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8,650,481 | 10 | 11 | 10. A method comprising: storing an extension file configured to perform an action with respect to a browser application during rendering therewith of a page using a page script associated with a page model, the extension file associated with a content script configured to interact with the page model during rendering of the page sript to provide the page; loading the page script, including the page model, into a page script execution environment within a rendering environment of the browser application, the page script execution environment having a page script namespace; implementing a content script execution environment within the rendering environment of the browser application, using a copy of the page model within a content script namespac; wherein communication between the content script execution environment and the page script execution environment is restricted to a one-way direction from the content script execution environment to the page script execution environment; initiating the action using the content script within the content script execution environment; sending a message to the extension file to implement the action; and performing the action using the extension file and in conjunction with the rendering of the page. | 10. A method comprising: storing an extension file configured to perform an action with respect to a browser application during rendering therewith of a page using a page script associated with a page model, the extension file associated with a content script configured to interact with the page model during rendering of the page sript to provide the page; loading the page script, including the page model, into a page script execution environment within a rendering environment of the browser application, the page script execution environment having a page script namespace; implementing a content script execution environment within the rendering environment of the browser application, using a copy of the page model within a content script namespac; wherein communication between the content script execution environment and the page script execution environment is restricted to a one-way direction from the content script execution environment to the page script execution environment; initiating the action using the content script within the content script execution environment; sending a message to the extension file to implement the action; and performing the action using the extension file and in conjunction with the rendering of the page. 11. The method of claim 10 , wherein the page model is associated with a global object which is at least indirectly a parent of all other objects of the page model and which thereby defines the page script namespace, and wherein the content script execution environment utilizes a new global object as a wrapper of the global object to thereby provide the content script namespace. | 0.652372 |
8,775,184 | 17 | 18 | 17. A system for evaluating one or more spoken language skills of a speaker, comprising: a memory; and at least one processor coupled to said memory and operative to: identify one or more temporal locations of interest in an output of a spoken language skill evaluation performed on a speech passage spoken by a speaker; compute one or more acoustic parameters to capture one or more properties of one or more acoustic-phonetic features of the one or more locations of interest, said computing comprising determining one or more spectral differences between the onset of a fricative, a vowel and a stop burst by computing a ratio of energy in a high frequency region of the speech passage to energy in a low frequency region of the speech passage over a predetermined time period via 1 N f ∑ f = 1 N f [ Δ ( f , l ) - μΔ , l ] 2 , wherein f is a given frequency channel, N f is a total number of frequency channels, l is a given frame number, Δ(f, l) is an energy difference in adjacent frames for the given frequency channel f, and is the mean of Δ (f, l) over all frequency channels for the given l; and combine the one or more acoustic parameters with the output of an automatic speech recognizer to generate a modified output of the spoken language skill evaluation. | 17. A system for evaluating one or more spoken language skills of a speaker, comprising: a memory; and at least one processor coupled to said memory and operative to: identify one or more temporal locations of interest in an output of a spoken language skill evaluation performed on a speech passage spoken by a speaker; compute one or more acoustic parameters to capture one or more properties of one or more acoustic-phonetic features of the one or more locations of interest, said computing comprising determining one or more spectral differences between the onset of a fricative, a vowel and a stop burst by computing a ratio of energy in a high frequency region of the speech passage to energy in a low frequency region of the speech passage over a predetermined time period via 1 N f ∑ f = 1 N f [ Δ ( f , l ) - μΔ , l ] 2 , wherein f is a given frequency channel, N f is a total number of frequency channels, l is a given frame number, Δ(f, l) is an energy difference in adjacent frames for the given frequency channel f, and is the mean of Δ (f, l) over all frequency channels for the given l; and combine the one or more acoustic parameters with the output of an automatic speech recognizer to generate a modified output of the spoken language skill evaluation. 18. The system of claim 17 , wherein in identifying one or more temporal locations of interest the at least one processor coupled to said memory is further operative to locate one or more phones of interest. | 0.794643 |
10,133,818 | 15 | 19 | 15. The system of claim 11 , wherein determining a level of social interest in the event based upon the set of mappings further comprises: determining a score by aggregating the mappings, the mappings weighted based on at least one weight determined based on the social media content item. | 15. The system of claim 11 , wherein determining a level of social interest in the event based upon the set of mappings further comprises: determining a score by aggregating the mappings, the mappings weighted based on at least one weight determined based on the social media content item. 19. The system of claim 15 wherein the at least one weight comprises an author-based weight having a numerical value based on a demographic information of an author of the social media content item. | 0.934088 |
9,996,624 | 15 | 21 | 15. A computer readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: receiving, by the one or more processors, general search results that are responsive to a query; cross-referencing uniform resource locators (URLs) of the general search results with a site pattern of a publishing entity that is identified as publishing in-depth articles; determining, by the one or more processors, that one or more general search results to be provided in response to the query is an in-depth article search result based on the URL of the general search result corresponding to the site pattern of the publishing entity; and in response to determining that one or more in-depth article search results are to be provided in response to the query: obtaining a topicality score for each in-depth article referenced by the one or more in-depth article search results responsive to the query, each topicality score indicating a degree of relevance of a respective in-depth article to the query; obtaining a document score for each in-depth article referenced by the one or more in-depth article search results responsive to the query, each document score being based on a respective topicality score and a respective in-depth article score; selecting one or more in-depth articles referenced by the one or more in-depth article search results responsive to the query based on respective document scores; and providing the one or more in-depth article search results for display, each in-depth article search result representing an in-depth article of the one or more in-depth articles. | 15. A computer readable medium storing instructions that, when executed by one or more processors, cause the one or more processors to perform operations comprising: receiving, by the one or more processors, general search results that are responsive to a query; cross-referencing uniform resource locators (URLs) of the general search results with a site pattern of a publishing entity that is identified as publishing in-depth articles; determining, by the one or more processors, that one or more general search results to be provided in response to the query is an in-depth article search result based on the URL of the general search result corresponding to the site pattern of the publishing entity; and in response to determining that one or more in-depth article search results are to be provided in response to the query: obtaining a topicality score for each in-depth article referenced by the one or more in-depth article search results responsive to the query, each topicality score indicating a degree of relevance of a respective in-depth article to the query; obtaining a document score for each in-depth article referenced by the one or more in-depth article search results responsive to the query, each document score being based on a respective topicality score and a respective in-depth article score; selecting one or more in-depth articles referenced by the one or more in-depth article search results responsive to the query based on respective document scores; and providing the one or more in-depth article search results for display, each in-depth article search result representing an in-depth article of the one or more in-depth articles. 21. The computer readable medium of claim 15 , wherein each in-depth article score is based on one or more sub-scores comprising at least one of an article score, a commercial score, an evergreen score, and an author score. | 0.567829 |
7,818,278 | 1 | 3 | 1. A computerized method for matching item representations within a collection of item representations, the method comprising: determining candidate pairs of item representations based on frequency information indicative of the frequency at which terms appear in the collection of item representations, wherein the frequency information comprises an IDF score determined for each term based on the respective term's frequency of use within the collection of item representations, and wherein determining candidate pairs comprises determining an aggregate IDF score for pairs of item representations by adding the IDF scores for terms shared by each pair of item representations and comparing the aggregate IDF score for each pair of item representations against a threshold to determine if each pair of item representations qualifies as a candidate pair; and matching item representations by analyzing the candidate pairs using one or more fuzzy matching functions. | 1. A computerized method for matching item representations within a collection of item representations, the method comprising: determining candidate pairs of item representations based on frequency information indicative of the frequency at which terms appear in the collection of item representations, wherein the frequency information comprises an IDF score determined for each term based on the respective term's frequency of use within the collection of item representations, and wherein determining candidate pairs comprises determining an aggregate IDF score for pairs of item representations by adding the IDF scores for terms shared by each pair of item representations and comparing the aggregate IDF score for each pair of item representations against a threshold to determine if each pair of item representations qualifies as a candidate pair; and matching item representations by analyzing the candidate pairs using one or more fuzzy matching functions. 3. The computerized method of claim 1 , wherein the terms appearing in the collection of item representations comprises at least one of individual words and phrases. | 0.893411 |
8,478,592 | 15 | 16 | 15. The computer system of claim 14 , wherein the media file comprises a video file. | 15. The computer system of claim 14 , wherein the media file comprises a video file. 16. The computer system of claim 15 , wherein a time stamp includes an hour, minute and second indicator. | 0.973881 |
8,402,029 | 10 | 12 | 10. A non-transitory computer-readable medium comprising instructions for execution by a computer, the instructions implementing the method comprising: determining a first set of clusters to display from a plurality of search query results, each of the plurality of search query results being associated with at least one cluster in the first set of clusters; determining a title to display of at least one cluster in the first set of clusters; after determining the title to display of the at least one cluster in the set of clusters, identifying an input indication to recluster the plurality of search query results; determining a second set of clusters to display, which excludes one or more clusters from the first set of clusters, each of the plurality of search query results being associated with at least one cluster in the second set of clusters. | 10. A non-transitory computer-readable medium comprising instructions for execution by a computer, the instructions implementing the method comprising: determining a first set of clusters to display from a plurality of search query results, each of the plurality of search query results being associated with at least one cluster in the first set of clusters; determining a title to display of at least one cluster in the first set of clusters; after determining the title to display of the at least one cluster in the set of clusters, identifying an input indication to recluster the plurality of search query results; determining a second set of clusters to display, which excludes one or more clusters from the first set of clusters, each of the plurality of search query results being associated with at least one cluster in the second set of clusters. 12. The non-transitory computer-readable medium of claim 10 , wherein the method further comprises: determining a linguistic equivalence class of each cluster in the first set of clusters; and when determining the second set of clusters to display, further excluding the linguistic equivalence class of each cluster in the first set of clusters. | 0.863204 |
9,588,955 | 1 | 3 | 1. A method implemented on a computer comprising a memory, a processor, and a program stored in the memory, the method for making publisher recommendations and comprising: a) accessing from the memory a word processing module for execution by the processor; b) initializing the program via the word processing module, the program executed by the processor and comprising a bibliographic software module and a recommendation sub-module, the initializing permitting interaction among the bibliographic software module, the recommendation sub-module and the word processing module; c) invoking the recommendation sub-module to automatically generate a set of at least one recommendation as to a publication to which to submit an unpublished article for publication consideration, the recommendation based upon an analysis of a set of information associated with the unpublished article, the set of information comprising a bibliography and an overall score, the overall score representing a match probability determined using at least one model selected from a group consisting of a nearest neighbor model and a fingerprint model; d) storing the recommendation in the memory; and e) transmitting a file associated with the unpublished article to an electronic repository associated with at least one publication from the set of at least one publication. | 1. A method implemented on a computer comprising a memory, a processor, and a program stored in the memory, the method for making publisher recommendations and comprising: a) accessing from the memory a word processing module for execution by the processor; b) initializing the program via the word processing module, the program executed by the processor and comprising a bibliographic software module and a recommendation sub-module, the initializing permitting interaction among the bibliographic software module, the recommendation sub-module and the word processing module; c) invoking the recommendation sub-module to automatically generate a set of at least one recommendation as to a publication to which to submit an unpublished article for publication consideration, the recommendation based upon an analysis of a set of information associated with the unpublished article, the set of information comprising a bibliography and an overall score, the overall score representing a match probability determined using at least one model selected from a group consisting of a nearest neighbor model and a fingerprint model; d) storing the recommendation in the memory; and e) transmitting a file associated with the unpublished article to an electronic repository associated with at least one publication from the set of at least one publication. 3. The method of claim 1 wherein the method further comprises presenting via a display the set of information about the journal to which to submit the unpublished article. | 0.755714 |
8,676,731 | 23 | 26 | 23. The server of claim 22 wherein the data capture server is for computing, in a production mode, from the combined component confidences, for each of the scanned data items, a confidence attribute, the confidence attribute indicative of a confidence that the scanned data item matches the data value. | 23. The server of claim 22 wherein the data capture server is for computing, in a production mode, from the combined component confidences, for each of the scanned data items, a confidence attribute, the confidence attribute indicative of a confidence that the scanned data item matches the data value. 26. The server of claim 23 wherein the transformations are a series of data transformations, each transformation having an input and an output, the output of a particular transformation providing input to a successive transformation such that each transformation represents a different data type representative of the data value. | 0.936017 |
7,685,252 | 1 | 38 | 1. A method of generating an application accessible by a user through one or more computer-based devices, the method comprising the steps of: representing interactions that the user is permitted to have with the one or more computer-based devices used to access the application by interaction-based programming components, wherein the interaction-based programming components are independent of content/application logic and presentation requirements associated with the application, and further wherein the interaction-based programming components may be transcoded on a component by component basis to generate one or more modality-specific renderings of the application renderable in accordance with one or more modality-specific browsers associated with the one or more computer-based devices, such that the interaction-based programming components are independent of any modality and any modality-specific browser; and authoring the application using at least a portion of the interaction-based programming components; wherein representation by the interaction-based programming components permits synchronization of the one or more modality-specific renderings of the application on the one or more computer-based devices. | 1. A method of generating an application accessible by a user through one or more computer-based devices, the method comprising the steps of: representing interactions that the user is permitted to have with the one or more computer-based devices used to access the application by interaction-based programming components, wherein the interaction-based programming components are independent of content/application logic and presentation requirements associated with the application, and further wherein the interaction-based programming components may be transcoded on a component by component basis to generate one or more modality-specific renderings of the application renderable in accordance with one or more modality-specific browsers associated with the one or more computer-based devices, such that the interaction-based programming components are independent of any modality and any modality-specific browser; and authoring the application using at least a portion of the interaction-based programming components; wherein representation by the interaction-based programming components permits synchronization of the one or more modality-specific renderings of the application on the one or more computer-based devices. 38. The method of claim 1 , wherein the components may be active in parallel. | 0.896783 |
7,689,423 | 14 | 18 | 14. A computer readable medium storing a computer program comprising: computer readable code for receiving a user utterance at the telematics unit from a user, the user utterance including a plurality of segments including a user pause between each segment, each of the plurality of segments having a plurality of words and a plurality of user pauses between the words; computer readable code for parsing the user utterance into a plurality of phonemes; computer readable code for forming a data string in which each user pause is associated with a phoneme adjacent to the user pause, wherein the computer readable code for forming the data string includes i) computer readable code for determining an average duration of each pause between the plurality of words in each segment, ii) computer readable code for assigning a time duration for each of the user pauses based on the average duration determination of each user pause between the plurality of words, iii) computer readable code for determining an average duration of each user pause between each segment, iv) computer readable code for assigning a time duration for each of the user pauses based on the average duration determination of each user pause between each segment, v) computer readable code for associating each pause with the phoneme adjacent to the user pause, and vi) computer readable code for concatenating each user pause and the associated phoneme, each user pause including its associated assigned time duration; computer readable code for generating a virtual utterance corresponding to the data string; and computer readable code for playing back the virtual utterance to the user. | 14. A computer readable medium storing a computer program comprising: computer readable code for receiving a user utterance at the telematics unit from a user, the user utterance including a plurality of segments including a user pause between each segment, each of the plurality of segments having a plurality of words and a plurality of user pauses between the words; computer readable code for parsing the user utterance into a plurality of phonemes; computer readable code for forming a data string in which each user pause is associated with a phoneme adjacent to the user pause, wherein the computer readable code for forming the data string includes i) computer readable code for determining an average duration of each pause between the plurality of words in each segment, ii) computer readable code for assigning a time duration for each of the user pauses based on the average duration determination of each user pause between the plurality of words, iii) computer readable code for determining an average duration of each user pause between each segment, iv) computer readable code for assigning a time duration for each of the user pauses based on the average duration determination of each user pause between each segment, v) computer readable code for associating each pause with the phoneme adjacent to the user pause, and vi) computer readable code for concatenating each user pause and the associated phoneme, each user pause including its associated assigned time duration; computer readable code for generating a virtual utterance corresponding to the data string; and computer readable code for playing back the virtual utterance to the user. 18. The medium of claim 14 , further comprising: computer readable code for setting frequency parameters in a speech generation algorithm in a speech recognition engine at the telematics unit. | 0.706422 |
9,851,897 | 9 | 10 | 9. An article comprising: a computer-readable storage medium that contains instructions, which when executed by one or more processors result in performing operations comprising: sensing a contact patch on a touchscreen of a handheld electronic device; determining a centroid for a contact patch for the touch; and determining an active point for the contact patch. | 9. An article comprising: a computer-readable storage medium that contains instructions, which when executed by one or more processors result in performing operations comprising: sensing a contact patch on a touchscreen of a handheld electronic device; determining a centroid for a contact patch for the touch; and determining an active point for the contact patch. 10. The article of claim 9 , wherein the operation of determining the active point is based at least in part on one or more factors selected from a list consisting of: a centroid of the contact patch; a size of the contact patch; a shape of the contact patch; a difference in pressure sensed at the multiple points; a location on the keyboard of the contact patch; a positional relationship between the contact patch and a keyboard key that is at least partly overlapped by the contact patch; a previous history of the positional relationship between the contact patch and the keyboard key. | 0.500846 |
9,715,557 | 1 | 5 | 1. An electronic device comprising: storage configured to maintain a primary web-browser application and a secondary web-browser application; at least one processor connected to said storage and configured to execute said primary web-browser application; an interface connected to said processor, said processor configured to receive a web-page stored at a web-server via said interface, said web-page including context sensitive content related to a plurality of context sensitive items on said web-page, said context sensitive content being able to change without further input from the web-server, said context sensitive content comprising a data portion and a non-data portion, said non-data portion comprising scripts executable by said primary web-browser application and said data portion comprising tags, labels, or text; a display connected to said processor; said processor further configured to render said web-page on said display; an input device connected to said processor, said processor configured to receive focus on one of said plurality of context sensitive items via said input device placing a pointer over the one context sensitive item; said processor further configured to respond to receiving the focus by rendering only the tags, labels, or text constituting the data portion of the context sensitive content related to said one of the plurality of context sensitive items on said display via the secondary web-browser application; and said processor further configured to not execute said scripts associated with said context sensitive content using said secondary web-browser application. | 1. An electronic device comprising: storage configured to maintain a primary web-browser application and a secondary web-browser application; at least one processor connected to said storage and configured to execute said primary web-browser application; an interface connected to said processor, said processor configured to receive a web-page stored at a web-server via said interface, said web-page including context sensitive content related to a plurality of context sensitive items on said web-page, said context sensitive content being able to change without further input from the web-server, said context sensitive content comprising a data portion and a non-data portion, said non-data portion comprising scripts executable by said primary web-browser application and said data portion comprising tags, labels, or text; a display connected to said processor; said processor further configured to render said web-page on said display; an input device connected to said processor, said processor configured to receive focus on one of said plurality of context sensitive items via said input device placing a pointer over the one context sensitive item; said processor further configured to respond to receiving the focus by rendering only the tags, labels, or text constituting the data portion of the context sensitive content related to said one of the plurality of context sensitive items on said display via the secondary web-browser application; and said processor further configured to not execute said scripts associated with said context sensitive content using said secondary web-browser application. 5. The electronic device of claim 1 wherein said processor is configured to parse said context sensitive content to extract said data portion. | 0.709016 |
9,747,556 | 1 | 16 | 1. A method of operation in an automated Web portal generation system to generate sets of customizations of Web portal templates, the method comprising: parsing, by at least one component of the automated Web portal generation system, a number of Webpages of a first Website, represented by a domain or Universal Resource Locator (URL), from which a Web portal template to be customized is to be accessed; producing an entity feature set for the first Website based on a result of the parsing; processing the entity feature set for the first Website via a classifier executed by at least one component of the automated Web portal generation system to produce a set of data that represents, for each of a plurality of entities, a respective probability of the entity belonging to a respective one of a plurality of classes; performing color matching on the set of data produced via the classifier to generate a number of proposed color combinations for a proposed customization of the Web portal template, wherein performing color matching to generate a number of proposed color combinations includes identifying candidate background colors by evaluating contrast between colors of each pair of a plurality of pairs of colors in a device-independent color space; ranking pairs of color combinations based at least in part on the probabilities from the processing via the classifier; returning the ranking as a collection of results for user evaluation; and identifying one of the proposed color combinations for a proposed customization of the Web portal template. | 1. A method of operation in an automated Web portal generation system to generate sets of customizations of Web portal templates, the method comprising: parsing, by at least one component of the automated Web portal generation system, a number of Webpages of a first Website, represented by a domain or Universal Resource Locator (URL), from which a Web portal template to be customized is to be accessed; producing an entity feature set for the first Website based on a result of the parsing; processing the entity feature set for the first Website via a classifier executed by at least one component of the automated Web portal generation system to produce a set of data that represents, for each of a plurality of entities, a respective probability of the entity belonging to a respective one of a plurality of classes; performing color matching on the set of data produced via the classifier to generate a number of proposed color combinations for a proposed customization of the Web portal template, wherein performing color matching to generate a number of proposed color combinations includes identifying candidate background colors by evaluating contrast between colors of each pair of a plurality of pairs of colors in a device-independent color space; ranking pairs of color combinations based at least in part on the probabilities from the processing via the classifier; returning the ranking as a collection of results for user evaluation; and identifying one of the proposed color combinations for a proposed customization of the Web portal template. 16. The method of claim 1 , further comprising: autonomously applying the identified one of the proposed color combinations to the Web portal template to produce an instance of a customized Web portal. | 0.858848 |
7,831,442 | 37 | 38 | 37. The system according to claim 27 , wherein the software further includes instructions to compare each edit to each other edit in the edit list. | 37. The system according to claim 27 , wherein the software further includes instructions to compare each edit to each other edit in the edit list. 38. The system according to claim 37 , further comprising: wherein the reducing comprises consolidating selected ones of the edits in the edit list into more than one new edit; and wherein the software further includes instructions to generate a list of each new edit formed from said consolidation into the more than one new edit. | 0.901017 |
9,052,934 | 19 | 21 | 19. A non-transitory computer-readable medium carrying instructions for a method to permit a user to debug a set of interpretation rules for a host instrument, the method comprising: providing one or more sets of interpretation rules to be selected by a user for downloading to a host instrument; transmitting one or more non-native commands to the host instrument, wherein the one or more non-native commands is part of a command set supported by an alternate instrument to trigger the alternate instrument to perform one or more actions when received; and providing access to the one or more sets of interpretation rules for editing by the user, wherein the host instrument applies the downloaded and edited interpretation rules to the one or more non-native commands to determine the one or more actions that the one or more non-native commands instruct the alternate instrument to perform; wherein the edited interpretation rules are subsequently used by the host instrument to interpret the one or more non-native commands to determine the one or more actions and performing by the host instrument the one or more actions that the alternate instrument performs upon receiving the non-native command. | 19. A non-transitory computer-readable medium carrying instructions for a method to permit a user to debug a set of interpretation rules for a host instrument, the method comprising: providing one or more sets of interpretation rules to be selected by a user for downloading to a host instrument; transmitting one or more non-native commands to the host instrument, wherein the one or more non-native commands is part of a command set supported by an alternate instrument to trigger the alternate instrument to perform one or more actions when received; and providing access to the one or more sets of interpretation rules for editing by the user, wherein the host instrument applies the downloaded and edited interpretation rules to the one or more non-native commands to determine the one or more actions that the one or more non-native commands instruct the alternate instrument to perform; wherein the edited interpretation rules are subsequently used by the host instrument to interpret the one or more non-native commands to determine the one or more actions and performing by the host instrument the one or more actions that the alternate instrument performs upon receiving the non-native command. 21. The computer-readable medium of claim 19 wherein the one or more non-native commands are individually entered by the user. | 0.704225 |
9,659,563 | 10 | 11 | 10. A method comprising: receiving at a client device from a server first content containing regions of the world; generating at the client device a user interface for a user to select of a region from the regions of the world that the user desires to listen to the region-specific pronunciations of phrases of a first language, wherein the server determines that first regions of the regions of the world include at least one voice recording in the first language; transmitting from the client device to the server a region selected from the first regions by the user; receiving at the client device from the server second content containing a list of phrases and voice recordings corresponding to each of the phrases of the first language, wherein the voice recordings contain the region-specific pronunciations of the phrases of the region selected by the user; and generating an output of a voice recording of a phrase selected by the user from the list of phrases. | 10. A method comprising: receiving at a client device from a server first content containing regions of the world; generating at the client device a user interface for a user to select of a region from the regions of the world that the user desires to listen to the region-specific pronunciations of phrases of a first language, wherein the server determines that first regions of the regions of the world include at least one voice recording in the first language; transmitting from the client device to the server a region selected from the first regions by the user; receiving at the client device from the server second content containing a list of phrases and voice recordings corresponding to each of the phrases of the first language, wherein the voice recordings contain the region-specific pronunciations of the phrases of the region selected by the user; and generating an output of a voice recording of a phrase selected by the user from the list of phrases. 11. The method of claim 10 wherein the region is a country where its primary language is a second language that is different from the first language. | 0.8808 |
6,155,485 | 4 | 5 | 4. The method of claim 1, step (d) including the step of printing an image of the medicament as said medicament indicia on said package label. | 4. The method of claim 1, step (d) including the step of printing an image of the medicament as said medicament indicia on said package label. 5. The method of claim 4, the medicament having opposed faces, step (d) including the step of printing an image of both of said opposed faces as said medicament indicia on said package label. | 0.947786 |
9,536,352 | 13 | 16 | 13. One or more non-transitory computer-readable storage media comprising a plurality of instructions that in response to being executed cause an augmented reality device to: capture an image; analyze the image to recognize a subject represented in the image and a background item in the image; access a character profile based on the subject; determine, based on the character profile, whether the background item is associated with the subject; determine, based on the character profile and in response to a determination that the background item is associated with the subject, a theme of the image; determine a context associated with the subject based on the image and the background item, wherein the context is related to the theme, wherein to determine the context comprises to classify a type of an accessory object represented in the image that is related to the subject; select a virtual object based on the context of the subject and the background item, wherein the virtual object comprises an accessory object that is composable with the virtual character and is of the same type as the accessory object represented in the image, and wherein to select the virtual object comprises to select the virtual object based on similarity between the virtual object and a feature of the subject; apply the virtual object to a virtual character; and render an augmented reality scene based on the captured image and including the virtual character with the virtual object applied thereto. | 13. One or more non-transitory computer-readable storage media comprising a plurality of instructions that in response to being executed cause an augmented reality device to: capture an image; analyze the image to recognize a subject represented in the image and a background item in the image; access a character profile based on the subject; determine, based on the character profile, whether the background item is associated with the subject; determine, based on the character profile and in response to a determination that the background item is associated with the subject, a theme of the image; determine a context associated with the subject based on the image and the background item, wherein the context is related to the theme, wherein to determine the context comprises to classify a type of an accessory object represented in the image that is related to the subject; select a virtual object based on the context of the subject and the background item, wherein the virtual object comprises an accessory object that is composable with the virtual character and is of the same type as the accessory object represented in the image, and wherein to select the virtual object comprises to select the virtual object based on similarity between the virtual object and a feature of the subject; apply the virtual object to a virtual character; and render an augmented reality scene based on the captured image and including the virtual character with the virtual object applied thereto. 16. The one or more non-transitory computer-readable storage media of claim 13 , wherein to determine the context comprises to determine a current activity of the subject. | 0.751453 |
8,700,414 | 11 | 12 | 11. An apparatus comprising: a computer system wherein messages are transferred between participants, at least some of which are human users of the computer system using the computer system in furtherance of work projects; a workflow system that is configured to handle task-based operations in a structured environment; at least one monitored operations system that is configured to generate alerts to notify participants of events within the at least one monitored operations system; an alert generator that is configured to transmit, to a determined participant, a message comprising a first alert that a particular first event occurred, wherein the first event is determinable from at least one of the state of the computer system, the computer system's data or external data available to the computer system, wherein an alert rule indicates that the determined participant is to be alerted with the message when the particular first event occurs; and a structured event handler that is configured to initiate a logging of event resolution responses by the determined participant in response to the first event to form an event resolution log, and that is configured to store the event resolution log for use in informing a future determined participant, via the workflow system, as to a possible event resolution process when the future determined participant encounters a second alert of a second event wherein the second alert is similar to the first alert, the second event is similar to the first event or both, the possible event resolution process depending, at least in part, on the event resolution log for the first event, wherein the structured event handler is configured to end the event resolution log when the determined participant signals to the computer system a resolution of the first event, wherein the structured event handler is configured to generate a workflow process template from the event resolution log, the workflow process template comprising at least one workflow item, and wherein the workflow system is configured to store the workflow process template in association with a category identifier associated with the first event. | 11. An apparatus comprising: a computer system wherein messages are transferred between participants, at least some of which are human users of the computer system using the computer system in furtherance of work projects; a workflow system that is configured to handle task-based operations in a structured environment; at least one monitored operations system that is configured to generate alerts to notify participants of events within the at least one monitored operations system; an alert generator that is configured to transmit, to a determined participant, a message comprising a first alert that a particular first event occurred, wherein the first event is determinable from at least one of the state of the computer system, the computer system's data or external data available to the computer system, wherein an alert rule indicates that the determined participant is to be alerted with the message when the particular first event occurs; and a structured event handler that is configured to initiate a logging of event resolution responses by the determined participant in response to the first event to form an event resolution log, and that is configured to store the event resolution log for use in informing a future determined participant, via the workflow system, as to a possible event resolution process when the future determined participant encounters a second alert of a second event wherein the second alert is similar to the first alert, the second event is similar to the first event or both, the possible event resolution process depending, at least in part, on the event resolution log for the first event, wherein the structured event handler is configured to end the event resolution log when the determined participant signals to the computer system a resolution of the first event, wherein the structured event handler is configured to generate a workflow process template from the event resolution log, the workflow process template comprising at least one workflow item, and wherein the workflow system is configured to store the workflow process template in association with a category identifier associated with the first event. 12. The apparatus of claim 11 , wherein: the workflow system is configured to provide the stored workflow process template to the future determined participant for use in informing the future determined participant as to a possible event resolution process when the future determined participant encounters the second alert; and the workflow system is configured to accept input from the future determined participant as to modifications to the stored workflow process template in response to actions performed by the future determined participant in resolving the second event, thereby generating one other dated stored workflow process template iteratively refined by a plurality of event resolutions. | 0.50071 |
9,843,668 | 1 | 2 | 1. A method for determining a number of authorized and unauthorized participants of a telephone conversation, the method comprising: continuously sampling voice data from the telephone conversation; analyzing the sampled voice data using biometric voice identification to identify one or more unique voiceprints; comparing each of the identified one or more unique voiceprints to a first registered voiceprint of a resident of a facility and a second registered voiceprint of a party remote from the facility, wherein the second registered voiceprint was obtained via a remote participant registration process conducted prior to the telephone conversation; identifying the number of authorized and unauthorized participants of the telephone conversation based on the comparison; taking a first predefined action when the number of authorized or unauthorized participants is greater than a first predetermined number; and taking a second predefined action when the number of unauthorized participants is greater than a second predetermined number. | 1. A method for determining a number of authorized and unauthorized participants of a telephone conversation, the method comprising: continuously sampling voice data from the telephone conversation; analyzing the sampled voice data using biometric voice identification to identify one or more unique voiceprints; comparing each of the identified one or more unique voiceprints to a first registered voiceprint of a resident of a facility and a second registered voiceprint of a party remote from the facility, wherein the second registered voiceprint was obtained via a remote participant registration process conducted prior to the telephone conversation; identifying the number of authorized and unauthorized participants of the telephone conversation based on the comparison; taking a first predefined action when the number of authorized or unauthorized participants is greater than a first predetermined number; and taking a second predefined action when the number of unauthorized participants is greater than a second predetermined number. 2. The method of claim 1 , wherein the first predefined action is one or more of terminating a telephone call on which the telephone conversation is taking place and alerting appropriate authorities. | 0.96576 |
7,933,914 | 1 | 11 | 1. A task system, including a processor communicatively coupled to a memory, the memory having stored therein computer-executable instructions configured to implement the task system comprising: a browser that receives a query, and in response to receiving the query, further receives search results from a search engine for a search based at least in part on the query received, and further receives information related to at least one task object, wherein the at least one task object is selected from one or more sets of task objects stored in one or more memories, each task object comprises at least one modifiable parameter facilitating selection of the at least one task object based at least in part on the query received by the browser; a browser helper object that binds to the browser at runtime, the browser helper object provides information associated with a user's action with respect to the received search results or the received information related to at least one task object, the browser helper object creates an object model corresponding to a schema associated with a web page associated with the user's action, the browser helper object further inserts at least one of the at least one modifiable parameter into a form associated with a web page associated with the user's action, the browser helper object further provides click-through information when the user's action comprises selecting a Uniform Resource Locator (URL) from the received search results, the click-through information including the selected URL, the browser helper object further provides information regarding a website when the user's action comprises manually navigating to the website, the information regarding the website including the URL of the website; a task retrieval model that is updated when the search results are received, the task retrieval model updated based on the click-through information obtained from the browser helper object; and a slot-filling model that is updated when the search results are received, the slot-filling model having one or more slots that hold pieces of information about the at least one task object, the slot-filling model being updated with at least one new parameter representing one new piece of information not currently present in the slot-filling model when the search results include the new piece of information and the new piece of information is not present in the slot-filling model, the slot-filling model also learning one or more new patterns for filling slots based on the search results. | 1. A task system, including a processor communicatively coupled to a memory, the memory having stored therein computer-executable instructions configured to implement the task system comprising: a browser that receives a query, and in response to receiving the query, further receives search results from a search engine for a search based at least in part on the query received, and further receives information related to at least one task object, wherein the at least one task object is selected from one or more sets of task objects stored in one or more memories, each task object comprises at least one modifiable parameter facilitating selection of the at least one task object based at least in part on the query received by the browser; a browser helper object that binds to the browser at runtime, the browser helper object provides information associated with a user's action with respect to the received search results or the received information related to at least one task object, the browser helper object creates an object model corresponding to a schema associated with a web page associated with the user's action, the browser helper object further inserts at least one of the at least one modifiable parameter into a form associated with a web page associated with the user's action, the browser helper object further provides click-through information when the user's action comprises selecting a Uniform Resource Locator (URL) from the received search results, the click-through information including the selected URL, the browser helper object further provides information regarding a website when the user's action comprises manually navigating to the website, the information regarding the website including the URL of the website; a task retrieval model that is updated when the search results are received, the task retrieval model updated based on the click-through information obtained from the browser helper object; and a slot-filling model that is updated when the search results are received, the slot-filling model having one or more slots that hold pieces of information about the at least one task object, the slot-filling model being updated with at least one new parameter representing one new piece of information not currently present in the slot-filling model when the search results include the new piece of information and the new piece of information is not present in the slot-filling model, the slot-filling model also learning one or more new patterns for filling slots based on the search results. 11. The system of claim 1 , the information associated with the user's action does not contain any information which is constituted as personally identifiable. | 0.51227 |
8,823,744 | 1 | 3 | 1. An annotation method for a three-dimensional model, the method comprising: storing in a computer memory a first set of data representative of the three-dimensional model; storing in the computer memory a second set of data representative of an annotation associated with a first spatial location on the three-dimensional model and a first display view; displaying the three-dimensional model and a first graphical representation of the annotation in a display window according to the first display view, the first graphical representation of the annotation being positioned as specified by the first spatial location associated with the annotation; modifying the displaying of the three-dimensional model in the display window to a second display view different from the first display view; removing, in response to modifying the displaying to the second display view, the first graphical representation of the annotation from the display window; and displaying, in the display window in response to modifying the displaying to the second display view and as a substitute for the removed first graphical representation of the annotation, an annotation indicator representative of the annotation, the annotation indicator being visible on the display window independent of any display view of the three-dimensional model. | 1. An annotation method for a three-dimensional model, the method comprising: storing in a computer memory a first set of data representative of the three-dimensional model; storing in the computer memory a second set of data representative of an annotation associated with a first spatial location on the three-dimensional model and a first display view; displaying the three-dimensional model and a first graphical representation of the annotation in a display window according to the first display view, the first graphical representation of the annotation being positioned as specified by the first spatial location associated with the annotation; modifying the displaying of the three-dimensional model in the display window to a second display view different from the first display view; removing, in response to modifying the displaying to the second display view, the first graphical representation of the annotation from the display window; and displaying, in the display window in response to modifying the displaying to the second display view and as a substitute for the removed first graphical representation of the annotation, an annotation indicator representative of the annotation, the annotation indicator being visible on the display window independent of any display view of the three-dimensional model. 3. The method of claim 1 , wherein the first display view and the second display view are each further defined by one or more view parameters that sets a visual appearance of the three dimensional model. | 0.873125 |
7,831,429 | 6 | 8 | 6. A mobile terminal having speech recognition capabilities, comprising: an antenna for receiving one or more graphical user interface (GUI) files from a host computer, wherein the GUI files have attached thereto a dictionary file having phonemes and syntax file having allowable patterns of words being content specific to the graphical display file and associated with a particular context state; a processor; a memory to store the received one or more graphical user interface (GUI) files; a display operatively coupled to the processor, the display adapted to display at least one GUI based on the received one or more graphical user interface (GUI) files; a microphone for receiving speech input from a user; and a speech recognition system for determining a current context state of interactive communication with the user and assigning a correct meaning to received input speech by assigning one meaning to received input speech by utilizing the dictionary file and syntax file when the current context state is determined to be a first context state, and assigning a different meaning to the same received speech by utilizing the dictionary file and syntax file when the current context state is determined to be a second context state. | 6. A mobile terminal having speech recognition capabilities, comprising: an antenna for receiving one or more graphical user interface (GUI) files from a host computer, wherein the GUI files have attached thereto a dictionary file having phonemes and syntax file having allowable patterns of words being content specific to the graphical display file and associated with a particular context state; a processor; a memory to store the received one or more graphical user interface (GUI) files; a display operatively coupled to the processor, the display adapted to display at least one GUI based on the received one or more graphical user interface (GUI) files; a microphone for receiving speech input from a user; and a speech recognition system for determining a current context state of interactive communication with the user and assigning a correct meaning to received input speech by assigning one meaning to received input speech by utilizing the dictionary file and syntax file when the current context state is determined to be a first context state, and assigning a different meaning to the same received speech by utilizing the dictionary file and syntax file when the current context state is determined to be a second context state. 8. The mobile terminal of claim 6 , further comprises an operator input device in the form of a virtual keypad that is part of the web page being displayed. | 0.662338 |
7,752,204 | 37 | 38 | 37. The method of claim 36 , further comprising highlighting at least one of a query term and a secondary term in the returned text summarization segment. | 37. The method of claim 36 , further comprising highlighting at least one of a query term and a secondary term in the returned text summarization segment. 38. The method of claim 37 , wherein the form of highlighting of each highlighted term is based upon the respective computed weight. | 0.979823 |
9,454,729 | 8 | 11 | 8. A system comprising one or more processor-based devices configured to: select a first affinity vector comprising a first plurality of topic affinity level values that are associated with a first user of a computer-implemented system, wherein a plurality of the first plurality of topic affinity level values are each based on an inference from a first one or more usage behaviors; select a second affinity vector comprising a second plurality of topic affinity level values that are associated with a second user of the computer-implemented system, wherein a plurality of the second plurality of topic affinity level values are each based on an inference from a second one or more usage behaviors, and wherein the selection of the second affinity vector is in accordance with a determination of a relatively high level of similarity between a plurality of the first plurality of topic affinity level values and a corresponding plurality of the second plurality of topic affinity level values; identify one or more pairs of contrasting corresponding topic affinity level values by comparing topic affinity level values in the first affinity vector with topic affinity level values in the second affinity vector; and generate a recommendation for delivery to the first user, wherein the recommendation is generated in accordance with the one or more pairs of contrasting corresponding topic affinity level values. | 8. A system comprising one or more processor-based devices configured to: select a first affinity vector comprising a first plurality of topic affinity level values that are associated with a first user of a computer-implemented system, wherein a plurality of the first plurality of topic affinity level values are each based on an inference from a first one or more usage behaviors; select a second affinity vector comprising a second plurality of topic affinity level values that are associated with a second user of the computer-implemented system, wherein a plurality of the second plurality of topic affinity level values are each based on an inference from a second one or more usage behaviors, and wherein the selection of the second affinity vector is in accordance with a determination of a relatively high level of similarity between a plurality of the first plurality of topic affinity level values and a corresponding plurality of the second plurality of topic affinity level values; identify one or more pairs of contrasting corresponding topic affinity level values by comparing topic affinity level values in the first affinity vector with topic affinity level values in the second affinity vector; and generate a recommendation for delivery to the first user, wherein the recommendation is generated in accordance with the one or more pairs of contrasting corresponding topic affinity level values. 11. The system of claim 8 , further comprising the one or more processor-based devices configured to: generate the recommendation for delivery to the first user, wherein the recommendation is generated in response to a search request by the first user. | 0.776199 |
9,317,605 | 19 | 29 | 19. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by a data processing apparatus cause the data processing apparatus to perform operations comprising: receiving one or more characters from a user device; obtaining an auto-completion corresponding to the one or more characters; obtaining data identifying multiple corpora and a respective corpus score associated with the auto-completion for each identified corpus; selecting a first corpus of the multiple corpora whose corpus score satisfies a threshold and a universal search corpus that includes two or more of the multiple corpora and excludes the first corpus; and providing, for display in a drop-down menu and to the user device, a first drop down entry that indicates a first instance of the auto-completion and that includes an icon representing the first corpus adjacent to the first instance of the auto-completion, and a second drop down entry that indicates a second instance of the auto-completion that corresponds to the universal search corpus and that excludes the icon representing the first corpus, wherein the universal search corpus includes two or more of a web search corpus, a places search corpus, a literature search corpus, a patent search corpus, an images search corpus, a videos search corpus, a news search corpus, a shopping search corpus, and a blocs search corpus. | 19. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by a data processing apparatus cause the data processing apparatus to perform operations comprising: receiving one or more characters from a user device; obtaining an auto-completion corresponding to the one or more characters; obtaining data identifying multiple corpora and a respective corpus score associated with the auto-completion for each identified corpus; selecting a first corpus of the multiple corpora whose corpus score satisfies a threshold and a universal search corpus that includes two or more of the multiple corpora and excludes the first corpus; and providing, for display in a drop-down menu and to the user device, a first drop down entry that indicates a first instance of the auto-completion and that includes an icon representing the first corpus adjacent to the first instance of the auto-completion, and a second drop down entry that indicates a second instance of the auto-completion that corresponds to the universal search corpus and that excludes the icon representing the first corpus, wherein the universal search corpus includes two or more of a web search corpus, a places search corpus, a literature search corpus, a patent search corpus, an images search corpus, a videos search corpus, a news search corpus, a shopping search corpus, and a blocs search corpus. 29. The computer storage medium of claim 19 , providing, for display in a drop-down menu and to the user device, a first drop down entry that indicates a first instance of the auto-completion and that includes an icon representing the first corpus adjacent to the first instance of the auto-completion, and a second drop down entry that indicates a second instance of the auto-completion that corresponds to the universal search corpus and that excludes the icon representing the first corpus comprises: providing a first user-selectable option for initiating a search of items in the first corpus using the auto-completion as a query; and providing a second user-selectable option for initiating a search of items in the universal search corpus using the auto-completion as a query. | 0.553592 |
8,171,052 | 14 | 15 | 14. The computer readable storage medium according to claim 13 , wherein the method further comprises the steps of: specifying at least one word as a base node; and reading the occurrence information on the word of the base node and listing words having occurrence information which has the same document ID as a larger first order than, a smaller second order than and a depth difference not more than the predetermined value from the occurrence information on the word of the base node. | 14. The computer readable storage medium according to claim 13 , wherein the method further comprises the steps of: specifying at least one word as a base node; and reading the occurrence information on the word of the base node and listing words having occurrence information which has the same document ID as a larger first order than, a smaller second order than and a depth difference not more than the predetermined value from the occurrence information on the word of the base node. 15. The computer readable storage medium according to claim 14 , wherein the words are listed in order of frequency of the occurrence information on the word. | 0.953828 |
7,805,240 | 3 | 4 | 3. The driving behavior prediction apparatus of claim 2 , wherein the first weight update unit updates the weighting factor for each of the relevant templates in a manner that increases the reliability in proportion to the object point distance at the time of predicting the driving behavior. | 3. The driving behavior prediction apparatus of claim 2 , wherein the first weight update unit updates the weighting factor for each of the relevant templates in a manner that increases the reliability in proportion to the object point distance at the time of predicting the driving behavior. 4. The driving behavior prediction apparatus of claim 3 , wherein the first weight update unit updates the weighting factor for each of the relevant templates by adding a reward for increasing the reliability of each of the relevant templates, and the reward is configured to increase in geometric progression in proportion to the object point distance. | 0.931748 |
7,617,187 | 1 | 5 | 1. A method of searching in a second dataset using a query from a first dataset, the method comprising: receiving a first query using the first dataset, the first query being generated using a first collation associated with the first dataset, the first collation having a case sensitivity flag, an accent use sensitivity flag, a character width sensitivity flag, and a kana sensitivity flag for a first human language; rewriting the first query to form a second query, the second query comprising a second collation and a residue predicate, the second collation comprising a superset of the first collation, the second collation of the second query being broader than the first collation of the first query and being insensitive with respect to at least one of case, accent use, character width, and kana, the second collation encompassing the first collation, the second collation having an associated index for the second collation, and the residue predicate comprising an original search term from the first query, wherein the residue predicate is selected to ensure that a set of results returned in response to the second query satisfies the case sensitivity flag, the accent use sensitivity flag, the character width sensitivity flag, and the kana sensitivity flag of the first collation; optimizing the second query by choosing an index plan that targets an index associated with multiple human languages that is useful in searching across a multiplicity of human language collations; executing the second query to search the first dataset; and returning information satisfying the first query; wherein the first and second datasets each comprise one of a database, a user session and an explicit user query. | 1. A method of searching in a second dataset using a query from a first dataset, the method comprising: receiving a first query using the first dataset, the first query being generated using a first collation associated with the first dataset, the first collation having a case sensitivity flag, an accent use sensitivity flag, a character width sensitivity flag, and a kana sensitivity flag for a first human language; rewriting the first query to form a second query, the second query comprising a second collation and a residue predicate, the second collation comprising a superset of the first collation, the second collation of the second query being broader than the first collation of the first query and being insensitive with respect to at least one of case, accent use, character width, and kana, the second collation encompassing the first collation, the second collation having an associated index for the second collation, and the residue predicate comprising an original search term from the first query, wherein the residue predicate is selected to ensure that a set of results returned in response to the second query satisfies the case sensitivity flag, the accent use sensitivity flag, the character width sensitivity flag, and the kana sensitivity flag of the first collation; optimizing the second query by choosing an index plan that targets an index associated with multiple human languages that is useful in searching across a multiplicity of human language collations; executing the second query to search the first dataset; and returning information satisfying the first query; wherein the first and second datasets each comprise one of a database, a user session and an explicit user query. 5. The method of claim 1 , wherein executing the second query to search the first dataset comprises executing the second query to search for system objects in a system resource database. | 0.913649 |
9,734,205 | 10 | 14 | 10. A non-transitory computer-readable storage device storing computer-readable instructions, comprising: instructions for receiving, by a computer system in a computer network, a user selection of a list of columns, wherein the list of columns is a subset of a finite set of columns; instructions for analyzing, by the computer system, the list of columns to determine cardinality information of the list of columns, wherein the analyzing includes expressing at least the list of columns and the cardinality information of the list of columns as a meta query language; instructions for predicting, by the computer system and based at least in part on a set of queries received at the computer system, a set of the columns to be requested in the future; instructions for determining, by the computer system and based at least in part on the cardinality information and the set of the columns, different subsets of the set of columns using the meta query language; instructions for generating, by the computer system, multiple tables in a storage system, each of the multiple tables having one of the different subsets of the set of columns; instructions for receiving, from an entity in the computer network, a query having a plurality of query parameters; and instructions for selecting, by the computer system and in response to receiving a query, one of the multiple tables to obtain query results from, wherein selecting the one of the multiple tables includes: analyzing the multiple tables to determine a prefix of each of the multiple tables, and selecting a specified table of the multiple tables that has a longest common prefix with query parameters, the longest common prefix being one of the determined prefixes containing a longest sequence of a plurality of leading columns that matches with the query parameters; and instructions for obtaining, in response to the query, the query results from the selected table. | 10. A non-transitory computer-readable storage device storing computer-readable instructions, comprising: instructions for receiving, by a computer system in a computer network, a user selection of a list of columns, wherein the list of columns is a subset of a finite set of columns; instructions for analyzing, by the computer system, the list of columns to determine cardinality information of the list of columns, wherein the analyzing includes expressing at least the list of columns and the cardinality information of the list of columns as a meta query language; instructions for predicting, by the computer system and based at least in part on a set of queries received at the computer system, a set of the columns to be requested in the future; instructions for determining, by the computer system and based at least in part on the cardinality information and the set of the columns, different subsets of the set of columns using the meta query language; instructions for generating, by the computer system, multiple tables in a storage system, each of the multiple tables having one of the different subsets of the set of columns; instructions for receiving, from an entity in the computer network, a query having a plurality of query parameters; and instructions for selecting, by the computer system and in response to receiving a query, one of the multiple tables to obtain query results from, wherein selecting the one of the multiple tables includes: analyzing the multiple tables to determine a prefix of each of the multiple tables, and selecting a specified table of the multiple tables that has a longest common prefix with query parameters, the longest common prefix being one of the determined prefixes containing a longest sequence of a plurality of leading columns that matches with the query parameters; and instructions for obtaining, in response to the query, the query results from the selected table. 14. The non-transitory computer-readable storage device of claim 10 further comprising: instructions for retrieving statistical information from the storage system, the statistical information including information pertaining to management of the tables; instructions for determining, at predefined time intervals, criteria for adapting the tables based on the statistical information; and instructions for adapting, at predefined intervals, the tables, the adapting including at least one of (a) creating one or more new tables, (b) altering one or more existing tables, or (c) deleting one or more existing tables. | 0.50081 |
9,829,984 | 10 | 31 | 10. The method of claim 1 , further comprising: providing the visual gesture to a computer system having a video sensor; and activating one or more computer commands associated with the computer system using the visual gesture. | 10. The method of claim 1 , further comprising: providing the visual gesture to a computer system having a video sensor; and activating one or more computer commands associated with the computer system using the visual gesture. 31. The method of claim 10 , wherein the visual gesture is comprised of a current position of a hand relative to an initial or reference position of the hand. | 0.975016 |
8,301,628 | 3 | 4 | 3. The computer based assessment tool of claim 1 , wherein the status matrix is organized by a sponsoring organization. | 3. The computer based assessment tool of claim 1 , wherein the status matrix is organized by a sponsoring organization. 4. The computer based assessment tool of claim 3 , wherein the status matrix of the sponsoring organizations is broken down into projects. | 0.972132 |
7,730,395 | 24 | 43 | 24. A system for transforming a dynamically changing electronic document comprising: means for providing a visual representation of one or more instances of a dynamically changing electronic document to a user; means for receiving feedback from interaction by said user with said visual representation, said feedback identifying one or more portions of said visual representation, said feedback being used to generate one or more virtual tags, said virtual tags identifying features of said one or more portions of said visual representation; means for constructing one or more transformation rules using said feedback and said one or more virtual tags; and means for applying said one or more transformation rules to said one or more instances of said electronic document, a second electronic document or future versions of said one or more instances of said electronic document to extract customized content identified from said one or more virtual tags and generate a virtual page of said customized content. | 24. A system for transforming a dynamically changing electronic document comprising: means for providing a visual representation of one or more instances of a dynamically changing electronic document to a user; means for receiving feedback from interaction by said user with said visual representation, said feedback identifying one or more portions of said visual representation, said feedback being used to generate one or more virtual tags, said virtual tags identifying features of said one or more portions of said visual representation; means for constructing one or more transformation rules using said feedback and said one or more virtual tags; and means for applying said one or more transformation rules to said one or more instances of said electronic document, a second electronic document or future versions of said one or more instances of said electronic document to extract customized content identified from said one or more virtual tags and generate a virtual page of said customized content. 43. The system of claim 24 wherein said graphical user interface includes a proxy for monitoring actions of said user. | 0.923277 |
9,916,519 | 1 | 15 | 1. A method practiced by a battery-powered mobile wireless communications device equipped with a camera and microphone, the device having multiple recognition modes enabling recognition of multiple types of content, the method comprising the acts: initiating one or more stages of a first recognition agent process to recognize audio or image content data captured by the mobile device, the first recognition agent process performing a recognition selected from a list consisting of: image watermark recognition, image recognition, object recognition, facial recognition, barcode recognition, optical character recognition, audio watermark recognition, speech recognition, speaker recognition, or music recognition; receiving detection state data indicating a state of the first recognition agent process in performing the selected recognition; after initiating the first recognition agent process, receiving first user interest data indicating interest of the user in obtaining a result of the first recognition agent process; and varying an allocation of processing resources to the first recognition agent process based on both said detection state data and on said user interest data; the method thereby optimizing use of the device battery by allocating processing resources in response both to the state of the first recognition agent process in performing the selected recognition, and to user input received after the first recognition agent process has been initiated, indicating user interest in the result of the first recognition agent process. | 1. A method practiced by a battery-powered mobile wireless communications device equipped with a camera and microphone, the device having multiple recognition modes enabling recognition of multiple types of content, the method comprising the acts: initiating one or more stages of a first recognition agent process to recognize audio or image content data captured by the mobile device, the first recognition agent process performing a recognition selected from a list consisting of: image watermark recognition, image recognition, object recognition, facial recognition, barcode recognition, optical character recognition, audio watermark recognition, speech recognition, speaker recognition, or music recognition; receiving detection state data indicating a state of the first recognition agent process in performing the selected recognition; after initiating the first recognition agent process, receiving first user interest data indicating interest of the user in obtaining a result of the first recognition agent process; and varying an allocation of processing resources to the first recognition agent process based on both said detection state data and on said user interest data; the method thereby optimizing use of the device battery by allocating processing resources in response both to the state of the first recognition agent process in performing the selected recognition, and to user input received after the first recognition agent process has been initiated, indicating user interest in the result of the first recognition agent process. 15. The method of claim 1 in which the device includes a touch screen display and the method also includes: initiating a discovery mode, in response to a request received from the user via a device input, in which the discovery mode includes processing camera-captured imagery to recognize an object depicted therein using said first recognition agent process; presenting captured imagery, including video, in a first area of said display of said device, along with augmented reality graphics; controlling a user interface to display user-selectable graphic icons in a second area of said display, wherein the user-selectable graphic icons include visible indicia to graphically represent content; controlling the user interface to present a user-selectable graphic icon on the display to facilitate switching discovery modes from an image discovery mode to an audio discovery mode; and wherein the audio discovery mode includes processing microphone-captured audio to determine identification therefrom, employing an audio recognition agent process. | 0.571078 |
6,076,039 | 2 | 3 | 2. The navigation device as set forth in claim 1, wherein said character string is comprised of characters from a group consisting of special characters, consonants, vowels, and spaces, wherein said processor abbreviates said character string by performing at least one of the following processing steps: when said character string has a special character therein, eliminating a special character; when said character string has at least one space therein, eliminating a space; when said character string has at least one vowel therein, eliminating a vowel; when said character string has a pair of double consonants therein, eliminating one of said consonants of said pair; and when said character string has a pair of double vowels therein, eliminating one of said vowels of said pair. | 2. The navigation device as set forth in claim 1, wherein said character string is comprised of characters from a group consisting of special characters, consonants, vowels, and spaces, wherein said processor abbreviates said character string by performing at least one of the following processing steps: when said character string has a special character therein, eliminating a special character; when said character string has at least one space therein, eliminating a space; when said character string has at least one vowel therein, eliminating a vowel; when said character string has a pair of double consonants therein, eliminating one of said consonants of said pair; and when said character string has a pair of double vowels therein, eliminating one of said vowels of said pair. 3. The navigation device as set forth in claim 2, wherein said processor processes a character string from a right most character thereof, to a left most character thereof. | 0.835878 |
8,256,006 | 1 | 10 | 1. A method of minimizing the risk of theft or disclosure of personally identifiable or sensitive information comprising the steps of: identifying data from a data source in a first stage of a search mechanism performed by a computer, said first stage identifying as potentially sensitive any data from said data source that exhibits any attributes relating to sensitive information; escalating said identified data to at least a second more sensitive stage of said search mechanism, said second stage including the step of scoring said identified data based on minimal information entropy; evaluating any identified data that includes a score beyond a predetermined threshold, said evaluating step utilizing a rule table to determine whether remediation is necessary; and remediating identified data in which remediation is determined to be necessary in said evaluating step; wherein said scoring step includes the step of using an information retrieval tool from the group consisting of Vector Space Models, Latent Semantic Analysis, Latent Dirichlet Allocation and Bayesian Networks to compare attributes of said data to attributes of similar concept data files; wherein said information retrieval tool is Vector Space Models and said step of using Vector Space Models comprises the step of voting by said similar concept data files to determine a classification for said data file; wherein said concept data files include clean data file and target data file classifications; and wherein said voting step further comprises the steps of: determining the N closest concept data files to said data; calculating a value representative of how close each of said N closest concept data files is relative to said data; summing separately values calculated for clean data files and for target data files; and classifying said data as clean or target based upon the relative values of clean data files and target data files obtained in said summing step. | 1. A method of minimizing the risk of theft or disclosure of personally identifiable or sensitive information comprising the steps of: identifying data from a data source in a first stage of a search mechanism performed by a computer, said first stage identifying as potentially sensitive any data from said data source that exhibits any attributes relating to sensitive information; escalating said identified data to at least a second more sensitive stage of said search mechanism, said second stage including the step of scoring said identified data based on minimal information entropy; evaluating any identified data that includes a score beyond a predetermined threshold, said evaluating step utilizing a rule table to determine whether remediation is necessary; and remediating identified data in which remediation is determined to be necessary in said evaluating step; wherein said scoring step includes the step of using an information retrieval tool from the group consisting of Vector Space Models, Latent Semantic Analysis, Latent Dirichlet Allocation and Bayesian Networks to compare attributes of said data to attributes of similar concept data files; wherein said information retrieval tool is Vector Space Models and said step of using Vector Space Models comprises the step of voting by said similar concept data files to determine a classification for said data file; wherein said concept data files include clean data file and target data file classifications; and wherein said voting step further comprises the steps of: determining the N closest concept data files to said data; calculating a value representative of how close each of said N closest concept data files is relative to said data; summing separately values calculated for clean data files and for target data files; and classifying said data as clean or target based upon the relative values of clean data files and target data files obtained in said summing step. 10. The method as claimed in claim 1 wherein said concept data file attributes relate to personally identifiable information. | 0.835526 |
8,793,715 | 1 | 2 | 1. A method comprising: dividing a media instance into a first component and a second component, the first component and second component concurrently presented; correlating first physiological response data from a first subject exposed to media with the first component and the second component to form first correlated data and second correlated data; processing, using a processor, the first correlated data to identify a first transition representative of a first change; processing, using the processor, the second correlated data to identify a second transition representative of a second change; parsing the first component into a first plurality of events based on the first transition; parsing the second component into a second plurality of events based on the second transition; identifying a first event of the first plurality of events as a first candidate for modification based on the first change; and identifying a second event of the second plurality of events as a second candidate for modification based on the second change. | 1. A method comprising: dividing a media instance into a first component and a second component, the first component and second component concurrently presented; correlating first physiological response data from a first subject exposed to media with the first component and the second component to form first correlated data and second correlated data; processing, using a processor, the first correlated data to identify a first transition representative of a first change; processing, using the processor, the second correlated data to identify a second transition representative of a second change; parsing the first component into a first plurality of events based on the first transition; parsing the second component into a second plurality of events based on the second transition; identifying a first event of the first plurality of events as a first candidate for modification based on the first change; and identifying a second event of the second plurality of events as a second candidate for modification based on the second change. 2. The method of claim 1 , wherein the first component and the second component comprise at least one of voiceover, music, branding, dialogue, text, or a visual component, the first component being different from the second component. | 0.891264 |
9,292,589 | 6 | 7 | 6. The database system of claim 5 , wherein normalizing the text-to-topic association score and the total word score comprises: dividing the text-to-topic association score by an inflation factor; and dividing the total word score by the inflation factor. | 6. The database system of claim 5 , wherein normalizing the text-to-topic association score and the total word score comprises: dividing the text-to-topic association score by an inflation factor; and dividing the total word score by the inflation factor. 7. The database system of claim 6 , wherein the inflation factor has a value based on a measure of time. | 0.974129 |
9,288,493 | 1 | 8 | 1. A method of decoding video data in a merge mode, comprising: constructing a merge list using available spatial and temporal merge candidates; setting a merge candidate on the merge list corresponding to a merge index as motion information of a current prediction unit; generating a prediction block of the current prediction unit using the motion information; generating a quantized block by inverse-scanning quantized coefficient components, generating a transformed block by inverse-quantizing the quantized block using a quantization parameter, and generating a residual block by inverse-transforming the transformed block, wherein when the current prediction unit is a second prediction unit partitioned by asymmetric partitioning, a spatial merge candidate corresponding to a first prediction unit partitioned by the asymmetric partitioning is excluded from the merge list, and a motion vector of the temporal merge candidate is determined depending on a position of a current block within a largest coding unit (LCU), wherein the quantization parameter is generated per quantization unit, and a minimum size of the quantization unit is adjusted by a picture parameter set, wherein the quantization parameter is generated using a differential quantization parameter and a quantization parameter predictor, wherein if two or more quantization parameters are available among a left quantization parameter, an above quantization parameter and a previous quantization parameter of a current coding unit, the quantization parameter predictor is generated using two available quantization parameters determined according to a predetermined order, wherein if only one is available among the left quantization parameter, the above quantization parameter and the previous quantization parameter of the current coding unit, the available quantization parameter is set as the quantization parameter predictor, and wherein the differential quantization parameter is restored using a bin string indicating an absolute value of the differential quantization parameter and a bin indicating a sign of the differential quantization parameter. | 1. A method of decoding video data in a merge mode, comprising: constructing a merge list using available spatial and temporal merge candidates; setting a merge candidate on the merge list corresponding to a merge index as motion information of a current prediction unit; generating a prediction block of the current prediction unit using the motion information; generating a quantized block by inverse-scanning quantized coefficient components, generating a transformed block by inverse-quantizing the quantized block using a quantization parameter, and generating a residual block by inverse-transforming the transformed block, wherein when the current prediction unit is a second prediction unit partitioned by asymmetric partitioning, a spatial merge candidate corresponding to a first prediction unit partitioned by the asymmetric partitioning is excluded from the merge list, and a motion vector of the temporal merge candidate is determined depending on a position of a current block within a largest coding unit (LCU), wherein the quantization parameter is generated per quantization unit, and a minimum size of the quantization unit is adjusted by a picture parameter set, wherein the quantization parameter is generated using a differential quantization parameter and a quantization parameter predictor, wherein if two or more quantization parameters are available among a left quantization parameter, an above quantization parameter and a previous quantization parameter of a current coding unit, the quantization parameter predictor is generated using two available quantization parameters determined according to a predetermined order, wherein if only one is available among the left quantization parameter, the above quantization parameter and the previous quantization parameter of the current coding unit, the available quantization parameter is set as the quantization parameter predictor, and wherein the differential quantization parameter is restored using a bin string indicating an absolute value of the differential quantization parameter and a bin indicating a sign of the differential quantization parameter. 8. The method of claim 1 , wherein if the absolute value of the differential quantization parameter is zero, the bin indicating the sign of the differential quantization parameter does not exist. | 0.686495 |
9,916,629 | 6 | 7 | 6. A computer program product comprising: a non-transitory computer readable storage medium; and computer usable code stored on the computer readable storage medium, wherein when the computer usable code is executed by a processor, the computer usable code causes a computer to: identify a set of users associated with at least one collaboration artifact; identify a set of networks including a plurality of candidate social Internet or intranet networks; and determine a relationship strength between the set of users associated with the at least one collaboration artifact, the at least one collaboration artifact comprising at least a work product that enables cooperation between two or more users, and each of the candidate social Internet or intranet networks to identify at least one relevant social Internet or intranet network from the candidate social Internet or intranet networks. | 6. A computer program product comprising: a non-transitory computer readable storage medium; and computer usable code stored on the computer readable storage medium, wherein when the computer usable code is executed by a processor, the computer usable code causes a computer to: identify a set of users associated with at least one collaboration artifact; identify a set of networks including a plurality of candidate social Internet or intranet networks; and determine a relationship strength between the set of users associated with the at least one collaboration artifact, the at least one collaboration artifact comprising at least a work product that enables cooperation between two or more users, and each of the candidate social Internet or intranet networks to identify at least one relevant social Internet or intranet network from the candidate social Internet or intranet networks. 7. The computer program product of claim 6 , wherein the computer usable code, when executed, further causes a computer to calculate a similarity metric between the set of users associated with the at least one collaboration artifact and each of the candidate social Internet or intranet networks to determine the relationship strength. | 0.719064 |
9,069,759 | 6 | 7 | 6. An Internet based translation service provider system for automatically providing translations of text on an administrator's website by an Internet service provider comprising: a. a system server, comprising: i. a database comprising administrators' records comprising translations of an administrator's website character strings from an original language to one or more supported languages; ii. a database comprising a plurality of human translators' records comprising the identity of each translator's native language, wherein (i) and (ii) may be co-located; iii. one or more processors; iv. a non-transitory computer-readable storage device comprising instructions for processor(s), wherein said processors are configured to execute said instructions to perform operations comprising; maintaining a system website for a website administrator to electronically communicate with the processor(s); receiving a request from a website administrator via the system website to translate webpage strings from an original language to one or more supported languages; ordering the translation of the strings via human translation or machine translation in accordance with the administrator's request; storing the translated strings in the administrator's database record, wherein said strings are instantly retrieved and displayed when a user of the administrator's website selects a translation in one of the supported languages; automatically displaying the administrator's website in the user's selected supported language when the user subsequently visits the website; automatically identifying any new un-translated strings on the administrator's website in the original language; electronically transmitting the un-translated strings to an Internet service provider's processor for translation to the user's selected supported language; and, receiving and displaying the translated strings on the administrator's website; b. one of more user electronic computing devices for communicating with the system server to retrieve translated strings in one of the supported languages; c. one or more administrator electronic computing devices for requesting and receiving translation of strings from the system server via the system website; and, d. one or more human translator electronic computing devices for performing translations of the strings; e. one or more machine translation modules for performing automated translation of the strings; and, f. an Internet network for transmitting electronic communications between the electronic computing devices, the machine translation engine, and the server system. | 6. An Internet based translation service provider system for automatically providing translations of text on an administrator's website by an Internet service provider comprising: a. a system server, comprising: i. a database comprising administrators' records comprising translations of an administrator's website character strings from an original language to one or more supported languages; ii. a database comprising a plurality of human translators' records comprising the identity of each translator's native language, wherein (i) and (ii) may be co-located; iii. one or more processors; iv. a non-transitory computer-readable storage device comprising instructions for processor(s), wherein said processors are configured to execute said instructions to perform operations comprising; maintaining a system website for a website administrator to electronically communicate with the processor(s); receiving a request from a website administrator via the system website to translate webpage strings from an original language to one or more supported languages; ordering the translation of the strings via human translation or machine translation in accordance with the administrator's request; storing the translated strings in the administrator's database record, wherein said strings are instantly retrieved and displayed when a user of the administrator's website selects a translation in one of the supported languages; automatically displaying the administrator's website in the user's selected supported language when the user subsequently visits the website; automatically identifying any new un-translated strings on the administrator's website in the original language; electronically transmitting the un-translated strings to an Internet service provider's processor for translation to the user's selected supported language; and, receiving and displaying the translated strings on the administrator's website; b. one of more user electronic computing devices for communicating with the system server to retrieve translated strings in one of the supported languages; c. one or more administrator electronic computing devices for requesting and receiving translation of strings from the system server via the system website; and, d. one or more human translator electronic computing devices for performing translations of the strings; e. one or more machine translation modules for performing automated translation of the strings; and, f. an Internet network for transmitting electronic communications between the electronic computing devices, the machine translation engine, and the server system. 7. The system of claim 6 further comprising storing all translated strings in the administrator's record on the system database. | 0.838791 |
7,720,804 | 1 | 28 | 1. A method of generating and maintaining a data warehouse, the method comprising: providing a predefined reusable metadata model having a data information model including metadata describing models for generating a data warehouse including metadata describing business logic for extracting information from one or more source systems and transforming the information into a data warehouse structure, and an information needs model including metadata regarding information needs for building reports, wherein the information needs model of the data information model comprises metadata defining user roles, metadata defining measures important to the user roles, members of the user roles, and context filters that apply to the members; providing data management services by a data warehouse solution system engine that generates a source framework model which is a semantic layer providing a logical business representation of the one or more source systems, to automatically generate a data warehouse from the one or more source systems using the data information model and the source framework model; providing a modeling user interface for presenting the data information model to a user for allowing the user to manipulate objects of the data warehouse; automatically generating the data warehouse from the one or more source systems using the data information model and the source framework model; and automatically generating reports using the information needs model and the data warehouse based on the metadata defining user roles, metadata defining measures important to the user roles, members of the user roles, and context filters that apply to the members. | 1. A method of generating and maintaining a data warehouse, the method comprising: providing a predefined reusable metadata model having a data information model including metadata describing models for generating a data warehouse including metadata describing business logic for extracting information from one or more source systems and transforming the information into a data warehouse structure, and an information needs model including metadata regarding information needs for building reports, wherein the information needs model of the data information model comprises metadata defining user roles, metadata defining measures important to the user roles, members of the user roles, and context filters that apply to the members; providing data management services by a data warehouse solution system engine that generates a source framework model which is a semantic layer providing a logical business representation of the one or more source systems, to automatically generate a data warehouse from the one or more source systems using the data information model and the source framework model; providing a modeling user interface for presenting the data information model to a user for allowing the user to manipulate objects of the data warehouse; automatically generating the data warehouse from the one or more source systems using the data information model and the source framework model; and automatically generating reports using the information needs model and the data warehouse based on the metadata defining user roles, metadata defining measures important to the user roles, members of the user roles, and context filters that apply to the members. 28. The method of claim 1 , further comprising embedding the generated data warehouse in an application. | 0.914894 |
9,325,508 | 20 | 21 | 20. The method of claim 19 , wherein the name of the signing party is included in an appearance of the digital signature when the digitally signed electronic document is rendered into a visual or aural form. | 20. The method of claim 19 , wherein the name of the signing party is included in an appearance of the digital signature when the digitally signed electronic document is rendered into a visual or aural form. 21. The method of claim 20 , wherein the appearance of the digital signature when the digitally signed electronic document is rendered into the visual or aural form states that the digital signature is certified by the signature authority. | 0.955109 |
9,749,272 | 9 | 16 | 9. A computer system for messaging, the computer system comprising: one or more computer processors; one or more computer readable storage media; program instructions stored therein for execution by at least one of the one or more computer processors, the program instructions comprising instructions to: receive proxy recipient information from a target recipient; detect that a message is being drafted to the target recipient determine whether the target recipient is currently available without receiving a message from the target recipient; and in response to determining that the target recipient is currently unavailable, suggest a proxy recipient for the target recipient to a user. | 9. A computer system for messaging, the computer system comprising: one or more computer processors; one or more computer readable storage media; program instructions stored therein for execution by at least one of the one or more computer processors, the program instructions comprising instructions to: receive proxy recipient information from a target recipient; detect that a message is being drafted to the target recipient determine whether the target recipient is currently available without receiving a message from the target recipient; and in response to determining that the target recipient is currently unavailable, suggest a proxy recipient for the target recipient to a user. 16. The computer system of claim 9 , further comprising instructions to enable the target recipient to preemptively receive the message. | 0.57764 |
9,116,993 | 11 | 16 | 11. A non-transitory computer storage device encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: determining, by a query reissuer, a first estimate of quality of a first set of search results that a search engine identifies as responsive to a user search query received from a user device; classifying, by the query reissuer, the first set of search results that the search engine identifies as responsive to the user search query as unacceptable based at least on the first estimate of quality of the first set of search results; and in response to classifying the first set of search results that the search engine identifies as responsive to the user search query as unacceptable based at least on the first estimate of quality of the first set of search results, transmitting, by the query reissuer, an instruction to a query reviser to generate a modified search query for submission to the search engine. | 11. A non-transitory computer storage device encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: determining, by a query reissuer, a first estimate of quality of a first set of search results that a search engine identifies as responsive to a user search query received from a user device; classifying, by the query reissuer, the first set of search results that the search engine identifies as responsive to the user search query as unacceptable based at least on the first estimate of quality of the first set of search results; and in response to classifying the first set of search results that the search engine identifies as responsive to the user search query as unacceptable based at least on the first estimate of quality of the first set of search results, transmitting, by the query reissuer, an instruction to a query reviser to generate a modified search query for submission to the search engine. 16. The device of claim 11 , wherein the instruction transmitted by the query reissuer to the query reviser to generate a modified search query for submission to the search engine indicates a representation of the first estimate of quality of the first set of search results. | 0.829827 |
9,613,144 | 15 | 16 | 15. The computer system of claim 14 , wherein the computer system is further configured for: (A) receiving one or more search results associated with the Internet search; and (B) transmitting the one or more search results to a client device associated with the user. | 15. The computer system of claim 14 , wherein the computer system is further configured for: (A) receiving one or more search results associated with the Internet search; and (B) transmitting the one or more search results to a client device associated with the user. 16. The computer system of claim 15 , wherein modifying the one or more search terms based at least in part on the gender of the user comprises adding the gender of the user as a search term to the one or more search terms. | 0.924713 |
4,508,447 | 8 | 10 | 8. In an automatic document handling method for recirculating a set of documents sheets seriatim in a page order for copying on a copier imaging system for making precollated copy sheet sets, the improvement for higher speed document circulation for copying at a higher copying rate comprising the steps of: automatically, in a first circulation of the set of documents, separating the set of document sheets into two half-sets of alternate page document sheets and sequentially placing said half-sets respectively in two different document trays; automatically, on the second and subsequent copying circulations of the document set, feeding the document sheets alternately from said two document sheet half-sets in said two document trays, combined in page seriatim order, to be copied at said imaging station at said higher copying rate; and wherein during said second and subsequent, but not the last, copying circulations said document sheets are re-separated into said half-sets after they are copied as they are returned to said two document trays. | 8. In an automatic document handling method for recirculating a set of documents sheets seriatim in a page order for copying on a copier imaging system for making precollated copy sheet sets, the improvement for higher speed document circulation for copying at a higher copying rate comprising the steps of: automatically, in a first circulation of the set of documents, separating the set of document sheets into two half-sets of alternate page document sheets and sequentially placing said half-sets respectively in two different document trays; automatically, on the second and subsequent copying circulations of the document set, feeding the document sheets alternately from said two document sheet half-sets in said two document trays, combined in page seriatim order, to be copied at said imaging station at said higher copying rate; and wherein during said second and subsequent, but not the last, copying circulations said document sheets are re-separated into said half-sets after they are copied as they are returned to said two document trays. 10. The automatic document handling method of claim 8 wherein said separation is such that one said half-set in said one tray comprises even-page simplex document sheets and the other said half-set in the other said tray comprises odd-page simplex document sheets. | 0.827901 |
9,244,536 | 17 | 18 | 17. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a portable electronic device with a display, cause the portable electronic device to perform a method comprising: receiving a plurality of user inputs of characters through the keyboard, and displaying on the display a current character string as input by the user, displaying on the display a suggested replacement character string for the current character string, and receiving a further user input of a single touch, wherein the portable electronic device is configured to receive the further single user input to perform a selected character string function of a plurality of possible character string functions depending on where the further single user input is received, the plurality of possible character string functions comprising, replacing the current character string with the suggested replacement character string in response to a single user input at a first location, replacing the current character string with the suggested replacement character string in combination with a first punctuation mark in response to a single user input at a second location, the second location being a first punctuation mark key on the keyboard corresponding to the first punctuation mark, replacing the current character string with the suggested replacement character string in combination with a second punctuation mark in response to a single user input at a third location, the third location being a second punctuation mark key on the keyboard corresponding to the second punctuation mark, and accepting the current character string in response to a single user input at a fourth location. | 17. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by a portable electronic device with a display, cause the portable electronic device to perform a method comprising: receiving a plurality of user inputs of characters through the keyboard, and displaying on the display a current character string as input by the user, displaying on the display a suggested replacement character string for the current character string, and receiving a further user input of a single touch, wherein the portable electronic device is configured to receive the further single user input to perform a selected character string function of a plurality of possible character string functions depending on where the further single user input is received, the plurality of possible character string functions comprising, replacing the current character string with the suggested replacement character string in response to a single user input at a first location, replacing the current character string with the suggested replacement character string in combination with a first punctuation mark in response to a single user input at a second location, the second location being a first punctuation mark key on the keyboard corresponding to the first punctuation mark, replacing the current character string with the suggested replacement character string in combination with a second punctuation mark in response to a single user input at a third location, the third location being a second punctuation mark key on the keyboard corresponding to the second punctuation mark, and accepting the current character string in response to a single user input at a fourth location. 18. The non-transitory computer readable storage medium of claim 17 , wherein the display is a touch screen display, and wherein the keyboard is a virtual keyboard displayed on the touch screen display. | 0.502463 |
8,266,068 | 21 | 24 | 21. A system for interviewing a candidate, comprising: a processor; and a memory comprising a plurality of instructions executed by the processor, wherein the plurality of instructions are configured to: provide a virtual interview assistant comprising an interview plan, a recording module, an analysis module, and candidate screening criteria, wherein the interview plan comprises one or more interview sessions, wherein the recording module is configured to record at least one recording selected from a group consisting of video recording, audio recording, and physiological parameter recording, wherein the analysis module is configured for analyzing the at least one recording, and wherein the candidate screening criteria comprise an acceptance criterion for each of the one or more interview sessions; obtain a pre-determined qualification score representing a level of a current employee fitting a target requirement, wherein the pre-determined qualification score is assigned to the current employee based on a performance track record of the current employee in a position held by the current employee, and wherein the current employee is identified as a qualified candidate by a recruiter based on the target requirement; interviewing, in a mock interview subsequent to identifying the current employee, the current employee using the virtual interview assistant to generate score qualified candidate profile; adjust the interview plan to generate an adjusted interview plan based on the qualified candidate profile and the pre-determined qualification score; collect a candidate interview response by interviewing the candidate using the virtual interview assistant based on the adjusted interview plan, wherein at least a portion of the candidate interview response is collected using the recording module; analyze the candidate interview response using the analysis module to generate a candidate profile information comprising a score for each of the one or more interview sessions; and selectively present the candidate profile information to the recruiter in response to the candidate profile information meeting the candidate screening criteria, wherein each score in the candidate profile confirms to the acceptance criterion in the candidate screening criteria for a corresponding one of the one or more interview sessions, and wherein the recruiter makes a recruiting decision regarding the candidate based on the candidate profile information. | 21. A system for interviewing a candidate, comprising: a processor; and a memory comprising a plurality of instructions executed by the processor, wherein the plurality of instructions are configured to: provide a virtual interview assistant comprising an interview plan, a recording module, an analysis module, and candidate screening criteria, wherein the interview plan comprises one or more interview sessions, wherein the recording module is configured to record at least one recording selected from a group consisting of video recording, audio recording, and physiological parameter recording, wherein the analysis module is configured for analyzing the at least one recording, and wherein the candidate screening criteria comprise an acceptance criterion for each of the one or more interview sessions; obtain a pre-determined qualification score representing a level of a current employee fitting a target requirement, wherein the pre-determined qualification score is assigned to the current employee based on a performance track record of the current employee in a position held by the current employee, and wherein the current employee is identified as a qualified candidate by a recruiter based on the target requirement; interviewing, in a mock interview subsequent to identifying the current employee, the current employee using the virtual interview assistant to generate score qualified candidate profile; adjust the interview plan to generate an adjusted interview plan based on the qualified candidate profile and the pre-determined qualification score; collect a candidate interview response by interviewing the candidate using the virtual interview assistant based on the adjusted interview plan, wherein at least a portion of the candidate interview response is collected using the recording module; analyze the candidate interview response using the analysis module to generate a candidate profile information comprising a score for each of the one or more interview sessions; and selectively present the candidate profile information to the recruiter in response to the candidate profile information meeting the candidate screening criteria, wherein each score in the candidate profile confirms to the acceptance criterion in the candidate screening criteria for a corresponding one of the one or more interview sessions, and wherein the recruiter makes a recruiting decision regarding the candidate based on the candidate profile information. 24. The system of claim 21 , wherein at least one selected from a group consisting of the interview plan and the candidate screening criteria is selected from a predefined library based on the target requirement. | 0.883131 |
7,529,753 | 34 | 35 | 34. The computer accessible storage hardware of claim 28 , wherein the instructions are operable, at the decoding layer, to decode database messages of database implementations different from each other. | 34. The computer accessible storage hardware of claim 28 , wherein the instructions are operable, at the decoding layer, to decode database messages of database implementations different from each other. 35. The computer accessible storage hardware of claim 34 , wherein the instructions are operable, at the decoding layer, to decode Distributed Relational Database Architecture (DRDA) database messages, Tabular Data Stream (TDS) database messages, and OracleNet database messages. | 0.962348 |
10,114,891 | 1 | 4 | 1. A method comprising: receiving a textual query; retrieving a preliminary audio sample from an auxiliary audio database by matching the textual query with semantic information associated to the auxiliary audio database; performing one of retrieving a target audio sample from a target audio database by matching the preliminary audio sample with the target audio database; and performing an audio-source separation technique on the retrieved target audio sample for separating the retrieved target audio sample into a plurality of audio source signals, wherein retrieving the target audio sample from the target audio database and performing the audio-source separation technique on the retrieved target audio sample are performed jointly, retrieving the target audio sample from the target audio database including comparing the target audio sample with a negative data set; and separating a target source signal of an audio mixture, said target source signal being described by said textual query, by matching the preliminary audio sample with the audio mixture. | 1. A method comprising: receiving a textual query; retrieving a preliminary audio sample from an auxiliary audio database by matching the textual query with semantic information associated to the auxiliary audio database; performing one of retrieving a target audio sample from a target audio database by matching the preliminary audio sample with the target audio database; and performing an audio-source separation technique on the retrieved target audio sample for separating the retrieved target audio sample into a plurality of audio source signals, wherein retrieving the target audio sample from the target audio database and performing the audio-source separation technique on the retrieved target audio sample are performed jointly, retrieving the target audio sample from the target audio database including comparing the target audio sample with a negative data set; and separating a target source signal of an audio mixture, said target source signal being described by said textual query, by matching the preliminary audio sample with the audio mixture. 4. The method of claim 1 , wherein the negative data set is generated from the auxiliary database or a second auxiliary database. | 0.808036 |
9,349,099 | 16 | 20 | 16. A computer-implemented method comprising: accessing social graph information identifying one or more users connected to a particular user on a social graph; identifying preferences of the one or more users; and determining, one or more hardware processors, preferences of the particular user, based on the identified preferences of the one or more users. | 16. A computer-implemented method comprising: accessing social graph information identifying one or more users connected to a particular user on a social graph; identifying preferences of the one or more users; and determining, one or more hardware processors, preferences of the particular user, based on the identified preferences of the one or more users. 20. The method of claim 16 , wherein the determined preferences of the particular user are used to target advertising to the particular user. | 0.785714 |
8,515,749 | 1 | 4 | 1. A computer-implemented method for speech-based communication comprising: accepting, via an audio input device, data representing a first audio signal; recognizing, using a speech to text module of the computer, speech represented in the first audio signal to form a first text representation of the speech, the speech spoken by a first user in a first language; processing, using a speech processing module, the first text representation to form data representing a second audio signal which represents a second text representation of the speech, the second text representation comprising a transformation of the first text representation; soliciting, via a user interface of the computer, verification from the first user including audibly presenting the first text representation to the first user concurrently with processing the first text representation to form the data representing the second audio signal; and causing presentation of the second audio signal via an audio output device to a second user while responsive to an interrupt signal from the first user received during the presentation of the second audio signal. | 1. A computer-implemented method for speech-based communication comprising: accepting, via an audio input device, data representing a first audio signal; recognizing, using a speech to text module of the computer, speech represented in the first audio signal to form a first text representation of the speech, the speech spoken by a first user in a first language; processing, using a speech processing module, the first text representation to form data representing a second audio signal which represents a second text representation of the speech, the second text representation comprising a transformation of the first text representation; soliciting, via a user interface of the computer, verification from the first user including audibly presenting the first text representation to the first user concurrently with processing the first text representation to form the data representing the second audio signal; and causing presentation of the second audio signal via an audio output device to a second user while responsive to an interrupt signal from the first user received during the presentation of the second audio signal. 4. The computer-implemented method of claim 1 , further comprising accepting an interrupt signal from the first user and interrupting the presentation of the second audio signal. | 0.776942 |
8,521,664 | 2 | 4 | 2. The system of claim 1 , the operations further comprising: determining an output type for predictive output for the client-subscriber computing system comprising: determining from the information that describes each of the trained predictive models that one or more models included in the predictive model repository are compatible with one or more input types determined from the request to input types and that the one or more models can generate output of one or more output types, and selecting the output type from the one or more output types. | 2. The system of claim 1 , the operations further comprising: determining an output type for predictive output for the client-subscriber computing system comprising: determining from the information that describes each of the trained predictive models that one or more models included in the predictive model repository are compatible with one or more input types determined from the request to input types and that the one or more models can generate output of one or more output types, and selecting the output type from the one or more output types. 4. The system of claim 2 , wherein selecting the output type from the one or more output types comprises selecting the output type that is associated with a model from the one or more models that is best matched to the request. | 0.903568 |
9,575,951 | 8 | 9 | 8. The method of claim 7 , further comprising character generation and modeling of a personal assistant in virtual reality based on said semantic network, said personal assistant being configured to accept text or spoken commands for user interaction in aiding search queries of a user. | 8. The method of claim 7 , further comprising character generation and modeling of a personal assistant in virtual reality based on said semantic network, said personal assistant being configured to accept text or spoken commands for user interaction in aiding search queries of a user. 9. The method of claim 8 , wherein said text or spoken commands are transmitted to said top/down, bottom/up parser from said virtual reality system over a network. | 0.975076 |
8,832,197 | 7 | 8 | 7. The method of claim 1 , wherein the user device is a mobile device, and wherein the collaborative discussion is created at a collaboration application running on the mobile device. | 7. The method of claim 1 , wherein the user device is a mobile device, and wherein the collaborative discussion is created at a collaboration application running on the mobile device. 8. The method of claim 7 , wherein posting the created collaborative discussion includes transmitting the created collaborative discussion, over a network, to the plurality of users by way of respective other mobile devices, the created collaborative discussion accessible by a respective collaboration application running on each of the other mobile devices. | 0.844723 |
7,873,898 | 4 | 5 | 4. The method of claim 1 , wherein deriving the error messages from the input error message comprises: locating the error patterns representative of the input error message; and, deriving the error sub-patterns from the error patterns, each error sub-pattern being one of the error messages. | 4. The method of claim 1 , wherein deriving the error messages from the input error message comprises: locating the error patterns representative of the input error message; and, deriving the error sub-patterns from the error patterns, each error sub-pattern being one of the error messages. 5. The method of claim 4 , wherein deriving the error sub-patterns from the error patterns comprises constructing different combinations of sub-parts of the error patterns. | 0.914 |
7,533,172 | 15 | 16 | 15. The peer-to-peer network system as recited in claim 1 , wherein one or more of said service or content advertisements comprises a time-to-live indicator, wherein the corresponding advertisement is deleted or invalidated when the time-to-live indicator expires. | 15. The peer-to-peer network system as recited in claim 1 , wherein one or more of said service or content advertisements comprises a time-to-live indicator, wherein the corresponding advertisement is deleted or invalidated when the time-to-live indicator expires. 16. The peer-to-peer network system as recited in claim 15 , wherein said time-to-live indicator is decremented to reflect a current time-to-live when the corresponding advertisement is provided to another peer. | 0.943643 |
8,200,009 | 8 | 14 | 8. A computer implemented document processing system for processing a document comprising: a user-input function for receiving a user input sample document and storing the sample document in a data storage wherein the sample document having sample document attributes including a computer file type or file format and sample structural characteristics wherein said document processing system processing said document to generate an output document with the same computer file type or file format as said user input sample document. | 8. A computer implemented document processing system for processing a document comprising: a user-input function for receiving a user input sample document and storing the sample document in a data storage wherein the sample document having sample document attributes including a computer file type or file format and sample structural characteristics wherein said document processing system processing said document to generate an output document with the same computer file type or file format as said user input sample document. 14. The document processing system of claim 8 wherein: said document processing system referring to the user input sample document with a textual editable computer file type or file format and said document process system processing said document for generating an output file with the textual editable computer file type or format same as the input sample document. | 0.72969 |
6,041,293 | 7 | 10 | 7. A document processing method comprising: a first word extracting step for extracting a first word from document data; a preceding/subsequent word extracting step for extracting, from the document data, a second word that is one of a preceding word and a subsequent word of the first word; a keyword extracting step for extracting a keyword of the document data, based on a frequency of occurrence of the first word, wherein said keyword extracting step includes a word counting step of counting a number of occurrences of each word, other than unnecessary words which are pre-excluded from being keywords, in the document data, said keyword extracting step extracting a word having a high number of occurrences, counted by said word counting step, as the keyword; and a translation step for translating the keyword into a predetermined language by referring to a dictionary in a process that considers a meaning of the first and second words existing together in the document data. | 7. A document processing method comprising: a first word extracting step for extracting a first word from document data; a preceding/subsequent word extracting step for extracting, from the document data, a second word that is one of a preceding word and a subsequent word of the first word; a keyword extracting step for extracting a keyword of the document data, based on a frequency of occurrence of the first word, wherein said keyword extracting step includes a word counting step of counting a number of occurrences of each word, other than unnecessary words which are pre-excluded from being keywords, in the document data, said keyword extracting step extracting a word having a high number of occurrences, counted by said word counting step, as the keyword; and a translation step for translating the keyword into a predetermined language by referring to a dictionary in a process that considers a meaning of the first and second words existing together in the document data. 10. A document processing method according to claim 7, further comprising a step for displaying or outputting a result of translation by said translating step. | 0.877125 |
9,548,987 | 7 | 9 | 7. The apparatus of claim 4 wherein the classifier utilizes metadata associated with previous events stored in the first and second storage locations of the data store as a learning set in a machining learning algorithm in generating the risk scores for the one or more new events. | 7. The apparatus of claim 4 wherein the classifier utilizes metadata associated with previous events stored in the first and second storage locations of the data store as a learning set in a machining learning algorithm in generating the risk scores for the one or more new events. 9. The apparatus of claim 7 wherein the machine learning algorithm comprises a support vector machine algorithm. | 0.982154 |
10,146,861 | 3 | 5 | 3. The method of claim 1 , further including presenting the requested reports by a 2-dimensional visualization. | 3. The method of claim 1 , further including presenting the requested reports by a 2-dimensional visualization. 5. The method of claim 3 where the visualization is a 2-dimensional heatmap that uses a color scheme that conveys importance of each cell of the 2-dimensional visualization. | 0.955228 |
8,438,004 | 1 | 6 | 1. A method of language translation imaging comprising: receiving an image job; distinguishing variable data that is current language text from any other variable data and fixed data within the image job, wherein the distinguishing includes recognizing data tags inserted into the image job prior to the receiving, the data tags identifying the variable data that is current language text; translating the current language text into new language text; modifying the variable data that is current language text to new variable data that is new language text; and printing an image from the image job, wherein the image job comprises the new language text. | 1. A method of language translation imaging comprising: receiving an image job; distinguishing variable data that is current language text from any other variable data and fixed data within the image job, wherein the distinguishing includes recognizing data tags inserted into the image job prior to the receiving, the data tags identifying the variable data that is current language text; translating the current language text into new language text; modifying the variable data that is current language text to new variable data that is new language text; and printing an image from the image job, wherein the image job comprises the new language text. 6. A non-transitory computer-readable medium storing computer executable instructions configured to cause a computer to perform the method of claim 1 . | 0.711832 |
9,009,027 | 1 | 7 | 1. A computer-program product tangibly embodied in a non-transitory, computer-readable storage medium that stores instructions, the instructions executable by a data processing apparatus for performing operations including: accessing a mood evaluation index that maps text to mood categories, wherein text describes a state associated with at least one of the mood categories, and wherein a mood category is associated with a state; mapping text to a mood category using the mood evaluation index, wherein the mood evaluation index associates a state with the text; calculating a mood weight for the text, wherein mood weights are calculated using a mood evaluation index, and wherein mood weights represent an intensity of the state that the text describes; accessing a message, wherein the message includes text mapped by the mood evaluation index; using the mood evaluation index to identify text included in the message that is mapped to a mood category; determining whether a modifier is in proximity to identified text; adjusting the mood weight of the identified text that is in proximity to the modifier; summing the mood weights of the identified text, wherein summing includes determining a category score corresponding to the mood category; and outputting the category score corresponding to the mood category. | 1. A computer-program product tangibly embodied in a non-transitory, computer-readable storage medium that stores instructions, the instructions executable by a data processing apparatus for performing operations including: accessing a mood evaluation index that maps text to mood categories, wherein text describes a state associated with at least one of the mood categories, and wherein a mood category is associated with a state; mapping text to a mood category using the mood evaluation index, wherein the mood evaluation index associates a state with the text; calculating a mood weight for the text, wherein mood weights are calculated using a mood evaluation index, and wherein mood weights represent an intensity of the state that the text describes; accessing a message, wherein the message includes text mapped by the mood evaluation index; using the mood evaluation index to identify text included in the message that is mapped to a mood category; determining whether a modifier is in proximity to identified text; adjusting the mood weight of the identified text that is in proximity to the modifier; summing the mood weights of the identified text, wherein summing includes determining a category score corresponding to the mood category; and outputting the category score corresponding to the mood category. 7. The computer-program product of claim 1 , wherein multiple words are mapped to a same mood category within the mood evaluation index. | 0.701754 |
9,754,589 | 1 | 4 | 1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: receive text corresponding to at least a portion of a user input; generate a first natural language understanding (“NLU”) result using the text and a first NLU module, wherein the first NLU module is associated with a first subject matter, and wherein the first NLU result is associated with a first score indicative of a confidence in the first NLU result; generate a second NLU result using the text and a second NLU module, wherein the second NLU module is associated with a second subject matter, and wherein the second NLU result is associated with a second score indicative of a confidence in the second NLU result; select the first NLU result based at least partly on the first score and the second score; and generate a response based at least partly on the first NLU result. | 1. A system comprising: a computer-readable memory storing executable instructions; and one or more processors in communication with the computer-readable memory, wherein the one or more processors are programmed by the executable instructions to at least: receive text corresponding to at least a portion of a user input; generate a first natural language understanding (“NLU”) result using the text and a first NLU module, wherein the first NLU module is associated with a first subject matter, and wherein the first NLU result is associated with a first score indicative of a confidence in the first NLU result; generate a second NLU result using the text and a second NLU module, wherein the second NLU module is associated with a second subject matter, and wherein the second NLU result is associated with a second score indicative of a confidence in the second NLU result; select the first NLU result based at least partly on the first score and the second score; and generate a response based at least partly on the first NLU result. 4. The system of claim 1 , wherein the executable instructions that program the one or more processors to generate the first NLU result using the text and the first NLU module comprise instructions to: identify a plurality of tokens in the text; label a first token of the plurality of tokens as a first named entity; label a second token of the plurality of tokens as a second named entity; and identify an intent that corresponds to the first named entity and the second named entity, wherein the intent is associated with the first subject matter. | 0.527491 |
8,595,370 | 20 | 29 | 20. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause: receiving, from a process associated with a particular webpage, a request to display a clickable item on said particular webpage; providing, to said process, said clickable item to be displayed on said particular webpage; after providing said clickable item to said process, receiving an indication that the clickable item has been selected; and in response to said indication, providing a new page to be displayed that contains at least one of (a) URLs corresponding to a subset of linking webpages that each contains a link to said particular webpage, wherein the linking webpages are determined to contain a link to said particular webpage by an automated web crawler or (b) a subset of tags that have been associated with said particular webpage by a plurality of users who have visited said particular webpage, wherein each tag is one or more words and is created, by a user of the plurality of users who has visited said particular webpage to describe content of said particular webpage subsequent to the creation of said particular webpage. | 20. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause: receiving, from a process associated with a particular webpage, a request to display a clickable item on said particular webpage; providing, to said process, said clickable item to be displayed on said particular webpage; after providing said clickable item to said process, receiving an indication that the clickable item has been selected; and in response to said indication, providing a new page to be displayed that contains at least one of (a) URLs corresponding to a subset of linking webpages that each contains a link to said particular webpage, wherein the linking webpages are determined to contain a link to said particular webpage by an automated web crawler or (b) a subset of tags that have been associated with said particular webpage by a plurality of users who have visited said particular webpage, wherein each tag is one or more words and is created, by a user of the plurality of users who has visited said particular webpage to describe content of said particular webpage subsequent to the creation of said particular webpage. 29. The one or more non-transitory machine-readable media of claim 20 , wherein: the new page contains the URLs corresponding to the subset of linking webpages; and each linking webpage of said subset is from a different domain. | 0.86604 |
10,162,652 | 1 | 4 | 1. A game apparatus in which a scenario proceeds in such a way that a player character is moved on a field produced in a three-dimensional virtual space in a memory through a controller so as to search and obtain items located on the field, comprising: a sentence item control table stored in the memory of the game apparatus, said sentence item control table storing a first set of information associated with a plurality of sentence items, the first set of information comprising: a kind of language set for each sentence item, a display position on the field for each sentence item, and game information text for each sentence item; an item disclosure object table stored in the memory of the game apparatus, said item disclosure object table storing a second set of information associated with a plurality of item disclosure objections, the second set of information comprising: a disclosure item associated with each item disclosure object, a kind of language and a language level set for each item disclosure object, and a display position on the field for each item disclosure object located on the field; a language skill table (TB 2 ) stored in the memory of the game apparatus, the language skill table storing a language skill level of the player character for each kind of language identified in the sentence item control table and the item disclosure object table; and at least one processor, coupled to the memory and configured to: access the sentence item control table and the item disclosure object table, and further configured to control a language skill level of the player character for each kind of language identified in the sentence item control table and the item disclosure object table; locate two or more sentence items at predetermined positions on the field based on the display position on the field of each sentence item stored in the sentence item control table; locate two or more item disclosure objects on the field; wherein a kind of language and game information text are set for each of the two or more sentence items; wherein a disclosure item, the kind of language and a language level are set for each of the two or more item disclosure objects; in response to one or more instructions from a player through the controller cause the player character to access a sentence item located on the field and to read the game information text of the sentence item by referring to the sentence item control table; wherein whenever the player character reads the game information text of the sentence item, execute a process of improving the language skill so as to store an updated skill level of the player character in the language skill table for the kind of language set for the sentence item accessed by the player character and stored in the sentence item control table; judge the kind of language and the language level associated with the item disclosure object accessed by the player character by referring to the item disclosure object table and referring to the skill level of the player character for the kind of language associated with the item disclosure object requested to be accessed by referring to the language skill table, and comparing the skill level and the language level set for the accessed item disclosure object, only when the skill level of the player character is the same as the language level set on the item disclosure object or higher, grant access to the item disclosure object requested to be accessed; and execute a process of developing and displaying the disclosure item associated with the item disclosure object on the field by referring to the item disclosure object table when the execution of the process of accessing the item disclosure object is enabled by the at least one processor. | 1. A game apparatus in which a scenario proceeds in such a way that a player character is moved on a field produced in a three-dimensional virtual space in a memory through a controller so as to search and obtain items located on the field, comprising: a sentence item control table stored in the memory of the game apparatus, said sentence item control table storing a first set of information associated with a plurality of sentence items, the first set of information comprising: a kind of language set for each sentence item, a display position on the field for each sentence item, and game information text for each sentence item; an item disclosure object table stored in the memory of the game apparatus, said item disclosure object table storing a second set of information associated with a plurality of item disclosure objections, the second set of information comprising: a disclosure item associated with each item disclosure object, a kind of language and a language level set for each item disclosure object, and a display position on the field for each item disclosure object located on the field; a language skill table (TB 2 ) stored in the memory of the game apparatus, the language skill table storing a language skill level of the player character for each kind of language identified in the sentence item control table and the item disclosure object table; and at least one processor, coupled to the memory and configured to: access the sentence item control table and the item disclosure object table, and further configured to control a language skill level of the player character for each kind of language identified in the sentence item control table and the item disclosure object table; locate two or more sentence items at predetermined positions on the field based on the display position on the field of each sentence item stored in the sentence item control table; locate two or more item disclosure objects on the field; wherein a kind of language and game information text are set for each of the two or more sentence items; wherein a disclosure item, the kind of language and a language level are set for each of the two or more item disclosure objects; in response to one or more instructions from a player through the controller cause the player character to access a sentence item located on the field and to read the game information text of the sentence item by referring to the sentence item control table; wherein whenever the player character reads the game information text of the sentence item, execute a process of improving the language skill so as to store an updated skill level of the player character in the language skill table for the kind of language set for the sentence item accessed by the player character and stored in the sentence item control table; judge the kind of language and the language level associated with the item disclosure object accessed by the player character by referring to the item disclosure object table and referring to the skill level of the player character for the kind of language associated with the item disclosure object requested to be accessed by referring to the language skill table, and comparing the skill level and the language level set for the accessed item disclosure object, only when the skill level of the player character is the same as the language level set on the item disclosure object or higher, grant access to the item disclosure object requested to be accessed; and execute a process of developing and displaying the disclosure item associated with the item disclosure object on the field by referring to the item disclosure object table when the execution of the process of accessing the item disclosure object is enabled by the at least one processor. 4. The game apparatus according to claim 1 , wherein the at least one processor further monitors a distance between the player character and the sentence item on the field, and executes a process of allowing the player character to read the game information text of sentence item when the player character is within a predetermined distance of the sentence item on the field. | 0.547101 |
7,493,327 | 13 | 40 | 13. A computer-readable storage media embodying a schema comprising: multiple nodes arranged in a hierarchical structure, wherein the hierarchical structure describes a printer's properties and capabilities; wherein individual nodes are associated with printer properties or data values; and wherein the schema is protocol-independent allowing one or more standardized schema queries to be constructed by one or more devices to query the printer for information associated with its properties and capabilities, wherein each of the one or more schema queries is defined by the schema, at least one schema query being directed to discovering a particular data value by having syntax expressly identifying a data value node associated with the particular data value, and wherein one property node comprises at least one of: a printer information node that pertains to data that is associated with the printer, wherein the printer information node comprises a child manufacturer node associated with a printer manufacturer; a configuration node that pertains to configuration data that is associated with the printer, and wherein the configuration node comprises at least one of: a child memory node that contains values associated with the memory installed on the printer, and wherein the memory node comprises a child node associated with memory size and a child node associated with an amount of memory available to a Postscript interpreter; or a child hard disk node that contains values associated with a hard disk that is installed on the printer, and wherein the hard disk node comprises a child node that represents whether a hard disk is installed on the printer, a child node that represents the capacity of an installed hard disk, and a child node that represents currently available free space of an installed hard disk; a consumables node that pertains to information associated with consumable supplies in the printer, and wherein the consumables node comprises a child type node that corresponds to a consumable type on the printer, wherein the child type node comprises a child color node that corresponds to the color of a consumable, wherein the color node comprises a child installed node that represents whether a consumable is installed on the printer, a child display name node that represents a localized name for a particular consumable, and a child level node that represents a current level of a referenced consumable; or a layout node that pertains to data associated with how a print job is applied on a page, wherein the layout node comprises a child number up node that contains information associated with how many logical pages should be placed on a single page of media and which direction to layout multiple pages. | 13. A computer-readable storage media embodying a schema comprising: multiple nodes arranged in a hierarchical structure, wherein the hierarchical structure describes a printer's properties and capabilities; wherein individual nodes are associated with printer properties or data values; and wherein the schema is protocol-independent allowing one or more standardized schema queries to be constructed by one or more devices to query the printer for information associated with its properties and capabilities, wherein each of the one or more schema queries is defined by the schema, at least one schema query being directed to discovering a particular data value by having syntax expressly identifying a data value node associated with the particular data value, and wherein one property node comprises at least one of: a printer information node that pertains to data that is associated with the printer, wherein the printer information node comprises a child manufacturer node associated with a printer manufacturer; a configuration node that pertains to configuration data that is associated with the printer, and wherein the configuration node comprises at least one of: a child memory node that contains values associated with the memory installed on the printer, and wherein the memory node comprises a child node associated with memory size and a child node associated with an amount of memory available to a Postscript interpreter; or a child hard disk node that contains values associated with a hard disk that is installed on the printer, and wherein the hard disk node comprises a child node that represents whether a hard disk is installed on the printer, a child node that represents the capacity of an installed hard disk, and a child node that represents currently available free space of an installed hard disk; a consumables node that pertains to information associated with consumable supplies in the printer, and wherein the consumables node comprises a child type node that corresponds to a consumable type on the printer, wherein the child type node comprises a child color node that corresponds to the color of a consumable, wherein the color node comprises a child installed node that represents whether a consumable is installed on the printer, a child display name node that represents a localized name for a particular consumable, and a child level node that represents a current level of a referenced consumable; or a layout node that pertains to data associated with how a print job is applied on a page, wherein the layout node comprises a child number up node that contains information associated with how many logical pages should be placed on a single page of media and which direction to layout multiple pages. 40. The computer-readable storage media of claim 13 , wherein one property node comprises a finishing node that pertains to how a print job is composed upon completion, wherein the finishing node comprises a child output bins node that contains information that describes a printer's output bins, wherein the child output bins node comprises a child current value node that represents a current default output bin, and a child tray name bin associated with the name of an output bin. | 0.777214 |
9,037,606 | 8 | 12 | 8. A computer-implemented method comprising: clustering hierarchical database records into a first set of clusters having corresponding first cluster identifications (IDs), each hierarchical database record comprising one or more field values, the clustering based at least in part on determining similarity among corresponding field values of the hierarchical database records; determining highest compelling linkages among the hierarchical database records, the determining comprising: identifying mutually preferred pairs of records from the hierarchical database records, each mutually preferred pair of records consisting of a first record and a second record, the first record consisting of a preferred record associated with the second record and the second record consisting of a preferred record associated with the first record, wherein the mutually preferred pairs of records each has a match score that meets pre-specified match criteria; assigning, for each record from the database records, at least one associated preferred record, wherein a match value assigned to a given record together with its associated preferred record is at least as great as a match value assigned to the record together with any other record in the hierarchical database records; and forming and storing a plurality of entity representations in the database, each entity representation of the plurality of entity representations comprising at least one linked pair of mutually preferred records; receiving parent-child hierarchical relationship information for the hierarchical database records; re-clustering at least a portion of the hierarchical database records into a second set of clusters having corresponding second cluster IDs, the re-clustering based at least in part on the received parent-child hierarchical relationship information; and outputting hierarchical database record information, based at least in part on the re-clustering. | 8. A computer-implemented method comprising: clustering hierarchical database records into a first set of clusters having corresponding first cluster identifications (IDs), each hierarchical database record comprising one or more field values, the clustering based at least in part on determining similarity among corresponding field values of the hierarchical database records; determining highest compelling linkages among the hierarchical database records, the determining comprising: identifying mutually preferred pairs of records from the hierarchical database records, each mutually preferred pair of records consisting of a first record and a second record, the first record consisting of a preferred record associated with the second record and the second record consisting of a preferred record associated with the first record, wherein the mutually preferred pairs of records each has a match score that meets pre-specified match criteria; assigning, for each record from the database records, at least one associated preferred record, wherein a match value assigned to a given record together with its associated preferred record is at least as great as a match value assigned to the record together with any other record in the hierarchical database records; and forming and storing a plurality of entity representations in the database, each entity representation of the plurality of entity representations comprising at least one linked pair of mutually preferred records; receiving parent-child hierarchical relationship information for the hierarchical database records; re-clustering at least a portion of the hierarchical database records into a second set of clusters having corresponding second cluster IDs, the re-clustering based at least in part on the received parent-child hierarchical relationship information; and outputting hierarchical database record information, based at least in part on the re-clustering. 12. The method of claim 8 , wherein each hierarchical database record corresponds to an entity representation, each database record comprising a plurality of fields, each field configured to contain a field value, and each field value assigned a field value weight corresponding to a specificity of the field value in relation to all field values in a corresponding field of the records. | 0.916774 |
8,209,241 | 1 | 10 | 1. A method of illustrating locations of available tickets in an event venue, comprising: presenting, by a web browser of a client computing device, a filter module for allowing a user to perform a search of tickets listed for sale by a ticket service hosted by a web site; accepting, at the filter module, event criteria for at least one ticket and at least one event; accepting, at the filter module, price criteria for the at least one ticket and the at least one event; sending the request for filtering tickets by criteria to the ticket service; receiving, from the ticket service, data representing a filtered ticket set meeting the event criteria and the price criteria from the ticket service; displaying a ticket listing corresponding to tickets of the filtered ticket set located in a plurality of sections of an event venue; displaying, by the web browser, an interactive graphics-based event venue map for the event venue illustrating locations of sections having tickets of the filtered ticket set; accepting, at the interactive graphics-based event venue map, a particular section of interest in response to the user selecting the particular section from the interactive graphics-based event venue map; accepting, at the interactive graphics-based event venue map, a particular section of interest; and displaying ticket information in a web browsing language corresponding to the tickets of the filtered ticket set located in the particular section of interest as an overlay on the particular section of interest on the interactive graphics-based event venue map. | 1. A method of illustrating locations of available tickets in an event venue, comprising: presenting, by a web browser of a client computing device, a filter module for allowing a user to perform a search of tickets listed for sale by a ticket service hosted by a web site; accepting, at the filter module, event criteria for at least one ticket and at least one event; accepting, at the filter module, price criteria for the at least one ticket and the at least one event; sending the request for filtering tickets by criteria to the ticket service; receiving, from the ticket service, data representing a filtered ticket set meeting the event criteria and the price criteria from the ticket service; displaying a ticket listing corresponding to tickets of the filtered ticket set located in a plurality of sections of an event venue; displaying, by the web browser, an interactive graphics-based event venue map for the event venue illustrating locations of sections having tickets of the filtered ticket set; accepting, at the interactive graphics-based event venue map, a particular section of interest in response to the user selecting the particular section from the interactive graphics-based event venue map; accepting, at the interactive graphics-based event venue map, a particular section of interest; and displaying ticket information in a web browsing language corresponding to the tickets of the filtered ticket set located in the particular section of interest as an overlay on the particular section of interest on the interactive graphics-based event venue map. 10. The method of claim 1 , wherein: the interactive graphics-based event venue map is a FLASH-based event venue map; and the web browsing language is HTML. | 0.847953 |
8,099,407 | 18 | 19 | 18. A computer-readable storage medium containing computer executable program code, comprising: program code for monitoring at least one application for the occurrences of events wherein at least one event is associated with a media file; program code for capturing the at least one event upon the occurrence of the event by queuing event data associated with the event at a position in a queue; program code for indexing and storing at least some of the events and the media file associated with the event at a time after the occurrence of the event, wherein the time is based on performance data indicating a readiness to process the event and a position in the queue; program code for receiving a search query; program code for locating at least one relevant media file from the indexed and stored events relevant to the search query; and program code for outputting a result set comprising the at least one relevant media file. | 18. A computer-readable storage medium containing computer executable program code, comprising: program code for monitoring at least one application for the occurrences of events wherein at least one event is associated with a media file; program code for capturing the at least one event upon the occurrence of the event by queuing event data associated with the event at a position in a queue; program code for indexing and storing at least some of the events and the media file associated with the event at a time after the occurrence of the event, wherein the time is based on performance data indicating a readiness to process the event and a position in the queue; program code for receiving a search query; program code for locating at least one relevant media file from the indexed and stored events relevant to the search query; and program code for outputting a result set comprising the at least one relevant media file. 19. The computer-readable medium of claim 18 , wherein the search query is an explicit query. | 0.841297 |
8,538,081 | 17 | 18 | 17. A processor-based system for classifying an object in an image, the system comprising: one or more processors; and a non-transitory computer-readable medium or media comprising one or more sequences of instructions which, when executed by the one or more processors, causes steps to be performed comprising: for each local window of a set of local windows from the image: [a] computing a set of image features; [b] applying one or more pre-trained classifiers to the set of image features to obtain a set of classifier response values; [c] generating a classification context for the local window using the set of classifier response values of the local window and the sets of classifier response values of local windows that are within a neighborhood of the local window; and [d] constructing an augmented feature set comprising the classification context and the set of image features for the local window; [e] applying a pre-trained contextual boost classifier to the augmented feature set to obtain a set of contextual boost classifier response values; [f] responsive to a stop condition not being reached: adjusting the classification context for the local window using the set of contextual boost classifier response values; adjusting the augmented feature set for the local window using the classification context and a prior augmented feature set for the local window; and returning to [e]. | 17. A processor-based system for classifying an object in an image, the system comprising: one or more processors; and a non-transitory computer-readable medium or media comprising one or more sequences of instructions which, when executed by the one or more processors, causes steps to be performed comprising: for each local window of a set of local windows from the image: [a] computing a set of image features; [b] applying one or more pre-trained classifiers to the set of image features to obtain a set of classifier response values; [c] generating a classification context for the local window using the set of classifier response values of the local window and the sets of classifier response values of local windows that are within a neighborhood of the local window; and [d] constructing an augmented feature set comprising the classification context and the set of image features for the local window; [e] applying a pre-trained contextual boost classifier to the augmented feature set to obtain a set of contextual boost classifier response values; [f] responsive to a stop condition not being reached: adjusting the classification context for the local window using the set of contextual boost classifier response values; adjusting the augmented feature set for the local window using the classification context and a prior augmented feature set for the local window; and returning to [e]. 18. The processor-based system for classifying an object in an image of claim 17 wherein the step of computing a set of image features comprises: generating a context region for the local window comprising at least a portion of the image and formed by selecting a portion or portions of the image that are within a context region area defined relative to the local window; computing a local difference pattern feature by performing the steps comprising: partitioning the context region and the local window into blocks; calculating a brightness value for a reference block; calculating a brightness value for at least some of the blocks; computing a difference value between the brightness of the reference block and the brightness of at least some of the blocks; and forming the difference values into the local difference pattern feature; and constructing a multi-scale feature comprising: a high-scale feature comprising one or more features extracted from the local window at a high-resolution size; a mid-scale feature comprising a combination of one or more features extracted from the local window at a mid-resolution and one or more features extracted from a set of one or more regions at the mid-resolution, the set of one or more regions being formed from the context region; and a low-scale feature comprising one or more features extracted from a combined local window at a low-resolution size, the combined local window comprising the local window and the context region for the local window. | 0.500332 |
9,946,725 | 1 | 2 | 1. A method of collaborative document editing, the method comprising: receiving, at a server from a client system, a first request to access a document stored at the server; providing, by the server, to the client system, an application in a browser of the client system, wherein the application is enabled to modify the document; providing, by the server, to the client system, a first portion of the document in the application; receiving, by the server, a second request to access the document; determining, by the server, whether a user that is associated with the second request is authorized to access the document; in response to determining that the user is authorized to access the document, transmitting, by the server, a second portion of the document; receiving an edit to at least one of the first portion of the document or the second portion of the document; and saving, by the server, the edit to the at least one of the first portion of the document or the second portion of the document. | 1. A method of collaborative document editing, the method comprising: receiving, at a server from a client system, a first request to access a document stored at the server; providing, by the server, to the client system, an application in a browser of the client system, wherein the application is enabled to modify the document; providing, by the server, to the client system, a first portion of the document in the application; receiving, by the server, a second request to access the document; determining, by the server, whether a user that is associated with the second request is authorized to access the document; in response to determining that the user is authorized to access the document, transmitting, by the server, a second portion of the document; receiving an edit to at least one of the first portion of the document or the second portion of the document; and saving, by the server, the edit to the at least one of the first portion of the document or the second portion of the document. 2. The method of claim 1 , wherein the application is distributed over the server and the client system. | 0.734694 |
7,921,100 | 1 | 3 | 1. A method for calculating a similarity score of a query set comprising a query set of tokens and a first database set comprising a first database set of tokens, wherein the first database set is one of a plurality of database sets in a data collection set stored on a non-transitory computer readable medium, comprising the steps of: for each specific token in the query set, determining the number of database sets that contain the specific token; for each specific token in the query set, calculating an inverse document frequency (idf) weight, based at least in part on the number of database sets that contain the specific token and on the total number of database sets in the data collection set; calculating a normalized length of the first database set; calculating a normalized length of the query set; and, calculating a similarity score based at least in part on the normalized length of the first database set, the normalized length of the query set, and the idf weight of each of the tokens in the query set. | 1. A method for calculating a similarity score of a query set comprising a query set of tokens and a first database set comprising a first database set of tokens, wherein the first database set is one of a plurality of database sets in a data collection set stored on a non-transitory computer readable medium, comprising the steps of: for each specific token in the query set, determining the number of database sets that contain the specific token; for each specific token in the query set, calculating an inverse document frequency (idf) weight, based at least in part on the number of database sets that contain the specific token and on the total number of database sets in the data collection set; calculating a normalized length of the first database set; calculating a normalized length of the query set; and, calculating a similarity score based at least in part on the normalized length of the first database set, the normalized length of the query set, and the idf weight of each of the tokens in the query set. 3. The method of claim 1 further comprising the step of performing a shortest-first method. | 0.926494 |
9,697,249 | 1 | 9 | 1. A computer-implemented method comprising: obtaining training data including; for each of one or more original queries: (i) one or more features of the original query, (ii) one or more features of a revised query which was generated by a query revisor for the original query, and (iii) a label indicating whether the revised query is a successful revision of the original query; training, using the training data obtained for each of the one or more original queries that includes, for each respective original query, (i) the one or more features of the original query, (ii) the one or more features of the revised query which was generated by the query revisor for the original query, and (iii) the label indicating whether the revised query is a successful revision of the original query, a predictive model for predicting a likelihood that a given revised query is a successful revision of a given original query; and after receiving a particular original query, (a) using the predictive model to predict a likelihood that a particular revised query is a successful revision of the particular original query, and (b) determining whether to submit the particular revised search query to a search engine based on the likelihood. | 1. A computer-implemented method comprising: obtaining training data including; for each of one or more original queries: (i) one or more features of the original query, (ii) one or more features of a revised query which was generated by a query revisor for the original query, and (iii) a label indicating whether the revised query is a successful revision of the original query; training, using the training data obtained for each of the one or more original queries that includes, for each respective original query, (i) the one or more features of the original query, (ii) the one or more features of the revised query which was generated by the query revisor for the original query, and (iii) the label indicating whether the revised query is a successful revision of the original query, a predictive model for predicting a likelihood that a given revised query is a successful revision of a given original query; and after receiving a particular original query, (a) using the predictive model to predict a likelihood that a particular revised query is a successful revision of the particular original query, and (b) determining whether to submit the particular revised search query to a search engine based on the likelihood. 9. The method of claim 1 , wherein the one or more features of the original query include an information retrieval score associated with each original query. | 0.859319 |
10,162,735 | 9 | 10 | 9. A computer system comprising: a memory; and a processing device coupled to the memory to: receive a software testing executable script; append the software testing executable script to a list of executable scripts; identify a test environment comprising a management node and a testable component of a distributed network; establish, over the distributed network, a trusted connection between the management node and the testable component; receive an identifier of the software testing executable script, an identifier of a target for which the management node is to execute the software testing executable script, and a schedule for execution of the software testing executable script, wherein the management node is separate from the target; and execute, in view of the schedule, the identified software testing executable script with respect to the target. | 9. A computer system comprising: a memory; and a processing device coupled to the memory to: receive a software testing executable script; append the software testing executable script to a list of executable scripts; identify a test environment comprising a management node and a testable component of a distributed network; establish, over the distributed network, a trusted connection between the management node and the testable component; receive an identifier of the software testing executable script, an identifier of a target for which the management node is to execute the software testing executable script, and a schedule for execution of the software testing executable script, wherein the management node is separate from the target; and execute, in view of the schedule, the identified software testing executable script with respect to the target. 10. The computer system of claim 9 , wherein the identifier of the target comprises an address of the testable component. | 0.824638 |
10,068,617 | 1 | 4 | 1. A method comprising: storing comment data that indicates a plurality of comments that are associated with a media item; wherein two comments in the plurality of comments are from different users of a plurality of users; wherein each comment in the plurality of comments is associated with a time within the media item; receiving first input that indicates one or more search criteria; in response to receiving the first input: performing a search of the plurality of comments based on the one or more search criteria, wherein performing the search of the plurality of comments comprises limiting the search to comments that are associated with (1) the one or more search criteria and (2) a time that is within a time range that is based on a current playback position of the media item; identifying, as a result of performing the search, one or more comments of the plurality of comments; in response to identifying the one or more comments as the result of performing the search, causing, to be displayed on a screen of a computing device, the one or more comments of the plurality of comments; wherein the method is performed by one or more computing devices. | 1. A method comprising: storing comment data that indicates a plurality of comments that are associated with a media item; wherein two comments in the plurality of comments are from different users of a plurality of users; wherein each comment in the plurality of comments is associated with a time within the media item; receiving first input that indicates one or more search criteria; in response to receiving the first input: performing a search of the plurality of comments based on the one or more search criteria, wherein performing the search of the plurality of comments comprises limiting the search to comments that are associated with (1) the one or more search criteria and (2) a time that is within a time range that is based on a current playback position of the media item; identifying, as a result of performing the search, one or more comments of the plurality of comments; in response to identifying the one or more comments as the result of performing the search, causing, to be displayed on a screen of a computing device, the one or more comments of the plurality of comments; wherein the method is performed by one or more computing devices. 4. The method of claim 1 , further comprising: while playing the media item and while displaying a particular comment of the plurality of comments that are associated with the media item: identifying a current time of a second current playback position of the media item; comparing the current time to a particular time associated with the particular comment; in response to determining that the current time corresponds to the particular time associated with the particular comment, causing the particular comment to be highlighted. | 0.775295 |
9,706,403 | 22 | 23 | 22. The non-transitory computer-readable medium of claim 21 , wherein the GPS location is recorded between receiving the first alert and receiving a second alert requiring the enrollee to perform a second check-in. | 22. The non-transitory computer-readable medium of claim 21 , wherein the GPS location is recorded between receiving the first alert and receiving a second alert requiring the enrollee to perform a second check-in. 23. The non-transitory computer-readable medium of claim 22 , wherein the GPS location records the enrollee entering a disallowed geographic area. | 0.93881 |
10,008,208 | 1 | 2 | 1. A method of performing automated access control using speaker recognition performed via an automated user-machine interaction, the method comprising: in response to a user's contacting a computing system, prompting the user, via an automated user-machine interaction application, to speak a single phrase including a personal identifier and a common phrase component, the personal identifier and common phrase component being distinct, and the common phrase component being the same amongst a plurality of users; decomposing a received spoken phrase, the received spoken phrase being the single phrase, and the decomposing including locating the personal identifier within the spoken phrase and locating the common phrase component within the spoken phrase; identifying the user based on results of the decomposing, the identifying comprising comparing the personal identifier located against previously stored identifying information; verifying the user based on results of the decomposing, the verifying comprising comparing the common phrase component located against one or more previously stored voice prints associated with at least a subgroup of all users; and providing the user, if identified and verified, with access to the computing system. | 1. A method of performing automated access control using speaker recognition performed via an automated user-machine interaction, the method comprising: in response to a user's contacting a computing system, prompting the user, via an automated user-machine interaction application, to speak a single phrase including a personal identifier and a common phrase component, the personal identifier and common phrase component being distinct, and the common phrase component being the same amongst a plurality of users; decomposing a received spoken phrase, the received spoken phrase being the single phrase, and the decomposing including locating the personal identifier within the spoken phrase and locating the common phrase component within the spoken phrase; identifying the user based on results of the decomposing, the identifying comprising comparing the personal identifier located against previously stored identifying information; verifying the user based on results of the decomposing, the verifying comprising comparing the common phrase component located against one or more previously stored voice prints associated with at least a subgroup of all users; and providing the user, if identified and verified, with access to the computing system. 2. The method of claim 1 wherein the common phrase component is a component of the spoken phrase common amongst users within at least the subgroup of all users. | 0.898219 |
8,423,899 | 1 | 4 | 1. One or more computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: providing a first user input mode that restricts display of an input into a text field to a first set of characters; at least partly in response to receiving an input from a user specifying a character of the first set of characters, causing display of a character within the text field in a first manner; at least partly in response to receiving an input from the user specifying a character that the first set of characters does not include, refraining from causing display of a character within the text field; providing a second user input mode that restricts display of an input into the text field to a second set of characters that differs from the first set of characters; at least partly in response to receiving an input from the user specifying a character of the second set of characters, causing display of a character within the text field in a second manner that differs from the first manner; and at least partly in response to receiving an input from the user specifying a character that the second set of characters does not include, refraining from causing display of a character within the text field. | 1. One or more computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: providing a first user input mode that restricts display of an input into a text field to a first set of characters; at least partly in response to receiving an input from a user specifying a character of the first set of characters, causing display of a character within the text field in a first manner; at least partly in response to receiving an input from the user specifying a character that the first set of characters does not include, refraining from causing display of a character within the text field; providing a second user input mode that restricts display of an input into the text field to a second set of characters that differs from the first set of characters; at least partly in response to receiving an input from the user specifying a character of the second set of characters, causing display of a character within the text field in a second manner that differs from the first manner; and at least partly in response to receiving an input from the user specifying a character that the second set of characters does not include, refraining from causing display of a character within the text field. 4. One or more computer-readable media as recited in claim 1 , wherein the causing of the display of a character within the text field in the second manner comprises displaying a character other than the received character of the second set of characters. | 0.857701 |
8,660,960 | 9 | 10 | 9. A system for validating an electronic document, the system comprising: one or more processors; an electronic document reader; and a non-transient computer-readable medium having an electronic document stored thereon, the electronic document comprising: a plurality of content items including one or more invariant content items; a set of rules that defines a set of allowed operations which are authorized to be performed on the plurality of content items by the electronic document reader, wherein performing the allowed operations does not result in any changes being made to the one or more invariant content items; a first selective digest that is generated by a document author based on a first digesting of the one or more invariant content items; validation information that results from a comparison of the first selective digest and a second selective digest that is generated by the one or more processors based on a subsequent digesting of the one or more invariant content items, wherein the validation information indicates whether operations have been performed on the electronic document which are not allowed under the set of rules; and instructions configured to cause the electronic document reader to disable the allowed operations when the comparison of the first and second selective digests indicates that operations have been performed on the electronic document which are not allowed under the set of rules. | 9. A system for validating an electronic document, the system comprising: one or more processors; an electronic document reader; and a non-transient computer-readable medium having an electronic document stored thereon, the electronic document comprising: a plurality of content items including one or more invariant content items; a set of rules that defines a set of allowed operations which are authorized to be performed on the plurality of content items by the electronic document reader, wherein performing the allowed operations does not result in any changes being made to the one or more invariant content items; a first selective digest that is generated by a document author based on a first digesting of the one or more invariant content items; validation information that results from a comparison of the first selective digest and a second selective digest that is generated by the one or more processors based on a subsequent digesting of the one or more invariant content items, wherein the validation information indicates whether operations have been performed on the electronic document which are not allowed under the set of rules; and instructions configured to cause the electronic document reader to disable the allowed operations when the comparison of the first and second selective digests indicates that operations have been performed on the electronic document which are not allowed under the set of rules. 10. The system of claim 9 , wherein the second selective digest is represented as a hash having a lower layer containing functionality for digesting a basic content item that consists of a string, an intermediate layer containing functionality for digesting a semi-complex content item that consists of an annotation, and an upper layer containing functionality for digesting a complex content item that consists of a page. | 0.583661 |
9,613,004 | 1 | 8 | 1. A computer-implemented method for disambiguating one or more entities in an indicated text segment, comprising: processing the indicated text segment to determine a plurality of terms and their associated parts-of-speech tags and grammatical roles; performing linguistic analysis of the processed text segment to determine one or more potential entities which are referred to in the text segment by potential entity names; generating and storing, for each potential entity, an entity profile data structure storing one or more associated properties that characterize the entity based upon surrounding context and linguistic information received from the performed linguistic analysis of the processed text segment, the entity profile properties including one or more roles attributable to the potential entity based upon actions and/or modifiers associated with the determined potential entity name that have been retrieved from a linguistic analysis of the surrounding context; disambiguating which entities are being referred to in the indicated text segment by determining one or more mostly likely entities that are referred to in the text segment by comparing, using both linguistic and contextual information, the entity profiles generated for each potential entity with attributes of one or more candidate entities retrieved from a data repository; and invoking the method to annotate information on a web page. | 1. A computer-implemented method for disambiguating one or more entities in an indicated text segment, comprising: processing the indicated text segment to determine a plurality of terms and their associated parts-of-speech tags and grammatical roles; performing linguistic analysis of the processed text segment to determine one or more potential entities which are referred to in the text segment by potential entity names; generating and storing, for each potential entity, an entity profile data structure storing one or more associated properties that characterize the entity based upon surrounding context and linguistic information received from the performed linguistic analysis of the processed text segment, the entity profile properties including one or more roles attributable to the potential entity based upon actions and/or modifiers associated with the determined potential entity name that have been retrieved from a linguistic analysis of the surrounding context; disambiguating which entities are being referred to in the indicated text segment by determining one or more mostly likely entities that are referred to in the text segment by comparing, using both linguistic and contextual information, the entity profiles generated for each potential entity with attributes of one or more candidate entities retrieved from a data repository; and invoking the method to annotate information on a web page. 8. The method of claim 1 wherein the disambiguating which entities are being referred to in the indicated text segment by determining the one or more most likely entities which are referred to in the text segment by comparing, using both linguistic and contextual information, the entity profiles generated for each potential entity name with attributes of one or more candidate entities further comprises: resolving the one or more most likely entities to a single identified entity by performing iterative comparisons reusing entity disambiguation information gained from a prior comparison until no new entity disambiguation information is gained. | 0.588608 |
9,177,553 | 3 | 5 | 3. The computer-implemented method of claim 2 , wherein determining whether the first input sentence has an underserving signal further comprises, for each first input sentence: determining that the first input sentence was processed as a search query; determining a quality metric value for search results provided in response to the search query; and determining the first input sentence has the underserving signal when the quality metric value does not meet a threshold quality value. | 3. The computer-implemented method of claim 2 , wherein determining whether the first input sentence has an underserving signal further comprises, for each first input sentence: determining that the first input sentence was processed as a search query; determining a quality metric value for search results provided in response to the search query; and determining the first input sentence has the underserving signal when the quality metric value does not meet a threshold quality value. 5. The computer-implemented method of claim 3 , wherein determining a quality metric value for search results provided in response to the search query comprises determining a quality score that is a measure of user satisfaction in response to the search results, the measure of user satisfaction being dependent on user interactions with the search results at the user device from which the input sentence was received. | 0.890601 |
9,230,540 | 9 | 14 | 9. At least one computer-readable storage medium having encoded thereon computer-executable instructions that, when executed by at least one computer, cause the at least one computer to carry out a method of processing results of a recognition by an automatic speech recognition (ASR) system on an utterance, the results comprising a first recognition result identified by the ASR system as most likely to be a correct recognition result for the utterance, the results further comprising at least one alternative recognition result identified by the ASR system, the method comprising: determining whether the first recognition result includes a member of a set of words or phrases, each member of the set comprising a word or phrase and being associated with at least one other member of the set, and whether the at least one alternative recognition result includes any of the at least one other member associated with the member in the set, wherein the first recognition result includes at least one first word or phrase other than the member of the set of words or phrases and each of the at least one alternative recognition result includes at least one second word or phrase other than the at least one other member, the at least one first word or phrase and the at least one second word or phrase being the same or different; and in response to determining that the first recognition result includes the member of the set of words or phrases and that the at least one alternative recognition result includes any of the at least one other member associated with the member in the set, triggering an alert. | 9. At least one computer-readable storage medium having encoded thereon computer-executable instructions that, when executed by at least one computer, cause the at least one computer to carry out a method of processing results of a recognition by an automatic speech recognition (ASR) system on an utterance, the results comprising a first recognition result identified by the ASR system as most likely to be a correct recognition result for the utterance, the results further comprising at least one alternative recognition result identified by the ASR system, the method comprising: determining whether the first recognition result includes a member of a set of words or phrases, each member of the set comprising a word or phrase and being associated with at least one other member of the set, and whether the at least one alternative recognition result includes any of the at least one other member associated with the member in the set, wherein the first recognition result includes at least one first word or phrase other than the member of the set of words or phrases and each of the at least one alternative recognition result includes at least one second word or phrase other than the at least one other member, the at least one first word or phrase and the at least one second word or phrase being the same or different; and in response to determining that the first recognition result includes the member of the set of words or phrases and that the at least one alternative recognition result includes any of the at least one other member associated with the member in the set, triggering an alert. 14. The at least one computer-readable storage medium of claim 9 , wherein: at least one member of the set comprises a null word; and the determining whether the first recognition result includes a member of the set and whether the at least one alternative recognition result includes any of the at least one other member comprises determining that the first recognition result or the at least one alternative recognition result comprises the null word without evaluating words of the first recognition result or the at least one alternative recognition result. | 0.616279 |
9,170,918 | 9 | 11 | 9. A model verification method by a computer system including a processor, a storage section, an input part, and an output part, the model verification method comprising: acquiring an original model figure data registered as a design pattern in association with a program to the storage section by the input part; converting the original model figure data by the processor into formal language expression data based upon an expression format of a predetermined formal language; adding formal language expression data of a derivative design by the processor, by adding a modification to a component of the formal language on the converted formal language expression data, and storing the formal language expression data of the derivative design to the storage section; and verifying the original model figure data with use of the generated information processor and outputting verifying result by the output part; the conversion to the formal language expression data includes: determining an expression format of a formal language into which the original model figure data are converted based upon an extension and/or type information defined at a header of a file, extracting a parameter that specifies the model figure among the original model figure data from characteristics of the determined formal language, generating the formal language expression data based upon the extracted parameter to verify the original model figure data with use of the generated information; acquiring a recommended Key performance indicator (KPI) range value, a KPI calculation function, and existing design log data based upon the matching result; calculating a KPI value of the matched information description expression data, to verify the model figure data with use of the calculated information; generating information for selecting a replacing candidate and a replaced candidate based upon the KPI value of the information description expression data, to verify the model figure data with use of the generated information, comparing KPI values that are equivalent and comparable in a plurality of pieces of the information description expression data quantified by the quantification part, setting information description expression data having a high KPI value as a replacing candidate, setting other information description expression data as replaced candidates, and store the relationship between the candidates, and calculating a ratio of KPI values of the replacing candidate and the replaced candidates and Return On Investment (ROI) value in a case of the replacement. | 9. A model verification method by a computer system including a processor, a storage section, an input part, and an output part, the model verification method comprising: acquiring an original model figure data registered as a design pattern in association with a program to the storage section by the input part; converting the original model figure data by the processor into formal language expression data based upon an expression format of a predetermined formal language; adding formal language expression data of a derivative design by the processor, by adding a modification to a component of the formal language on the converted formal language expression data, and storing the formal language expression data of the derivative design to the storage section; and verifying the original model figure data with use of the generated information processor and outputting verifying result by the output part; the conversion to the formal language expression data includes: determining an expression format of a formal language into which the original model figure data are converted based upon an extension and/or type information defined at a header of a file, extracting a parameter that specifies the model figure among the original model figure data from characteristics of the determined formal language, generating the formal language expression data based upon the extracted parameter to verify the original model figure data with use of the generated information; acquiring a recommended Key performance indicator (KPI) range value, a KPI calculation function, and existing design log data based upon the matching result; calculating a KPI value of the matched information description expression data, to verify the model figure data with use of the calculated information; generating information for selecting a replacing candidate and a replaced candidate based upon the KPI value of the information description expression data, to verify the model figure data with use of the generated information, comparing KPI values that are equivalent and comparable in a plurality of pieces of the information description expression data quantified by the quantification part, setting information description expression data having a high KPI value as a replacing candidate, setting other information description expression data as replaced candidates, and store the relationship between the candidates, and calculating a ratio of KPI values of the replacing candidate and the replaced candidates and Return On Investment (ROI) value in a case of the replacement. 11. The model verification method as recited in claim 9 , comprising: converting model figure data, which are existing designed data, into information description expression data in an information expression format corresponding to the expression format of the converted formal language expression data and determining whether the formal language expression data and the information description expression data match each other, to verify the model figure data with use of the generated information; performing an operation verification of the replacing candidate and the replaced candidate with use of test data, to verify the model figure data; using, as the formal language expression data, data in an XML schema format or an XPath format used for grammar check and extraction check of an XML language and/or a BPEL to verify the model figure data. | 0.644528 |
10,108,712 | 14 | 15 | 14. The method of claim 9 further comprising: analyzing, using a rewrite optimizer module, the first standardized rewrite to identify a first logical structure of the first standardized rewrite as expressed in the first rewrite semantic structure; identifying a second logical structure different from the first logical structure and that is logically equivalent to the first logical structure; and generating an optimized first standardized rewrite comprising the second logical structure expressed in the first rewrite semantic structure using the first standardized rewrite. | 14. The method of claim 9 further comprising: analyzing, using a rewrite optimizer module, the first standardized rewrite to identify a first logical structure of the first standardized rewrite as expressed in the first rewrite semantic structure; identifying a second logical structure different from the first logical structure and that is logically equivalent to the first logical structure; and generating an optimized first standardized rewrite comprising the second logical structure expressed in the first rewrite semantic structure using the first standardized rewrite. 15. The method of claim 14 wherein the first standardized rewrite comprises at least two search commands associated with a first category of a category tree; and wherein the optimized first standardized rewrite consists of a single search command associated with the first category of the category tree. | 0.905784 |
9,177,053 | 1 | 8 | 1. A method programmed in a non-transitory memory of a first device, the first device comprising: receiving, at the first device, broadcast information; converting at least a portion of the broadcast information into searchable information; automatically performing a first fact check for factual accuracy of the broadcast information using the first device, the first fact check including comparing the searchable information with information from one or more first sources; automatically performing a second fact check for factual accuracy of the broadcast information in parallel with the first fact check, the second fact check including comparing the searchable information with information from one or more second sources; wherein automatically performing the first fact check results in generating a first result of the first fact check; wherein automatically performing the second fact check results in generating a second result of the second fact check; causing to be displayed, on a second device, an indication of the first result of the first fact check and the second result of the second fact check. | 1. A method programmed in a non-transitory memory of a first device, the first device comprising: receiving, at the first device, broadcast information; converting at least a portion of the broadcast information into searchable information; automatically performing a first fact check for factual accuracy of the broadcast information using the first device, the first fact check including comparing the searchable information with information from one or more first sources; automatically performing a second fact check for factual accuracy of the broadcast information in parallel with the first fact check, the second fact check including comparing the searchable information with information from one or more second sources; wherein automatically performing the first fact check results in generating a first result of the first fact check; wherein automatically performing the second fact check results in generating a second result of the second fact check; causing to be displayed, on a second device, an indication of the first result of the first fact check and the second result of the second fact check. 8. The method of claim 1 wherein the first fact check and the second fact check each utilize a different set of fact checking criteria. | 0.907913 |
8,538,973 | 1 | 11 | 1. A computer-implemented method for ranking search results of local search queries, comprising: at a server including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: receiving a search query and a current location of a user; identifying two or more places that satisfy the search query, and for each respective place determining a corresponding distance from the current location of the user to the respective place and a count of the number of historical queries for directions to the respective place, the respective place having a respective location; ranking the two or more places in accordance with scores for each place, wherein the score for a respective place is based on the count of the number of historical directions queries for directions to the respective place, distances between the respective location of the respective place and origins in historical queries for directions to the respective location of the respective place, and the distance from the current location of the user to the respective place, to produce a set of ranked places; and providing the ranked set of places to the user. | 1. A computer-implemented method for ranking search results of local search queries, comprising: at a server including one or more processors and memory storing one or more programs, the one or more processors executing the one or more programs to perform the operations of: receiving a search query and a current location of a user; identifying two or more places that satisfy the search query, and for each respective place determining a corresponding distance from the current location of the user to the respective place and a count of the number of historical queries for directions to the respective place, the respective place having a respective location; ranking the two or more places in accordance with scores for each place, wherein the score for a respective place is based on the count of the number of historical directions queries for directions to the respective place, distances between the respective location of the respective place and origins in historical queries for directions to the respective location of the respective place, and the distance from the current location of the user to the respective place, to produce a set of ranked places; and providing the ranked set of places to the user. 11. The method of claim 1 , wherein the score for each respective place is further based on factors selected from the group consisting of: reviews of the respective places; search engine rankings for web pages associated with the respective place; and a mode of travel. | 0.795903 |
8,493,208 | 1 | 5 | 1. A method comprising: periodically sampling a user environment via a set of environmental sensors integrated into a communication device; deriving a set of environmental circumstances based at least partially on an output of the set of environmental sensors by an analysis module in communication with the set of environmental sensors; and comparing, by the analysis module, the derived set of environmental circumstances to a set of templates to determine whether there is a matching template, wherein if more than one of the templates matches the derived set of environmental circumstances, a best-match template is determined, and wherein if there is a matching template, an action script is executed. | 1. A method comprising: periodically sampling a user environment via a set of environmental sensors integrated into a communication device; deriving a set of environmental circumstances based at least partially on an output of the set of environmental sensors by an analysis module in communication with the set of environmental sensors; and comparing, by the analysis module, the derived set of environmental circumstances to a set of templates to determine whether there is a matching template, wherein if more than one of the templates matches the derived set of environmental circumstances, a best-match template is determined, and wherein if there is a matching template, an action script is executed. 5. The method of claim 1 , further comprising relinquishing control of a component of the communication device to an emergency responding party at least partially based on the matching template. | 0.727528 |
7,788,104 | 4 | 6 | 4. The information processing terminal according to claim 3 , wherein the emotion specifying unit specifies an emotion expressed by a distinctive one of the stored parameters. | 4. The information processing terminal according to claim 3 , wherein the emotion specifying unit specifies an emotion expressed by a distinctive one of the stored parameters. 6. The information processing terminal according to claim 4 , wherein the emotion specifying unit specifies an emotion corresponding to a parameter with a highest total of numeral values generated from the start of the voice and the end of the voice, among the parameters of emotions stored in the storage unit. | 0.90152 |
8,359,202 | 1 | 5 | 1. A computer implemented method, comprising: displaying a sequence of words on a user interface rendered on a display device; applying, by one or more computers, in response to a user-based selection of a first portion of words in the sequence of words, a first indicium to the user-selected first portion of words in the sequence of words; associating, by the one or more computers, a first character having an associated first voice model to the first portion of words in the sequence of words; and associating, by the one or more computers, a second, different character having an associated second, different voice model to a second portion of words in the sequence of words, the second portion of the words in the sequence of words being different from the first portion of words in the sequence of words. | 1. A computer implemented method, comprising: displaying a sequence of words on a user interface rendered on a display device; applying, by one or more computers, in response to a user-based selection of a first portion of words in the sequence of words, a first indicium to the user-selected first portion of words in the sequence of words; associating, by the one or more computers, a first character having an associated first voice model to the first portion of words in the sequence of words; and associating, by the one or more computers, a second, different character having an associated second, different voice model to a second portion of words in the sequence of words, the second portion of the words in the sequence of words being different from the first portion of words in the sequence of words. 5. The method of claim 1 , further comprising generating, by the one or more computers, an audible output corresponding to the words in the sequence of words where the words in the first portion of words are narrated using the first voice model for the first character and the words in the second portion of words are narrated using the second voice model for the second character. | 0.623518 |
9,342,555 | 1 | 3 | 1. A computer program product, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code executable by at least one processor to perform operations of: generating a view schema from a view definition, wherein the view schema includes one or more relational views that are created by translating one or more object queries in the view definition into one or more relational queries; generating a report design schema from the view definition by: creating one or more report tables that correspond to the one or more relational views of the view schema; and extending the one or more report tables with one or more primary key constraints and one or more foreign key constraints; generating a reporting model by reverse engineering the report design schema, wherein the reporting model includes the one or more primary key constraints and the one or more foreign key constraints; and generating a report using the reporting model, wherein the report includes the one or more primary key constraints and the one or more foreign key constraints. | 1. A computer program product, the computer program product comprising a non-transitory computer readable storage medium having program code embodied therewith, the program code executable by at least one processor to perform operations of: generating a view schema from a view definition, wherein the view schema includes one or more relational views that are created by translating one or more object queries in the view definition into one or more relational queries; generating a report design schema from the view definition by: creating one or more report tables that correspond to the one or more relational views of the view schema; and extending the one or more report tables with one or more primary key constraints and one or more foreign key constraints; generating a reporting model by reverse engineering the report design schema, wherein the reporting model includes the one or more primary key constraints and the one or more foreign key constraints; and generating a report using the reporting model, wherein the report includes the one or more primary key constraints and the one or more foreign key constraints. 3. The computer program product of claim 1 , wherein the primary key constraints and the foreign key constraints are inferred from query result type information collected during the translation of the object queries and based on naming conventions. | 0.701923 |
7,801,912 | 102 | 115 | 102. A searchable data service node, comprising: one or more processors; a network interface configured to communicatively couple to a network; and a memory comprising program instructions, wherein the program instructions are executable by the one or more processors to: receive via the network searchable data service requests from a plurality of client applications in accordance with a web service interface, wherein the searchable data service requests comprise query requests, and wherein the web service interface provides a common message endpoint to the plurality of client applications to send the query requests; locate sets of one or more searchable data service objects in respective searchable indexes for a plurality of independent data stores used by the client applications that satisfy received query requests, wherein the query requests specify one of the searchable indexes, wherein the searchable indexes are distributed on a plurality of searchable data service nodes on the network, wherein the data stores are on one or more storage devices each on the network and separate from computer devices on the network that implement the searchable data service nodes, wherein each searchable index stores searchable data service objects for a particular one of the plurality of independent data stores such that each searchable index provides a complete index for only one of the independent data stores, wherein each searchable data service object specifies two or more attributes of a particular entity in a particular data store, and wherein the attributes include a unique entity identifier for locating the particular entity in the particular data store; and return via the network at least the entity identifiers from the sets of one or more searchable data service objects that satisfy the query requests to the client applications in accordance with the web service interface. | 102. A searchable data service node, comprising: one or more processors; a network interface configured to communicatively couple to a network; and a memory comprising program instructions, wherein the program instructions are executable by the one or more processors to: receive via the network searchable data service requests from a plurality of client applications in accordance with a web service interface, wherein the searchable data service requests comprise query requests, and wherein the web service interface provides a common message endpoint to the plurality of client applications to send the query requests; locate sets of one or more searchable data service objects in respective searchable indexes for a plurality of independent data stores used by the client applications that satisfy received query requests, wherein the query requests specify one of the searchable indexes, wherein the searchable indexes are distributed on a plurality of searchable data service nodes on the network, wherein the data stores are on one or more storage devices each on the network and separate from computer devices on the network that implement the searchable data service nodes, wherein each searchable index stores searchable data service objects for a particular one of the plurality of independent data stores such that each searchable index provides a complete index for only one of the independent data stores, wherein each searchable data service object specifies two or more attributes of a particular entity in a particular data store, and wherein the attributes include a unique entity identifier for locating the particular entity in the particular data store; and return via the network at least the entity identifiers from the sets of one or more searchable data service objects that satisfy the query requests to the client applications in accordance with the web service interface. 115. The searchable data service node as recited in claim 102 , wherein the propagated searchable data service information includes local health information for the searchable data service node. | 0.923922 |
8,682,647 | 11 | 14 | 11. A system for providing a natural language answer to a natural language question, the system comprising: an interface configured to receive, over a computer network, a query comprising a grammatical question; an interface configured to submit the query to a lookup engine; an interface configured to receive initial search results from the lookup engine, the initial search results comprising a plurality of documents; a processor configured to identify, in the plurality of documents, a plurality of candidate sentences; a processor configured to calculate a frequency of a plurality of n-grams appearing in the plurality of candidate sentences, wherein n ranges at least from 1 to 2; a processor configured to calculate, for each candidate sentence, a measure of commonality between the candidate sentence and the query; a processor configured to assign, to each candidate sentence, a score, wherein the score comprises (1) the frequency of a plurality of n-grams appearing in the candidate sentence, and (2) the measure of commonality between the candidate sentence and the query; a processor configured to sort the candidate sentences according to score, whereby a rating of candidate sentences is produced; and an interface configured to send, over a computer network, a reply to the query, the reply comprising at least a top candidate sentence from the rating of candidate sentences. | 11. A system for providing a natural language answer to a natural language question, the system comprising: an interface configured to receive, over a computer network, a query comprising a grammatical question; an interface configured to submit the query to a lookup engine; an interface configured to receive initial search results from the lookup engine, the initial search results comprising a plurality of documents; a processor configured to identify, in the plurality of documents, a plurality of candidate sentences; a processor configured to calculate a frequency of a plurality of n-grams appearing in the plurality of candidate sentences, wherein n ranges at least from 1 to 2; a processor configured to calculate, for each candidate sentence, a measure of commonality between the candidate sentence and the query; a processor configured to assign, to each candidate sentence, a score, wherein the score comprises (1) the frequency of a plurality of n-grams appearing in the candidate sentence, and (2) the measure of commonality between the candidate sentence and the query; a processor configured to sort the candidate sentences according to score, whereby a rating of candidate sentences is produced; and an interface configured to send, over a computer network, a reply to the query, the reply comprising at least a top candidate sentence from the rating of candidate sentences. 14. The system of claim 11 , wherein the measure of commonality comprises a count of common words. | 0.832765 |
8,036,876 | 10 | 12 | 10. The method of claim 1 further comprising, for an individual one of the event classes, selecting one of the words of the respective concept of the event class as the name of the respective event class for use in disambiguation of instances of the event class. | 10. The method of claim 1 further comprising, for an individual one of the event classes, selecting one of the words of the respective concept of the event class as the name of the respective event class for use in disambiguation of instances of the event class. 12. The method of claim 10 wherein the accessing the lexical database comprises accessing a version of WordNet. | 0.958582 |
7,707,201 | 1 | 8 | 1. A method for assisting a user with a search, the method comprising: providing one or more concept networks, each concept network including a plurality of units and relationships among the units, wherein the relationships among the units are selected from a group consisting of extensions, associations and alternatives; receiving a baseline query; executing, using a processing device, a baseline search using the baseline query; transmitting, using the processing device, a result of the baseline search to the user; and in response to a user request: modifying, using the processing device, the baseline query to generate a modified query based at least in part on relationship information from at least one of the concept networks, the relationship information pertaining to at least one baseline unit extracted from the baseline query; executing a modified search using the modified query; transmitting, using the processing device, to the user a result of the modified search; and prompting, via the processing device, the user to provide feedback on the result of the modified search, wherein the user feedback is usable to perform a further modification to at least one of the baseline query and the modified query. | 1. A method for assisting a user with a search, the method comprising: providing one or more concept networks, each concept network including a plurality of units and relationships among the units, wherein the relationships among the units are selected from a group consisting of extensions, associations and alternatives; receiving a baseline query; executing, using a processing device, a baseline search using the baseline query; transmitting, using the processing device, a result of the baseline search to the user; and in response to a user request: modifying, using the processing device, the baseline query to generate a modified query based at least in part on relationship information from at least one of the concept networks, the relationship information pertaining to at least one baseline unit extracted from the baseline query; executing a modified search using the modified query; transmitting, using the processing device, to the user a result of the modified search; and prompting, via the processing device, the user to provide feedback on the result of the modified search, wherein the user feedback is usable to perform a further modification to at least one of the baseline query and the modified query. 8. The method of claim 1 , comprising: redefining the modified query as a new baseline query in response to receipt of positive feedback. | 0.763793 |
9,076,009 | 2 | 4 | 2. A method of claim 1 , wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following further comprises: at least one determination of a presentation of a prompt that solicits the personal relationship from the first user, wherein the association is based at least in part on a response received in response to the presentation of the prompt. | 2. A method of claim 1 , wherein the (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following further comprises: at least one determination of a presentation of a prompt that solicits the personal relationship from the first user, wherein the association is based at least in part on a response received in response to the presentation of the prompt. 4. A method of claim 2 , wherein (1) data and/or (2) information and/or (3) at least one signal are further based, at least in part, on the following: at least one determination of a presentation of the one or more personal description vocabulary labels and a prompt that solicits user selection from the first user; and receiving the user selection of at least one of the personal description vocabulary labels. | 0.867864 |
9,397,977 | 20 | 21 | 20. The apparatus of claim 16 , wherein the memory holds further instructions for determining a corresponding registration fee based on the count of domain names. | 20. The apparatus of claim 16 , wherein the memory holds further instructions for determining a corresponding registration fee based on the count of domain names. 21. The apparatus of claim 20 , wherein the memory holds further instructions for analyzing an IP address associated with a source of the request, and determining a response to the request based on the IP address associated with the source of the request. | 0.897426 |
9,330,376 | 6 | 10 | 6. A system for managing information in an enterprise, comprising: a processor operable to: receive a document from a component of an enterprise network; determine one or more characteristics associated with the document, wherein the one or more characteristics are selected from the group comprising a creator of the document, a sender of the document, a receiver of the document, and a quantity of recipients of the document; determine a priority score for the document based on a respective level of risk that each user in a set of users associated with the document poses to the enterprise, each respective level of risk corresponding to each user's role in the enterprise, wherein the set of users comprises the sender of the document and the receiver of the document; assign a business value rating to the document based, at least in part, on the one or more characteristics and the priority score; and perform an operation with the document based on the business value rating. | 6. A system for managing information in an enterprise, comprising: a processor operable to: receive a document from a component of an enterprise network; determine one or more characteristics associated with the document, wherein the one or more characteristics are selected from the group comprising a creator of the document, a sender of the document, a receiver of the document, and a quantity of recipients of the document; determine a priority score for the document based on a respective level of risk that each user in a set of users associated with the document poses to the enterprise, each respective level of risk corresponding to each user's role in the enterprise, wherein the set of users comprises the sender of the document and the receiver of the document; assign a business value rating to the document based, at least in part, on the one or more characteristics and the priority score; and perform an operation with the document based on the business value rating. 10. The system of claim 6 , wherein the processor is operable to perform an operation by performing an operation selected from the group of: storing a record associated with the document, wherein the record includes the assigned business value rating and the one or more characteristics; storing the document; transmitting an alert based on the assigned business value rating, wherein the alert is transmitted to at least one of the sender of the document and a third party; preventing the document from being transmitted; preventing the document from being accessed on one of the plurality of heterogeneous data servers; transmitting the document; transmitting the document in response to receiving transmission approval from a third party; and allowing the document to be accessed on one of the plurality of heterogeneous data server in response to receiving access approval from a third party. | 0.592727 |
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