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9,727,933 | 1 | 5 | 1. A method comprising: (a) providing a interactive three-dimensional reserve study to a user system, wherein the interactive three-dimensional reserve study is rendered on a display of the user system, wherein the interactive three-dimensional reserve study comprises a three-dimensional line art diagram of a Common Interest Development (CID), a first graphical element that corresponds to a first reserve component of the CID, and a second graphical element that corresponds to a second reserve component of the CID, wherein the first reserve component is different from the second reserve component, wherein the first graphical element includes a first amount of color or shading that is overlaid above a first portion of the three-dimensional line art diagram of the CID at a first location, wherein the first graphical element is configured to respond to user input, wherein the second graphical element includes a second amount of color or shading that is overlaid above a second portion of the three-dimensional line art diagram of the CID at a second location, wherein the second graphical element is configured to respond to user input, and wherein the first location is distinct from the second location; (b) in response to detecting a first input event on the first graphical element, presenting a first amount of reserve component information of the first reserve component on the display of the user system; and (c) in response to detecting a second input event on the second graphical element, presenting a second amount of reserve component information of the second reserve component on the display of the user system, wherein the interactive three-dimensional reserve study is provided on a single web page. | 1. A method comprising: (a) providing a interactive three-dimensional reserve study to a user system, wherein the interactive three-dimensional reserve study is rendered on a display of the user system, wherein the interactive three-dimensional reserve study comprises a three-dimensional line art diagram of a Common Interest Development (CID), a first graphical element that corresponds to a first reserve component of the CID, and a second graphical element that corresponds to a second reserve component of the CID, wherein the first reserve component is different from the second reserve component, wherein the first graphical element includes a first amount of color or shading that is overlaid above a first portion of the three-dimensional line art diagram of the CID at a first location, wherein the first graphical element is configured to respond to user input, wherein the second graphical element includes a second amount of color or shading that is overlaid above a second portion of the three-dimensional line art diagram of the CID at a second location, wherein the second graphical element is configured to respond to user input, and wherein the first location is distinct from the second location; (b) in response to detecting a first input event on the first graphical element, presenting a first amount of reserve component information of the first reserve component on the display of the user system; and (c) in response to detecting a second input event on the second graphical element, presenting a second amount of reserve component information of the second reserve component on the display of the user system, wherein the interactive three-dimensional reserve study is provided on a single web page. 5. The method of claim 1 , wherein only one of the first amount of reserve component information or the second amount of reserve component information is presented on the display at a time. | 0.8125 |
9,307,031 | 2 | 3 | 2. The system of claim 1 , wherein the newly created JavaScript package registers itself as a package handler with a session layer created between the HTML5 application and said server-side real-time communication signaling controller. | 2. The system of claim 1 , wherein the newly created JavaScript package registers itself as a package handler with a session layer created between the HTML5 application and said server-side real-time communication signaling controller. 3. The system of claim 2 , wherein the package handler is identifiable by a package identifier, and handles messages that contains the package identifier. | 0.5 |
8,881,016 | 7 | 12 | 7. A method for implementing an initial setup of a digital device, the digital device including a screen displaying a graphic user interface (GUI), the GUI including a first panel and a second panel, the method comprising: automatically detecting at least one of an Internet network, a television cable, and a plurality of inputs connected to the digital device, wherein the first panel displays advertisements during process of automatically detecting; populating a connections list in the second panel including a result of the automatic detection; when the result of the automatic detection includes the Internet network, guiding the user through the detected Internet network set up by (i) displaying in the second panel a type of Internet network that is detected and is to be set up, wherein the type of Internet network includes at least one of a wired network and a wireless network, and (ii) displaying in the first panel at least one of an image and an animation describing the type of Internet network being highlighted in the second panel; and when the result of the automatic detection includes the plurality of inputs, guiding the user through setting up each of the plurality of detected inputs by (i) displaying in the second panel a list of the plurality of detected inputs to be labeled, and (ii) displaying in the first panel at least one of a text, image, and animation describing the list of the plurality of detected inputs. | 7. A method for implementing an initial setup of a digital device, the digital device including a screen displaying a graphic user interface (GUI), the GUI including a first panel and a second panel, the method comprising: automatically detecting at least one of an Internet network, a television cable, and a plurality of inputs connected to the digital device, wherein the first panel displays advertisements during process of automatically detecting; populating a connections list in the second panel including a result of the automatic detection; when the result of the automatic detection includes the Internet network, guiding the user through the detected Internet network set up by (i) displaying in the second panel a type of Internet network that is detected and is to be set up, wherein the type of Internet network includes at least one of a wired network and a wireless network, and (ii) displaying in the first panel at least one of an image and an animation describing the type of Internet network being highlighted in the second panel; and when the result of the automatic detection includes the plurality of inputs, guiding the user through setting up each of the plurality of detected inputs by (i) displaying in the second panel a list of the plurality of detected inputs to be labeled, and (ii) displaying in the first panel at least one of a text, image, and animation describing the list of the plurality of detected inputs. 12. The method of claim 7 , further comprising at least one of the following being connected to the plurality of inputs, respectively: a video game console, a DVD player, an audio system, cable set-top box, a satellite box and a modem. | 0.78281 |
9,684,690 | 9 | 10 | 9. The computer-implemented method of claim 1 , wherein the dimensions portion includes a flights scatterplot displaying flights with respect to a pair of dimensions. | 9. The computer-implemented method of claim 1 , wherein the dimensions portion includes a flights scatterplot displaying flights with respect to a pair of dimensions. 10. The computer-implemented method of claim 9 , further comprising: receiving, by the one or more computing devices, a user input modifying a marker position associated with one or more of the pair of dimensions in the scatterplot; and updating, by the one or more computing devices, the plurality of specific flight search results according to flights within the region of the scatterplot demarcated by the user input. | 0.5 |
9,916,286 | 1 | 5 | 1. A method for reformatting a plurality of target paragraphs with a format pattern of a plurality of sample paragraphs, the method comprising: generating a sample combination by dividing the plurality of sample paragraphs into sample groups according to their order and format pattern, each sample group includes adjacent sample paragraphs of the same format pattern; generating a plurality of different candidate combinations by assigning the plurality of target paragraphs to the sample groups, wherein each of the plurality of candidate combinations comprises a different combination of target paragraphs and sample groups, and each of the plurality of target paragraphs is assigned to only one sample group for each of the plurality of candidate combinations; selecting two or more preferred candidate combinations from the plurality of candidate combinations based on a degree of similarity between the sample combination and each of the plurality of candidate combinations; selecting a single matching combination from the two or more preferred candidate combinations; and applying the format pattern of the plurality of sample paragraphs to the plurality of target paragraphs in accordance with the single matching combination. | 1. A method for reformatting a plurality of target paragraphs with a format pattern of a plurality of sample paragraphs, the method comprising: generating a sample combination by dividing the plurality of sample paragraphs into sample groups according to their order and format pattern, each sample group includes adjacent sample paragraphs of the same format pattern; generating a plurality of different candidate combinations by assigning the plurality of target paragraphs to the sample groups, wherein each of the plurality of candidate combinations comprises a different combination of target paragraphs and sample groups, and each of the plurality of target paragraphs is assigned to only one sample group for each of the plurality of candidate combinations; selecting two or more preferred candidate combinations from the plurality of candidate combinations based on a degree of similarity between the sample combination and each of the plurality of candidate combinations; selecting a single matching combination from the two or more preferred candidate combinations; and applying the format pattern of the plurality of sample paragraphs to the plurality of target paragraphs in accordance with the single matching combination. 5. The method of claim 1 , further comprising: conducting semantic analysis on the content of the sample paragraphs and the content of the target paragraphs to determine a relationship between the content of the sample paragraphs and the content of the target paragraphs. | 0.69482 |
8,369,272 | 15 | 16 | 15. The apparatus of claim 14 , wherein said configuration data comprise, for each of said cells, a definition of a list of other cells in overlap therewith and belonging to a different group of system radio resources. | 15. The apparatus of claim 14 , wherein said configuration data comprise, for each of said cells, a definition of a list of other cells in overlap therewith and belonging to a different group of system radio resources. 16. The apparatus of claim 15 , wherein said configuration data comprise, for each of said cells, an indication of a modality of determination of an admissible alternative radio resource of a system susceptible of being used for satisfying the communication service request. | 0.5 |
8,832,542 | 10 | 14 | 10. An apparatus for providing a hyperlink on a network comprising: a communication device for receiving an image of at least one character fixed in a medium; a processor coupled to a memory for storing a control program, the control program renders the apparatus to function as: a first module for determining at least one letter of an alphabet corresponding to the at least one character; a decoding module for identifying at least one symbol applied onto at least a portion of the determined letter, determining a type of the identified at least one symbol and a location of the identified at least one symbol on the determined letter and determining a numerical value for the identified at least one symbol based on the determined letter, the determined type of the at least one symbol and location of the identified at least one symbol on the determined letter; and a lookup module for looking up in a database a hyperlink corresponding to the numerical value and presenting the hyperlink on a display device. | 10. An apparatus for providing a hyperlink on a network comprising: a communication device for receiving an image of at least one character fixed in a medium; a processor coupled to a memory for storing a control program, the control program renders the apparatus to function as: a first module for determining at least one letter of an alphabet corresponding to the at least one character; a decoding module for identifying at least one symbol applied onto at least a portion of the determined letter, determining a type of the identified at least one symbol and a location of the identified at least one symbol on the determined letter and determining a numerical value for the identified at least one symbol based on the determined letter, the determined type of the at least one symbol and location of the identified at least one symbol on the determined letter; and a lookup module for looking up in a database a hyperlink corresponding to the numerical value and presenting the hyperlink on a display device. 14. The apparatus as in claim 10 , wherein the at least one symbol is a hatch mark, at least one dot, a line, a bolded element or a combination thereof. | 0.705426 |
9,959,296 | 1 | 11 | 1. A method implemented by data processing apparatus, the method comprising: obtaining, during a current editing session, textual input provided to a document editing application by a user associated with a user device, the textual input being provided to the document editing application for inclusion in a document; receiving textual suggestions from a suggestion model based on the obtained textual input, each textual suggestion comprising one or more words to be suggested for inclusion in the document, each textual suggestion having a confidence score; providing, during the current editing session and not to the user, respective textual suggestions having confidence scores above a current threshold value; identifying, during the current editing session, one or more performance measures associated with the current editing session for the document, each performance measure being at least one of a typing speed of the user or a latency of the user device based on session data obtained during a document editing session, the session data being for the obtained textual input and prior texts included in the document prior to the obtained textual input; providing the one or more performance measures as input to the suggestion model that was trained using historical performance measures identified in performance logs for a plurality of historical document editing sessions of a plurality of users prior to the current editing session; generating a modified threshold value based on the inputted one or more performance measures, the modified threshold value different from the current threshold value; and throttling the textual suggestions during the current editing session by providing, during the current editing session and to the user, at least one of the respective textual suggestions having a confidence score above the modified threshold value. | 1. A method implemented by data processing apparatus, the method comprising: obtaining, during a current editing session, textual input provided to a document editing application by a user associated with a user device, the textual input being provided to the document editing application for inclusion in a document; receiving textual suggestions from a suggestion model based on the obtained textual input, each textual suggestion comprising one or more words to be suggested for inclusion in the document, each textual suggestion having a confidence score; providing, during the current editing session and not to the user, respective textual suggestions having confidence scores above a current threshold value; identifying, during the current editing session, one or more performance measures associated with the current editing session for the document, each performance measure being at least one of a typing speed of the user or a latency of the user device based on session data obtained during a document editing session, the session data being for the obtained textual input and prior texts included in the document prior to the obtained textual input; providing the one or more performance measures as input to the suggestion model that was trained using historical performance measures identified in performance logs for a plurality of historical document editing sessions of a plurality of users prior to the current editing session; generating a modified threshold value based on the inputted one or more performance measures, the modified threshold value different from the current threshold value; and throttling the textual suggestions during the current editing session by providing, during the current editing session and to the user, at least one of the respective textual suggestions having a confidence score above the modified threshold value. 11. The method of claim 1 , wherein the document editing session from which session data is obtained is the current editing session. | 0.852018 |
8,290,946 | 3 | 4 | 3. A method according to claim 1 , wherein the sigmoid function is used to combine multiple similarity scores together to predict the probability. | 3. A method according to claim 1 , wherein the sigmoid function is used to combine multiple similarity scores together to predict the probability. 4. A method according to claim 3 , wherein different of the multiple similarity scores correspond to respective different keyword weighting algorithms used to weight terms in term vectors used to generate the similarity scores. | 0.5 |
10,108,610 | 10 | 13 | 10. The computer-implemented method of claim 8 , wherein the web page comprises a second content item, and wherein the method further comprises: receiving a translation of the second content item, the translation of the second content item generated by a selected one of the first machine translation service or the second machine translation service; and presenting the translation of the second content item in the user interface. | 10. The computer-implemented method of claim 8 , wherein the web page comprises a second content item, and wherein the method further comprises: receiving a translation of the second content item, the translation of the second content item generated by a selected one of the first machine translation service or the second machine translation service; and presenting the translation of the second content item in the user interface. 13. The computer-implemented method of claim 10 , wherein the selected machine translation service is selected based upon a size of the second content item. | 0.595855 |
6,092,036 | 1 | 5 | 1. A multi-lingual data processing system, said data processing system comprising: computer software for processing data in said data processing system, said computer software including at least one application program that generates a plurality of displayed objects having text to be displayed, said application program including an embedded translator; a locality setting identifying a target language into which text associated with said computer software is to be translated; and at least one text translation table corresponding to said target language identified by said locality setting and including source language text items and target language text items for each of said plurality of displayed objects having text, wherein said translator embedded in said application program is responsive to the generation of each of said plurality of displayed objects having text to be displayed, for finding said source language text items corresponding to said text to be displayed in said text translation table, and for replacing said text to be displayed associated with each of said plurality of displayed objects having text to be displayed with said target language text items from said text translation table. | 1. A multi-lingual data processing system, said data processing system comprising: computer software for processing data in said data processing system, said computer software including at least one application program that generates a plurality of displayed objects having text to be displayed, said application program including an embedded translator; a locality setting identifying a target language into which text associated with said computer software is to be translated; and at least one text translation table corresponding to said target language identified by said locality setting and including source language text items and target language text items for each of said plurality of displayed objects having text, wherein said translator embedded in said application program is responsive to the generation of each of said plurality of displayed objects having text to be displayed, for finding said source language text items corresponding to said text to be displayed in said text translation table, and for replacing said text to be displayed associated with each of said plurality of displayed objects having text to be displayed with said target language text items from said text translation table. 5. The system of claim 1 further including a translation table builder, responsive to a user input, for building said at least one text translation table. | 0.789617 |
9,411,907 | 8 | 9 | 8. An article of manufacture comprising a computer readable non-transitory medium, having stored thereon instructions to cause one or more processors to perform a search operation in a multitenant database environment, the instructions comprising instructions that, when executed, cause the one or more processors to: provide a graphical user interface on a display of an electronic computing device, wherein the graphical user interface includes a search functionality for searching a database within a multitenant database environment, wherein the multitenant environment includes data for multiple client entities, each identified by a tenant identifier (ID) having one of one or more users associated with the tenant ID, users of each of multiple client identities can only access data identified by a tenant ID associated with the respective client entity, and the multitenant environment is at least a hosted database provided by an entity separate from the client entities, and provides on-demand database service to the client entities; maintain, for a plurality of users corresponding to one or more tenants of the multitenant environment, a list of most recently used records for a plurality of database object types; provide suggested search results via the graphical user interface in response to a user-generated partial search query input by performing one or more anticipated searches based on the user-generated partial search query, wherein the suggested search results are derived from database objects that match the user-generated partial search query input and include database records of multiple object types that have been recently edited by a user generating the user-generated partial search query input by utilizing the list of most recently used records corresponding to the user, the suggested search results being grouped by database object type, and further wherein the suggested search results also include content from one or more real-time feeds comprising at least one social media feed within the multitenant environment of at least one other user from the same client entity as the user; refine the suggested search results in response to subsequent user-generated search query input by performing one or more subsequent anticipated searches based on the subsequent user-generated search query input, the refined suggested search results also based on multiple object types that have been recently edited by a user generating the subsequent user-generated search query input by utilizing the list of most recently used records corresponding to the user, the suggested search results being grouped by database object type, and further wherein the suggested search results also include content from one or more real-time feeds comprising at least one social media feed within the multitenant environment of at least one other user from the same client entity as the user; and provide search results in the graphical user interface based on the user-generated search query input and/or a user selection from the suggested search results. | 8. An article of manufacture comprising a computer readable non-transitory medium, having stored thereon instructions to cause one or more processors to perform a search operation in a multitenant database environment, the instructions comprising instructions that, when executed, cause the one or more processors to: provide a graphical user interface on a display of an electronic computing device, wherein the graphical user interface includes a search functionality for searching a database within a multitenant database environment, wherein the multitenant environment includes data for multiple client entities, each identified by a tenant identifier (ID) having one of one or more users associated with the tenant ID, users of each of multiple client identities can only access data identified by a tenant ID associated with the respective client entity, and the multitenant environment is at least a hosted database provided by an entity separate from the client entities, and provides on-demand database service to the client entities; maintain, for a plurality of users corresponding to one or more tenants of the multitenant environment, a list of most recently used records for a plurality of database object types; provide suggested search results via the graphical user interface in response to a user-generated partial search query input by performing one or more anticipated searches based on the user-generated partial search query, wherein the suggested search results are derived from database objects that match the user-generated partial search query input and include database records of multiple object types that have been recently edited by a user generating the user-generated partial search query input by utilizing the list of most recently used records corresponding to the user, the suggested search results being grouped by database object type, and further wherein the suggested search results also include content from one or more real-time feeds comprising at least one social media feed within the multitenant environment of at least one other user from the same client entity as the user; refine the suggested search results in response to subsequent user-generated search query input by performing one or more subsequent anticipated searches based on the subsequent user-generated search query input, the refined suggested search results also based on multiple object types that have been recently edited by a user generating the subsequent user-generated search query input by utilizing the list of most recently used records corresponding to the user, the suggested search results being grouped by database object type, and further wherein the suggested search results also include content from one or more real-time feeds comprising at least one social media feed within the multitenant environment of at least one other user from the same client entity as the user; and provide search results in the graphical user interface based on the user-generated search query input and/or a user selection from the suggested search results. 9. The article of claim 8 wherein the user is identified by a session cookie. | 0.927903 |
9,418,058 | 10 | 11 | 10. A social media issue processing method, comprising: an inputting step of receiving a question; a step of determining a question type of the input question through a question pattern dictionary which is stored in advance; an analyzing step of performing issue period recognition for the question, question type based analysis, question based summary creation, and question based reliability calculation; and a summarizing step of creating a summary in accordance with at least one of the correlation between the question type and the question based summary, correlation between the issue period and a question type based analysis result, and correlation between the reliability and the question based summary. | 10. A social media issue processing method, comprising: an inputting step of receiving a question; a step of determining a question type of the input question through a question pattern dictionary which is stored in advance; an analyzing step of performing issue period recognition for the question, question type based analysis, question based summary creation, and question based reliability calculation; and a summarizing step of creating a summary in accordance with at least one of the correlation between the question type and the question based summary, correlation between the issue period and a question type based analysis result, and correlation between the reliability and the question based summary. 11. The method of claim 10 , wherein the inputting step is a step of receiving a natural word question. | 0.828904 |
7,865,491 | 4 | 5 | 4. The computer-readable storage medium of claim 1 , wherein the identifier in the physical database comprises a primary key from a column of a relational table, and wherein the identifier used to distinguish instances of the model entity comprises values stored in the primary key column of the relational table. | 4. The computer-readable storage medium of claim 1 , wherein the identifier in the physical database comprises a primary key from a column of a relational table, and wherein the identifier used to distinguish instances of the model entity comprises values stored in the primary key column of the relational table. 5. The computer-readable storage medium of claim 4 , wherein the linking function comprises an SQL query configured to retrieve values stored in the primary key column of the relational table related to a primary key value input to the function. | 0.5 |
9,460,074 | 1 | 3 | 1. A computer-implemented method of parsing data using a plurality of pattern matching rules, the method comprising: parsing training data using a plurality of pattern matching rules; assigning a pattern matching rule as a parent rule of one or more child rules upon determining that failure of the parent rule to match the training data is a predictor of the one or more child rules failure to match the training data; receiving data as input to be parsed; and parsing the data using the plurality of pattern matching rules, the plurality of pattern matching rules organized according to a hierarchy including the parent rule and the one or more child rules of the parent rule, and wherein the parsing comprises: applying the parent rule to the data, determining the parent rule is unable to find a pattern match in the data, and bypassing application of each child rule to the data in response to the determination that the parent rule is unable to find a pattern match. | 1. A computer-implemented method of parsing data using a plurality of pattern matching rules, the method comprising: parsing training data using a plurality of pattern matching rules; assigning a pattern matching rule as a parent rule of one or more child rules upon determining that failure of the parent rule to match the training data is a predictor of the one or more child rules failure to match the training data; receiving data as input to be parsed; and parsing the data using the plurality of pattern matching rules, the plurality of pattern matching rules organized according to a hierarchy including the parent rule and the one or more child rules of the parent rule, and wherein the parsing comprises: applying the parent rule to the data, determining the parent rule is unable to find a pattern match in the data, and bypassing application of each child rule to the data in response to the determination that the parent rule is unable to find a pattern match. 3. The method of claim 1 , further comprising: processing, before applying a second parent rule, an optimized search related to the second parent rule, wherein the optimized search is one of: a search for a text string extracted from a respective pattern matching rule; and bypassing the processing of the second parent rule and one or more child rules of the second parent rule upon determining the optimized search is unable to match the data. | 0.5 |
7,596,755 | 31 | 34 | 31. A system for displaying multimedia information stored in a multimedia document, the system comprising: a display; a processor; and a memory coupled to the processor, the memory configured to store a plurality of code modules for execution by the processor, the plurality of code modules comprising: a code module for displaying a graphical user interface (GUI) on the display; a code module for displaying, in a first area of the GUI, a first visual representation of the multimedia information stored in the multimedia document, the first visual representation including a first representation of information of a first type stored in the multimedia document and a first representation of information of a second type stored in the multimedia document; a code module for displaying, in the first area of the GUI, a first lens positionable over a plurality of portions of the first visual representation displayed within the first area of the GUI, the first lens covering a first portion of the first visual representation within the first area; a code module for displaying, in a second area of the GUI, a second visual representation of the multimedia information stored in the multimedia document based on the first lens covering the first portion of the first visual representation within the first area, the second visual representation including a second representation of the information of the first type stored in the multimedia document and a second representation of the information of the second type stored in the multimedia document; a code module for displaying, in the second area of the GUI, a second lens positionable over a plurality of portions of the second visual representation displayed within the second area of the GUI, the second lens covering a first portion of the second visual representation within the second area; and a code module for displaying, in a third area of the GUI, a third visual representation of the multimedia information stored in the multimedia document based on the second lens covering the first portion of the second visual representation within the second area, the third visual representation including a third representation of the information of the first type and a third representation of the information of the second type, wherein the code module for displaying the first visual representation of the multimedia information stored in the multimedia document in the first area of the GUI comprises: a code module for displaying a first thumbnail image in the first area of the GUI, the first thumbnail image comprising the first representation of the information of the first type; and a code module for displaying a second thumbnail image in the first area of the GUI, the second thumbnail image comprising the first representation of the information of the second type, wherein the code module for displaying the second visual representation of the multimedia information stored in the multimedia document in the second area of the GUI comprises: a code module for displaying, in a first sub-area of the second area of the GUI, the portion of the first representation of the information of the first type covered by the first lens as the second representation of the information of the first type; and a code module for displaying, in a second sub-area of the second area of the GUI, the portion of the first representation of the information of the second type covered by the first lens as the second representation of the information of the second type, wherein the code module for displaying the third visual representation of the multimedia information stored in the multimedia document in the third area of the GUI comprises: a code module for displaying, in a first sub-area of the third area of the GUI, the portion of the second representation of the information of the first type covered by the second lens as the third representation of the information of the first type; and a code module for displaying, in a second sub-area of the third area of the GUI, the portion of the second representation of the information of the second type covered by the second lens as the third representation of the information of the first type. | 31. A system for displaying multimedia information stored in a multimedia document, the system comprising: a display; a processor; and a memory coupled to the processor, the memory configured to store a plurality of code modules for execution by the processor, the plurality of code modules comprising: a code module for displaying a graphical user interface (GUI) on the display; a code module for displaying, in a first area of the GUI, a first visual representation of the multimedia information stored in the multimedia document, the first visual representation including a first representation of information of a first type stored in the multimedia document and a first representation of information of a second type stored in the multimedia document; a code module for displaying, in the first area of the GUI, a first lens positionable over a plurality of portions of the first visual representation displayed within the first area of the GUI, the first lens covering a first portion of the first visual representation within the first area; a code module for displaying, in a second area of the GUI, a second visual representation of the multimedia information stored in the multimedia document based on the first lens covering the first portion of the first visual representation within the first area, the second visual representation including a second representation of the information of the first type stored in the multimedia document and a second representation of the information of the second type stored in the multimedia document; a code module for displaying, in the second area of the GUI, a second lens positionable over a plurality of portions of the second visual representation displayed within the second area of the GUI, the second lens covering a first portion of the second visual representation within the second area; and a code module for displaying, in a third area of the GUI, a third visual representation of the multimedia information stored in the multimedia document based on the second lens covering the first portion of the second visual representation within the second area, the third visual representation including a third representation of the information of the first type and a third representation of the information of the second type, wherein the code module for displaying the first visual representation of the multimedia information stored in the multimedia document in the first area of the GUI comprises: a code module for displaying a first thumbnail image in the first area of the GUI, the first thumbnail image comprising the first representation of the information of the first type; and a code module for displaying a second thumbnail image in the first area of the GUI, the second thumbnail image comprising the first representation of the information of the second type, wherein the code module for displaying the second visual representation of the multimedia information stored in the multimedia document in the second area of the GUI comprises: a code module for displaying, in a first sub-area of the second area of the GUI, the portion of the first representation of the information of the first type covered by the first lens as the second representation of the information of the first type; and a code module for displaying, in a second sub-area of the second area of the GUI, the portion of the first representation of the information of the second type covered by the first lens as the second representation of the information of the second type, wherein the code module for displaying the third visual representation of the multimedia information stored in the multimedia document in the third area of the GUI comprises: a code module for displaying, in a first sub-area of the third area of the GUI, the portion of the second representation of the information of the first type covered by the second lens as the third representation of the information of the first type; and a code module for displaying, in a second sub-area of the third area of the GUI, the portion of the second representation of the information of the second type covered by the second lens as the third representation of the information of the first type. 34. The system of claim 31 wherein the code module for displaying the second visual representation of the multimedia information stored in the multimedia document comprises: a code module for determining a first time and a second time associated with the first lens; a code module for displaying, in the second area of the GUI, a representation of the information of the first type occurring between the first time and the second time associated with the first lens as the second representation of the information of the first type; and a code module for displaying, in the second area of the GUI, a representation of the information of the second type occurring between the first time and the second time associated with the first lens as the second representation of the information of the second type. | 0.639138 |
4,783,811 | 7 | 11 | 7. A method for determining syllable boundaries in a series of segments without marked syllable boundaries by automated apparatus, comprising: storing a set of transforming rules defining syllable boundaries, said rules each including a source part for comparing with an input segment having a number of input bytes, a left environment for comparing with a number of left environment bytes to the left of said input segment, a right environment for comparing with a number of right, environment bytes to the right of said input segment and an output part having syllabifying indicia; sequentially comparing said rules with ones of said input segments; and transforming said ones of said input segments with said output parts of matching rules to obtain output data when said input segments and the associated left and right environment bytes match said rules. | 7. A method for determining syllable boundaries in a series of segments without marked syllable boundaries by automated apparatus, comprising: storing a set of transforming rules defining syllable boundaries, said rules each including a source part for comparing with an input segment having a number of input bytes, a left environment for comparing with a number of left environment bytes to the left of said input segment, a right environment for comparing with a number of right, environment bytes to the right of said input segment and an output part having syllabifying indicia; sequentially comparing said rules with ones of said input segments; and transforming said ones of said input segments with said output parts of matching rules to obtain output data when said input segments and the associated left and right environment bytes match said rules. 11. The method of claim 7 wherein said set of rules does not stress allophone varieties following a stressed vowel and preceding a syllable boundary. | 0.778274 |
9,971,849 | 2 | 3 | 2. The method of claim 1 , further comprising parsing the received first data using an XML, parser to derive a data XML instance. | 2. The method of claim 1 , further comprising parsing the received first data using an XML, parser to derive a data XML instance. 3. The method of claim 2 , where the data XML instance is used, when processing semantic constraints, in conjunction with a facts XML instance obtained from a facts database in order to infer if an inter-dependency is present. | 0.5 |
9,854,399 | 1 | 2 | 1. A proximity service (ProSe) information transmission method, comprising: receiving, by the receiving ProSe entity, a code message sent by the monitoring terminal, wherein the code message is configured to instruct the receiving ProSe entity to acquire a code word, the code word is allocated to the first terminal by a first ProSe entity, and the first ProSe entity is the ProSe entity in the HPLMN of the first terminal; acquiring, by the receiving ProSe entity, the code word; sending, by the receiving ProSe entity, a monitoring message to the monitoring terminal, wherein the monitoring message carries the code word; receiving, by a receiving ProSe entity at a 3GPP network layer in a home public land mobile network (HPLMN), a first message sent by a monitoring terminal, wherein the first message is configured to instruct the receiving ProSe entity to acquire an application user identity that is allocated to a first application user by a first application server, the first application user is a user of a first application of a first terminal, the first application server is an application server of the first application, and the receiving ProSe entity is a ProSe entity in the HPLMN; acquiring, by the receiving ProSe entity, the application user identity via the HPLMN; and sending, by the receiving ProSe entity at the 3GPP network layer in the HPLMN, a second message to the monitoring terminal, wherein the second message carries the application user identity, and the application user identity is configured to indicate the first application user discovered by the monitoring terminal in the HPLMN, wherein the second message further carries a first application identity, the first application identity is an application identity of the first application, and the first application identity is configured to indicate the first application corresponding to the application user identity. | 1. A proximity service (ProSe) information transmission method, comprising: receiving, by the receiving ProSe entity, a code message sent by the monitoring terminal, wherein the code message is configured to instruct the receiving ProSe entity to acquire a code word, the code word is allocated to the first terminal by a first ProSe entity, and the first ProSe entity is the ProSe entity in the HPLMN of the first terminal; acquiring, by the receiving ProSe entity, the code word; sending, by the receiving ProSe entity, a monitoring message to the monitoring terminal, wherein the monitoring message carries the code word; receiving, by a receiving ProSe entity at a 3GPP network layer in a home public land mobile network (HPLMN), a first message sent by a monitoring terminal, wherein the first message is configured to instruct the receiving ProSe entity to acquire an application user identity that is allocated to a first application user by a first application server, the first application user is a user of a first application of a first terminal, the first application server is an application server of the first application, and the receiving ProSe entity is a ProSe entity in the HPLMN; acquiring, by the receiving ProSe entity, the application user identity via the HPLMN; and sending, by the receiving ProSe entity at the 3GPP network layer in the HPLMN, a second message to the monitoring terminal, wherein the second message carries the application user identity, and the application user identity is configured to indicate the first application user discovered by the monitoring terminal in the HPLMN, wherein the second message further carries a first application identity, the first application identity is an application identity of the first application, and the first application identity is configured to indicate the first application corresponding to the application user identity. 2. The method according to claim 1 , wherein the first message carries a code word and a first application identity, the code word is allocated to the first terminal by a first ProSe entity, the first application identity is an application identity of the first application, and the first ProSe entity is a ProSe entity in an HPLMN of the first terminal; and the acquiring, by the receiving ProSe entity, the application user identity comprises: sending, by the receiving ProSe entity, a third message to the first ProSe entity, wherein the third message carries the code word and the first application identity, so that the first ProSe entity acquires the code word and the application user identity corresponding to the first application identity; and receiving, by the receiving ProSe entity, a fourth message sent by the first ProSe entity, wherein the fourth message carries the application user identity. | 0.707019 |
9,942,611 | 12 | 14 | 12. A system for creating countdown animations, the system comprising: storage circuitry that stores text received from a first user including a plurality of words representing a task to be started at a given time by a second user; and control circuitry that: generates a countdown of an amount of time remaining in a user selected period of time for accessing media content based on a difference between a current time and the given time; processes the text to select a word of the plurality of words associated with the task; identifies a character of a plurality of characters based on a user criterion by automatically determining one of the plurality of characters that is associated with the selected word associated with the task, wherein each of the plurality of characters is associated with a different type of task; searches a database of a plurality of countdown animations to select a countdown animation associated with the identified character; and generates for display to the second user the selected countdown animation simultaneously with the media content, wherein the selected countdown animation identifies the task to be started by the second user at the end of the countdown of the amount of time. | 12. A system for creating countdown animations, the system comprising: storage circuitry that stores text received from a first user including a plurality of words representing a task to be started at a given time by a second user; and control circuitry that: generates a countdown of an amount of time remaining in a user selected period of time for accessing media content based on a difference between a current time and the given time; processes the text to select a word of the plurality of words associated with the task; identifies a character of a plurality of characters based on a user criterion by automatically determining one of the plurality of characters that is associated with the selected word associated with the task, wherein each of the plurality of characters is associated with a different type of task; searches a database of a plurality of countdown animations to select a countdown animation associated with the identified character; and generates for display to the second user the selected countdown animation simultaneously with the media content, wherein the selected countdown animation identifies the task to be started by the second user at the end of the countdown of the amount of time. 14. The system of claim 12 , wherein the control circuitry: compares an attribute associated with each character of the plurality of characters to the user criterion; and selects the character of the plurality of characters associated with an attribute matching the user criterion. | 0.636951 |
7,562,069 | 1 | 3 | 1. A method for resolving a query, the method comprising: maintaining, in electronic storage, a query ontology that includes one or more query categories and one or more queries associated with each of the one or more categories; receiving a query from a user, the received query including a first portion and a second portion that is different than the first portion; in response to receiving the query, accessing, from the electronic storage, one or more queries included within the query ontology; comparing the first portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology; based on the comparison of the first portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology, identifying, from within the query ontology, a first group of multiple categories that are associated with a query that matches the first portion of the received query; comparing the second portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology; based on the comparison of the second portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology, identifying, from within the query ontology, a second group of multiple categories that are associated with a query that matches the second portion of the received query, the second group of multiple categories being different than the first group of multiple categories; comparing the second group of multiple categories with the first group of multiple categories; based on the comparison of the second group of multiple categories with the first group of multiple categories, identifying a category that is included in the second group of multiple categories identified for the second portion of the received query and the first group of multiple categories identified for the first portion of the received query; performing a search process that uses the identified category in identifying search results responsive to the received query, the search process comprising: accessing, from the electronic storage, a subset of one or more query terms included within the query ontology and associated with the identified category; configuring the received query to include the accessed subset of one or more query terms associated with the identified category, the configured query being different than the received query; submitting the configured query to a search engine; receiving, from the search engine, search results corresponding to the configured query; and storing, using a processor in electronic storage, the received search results corresponding to the configured query. | 1. A method for resolving a query, the method comprising: maintaining, in electronic storage, a query ontology that includes one or more query categories and one or more queries associated with each of the one or more categories; receiving a query from a user, the received query including a first portion and a second portion that is different than the first portion; in response to receiving the query, accessing, from the electronic storage, one or more queries included within the query ontology; comparing the first portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology; based on the comparison of the first portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology, identifying, from within the query ontology, a first group of multiple categories that are associated with a query that matches the first portion of the received query; comparing the second portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology; based on the comparison of the second portion of the received query against one or more queries included in the accessed one or more queries that are included within the query ontology, identifying, from within the query ontology, a second group of multiple categories that are associated with a query that matches the second portion of the received query, the second group of multiple categories being different than the first group of multiple categories; comparing the second group of multiple categories with the first group of multiple categories; based on the comparison of the second group of multiple categories with the first group of multiple categories, identifying a category that is included in the second group of multiple categories identified for the second portion of the received query and the first group of multiple categories identified for the first portion of the received query; performing a search process that uses the identified category in identifying search results responsive to the received query, the search process comprising: accessing, from the electronic storage, a subset of one or more query terms included within the query ontology and associated with the identified category; configuring the received query to include the accessed subset of one or more query terms associated with the identified category, the configured query being different than the received query; submitting the configured query to a search engine; receiving, from the search engine, search results corresponding to the configured query; and storing, using a processor in electronic storage, the received search results corresponding to the configured query. 3. The method of claim 1 further comprising reformulating the configured query to comply with a format in which queries may be submitted to the search engine. | 0.937697 |
8,682,646 | 8 | 11 | 8. A system comprising at least one computing device and at least one module that are together configured for performing actions comprising: extracting, based on grammatical rules, location keywords from a location description; and checking for a semantic relationship among the extracted location keywords to derive a valid semantic meaning of the location description, the checking configured for further deriving: a) a spatial part-of relationship between two locations represented by the location keywords extracted from the location description, where a first of the two locations as indicated by a first of the extracted location keywords is a part of a second of the two locations as indicated by a second of the extracted location keywords, b) a spatial near-by relationship between the two locations represented by the location keywords extracted from the location description, where the first of the two locations as indicated by the first of the extracted location keywords is located proximate to the second of the two locations as indicated by the second of the extracted location keywords, and c) a spatial intersects relationship between the two locations represented by the location keywords extracted from the location description, where the first of the two locations as indicated by the first of the extracted location keywords intersects the second of the two locations as indicated by the second of the extracted location keywords. | 8. A system comprising at least one computing device and at least one module that are together configured for performing actions comprising: extracting, based on grammatical rules, location keywords from a location description; and checking for a semantic relationship among the extracted location keywords to derive a valid semantic meaning of the location description, the checking configured for further deriving: a) a spatial part-of relationship between two locations represented by the location keywords extracted from the location description, where a first of the two locations as indicated by a first of the extracted location keywords is a part of a second of the two locations as indicated by a second of the extracted location keywords, b) a spatial near-by relationship between the two locations represented by the location keywords extracted from the location description, where the first of the two locations as indicated by the first of the extracted location keywords is located proximate to the second of the two locations as indicated by the second of the extracted location keywords, and c) a spatial intersects relationship between the two locations represented by the location keywords extracted from the location description, where the first of the two locations as indicated by the first of the extracted location keywords intersects the second of the two locations as indicated by the second of the extracted location keywords. 11. The system of claim 8 where the grammatical rules are implemented by one or more of tokenization technologies, pattern matching technologies, or dictionary-driven technologies. | 0.560976 |
8,849,034 | 2 | 4 | 2. The method of claim 1 , further comprising: producing a candidate shape upon triggering the shape recognition by the handwriting recognition engine; and outputting the candidate shape. | 2. The method of claim 1 , further comprising: producing a candidate shape upon triggering the shape recognition by the handwriting recognition engine; and outputting the candidate shape. 4. The method of claim 2 , further comprising: repeating the drawing, inputting, triggering, producing, and outputting steps to enter a next shape. | 0.537736 |
9,047,612 | 22 | 28 | 22. A brand management system (BMS) operatively connected to one or more social media systems (SMSs) for managing a plurality of brand item profiles associated with a marketer and displayed on the one or more SMSs, comprising: a computer including at least one processor and memory; an interface that enables a developer to input content information to the BMS, the interface including one or more predetermined rules for entering the content information by the developer, wherein the BMS is different from the one or more SMSs, and wherein the BMS manages content corresponding to multiple SMSs; an input module for receiving the content information at the BMS from the developer; a content integration module for associating the content information with a brand item profile of the plurality of brand item profiles in a BMS database, and for, using the processor, integrating the brand item profile into a SMS account associated with the marketer, based at least in part upon one or more predetermined content display regions on one or more pages corresponding to the SMS account, wherein the predetermined content display regions comprise at least one content display region for standardized marketer content and one or more content display regions for brand item profile content; and a communication link between the BMS and a respective SMS to provide operative communications between the BMS and the respective SMS, the communication link configured to transmit information corresponding to the SMS account to the respective SMS, such that the one or more pages of a global SMS account, when displayed in response to a request of a member of the respective SMS via a portal of the respective SMS, comprises the standardized marketer content displayed in the at least one content display region for standardized marketer content and the content information associated with the brand item profile displayed in the one or more content display regions for the brand item profile content. | 22. A brand management system (BMS) operatively connected to one or more social media systems (SMSs) for managing a plurality of brand item profiles associated with a marketer and displayed on the one or more SMSs, comprising: a computer including at least one processor and memory; an interface that enables a developer to input content information to the BMS, the interface including one or more predetermined rules for entering the content information by the developer, wherein the BMS is different from the one or more SMSs, and wherein the BMS manages content corresponding to multiple SMSs; an input module for receiving the content information at the BMS from the developer; a content integration module for associating the content information with a brand item profile of the plurality of brand item profiles in a BMS database, and for, using the processor, integrating the brand item profile into a SMS account associated with the marketer, based at least in part upon one or more predetermined content display regions on one or more pages corresponding to the SMS account, wherein the predetermined content display regions comprise at least one content display region for standardized marketer content and one or more content display regions for brand item profile content; and a communication link between the BMS and a respective SMS to provide operative communications between the BMS and the respective SMS, the communication link configured to transmit information corresponding to the SMS account to the respective SMS, such that the one or more pages of a global SMS account, when displayed in response to a request of a member of the respective SMS via a portal of the respective SMS, comprises the standardized marketer content displayed in the at least one content display region for standardized marketer content and the content information associated with the brand item profile displayed in the one or more content display regions for the brand item profile content. 28. The system of claim 22 , wherein the predetermined rules for entering the content information by the developer include one or more of: marketer-specified format requirements, marketer-specified content style requirements, predetermined content display regions, marketer-required content, SMS-required display regions. | 0.53207 |
7,612,897 | 18 | 20 | 18. The method of claim 17 wherein the first set of characters includes multilingual characters and Latin characters and wherein the second set of characters includes Latin characters. | 18. The method of claim 17 wherein the first set of characters includes multilingual characters and Latin characters and wherein the second set of characters includes Latin characters. 20. The method of claim 18 wherein the received double-byte word is determined to identify a character from the second set of characters if the double-byte word includes a null data byte. | 0.5 |
9,501,469 | 27 | 28 | 27. The non-transitory computer-readable medium of claim 19 , wherein the method further comprises: (G) filtering the subset of the dataset to produce a filtered subset of the dataset. | 27. The non-transitory computer-readable medium of claim 19 , wherein the method further comprises: (G) filtering the subset of the dataset to produce a filtered subset of the dataset. 28. The non-transitory computer-readable medium of claim 27 , wherein the method further comprises: (H) before (G), receiving input from a user; wherein (G) comprises filtering the subset of the dataset based on the input received from the user. | 0.5 |
7,962,331 | 20 | 26 | 20. A system for facilitating the tuning of a speech recognizer, the system comprising: a processor; a memory; a playback module configured to play a selected portion of a digital audio data file; a user interface configured to provide a menu of selectable noise tags for identifying noise events in a transcript; an editor module configured to receive input modifying the transcript or the notes, wherein the input includes noise tags, selected from the menu of selectable noise tags, attaching markers to the transcript; and a detail viewing module configured to display information associated with a decoding of the selected portion by the speech recognizer, the information including the noise tags identifying noise events in the transcript. | 20. A system for facilitating the tuning of a speech recognizer, the system comprising: a processor; a memory; a playback module configured to play a selected portion of a digital audio data file; a user interface configured to provide a menu of selectable noise tags for identifying noise events in a transcript; an editor module configured to receive input modifying the transcript or the notes, wherein the input includes noise tags, selected from the menu of selectable noise tags, attaching markers to the transcript; and a detail viewing module configured to display information associated with a decoding of the selected portion by the speech recognizer, the information including the noise tags identifying noise events in the transcript. 26. The system of claim 20 , wherein the information associated with the decoding comprises a confidence score. | 0.659509 |
8,812,322 | 1 | 8 | 1. A method, comprising: performing, by one or more computing devices: generating a source model for a sound source based, at least in part, on a training signal, the source model including a plurality of spectral dictionaries corresponding to the training signal, a given segment of the training signal being represented by a given one of the plurality of spectral dictionaries, the given segment of the training signal being less than the training signal in whole, each of the plurality of spectral dictionaries including at least one spectral component, and the source model further including probabilities of transition among the plurality of spectral dictionaries; receiving a mixed signal including a combination of a signal of interest with a noise signal, the signal of interest being emitted by the sound source; in response to receiving an instruction to separate the signal of interest from the noise signal, generating a mixture model for the mixed signal using, at least in part, the source model, the mixture model including a plurality of mixture weights corresponding to the combination of the signal of interest and the noise signal, and a spectral dictionary corresponding to the noise signal; constructing a mask for the mixed signal based, at least in part, on the mixture model; and applying the mask to the mixture signal to separate the signal of interest from the noise signal. | 1. A method, comprising: performing, by one or more computing devices: generating a source model for a sound source based, at least in part, on a training signal, the source model including a plurality of spectral dictionaries corresponding to the training signal, a given segment of the training signal being represented by a given one of the plurality of spectral dictionaries, the given segment of the training signal being less than the training signal in whole, each of the plurality of spectral dictionaries including at least one spectral component, and the source model further including probabilities of transition among the plurality of spectral dictionaries; receiving a mixed signal including a combination of a signal of interest with a noise signal, the signal of interest being emitted by the sound source; in response to receiving an instruction to separate the signal of interest from the noise signal, generating a mixture model for the mixed signal using, at least in part, the source model, the mixture model including a plurality of mixture weights corresponding to the combination of the signal of interest and the noise signal, and a spectral dictionary corresponding to the noise signal; constructing a mask for the mixed signal based, at least in part, on the mixture model; and applying the mask to the mixture signal to separate the signal of interest from the noise signal. 8. The method of claim 1 , wherein the mixture model IS a non-negative factorial hidden Markov model (N-FHMM). | 0.786822 |
9,298,699 | 8 | 9 | 8. One or more non-transitory computer-readable media maintaining instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: determining a character identity in a work; determining a voice for the character identity, wherein the voice is associated with indicators within the work that suggest at least one of: a place that the character identity is from, a tribe of the character identity, a caste of the character identity, a dialect of the character identity, an education level of the character identity, an approximate age of the character identity, an ethnicity of the character identity, an era in which the character identity exists, or a socioeconomic class of the character identity; arranging, into a script, the work such that an indicator of the character identity is followed by a portion of text associated with the character identity; and using the voice to audibly present a portion of the work, wherein the portion is associated with the character identity. | 8. One or more non-transitory computer-readable media maintaining instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: determining a character identity in a work; determining a voice for the character identity, wherein the voice is associated with indicators within the work that suggest at least one of: a place that the character identity is from, a tribe of the character identity, a caste of the character identity, a dialect of the character identity, an education level of the character identity, an approximate age of the character identity, an ethnicity of the character identity, an era in which the character identity exists, or a socioeconomic class of the character identity; arranging, into a script, the work such that an indicator of the character identity is followed by a portion of text associated with the character identity; and using the voice to audibly present a portion of the work, wherein the portion is associated with the character identity. 9. The one or more non-transitory computer-readable media of claim 8 , wherein the character identity comprises a narrator for the work. | 0.683721 |
6,101,338 | 7 | 8 | 7. The camera as claimed in claimed in claim 6 wherein the displayed words or phrases are initial words or phrases representative of words or phrases in an initial set of voice commands that the microcontroller is capable of recognizing. | 7. The camera as claimed in claimed in claim 6 wherein the displayed words or phrases are initial words or phrases representative of words or phrases in an initial set of voice commands that the microcontroller is capable of recognizing. 8. The camera as claimed in claim 7 wherein the microcontroller further displays a pull-down menu, upon receiving any of the initial words or phrases, containing a subset of preprogrammed words or phrases that are voice commands pre-programmed in said microcontroller, and that are further descriptive of the initial set of words or phrases. | 0.5 |
8,620,958 | 17 | 18 | 17. A computer system comprising: a processor, a computer readable memory, and a computer readable storage medium; first program instructions to associate a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, and wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object; second program instructions to associate the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; third program instructions to construct a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same context object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different non-contextual data objects; fourth program instructions to receive, from a requester, a request for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and fifth program instructions to return, to the requester, said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and wherein the first, second, third, fourth, and fifth program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. | 17. A computer system comprising: a processor, a computer readable memory, and a computer readable storage medium; first program instructions to associate a non-contextual data object with a context object to define a synthetic context-based object, wherein the non-contextual data object ambiguously relates to multiple subject-matters, and wherein the context object provides a context that identifies a specific subject-matter, from the multiple subject-matters, of the non-contextual data object; second program instructions to associate the synthetic context-based object with at least one specific data store, wherein said at least one specific data store comprises data that is associated with data contained in the non-contextual data object and the context object; third program instructions to construct a dimensionally constrained hierarchical synthetic context-based object library for multiple synthetic context-based objects, wherein synthetic context-based objects within a same dimension of the dimensionally constrained hierarchical synthetic context-based object library share data from a same context object, and wherein synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library contain disparate data from different non-contextual data objects; fourth program instructions to receive, from a requester, a request for at least one data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and fifth program instructions to return, to the requester, said at least one specific data store that is associated with synthetic context-based objects within the same dimension of the dimensionally constrained hierarchical synthetic context-based object library; and wherein the first, second, third, fourth, and fifth program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. 18. The computer system of claim 17 , further comprising: sixth program instructions to data mine a data structure for the non-contextual data object and the context object, wherein said data mining locates said at least one specific data store that comprises data contained in the non-contextual data object and the context object; and wherein the sixth program instructions are stored on the computer readable storage medium for execution by the processor via the computer readable memory. | 0.5 |
9,886,518 | 19 | 20 | 19. A non-transitory computer readable storage medium comprising computer executable program code, which when executed by a computer system caused the computer system to perform steps comprising: receiving a document having: markup language constructs comprising a plurality of tags in a first section of the document comprising a first plurality of lines of code; and object oriented language constructs in a second section of the document separate from the first section of the document and comprising one or more class declarations, each class declaration comprising a second plurality of lines of code wherein one or more of the class declarations correspond to tags in the first section and have class names the same as tag names of the corresponding tags; and performing a step of class processing on a first tag among the plurality of tags in the markup language constructs, including: executing the body of the first tag and producing tag output; and subsequent to executing the first tag, invoking a predefined method referenced in a class declaration having a class name the same as the first tag, and during invocation of the predefined method accessing the tag output produced as a result of executing the body of the first tag. | 19. A non-transitory computer readable storage medium comprising computer executable program code, which when executed by a computer system caused the computer system to perform steps comprising: receiving a document having: markup language constructs comprising a plurality of tags in a first section of the document comprising a first plurality of lines of code; and object oriented language constructs in a second section of the document separate from the first section of the document and comprising one or more class declarations, each class declaration comprising a second plurality of lines of code wherein one or more of the class declarations correspond to tags in the first section and have class names the same as tag names of the corresponding tags; and performing a step of class processing on a first tag among the plurality of tags in the markup language constructs, including: executing the body of the first tag and producing tag output; and subsequent to executing the first tag, invoking a predefined method referenced in a class declaration having a class name the same as the first tag, and during invocation of the predefined method accessing the tag output produced as a result of executing the body of the first tag. 20. The non-transitory computer readable storage medium of claim 19 wherein, while executing the body of the first tag, if a child tag of the first tag corresponds to a class variable defined in a class that corresponds to the first tag, then producing output from the child tag and associating the output with the class variable. | 0.5 |
9,087,090 | 10 | 13 | 10. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for executing a query, the method comprising: receiving the query, wherein the query applies one or more qualitative search terms to an attribute of data items in a set of data items; and while executing the query, processing each data item in the set of data items by, extracting an attribute value from the data item, using a concept-mapping to determine a compatibility index for the attribute value, wherein the concept-mapping associates each attribute value with a numerical compatibility index that indicates a compatibility between the attribute value and the one or more qualitative search terms, wherein the concept mapping is represented using an array containing X and Y coordinate pairs describing a shape of a concept-mapping function, wherein using the concept-mapping to determine the compatibility index includes using the attribute value to perform a lookup in the array to retrieve the compatibility index, and using the compatibility index as a factor in determining whether to include the data item in a set of query results; and wherein when the query includes multiple qualitative search terms, executing the query comprises, determining compatibility indices for the multiple qualitative search terms for each data item, combining the determined compatibility indices into an aggregate compatibility index for each data item, wherein combining the determined compatibility indices involves one of computing an average for the multiple compatibility indices, and computing a weighted average for the multiple compatibility indices based on an ordering of associated qualitative search terms in the query, and determining whether to include each data item in the set of query results based on whether the aggregate compatibility index for the data item meets or exceeds a threshold. | 10. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for executing a query, the method comprising: receiving the query, wherein the query applies one or more qualitative search terms to an attribute of data items in a set of data items; and while executing the query, processing each data item in the set of data items by, extracting an attribute value from the data item, using a concept-mapping to determine a compatibility index for the attribute value, wherein the concept-mapping associates each attribute value with a numerical compatibility index that indicates a compatibility between the attribute value and the one or more qualitative search terms, wherein the concept mapping is represented using an array containing X and Y coordinate pairs describing a shape of a concept-mapping function, wherein using the concept-mapping to determine the compatibility index includes using the attribute value to perform a lookup in the array to retrieve the compatibility index, and using the compatibility index as a factor in determining whether to include the data item in a set of query results; and wherein when the query includes multiple qualitative search terms, executing the query comprises, determining compatibility indices for the multiple qualitative search terms for each data item, combining the determined compatibility indices into an aggregate compatibility index for each data item, wherein combining the determined compatibility indices involves one of computing an average for the multiple compatibility indices, and computing a weighted average for the multiple compatibility indices based on an ordering of associated qualitative search terms in the query, and determining whether to include each data item in the set of query results based on whether the aggregate compatibility index for the data item meets or exceeds a threshold. 13. The non-transitory computer-readable storage medium of claim 10 , wherein the concept-mapping is stored in a container file that contains a related set of concept-mappings. | 0.80744 |
9,367,627 | 15 | 18 | 15. A method, comprising: receiving, by a first computing device, a search query from a second computing device; generating, by the first computing device, a set of search results by executing a search based at least in part on the search query; selecting, by the first computing device, a subset of a plurality of supplemental content providers based at least in part on respective relevancies of the plurality of supplemental content providers to the search query; selecting, by the first computing device, the subset of the plurality of supplemental content providers further based at least in part on a compatibility rule that defines compatibility between supplemental content from a first supplemental content provider and supplemental content from a second supplemental content provider as permission to be rendered together in a search results page; selecting, by the first computing device, the subset of the plurality of supplemental content providers further based at least in part on relative immediate monetary values associated with the plurality of supplemental content providers; selecting, by the first computing device, the subset of the plurality of supplemental content providers further based at least in part on relative downstream business values associated with the plurality of supplemental content providers; generating, by the first computing device, the search results page configured to present supplemental content from the subset of the plurality of supplemental content providers in association with the set of search results; and sending, by the first computing device, data encoding the search results page to the second computing device. | 15. A method, comprising: receiving, by a first computing device, a search query from a second computing device; generating, by the first computing device, a set of search results by executing a search based at least in part on the search query; selecting, by the first computing device, a subset of a plurality of supplemental content providers based at least in part on respective relevancies of the plurality of supplemental content providers to the search query; selecting, by the first computing device, the subset of the plurality of supplemental content providers further based at least in part on a compatibility rule that defines compatibility between supplemental content from a first supplemental content provider and supplemental content from a second supplemental content provider as permission to be rendered together in a search results page; selecting, by the first computing device, the subset of the plurality of supplemental content providers further based at least in part on relative immediate monetary values associated with the plurality of supplemental content providers; selecting, by the first computing device, the subset of the plurality of supplemental content providers further based at least in part on relative downstream business values associated with the plurality of supplemental content providers; generating, by the first computing device, the search results page configured to present supplemental content from the subset of the plurality of supplemental content providers in association with the set of search results; and sending, by the first computing device, data encoding the search results page to the second computing device. 18. The method of claim 15 , further comprising generating, by the first computing device, a relative layout for the search results page based at least in part on respective relevancies of the subset of the plurality of supplemental content providers. | 0.770147 |
8,909,810 | 11 | 12 | 11. The system of claim 8 , wherein one or more of the third-party servers receive content from the shared content server. | 11. The system of claim 8 , wherein one or more of the third-party servers receive content from the shared content server. 12. The system of claim 11 , wherein one or more of the servers that receives content from the shared content server comprises a printing service. | 0.5 |
8,651,873 | 1 | 6 | 1. A computer-implemented method of designing an assessment, the method comprising: receiving subject matter information related to one or more subject matters of an assessment; receiving requirements information related to one or more requirements for an assessment; storing the subject matter information and the requirements information in a computer-readable database; generating one or more trifles using a processing system, wherein each trifle is based on one or more of the subject matter information and the requirements information; wherein a trifle provides a reference to a source of the subject matter information or the requirement information on which the trifle is based for subsequent access; storing the trifles in the computer-readable database; generating one or more task models using the processing system, wherein each task model is based on at least one trifle identified via a computer-implemented keyword search; wherein each task model comprises: an identification of an audience for the task model; a format for communicating a task to a student for the task model; a task feature description for the task model; an outcome feature description for the task model; and a task family feature description; storing the task models in the computer-readable database; generating one or more student models using the processing system, wherein each student model is based on at least one trifle, and wherein generating a student model comprises specifying statistical relationships between multiple variables in the student model; storing the student models in the computer-readable database; generating one or more evidence models using the processing system, wherein each evidence model is based on at least one trifle; storing the evidence models in the computer-readable database; generating one or more tasks using the processing system, wherein each task is based on one or more of the task models; and generating and outputting an assessment using the processing system, wherein each assessment comprises one or more tasks, an evidence model corresponding to each task, and one or more student models; wherein a number of tasks of a first kind to be included in the assessment for a particular student is determined based on a student model associated with the particular student, a task model, and an evidence model. | 1. A computer-implemented method of designing an assessment, the method comprising: receiving subject matter information related to one or more subject matters of an assessment; receiving requirements information related to one or more requirements for an assessment; storing the subject matter information and the requirements information in a computer-readable database; generating one or more trifles using a processing system, wherein each trifle is based on one or more of the subject matter information and the requirements information; wherein a trifle provides a reference to a source of the subject matter information or the requirement information on which the trifle is based for subsequent access; storing the trifles in the computer-readable database; generating one or more task models using the processing system, wherein each task model is based on at least one trifle identified via a computer-implemented keyword search; wherein each task model comprises: an identification of an audience for the task model; a format for communicating a task to a student for the task model; a task feature description for the task model; an outcome feature description for the task model; and a task family feature description; storing the task models in the computer-readable database; generating one or more student models using the processing system, wherein each student model is based on at least one trifle, and wherein generating a student model comprises specifying statistical relationships between multiple variables in the student model; storing the student models in the computer-readable database; generating one or more evidence models using the processing system, wherein each evidence model is based on at least one trifle; storing the evidence models in the computer-readable database; generating one or more tasks using the processing system, wherein each task is based on one or more of the task models; and generating and outputting an assessment using the processing system, wherein each assessment comprises one or more tasks, an evidence model corresponding to each task, and one or more student models; wherein a number of tasks of a first kind to be included in the assessment for a particular student is determined based on a student model associated with the particular student, a task model, and an evidence model. 6. The method of claim 1 wherein each assessment comprises one or more of the following: a strategy for assembling a grouping of one or more tasks; a requirement for presenting material to an assessment participant; and a requirement for receiving a response from the assessment participant. | 0.759106 |
9,817,949 | 2 | 4 | 2. The method of claim 1 further comprising: determining by the one or more computers a prediction of mental health status of the groups. | 2. The method of claim 1 further comprising: determining by the one or more computers a prediction of mental health status of the groups. 4. The method of claim 2 wherein the prediction is suicidal ideation. | 0.514085 |
9,110,990 | 21 | 23 | 21. One or more tangible non-transitory computer-readable storage media for storing computer-executable instructions executable by a computer system, the media storing one or more instructions to: receive, at an interactive program guide, search criteria from a client device; receive, at the interactive program guide and from the client device, a user identifier and a selection from predetermined genres, wherein the predetermined genres are mapped to a set of television programming; determine, with the interactive program guide, one or more search results in response to the search criteria, the user identifier and the selection from the predetermined genres; query one or more databases of attributes with portions of the search results, wherein the attributes include genre terms; compare each of the search results to the attributes to determine matches between selection from the predetermined genres, the portions of the search results and the genre terms; customize search result attribute correlations and correlation weights for each of the search results based on the user identifier, matches between 1) the portions of the search results, 2) the genre terms and 3) the selection from predetermined genres; calculate result weights for each of the search results by summing the correlation weights associated with each search result; sort the search results so the search results are returned in order of relevance according to the result weights; and return the search results. | 21. One or more tangible non-transitory computer-readable storage media for storing computer-executable instructions executable by a computer system, the media storing one or more instructions to: receive, at an interactive program guide, search criteria from a client device; receive, at the interactive program guide and from the client device, a user identifier and a selection from predetermined genres, wherein the predetermined genres are mapped to a set of television programming; determine, with the interactive program guide, one or more search results in response to the search criteria, the user identifier and the selection from the predetermined genres; query one or more databases of attributes with portions of the search results, wherein the attributes include genre terms; compare each of the search results to the attributes to determine matches between selection from the predetermined genres, the portions of the search results and the genre terms; customize search result attribute correlations and correlation weights for each of the search results based on the user identifier, matches between 1) the portions of the search results, 2) the genre terms and 3) the selection from predetermined genres; calculate result weights for each of the search results by summing the correlation weights associated with each search result; sort the search results so the search results are returned in order of relevance according to the result weights; and return the search results. 23. The computer-readable storage media of claim 21 , wherein the instructions to calculate the result weights further comprise instructions to: determining a location of the client device; calculate the result weights further based on the location. | 0.564685 |
7,689,404 | 10 | 11 | 10. The method of claim 9 wherein the language specific recognizers comprise a facility to prune active states of pronunciations based on score threshold and the multilingual dispatcher engine controlling the pruning threshold of each individual recognizer, the controlling comprising: determining the common prune threshold as the minimum of individual thresholds produced by said language specific recognizers, scaled to the multilingual dispatcher engine scale, relaxed by a tunable parameter; and dispatching a common pruning threshold to each said recognizer in the format scaled to the format of that recognizer. | 10. The method of claim 9 wherein the language specific recognizers comprise a facility to prune active states of pronunciations based on score threshold and the multilingual dispatcher engine controlling the pruning threshold of each individual recognizer, the controlling comprising: determining the common prune threshold as the minimum of individual thresholds produced by said language specific recognizers, scaled to the multilingual dispatcher engine scale, relaxed by a tunable parameter; and dispatching a common pruning threshold to each said recognizer in the format scaled to the format of that recognizer. 11. The method of claim 10 wherein components common to all supported languages are factored out of language-specific recognizers and incorporated into the multilingual dispatcher engine. | 0.5 |
9,268,765 | 1 | 8 | 1. A computer-implemented method for neurolinguistically analyzing text, comprising: receiving a meaningful first text sequence; deriving first text sequence n-grams from the first text sequence; comparing the first text sequence n-grams to a plurality of predetermined indicator n-grams, wherein: each predetermined indicator n-gram is associated with at least one cognitive motivation orientation; each predetermined indicator n-gram is further associated with at least one cognitive motivation orientation confidence weight, there being one cognitive motivation orientation confidence weight corresponding to each cognitive motivation orientation with which that particular predetermined indicator n-gram is associated; and recording at least one cognitive motivation orientation confidence weight for the first text sequence by, for each first text sequence n-gram matching any one of the predetermined indicator n-grams, recording each cognitive motivation orientation confidence weight associated with the particular predetermined indicator n-gram matching that particular first text sequence n-gram; using the at least one cognitive motivation orientation confidence weight recorded for the first text sequence to determine a first dominant cognitive motivation orientation set expressed in the first text sequence; generating an electronic signal which encodes a message, wherein the message subsumes the first dominant cognitive motivation orientation set expressed in the first text sequence; and transforming the electronic signal into a display signal which encodes the message, and using the display signal to present the message in visible form on a physical display. | 1. A computer-implemented method for neurolinguistically analyzing text, comprising: receiving a meaningful first text sequence; deriving first text sequence n-grams from the first text sequence; comparing the first text sequence n-grams to a plurality of predetermined indicator n-grams, wherein: each predetermined indicator n-gram is associated with at least one cognitive motivation orientation; each predetermined indicator n-gram is further associated with at least one cognitive motivation orientation confidence weight, there being one cognitive motivation orientation confidence weight corresponding to each cognitive motivation orientation with which that particular predetermined indicator n-gram is associated; and recording at least one cognitive motivation orientation confidence weight for the first text sequence by, for each first text sequence n-gram matching any one of the predetermined indicator n-grams, recording each cognitive motivation orientation confidence weight associated with the particular predetermined indicator n-gram matching that particular first text sequence n-gram; using the at least one cognitive motivation orientation confidence weight recorded for the first text sequence to determine a first dominant cognitive motivation orientation set expressed in the first text sequence; generating an electronic signal which encodes a message, wherein the message subsumes the first dominant cognitive motivation orientation set expressed in the first text sequence; and transforming the electronic signal into a display signal which encodes the message, and using the display signal to present the message in visible form on a physical display. 8. The method of claim 1 , further comprising: receiving a meaningful second text sequence, the second text sequence address the first text sequence; deriving second text sequence n-grams from the second text sequence; comparing the second text sequence n-grams to the plurality of predetermined indicator n-grams; recording at least one cognitive motivation orientation confidence weight for the second text sequence by, for each second text sequence n-gram matching any one of the predetermined indicator n-grams, recording each cognitive motivation orientation confidence weight associated with the particular predetermined indicator n-gram matching that particular second text sequence n-gram; and using the at least one cognitive motivation orientation confidence weight recorded for the second text sequence to determine a second dominant cognitive motivation orientation set expressed in the second text sequence. | 0.530133 |
7,546,578 | 1 | 12 | 1. A system for providing mathematical modeling in an object-oriented software environment, comprising: a processor operable to execute instructions contained in computer program code; and at least one computer readable medium including instructions in an object-oriented programming language that, when executed by the processor, cause the processor to: provide at least one library including a model class that when instantiated as a model object provides an interface allowing user interaction with a mathematical programming model, the mathematical programming model configured for generating a solution for a mathematical decision making problem; generate a numerical model, based on instance data associated with one or more parameters and one or more index sets of the mathematical programming model; solve the mathematical programming model using a selected solver running in the object-oriented programming language; and output a result of the solving process, wherein the model class instantiated as a user interface object comprises a set of methods to allow a user to add/remove mathematical expressions, constraints, or objective functions to/from the mathematical programming model, pass the instance data to a selected solver for solving the mathematical programming model, solve the numerical model through the solver and return the solution, and update the mathematical programming model with at least one incremental change to be passed to the selected solver. | 1. A system for providing mathematical modeling in an object-oriented software environment, comprising: a processor operable to execute instructions contained in computer program code; and at least one computer readable medium including instructions in an object-oriented programming language that, when executed by the processor, cause the processor to: provide at least one library including a model class that when instantiated as a model object provides an interface allowing user interaction with a mathematical programming model, the mathematical programming model configured for generating a solution for a mathematical decision making problem; generate a numerical model, based on instance data associated with one or more parameters and one or more index sets of the mathematical programming model; solve the mathematical programming model using a selected solver running in the object-oriented programming language; and output a result of the solving process, wherein the model class instantiated as a user interface object comprises a set of methods to allow a user to add/remove mathematical expressions, constraints, or objective functions to/from the mathematical programming model, pass the instance data to a selected solver for solving the mathematical programming model, solve the numerical model through the solver and return the solution, and update the mathematical programming model with at least one incremental change to be passed to the selected solver. 12. The system of claim 1 , further comprising program code for providing at least one comparison operator, a constraint type of a mathematical programming model being expressible without specifying a valid range of the constraint type, the constraint type being expressible as an algebraic expression array object on a left hand side of the comparison operator and a constant expression array object on a right hand side of the comparison operator. | 0.727217 |
8,498,906 | 23 | 24 | 23. A system comprising: a memory; a processing device; and a communications network linked to the memory, the memory storing an electronic catalog comprising a plurality of collaborative taxonomy instantiations, each collaborative taxonomy instantiation comprising a union of distinct attributes and values obtained from at least two sets of attributes and values for a product through a communications network, each set of attributes representing quantifiable properties of the product and each set of values representing numerical quantities of the respective properties with at least one difference between each of the sets of attributes and values, and each collaborative taxonomy instantiation being linked to an exchange part number, wherein the processing device is configured to: (i) compare the union of product attributes and values to product catalog information received from different computing systems through the communications network, (ii) associate respective exchange part numbers with those matching products included in the received product catalog information based on the comparing, and (iii) distribute the respective exchange part number and the association with a corresponding matching product to each computing system having product catalog information containing the corresponding matching product through the communications network, wherein the exchange part number is associated with each matching product at each computing system through the distributing. | 23. A system comprising: a memory; a processing device; and a communications network linked to the memory, the memory storing an electronic catalog comprising a plurality of collaborative taxonomy instantiations, each collaborative taxonomy instantiation comprising a union of distinct attributes and values obtained from at least two sets of attributes and values for a product through a communications network, each set of attributes representing quantifiable properties of the product and each set of values representing numerical quantities of the respective properties with at least one difference between each of the sets of attributes and values, and each collaborative taxonomy instantiation being linked to an exchange part number, wherein the processing device is configured to: (i) compare the union of product attributes and values to product catalog information received from different computing systems through the communications network, (ii) associate respective exchange part numbers with those matching products included in the received product catalog information based on the comparing, and (iii) distribute the respective exchange part number and the association with a corresponding matching product to each computing system having product catalog information containing the corresponding matching product through the communications network, wherein the exchange part number is associated with each matching product at each computing system through the distributing. 24. The system of claim 23 , being web accessible by at least one enterprise computing system. | 0.651852 |
9,727,842 | 17 | 18 | 17. The computer-implemented method of claim 16 , wherein the relevance score assigned to the one or more identity records associated with the first entity provide a quantitative measure of perceived relevance of the identity records to a user of the entity resolution system without requiring any entity alerts to be configured by the user. | 17. The computer-implemented method of claim 16 , wherein the relevance score assigned to the one or more identity records associated with the first entity provide a quantitative measure of perceived relevance of the identity records to a user of the entity resolution system without requiring any entity alerts to be configured by the user. 18. The computer-implemented method of claim 17 , wherein the received identity record is assigned an explicit relevance score by a user of the entity resolution system. | 0.5 |
8,495,062 | 35 | 39 | 35. A system for generating a search term comprising: a. in response to a user dragging-and-dropping a graphical representation of an object comprising a plurality of items, at least one of the plurality of items comprising an item pointed to by a Universal Resource Locator (URL), onto a graphical representation of a search engine on a display screen, an object manager configured to select at least one but not all of the items based on a profile defined by a selection made by the user; b. an object parser configured to parse only the selected items to generate a search term; and c. a search engine configured to perform a search with the search term to generate search results. | 35. A system for generating a search term comprising: a. in response to a user dragging-and-dropping a graphical representation of an object comprising a plurality of items, at least one of the plurality of items comprising an item pointed to by a Universal Resource Locator (URL), onto a graphical representation of a search engine on a display screen, an object manager configured to select at least one but not all of the items based on a profile defined by a selection made by the user; b. an object parser configured to parse only the selected items to generate a search term; and c. a search engine configured to perform a search with the search term to generate search results. 39. The system of claim 35 , wherein the object manager is configured to select the profile from a plurality of stored profiles each indicating items that are to be used to generate a search term. | 0.5 |
7,861,154 | 1 | 11 | 1. A computer system that facilitates enhancing data in a computer readable storage medium, the computer system comprising at least a processor and memory and also comprising: a dynamic collection component stored in the memory and executed by the processor that concurrently stores and maintains a plurality of dynamic collections of files comprising respective able user-defined queries of a file system that is maintained by the computer system, where the dynamic collections are dynamically and automatically maintained by the dynamic collection component by background monitoring of changes to the file system and automatically and dynamically adding and removing files to the dynamic collections of files according to the monitoring determining whether the files satisfy the respective queries, wherein when the dynamic collections are displayed a user interacts with the dynamic collections to generate first annotations comprising annotations of the files in respective dynamic collections therein and second annotations of respective dynamic collections but not of particular files; an annotation storage component in the memory that, by execution of the processor, stores the user-generated annotations, the annotations having been interactively generated by a user interacting with the displayed dynamic collections; an integration component that, as executed by the processor, stores first association information that associates each of the stored first annotations with a particular file and a particular dynamic collection containing the file such that a file can have multiple first annotations that are each associated with the particular file and with different respective dynamic collections, stores second association information that associates each of the stored second annotations with a particular dynamic collection but not with a particular file, wherein when a dynamic collection is displayed the first and second associations are searched to find any first and second annotations associated with the displayed dynamic collection, and any first annotations associated with a particular file in the displayed dynamic collection are displayed with respect to the corresponding file and any annotations associated with the displayed dynamic collection but not with a particular file are displayed during display of the dynamic collection. | 1. A computer system that facilitates enhancing data in a computer readable storage medium, the computer system comprising at least a processor and memory and also comprising: a dynamic collection component stored in the memory and executed by the processor that concurrently stores and maintains a plurality of dynamic collections of files comprising respective able user-defined queries of a file system that is maintained by the computer system, where the dynamic collections are dynamically and automatically maintained by the dynamic collection component by background monitoring of changes to the file system and automatically and dynamically adding and removing files to the dynamic collections of files according to the monitoring determining whether the files satisfy the respective queries, wherein when the dynamic collections are displayed a user interacts with the dynamic collections to generate first annotations comprising annotations of the files in respective dynamic collections therein and second annotations of respective dynamic collections but not of particular files; an annotation storage component in the memory that, by execution of the processor, stores the user-generated annotations, the annotations having been interactively generated by a user interacting with the displayed dynamic collections; an integration component that, as executed by the processor, stores first association information that associates each of the stored first annotations with a particular file and a particular dynamic collection containing the file such that a file can have multiple first annotations that are each associated with the particular file and with different respective dynamic collections, stores second association information that associates each of the stored second annotations with a particular dynamic collection but not with a particular file, wherein when a dynamic collection is displayed the first and second associations are searched to find any first and second annotations associated with the displayed dynamic collection, and any first annotations associated with a particular file in the displayed dynamic collection are displayed with respect to the corresponding file and any annotations associated with the displayed dynamic collection but not with a particular file are displayed during display of the dynamic collection. 11. The system of claim 1 , the file comprises a folder of a file system of the computer system. | 0.822222 |
8,947,736 | 1 | 2 | 1. A method implemented in a data processing apparatus for binarizing a gray-scale document image which has been generated by scanning a paper-based document, the method comprising: (a) identifying text characters in the gray-scale document image, including: performing an initial binarization of the gray-scale image to generate an initial binary image; and extracting connected image components in the initial binary image as text characters; (b) classifying each text character identified in step (a) as either a halftone text character which is a character formed by a halftone pattern or a non-halftone text character based on a topological analysis of the text character which determines a number of holes in a connected image component corresponding to the text character, including calculating an Euler number for each text character; and classifying a text character as halftone text if the Euler number for the text character is below a predetermined value, and classifying a text character as non-halftone text if the Euler number of the text character is equal to or above the predetermined value; and (c) binarizing halftone text characters using pixel value characteristics obtained from only halftone text characters classified in step (b). | 1. A method implemented in a data processing apparatus for binarizing a gray-scale document image which has been generated by scanning a paper-based document, the method comprising: (a) identifying text characters in the gray-scale document image, including: performing an initial binarization of the gray-scale image to generate an initial binary image; and extracting connected image components in the initial binary image as text characters; (b) classifying each text character identified in step (a) as either a halftone text character which is a character formed by a halftone pattern or a non-halftone text character based on a topological analysis of the text character which determines a number of holes in a connected image component corresponding to the text character, including calculating an Euler number for each text character; and classifying a text character as halftone text if the Euler number for the text character is below a predetermined value, and classifying a text character as non-halftone text if the Euler number of the text character is equal to or above the predetermined value; and (c) binarizing halftone text characters using pixel value characteristics obtained from only halftone text characters classified in step (b). 2. The method of claim 1 , further comprising: (d) after step (b) and before step (c), dividing the gray-scale document image into halftone text regions containing only halftone text characters and non-halftone text regions containing non-halftone text characters, wherein step (c) comprises binarizing each halftone text region using pixel value statistics calculated from pixels in that region only, to generate a binary map for each halftone text region. | 0.610733 |
8,977,538 | 1 | 10 | 1. A method for constructing a word graph, the method comprising: obtaining a subject text; dividing the subject text into one or more units; dividing the units into one or more sub-units; and recording each of the one or more sub-units, wherein recording each of the one or more sub-units includes: determining whether each sub-unit has been previously encountered; storing the sub-unit as a node if the sub-unit has not been previously encountered; proceeding with an existing node if the sub-unit has been previously encountered; preserving a relationship of each of the one or more units to one another; and preserving a relationship of each of the one or more sub-units to one another; storing a repeat factor, wherein the repeat factor indicates a number of instances in which one or more repeated sub-units have been encountered since some prior point in each of the one or more units; incrementing the repeat factor each time a repeated sub-unit is encountered since some prior point in each of the one or more units; and preserving and analyzing the relationship of each of the one or more sub-units to one another to perform a function as directed by a user, wherein the function includes comparing the constructed word graph to a user input; and outputting a result of the function to the user. | 1. A method for constructing a word graph, the method comprising: obtaining a subject text; dividing the subject text into one or more units; dividing the units into one or more sub-units; and recording each of the one or more sub-units, wherein recording each of the one or more sub-units includes: determining whether each sub-unit has been previously encountered; storing the sub-unit as a node if the sub-unit has not been previously encountered; proceeding with an existing node if the sub-unit has been previously encountered; preserving a relationship of each of the one or more units to one another; and preserving a relationship of each of the one or more sub-units to one another; storing a repeat factor, wherein the repeat factor indicates a number of instances in which one or more repeated sub-units have been encountered since some prior point in each of the one or more units; incrementing the repeat factor each time a repeated sub-unit is encountered since some prior point in each of the one or more units; and preserving and analyzing the relationship of each of the one or more sub-units to one another to perform a function as directed by a user, wherein the function includes comparing the constructed word graph to a user input; and outputting a result of the function to the user. 10. The method of claim 1 , wherein at least one of the one or more units is a sentence. | 0.913043 |
10,102,454 | 1 | 6 | 1. A computer-implemented method comprising: utilizing two or more classifiers to calculate, for an input image, probability scores for a plurality of classes based on visual information extracted from the input image and semantic relationships in a classification hierarchy, wherein each of the two or more classifiers is associated with a given one of two or more levels in the classification hierarchy with each level in the classification hierarchy comprising a subset of the plurality of classes; classifying the input image based on the calculated probability scores; training the two or more classifiers to calculate probability scores for respective subset of the plurality of classes; and performing label inference to refine classification probabilities in the two or more classifiers based on semantic relationships in the classification hierarchy; wherein training the two or more classifiers and performing label inference comprises at least one of: taking as input a graph structure having initial values for nodes corresponding to classification probabilities in the two or more classifier and outputting the graph structure with modified values for the nodes; utilizing a multi-task learning based loss function that jointly optimizes classifiers associated with each of the two or more levels in the classification hierarchy; and utilizing a random walk process that smooths classification probabilities over two or more classes in a same semantic path in the classification hierarchy. | 1. A computer-implemented method comprising: utilizing two or more classifiers to calculate, for an input image, probability scores for a plurality of classes based on visual information extracted from the input image and semantic relationships in a classification hierarchy, wherein each of the two or more classifiers is associated with a given one of two or more levels in the classification hierarchy with each level in the classification hierarchy comprising a subset of the plurality of classes; classifying the input image based on the calculated probability scores; training the two or more classifiers to calculate probability scores for respective subset of the plurality of classes; and performing label inference to refine classification probabilities in the two or more classifiers based on semantic relationships in the classification hierarchy; wherein training the two or more classifiers and performing label inference comprises at least one of: taking as input a graph structure having initial values for nodes corresponding to classification probabilities in the two or more classifier and outputting the graph structure with modified values for the nodes; utilizing a multi-task learning based loss function that jointly optimizes classifiers associated with each of the two or more levels in the classification hierarchy; and utilizing a random walk process that smooths classification probabilities over two or more classes in a same semantic path in the classification hierarchy. 6. The method of claim 1 , wherein the multi-task learning based loss function trains the two or more classifiers such that misclassification of the input image based on the calculated probability scores falls within a semantically-related category of classes for a correct classification of the input image. | 0.760125 |
10,032,463 | 5 | 11 | 5. A computer-implemented method comprising: as performed by one or more computing devices configured with specific computer-executable instructions, generating language model input data regarding an utterance of a user, wherein the language model input data is generated using an acoustic model and audio data regarding the utterance, and wherein the language model input data is associated with a plurality of transcription hypotheses for the utterance; obtaining interaction history data regarding a prior interaction of the user with a computing system; obtaining encoder state data regarding an internal state of a neural-network-based encoder reached during generation of a prior interaction history vector for the user; restoring the internal state of the neural-network-based encoder using the encoder state data; processing at least a portion of the interaction history data using the neural-network-based encoder to generate an interaction history vector, wherein the interaction history vector comprises an encoded representation of at least a portion of a plurality of prior interactions of the user, and wherein the plurality of prior interactions comprises a verbal interaction, and a separate non-verbal interaction with displayed content; processing the language model input data and the interaction history vector using a neural-network-based decoder to generate scores for individual transcription hypotheses of the plurality of transcription hypotheses; and selecting a transcription of the utterance using the scores for the individual transcription hypotheses. | 5. A computer-implemented method comprising: as performed by one or more computing devices configured with specific computer-executable instructions, generating language model input data regarding an utterance of a user, wherein the language model input data is generated using an acoustic model and audio data regarding the utterance, and wherein the language model input data is associated with a plurality of transcription hypotheses for the utterance; obtaining interaction history data regarding a prior interaction of the user with a computing system; obtaining encoder state data regarding an internal state of a neural-network-based encoder reached during generation of a prior interaction history vector for the user; restoring the internal state of the neural-network-based encoder using the encoder state data; processing at least a portion of the interaction history data using the neural-network-based encoder to generate an interaction history vector, wherein the interaction history vector comprises an encoded representation of at least a portion of a plurality of prior interactions of the user, and wherein the plurality of prior interactions comprises a verbal interaction, and a separate non-verbal interaction with displayed content; processing the language model input data and the interaction history vector using a neural-network-based decoder to generate scores for individual transcription hypotheses of the plurality of transcription hypotheses; and selecting a transcription of the utterance using the scores for the individual transcription hypotheses. 11. The computer-implemented method of claim 5 , further comprising training the neural-network-based encoder jointly with the neural-network-based decoder, wherein the training comprises: computing a gradient of an objective function, wherein the objective function represents a measure of error in output of the neural-network-based decoder; modifying a value of a parameter of the neural-network-based decoder by an amount indicated by the gradient, wherein the gradient indicates a degree to which the objective function changes with respect to a change in the parameter; and modifying a value of a parameter of the neural-network-based encoder by an amount indicated by the gradient. | 0.5 |
9,576,210 | 15 | 17 | 15. The computer-implemented method of claim 12 , wherein an output of the edge detection filter comprises a first intensity gradient in a first direction for each point of the image and a second intensity gradient in a second direction for each point of the image, the first and second directions being perpendicular to each other, and identifying the edges comprises: combining the first intensity gradient and the second intensity gradient for each point of the image; wherein the edges are identified based on the combined intensity gradients. | 15. The computer-implemented method of claim 12 , wherein an output of the edge detection filter comprises a first intensity gradient in a first direction for each point of the image and a second intensity gradient in a second direction for each point of the image, the first and second directions being perpendicular to each other, and identifying the edges comprises: combining the first intensity gradient and the second intensity gradient for each point of the image; wherein the edges are identified based on the combined intensity gradients. 17. The computer-implemented method of claim 15 , wherein determining the edge transition width of at each edge point of the plurality of edge points comprises: determining an angle based on a combination of the first intensity gradient and the second intensity gradient for the respective edge point, wherein the line is oriented based on the angle. | 0.698795 |
9,754,020 | 1 | 7 | 1. A device for determining a measure of relevancy for a seed word-keyword pair (d,k) comprising: a word identifier for identifying each unique word in the set of documents as a search word; a word pair identifier in communication with said word identifier and for combining the identified search words to define search word pairs; a unit portioner for portioning the set of documents into user-definable units, said unit portioner in communication with said interface and with said word pair identifier; a co-occurrence matrix generator in communication with said unit portioner and said word pair identifier for determining, for each defined search word pair, the number of units in which the identified search word pair occurs and for storing the number of occurrences in a co-occurrence matrix a probability matrix generator in communication with said co-occurrence matrix generator and for generating a probability matrix as a function of the co-occurrence matrix, a calibrating column vector generator, ψ, in communication with said co-occurrence matrix generator for generating a calibrating column vector; a matrix normalizer in communication with said probability matrix generator for normalizing the probability matrix to form a transition matrix, R; a word pair selector in communication with said word pair identifier for selecting the seed word-keyword pair to be measured, wherein said word pair selector provides a first column vector, {right arrow over (Γ)}(d), relating to the seed word and a second column vector, {right arrow over (Γ)}(k), relating to the keyword; an expected search distance generator in communication with said word pair selector, said probability matrix generator and said matrix normalizer, for calculating the expected search distance of the seed word-keyword pair; a weighted average expected search distance generator in communication with said expected search distance generator, said probability matrix generator, said matrix normalizer, and said calibrating column vector, said weighted average expected search distance generator for determining a weighted average expected search distance for the keyword; and a calibrator in communication with said expected search distance generator and said weighted average expected search distance generator, wherein said calibrator determines the relevancy, s d,k , of the seed word to the key word, based upon said expected search distance and said weighted averaged expected search distance. | 1. A device for determining a measure of relevancy for a seed word-keyword pair (d,k) comprising: a word identifier for identifying each unique word in the set of documents as a search word; a word pair identifier in communication with said word identifier and for combining the identified search words to define search word pairs; a unit portioner for portioning the set of documents into user-definable units, said unit portioner in communication with said interface and with said word pair identifier; a co-occurrence matrix generator in communication with said unit portioner and said word pair identifier for determining, for each defined search word pair, the number of units in which the identified search word pair occurs and for storing the number of occurrences in a co-occurrence matrix a probability matrix generator in communication with said co-occurrence matrix generator and for generating a probability matrix as a function of the co-occurrence matrix, a calibrating column vector generator, ψ, in communication with said co-occurrence matrix generator for generating a calibrating column vector; a matrix normalizer in communication with said probability matrix generator for normalizing the probability matrix to form a transition matrix, R; a word pair selector in communication with said word pair identifier for selecting the seed word-keyword pair to be measured, wherein said word pair selector provides a first column vector, {right arrow over (Γ)}(d), relating to the seed word and a second column vector, {right arrow over (Γ)}(k), relating to the keyword; an expected search distance generator in communication with said word pair selector, said probability matrix generator and said matrix normalizer, for calculating the expected search distance of the seed word-keyword pair; a weighted average expected search distance generator in communication with said expected search distance generator, said probability matrix generator, said matrix normalizer, and said calibrating column vector, said weighted average expected search distance generator for determining a weighted average expected search distance for the keyword; and a calibrator in communication with said expected search distance generator and said weighted average expected search distance generator, wherein said calibrator determines the relevancy, s d,k , of the seed word to the key word, based upon said expected search distance and said weighted averaged expected search distance. 7. The device of claim 1 , wherein said expected search distance is provided by: c _ d , k = ∑ n = 1 g n [ Γ → ( d ) ] T · [ ( I - Γ → ( k ) ⊗ Γ → ( k ) ) · R · ( I - Γ → ( k ) ⊗ Γ → ( k ) ) ] n - 1 · M · Γ → ( k ) wherein: I represents an identity matrix; {right arrow over (Γ)}(d) represents a column vector for selecting values in the transition matrix related to the word, d; {right arrow over (Γ)}(k) represents a column vector for selecting values in the transition matrix related to the word, k; R represents the transition matrix; M represents the probability matrix; and g represents the upper limit of the summation as selected by the user. | 0.5 |
7,559,022 | 1 | 18 | 1. A method of communicating information between parties comprising: automatically creating a content-dependent just-in-time application file for an electronic authored work based on the content assembled together in the authored work created by an author, wherein the file includes code for: information contained in the authored work, wherein at least a portion of the information may be stored remotely from a networked device processing the just-in-time application for presenting the authored work, creating or invoking at least one first application for presenting the content of the authored work on a networked device, disseminating the file through a computer network; and forwarding the disseminated file to a distribution channel for presenting the authored work to a recipient on a networked device, wherein upon receiving the file on the networked device, the just-in-time application file is processed creating and/or invoking the at least one first application for presenting the authored work based on the content of the authored work. | 1. A method of communicating information between parties comprising: automatically creating a content-dependent just-in-time application file for an electronic authored work based on the content assembled together in the authored work created by an author, wherein the file includes code for: information contained in the authored work, wherein at least a portion of the information may be stored remotely from a networked device processing the just-in-time application for presenting the authored work, creating or invoking at least one first application for presenting the content of the authored work on a networked device, disseminating the file through a computer network; and forwarding the disseminated file to a distribution channel for presenting the authored work to a recipient on a networked device, wherein upon receiving the file on the networked device, the just-in-time application file is processed creating and/or invoking the at least one first application for presenting the authored work based on the content of the authored work. 18. The method according to claim 1 , wherein the code further includes code related to means for transporting the just-in-time application file over a computer network, controlling editing rights of the authored work, and the presentation of the authored work on the networked device. | 0.653285 |
7,533,172 | 1 | 2 | 1. A peer-to-peer network system, comprising: a plurality of peers, wherein each peer comprises a network node configured to communicate with one or more other ones of said peers over one or more networks; a plurality of peer services or content provided by one or more of said peers; a service or content advertisement for each of said services or content, wherein each service or content advertisement comprises an identification of a corresponding service or content and an indication of how to access the corresponding service or content; a peer advertisement for each of said peers, wherein each peer advertisement comprises an identification of a corresponding one of said peers and communication address for the corresponding one of said peers, wherein one or more of said peer advertisements further comprises an indication of a service or a content provided by the peer corresponding to that peer advertisement; wherein one or more of said peers are configured to publish their corresponding peer advertisements and one or more of said service or content advertisements in the peer-to-peer network system to be discoverable by other peers; and wherein each advertisement is a separate programming language independent metadata document. | 1. A peer-to-peer network system, comprising: a plurality of peers, wherein each peer comprises a network node configured to communicate with one or more other ones of said peers over one or more networks; a plurality of peer services or content provided by one or more of said peers; a service or content advertisement for each of said services or content, wherein each service or content advertisement comprises an identification of a corresponding service or content and an indication of how to access the corresponding service or content; a peer advertisement for each of said peers, wherein each peer advertisement comprises an identification of a corresponding one of said peers and communication address for the corresponding one of said peers, wherein one or more of said peer advertisements further comprises an indication of a service or a content provided by the peer corresponding to that peer advertisement; wherein one or more of said peers are configured to publish their corresponding peer advertisements and one or more of said service or content advertisements in the peer-to-peer network system to be discoverable by other peers; and wherein each advertisement is a separate programming language independent metadata document. 2. The peer-to-peer network system as recited in claim 1 , wherein said indication of a service or content comprises one of said service or content advertisements. | 0.847378 |
9,092,437 | 15 | 18 | 15. A computer storage media having computer executable instructions stored therein, that, when executed, cause one or more processors to perform acts for creating one or more “experience streams” for use in enabling interactive narratives, said instructions comprising: defining an “experience stream” as including a set of “data binding” elements that define and populate an environment through which the experience stream runs and a set of “trajectory” elements comprising any combination of “keyframes”, “transitions”, and “markers”; wherein the set of data binding elements further includes “environment data” comprising elements including any combination of images, video, and audio; wherein the set of data binding elements further includes zero or more “artifacts” comprising one or more objects logically embedded in an image; wherein the set of data binding elements further includes zero or more highlighted regions within an image; said keyframes each comprising information states that define states of corresponding elements of the environment data at one or more points in time; said keyframes each further comprising a particular environment-to-viewport mapping at a particular point in time; wherein each environment-to-viewport mapping is defined by one or more layout constraints that dictate a size and position of each viewport relative to each other viewport in the environment; and said “markers” being used to specify a particular point in a logical sequence of an interactive narrative constructed by combining multiple experience streams. | 15. A computer storage media having computer executable instructions stored therein, that, when executed, cause one or more processors to perform acts for creating one or more “experience streams” for use in enabling interactive narratives, said instructions comprising: defining an “experience stream” as including a set of “data binding” elements that define and populate an environment through which the experience stream runs and a set of “trajectory” elements comprising any combination of “keyframes”, “transitions”, and “markers”; wherein the set of data binding elements further includes “environment data” comprising elements including any combination of images, video, and audio; wherein the set of data binding elements further includes zero or more “artifacts” comprising one or more objects logically embedded in an image; wherein the set of data binding elements further includes zero or more highlighted regions within an image; said keyframes each comprising information states that define states of corresponding elements of the environment data at one or more points in time; said keyframes each further comprising a particular environment-to-viewport mapping at a particular point in time; wherein each environment-to-viewport mapping is defined by one or more layout constraints that dictate a size and position of each viewport relative to each other viewport in the environment; and said “markers” being used to specify a particular point in a logical sequence of an interactive narrative constructed by combining multiple experience streams. 18. The computer storage media of claim 15 wherein each experience stream provides an interactive scripted path through the environment data, and wherein two or more keyframes are bundled into a keyframe sequence that makes up the interactive scripted path through the environment data. | 0.657074 |
8,606,652 | 8 | 9 | 8. A system comprising: one or more computers configured to generate a graphical user interface for a retail environment on at least one display, the graphical user interface including: a vertical scroll means; an upper region including a horizontal rotating carousel including a plurality of product tile regions and a main product image extending beyond an upper border or a lower border of the horizontal rotating carousel and having an image size substantially larger than a tile region size of any product tile region, the main product image visually depicting a main product, the main product image being of a main product within a product category, each of the product tile regions including a respective thumbnail image visually depicting a respective product within the product category, the horizontal rotating carousel being configured to allow a user to scroll horizontally through the plurality of product tile regions; a middle region positioned below the upper region comprised of two generally parallel and vertical column sub-regions, the column sub-regions including a left sub-region and a right sub-region, wherein the left sub-region displays a widget bar including one or more user reviews from one or more socially networked users being socially networked with the web page user, and one or more aggregate customer reviews, the widget bar being configured to accept category reviews from a web page user, wherein the user reviews are categorized into two or more product categories; and wherein a subset of the user reviews presented on the web page are selected based in part upon the product category of a user review section hovered over by a cursor, the user review section being a portion of the user reviews, and wherein the right sub-region comprises one or more detailed features of the main product, one or more third party recommendations about the main product, one or more product images showing customers using the main product; and a comparable alternative product tile; and a lower region positioned below the middle region comprising an array of product tiles, each product tile having a respective thumbnail image of a respective alternative product selected from the product category, the thumbnail image being a visual depiction of the respective alternative product, wherein a ratio of overall height to overall width of the graphical user interface is at least about 4:1 or greater, wherein the array of product tiles exists substantially below the lower boundary viewable on a conventional display monitor when the vertical scroll means is at an uppermost scroll position. | 8. A system comprising: one or more computers configured to generate a graphical user interface for a retail environment on at least one display, the graphical user interface including: a vertical scroll means; an upper region including a horizontal rotating carousel including a plurality of product tile regions and a main product image extending beyond an upper border or a lower border of the horizontal rotating carousel and having an image size substantially larger than a tile region size of any product tile region, the main product image visually depicting a main product, the main product image being of a main product within a product category, each of the product tile regions including a respective thumbnail image visually depicting a respective product within the product category, the horizontal rotating carousel being configured to allow a user to scroll horizontally through the plurality of product tile regions; a middle region positioned below the upper region comprised of two generally parallel and vertical column sub-regions, the column sub-regions including a left sub-region and a right sub-region, wherein the left sub-region displays a widget bar including one or more user reviews from one or more socially networked users being socially networked with the web page user, and one or more aggregate customer reviews, the widget bar being configured to accept category reviews from a web page user, wherein the user reviews are categorized into two or more product categories; and wherein a subset of the user reviews presented on the web page are selected based in part upon the product category of a user review section hovered over by a cursor, the user review section being a portion of the user reviews, and wherein the right sub-region comprises one or more detailed features of the main product, one or more third party recommendations about the main product, one or more product images showing customers using the main product; and a comparable alternative product tile; and a lower region positioned below the middle region comprising an array of product tiles, each product tile having a respective thumbnail image of a respective alternative product selected from the product category, the thumbnail image being a visual depiction of the respective alternative product, wherein a ratio of overall height to overall width of the graphical user interface is at least about 4:1 or greater, wherein the array of product tiles exists substantially below the lower boundary viewable on a conventional display monitor when the vertical scroll means is at an uppermost scroll position. 9. The system of claim 8 , wherein the upper region includes one or more thumbnail images of the main product which allow the web page user upon selection to change the main product image. | 0.5 |
10,146,979 | 1 | 3 | 1. A method comprising: by first program instructions on a computing device: receiving a visual cue, said visual cue including visual media of a target, the visual media comprising a digital graphic image, the target comprising an object depicted in the image, the visual cue comprising a characteristic of the target; extracting visual cue identification data from the visual cue, including performing at least one of an image recognition operation and an object recognition operation; determining from the extracted visual cue identification data a list of words representing the target; storing the list of words representing the target; updating a probable words dictionary to include the list of words; and assigning a priority weighting factor to each word determined from the visual cue identification data extracted from the object depicted in the image and added to the probable word dictionary, wherein the priority weighting factor indicates that each word added to the probable word dictionary is given a higher priority than existing words in the probable word dictionary that were not determined from the visual cue identification data extracted from the object depicted in the image. | 1. A method comprising: by first program instructions on a computing device: receiving a visual cue, said visual cue including visual media of a target, the visual media comprising a digital graphic image, the target comprising an object depicted in the image, the visual cue comprising a characteristic of the target; extracting visual cue identification data from the visual cue, including performing at least one of an image recognition operation and an object recognition operation; determining from the extracted visual cue identification data a list of words representing the target; storing the list of words representing the target; updating a probable words dictionary to include the list of words; and assigning a priority weighting factor to each word determined from the visual cue identification data extracted from the object depicted in the image and added to the probable word dictionary, wherein the priority weighting factor indicates that each word added to the probable word dictionary is given a higher priority than existing words in the probable word dictionary that were not determined from the visual cue identification data extracted from the object depicted in the image. 3. The method of claim 1 wherein updating the probable words dictionary comprises: determining whether each word in the list of words is present in the probable words dictionary; and for each word not found in the probable words dictionary, adding the word to the probable words dictionary. | 0.5 |
8,793,124 | 1 | 2 | 1. A speech processing method performed using a processor for deciding whether a portion of input speech is emphasized or not based on a set of speech parameters for each frame, comprising the steps of: (a) obtaining from a codebook a plurality of speech parameter vectors each corresponding to a respective set of speech parameters obtained from respective ones of a plurality of frames in the portion of the input speech, said codebook storing, for each of a plural number of predetermined speech parameter vectors, a corresponding pair of a normal-state appearance probability and an emphasized-state appearance probability both predetermined using a training speech signal, each of said plural number of predetermined speech parameter vectors being composed of a set of speech parameters including at least one of a fundamental frequency, power and a temporal variation of dynamic-measure and/or an inter-frame difference in at least one of those speech parameters, and obtaining from said codebook a pair of an emphasized-state appearance probability and a normal-state appearance probability both corresponding to each speech parameter vector obtained for the respective ones of the plurality of frames in the portion of the input speech; (b) using the processor, calculating an emphasized-state likelihood of the portion of the input speech by multiplying together emphasized-state appearance probabilities corresponding to the respective speech parameter vectors for the plurality of frames in the portion of the input speech, and calculating a normal-state likelihood of the portion of the input speech by multiplying together normal-state appearance probabilities corresponding to the respective speech parameter vectors for the plurality of frames in the portion of the input speech; and (c) deciding whether the portion of the input speech is emphasized or not based on said calculated emphasized-state likelihood and said calculated normal-state likelihood, and outputting a decision result of said deciding, the decision result indicating whether the portion of the input speech is emphasized or not, wherein the codebook stores, for each of the plural predetermined speech parameter vectors, a respective independent emphasized-state appearance probability and a respective set of conditional emphasized-state appearance probabilities, both used as respective said emphasized-state appearance probability, and stores, for each of the plural predetermined speech parameter vectors, a respective independent normal-state appearance probability and a set of conditional normal-state appearance probabilities, both used as respective said normal-state appearance probability, such that there is at least stored a separate conditional emphasized-state appearance probability and a separate conditional normal-state appearance probability for a possible speech parameter vector that immediately follows the respective speech parameter vector in the codebook, and wherein the step of calculating the emphasized-state likelihood in said step (b) is implemented by multiplying together the independent emphasized-state appearance probability and the conditional emphasized-state appearance probabilities corresponding to the speech parameter vectors of respective first frame and subsequent frames in said portion of the input speech, and the step of calculating the normal-state likelihood in said step (b) is implemented by multiplying together the independent normal-state appearance probability and the conditional normal-state appearance probabilities corresponding to the speech parameter vectors of respective said first frame and said subsequent frames in said portion of the input speech. | 1. A speech processing method performed using a processor for deciding whether a portion of input speech is emphasized or not based on a set of speech parameters for each frame, comprising the steps of: (a) obtaining from a codebook a plurality of speech parameter vectors each corresponding to a respective set of speech parameters obtained from respective ones of a plurality of frames in the portion of the input speech, said codebook storing, for each of a plural number of predetermined speech parameter vectors, a corresponding pair of a normal-state appearance probability and an emphasized-state appearance probability both predetermined using a training speech signal, each of said plural number of predetermined speech parameter vectors being composed of a set of speech parameters including at least one of a fundamental frequency, power and a temporal variation of dynamic-measure and/or an inter-frame difference in at least one of those speech parameters, and obtaining from said codebook a pair of an emphasized-state appearance probability and a normal-state appearance probability both corresponding to each speech parameter vector obtained for the respective ones of the plurality of frames in the portion of the input speech; (b) using the processor, calculating an emphasized-state likelihood of the portion of the input speech by multiplying together emphasized-state appearance probabilities corresponding to the respective speech parameter vectors for the plurality of frames in the portion of the input speech, and calculating a normal-state likelihood of the portion of the input speech by multiplying together normal-state appearance probabilities corresponding to the respective speech parameter vectors for the plurality of frames in the portion of the input speech; and (c) deciding whether the portion of the input speech is emphasized or not based on said calculated emphasized-state likelihood and said calculated normal-state likelihood, and outputting a decision result of said deciding, the decision result indicating whether the portion of the input speech is emphasized or not, wherein the codebook stores, for each of the plural predetermined speech parameter vectors, a respective independent emphasized-state appearance probability and a respective set of conditional emphasized-state appearance probabilities, both used as respective said emphasized-state appearance probability, and stores, for each of the plural predetermined speech parameter vectors, a respective independent normal-state appearance probability and a set of conditional normal-state appearance probabilities, both used as respective said normal-state appearance probability, such that there is at least stored a separate conditional emphasized-state appearance probability and a separate conditional normal-state appearance probability for a possible speech parameter vector that immediately follows the respective speech parameter vector in the codebook, and wherein the step of calculating the emphasized-state likelihood in said step (b) is implemented by multiplying together the independent emphasized-state appearance probability and the conditional emphasized-state appearance probabilities corresponding to the speech parameter vectors of respective first frame and subsequent frames in said portion of the input speech, and the step of calculating the normal-state likelihood in said step (b) is implemented by multiplying together the independent normal-state appearance probability and the conditional normal-state appearance probabilities corresponding to the speech parameter vectors of respective said first frame and said subsequent frames in said portion of the input speech. 2. The method of claim 1 , wherein said codebook stores, for the plural number of predetermined speech parameter vectors, respective codes representing the respective predetermined speech parameter vectors, and said step (a) further includes a step of quantizing each set of speech parameters obtained from respective one of the plurality of the frames in the portion of the input speech by using said codebook to obtain the code. | 0.742515 |
4,178,472 | 8 | 11 | 8. A voiced instruction identification system, particularly for controlling a powered device by voiced instructions of a source person, comprising: means including a microphone and band pass filter for passing a limited frequency band of electrical signals corresponding to spoken moras; Schmidt trigger means for converting said limited frequency band of electrical signals from sine wave form to square wave pulses with several Schmidt pulses per mora; means for eliminating the initial unstable portion of the Schmidt pulses for each mora; a clock pulse source of frequency greater than frequencies in said band, and counter means responsive in each mora to Schmidt pulses occurring subsequent to said initial unstable portion for counting the number of clock pulses in each of a selected number of said subsequent Schmidt pulses so as to produce a selected number of clock pulse totals for each mora; symbolic value sampling means for selecting a representative one of said clock pulse totals and producing an output corresponding quantatively to said representative total, for each mora; tonal pattern change detecting means for detecting a change in said symbolic value sampling means output between consecutively occurring ones of said moras, such that the detected changes provide a tonal change pattern usable to identify the spoken command comprising said moras. | 8. A voiced instruction identification system, particularly for controlling a powered device by voiced instructions of a source person, comprising: means including a microphone and band pass filter for passing a limited frequency band of electrical signals corresponding to spoken moras; Schmidt trigger means for converting said limited frequency band of electrical signals from sine wave form to square wave pulses with several Schmidt pulses per mora; means for eliminating the initial unstable portion of the Schmidt pulses for each mora; a clock pulse source of frequency greater than frequencies in said band, and counter means responsive in each mora to Schmidt pulses occurring subsequent to said initial unstable portion for counting the number of clock pulses in each of a selected number of said subsequent Schmidt pulses so as to produce a selected number of clock pulse totals for each mora; symbolic value sampling means for selecting a representative one of said clock pulse totals and producing an output corresponding quantatively to said representative total, for each mora; tonal pattern change detecting means for detecting a change in said symbolic value sampling means output between consecutively occurring ones of said moras, such that the detected changes provide a tonal change pattern usable to identify the spoken command comprising said moras. 11. The apparatus of claim 8, in which said tonal pattern change detecting means includes a pitch data stack for sequentially storing said symbolic value sampling means outputs each quantatively corresponding to a respective clock pulse total, said apparatus further including a rhythm counter and means supplying same with further clock pulses for counting the time interval during which the sound for each mora is present, and a rhythm data stack for receiving count data from said rhythm counter for each of the desired number of moras. | 0.5 |
8,952,897 | 15 | 16 | 15. An electronic device comprising a touchscreen, the touchscreen being configured to be used as a soft input panel (SIP) for the electronic device, wherein the SIP is configured for entering text in a non-English language, wherein the characters used in the language are available to be entered with the SIP without switching between different pages of keys and without using a function key, wherein at least one of the keys on the main page of keys is a diacritic base key that is configured to open a diacritic picker window when activated, the diacritic picker window comprising plural diacritic picker keys, the plural diacritic picker keys representing different diacritics used in the language, wherein the SIP comprises a plurality of vowel keys grouped together in a row separate from consonant keys, the plurality of vowel keys comprising one vowel key for each vowel of the language, wherein each vowel key is configured to select either a short form or a long form of the respective vowel when touched and released, wherein the plurality of vowel keys comprises a plurality of joining vowel keys grouped together in a first portion of the row and a plurality of independent vowel keys grouped together in a second portion of the row, the second portion of the row adjoining the first portion of the row, wherein each of the independent vowel keys in the second portion of the row is configured to open an associated picker window when activated, each picker window comprising a first picker key for a long form of the respective independent vowel and a second picker key for a short form of the respective vowel. | 15. An electronic device comprising a touchscreen, the touchscreen being configured to be used as a soft input panel (SIP) for the electronic device, wherein the SIP is configured for entering text in a non-English language, wherein the characters used in the language are available to be entered with the SIP without switching between different pages of keys and without using a function key, wherein at least one of the keys on the main page of keys is a diacritic base key that is configured to open a diacritic picker window when activated, the diacritic picker window comprising plural diacritic picker keys, the plural diacritic picker keys representing different diacritics used in the language, wherein the SIP comprises a plurality of vowel keys grouped together in a row separate from consonant keys, the plurality of vowel keys comprising one vowel key for each vowel of the language, wherein each vowel key is configured to select either a short form or a long form of the respective vowel when touched and released, wherein the plurality of vowel keys comprises a plurality of joining vowel keys grouped together in a first portion of the row and a plurality of independent vowel keys grouped together in a second portion of the row, the second portion of the row adjoining the first portion of the row, wherein each of the independent vowel keys in the second portion of the row is configured to open an associated picker window when activated, each picker window comprising a first picker key for a long form of the respective independent vowel and a second picker key for a short form of the respective vowel. 16. The device of claim 15 , wherein the SIP comprises a plurality of consonant keys, at least one of the consonant keys being a consonant base key that is configured to open a consonant picker window when activated, the consonant picker window comprising a plurality of consonant picker keys associated with plurality of consonants grouped together by sound. | 0.5 |
9,760,568 | 4 | 5 | 4. The computer-implemented method of claim 1 , the method further comprising the following operations performed by the at least one processor: enabling the second user to provide preference information related to a description of activities taking place in a sub-portion of the virtual world environment; and providing the second user with the description of activities taking place in the sub-portion of the virtual world environment in accordance with the preference information. | 4. The computer-implemented method of claim 1 , the method further comprising the following operations performed by the at least one processor: enabling the second user to provide preference information related to a description of activities taking place in a sub-portion of the virtual world environment; and providing the second user with the description of activities taking place in the sub-portion of the virtual world environment in accordance with the preference information. 5. The computer-implemented method of claim 4 , wherein the preference information includes at least one of: a quantity of descriptions to be provided to the second user, a type of descriptions to be provided to the second user, or a list of other users about whom descriptions are to be provided to the second user. | 0.5 |
8,781,991 | 1 | 2 | 1. An emotion recognition apparatus, comprising: a data collection unit configured to collect sensing data from a terminal; a first emotion value acquisition unit configured to acquire a first emotion value corresponding to a first axis of a multidimensional emotion model based on an amount or an intensity of the sensing data; a second emotion value acquisition unit configured to acquire a second emotion value corresponding to a second axis of the multidimensional emotion model based on a textual meaning of the sensing data; and an emotion estimation unit configured to estimate an emotional state of a user based on the first emotion value and the second emotion value. | 1. An emotion recognition apparatus, comprising: a data collection unit configured to collect sensing data from a terminal; a first emotion value acquisition unit configured to acquire a first emotion value corresponding to a first axis of a multidimensional emotion model based on an amount or an intensity of the sensing data; a second emotion value acquisition unit configured to acquire a second emotion value corresponding to a second axis of the multidimensional emotion model based on a textual meaning of the sensing data; and an emotion estimation unit configured to estimate an emotional state of a user based on the first emotion value and the second emotion value. 2. The emotion recognition apparatus of claim 1 , wherein the first emotion value acquisition unit further acquires first-level data relating to the user's level of arousal by analyzing the amount or the intensity of the sensing data, and acquires the first emotion value based on the first-level data. | 0.782734 |
8,712,989 | 1 | 9 | 1. A method comprising: accepting a request to a wild card auto completion service including an input term at least partly in a target language and at least partly in an initial language, wherein the initial language and the target language are two different languages, the service employing a syntax to accept the input term including zero to multiple wild card characters in the target language or in the initial language in a first part and a delimiter indicating a second part, the second part comprising the target language or the initial language such that: if the language of the first part includes the initial language, the second part includes the target language and if the language of the first part includes the target language, the second part includes the initial language, and the second part identifying at least one of a context or a domain for the wild card auto completion service; identifying an initial-target language pair for the request; aggregating two or more consecutive homogenous wild card characters, wherein the aggregating comprises replacing the two or more consecutive homogenous wild card characters with a single wild card character of a same type as the homogenous wild card character; parsing the input term to identify a pattern of the input term; selecting a matcher corresponding to the pattern of the input term; matching the input term to an entry using the matcher selected; and returning the entry. | 1. A method comprising: accepting a request to a wild card auto completion service including an input term at least partly in a target language and at least partly in an initial language, wherein the initial language and the target language are two different languages, the service employing a syntax to accept the input term including zero to multiple wild card characters in the target language or in the initial language in a first part and a delimiter indicating a second part, the second part comprising the target language or the initial language such that: if the language of the first part includes the initial language, the second part includes the target language and if the language of the first part includes the target language, the second part includes the initial language, and the second part identifying at least one of a context or a domain for the wild card auto completion service; identifying an initial-target language pair for the request; aggregating two or more consecutive homogenous wild card characters, wherein the aggregating comprises replacing the two or more consecutive homogenous wild card characters with a single wild card character of a same type as the homogenous wild card character; parsing the input term to identify a pattern of the input term; selecting a matcher corresponding to the pattern of the input term; matching the input term to an entry using the matcher selected; and returning the entry. 9. A method as recited in claim 1 , wherein the pattern of the input term includes one or more of a pattern string parameter that represents the input term, a patternStartIndex parameter that represents a location to start matching the input term to dictionary entries, or a patternLength parameter that represents a length of the input term in terms of a number of characters entered. | 0.605533 |
9,122,376 | 1 | 11 | 1. A method comprising: after receiving, an indication of user input that selects one or more textual characters, receiving, by a computing device, an indication of user input that selects an end-of-word identifier; determining, by the computing device, based at least in part on the one or more textual characters and in response to receiving the end-of-word identifier, a first auto-complete word suggestion from a plurality of auto-complete word suggestions, wherein the first auto-complete word suggestion is determined to be more likely to be a correct word suggestion than a second auto-complete word suggestion from the plurality of auto-complete word suggestions; outputting, by the computing device, for display, the first auto-complete word suggestion that replaces the one or more textual characters followed by the end-of-word identifier; receiving, by the computing device, an indication of user input that deletes the end-of-word identifier, wherein the indication of user input that deletes the end-of-word identifier comprises a combination of a selection of both a backspace key and a spacebar key; and responsive to receiving the indication of user input that deletes the end-of-word identifier, outputting, by the computing device, for display, the second auto-complete word suggestion, wherein the second auto-complete word suggestion replaces the first auto-complete word suggestion; wherein the end-of-word identifier is a first end-of-word identifier and outputting the second auto-complete word suggestion comprises outputting, by the computing device, for display, the second auto-complete word suggestion followed by a second end-of-word identifier replacing the first auto-complete word suggestion and the first end-of-word identifier. | 1. A method comprising: after receiving, an indication of user input that selects one or more textual characters, receiving, by a computing device, an indication of user input that selects an end-of-word identifier; determining, by the computing device, based at least in part on the one or more textual characters and in response to receiving the end-of-word identifier, a first auto-complete word suggestion from a plurality of auto-complete word suggestions, wherein the first auto-complete word suggestion is determined to be more likely to be a correct word suggestion than a second auto-complete word suggestion from the plurality of auto-complete word suggestions; outputting, by the computing device, for display, the first auto-complete word suggestion that replaces the one or more textual characters followed by the end-of-word identifier; receiving, by the computing device, an indication of user input that deletes the end-of-word identifier, wherein the indication of user input that deletes the end-of-word identifier comprises a combination of a selection of both a backspace key and a spacebar key; and responsive to receiving the indication of user input that deletes the end-of-word identifier, outputting, by the computing device, for display, the second auto-complete word suggestion, wherein the second auto-complete word suggestion replaces the first auto-complete word suggestion; wherein the end-of-word identifier is a first end-of-word identifier and outputting the second auto-complete word suggestion comprises outputting, by the computing device, for display, the second auto-complete word suggestion followed by a second end-of-word identifier replacing the first auto-complete word suggestion and the first end-of-word identifier. 11. The method of claim 1 , wherein the indication of user input that selects the one or more textual characters, the indication of user input that selects the end-of-word identifier, and the indication of user input that deletes the end-of-word identifier are each received at an input device comprising a presence-sensitive screen, the method further comprising: outputting, by the computing device, for display at the presence-sensitive screen, a graphical keyboard comprising a plurality of keys, wherein the indication of user input that selects the one or more textual characters, the indication of user input that selects the end-of-word identifier, and the indication of user input that deletes the end-of-word identifier each comprise respective representations of selections of one or more of the plurality of keys. | 0.541157 |
8,332,383 | 50 | 52 | 50. A system to process a data search request, the system including: a processor controlling operation of the system, including communication of information and control of a plurality of modules; a query controller module to receive the data search request, the data search request including a plurality of constraints that includes a first keyword; an expansion module to associate the first keyword to at least one category; a search engine to perform a search of a data source based on the data search request to find and count a number of data items; a reduced constraint builder module to formulate a search definition that includes the at least one category in response to an identification of the number of data items in excess of a predetermined threshold minimum number of data items, each search definition being formulated to exclude at least one constraint; and a data source to store database tables, including a data item table, a configuration table, and a keyword expansion table, the data item table to store and retrieve data items, the configuration table to store various configurable parameters for the search engine, and the keyword expansion table to expand a keyword constraint to forms of the keyword constraint by the expansion module; wherein the search engine is configured to perform a search of the data source based on the search definition, and to calculate a data item count for the search definition. | 50. A system to process a data search request, the system including: a processor controlling operation of the system, including communication of information and control of a plurality of modules; a query controller module to receive the data search request, the data search request including a plurality of constraints that includes a first keyword; an expansion module to associate the first keyword to at least one category; a search engine to perform a search of a data source based on the data search request to find and count a number of data items; a reduced constraint builder module to formulate a search definition that includes the at least one category in response to an identification of the number of data items in excess of a predetermined threshold minimum number of data items, each search definition being formulated to exclude at least one constraint; and a data source to store database tables, including a data item table, a configuration table, and a keyword expansion table, the data item table to store and retrieve data items, the configuration table to store various configurable parameters for the search engine, and the keyword expansion table to expand a keyword constraint to forms of the keyword constraint by the expansion module; wherein the search engine is configured to perform a search of the data source based on the search definition, and to calculate a data item count for the search definition. 52. The system of claim 50 , wherein the expansion module associates the second keyword to a second constraint that is included in the search definition, the second constraint to include any one of a group of alternate forms of the second keyword including a plural form of the second keyword, an alternate spelling of the second keyword, an alternate word form of the second keyword, an acronym of the second keyword, and a synonym of the second keyword. | 0.5 |
9,613,024 | 13 | 20 | 13. The system of claim 12 , wherein the one or more processors are further operable to produce a first score to represent the strength measure based on the occurrence, location, or attributes associated with the first term or the one or more second terms, wherein the group of second terms are collected based on the first score. | 13. The system of claim 12 , wherein the one or more processors are further operable to produce a first score to represent the strength measure based on the occurrence, location, or attributes associated with the first term or the one or more second terms, wherein the group of second terms are collected based on the first score. 20. The system of claim 13 , wherein the first score is produced based on the occurrence or attributes associated with the one or more second terms in text units that do not contain the first term, or based on the number of text units that contain the one or more second terms but do not contain the first term. | 0.501603 |
4,228,510 | 4 | 5 | 4. An apparatus of claim 1, including means for increasing the size of the character. | 4. An apparatus of claim 1, including means for increasing the size of the character. 5. An apparatus of claim 4, wherein said size increasing means includes means for increasing the numerical value of the count information prior to the count information being presented to said counter. | 0.5 |
9,293,061 | 1 | 3 | 1. A method for creating a mnemonic experience for a user, which comprises: selecting a concentration of information to be remembered; gathering information on said concentration, said information being intended to be remembered by the user; providing a building; placing a display to be observed in said building, said display teaching said information when observed by the user; providing a character to interact with the user and said display, said character being contextually related to said display; interacting said character with the user with while the user observes said display; gathering further information on said concentration; determining an importance of said information relative to an importance of said further information; and not creating a display of said further information when said importance of said further information is less than the importance of said piece of information. | 1. A method for creating a mnemonic experience for a user, which comprises: selecting a concentration of information to be remembered; gathering information on said concentration, said information being intended to be remembered by the user; providing a building; placing a display to be observed in said building, said display teaching said information when observed by the user; providing a character to interact with the user and said display, said character being contextually related to said display; interacting said character with the user with while the user observes said display; gathering further information on said concentration; determining an importance of said information relative to an importance of said further information; and not creating a display of said further information when said importance of said further information is less than the importance of said piece of information. 3. The method according to claim 1 , which further comprises: placing a further display to be observed in said building, said display teaching said further information when observed by the user; and locating said display and said further display to cause the user to remember about said concentration. | 0.5 |
9,489,374 | 9 | 11 | 9. The computer readable storage medium according to claim 1 , wherein the program causes the computer to perform further operations comprising: receiving an instruction to delete the fixed character string; identifying a character string preceding the fixed character string to be deleted and a character string following the fixed character string to be deleted; determining whether or not the character string preceding the fixed character string to be deleted and the character string following the fixed character string to be deleted are connectable to each other; and when it is determined that the character strings preceding and following the fixed character string to be deleted are connectable to each other, changing the fixed character string to be deleted into an unfixed character. | 9. The computer readable storage medium according to claim 1 , wherein the program causes the computer to perform further operations comprising: receiving an instruction to delete the fixed character string; identifying a character string preceding the fixed character string to be deleted and a character string following the fixed character string to be deleted; determining whether or not the character string preceding the fixed character string to be deleted and the character string following the fixed character string to be deleted are connectable to each other; and when it is determined that the character strings preceding and following the fixed character string to be deleted are connectable to each other, changing the fixed character string to be deleted into an unfixed character. 11. The computer readable storage medium according to claim 9 , wherein the program causes the computer to perform further operations comprising: when the character string preceding the fixed character string and the character string following the fixed character string are determined to be not connectable to each other, determining, as a connectable character string, a character string located at a rearmost position among character strings that precede the fixed character string and that are connectable to the character string following the fixed character string, and changing all character strings present between the connectable character string and the character string following the fixed character string, into unfixed characters. | 0.5 |
8,832,212 | 16 | 19 | 16. A method for initiating instant messaging within a social networking website, the method comprising: providing for display of a post within the social networking website, the post being associated with a first user, a second user, and a third user; providing for display of a graphical component within the social networking website, wherein the graphical component provides an interface for requesting communication related to the post by instant messaging, the interface comprising one of a separate window and a separate menu allowing for selection of users to be invited to communicate by instant messaging; receiving a request for communication related to the post by instant messaging via the graphical component; initiating instant messaging between the first user, the second user, and the third user in response to the received request for communication related to the post; providing for the display of a chat window of the initiated instant messaging, the chat window comprising information associated with the post, wherein all users invited into the initiated instant messaging are listed in a heading of the chat window; and sending a notification to each user of the first user, the second user, and the third user that is idle within the social networking website or offline. | 16. A method for initiating instant messaging within a social networking website, the method comprising: providing for display of a post within the social networking website, the post being associated with a first user, a second user, and a third user; providing for display of a graphical component within the social networking website, wherein the graphical component provides an interface for requesting communication related to the post by instant messaging, the interface comprising one of a separate window and a separate menu allowing for selection of users to be invited to communicate by instant messaging; receiving a request for communication related to the post by instant messaging via the graphical component; initiating instant messaging between the first user, the second user, and the third user in response to the received request for communication related to the post; providing for the display of a chat window of the initiated instant messaging, the chat window comprising information associated with the post, wherein all users invited into the initiated instant messaging are listed in a heading of the chat window; and sending a notification to each user of the first user, the second user, and the third user that is idle within the social networking website or offline. 19. The method of claim 16 , further comprising: receiving a comment on the post from a fourth user during the initiated instant messaging; and sending a notification to the first user, the second user, and the third user. | 0.5 |
7,496,559 | 50 | 74 | 50. A computerized search system, comprising: a single search interface configured for display on a display device, the single search interface comprising at least an email search interface, an email attachment search interface, a Web history search interface, a favorites search interface, and a file search interface, wherein the interfaces are configured for alternate display within the single search interface; a first target search interface including: a plurality of target-specific attribute search fields that are displayed at the same time, the target-specific attribute search fields comprising one or more of a date field, a from field, and a sender field that are displayed at the same time when searching a plurality of emails and the target-specific attribute search fields comprising one or more of a file name field, a file type field, a date field, a file size field, and a path field that are displayed at the same time when searching a plurality of files; a view area; a list area; and at least one processor configured to access at least one index comprising data regarding at least one of a plurality of emails and a plurality of files in order to perform incremental searching of at least one of the plurality of emails and the plurality of files as the user enters characters into one or more of the target-specific attribute search fields and outputs a list of search results in the list area and content of a selected search result in the view area. | 50. A computerized search system, comprising: a single search interface configured for display on a display device, the single search interface comprising at least an email search interface, an email attachment search interface, a Web history search interface, a favorites search interface, and a file search interface, wherein the interfaces are configured for alternate display within the single search interface; a first target search interface including: a plurality of target-specific attribute search fields that are displayed at the same time, the target-specific attribute search fields comprising one or more of a date field, a from field, and a sender field that are displayed at the same time when searching a plurality of emails and the target-specific attribute search fields comprising one or more of a file name field, a file type field, a date field, a file size field, and a path field that are displayed at the same time when searching a plurality of files; a view area; a list area; and at least one processor configured to access at least one index comprising data regarding at least one of a plurality of emails and a plurality of files in order to perform incremental searching of at least one of the plurality of emails and the plurality of files as the user enters characters into one or more of the target-specific attribute search fields and outputs a list of search results in the list area and content of a selected search result in the view area. 74. The computerized search system as defined in claim 50 , wherein the search system automatically displays the first occurrence of a search string. | 0.891399 |
9,740,297 | 1 | 7 | 1. A computer-implemented method, comprising: receiving first image data captured using one or more imaging sensors associated with an electronic device; analyzing the first image data to determine a first relative orientation between the electronic device and at least a first portion of an object represented in the first image data; displaying a plurality of selectable elements on a display element associated with the electronic device; receiving second image data captured using the one or more imaging sensors; analyzing the second image data to determine a second relative orientation between the electronic device and at least a second portion of the object represented in the second image data; determining a first rate of a first change in orientation between the first relative orientation and the second relative orientation; displaying a first movement of a selection element to a first selectable element of the plurality of selectable elements on the display element such that a first direction of the first movement corresponds to the first change in orientation and a second rate of the first movement corresponds to the first rate of the first change in orientation; receiving third image data captured using the one or more imaging sensors; analyzing the third image data to determine a third relative orientation between the electronic device and at least a third portion of the object represented in the third image data; determining a third rate of a second change in orientation between the second relative orientation and the third relative orientation; displaying a second movement of the selection element to a second selectable element of the plurality of selectable elements on the display element such that a second direction of the second movement corresponds to the second change in orientation and a fourth rate of the second movement corresponds to the third rate of the second change in orientation; receiving a selection of the second selectable element; and performing an action on the electronic device associated with the selection of the second selectable element. | 1. A computer-implemented method, comprising: receiving first image data captured using one or more imaging sensors associated with an electronic device; analyzing the first image data to determine a first relative orientation between the electronic device and at least a first portion of an object represented in the first image data; displaying a plurality of selectable elements on a display element associated with the electronic device; receiving second image data captured using the one or more imaging sensors; analyzing the second image data to determine a second relative orientation between the electronic device and at least a second portion of the object represented in the second image data; determining a first rate of a first change in orientation between the first relative orientation and the second relative orientation; displaying a first movement of a selection element to a first selectable element of the plurality of selectable elements on the display element such that a first direction of the first movement corresponds to the first change in orientation and a second rate of the first movement corresponds to the first rate of the first change in orientation; receiving third image data captured using the one or more imaging sensors; analyzing the third image data to determine a third relative orientation between the electronic device and at least a third portion of the object represented in the third image data; determining a third rate of a second change in orientation between the second relative orientation and the third relative orientation; displaying a second movement of the selection element to a second selectable element of the plurality of selectable elements on the display element such that a second direction of the second movement corresponds to the second change in orientation and a fourth rate of the second movement corresponds to the third rate of the second change in orientation; receiving a selection of the second selectable element; and performing an action on the electronic device associated with the selection of the second selectable element. 7. The computer-implemented method of claim 1 , further comprising: providing at least two modes of control over the selection element. | 0.833744 |
9,342,907 | 8 | 14 | 8. A method for analyzing ballistic trajectories comprising: determining, using a preprocessor, invariants for known ballistic objects; defining, using the preprocessor, a reference graph having nodes corresponding to the invariants for the known ballistic objects; defining, using the preprocessor, a query graph having nodes connected to nodes of the reference graph corresponding to anticipated invariant queries to be made using the query graph; inputting into the reference graph, using a runtime processor, one or more sets of invariants corresponding to trajectories of one or more observed objects, each of the one or more sets of invariants traversing through the nodes of the reference graph corresponding to the each of the one or more sets of invariants and leaving a record in the nodes traversed; selecting, using an interface, a query for the query graph corresponding to one or more range of invariants, said query generating a query result identifying the nodes of the reference graph that satisfy the query; and identifying, using the runtime processor, each of the one or more observed objects identified by a record in the identified nodes, thereby determining which of the one or more observed objects satisfy the query. | 8. A method for analyzing ballistic trajectories comprising: determining, using a preprocessor, invariants for known ballistic objects; defining, using the preprocessor, a reference graph having nodes corresponding to the invariants for the known ballistic objects; defining, using the preprocessor, a query graph having nodes connected to nodes of the reference graph corresponding to anticipated invariant queries to be made using the query graph; inputting into the reference graph, using a runtime processor, one or more sets of invariants corresponding to trajectories of one or more observed objects, each of the one or more sets of invariants traversing through the nodes of the reference graph corresponding to the each of the one or more sets of invariants and leaving a record in the nodes traversed; selecting, using an interface, a query for the query graph corresponding to one or more range of invariants, said query generating a query result identifying the nodes of the reference graph that satisfy the query; and identifying, using the runtime processor, each of the one or more observed objects identified by a record in the identified nodes, thereby determining which of the one or more observed objects satisfy the query. 14. The method of claim 8 , wherein selecting the query for the query graph further comprises making available queries for selection corresponding to connections between the nodes of the query graph and the nodes of the reference graph. | 0.691099 |
8,655,875 | 14 | 17 | 14. The system of claim 11 , comprising a target object disposition logic. | 14. The system of claim 11 , comprising a target object disposition logic. 17. The system of claim 14 , comprising a mapping rule object identifier for storing an identifier of one or more mapping rule objects to invoke upon completing the processing of one or more of, the source logic, the destination logic, the rule logic, the source filter rule logic, the translation rule form logic, the post translation execution logic, and the target object disposition logic. | 0.5 |
9,069,828 | 5 | 6 | 5. The method of claim 1 wherein said one or more computing devices, further processing the association matrix to perform: selecting a first set of ontological subject, having at least one member; selecting a number of first associated sets of ontological subject, each of said first associated set having at least one member, wherein each of said first associated sets is corresponded to a member of the first set, wherein each member of each set of said first associated sets having association value greater than a predefined threshold with at least one member of the first set; selecting an ith set of ontological subject, having at least one member, from sets of the (i−1)th associated sets, wherein i is an integer number greater than one; selecting a number of ith associated sets of ontological subjects, wherein each set of said ith associated sets is corresponded to a member of said ith set of ontological subjects and each of it's member having association value greater than a predefined threshold with at least one member of said ith set of ontological subjects; and making one or more data structures with data thereon usable in determining the selected associated set of ontological subjects for each member of jth set of ontological subjects, wherein j is an integer number greater than or equal to one. | 5. The method of claim 1 wherein said one or more computing devices, further processing the association matrix to perform: selecting a first set of ontological subject, having at least one member; selecting a number of first associated sets of ontological subject, each of said first associated set having at least one member, wherein each of said first associated sets is corresponded to a member of the first set, wherein each member of each set of said first associated sets having association value greater than a predefined threshold with at least one member of the first set; selecting an ith set of ontological subject, having at least one member, from sets of the (i−1)th associated sets, wherein i is an integer number greater than one; selecting a number of ith associated sets of ontological subjects, wherein each set of said ith associated sets is corresponded to a member of said ith set of ontological subjects and each of it's member having association value greater than a predefined threshold with at least one member of said ith set of ontological subjects; and making one or more data structures with data thereon usable in determining the selected associated set of ontological subjects for each member of jth set of ontological subjects, wherein j is an integer number greater than or equal to one. 6. The method of claim 5 , wherein said one or more computing devices, further processing the association matrix to perform: index the members of said first set of ontological subjects and the members of said first associated sets and/or one or more of said ith set of ontological subjects and one or member of said ith associated set in a multilayer ontological subject index, or place in one or more corresponding data structures, wherein the i is selected from one or more integers numbers of greater than one. | 0.5 |
8,286,136 | 7 | 9 | 7. A computer program product stored on a non-transitory computer readable storage medium for testing international software that conducts processing with reference to an externalized resource file, the computer program product being configured to be able, when executed on a computer, to cause the computer to execute the steps of: reading data from an externalized resource file written in a first language; generating a test resource file written in a second language from the externalized resource file by converting characters of the first language contained in the data into characters of the second language with reference to a conversion table in which the characters of the first language are associated one-for-one with the characters of the second language; creating character codes for representing the characters of the first language and the characters of the second language; creating mapping between the first language and the second language such that the number of character codes for the second language is greater than the number of character codes for the first language; extracting a key attached to a character string from an item read from the externalized resource file, and to assign the extracted key to a variable key; writing the variable key to the test resource file; assigning variables to each of the characters in the character string and to compare each of the characters in the character string with a string boundary character; executing the internationalization software; and testing output information including character codes outputted from the internationalization software and displayed on a display screen with one of a plurality of fonts prepared for each test category of the internationalization software; classifying the character codes included in the output information to one of three groups: a first group composed of a plurality of character codes corresponding to a first plurality of characters for the first language, which are not supposed to be included in the output information; a second group composed of a second plurality of character codes corresponding to the characters for the second language included in the conversion table, which are supposed to be included in the output information; and a third group composed of a plurality of character codes not corresponding to any of the first plurality of characters for the first language and the second plurality of characters for the second language included in the conversion table, and which are not supposed to be included in the output information, confirming character strings included in the externalized resource file, wherein the plurality of fonts except for fonts used for the character string confirmation relate a first same character shape or a plurality of different character shapes to the character codes included in any one group of the first to the third groups, which are test objects in corresponding test items, respectively, and, relate a second same character shape, which is different from the first same character shape to character codes included in any remaining two groups of the first to the third groups, respectively, and a character code that is a test object and the other character codes are distinguishable on the display of the output information using the fonts. | 7. A computer program product stored on a non-transitory computer readable storage medium for testing international software that conducts processing with reference to an externalized resource file, the computer program product being configured to be able, when executed on a computer, to cause the computer to execute the steps of: reading data from an externalized resource file written in a first language; generating a test resource file written in a second language from the externalized resource file by converting characters of the first language contained in the data into characters of the second language with reference to a conversion table in which the characters of the first language are associated one-for-one with the characters of the second language; creating character codes for representing the characters of the first language and the characters of the second language; creating mapping between the first language and the second language such that the number of character codes for the second language is greater than the number of character codes for the first language; extracting a key attached to a character string from an item read from the externalized resource file, and to assign the extracted key to a variable key; writing the variable key to the test resource file; assigning variables to each of the characters in the character string and to compare each of the characters in the character string with a string boundary character; executing the internationalization software; and testing output information including character codes outputted from the internationalization software and displayed on a display screen with one of a plurality of fonts prepared for each test category of the internationalization software; classifying the character codes included in the output information to one of three groups: a first group composed of a plurality of character codes corresponding to a first plurality of characters for the first language, which are not supposed to be included in the output information; a second group composed of a second plurality of character codes corresponding to the characters for the second language included in the conversion table, which are supposed to be included in the output information; and a third group composed of a plurality of character codes not corresponding to any of the first plurality of characters for the first language and the second plurality of characters for the second language included in the conversion table, and which are not supposed to be included in the output information, confirming character strings included in the externalized resource file, wherein the plurality of fonts except for fonts used for the character string confirmation relate a first same character shape or a plurality of different character shapes to the character codes included in any one group of the first to the third groups, which are test objects in corresponding test items, respectively, and, relate a second same character shape, which is different from the first same character shape to character codes included in any remaining two groups of the first to the third groups, respectively, and a character code that is a test object and the other character codes are distinguishable on the display of the output information using the fonts. 9. The computer program product according to claim 7 , wherein the test categories include detection of the character strings that are hard-coded character strings, and the fonts used for the detection of the hard-coded character strings regard the first group as a group of the test object, and relate the plurality of character codes in the first group to the character shapes of the characters for the first language corresponding to said character codes without modification, respectively. | 0.566784 |
9,348,851 | 2 | 3 | 2. The computer system of claim 1 , wherein the one or more data quality criterion are configured to identify the potential data quality problems including at least one of: possible duplicate objects, missing properties, multi-valued properties, unparsed properties, disallowed enumerations, numeric range violations, and date range violations. | 2. The computer system of claim 1 , wherein the one or more data quality criterion are configured to identify the potential data quality problems including at least one of: possible duplicate objects, missing properties, multi-valued properties, unparsed properties, disallowed enumerations, numeric range violations, and date range violations. 3. The computer system of claim 2 , wherein the potential data quality problem is missing properties; and said one or more data quality criterion identify objects that are missing at least a property value that is predetermined to be necessary. | 0.576389 |
8,805,843 | 7 | 11 | 7. A method executed by a computer processor, comprising: extracting a set of documents related to a specified topic from a data warehouse; automatically generating a first taxonomy through a feature space derived from the set of documents, wherein the feature space includes at least one of unstructured data; structured data, and annotations derived from text of the set of documents, and the first taxonomy provides a first partition of the set of documents according to the first taxonomy; using domain-specific knowledge to re-partition the set of documents to provide a second partition of the set of documents; using a first taxonomy to categorize the set of documents into a first set of categories; creating a second set of categories of the set of documents, wherein the second set of categories are independent of the second partition based on at least one of unstructured data, structured data, and annotations derived from text in the set of documents; constructing a contingency table having the first set of categories along a first axis and the second set of categories along a second axis, wherein the contingency table includes cells having respective actual values and for which respective expected values are computed, and includes a cell having trending information; displaying the first set of categories along a first axis and the second set of categories along a second axis on a display device; comparing the expected value of a cell against the actual value of a cell to identify a category of interest; computing a degree of significance for the actual value of the cell; identifying a relationship between at least two different categories using the contingency table; using the contingency table and trending information to identify a recent category with respect to some pre-determined date; creating a second taxonomy different from and independent of the first taxonomy for the set of documents according to the second partition so that the different second taxonomy incorporates the domain-specific knowledge; comparing each of a plurality of categories in the first partition of the set of documents with each of a plurality of categories in the second partition of the set of documents; and combining the first taxonomy with the second taxonomy by merging classes in the first taxonomy with classes in the second taxonomy. | 7. A method executed by a computer processor, comprising: extracting a set of documents related to a specified topic from a data warehouse; automatically generating a first taxonomy through a feature space derived from the set of documents, wherein the feature space includes at least one of unstructured data; structured data, and annotations derived from text of the set of documents, and the first taxonomy provides a first partition of the set of documents according to the first taxonomy; using domain-specific knowledge to re-partition the set of documents to provide a second partition of the set of documents; using a first taxonomy to categorize the set of documents into a first set of categories; creating a second set of categories of the set of documents, wherein the second set of categories are independent of the second partition based on at least one of unstructured data, structured data, and annotations derived from text in the set of documents; constructing a contingency table having the first set of categories along a first axis and the second set of categories along a second axis, wherein the contingency table includes cells having respective actual values and for which respective expected values are computed, and includes a cell having trending information; displaying the first set of categories along a first axis and the second set of categories along a second axis on a display device; comparing the expected value of a cell against the actual value of a cell to identify a category of interest; computing a degree of significance for the actual value of the cell; identifying a relationship between at least two different categories using the contingency table; using the contingency table and trending information to identify a recent category with respect to some pre-determined date; creating a second taxonomy different from and independent of the first taxonomy for the set of documents according to the second partition so that the different second taxonomy incorporates the domain-specific knowledge; comparing each of a plurality of categories in the first partition of the set of documents with each of a plurality of categories in the second partition of the set of documents; and combining the first taxonomy with the second taxonomy by merging classes in the first taxonomy with classes in the second taxonomy. 11. The method of claim 7 , including: classifying the set of documents into classes independent of the second partition; generating a contingency table for comparing the categories of the different second taxonomy with the classes of the set of documents; and identifying a set of mutually different recent categories using the contingency table. | 0.686823 |
8,070,775 | 25 | 29 | 25. A spine implant comprising: an anchor adapted to be inserted into the bone of a patient; an anchor head having a deflection guide cavity, the deflection guide cavity having a deflection guide cavity wall, a central axis, and a deflection guide cavity opening; a deflection rod having a distal end secured within said deflection guide cavity and a proximal end extending out of the deflection guide cavity opening; wherein the spine implant is configured such that said deflection rod is resiliently held in alignment with the central axis of the deflection guide cavity; wherein, with the deflection rod aligned with a central axis of the deflection guide cavity, there exists a gap between the deflection guide cavity wall and the deflection rod at the deflection guide cavity opening which gap diminishes in size towards the distal end of the deflection rod; and wherein the proximal end of the deflection rod can resiliently deflect in response to a load applied to the proximal end of the deflection rod and wherein contact between the deflection rod and the deflection guide cavity wall limits deflection of the deflection rod. | 25. A spine implant comprising: an anchor adapted to be inserted into the bone of a patient; an anchor head having a deflection guide cavity, the deflection guide cavity having a deflection guide cavity wall, a central axis, and a deflection guide cavity opening; a deflection rod having a distal end secured within said deflection guide cavity and a proximal end extending out of the deflection guide cavity opening; wherein the spine implant is configured such that said deflection rod is resiliently held in alignment with the central axis of the deflection guide cavity; wherein, with the deflection rod aligned with a central axis of the deflection guide cavity, there exists a gap between the deflection guide cavity wall and the deflection rod at the deflection guide cavity opening which gap diminishes in size towards the distal end of the deflection rod; and wherein the proximal end of the deflection rod can resiliently deflect in response to a load applied to the proximal end of the deflection rod and wherein contact between the deflection rod and the deflection guide cavity wall limits deflection of the deflection rod. 29. The implant of claim 25 , wherein the central axis of the deflection guide cavity is in-line with a longitudinal axis of the anchor. | 0.756272 |
7,639,257 | 56 | 61 | 56. A computer readable medium encoded with a computer program for constructing a text document, the computer program comprising instructions that when executed by a programmable processor of a computer cause the programmable processor to perform operations comprising: receiving user input at the computer selecting a character for insertion into a text document; identifying in a memory of the computer a glyphlet representing the selected character, the glyphlet being a data structure including both a set of one or more character attributes defining semantic information of the selected character and a set of one or more glyph attributes defining appearance information for a glyph representative of the selected character, the glyph attributes including all the information necessary to render a glyph image of the glyph; inserting the character into the text document by inserting a reference to the identified glyphlet into a text document, where the reference can be used to access the sets of character and glyph attributes from the glyphlet for the character selected by the user input; and displaying the character in the text document, the displayed character being rendered from the glyph attributes. | 56. A computer readable medium encoded with a computer program for constructing a text document, the computer program comprising instructions that when executed by a programmable processor of a computer cause the programmable processor to perform operations comprising: receiving user input at the computer selecting a character for insertion into a text document; identifying in a memory of the computer a glyphlet representing the selected character, the glyphlet being a data structure including both a set of one or more character attributes defining semantic information of the selected character and a set of one or more glyph attributes defining appearance information for a glyph representative of the selected character, the glyph attributes including all the information necessary to render a glyph image of the glyph; inserting the character into the text document by inserting a reference to the identified glyphlet into a text document, where the reference can be used to access the sets of character and glyph attributes from the glyphlet for the character selected by the user input; and displaying the character in the text document, the displayed character being rendered from the glyph attributes. 61. The computer readable medium encoded with the computer program of claim 56 , wherein: the reference to the identified glyphlet includes one or more out-of-band values not defined in an encoding standard. | 0.660656 |
8,516,458 | 19 | 20 | 19. A code-portion-handling tool as claimed in claim 17 , wherein said at least one processor is operable to verify such manipulation against said implementation, and to disallow manipulation that is incompliant with at least one of the second data structure and the implementation rules. | 19. A code-portion-handling tool as claimed in claim 17 , wherein said at least one processor is operable to verify such manipulation against said implementation, and to disallow manipulation that is incompliant with at least one of the second data structure and the implementation rules. 20. A code-portion-handling tool as claimed in claim 19 , wherein said at least one processor is operable to allow manipulation that is compliant with the second data structure and the implementation rules. | 0.5 |
8,924,414 | 1 | 10 | 1. A computer-implemented method for facilitating document retrieval in an electronic document management system, the method comprising the steps of: identifying, by at least one processor, one or more user-specific naming patterns in metadata created by a first user in connection with a plurality of documents that the first user has a first entitlement to access; recording, by at least one processor and in a storage medium, said identified one or more user-specific naming patterns in at least one of a naming patterns file (NPF), database, and lookup table with entries corresponding to said first user; and modifying, by at least one processor and based on the recorded user-specific naming patterns, at least a portion of the metadata created by the first user to improve searchability by other users, the modified metadata being available in a document query for one or more of the plurality of documents by a second user, the second user having a second entitlement that is equivalent or similar to the first entitlement such that the second user is entitled to access at least some of the plurality of documents. | 1. A computer-implemented method for facilitating document retrieval in an electronic document management system, the method comprising the steps of: identifying, by at least one processor, one or more user-specific naming patterns in metadata created by a first user in connection with a plurality of documents that the first user has a first entitlement to access; recording, by at least one processor and in a storage medium, said identified one or more user-specific naming patterns in at least one of a naming patterns file (NPF), database, and lookup table with entries corresponding to said first user; and modifying, by at least one processor and based on the recorded user-specific naming patterns, at least a portion of the metadata created by the first user to improve searchability by other users, the modified metadata being available in a document query for one or more of the plurality of documents by a second user, the second user having a second entitlement that is equivalent or similar to the first entitlement such that the second user is entitled to access at least some of the plurality of documents. 10. The method according to claim 1 , further comprising: retrieving at least one document based on the document query from the second user and further based at least in part on the modified at least a portion of the metadata. | 0.667647 |
8,713,485 | 6 | 8 | 6. A computer implemented method for categorizing violations of a design rule, comprising: receiving, from a design rule checker, two or more of violations of a design rule within an integrated circuit (IC) layout, each violation having an error marker and the IC layout having two or more cells; determining dynamically, by using a computer, a local region for each of the violations wherein the local region is in a first cell, the violation is associated with a particular cell adjacent to the first cell, and parameters associated with the local region include an identification parameter of the adjacent cell, wherein the adjacent cell includes a violating shape; and for each of the violations: determining one or more parameters associated with the local region, wherein the parameters include the identification parameter associated with a cell associated with the design rule violation, the identification parameter including at least that the cell associated with the design rule violation is an instance of a particular parent cell, wherein the parameters associated with the local region includes a dimension of the error marker and includes a distance from the error marker to the violating shape, and classifying the violation as being in a particular error category when the associated parameters are substantially similar to corresponding parameters for the error category. | 6. A computer implemented method for categorizing violations of a design rule, comprising: receiving, from a design rule checker, two or more of violations of a design rule within an integrated circuit (IC) layout, each violation having an error marker and the IC layout having two or more cells; determining dynamically, by using a computer, a local region for each of the violations wherein the local region is in a first cell, the violation is associated with a particular cell adjacent to the first cell, and parameters associated with the local region include an identification parameter of the adjacent cell, wherein the adjacent cell includes a violating shape; and for each of the violations: determining one or more parameters associated with the local region, wherein the parameters include the identification parameter associated with a cell associated with the design rule violation, the identification parameter including at least that the cell associated with the design rule violation is an instance of a particular parent cell, wherein the parameters associated with the local region includes a dimension of the error marker and includes a distance from the error marker to the violating shape, and classifying the violation as being in a particular error category when the associated parameters are substantially similar to corresponding parameters for the error category. 8. The method of claim 6 , wherein the parameters associated with the local region includes a geometric parameter. | 0.765432 |
8,155,943 | 1 | 2 | 1. A computer system for converting a computer aided design drawing file of an electrical power system comprising a plurality of components into one or more component objects for power analytic analysis and simulation, the computer system comprising: at least one processor; a memory; at least one executable software module configured to, when executed by the at least one processor, import the computer aided design drawing file to the memory, parse the computer aided design drawing file into a plurality of component objects corresponding to the plurality of components of the electrical power system, each of the plurality of component objects comprising a component symbol, assign a component classification to the component symbol of each of the plurality of component objects, wherein the component classification comprises one or more attributes which define at least one of an electrical characteristic, connectivity characteristic, and interdependency characteristic of the associated component object, receive a modification of one or more attributes of a component classification, and update the computer aided design drawing file based on the modification; a virtual system model of the electrical power system, wherein the virtual system model comprises virtual component data corresponding to the plurality of components of the electrical power system; and an analytics engine configured to monitor real-time data from one or more sensors interfaced with the electrical power system, monitor predicted operational data generated using the virtual system model, synchronize the virtual system model in real-time based on a difference between the real-time data and the predicted operational data, and update the virtual system model based on the updated computer aided design drawing file. | 1. A computer system for converting a computer aided design drawing file of an electrical power system comprising a plurality of components into one or more component objects for power analytic analysis and simulation, the computer system comprising: at least one processor; a memory; at least one executable software module configured to, when executed by the at least one processor, import the computer aided design drawing file to the memory, parse the computer aided design drawing file into a plurality of component objects corresponding to the plurality of components of the electrical power system, each of the plurality of component objects comprising a component symbol, assign a component classification to the component symbol of each of the plurality of component objects, wherein the component classification comprises one or more attributes which define at least one of an electrical characteristic, connectivity characteristic, and interdependency characteristic of the associated component object, receive a modification of one or more attributes of a component classification, and update the computer aided design drawing file based on the modification; a virtual system model of the electrical power system, wherein the virtual system model comprises virtual component data corresponding to the plurality of components of the electrical power system; and an analytics engine configured to monitor real-time data from one or more sensors interfaced with the electrical power system, monitor predicted operational data generated using the virtual system model, synchronize the virtual system model in real-time based on a difference between the real-time data and the predicted operational data, and update the virtual system model based on the updated computer aided design drawing file. 2. The computer system for converting a computer aided design drawing file of an electrical power system into one or more component objects for power analytic analysis and simulation, as recited in claim 1 , wherein the component classification represents an equipment type. | 0.664216 |
9,286,405 | 7 | 9 | 7. A system, comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining a token sequence for a resource, wherein each token in the token sequence comprises one or more characters; selecting a particular token from the token sequence, wherein the particular token comprises two or more characters that comprise at least one numeric portion having at least one contiguous numeric character, and at least one non-numeric portion having at least one non-numeric character; generating a new token for each of the at least one numeric portion that is not separately a token in the token sequence, the new token comprising the respective at least one numeric portion of the particular token without the at least one non-numeric portion of the particular token; and storing, in a search engine index, (i) data indicating the particular token and data indicating the new token as index terms for the resource, and (ii) data indicating that the particular token and the at least one numeric portion correspond to the same token in the resource. | 7. A system, comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: obtaining a token sequence for a resource, wherein each token in the token sequence comprises one or more characters; selecting a particular token from the token sequence, wherein the particular token comprises two or more characters that comprise at least one numeric portion having at least one contiguous numeric character, and at least one non-numeric portion having at least one non-numeric character; generating a new token for each of the at least one numeric portion that is not separately a token in the token sequence, the new token comprising the respective at least one numeric portion of the particular token without the at least one non-numeric portion of the particular token; and storing, in a search engine index, (i) data indicating the particular token and data indicating the new token as index terms for the resource, and (ii) data indicating that the particular token and the at least one numeric portion correspond to the same token in the resource. 9. The system of claim 7 , wherein the operations further comprise: determining a relative position of each of the at least one numeric portion within the particular token; and storing data indicating the relative position of each of the at least one numeric portion. | 0.680622 |
8,103,510 | 1 | 4 | 1. A device control device comprising: speech recognition means which acquires speech data representing a speech and specifies words candidates included in the speech by performing speech recognition on the speech data and calculates a likelihood of each of the specified words candidates; specifying means which specifies words included in the speech based on the likelihoods calculated by the speech recognition means and specifies a content of the speech uttered by an utterer based on the words specified; a database which stores preceding controls, subsequent controls, and weighting factors, each of which is associated with one another; and process execution means which specifies content of a subsequent control to be performed on an external device to be a control target based on a currently executed control, a weighting factor stored in association with the currently executed control and the content of the uttered speech specified by the specifying means, and performs the subsequent control, wherein the process execution means obtains the weighting factor by calculating a product of transition constants defined on routes from the currently executed control to the subsequent control associated with the currently executed control, writes the obtained weighting factor into the database, and, among the subsequent controls stored in the database associated with the currently executed control, identifies a control in which a product is a largest product of the weighting factor and the calculated likelihood. | 1. A device control device comprising: speech recognition means which acquires speech data representing a speech and specifies words candidates included in the speech by performing speech recognition on the speech data and calculates a likelihood of each of the specified words candidates; specifying means which specifies words included in the speech based on the likelihoods calculated by the speech recognition means and specifies a content of the speech uttered by an utterer based on the words specified; a database which stores preceding controls, subsequent controls, and weighting factors, each of which is associated with one another; and process execution means which specifies content of a subsequent control to be performed on an external device to be a control target based on a currently executed control, a weighting factor stored in association with the currently executed control and the content of the uttered speech specified by the specifying means, and performs the subsequent control, wherein the process execution means obtains the weighting factor by calculating a product of transition constants defined on routes from the currently executed control to the subsequent control associated with the currently executed control, writes the obtained weighting factor into the database, and, among the subsequent controls stored in the database associated with the currently executed control, identifies a control in which a product is a largest product of the weighting factor and the calculated likelihood. 4. The device control device according to claim 1 , wherein the specifying means holds information which associates words with one or more categories, and specifies a content of the speech uttered by the utterer based on a category in which the words specified by the speech recognition means are classified. | 0.686992 |
7,742,106 | 20 | 21 | 20. The method of claim 10 , further comprising: extracting language information from a tuned transport stream by parsing additional information from the tuned transport stream; storing the extracted language information in a memory; and outputting the stored information to enable the user selection. | 20. The method of claim 10 , further comprising: extracting language information from a tuned transport stream by parsing additional information from the tuned transport stream; storing the extracted language information in a memory; and outputting the stored information to enable the user selection. 21. The method of claim 20 , wherein said outputting comprises: simultaneously outputting the stored language information as an audio signal and as an image displayed on a screen. | 0.5 |
4,031,374 | 5 | 9 | 5. The combination defined in claim 1, in which the memory has at least one block of multi-bit data words stored therein and which contains a particular number of data words at known memory locations, and in which the memory further has a multi-bit error correction word stored therein, in which said further logic circuit means forms a computed error correction word on all the words in the block including the altered data word and the error correction word, and in which said further logic circuit introduces the computed error correction word to the second register means for introduction into the memory of the reconstituted word to replace the altered word in the block at the memory location of the altered word. | 5. The combination defined in claim 1, in which the memory has at least one block of multi-bit data words stored therein and which contains a particular number of data words at known memory locations, and in which the memory further has a multi-bit error correction word stored therein, in which said further logic circuit means forms a computed error correction word on all the words in the block including the altered data word and the error correction word, and in which said further logic circuit introduces the computed error correction word to the second register means for introduction into the memory of the reconstituted word to replace the altered word in the block at the memory location of the altered word. 9. The combination defined in claim 5, and which includes third register means coupled to the accessing means for storing each data word being accessed by the accessing means; fourth register means; and logic circuitry coupled to the accessing means to the fourth register means for up-dating the error correction word when any data word is replaced in the block by a different data word, and for inserting the up-dated error correction word into the fourth register means for introduction into the memory at the memory location of the original error correction word to replace the original error correction word. | 0.5 |
9,916,296 | 1 | 7 | 1. A computer-implemented method, comprising: generating one or more alternate versions of one or more document annotators selected from a set of multiple document annotators, wherein each of the one or more alternate versions comprises a version of one of the selected document annotators that contains (i) one or more generalizations of one or more entity patterns derived from the selected document annotator and (ii) one or more generalizations of one or more relationship patterns derived from the selected document annotator, wherein said generating the alternate versions comprises implementing entity pattern generalization and relationship pattern generalization across the set of multiple document annotators, wherein said entity pattern generalization comprises replacing at least one element in an entity pattern of the given document annotator with an expanded version of the element to increase entity matches of the given document annotator to a given taxonomy, and said relationship pattern generalization comprises replacing at least one element in a relationship pattern of the given document annotator with an expanded version of the element to increase relationship matches of the given document annotator to a given taxonomy, and wherein said generating is carried out by an enhanced annotator component executing on at least one computing device and communicatively linked to a database storing the set of multiple document annotators; executing, on one or more document data sets, (i) one or more document annotators from the set of multiple document annotators and (ii) the one or more alternate versions to generate log information for each document annotator in the set and each alternate version of the one or more alternate versions, wherein said executing is carried out by the enhanced annotator component executing on the at least one computing device and communicatively linked to a source for the one or more document data sets; and outputting an instruction to modify, based on the generated log information for each document annotator in the set and each alternate version, at least one document annotator from the set with at least one alternate version from the one or more alternate versions, wherein said outputting is carried out by a recommendation engine executing on the at least one computing device and communicatively linked to the enhanced annotator component. | 1. A computer-implemented method, comprising: generating one or more alternate versions of one or more document annotators selected from a set of multiple document annotators, wherein each of the one or more alternate versions comprises a version of one of the selected document annotators that contains (i) one or more generalizations of one or more entity patterns derived from the selected document annotator and (ii) one or more generalizations of one or more relationship patterns derived from the selected document annotator, wherein said generating the alternate versions comprises implementing entity pattern generalization and relationship pattern generalization across the set of multiple document annotators, wherein said entity pattern generalization comprises replacing at least one element in an entity pattern of the given document annotator with an expanded version of the element to increase entity matches of the given document annotator to a given taxonomy, and said relationship pattern generalization comprises replacing at least one element in a relationship pattern of the given document annotator with an expanded version of the element to increase relationship matches of the given document annotator to a given taxonomy, and wherein said generating is carried out by an enhanced annotator component executing on at least one computing device and communicatively linked to a database storing the set of multiple document annotators; executing, on one or more document data sets, (i) one or more document annotators from the set of multiple document annotators and (ii) the one or more alternate versions to generate log information for each document annotator in the set and each alternate version of the one or more alternate versions, wherein said executing is carried out by the enhanced annotator component executing on the at least one computing device and communicatively linked to a source for the one or more document data sets; and outputting an instruction to modify, based on the generated log information for each document annotator in the set and each alternate version, at least one document annotator from the set with at least one alternate version from the one or more alternate versions, wherein said outputting is carried out by a recommendation engine executing on the at least one computing device and communicatively linked to the enhanced annotator component. 7. The method of claim 1 , wherein said executing comprises executing (i) one or more document annotators, from the set of multiple document annotators, that identify one or more entities, and (ii) one or more alternate versions of one or more document annotators, from the set of multiple document annotators, that identify one or more relationships between two or more entities. | 0.5 |
9,361,879 | 1 | 17 | 1. A computer implemented method for processing media comprising: using a computer to perform the steps of: accepting the media; accepting language data; accepting a query; processing the query using the language data to identify one or more language patterns each having a length larger than a length of a language pattern of the query, each language pattern including a first portion that is acoustically similar to the language pattern of the query and a second portion that is not acoustically similar to the language pattern of the query; locating a putative instance of the query in the media, the putative instance being associated with a first time interval in the media, the locating including determining a match score for the located putative instance of the query to the media in the first time interval; selecting a second time interval of the media according to the first time interval, the second time interval being larger than and including the first time interval; determining a degree of acoustic similarity between the media in the second time interval and one or more of the identified language patterns; determining a score for the putative instance according to the match score for the located putative instance of the query and to at least one score associated with the determined degree of acoustic similarity between the media in the second time interval and one or more of the identified language patterns; and providing data characterizing the putative instance of the query according to the determined degree of acoustic similarity, including identifying the putative instance of the query as a potential falsely identified instance of the query based on the determined score for the putative instance. | 1. A computer implemented method for processing media comprising: using a computer to perform the steps of: accepting the media; accepting language data; accepting a query; processing the query using the language data to identify one or more language patterns each having a length larger than a length of a language pattern of the query, each language pattern including a first portion that is acoustically similar to the language pattern of the query and a second portion that is not acoustically similar to the language pattern of the query; locating a putative instance of the query in the media, the putative instance being associated with a first time interval in the media, the locating including determining a match score for the located putative instance of the query to the media in the first time interval; selecting a second time interval of the media according to the first time interval, the second time interval being larger than and including the first time interval; determining a degree of acoustic similarity between the media in the second time interval and one or more of the identified language patterns; determining a score for the putative instance according to the match score for the located putative instance of the query and to at least one score associated with the determined degree of acoustic similarity between the media in the second time interval and one or more of the identified language patterns; and providing data characterizing the putative instance of the query according to the determined degree of acoustic similarity, including identifying the putative instance of the query as a potential falsely identified instance of the query based on the determined score for the putative instance. 17. The method of claim 1 , wherein processing the query using the language data to identify one or more language patterns that each include the first portion of the pattern that is acoustically similar to the query includes identifying at least one language pattern such that the query is similar to a portion less than the entire language pattern. | 0.559343 |
9,311,395 | 1 | 9 | 1. A computer-implemented method for manipulating electronic multimedia content, the method comprising: generating, using a processor, a speech model, a non-speech model, at least one speaker model of an individual speaker, and a non-speaker speech model; receiving electronic media content over a network; extracting an audio track from the electronic media content; detecting speech segments within the extracted audio track based on the speech model and the non-speech model, the speech segments containing speech from at least one of a plurality of speakers; detecting a speaker segment within the detected speech segments based on the speaker model and the non-speaker speech model, the speaker segment containing speech from the individual speaker; calculating a first probability of the detected speaker segment involving the individual speaker based on the at least one speaker speech model and the non-speaker speech model; determining a ranking or filtration of the electronic media content relative to other electronic media content based on the first probability of the detected speaker segment; detecting a face within a part of the electronic media content corresponding to the detected speaker segment and calculating a second probability of the detected face being a face of the individual speaker; and adjusting the ranking or filtration of the electronic media content based on the second probability. | 1. A computer-implemented method for manipulating electronic multimedia content, the method comprising: generating, using a processor, a speech model, a non-speech model, at least one speaker model of an individual speaker, and a non-speaker speech model; receiving electronic media content over a network; extracting an audio track from the electronic media content; detecting speech segments within the extracted audio track based on the speech model and the non-speech model, the speech segments containing speech from at least one of a plurality of speakers; detecting a speaker segment within the detected speech segments based on the speaker model and the non-speaker speech model, the speaker segment containing speech from the individual speaker; calculating a first probability of the detected speaker segment involving the individual speaker based on the at least one speaker speech model and the non-speaker speech model; determining a ranking or filtration of the electronic media content relative to other electronic media content based on the first probability of the detected speaker segment; detecting a face within a part of the electronic media content corresponding to the detected speaker segment and calculating a second probability of the detected face being a face of the individual speaker; and adjusting the ranking or filtration of the electronic media content based on the second probability. 9. The computer-implemented method of claim 1 , further comprising: applying speaker segments and their probabilities to detect individual speakers represented in electronic media content. | 0.732955 |
9,507,947 | 6 | 9 | 6. A method as in claim 5 wherein performing the evaluation operations further includes: based on results of the matching operations, providing each variant with a numerical risk score indicating a likelihood that the variant includes sensitive data. | 6. A method as in claim 5 wherein performing the evaluation operations further includes: based on results of the matching operations, providing each variant with a numerical risk score indicating a likelihood that the variant includes sensitive data. 9. A method as in claim 6 wherein the content source is a file; and wherein performing the control operation further includes: releasing the file to the destination when all numerical risk scores provided to all of the variants do not exceed the predefined threshold score, and providing, in place of the file, a redacted file to the destination when at least one numerical risk score provided to a variant exceeds the predefined threshold score. | 0.5 |
10,037,313 | 13 | 14 | 13. A system for smoothed captioning of non-speech sounds in an audio stream, comprising: a content system coupled to a network and configured to: access an audio stream; input portions of the audio stream into one or more non-speech classifiers for classification; generating, by the non-speech classifiers, for one or more of the portions of the audio stream, a set of raw scores representing likelihoods that the respective portion of the audio stream includes an occurrence of a particular class of non-speech sounds associated with each of the non-speech classifiers; generate a set of binary scores for each of the sets of raw scores, each set of binary scores generated based on a smoothing of a respective set of raw scores, the smoothing of the respective set of raw scores determined based on the raw scores of the same class of non-speech sounds from neighboring portions of the audio stream in time, wherein for a portion of the portions, a first binary value indicates that a first class of the non-speech sounds occurs in the portion, and a second binary value indicates that the first class of the non-speech sounds does not occur in the portion, and wherein to generate the set of binary scores for each of the sets of raw scores comprises to: determine, using transition probabilities and a sequence of emission probabilities, a sequence of most likely binary scores for each set of raw scores, the sequence of binary scores corresponding to a sequence of on states and off states, the sequence of emission probabilities of the on states corresponding to the raw scores of the set of raw scores and the sequence of emission probabilities of the off states corresponding to a function of the raw scores, and the transition probabilities predefined such that a probability of a transition between different states is lower than a probability of transitioning between the same states; and apply a set of non-speech captions to portions of the audio stream in time, each of the sets of non-speech captions based on a different one of the set binary scores of the corresponding portion of the audio stream; and a client device coupled to the network and configured to: receive content from a content server; receive speech captions and non-speech captions; and present the content with the speech captions and non-speech captions to a user. | 13. A system for smoothed captioning of non-speech sounds in an audio stream, comprising: a content system coupled to a network and configured to: access an audio stream; input portions of the audio stream into one or more non-speech classifiers for classification; generating, by the non-speech classifiers, for one or more of the portions of the audio stream, a set of raw scores representing likelihoods that the respective portion of the audio stream includes an occurrence of a particular class of non-speech sounds associated with each of the non-speech classifiers; generate a set of binary scores for each of the sets of raw scores, each set of binary scores generated based on a smoothing of a respective set of raw scores, the smoothing of the respective set of raw scores determined based on the raw scores of the same class of non-speech sounds from neighboring portions of the audio stream in time, wherein for a portion of the portions, a first binary value indicates that a first class of the non-speech sounds occurs in the portion, and a second binary value indicates that the first class of the non-speech sounds does not occur in the portion, and wherein to generate the set of binary scores for each of the sets of raw scores comprises to: determine, using transition probabilities and a sequence of emission probabilities, a sequence of most likely binary scores for each set of raw scores, the sequence of binary scores corresponding to a sequence of on states and off states, the sequence of emission probabilities of the on states corresponding to the raw scores of the set of raw scores and the sequence of emission probabilities of the off states corresponding to a function of the raw scores, and the transition probabilities predefined such that a probability of a transition between different states is lower than a probability of transitioning between the same states; and apply a set of non-speech captions to portions of the audio stream in time, each of the sets of non-speech captions based on a different one of the set binary scores of the corresponding portion of the audio stream; and a client device coupled to the network and configured to: receive content from a content server; receive speech captions and non-speech captions; and present the content with the speech captions and non-speech captions to a user. 14. The system of claim 13 , wherein the content system is further configured to, for the input of the portions of the audio stream into one or more non-speech classifiers for classification: divide the audio stream into portions, each portion being of a particular duration and offset from a start of a previous portion by a particular interval; input each portion into each of the one or more non-speech classifiers, where each non-speech classifier generates the raw scores for a corresponding portion of the audio stream for a class of non-speech sound by: use a filter cascade model to filter an audio signal of each portion to generate an output with multiple frequency channels; generate values for features based on the output from the filter cascade model; and use a machine learning model to determine a raw score likelihood of the occurrence of the class of non-speech sound at the portion of the audio stream. | 0.5 |
9,922,050 | 15 | 20 | 15. A non-transitory computer-readable storage medium storing computer executable instructions that when executed by a processor perform operations comprising: receiving a search phrase; determining a plurality of color palettes based at least in part on the search phrase being associated with the plurality of color palettes, wherein each color palette of the plurality of color palettes comprise one or more colors; selecting a subset of color palettes from the plurality of color palettes, wherein selecting the subset of color palettes comprises: determining, from the plurality of color palettes, a greater number of color palettes comprising a first color and having a creation time or update time within a threshold period of time than a number of color palettes comprising the first color and having a creation time or update time outside of the threshold period; and determining, from the plurality of color palettes, each color palette of the subset of the plurality of color palettes comprising the first color; selecting a priority color palette from the subset of color palettes, wherein the priority color palette is selected from the subset of color palettes based at least in part on a creation time or update time of the priority color palette; identifying a first set of images corresponding to a first color of the priority color palette, wherein the identification of the first set of images is based at least in part on a first category associated with the first set of images; identifying a second set of images corresponding to a second color of the priority color palette, wherein the identification of the second set of images is based at least in part on a second category associated with the second set of images; and providing the first set of images and the second set of images for presentation. | 15. A non-transitory computer-readable storage medium storing computer executable instructions that when executed by a processor perform operations comprising: receiving a search phrase; determining a plurality of color palettes based at least in part on the search phrase being associated with the plurality of color palettes, wherein each color palette of the plurality of color palettes comprise one or more colors; selecting a subset of color palettes from the plurality of color palettes, wherein selecting the subset of color palettes comprises: determining, from the plurality of color palettes, a greater number of color palettes comprising a first color and having a creation time or update time within a threshold period of time than a number of color palettes comprising the first color and having a creation time or update time outside of the threshold period; and determining, from the plurality of color palettes, each color palette of the subset of the plurality of color palettes comprising the first color; selecting a priority color palette from the subset of color palettes, wherein the priority color palette is selected from the subset of color palettes based at least in part on a creation time or update time of the priority color palette; identifying a first set of images corresponding to a first color of the priority color palette, wherein the identification of the first set of images is based at least in part on a first category associated with the first set of images; identifying a second set of images corresponding to a second color of the priority color palette, wherein the identification of the second set of images is based at least in part on a second category associated with the second set of images; and providing the first set of images and the second set of images for presentation. 20. The non-transitory computer-readable storage medium of claim 15 , wherein the search phrase is based at least in part on user input. | 0.703057 |
4,616,327 | 1 | 2 | 1. An apparatus for producing a personalized drawing of a user within preprinted background material comprising: a means for recording a plurality of factors affecting the user's appearence; a means for selecting at least two predesigned visual features most fitting to the user from a plurality of predesigned visual features in accordance with the plurality of factors affecting the user's appearance; a means for automatically controlling a plotter to draw the at least two predesigned visual features most fitting to the user within the preprinted background material to produce a continuous and personalized drawing of the user. | 1. An apparatus for producing a personalized drawing of a user within preprinted background material comprising: a means for recording a plurality of factors affecting the user's appearence; a means for selecting at least two predesigned visual features most fitting to the user from a plurality of predesigned visual features in accordance with the plurality of factors affecting the user's appearance; a means for automatically controlling a plotter to draw the at least two predesigned visual features most fitting to the user within the preprinted background material to produce a continuous and personalized drawing of the user. 2. The apparatus in accordance with claim 1 in which the at least two visual features most fitting to the user comprise the user's nose, hair style, eye, chin and ear. | 0.858234 |
9,063,985 | 11 | 12 | 11. The method of claim 10 , further comprising: comparing the first information to the second information to identify the non-redundant portions of the first information that are not redundant. | 11. The method of claim 10 , further comprising: comparing the first information to the second information to identify the non-redundant portions of the first information that are not redundant. 12. The method of claim 11 , further comprising inserting the identified portions of the first information into the database. | 0.5 |
6,018,342 | 21 | 22 | 21. A computer system comprising: a computer processor; a memory, operatively coupled to the computer processor and including a history apparatus which in turn comprises: a user interface which converts signals generated by a user to user data which is stored in the memory and which has a user data description, the user data description comprising one or more instances of one or more selected elements of a collection of two or more elements; a history database, operatively coupled to the user interface, the history database comprising two or more categories, each of which is associated with a respective one of two or more elements of the collection; and a user data classifier, operatively coupled between the user interface and the history database, for storing the user data in the history database in a selected one of the categories which is associated with one of the selected elements; and a user data retriever, operatively coupled to the history database, for retrieving user data from the history database, the user data retriever comprising: a category selector, which is operatively coupled to the user interface and which specifies, in response to signals generated by a category selection gesture of the user, a selected one of the two or more categories; and a user data selector, which is operatively coupled to the user interface and which specifies, in response to signals generated by a user data selection gesture of the user, selected user data of the select category. | 21. A computer system comprising: a computer processor; a memory, operatively coupled to the computer processor and including a history apparatus which in turn comprises: a user interface which converts signals generated by a user to user data which is stored in the memory and which has a user data description, the user data description comprising one or more instances of one or more selected elements of a collection of two or more elements; a history database, operatively coupled to the user interface, the history database comprising two or more categories, each of which is associated with a respective one of two or more elements of the collection; and a user data classifier, operatively coupled between the user interface and the history database, for storing the user data in the history database in a selected one of the categories which is associated with one of the selected elements; and a user data retriever, operatively coupled to the history database, for retrieving user data from the history database, the user data retriever comprising: a category selector, which is operatively coupled to the user interface and which specifies, in response to signals generated by a category selection gesture of the user, a selected one of the two or more categories; and a user data selector, which is operatively coupled to the user interface and which specifies, in response to signals generated by a user data selection gesture of the user, selected user data of the select category. 22. The computer system of claim 21 wherein the elements are symbols of the user data. | 0.892231 |
9,306,965 | 1 | 3 | 1. A cybersecurity system for processing events to produce scores, alerts, and mitigation actions, the system comprising: a plurality of sensors, each of the plurality of sensors being configured to: receive sensor data from a network, process the sensor data to form events, and transmit the events; a distributed analytic platform, the distributed analytic platform configured to: receive the events from the plurality of sensors, process the events to form analytic workflows and distributed analytic platform messages, each of the distributed analytic platform messages associated with at least one of an alert, an update to a first analytic model, and cyber behavioral information, each of the analytic workflows: associated with one or more logical segments, and including at least one of the first analytic model, a second analytic model, a rule, a data transformation, and a data aggregation, and transmit the analytic workflows and distributed analytic platform messages; a plurality of scoring engines, each of the plurality of scoring engines being configured to: receive the analytic workflows from the distributed analytic platform, receive the events from at least one of the plurality of sensors, process the received events using the analytic workflows to produce scoring engine messages, and transmit the scoring engine messages; and a real time analytic engine, the real time analytic engine configured to: receive the analytic workflows from the distributed analytic platform, receive analytic workflow and event processing rules, receive the scoring engine messages from the plurality of scoring engines, receive the distributed analytic platform messages from the distributed analytic platform, and process the scoring engine messages and the distributed analytic platform messages using the analytic workflows from the distributed analytic platform and the analytic workflow and event processing rules to form a threat intelligence message, wherein the threat intelligence message comprises at least one of: a broadcast message, the real time analytic engine configured to transmit the broadcast message, a mitigation message, the real time analytic engine configured to transmit the mitigation message to a control plane engine for taking a mitigation action associated with a first logical segment of the one or more logical segments when the processing by the real time analytic engine indicates the mitigation action limits the impact of anomalous activity, and a model update message, the real time analytic engine configured to transmit the model update message for updating one or more analytic workflows when the processing by the real time analytic engine indicates the model update message improves at least one of a detection rate of the anomalous activity and a reduction in a false positive rate, each of the one or more logical segments associating: at least one of the first analytic model, the second analytic model, a third analytic model, a set of analytic models, and an analytic workflow, one or more sources of inputs about activity within the logical segment, and a set of actions for mitigating an impact of the anomalous activity occurring within the logical segment. | 1. A cybersecurity system for processing events to produce scores, alerts, and mitigation actions, the system comprising: a plurality of sensors, each of the plurality of sensors being configured to: receive sensor data from a network, process the sensor data to form events, and transmit the events; a distributed analytic platform, the distributed analytic platform configured to: receive the events from the plurality of sensors, process the events to form analytic workflows and distributed analytic platform messages, each of the distributed analytic platform messages associated with at least one of an alert, an update to a first analytic model, and cyber behavioral information, each of the analytic workflows: associated with one or more logical segments, and including at least one of the first analytic model, a second analytic model, a rule, a data transformation, and a data aggregation, and transmit the analytic workflows and distributed analytic platform messages; a plurality of scoring engines, each of the plurality of scoring engines being configured to: receive the analytic workflows from the distributed analytic platform, receive the events from at least one of the plurality of sensors, process the received events using the analytic workflows to produce scoring engine messages, and transmit the scoring engine messages; and a real time analytic engine, the real time analytic engine configured to: receive the analytic workflows from the distributed analytic platform, receive analytic workflow and event processing rules, receive the scoring engine messages from the plurality of scoring engines, receive the distributed analytic platform messages from the distributed analytic platform, and process the scoring engine messages and the distributed analytic platform messages using the analytic workflows from the distributed analytic platform and the analytic workflow and event processing rules to form a threat intelligence message, wherein the threat intelligence message comprises at least one of: a broadcast message, the real time analytic engine configured to transmit the broadcast message, a mitigation message, the real time analytic engine configured to transmit the mitigation message to a control plane engine for taking a mitigation action associated with a first logical segment of the one or more logical segments when the processing by the real time analytic engine indicates the mitigation action limits the impact of anomalous activity, and a model update message, the real time analytic engine configured to transmit the model update message for updating one or more analytic workflows when the processing by the real time analytic engine indicates the model update message improves at least one of a detection rate of the anomalous activity and a reduction in a false positive rate, each of the one or more logical segments associating: at least one of the first analytic model, the second analytic model, a third analytic model, a set of analytic models, and an analytic workflow, one or more sources of inputs about activity within the logical segment, and a set of actions for mitigating an impact of the anomalous activity occurring within the logical segment. 3. The system of claim 1 , wherein the plurality of sensors, the plurality of scoring engines, the distributed analytic platform, the real time analytic engine, and the control plane engine communicate by sending associated messages over an enterprise system bus. | 0.908362 |
8,661,338 | 1 | 3 | 1. A document layout processing device comprising: at least one processor; at least one memory coupled to the processor configured to execute programmed instructions stored in the memory comprising: a comparison system configured to compare one or more elements of at least a portion of an original document against the same types of elements in at least a portion each of a plurality of stored documents, wherein the portion of the original document is the portion that requires adjustment or re-layout; a determination system configured to identify a particular stored document in the plurality of stored documents, with the portion which is closest to the portion of the original document based on the comparing; an identification system configured to identify a designated output device and designated output device characteristics; a mutation system configured to apply one or more mutators, to the portion of the original document which were applied to mutate the portion of the identified particular stored document, to form a mutated portion in the original document, having obtained one or more mutators from a list of stored mutators which correspond to the identified particular stored document, wherein the mutation system determines which of the one or more mutators to apply based on one or more designated output device characteristics and the identified particular stored document that matches the portion of the original document; and wherein the mutation system is further configured to apply the determined one or more mutators by retrieving stored priority data and applying the determined one or more mutators to the portion of the original document according the retrieved stored priority order. | 1. A document layout processing device comprising: at least one processor; at least one memory coupled to the processor configured to execute programmed instructions stored in the memory comprising: a comparison system configured to compare one or more elements of at least a portion of an original document against the same types of elements in at least a portion each of a plurality of stored documents, wherein the portion of the original document is the portion that requires adjustment or re-layout; a determination system configured to identify a particular stored document in the plurality of stored documents, with the portion which is closest to the portion of the original document based on the comparing; an identification system configured to identify a designated output device and designated output device characteristics; a mutation system configured to apply one or more mutators, to the portion of the original document which were applied to mutate the portion of the identified particular stored document, to form a mutated portion in the original document, having obtained one or more mutators from a list of stored mutators which correspond to the identified particular stored document, wherein the mutation system determines which of the one or more mutators to apply based on one or more designated output device characteristics and the identified particular stored document that matches the portion of the original document; and wherein the mutation system is further configured to apply the determined one or more mutators by retrieving stored priority data and applying the determined one or more mutators to the portion of the original document according the retrieved stored priority order. 3. The document layout processing device as set forth in claim 1 wherein the determination system further comprises a scoring system configured to generate a score for each of the comparisons of the portion of the original document against each of the portions of each of the plurality of stored documents, wherein the determination system identifies the particular stored document with the portion with the score which is closest to the portion of the original document based on the generated scores. | 0.530899 |
7,877,258 | 22 | 24 | 22. The computer program product of claim 18 , where generating the integer trie further comprises using a third vector and a fourth vector, where the first vector identifies each distinct left word for each distinct context in the collection, the second vector identifies a count of distinct left words for each context in the collection, the third vector identifies each distinct predicted word for a given context in the collection, and the fourth vector identifies a count of distinct predicted words for each context in the collection. | 22. The computer program product of claim 18 , where generating the integer trie further comprises using a third vector and a fourth vector, where the first vector identifies each distinct left word for each distinct context in the collection, the second vector identifies a count of distinct left words for each context in the collection, the third vector identifies each distinct predicted word for a given context in the collection, and the fourth vector identifies a count of distinct predicted words for each context in the collection. 24. The computer program product of claim 22 , further comprising: encoding the first, second, third, and fourth vectors using a lossless block encoding technique. | 0.745313 |
9,569,728 | 3 | 5 | 3. The method of claim 2 , wherein the copresence counts associated with the second link ID and the third link ID respectively in the first set of related link IDs meets or exceeds a specified threshold. | 3. The method of claim 2 , wherein the copresence counts associated with the second link ID and the third link ID respectively in the first set of related link IDs meets or exceeds a specified threshold. 5. The method of claim 3 , wherein the threshold is an integer specified by the server computer. | 0.5 |
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