusion and an associated advertisement to a user via a presentation module. 20. The platform of claim 1 , wherein the available reasoning rules sets include at least one of the following types of reasoning rules: inductive rules, deductive rules, abductive rules, ampliative reasoning rules, case-based reasoning rules, metaphorical mapping rules, forward chaining rules, backward chaining rules, analogical reasoning rules, cause-and-effect reasoning rules, defeasible reasoning rules, indefeasible reasoning rules, comparative reasoning rules, conditional reasoning rules, modal logic rules, set-based reasoning rules, systemic reasoning rules, syllogistic reasoning rules, probabilistic reasoning rules, and paraconsistent reasoning rules. | 0.5 |
8,433,698 | 13 | 14 | 13. A method of retrieving media objects associated with a query, the method being executed by a computer system and comprising: receiving a query including a first search term from a user; retrieving, based upon the query, at least one web page; generating a content analysis that describes a plurality of positional relationships between the first search term and terms within an individual one of the at least one web page; and retrieving, based upon the content analysis, at least one media object, wherein the generating comprises scoring, via the computer system, the plurality of positional relationships and the content analysis includes scoring information for the plurality of positional relationships. | 13. A method of retrieving media objects associated with a query, the method being executed by a computer system and comprising: receiving a query including a first search term from a user; retrieving, based upon the query, at least one web page; generating a content analysis that describes a plurality of positional relationships between the first search term and terms within an individual one of the at least one web page; and retrieving, based upon the content analysis, at least one media object, wherein the generating comprises scoring, via the computer system, the plurality of positional relationships and the content analysis includes scoring information for the plurality of positional relationships. 14. The method of claim 13 , wherein the at least one web page is retrieved using an internet search engine. | 0.687861 |
9,208,262 | 1 | 5 | 1. A computer-implemented method for providing a graphical representation of a plurality of items in a collaborative innovation environment, the method comprising: initiating a collaborative innovation process with a seed item wherein the seed item includes an idea, a question, an opinion or a statement for which a result is sought, and innovating one or more idea items directly or indirectly in response to the seed item to determine the result for the seed item based on the one or more idea items in the collaborative innovation process, wherein the seed item and the one or more idea items comprise a plurality of items; providing, by a processor to a device of a user, a list of a plurality of seed items in a graphical user interface; providing, by the processor to the device of the user in the graphical user interface, a graphical representation of the plurality of items including a seed item selected by the user from the plurality of seed items and one or more idea items innovated in response to the selected seed item, each item of the plurality of items having an association with at least one other item in the graphical representation, wherein each item of the plurality of items is represented by a shape and the association of each item with the at least one other item is represented by a line between each shape representing each item and each shape representing the at least one other item, wherein the line between each shape representing each item and each shape representing the at least one other item identifies whether the item is an idea item that was innovated from the at least one other item; receiving, by the processor from the device of the user, a request to associate a first metric of the plurality of items with a size of each shape representing each respective item, wherein the size of each shape is based on a first value of the first metric of each respective item; receiving, by the processor from the device of the user, a request to associate a second metric of the plurality of items with a color of each shape representing each respective item, wherein the color of each shape is based on a second value of the second metric of each respective item; transforming, by the processor, the graphical representation of the plurality of items such that the size of each shape representing each respective item is based on the first value of the first metric of each respective item and the color of each shape representing each respective item is based on the second value of the second metric of each respective item; transforming, by the processor, the plurality of items into a textual outline representation of the plurality of items; providing, by the processor to the device of the user, the transformed graphical representation and the textual outline representation of the plurality of items in the graphical user interface, wherein the transformed graphical representation of the plurality of items and the textual outline representation of the plurality of items are simultaneously displayed on the device of the user in a graphical representation display area and a textual outline display area respectively, wherein the graphical representation display area and the textual outline display area are each a responsive display area to each other; responsively, reflecting actions performed in either the graphical representation display area or the textual outline display area in the responsive display area of the other, including: creating an item innovated from one of the plurality of items in the responsive display area of the other in instances when one of the plurality of items is selected and when a selection is received from a user selection made in either the graphical representation display area or the textual outline display area; and receiving, by the processor from the device of the user, a request to search through a set of idea items of the plurality of items based on a characteristic of an idea item, wherein the set of idea items to be searched based on the characteristic is determined based on a user selection that indicates whether to search all of the one or more idea items or to search only a subset of the one or more idea items that have received a specified rating; moving a user-selected one item of the plurality of items having an association with the at least one other item in the graphical representation to a user-selected destination by: disassociating the user-selected one item of the plurality of items from an item it was innovated from; associating the user-selected one item of the plurality of items with another item based on user input; providing by the processor to the device of the user a preview for display of the graphical representation including the moved user-selected one item of the plurality of items to the destination item; and allowing the user to cancel or confirm the move of the user-selected one item of the plurality of items; wherein in response to a click of a move descendants button in a user interface by the user, including the descendants of the user-selected one item of the plurality of items in the moving of the user-selected one item of the plurality of items to the user-selected destination, and including the descendants of the moved user-selected one item of the plurality of items in the preview for display of the graphical representation; in response to a click of a like it button or a click of a don't like it button in the graphical user interface, entering a rating of a selected item in the graphical user interface; in response to a click of an enhance button in the graphical user interface allowing a user to create an item enhancing a selected item in the graphical user interface; in response to a click of an edit button in the graphical user interface allowing a user to edit a selected item in the graphical user interface; and in response to a click of a delete button in the graphical user interface deleting a selected item in the graphical user interface; wherein the graphical user interface includes the like it button, the don't like it button, the enhance button, the edit button and the delete button. | 1. A computer-implemented method for providing a graphical representation of a plurality of items in a collaborative innovation environment, the method comprising: initiating a collaborative innovation process with a seed item wherein the seed item includes an idea, a question, an opinion or a statement for which a result is sought, and innovating one or more idea items directly or indirectly in response to the seed item to determine the result for the seed item based on the one or more idea items in the collaborative innovation process, wherein the seed item and the one or more idea items comprise a plurality of items; providing, by a processor to a device of a user, a list of a plurality of seed items in a graphical user interface; providing, by the processor to the device of the user in the graphical user interface, a graphical representation of the plurality of items including a seed item selected by the user from the plurality of seed items and one or more idea items innovated in response to the selected seed item, each item of the plurality of items having an association with at least one other item in the graphical representation, wherein each item of the plurality of items is represented by a shape and the association of each item with the at least one other item is represented by a line between each shape representing each item and each shape representing the at least one other item, wherein the line between each shape representing each item and each shape representing the at least one other item identifies whether the item is an idea item that was innovated from the at least one other item; receiving, by the processor from the device of the user, a request to associate a first metric of the plurality of items with a size of each shape representing each respective item, wherein the size of each shape is based on a first value of the first metric of each respective item; receiving, by the processor from the device of the user, a request to associate a second metric of the plurality of items with a color of each shape representing each respective item, wherein the color of each shape is based on a second value of the second metric of each respective item; transforming, by the processor, the graphical representation of the plurality of items such that the size of each shape representing each respective item is based on the first value of the first metric of each respective item and the color of each shape representing each respective item is based on the second value of the second metric of each respective item; transforming, by the processor, the plurality of items into a textual outline representation of the plurality of items; providing, by the processor to the device of the user, the transformed graphical representation and the textual outline representation of the plurality of items in the graphical user interface, wherein the transformed graphical representation of the plurality of items and the textual outline representation of the plurality of items are simultaneously displayed on the device of the user in a graphical representation display area and a textual outline display area respectively, wherein the graphical representation display area and the textual outline display area are each a responsive display area to each other; responsively, reflecting actions performed in either the graphical representation display area or the textual outline display area in the responsive display area of the other, including: creating an item innovated from one of the plurality of items in the responsive display area of the other in instances when one of the plurality of items is selected and when a selection is received from a user selection made in either the graphical representation display area or the textual outline display area; and receiving, by the processor from the device of the user, a request to search through a set of idea items of the plurality of items based on a characteristic of an idea item, wherein the set of idea items to be searched based on the characteristic is determined based on a user selection that indicates whether to search all of the one or more idea items or to search only a subset of the one or more idea items that have received a specified rating; moving a user-selected one item of the plurality of items having an association with the at least one other item in the graphical representation to a user-selected destination by: disassociating the user-selected one item of the plurality of items from an item it was innovated from; associating the user-selected one item of the plurality of items with another item based on user input; providing by the processor to the device of the user a preview for display of the graphical representation including the moved user-selected one item of the plurality of items to the destination item; and allowing the user to cancel or confirm the move of the user-selected one item of the plurality of items; wherein in response to a click of a move descendants button in a user interface by the user, including the descendants of the user-selected one item of the plurality of items in the moving of the user-selected one item of the plurality of items to the user-selected destination, and including the descendants of the moved user-selected one item of the plurality of items in the preview for display of the graphical representation; in response to a click of a like it button or a click of a don't like it button in the graphical user interface, entering a rating of a selected item in the graphical user interface; in response to a click of an enhance button in the graphical user interface allowing a user to create an item enhancing a selected item in the graphical user interface; in response to a click of an edit button in the graphical user interface allowing a user to edit a selected item in the graphical user interface; and in response to a click of a delete button in the graphical user interface deleting a selected item in the graphical user interface; wherein the graphical user interface includes the like it button, the don't like it button, the enhance button, the edit button and the delete button. 5. The computer-implemented method of claim 1 wherein the color of each shape becomes a first color as the second value of the second metric of each item increases and the color of each shape becomes a second color as the second value of the second metric of each item decreases. | 0.833731 |
9,591,065 | 13 | 22 | 13. One or more non-transitory machine-readable storage media storing instructions that are executable by a device associated with an apparatus to perform operations comprising: receiving a script from a processing device, the script containing simple object access protocol (SOAP) commands for execution, the script defining one or more variables that are used in execution of the script, at least some of the SOAP commands in the script including corresponding arguments; interpreting the script to execute functions contained in the script; parsing the SOAP commands from the script during execution of the functions; executing the SOAP commands; wherein the apparatus is configured by execution of the SOAP commands and the functions; and wherein the execution of the SOAP commands and the functions comprises passing a variable in the script as an argument to a first SOAP command, returning an output of the first SOAP command to the script, and executing a second SOAP command based on the output. | 13. One or more non-transitory machine-readable storage media storing instructions that are executable by a device associated with an apparatus to perform operations comprising: receiving a script from a processing device, the script containing simple object access protocol (SOAP) commands for execution, the script defining one or more variables that are used in execution of the script, at least some of the SOAP commands in the script including corresponding arguments; interpreting the script to execute functions contained in the script; parsing the SOAP commands from the script during execution of the functions; executing the SOAP commands; wherein the apparatus is configured by execution of the SOAP commands and the functions; and wherein the execution of the SOAP commands and the functions comprises passing a variable in the script as an argument to a first SOAP command, returning an output of the first SOAP command to the script, and executing a second SOAP command based on the output. 22. The one or more non-transitory machine-readable storage media of claim 13 , wherein parsing is performed by an XML interpreter and executing is performed by a SOAP interpreter, the XML interpreter passing the SOAP commands to the SOAP interpreter and the SOAP interpreter passing outputs of the SOAP commands to the XML interpreter. | 0.5 |
8,361,117 | 15 | 16 | 15. The spinal cross connector of claim 1 , wherein the retaining element is disposed within a bore formed in the male member. | 15. The spinal cross connector of claim 1 , wherein the retaining element is disposed within a bore formed in the male member. 16. The spinal cross connector of claim 15 , wherein the retaining element is threadably engaged with the bore. | 0.5 |
8,386,405 | 1 | 7 | 1. A method for interacting with a user, the method performed by a computer having access to an electronic knowledge database, the method comprising: automatically with the computer (a) generating a structured representation of a received user input; (b) comparing the structured representation of the received user input with each of a plurality of expected user statement fields that are entries in the electronic knowledge database, and are associated with respective action fields specifying at least one action; and (c) when one of the plurality of expected user statements fields matches the structured representation of the received user inputs, causing the at least one action specified by the action field associated with the matching one of the plurality of expected user statement fields to be performed; the method further comprising: (i) when a match is identified in part (c), generating a second structural representation of a second received user input; and (ii) comparing the second structured representation of the second received user input with a second plurality of expected user statement fields that are entries in the electronic knowledge database and are associated with respective actions fields specifying at least one action: (A) wherein the entries of the knowledge database are arranged in a hierarchical structure; (B) wherein each entry in the electronic knowledge database also comprises an associated identification field indicative of a position in the hierarchical structure; and (C) wherein all the positions indicated by the identification fields associated with the second plurality of expected user statement fields substantially match; and (iii) when one of the second plurality of expected user statements fields matches the second structured representation of the second received user input, causing the at least one action specified by the action field associated with the matching one of the second plurality of expected user statement fields to be performed. | 1. A method for interacting with a user, the method performed by a computer having access to an electronic knowledge database, the method comprising: automatically with the computer (a) generating a structured representation of a received user input; (b) comparing the structured representation of the received user input with each of a plurality of expected user statement fields that are entries in the electronic knowledge database, and are associated with respective action fields specifying at least one action; and (c) when one of the plurality of expected user statements fields matches the structured representation of the received user inputs, causing the at least one action specified by the action field associated with the matching one of the plurality of expected user statement fields to be performed; the method further comprising: (i) when a match is identified in part (c), generating a second structural representation of a second received user input; and (ii) comparing the second structured representation of the second received user input with a second plurality of expected user statement fields that are entries in the electronic knowledge database and are associated with respective actions fields specifying at least one action: (A) wherein the entries of the knowledge database are arranged in a hierarchical structure; (B) wherein each entry in the electronic knowledge database also comprises an associated identification field indicative of a position in the hierarchical structure; and (C) wherein all the positions indicated by the identification fields associated with the second plurality of expected user statement fields substantially match; and (iii) when one of the second plurality of expected user statements fields matches the second structured representation of the second received user input, causing the at least one action specified by the action field associated with the matching one of the second plurality of expected user statement fields to be performed. 7. The method according to claim 1 wherein at least one of the plurality of expected statement fields comprises at least one expected user statement expressed in natural language. | 0.917053 |
9,626,358 | 1 | 7 | 1. A method, comprising: receiving a plurality of semantic structures associated with a text corpus; identifying, by a processing device, a first semantic structure and a second semantic structure, wherein the first semantic structure comprises a first substructure and a second substructure, wherein the second semantic structure comprises a third substructure and a fourth substructure, and wherein the first substructure is similar to the third substructure in view of a first similarity criterion; and responsive to determining that the second substructure is similar to the fourth substructure in view of a second similarity criterion, associating, with a certain concept of an ontology associated with the text corpus, objects represented by the second substructure and the fourth substructure. | 1. A method, comprising: receiving a plurality of semantic structures associated with a text corpus; identifying, by a processing device, a first semantic structure and a second semantic structure, wherein the first semantic structure comprises a first substructure and a second substructure, wherein the second semantic structure comprises a third substructure and a fourth substructure, and wherein the first substructure is similar to the third substructure in view of a first similarity criterion; and responsive to determining that the second substructure is similar to the fourth substructure in view of a second similarity criterion, associating, with a certain concept of an ontology associated with the text corpus, objects represented by the second substructure and the fourth substructure. 7. The method of claim 1 , wherein identifying the first semantic structure and the second semantic structure comprises comparing a first plurality of semantic classes associated with a first plurality of nodes of a first graph representing the first semantic structure to a second plurality of semantic classes associated with a second plurality of nodes of a second graph representing the second semantic structure. | 0.587945 |
8,572,099 | 5 | 8 | 5. The computer-implemented method of claim 1 , further comprising selecting the labels based on the content associated with the portion of the users on the social network. | 5. The computer-implemented method of claim 1 , further comprising selecting the labels based on the content associated with the portion of the users on the social network. 8. The computer-implemented method of claim 5 , wherein the labels comprise one or more categories of content that are identified from the content. | 0.643204 |
4,504,925 | 3 | 11 | 3. A stack according to claim 2, wherein the control cells are interconnected for communicating the storage state of the corresponding data storage cells to and from the adjacent control cells; and wherein each (n)th control cell in the array from the top of the stack includes a cell-state flip-flop for providing indication signals indicating the storage state of the (n)th data storage cell; a first control gate connected to the push gate between the (n)th data storage cell and the (n+1)th data storage cell for providing a push signal to said push gate in response to indication signals from the cell-state flip-flop of the (n)th control cell indicating that the (n)th data storage cell is full, from the cell-state flip-flop of the (n+1) the control cell indicating that the (n+1)th data storage cell is empty, and from the cell-state flip-flop of the (n-1)th control cell indicating that the (n-1)th data storage cell is full; and a second control gate connected to the pop gate between the (n)th data storage cell and the (n+1)th data storage cell for providing a pop signal to said pop gate in response to indication signals from the cell-state flip-flop of the (n)th control cell indicating that the (n)th data storage cell is empty, from the cell-state flip-flop of the (n+1)th control cell indicating that the (n+1)th data storage cell is full, and from the cell-state flip-flop of the (n-1)th control cell indicating that the (n-1)th data storage cell is empty. | 3. A stack according to claim 2, wherein the control cells are interconnected for communicating the storage state of the corresponding data storage cells to and from the adjacent control cells; and wherein each (n)th control cell in the array from the top of the stack includes a cell-state flip-flop for providing indication signals indicating the storage state of the (n)th data storage cell; a first control gate connected to the push gate between the (n)th data storage cell and the (n+1)th data storage cell for providing a push signal to said push gate in response to indication signals from the cell-state flip-flop of the (n)th control cell indicating that the (n)th data storage cell is full, from the cell-state flip-flop of the (n+1) the control cell indicating that the (n+1)th data storage cell is empty, and from the cell-state flip-flop of the (n-1)th control cell indicating that the (n-1)th data storage cell is full; and a second control gate connected to the pop gate between the (n)th data storage cell and the (n+1)th data storage cell for providing a pop signal to said pop gate in response to indication signals from the cell-state flip-flop of the (n)th control cell indicating that the (n)th data storage cell is empty, from the cell-state flip-flop of the (n+1)th control cell indicating that the (n+1)th data storage cell is full, and from the cell-state flip-flop of the (n-1)th control cell indicating that the (n-1)th data storage cell is empty. 11. A stack according to claim 3, wherein the control cell corresponding to the top data storage cell in the stack comprises a cell-state flip-flop for providing indication signals indicating the storage state of the top data storage cell; a first control state connected to the push gate between the top data storage cell and the second data storage cell for providing a push signal to said push gate in response to an external push stack signal and indication signals from the cell-state flip-flop of the top control cell indicating that the top data storage cell is full and from the cell-state flip-flop of the second control cell indicating that the second data storage is empty; and a second control gate connected to the pop gate between the top date storage cell and the second data storage cell for providing a pop signal to said pop gate in response to an external pop stack signal and indication signals from the cell state flip-flop of the top control cell indicating that the top data storage cell is empty and from the cell-state flip-flop of the second control cell indicating that the second data storage cell is full. | 0.5 |
8,412,714 | 1 | 2 | 1. A method of adaptively evaluating a top-k query with respect to a document, the method comprising: relaxing an original query to form a relaxed query, the original query comprising a tree structure having a plurality of query nodes; based on the relaxed query, forming a plurality of servers, each server corresponding to a respective query node in the tree structure and having a respective server queue configured to store candidate answers that constitute one of partial answers and final answers; processing the candidate answers in the server queues by steps including: adaptively choosing a winning server, from the plurality of servers, that is likely to produce fewest candidate answers after pruning against a top-k set and to whose queue a current candidate answer should be sent; sending the current candidate answer to the winning server's queue; adaptively choosing a next candidate answer to process from among candidate answers in the winning server's queue by selecting an answer with a maximum possible next score, the maximum possible next score determined by adding a current score of the answer to a maximum possible score the answer could receive from its current server; computing a join between the current candidate answer and next candidate answers at the winning server, so as to produce a new current candidate answer; and updating the top-k set with the new current candidate answer only if a score of the new current candidate answer exceeds a score of a top-k answer in a top-k set; and providing the top-k set as an evaluation of the top-k query; wherein the candidate answers include fragments of the document that are less than the entire document and the score of each candidate answer is calculated by calculating scores of progressively smaller fragments of the query that are matched by each candidate answer to be correspondingly smaller scores, the candidate answers including a complete answer to the relaxed query and satisfying all requirements of the relaxed query but satisfying less than all requirements of the original query. | 1. A method of adaptively evaluating a top-k query with respect to a document, the method comprising: relaxing an original query to form a relaxed query, the original query comprising a tree structure having a plurality of query nodes; based on the relaxed query, forming a plurality of servers, each server corresponding to a respective query node in the tree structure and having a respective server queue configured to store candidate answers that constitute one of partial answers and final answers; processing the candidate answers in the server queues by steps including: adaptively choosing a winning server, from the plurality of servers, that is likely to produce fewest candidate answers after pruning against a top-k set and to whose queue a current candidate answer should be sent; sending the current candidate answer to the winning server's queue; adaptively choosing a next candidate answer to process from among candidate answers in the winning server's queue by selecting an answer with a maximum possible next score, the maximum possible next score determined by adding a current score of the answer to a maximum possible score the answer could receive from its current server; computing a join between the current candidate answer and next candidate answers at the winning server, so as to produce a new current candidate answer; and updating the top-k set with the new current candidate answer only if a score of the new current candidate answer exceeds a score of a top-k answer in a top-k set; and providing the top-k set as an evaluation of the top-k query; wherein the candidate answers include fragments of the document that are less than the entire document and the score of each candidate answer is calculated by calculating scores of progressively smaller fragments of the query that are matched by each candidate answer to be correspondingly smaller scores, the candidate answers including a complete answer to the relaxed query and satisfying all requirements of the relaxed query but satisfying less than all requirements of the original query. 2. The method of claim 1 , wherein: the document is expressed in a nested-structure, document-specific markup language; and the query further comprises: links that are associated with join conditions that define relationships among the query nodes as being children, parents, ancestors or descendants of each other; and a query root node that represents answers to be returned. | 0.66158 |
8,996,459 | 17 | 18 | 17. The system as recited in claim 12 , wherein the application is defined by an application package, wherein the application package includes a list of the indicated set of resources. | 17. The system as recited in claim 12 , wherein the application is defined by an application package, wherein the application package includes a list of the indicated set of resources. 18. The system as recited in claim 17 , wherein multiple concurrently running instances of an application share a single application package to conserve resources. | 0.5 |
7,791,592 | 1 | 6 | 1. A method for inputting characters in an electronic device having a user input device, a display for displaying characters input through the user input device, and a memory for storing characters input through the user input device, comprising: selecting a set of characters on the display; receiving an input character, the input character being an opening character of a predefined character pair through the user input device; and automatically adding to the memory and displaying on the display both the opening character and a corresponding closing character of the predefined character pair, the opening character being displayed before the selected set of characters, and the corresponding closing character being displayed after the selected set of characters. | 1. A method for inputting characters in an electronic device having a user input device, a display for displaying characters input through the user input device, and a memory for storing characters input through the user input device, comprising: selecting a set of characters on the display; receiving an input character, the input character being an opening character of a predefined character pair through the user input device; and automatically adding to the memory and displaying on the display both the opening character and a corresponding closing character of the predefined character pair, the opening character being displayed before the selected set of characters, and the corresponding closing character being displayed after the selected set of characters. 6. The method of claim 1 further comprising the step of receiving a plurality of successive character inputs through the user input device; and determining if the plurality of successive character inputs correspond to an opening character sequence of a predetermined character sequence pair, and if so, adding to the memory and displaying on the display both the opening character sequence and a corresponding closing character sequence of the character sequence pair. | 0.5 |
7,668,888 | 26 | 40 | 26. A computer program product stored on a computer readable medium, the computer program product providing at least one readable object that is readable by a search engine from at least one structured data object stored in a database, the product comprising instructions configured to cause a processor to: extract the structured data object from the database, wherein the structured data object includes a hierarchical sequence of nodes related by at least one link and a plurality of content, and wherein at least one content of the plurality of content is nonreadable content that cannot be read by the search engine; map the structured data object into a generic data model according to the hierarchical sequence of nodes and content; and create the readable object from the generic data model, wherein creating includes converting the nonreadable content of the structured data object into readable content for the search engine. | 26. A computer program product stored on a computer readable medium, the computer program product providing at least one readable object that is readable by a search engine from at least one structured data object stored in a database, the product comprising instructions configured to cause a processor to: extract the structured data object from the database, wherein the structured data object includes a hierarchical sequence of nodes related by at least one link and a plurality of content, and wherein at least one content of the plurality of content is nonreadable content that cannot be read by the search engine; map the structured data object into a generic data model according to the hierarchical sequence of nodes and content; and create the readable object from the generic data model, wherein creating includes converting the nonreadable content of the structured data object into readable content for the search engine. 40. The computer program product of claim 26 , wherein the instructions configured to cause the processor to create the readable object from the generic data model include instructions configured to cause the processor to create one the readable object for each node mapped for the structured data object within the generic data model. | 0.600239 |
9,786,284 | 1 | 10 | 1. A computing device comprising: one or more computer processors; one or more computer-readable media having instructions stored thereon that, responsive to execution by the one or more computer processors, perform operations comprising: determining, based on one speech waveform, a wideband speech feature and a narrowband speech feature; determining, based on the wideband speech feature, an estimate of the narrowband speech feature; determining, based on the narrowband speech feature and the estimate of the narrowband speech feature, an estimation error of the estimate of the narrowband speech feature; transmitting the wideband speech feature and the estimation error to a remote entity; receiving, from the remote entity, data associated with a speech-based service based on the wideband speech feature; and outputting, by the computing device, speech recognition results for the one speech waveform based on the received data associated with the speech-based service. | 1. A computing device comprising: one or more computer processors; one or more computer-readable media having instructions stored thereon that, responsive to execution by the one or more computer processors, perform operations comprising: determining, based on one speech waveform, a wideband speech feature and a narrowband speech feature; determining, based on the wideband speech feature, an estimate of the narrowband speech feature; determining, based on the narrowband speech feature and the estimate of the narrowband speech feature, an estimation error of the estimate of the narrowband speech feature; transmitting the wideband speech feature and the estimation error to a remote entity; receiving, from the remote entity, data associated with a speech-based service based on the wideband speech feature; and outputting, by the computing device, speech recognition results for the one speech waveform based on the received data associated with the speech-based service. 10. A computing device as described in claim 1 , wherein the speech recognition results are further processed by search, navigation, translation, or social networking services prior to being received by the computing device. | 0.702128 |
8,805,686 | 9 | 22 | 9. The method of claim 1 , applied to matching the likely word instances to catalog entries, the method further including: accessing a catalog of phrases sets each comprising multiple phrase representations; for each phrase representation, searching the reported subset of likely word instances for likely occurrences of each phrase and scoring each likely phrase occurrence for a probability of a match between the phrase and the utterance; wherein the subset of likely word instances is searched by multiple processors operating on the multiple phrase sets; and reporting at least a subset of likely phrase occurrences and respective probability scores for further processing. | 9. The method of claim 1 , applied to matching the likely word instances to catalog entries, the method further including: accessing a catalog of phrases sets each comprising multiple phrase representations; for each phrase representation, searching the reported subset of likely word instances for likely occurrences of each phrase and scoring each likely phrase occurrence for a probability of a match between the phrase and the utterance; wherein the subset of likely word instances is searched by multiple processors operating on the multiple phrase sets; and reporting at least a subset of likely phrase occurrences and respective probability scores for further processing. 22. The method of claim 9 , wherein the scoring further includes normalizing partial scores accumulated while applying the dynamic programming, whereby the scores for the likely word instances can be meaningfully compared between the likely word instances that match shorter and longer parts of the utterance. | 0.60687 |
8,332,383 | 26 | 35 | 26. The computer-implemented method of claim 25 , wherein each of the search definitions is formulated to include a constraint set that is unique, and wherein the constraints of the constraint set are selected from a group including a keyword constraint, a category constraint, a search parameter constraint, and an attribute constraint. | 26. The computer-implemented method of claim 25 , wherein each of the search definitions is formulated to include a constraint set that is unique, and wherein the constraints of the constraint set are selected from a group including a keyword constraint, a category constraint, a search parameter constraint, and an attribute constraint. 35. The computer implemented method of claim 26 , including determining whether a constraint set associated with an excluded constraint corresponds to a count of data items that equals a count of data items associated with a constraint set without an excluded constraint, and if so, not displaying the search definition associated with the excluded constraint. | 0.5 |
9,424,559 | 8 | 14 | 8. A computer program product residing on a non-transitory computer readable storage medium having a plurality of instructions stored thereon, which, when executed by a processor, cause the processor to perform operations comprising: generating a specific calendar event that is addressed to a plurality of calendar event recipients, said calendar event being an event scheduled to occur at a future time for a plurality of participants and recorded in an electronic calendar in a calendaring application, said calendar event recipients receiving an electronic notification of said calendar event via a computer network; generating a designation of a subset of the plurality of calendar event recipients as first annotation recipients, such that, with respect to the specific calendar event, there are both general event recipients and first annotation recipients; and associating a first annotation with the calendar event, the first annotation comprising information additional to the calendar event as originally created and being addressed to the first annotation recipients, such that, with respect to the specific calendar event, all recipients are sent the electronic notification, but the first annotation is sent only to the designated subset of recipients for that calendar event. | 8. A computer program product residing on a non-transitory computer readable storage medium having a plurality of instructions stored thereon, which, when executed by a processor, cause the processor to perform operations comprising: generating a specific calendar event that is addressed to a plurality of calendar event recipients, said calendar event being an event scheduled to occur at a future time for a plurality of participants and recorded in an electronic calendar in a calendaring application, said calendar event recipients receiving an electronic notification of said calendar event via a computer network; generating a designation of a subset of the plurality of calendar event recipients as first annotation recipients, such that, with respect to the specific calendar event, there are both general event recipients and first annotation recipients; and associating a first annotation with the calendar event, the first annotation comprising information additional to the calendar event as originally created and being addressed to the first annotation recipients, such that, with respect to the specific calendar event, all recipients are sent the electronic notification, but the first annotation is sent only to the designated subset of recipients for that calendar event. 14. The computer program product of claim 8 , wherein said subset of calendar event recipients is designated based on at least one common attribute that is common to the recipients designated to the subset. | 0.692537 |
7,809,719 | 1 | 3 | 1. A computer readable storage medium including executable instructions which, when executed, assist a user by: receiving input associated with a user operation; storing the input in a store component in a chronological order; predicting a number of textual candidates based in part on the user operation and a number of preceding textual words in the store component, wherein the predicting comprises: determining a number of textual candidate probabilities, wherein each textual candidate probability is based in part on a first quantity that corresponds with a number of times the textual candidate follows the number of preceding textual words in the store component and the number of times that the number of preceding textual words occur in the store component and a second quantity that corresponds with a number of times the textual candidate is observed in the store component and the total number of words in the store component; selecting a number of top textual candidates based on the textual candidate probabilities; determining adjusted probabilities of the selected top textual candidates, wherein each adjusted candidate probability is based in part on a candidate rank function multiplied by a first variable and an associated textual candidate probability multiplied by a second variable, wherein the candidate rank function is based in part on a third quantity that corresponds with the selected top textual candidate rank values; and displaying the selected number of top textual candidates ranked by the adjusted candidate probabilities. | 1. A computer readable storage medium including executable instructions which, when executed, assist a user by: receiving input associated with a user operation; storing the input in a store component in a chronological order; predicting a number of textual candidates based in part on the user operation and a number of preceding textual words in the store component, wherein the predicting comprises: determining a number of textual candidate probabilities, wherein each textual candidate probability is based in part on a first quantity that corresponds with a number of times the textual candidate follows the number of preceding textual words in the store component and the number of times that the number of preceding textual words occur in the store component and a second quantity that corresponds with a number of times the textual candidate is observed in the store component and the total number of words in the store component; selecting a number of top textual candidates based on the textual candidate probabilities; determining adjusted probabilities of the selected top textual candidates, wherein each adjusted candidate probability is based in part on a candidate rank function multiplied by a first variable and an associated textual candidate probability multiplied by a second variable, wherein the candidate rank function is based in part on a third quantity that corresponds with the selected top textual candidate rank values; and displaying the selected number of top textual candidates ranked by the adjusted candidate probabilities. 3. The computer-readable storage medium of claim 1 , wherein the instructions, when executed, assist a user by predicting the number of textual candidates including using data in a textual store to determine a number of recent words and using a threshold when suggesting the number of suggested textual candidates. | 0.865004 |
9,129,305 | 1 | 9 | 1. A system for generating targeted advertisement recommendations, the system comprising: under control of a hardware processor: a data aggregation module configured to obtain a plurality of words from a social network; a relationship mining module in communication with the data aggregation module, the relationship mining module configured to create word relationships between selected ones of the plurality of words to produce relationship data, each of the word relationships reflecting a degree of association between two or more of the selected words, wherein the degree of association is based at least in part on an amount of social momentum between said selected words; and a recommender configured to generate targeted advertising based at least in part on said relationship data, wherein the recommender module is further configured to generate the targeted advertising by at least accessing user data to identify one or more first words in the relationship data, identifying one or more second words in the relationship data that have one or more of the word relationships with the one or more first words, and identifying one or more advertisements having at least one keyword that corresponds to the one or more second words. | 1. A system for generating targeted advertisement recommendations, the system comprising: under control of a hardware processor: a data aggregation module configured to obtain a plurality of words from a social network; a relationship mining module in communication with the data aggregation module, the relationship mining module configured to create word relationships between selected ones of the plurality of words to produce relationship data, each of the word relationships reflecting a degree of association between two or more of the selected words, wherein the degree of association is based at least in part on an amount of social momentum between said selected words; and a recommender configured to generate targeted advertising based at least in part on said relationship data, wherein the recommender module is further configured to generate the targeted advertising by at least accessing user data to identify one or more first words in the relationship data, identifying one or more second words in the relationship data that have one or more of the word relationships with the one or more first words, and identifying one or more advertisements having at least one keyword that corresponds to the one or more second words. 9. The system of claim 1 , wherein the relationship mining module is further configured to create the word relationships by creating one or more graphs of the word relationships. | 0.735905 |
8,280,902 | 15 | 17 | 15. A precision search system comprising: a terminal configured to receive a full-text search request from a user interface; one or more databases storing information to be searched; and a precision search engine, the precision search engine being configured to: receive the full-text search request from the terminal, create a graphical profile from the full-text search request that is a graphical representation of key terms in the full-text search request, search the one or more databases based on the graphical profile to return search results, send the search results to the terminal, extract entities from the returned search results that are not included in the graphical profile as a set of suggested modifications to the graphical profile, extract concepts from the search results that are not included in the graphical profile but are included in an operational taxonomy, and determine the suggested modifications to the graphical profile based on the extracted entities and the extracted concepts. | 15. A precision search system comprising: a terminal configured to receive a full-text search request from a user interface; one or more databases storing information to be searched; and a precision search engine, the precision search engine being configured to: receive the full-text search request from the terminal, create a graphical profile from the full-text search request that is a graphical representation of key terms in the full-text search request, search the one or more databases based on the graphical profile to return search results, send the search results to the terminal, extract entities from the returned search results that are not included in the graphical profile as a set of suggested modifications to the graphical profile, extract concepts from the search results that are not included in the graphical profile but are included in an operational taxonomy, and determine the suggested modifications to the graphical profile based on the extracted entities and the extracted concepts. 17. The precision search system according to claim 15 , wherein the graphical profile includes a frequency ranking for each key term in the graphical profile that indicates at least one of a relative frequency and a specificity with which each key term appears in the full-text search request. | 0.740248 |
9,942,396 | 11 | 15 | 11. An electronic signature system comprising: a document repository storing (a) a document comprising a plurality of document terms, (b) an audio recording corresponding to at least a portion of the document terms, and (c) metadata that defines an electronic signature status of the document; a memory device; and a processor that is operatively coupled to the memory device, wherein the processor is configured to execute instructions stored in the memory device that, when executed, cause the processor to carry out an electronic signature process, the process comprising: receiving, from a document originator, instructions to invoke an electronic signature workflow that calls for the document to be distributed to a document recipient, establishing a communication session between the electronic signature system and the document recipient, wherein the communication session enables two-way audio communication between the electronic signature system and the document recipient, sending, from the electronic signature system to the document recipient, via the communication session, the audio recording corresponding to at least the portion of the document terms, sending, to the document recipient, via the communication session, a request for a spoken assent to the document terms associated with the audio recording, prompting the document recipient with an audible request to provide the spoken assent, receiving, by the electronic signature system, the spoken assent from the document recipient, wherein the spoken assent is received via the communication session, comparing a voiceprint of the spoken assent with a voiceprint of an authorized document signer, saving the spoken assent in the document repository, modifying the metadata to establish a logical connection between the document and the spoken assent that is saved in the document repository, wherein the metadata is modified only if the voiceprint of the spoken assent substantially matches the voiceprint of the authorized document signer, and sending, to the document originator, at least one of (a) a modified version of the document that is annotated with an indication of the spoken assent, and (b) the spoken assent. | 11. An electronic signature system comprising: a document repository storing (a) a document comprising a plurality of document terms, (b) an audio recording corresponding to at least a portion of the document terms, and (c) metadata that defines an electronic signature status of the document; a memory device; and a processor that is operatively coupled to the memory device, wherein the processor is configured to execute instructions stored in the memory device that, when executed, cause the processor to carry out an electronic signature process, the process comprising: receiving, from a document originator, instructions to invoke an electronic signature workflow that calls for the document to be distributed to a document recipient, establishing a communication session between the electronic signature system and the document recipient, wherein the communication session enables two-way audio communication between the electronic signature system and the document recipient, sending, from the electronic signature system to the document recipient, via the communication session, the audio recording corresponding to at least the portion of the document terms, sending, to the document recipient, via the communication session, a request for a spoken assent to the document terms associated with the audio recording, prompting the document recipient with an audible request to provide the spoken assent, receiving, by the electronic signature system, the spoken assent from the document recipient, wherein the spoken assent is received via the communication session, comparing a voiceprint of the spoken assent with a voiceprint of an authorized document signer, saving the spoken assent in the document repository, modifying the metadata to establish a logical connection between the document and the spoken assent that is saved in the document repository, wherein the metadata is modified only if the voiceprint of the spoken assent substantially matches the voiceprint of the authorized document signer, and sending, to the document originator, at least one of (a) a modified version of the document that is annotated with an indication of the spoken assent, and (b) the spoken assent. 15. The electronic signature system of claim 11 , wherein the document repository comprises a networked storage resource provided remotely with respect to the processor and the memory device. | 0.75323 |
9,852,448 | 3 | 5 | 3. The method of claim 1 , wherein: each application indicated in each set of search results defined in the target query record includes a result score associated therewith, and the result score indicates a degree of confidence in a match of the application to the search query. | 3. The method of claim 1 , wherein: each application indicated in each set of search results defined in the target query record includes a result score associated therewith, and the result score indicates a degree of confidence in a match of the application to the search query. 5. The method of claim 3 , wherein: each set of search results stored in the target query record includes a feedback indicator, and the feedback indicator indicates whether a user selected one or more of the search results in response to being presented with the search results. | 0.6525 |
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