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7,797,260 | 7 | 8 | 7. The method of claim 6 , further comprising updating the confidence indicator based on said comparison of the gathered statistics for the document with statistics of other documents interpreted to be correctly classified. | 7. The method of claim 6 , further comprising updating the confidence indicator based on said comparison of the gathered statistics for the document with statistics of other documents interpreted to be correctly classified. 8. The method of claim 7 , wherein the documents known to be correctly classified are classified based, at least in part, on a human-labeled training set. | 0.5 |
8,572,106 | 1 | 10 | 1. A token stitcher for determining whether an input string of characters matches a regular expression comprising a number of sub-expressions, the token stitcher comprising: a flag bank storing a number of flags, where each flag identifies one or more of the sub-expressions that match the input string; and a token stitcher engine configured to implement an unbounded sub-expression without utilizing resources of a deterministic finite state automaton (DFA) engine or a non-deterministic finite state automaton (NFA) engine and to identify one or lore programs stored in a program memory that are associated with a new token received by the token stitcher, wherein a particular program in the program memory is configured to indicate a match when a particular set of flags in the flag bank are asserted, and wherein the flag bank is configured to discard one or more flags upon satisfaction of a predetermined condition and wherein the token stitcher is implemented by at least one processor-based computing device. | 1. A token stitcher for determining whether an input string of characters matches a regular expression comprising a number of sub-expressions, the token stitcher comprising: a flag bank storing a number of flags, where each flag identifies one or more of the sub-expressions that match the input string; and a token stitcher engine configured to implement an unbounded sub-expression without utilizing resources of a deterministic finite state automaton (DFA) engine or a non-deterministic finite state automaton (NFA) engine and to identify one or lore programs stored in a program memory that are associated with a new token received by the token stitcher, wherein a particular program in the program memory is configured to indicate a match when a particular set of flags in the flag bank are asserted, and wherein the flag bank is configured to discard one or more flags upon satisfaction of a predetermined condition and wherein the token stitcher is implemented by at least one processor-based computing device. 10. The token stitcher of claim 1 , wherein the flag bank is configured to discard, upon satisfaction of the predetermined condition, any number of flags that are each associated with an offset that is more than a predetermined distance away from a current offset being examined. | 0.55 |
8,401,252 | 23 | 26 | 23. A method, comprising: receiving video data from a user over a data communication network using a processor; detecting human faces in a plurality of video frames in said video data using said processor; for at least one detected human face, identifying a face-specific set of video frames using said processor, irrespective of whether said detected human face is present in said face-specific set of video frames in a substantially temporally continuous manner; configuring said processor to use a face recognition method based on a Bayesian Network based classifier to identify those portions of said video data corresponding to said face-specific set of video frames wherein said at least one detected human face is present, wherein the Bayesian Network based classifier is constructed based on a ratio of a plurality of Bayesian networks and each of said Bayesian networks is a probability distribution representation derived from dependencies among video input variables that statistically depend upon each other; and using said processor, sending cueing information for said portions of said video data to said user over said data communication network so as to enable said user to selectively view face-specific video segments in said video data associated with said at least one detected human face without a need to search said video data for said video segments. | 23. A method, comprising: receiving video data from a user over a data communication network using a processor; detecting human faces in a plurality of video frames in said video data using said processor; for at least one detected human face, identifying a face-specific set of video frames using said processor, irrespective of whether said detected human face is present in said face-specific set of video frames in a substantially temporally continuous manner; configuring said processor to use a face recognition method based on a Bayesian Network based classifier to identify those portions of said video data corresponding to said face-specific set of video frames wherein said at least one detected human face is present, wherein the Bayesian Network based classifier is constructed based on a ratio of a plurality of Bayesian networks and each of said Bayesian networks is a probability distribution representation derived from dependencies among video input variables that statistically depend upon each other; and using said processor, sending cueing information for said portions of said video data to said user over said data communication network so as to enable said user to selectively view face-specific video segments in said video data associated with said at least one detected human face without a need to search said video data for said video segments. 26. The method of claim 23 , further comprising: charging a fee to said user for sending said cueing information. | 0.878755 |
8,670,974 | 2 | 4 | 2. The method of claim 1 further comprising: performing a verification operation on a candidate translation pair from the set of candidate translation pairs; based, at least in part, on results of the verification operation, determining whether to classify the candidate translation pair as a translation pair. | 2. The method of claim 1 further comprising: performing a verification operation on a candidate translation pair from the set of candidate translation pairs; based, at least in part, on results of the verification operation, determining whether to classify the candidate translation pair as a translation pair. 4. The method of claim 2 , wherein performing a verification operation on the candidate translation pair comprises determining if the candidate translation pair has a one-to-one correspondence relative to other candidate translation pairs. | 0.522 |
7,516,125 | 15 | 19 | 15. An apparatus for indexing a corpus of documents, wherein the words in the corpus of documents include a set of words having a characteristic to be subject of queries, comprising: a data processor arranged to parse documents in the corpus of documents to identify words found in the documents and locations of the words in the documents, and to create an index structure including entries representing words found in the corpus of documents mapping entries in the index structure to locations of the words in documents in the corpus memory storing the index structure writable and readable by the data processor; wherein the data processor includes an indexing processor which indentifies words in a set of words having a characteristic represent d by a mark in a set of marks, and add entries in the index structure representing marks for the identified the set mapping the marks to the locations of the identified words, and wherein one or more entries representing marks include fewer, if any, than all of the characters of the corresponding identified words; wherein entries in the index structure representing the marks comprise tokens coalesced with prefixes of respective marked words, the prefixes comprising one or more leading characters of the respective marked words. | 15. An apparatus for indexing a corpus of documents, wherein the words in the corpus of documents include a set of words having a characteristic to be subject of queries, comprising: a data processor arranged to parse documents in the corpus of documents to identify words found in the documents and locations of the words in the documents, and to create an index structure including entries representing words found in the corpus of documents mapping entries in the index structure to locations of the words in documents in the corpus memory storing the index structure writable and readable by the data processor; wherein the data processor includes an indexing processor which indentifies words in a set of words having a characteristic represent d by a mark in a set of marks, and add entries in the index structure representing marks for the identified the set mapping the marks to the locations of the identified words, and wherein one or more entries representing marks include fewer, if any, than all of the characters of the corresponding identified words; wherein entries in the index structure representing the marks comprise tokens coalesced with prefixes of respective marked words, the prefixes comprising one or more leading characters of the respective marked words. 19. The apparatus of claim 15 , wherein the characteristic identified by at least one mark includes a context of the marked word. | 0.856984 |
8,874,564 | 16 | 18 | 16. A server for communicating search results, the server comprising: a processor for executing a set of instructions; and a memory in communication with the processor for storing the set of instructions, wherein the set of instructions are executed by the processor to: receive user input from a first user to perform a search of a communications network; perform the search based on the user input to generate the search results; determine whether the search results include content dates for content; determine a publication date of the content for each search result; determine a post data of the content for each search result; display the search results and a plurality of selection elements associated with each of the search results, wherein each of the plurality of selection elements is associated with one or more second users separate from the first user and is selectable by the first user to communicate each of the search results to the one or more second users separate from the first user; receive a user selection of one or more of the plurality of selection elements associated with the one or more second users separate from the first user; and communicate one or more of the search results to the associated one or more second users separate from the first user, in response to the user selection. | 16. A server for communicating search results, the server comprising: a processor for executing a set of instructions; and a memory in communication with the processor for storing the set of instructions, wherein the set of instructions are executed by the processor to: receive user input from a first user to perform a search of a communications network; perform the search based on the user input to generate the search results; determine whether the search results include content dates for content; determine a publication date of the content for each search result; determine a post data of the content for each search result; display the search results and a plurality of selection elements associated with each of the search results, wherein each of the plurality of selection elements is associated with one or more second users separate from the first user and is selectable by the first user to communicate each of the search results to the one or more second users separate from the first user; receive a user selection of one or more of the plurality of selection elements associated with the one or more second users separate from the first user; and communicate one or more of the search results to the associated one or more second users separate from the first user, in response to the user selection. 18. The server according to claim 16 , wherein the set of instructions are further executed to: assign a graphic selected by the first user as each of the plurality of selection elements; and associate each of the plurality of selection elements with the one or more second users separate from the first user. | 0.518692 |
9,087,272 | 16 | 18 | 16. A computer program product for enhanced optical character recognition, the computer program product comprising logic code embedded in a non-transitory data storage medium, wherein execution of the logic code on a computer causes the computer to: identify a sample character in a textual context to be optically recognized; compare the sample character with a template character, wherein the sample character is scaled into a first grid and the template character is scaled into a second grid; identify one or more pixels in the sample character within the first grid and one or more pixels in the template character in the second grid, wherein the one or more pixels are identified as belonging to a foreground category in the textual content, a foreground pixel having at least N gradients corresponding to edges of the foreground pixel that are juxtaposed to a neighbor pixel, wherein a contour foreground pixel has at least one gradient that is neighbored by a background pixel in the textual context; identifying one or more template contour pixels in the template character that correspond to at least one sample contour pixel in the sample character, map the at least one sample contour pixel to the corresponding template contour pixels such that one or more distances are calculated between the at least one sample contour pixel and the respective one or more template contour pixels; and determine that the sample contour character and the template contour character are a match based on an analysis of the one or more distances. | 16. A computer program product for enhanced optical character recognition, the computer program product comprising logic code embedded in a non-transitory data storage medium, wherein execution of the logic code on a computer causes the computer to: identify a sample character in a textual context to be optically recognized; compare the sample character with a template character, wherein the sample character is scaled into a first grid and the template character is scaled into a second grid; identify one or more pixels in the sample character within the first grid and one or more pixels in the template character in the second grid, wherein the one or more pixels are identified as belonging to a foreground category in the textual content, a foreground pixel having at least N gradients corresponding to edges of the foreground pixel that are juxtaposed to a neighbor pixel, wherein a contour foreground pixel has at least one gradient that is neighbored by a background pixel in the textual context; identifying one or more template contour pixels in the template character that correspond to at least one sample contour pixel in the sample character, map the at least one sample contour pixel to the corresponding template contour pixels such that one or more distances are calculated between the at least one sample contour pixel and the respective one or more template contour pixels; and determine that the sample contour character and the template contour character are a match based on an analysis of the one or more distances. 18. The computer program product of claim 16 , wherein the first and the second grid are of the same size. | 0.821549 |
7,930,597 | 1 | 2 | 1. A method for testing a system under test, comprising: executing a test procedure for the system under test, wherein the test procedure has at least one parameterized pattern associated therewith; monitoring an execution trace generated during execution of the test procedure, wherein the execution trace comprises unstructured information, wherein the execution trace is monitored using the at least one parameterized pattern to identify at least one matching pattern; generating at least one structured term using the at least one matching pattern; and determining a system testing result for the system under test using the at least one structured term. | 1. A method for testing a system under test, comprising: executing a test procedure for the system under test, wherein the test procedure has at least one parameterized pattern associated therewith; monitoring an execution trace generated during execution of the test procedure, wherein the execution trace comprises unstructured information, wherein the execution trace is monitored using the at least one parameterized pattern to identify at least one matching pattern; generating at least one structured term using the at least one matching pattern; and determining a system testing result for the system under test using the at least one structured term. 2. The method of claim 1 , wherein each of the at least one parameterized pattern is defined using a pattern template and at least one pattern parameter. | 0.823326 |
9,361,385 | 1 | 9 | 1. A system, comprising: a processor configured to: determine a topic based on a user demand, wherein determining the topic comprises: determine frequencies of phrases based on an analysis of a search query log from a web site, a search query log from a search engine, or a combination thereof; compare the frequencies of the phrases to a predetermined threshold; determine at least one theme based on phrases having frequencies exceeding the predetermined threshold; sort the at least one theme based on common words in the phrases; cluster the at least one theme; and determine the topic based on the clustered at least one theme; automatically generate content for the topic, wherein the content is configured or organized differently than on other web pages of the web site; and select the content that is contextually relevant for display within a corpus of content, wherein the corpus of content includes a web site, a user's social networking web page, content customized for mobile devices, content customized based on location awareness, or an electronic mail message; and a memory coupled to the processor and configured to provide the processor with instructions. | 1. A system, comprising: a processor configured to: determine a topic based on a user demand, wherein determining the topic comprises: determine frequencies of phrases based on an analysis of a search query log from a web site, a search query log from a search engine, or a combination thereof; compare the frequencies of the phrases to a predetermined threshold; determine at least one theme based on phrases having frequencies exceeding the predetermined threshold; sort the at least one theme based on common words in the phrases; cluster the at least one theme; and determine the topic based on the clustered at least one theme; automatically generate content for the topic, wherein the content is configured or organized differently than on other web pages of the web site; and select the content that is contextually relevant for display within a corpus of content, wherein the corpus of content includes a web site, a user's social networking web page, content customized for mobile devices, content customized based on location awareness, or an electronic mail message; and a memory coupled to the processor and configured to provide the processor with instructions. 9. The system recited in claim 1 , wherein the content is selected for display in a plurality of modules, and wherein the processor is further configured to: determine performance metrics associated with the plurality of modules; and automatically modify each of the plurality of modules based on the performance metrics. | 0.62933 |
9,152,616 | 2 | 3 | 2. The method of claim 1 , wherein the source comprises web content published by a publisher. | 2. The method of claim 1 , wherein the source comprises web content published by a publisher. 3. The method of claim 2 , wherein the identified candidate templates are templates approved by the publisher. | 0.5 |
7,912,703 | 1 | 4 | 1. A computer implemented method for unsupervised stemming schema learning and lexicon acquisition from corpora, the computer implemented method comprising; obtaining a corpus from a corpora; analyzing the corpus to deduce a set of possible stemming schema, wherein analyzing the corpus to deduce the set of possible stemming schema further comprises: generating a first affix count in concepts, wherein each of the concepts is a word unique in the corpus; generating a second affix count in schemas, wherein each of the schemas contains a transformation from a first affix to a second affix for the word; and generating a schema score for the each of the schemas from a combination of the first affix count and the second affix count for the possible stemming schemas to identify useful stemming schemas comprising: identifying a first number of occurrences of the first affix in the corpus for each kernel size; identifying a second number of occurrences of the second affix in the corpus for the each kernel size; identifying a third number of occurrences of the each kernel size in the corpus; and dividing a lesser of the first number of occurrences and the second number of occurrences by the third number of occurrences to form the schema score; reviewing and revising the set of possible stemming schema to create a pruned set of stemming schema; and deducing a lexicon from the corpus using the pruned set of stemming schema. | 1. A computer implemented method for unsupervised stemming schema learning and lexicon acquisition from corpora, the computer implemented method comprising; obtaining a corpus from a corpora; analyzing the corpus to deduce a set of possible stemming schema, wherein analyzing the corpus to deduce the set of possible stemming schema further comprises: generating a first affix count in concepts, wherein each of the concepts is a word unique in the corpus; generating a second affix count in schemas, wherein each of the schemas contains a transformation from a first affix to a second affix for the word; and generating a schema score for the each of the schemas from a combination of the first affix count and the second affix count for the possible stemming schemas to identify useful stemming schemas comprising: identifying a first number of occurrences of the first affix in the corpus for each kernel size; identifying a second number of occurrences of the second affix in the corpus for the each kernel size; identifying a third number of occurrences of the each kernel size in the corpus; and dividing a lesser of the first number of occurrences and the second number of occurrences by the third number of occurrences to form the schema score; reviewing and revising the set of possible stemming schema to create a pruned set of stemming schema; and deducing a lexicon from the corpus using the pruned set of stemming schema. 4. The computer implemented method of claim 1 , wherein reviewing and revising the set of possible stemming schema to create a pruned set of stemming schema further comprises: analyzing each stemming schema of the set of possible stemming schema; and identifying stemming schema having a kernel that has a best schema matching a current stemming schema and keeping the kernel, otherwise deleting the stemming schema. | 0.5 |
8,103,962 | 1 | 18 | 1. In a computing environment, a method of extracting data from web pages and organizing the extracted data in a user searchable format, the method comprising: at a graphical user interface, receiving user input defining a tabular form; at the graphical user interface, receiving user input correlating one or more portions of the form with one or more user selected data items contained in one or more first web pages; a computer module correlating the user input to create an ontology defining relationships between the user selected data items based on the definition of the tabular form; a computer module accessing one or more other web pages, and based on a context of the one or more data items in the first web page being similar to a context of the selected data items in the one or more first web pages, extracting one or more similar data items from the one or more other web pages; a computer module correlating the extracted data items to each other in accordance with the ontology defining relationships between the user selected data items; a computer module outputting the correlated extracted data items as a user searchable data structure. | 1. In a computing environment, a method of extracting data from web pages and organizing the extracted data in a user searchable format, the method comprising: at a graphical user interface, receiving user input defining a tabular form; at the graphical user interface, receiving user input correlating one or more portions of the form with one or more user selected data items contained in one or more first web pages; a computer module correlating the user input to create an ontology defining relationships between the user selected data items based on the definition of the tabular form; a computer module accessing one or more other web pages, and based on a context of the one or more data items in the first web page being similar to a context of the selected data items in the one or more first web pages, extracting one or more similar data items from the one or more other web pages; a computer module correlating the extracted data items to each other in accordance with the ontology defining relationships between the user selected data items; a computer module outputting the correlated extracted data items as a user searchable data structure. 18. The method of claim 1 , wherein extracting is performed such that after a first iteration of extracting data, a list of suspected errors is provided to the user whereafter the user provides additional correlation, which is then used by subsequent iterations of the extraction. | 0.5 |
7,814,086 | 2 | 3 | 2. The method of claim 1 , wherein establishing a plurality of sequences of search queries comprises: adding a first search query associated with a first user to a first sequence; determining whether to add a second search query associated with the first user to the first sequence based on a similarity between the second search query and at least the first search query of the first sequence; adding the second search query to the first sequence in response to determining the similarity between the second search query and at least the first search query of the first sequence exceeds a similarity threshold; and adding the second query to a second sequence in response to determining the similarity between the second search query and at least the first search query of the first sequence does not exceed the similarity threshold. | 2. The method of claim 1 , wherein establishing a plurality of sequences of search queries comprises: adding a first search query associated with a first user to a first sequence; determining whether to add a second search query associated with the first user to the first sequence based on a similarity between the second search query and at least the first search query of the first sequence; adding the second search query to the first sequence in response to determining the similarity between the second search query and at least the first search query of the first sequence exceeds a similarity threshold; and adding the second query to a second sequence in response to determining the similarity between the second search query and at least the first search query of the first sequence does not exceed the similarity threshold. 3. The method of claim 2 , wherein determining a similarity between the second search query and at least the first search query of the first sequence is based on at least one of: an edit distance between the second search query and at least the first search query of the first sequence; a word edit distance between the second search query and at least the first search query of the first sequence; a difference between a time the second search query issued and the time that at least the first search query of the first sequence issued; whether there is a prefix overlap between the second search query and at least the first search query of the first sequence; whether there is a suffix overlap between the second search query and at least the first search query of the first sequence; a geographic location related to the second search query and at least the first search query of the first sequence; and a product brand associated with the second search query and at least the first search query of the first sequence. | 0.5 |
8,880,538 | 2 | 3 | 2. The method of claim 1 , wherein the first data element identifies semantics of the first data value. | 2. The method of claim 1 , wherein the first data element identifies semantics of the first data value. 3. The method of claim 2 , wherein the second data element identifies semantics of the second data value. | 0.5 |
8,612,469 | 1 | 12 | 1. A computer-implemented method comprising: providing a Web page comprising a plurality of content to be displayed on a computer display device using a Web browser; in response to a selection of a portion of a content by a first user using a pointing device, providing a first view of a pop-up toolbox to the first user, wherein the first view of the pop-up toolbox comprises a plurality of user-selectable options; in response to a selection of a first user-selectable option by the first user using the pointing device, providing a second view of the pop-up toolbox to the first user, wherein the second view of the toolbox comprises a suggestion text entry box; receiving at a server input from the first user comprising a first suggestion inputted into the suggestion text entry box; and storing the first suggestion and position information on the first suggestion in a suggestions database at the server, wherein the plurality of content is stored in a separate database and the position information comprises information identifying the content and information identifying a location of the selected portion within the content permitting a second user to select at least a portion of the content selected by the first user; and permitting the second user to input a second suggestion for the at least a portion of the content selected by the first user. | 1. A computer-implemented method comprising: providing a Web page comprising a plurality of content to be displayed on a computer display device using a Web browser; in response to a selection of a portion of a content by a first user using a pointing device, providing a first view of a pop-up toolbox to the first user, wherein the first view of the pop-up toolbox comprises a plurality of user-selectable options; in response to a selection of a first user-selectable option by the first user using the pointing device, providing a second view of the pop-up toolbox to the first user, wherein the second view of the toolbox comprises a suggestion text entry box; receiving at a server input from the first user comprising a first suggestion inputted into the suggestion text entry box; and storing the first suggestion and position information on the first suggestion in a suggestions database at the server, wherein the plurality of content is stored in a separate database and the position information comprises information identifying the content and information identifying a location of the selected portion within the content permitting a second user to select at least a portion of the content selected by the first user; and permitting the second user to input a second suggestion for the at least a portion of the content selected by the first user. 12. The computer-implemented method of claim 1 wherein the permitting the second user to input a second suggestion comprises: indicating to an owner of the Web page that the second suggestion is associated with the second user. | 0.671014 |
7,657,544 | 1 | 2 | 1. A storage medium readable by a computer, the storage medium storing a program for causing a computer connected to a document database where document files are categorized and stored into any of predefined category bins to perform a process comprising: selecting at least some of document files stored on the document database and categorized in object category bins as representative document files for each of the object category bins, the document files being selected as representative document files based on similarity to a document file to be categorized, the object category bins being at least part of the category bins, the representative document files comprising a proper subset of the document files categorized in each respective object category bin associated with the representative document files; and presenting information extracted from the selected representative document files to a user when the user queries contents of an object category bin of the object category bins without entering the object category bin, wherein a guide caption is presented describing keywords extracted from a file and obtained by a document summarizing process, and a highlight contrast to a background for guide captions of files having greater weights regarding access histories is increased. | 1. A storage medium readable by a computer, the storage medium storing a program for causing a computer connected to a document database where document files are categorized and stored into any of predefined category bins to perform a process comprising: selecting at least some of document files stored on the document database and categorized in object category bins as representative document files for each of the object category bins, the document files being selected as representative document files based on similarity to a document file to be categorized, the object category bins being at least part of the category bins, the representative document files comprising a proper subset of the document files categorized in each respective object category bin associated with the representative document files; and presenting information extracted from the selected representative document files to a user when the user queries contents of an object category bin of the object category bins without entering the object category bin, wherein a guide caption is presented describing keywords extracted from a file and obtained by a document summarizing process, and a highlight contrast to a background for guide captions of files having greater weights regarding access histories is increased. 2. The storage medium according to claim 1 , wherein the representative document files for each of the object category bins are selected based on access histories of the document files categorized in the object category bins. | 0.5 |
10,129,258 | 1 | 3 | 1. A system comprising: a processor; and a memory storing instructions configurable to cause: obtaining a plurality of documents for a web-based application, the web-based application comprising one or more of a plurality of custom components and one or more application programming interface (API) components; processing a document object model (DOM) corresponding to the web-based application, wherein the one or more custom components and the one or more API components are modeled in hierarchical form; and for each custom component: assigning a key to the custom component, the key constituting an object reference of the custom component such that the custom component is accessible only to other components capable of providing the key in accordance with one or more rules of capability security, identifying one or more accessible custom components for which the custom component is capable of providing a key assigned to the one or more accessible custom components, generating a virtual DOM for the custom component corresponding to the web-based application, wherein the custom component and the identified one or more accessible custom components are modeled in hierarchical form, and restricting access of the custom component to all inaccessible custom components for which the custom component is not capable of providing a key assigned to an inaccessible custom component. | 1. A system comprising: a processor; and a memory storing instructions configurable to cause: obtaining a plurality of documents for a web-based application, the web-based application comprising one or more of a plurality of custom components and one or more application programming interface (API) components; processing a document object model (DOM) corresponding to the web-based application, wherein the one or more custom components and the one or more API components are modeled in hierarchical form; and for each custom component: assigning a key to the custom component, the key constituting an object reference of the custom component such that the custom component is accessible only to other components capable of providing the key in accordance with one or more rules of capability security, identifying one or more accessible custom components for which the custom component is capable of providing a key assigned to the one or more accessible custom components, generating a virtual DOM for the custom component corresponding to the web-based application, wherein the custom component and the identified one or more accessible custom components are modeled in hierarchical form, and restricting access of the custom component to all inaccessible custom components for which the custom component is not capable of providing a key assigned to an inaccessible custom component. 3. The system of claim 1 , the instructions further configurable to cause: for each API component, determining whether the API component is a private API component or a public API component; and for each custom component: restricting access of the custom component to all private API components. | 0.5 |
9,729,924 | 14 | 17 | 14. A method comprising: combining, by a computing device, data describing at least two of linear content, non-linear content or managed content to produce a user interface that comprises a hierarchy of levels and that blends user-selectable content from the at least two of the linear content, the non-linear content or the managed content in at least two levels of the hierarchy of levels; and transmitting the user interface to one or more devices. | 14. A method comprising: combining, by a computing device, data describing at least two of linear content, non-linear content or managed content to produce a user interface that comprises a hierarchy of levels and that blends user-selectable content from the at least two of the linear content, the non-linear content or the managed content in at least two levels of the hierarchy of levels; and transmitting the user interface to one or more devices. 17. The method of claim 14 , wherein the transmitting the user interface to the one or more devices comprises broadcasting the user interface to the one or more devices. | 0.753644 |
9,471,706 | 5 | 14 | 5. A method to navigate through search results returned by a search query on unstructured or semi-structured data source, the search results being returned by a semantic organization upon receiving the search query and the search results being dynamically organized into categories and attributes in real-time, the method using an interface comprising at most a first user-engageable control dynamically populated with one of the categories and the attributes semantically related to the search query, and a second user-engageable control dynamically populated with filter values related to one of the categories or attributes, wherein a scope of the search results is responsive to a selection, by a user, of one of the categories or attributes which populate the first user-engageable control, and to a selection, by the user, of one of the filter values which populate the second user-engageable control, the method comprising: a) selecting one of the categories or attributes using the first user-engageable control; b) selecting one of the filter values using the second user-engageable control; and c) repeating a) and/or b), as necessary, to narrow the scope of the search results. | 5. A method to navigate through search results returned by a search query on unstructured or semi-structured data source, the search results being returned by a semantic organization upon receiving the search query and the search results being dynamically organized into categories and attributes in real-time, the method using an interface comprising at most a first user-engageable control dynamically populated with one of the categories and the attributes semantically related to the search query, and a second user-engageable control dynamically populated with filter values related to one of the categories or attributes, wherein a scope of the search results is responsive to a selection, by a user, of one of the categories or attributes which populate the first user-engageable control, and to a selection, by the user, of one of the filter values which populate the second user-engageable control, the method comprising: a) selecting one of the categories or attributes using the first user-engageable control; b) selecting one of the filter values using the second user-engageable control; and c) repeating a) and/or b), as necessary, to narrow the scope of the search results. 14. The method as claimed in claim 5 , wherein the method further comprises fetching words and links between the words related to the search query. | 0.78125 |
7,496,516 | 14 | 20 | 14. A computer program product comprising a computer usable storage medium including computer program logic stored therein that, when executed by a processor, causes the processor to perform a method comprising: receiving user input and information regarding a user from a communications subsystem; recognizing a voice command in the user input; requesting a dialog engine from a broker, wherein the broker is operable to distribute the processing load across a plurality of dialog engines; transmitting the recognized command to the dialog engine; retrieving information requested by the recognized command from a network via the dialog engine; converting the information from text to speech format when the retrieved information is in text format; and outputting the retrieved information to the user. | 14. A computer program product comprising a computer usable storage medium including computer program logic stored therein that, when executed by a processor, causes the processor to perform a method comprising: receiving user input and information regarding a user from a communications subsystem; recognizing a voice command in the user input; requesting a dialog engine from a broker, wherein the broker is operable to distribute the processing load across a plurality of dialog engines; transmitting the recognized command to the dialog engine; retrieving information requested by the recognized command from a network via the dialog engine; converting the information from text to speech format when the retrieved information is in text format; and outputting the retrieved information to the user. 20. The computer program product of claim 14 , wherein the method further comprises: instantiating a session object in response to the recognized command, wherein the session object performs one or more functions in the group of functions including: placing a second call; canceling a call; dropping one or more calls in the session; transferring a call; appending the prompt; playing accumulated prompts; and initiating voice recognition. | 0.5 |
8,838,617 | 10 | 11 | 10. A computer-readable storage medium whose contents, when executed by a computing system, cause the computing system perform operations of searching for recommended music using emotional information of music, the operations comprising: inputting a search condition that is used to search for recommended music; searching a music emotion database (DB), which stores information about emotional values including valence values and arousal values of respective pieces of music, for emotional value information corresponding to the input search condition; retrieving the emotional value information from the input search condition, the emotional value information including a valence value and an arousal value; extracting a combination of emotion ranks corresponding to the retrieved emotional value information by using an emotion model that includes information about mixed emotions corresponding to valence values and arousal values; searching the music emotion DB for music information corresponding to the extracted emotion ranks combination; and outputting a recommended music list including music information that corresponds to the extracted emotion ranks combination. | 10. A computer-readable storage medium whose contents, when executed by a computing system, cause the computing system perform operations of searching for recommended music using emotional information of music, the operations comprising: inputting a search condition that is used to search for recommended music; searching a music emotion database (DB), which stores information about emotional values including valence values and arousal values of respective pieces of music, for emotional value information corresponding to the input search condition; retrieving the emotional value information from the input search condition, the emotional value information including a valence value and an arousal value; extracting a combination of emotion ranks corresponding to the retrieved emotional value information by using an emotion model that includes information about mixed emotions corresponding to valence values and arousal values; searching the music emotion DB for music information corresponding to the extracted emotion ranks combination; and outputting a recommended music list including music information that corresponds to the extracted emotion ranks combination. 11. The computer-readable storage medium of claim 10 , wherein-outputting the recommended music list comprises: extracting a probability value condition corresponding to the emotional value information using the emotion model; searching the music information corresponding to the emotion ranks combination for music information satisfying the extracted probability value condition; and outputting a recommended music list including the music information satisfying the extracted probability value condition. | 0.612385 |
8,209,333 | 23 | 27 | 23. A method for providing contextually related content to a user, the method comprising: detecting an occurrence of a key phrase on a page of a site; transforming the occurrence of the key phrase on the page, as loaded by a browser on a user computing device, into a user-selectable display element that is selectable by a user to initiate a display of contextually related content, wherein the key phrase is transformed into the user-selectable display element based on a score generated for said key phrase, said score based at least partly on view counts of social media content items associated with the key phrase; and responding to user selection of the display element by displaying contextually related content in a panel on the page, said contextually related content including an advertisement associated with the key phrase and further including non-advertisement social media content associated with the key phrase, said panel generated on the page by execution by the browser of a browser-executable component loaded by the browser. | 23. A method for providing contextually related content to a user, the method comprising: detecting an occurrence of a key phrase on a page of a site; transforming the occurrence of the key phrase on the page, as loaded by a browser on a user computing device, into a user-selectable display element that is selectable by a user to initiate a display of contextually related content, wherein the key phrase is transformed into the user-selectable display element based on a score generated for said key phrase, said score based at least partly on view counts of social media content items associated with the key phrase; and responding to user selection of the display element by displaying contextually related content in a panel on the page, said contextually related content including an advertisement associated with the key phrase and further including non-advertisement social media content associated with the key phrase, said panel generated on the page by execution by the browser of a browser-executable component loaded by the browser. 27. The method of claim 23 , wherein the score is dependent upon a rate of change in popularity of the key phrase. | 0.82622 |
8,366,745 | 1 | 7 | 1. In a medical implant assembly having first and second bone attachment structures cooperating with a longitudinal connecting member, the improvement wherein the longitudinal connecting member comprises: a) an anchor member portion passing through and secured directly to the first bone attachment structure, the anchor member portion having a first width and having an integral core extension of reduced second width, the core extension extending from the anchor member portion along a substantially central axis of the longitudinal connecting member, the first and second widths being measured perpendicular to the central axis; b) a first elastic outer spacer, the core extension being received in the spacer, the spacer being positioned between the two bone attachment structures; c) a second elastic outer spacer, the core extension being received in the second spacer, the second spacer being more compressible than the first spacer, both the first and second spacers being pre-compressed prior to attachment of the assembly to the bone attachment structures; the second elastic outer spacer being located relative to the core extension so as to not be between the first and second bone attachment structures; and d) a substantially inelastic sleeve, the core extension being received through the sleeve and in slidable relationship therewith, the sleeve passing through and secured in the second bone attachment structure, the sleeve being disposed between the first and second pre-compressed spacers, the pre-compressed spacers exerting axial forces on the sleeve. | 1. In a medical implant assembly having first and second bone attachment structures cooperating with a longitudinal connecting member, the improvement wherein the longitudinal connecting member comprises: a) an anchor member portion passing through and secured directly to the first bone attachment structure, the anchor member portion having a first width and having an integral core extension of reduced second width, the core extension extending from the anchor member portion along a substantially central axis of the longitudinal connecting member, the first and second widths being measured perpendicular to the central axis; b) a first elastic outer spacer, the core extension being received in the spacer, the spacer being positioned between the two bone attachment structures; c) a second elastic outer spacer, the core extension being received in the second spacer, the second spacer being more compressible than the first spacer, both the first and second spacers being pre-compressed prior to attachment of the assembly to the bone attachment structures; the second elastic outer spacer being located relative to the core extension so as to not be between the first and second bone attachment structures; and d) a substantially inelastic sleeve, the core extension being received through the sleeve and in slidable relationship therewith, the sleeve passing through and secured in the second bone attachment structure, the sleeve being disposed between the first and second pre-compressed spacers, the pre-compressed spacers exerting axial forces on the sleeve. 7. The improvement of claim 1 wherein the anchor member portion has a substantially circular cross-section measured perpendicular to the axis. | 0.822055 |
9,785,954 | 6 | 8 | 6. An apparatus for generating recommended items for a current user in an unfamiliar domain, comprising: a reference user determining module configured to: select a plurality of candidate reference users sharing a user type with the current user in a reference domain, wherein the reference domain differs from the unfamiliar domain; calculate a plurality of user similarity indices for the plurality of candidate reference users, comprising calculating a user similarity index for a candidate reference user with respect to a reference domain and the current user, wherein the user similarity index is based at least in part on common behaviors between the current user and the candidate reference user in the reference domain, and is calculated according to history behavior data of a plurality of demarcated users in the unfamiliar domain and the reference domain, wherein the plurality of demarcated users are similar users in two or more domains that are different than the current user; and select the candidate reference user as a reference user in the reference domain, responsive to the user similarity index of the candidate reference user satisfying a user similarity index condition; a domain similarity determining module configured to determine a domain similarity index between the unfamiliar domain and the reference domain, wherein the domain similarity index is distinct from the user similarity index, and wherein the domain similarity index indicates a degree of similarity between the unfamiliar domain and the reference domain; and one or more computer processors configured to: calculate a user weight for the reference user with respect to the current user, wherein the user weight is calculated by multiplying the user similarity index by the domain similarity index; generate two or more candidate items in the unfamiliar domain for the current user according to history behavior data of other users, comprising at least the reference user, in the unfamiliar domain; assign an item weight to each of the two or more candidate items, wherein for each of the two or more candidate items, the item weight assigned is calculated by adding the user weights of the other users who are associated with the candidate item; and select, as the recommended items, a subset of the candidate items whose item weights meet an item weight condition. | 6. An apparatus for generating recommended items for a current user in an unfamiliar domain, comprising: a reference user determining module configured to: select a plurality of candidate reference users sharing a user type with the current user in a reference domain, wherein the reference domain differs from the unfamiliar domain; calculate a plurality of user similarity indices for the plurality of candidate reference users, comprising calculating a user similarity index for a candidate reference user with respect to a reference domain and the current user, wherein the user similarity index is based at least in part on common behaviors between the current user and the candidate reference user in the reference domain, and is calculated according to history behavior data of a plurality of demarcated users in the unfamiliar domain and the reference domain, wherein the plurality of demarcated users are similar users in two or more domains that are different than the current user; and select the candidate reference user as a reference user in the reference domain, responsive to the user similarity index of the candidate reference user satisfying a user similarity index condition; a domain similarity determining module configured to determine a domain similarity index between the unfamiliar domain and the reference domain, wherein the domain similarity index is distinct from the user similarity index, and wherein the domain similarity index indicates a degree of similarity between the unfamiliar domain and the reference domain; and one or more computer processors configured to: calculate a user weight for the reference user with respect to the current user, wherein the user weight is calculated by multiplying the user similarity index by the domain similarity index; generate two or more candidate items in the unfamiliar domain for the current user according to history behavior data of other users, comprising at least the reference user, in the unfamiliar domain; assign an item weight to each of the two or more candidate items, wherein for each of the two or more candidate items, the item weight assigned is calculated by adding the user weights of the other users who are associated with the candidate item; and select, as the recommended items, a subset of the candidate items whose item weights meet an item weight condition. 8. The apparatus according to claim 6 , wherein the reference user has scores for behaviors common to the current user that satisfy a common behavior score condition in the reference domain. | 0.90566 |
8,949,263 | 12 | 16 | 12. The method of claim 1 , further comprising: producing a second corpus, containing statements within a second temporal range that is different from a first temporal range of the statements of the first corpus; applying frame extraction, to the second corpus, in order to attempt to identify, for each statement of the corpus, an object and a sentiment expressed about the object; identifying a second object-specific corpus, that is a subset of the second corpus, where all the statements of the second object-specific corpus are about the same first object as the first object-specific corpus; categorizing the sentiment of each statement, of the second object-specific corpus; determining a net metric value as a function of the categorization of the second object-specific corpus; and producing a second graphical representation, of the second object-specific corpus, that is placed according to the second net metric. | 12. The method of claim 1 , further comprising: producing a second corpus, containing statements within a second temporal range that is different from a first temporal range of the statements of the first corpus; applying frame extraction, to the second corpus, in order to attempt to identify, for each statement of the corpus, an object and a sentiment expressed about the object; identifying a second object-specific corpus, that is a subset of the second corpus, where all the statements of the second object-specific corpus are about the same first object as the first object-specific corpus; categorizing the sentiment of each statement, of the second object-specific corpus; determining a net metric value as a function of the categorization of the second object-specific corpus; and producing a second graphical representation, of the second object-specific corpus, that is placed according to the second net metric. 16. The method of claim 12 , wherein producing a second graphical representation further comprises: producing a graphical representation additional to the first graphical representation. | 0.660584 |
8,036,937 | 9 | 16 | 9. An article of manufacture comprising at least one data storage device having one or more computer programs stored thereon and operable on one or more computing systems to: normalize a plurality of keywords received from a source, the source being from the group: a search query and a product listing; filter the normalized plurality of keywords against one or more keyword filtration lists; produce site-specific variants of the filtered plurality of keywords; associate a plurality of levels of dimension data with each of the plurality of keywords, the plurality of levels of dimension data including information indicative of a probability that a keyword of the plurality of keywords belongs to a particular product category in a product category hierarchy, the plurality of levels of dimension data including keyword clustering dimension data, the keyword clustering dimension data including information indicative of a probability that a keyword of the plurality of keywords belongs to a particular keyword cluster of a plurality of pre-defined keyword clusters, the plurality of levels of dimension data including keyword traffic dimension data, the keyword traffic dimension data including information indicative of a probability that a keyword of the plurality of keywords was trafficked by a particular search engine, wherein the probability that a keyword of the plurality of keywords was trafficked by a particular search engine is maintained for each of a plurality of search engines, the keyword traffic dimension data including information indicative of a probability that a keyword of the plurality of keywords will achieve a predicted revenue per click level, the keyword traffic dimension data including information indicative of a value related to confirmed registered users, the keyword traffic dimension data including information indicative of a landing page related to a particular cluster of keywords; define a time period of measurement for a metric corresponding to the plurality of levels of dimension data; and store the processed plurality of keywords and dimension data in a keyword database and select at least one keyword from the stored processed plurality of keywords according to the dimension data in the keyword database. | 9. An article of manufacture comprising at least one data storage device having one or more computer programs stored thereon and operable on one or more computing systems to: normalize a plurality of keywords received from a source, the source being from the group: a search query and a product listing; filter the normalized plurality of keywords against one or more keyword filtration lists; produce site-specific variants of the filtered plurality of keywords; associate a plurality of levels of dimension data with each of the plurality of keywords, the plurality of levels of dimension data including information indicative of a probability that a keyword of the plurality of keywords belongs to a particular product category in a product category hierarchy, the plurality of levels of dimension data including keyword clustering dimension data, the keyword clustering dimension data including information indicative of a probability that a keyword of the plurality of keywords belongs to a particular keyword cluster of a plurality of pre-defined keyword clusters, the plurality of levels of dimension data including keyword traffic dimension data, the keyword traffic dimension data including information indicative of a probability that a keyword of the plurality of keywords was trafficked by a particular search engine, wherein the probability that a keyword of the plurality of keywords was trafficked by a particular search engine is maintained for each of a plurality of search engines, the keyword traffic dimension data including information indicative of a probability that a keyword of the plurality of keywords will achieve a predicted revenue per click level, the keyword traffic dimension data including information indicative of a value related to confirmed registered users, the keyword traffic dimension data including information indicative of a landing page related to a particular cluster of keywords; define a time period of measurement for a metric corresponding to the plurality of levels of dimension data; and store the processed plurality of keywords and dimension data in a keyword database and select at least one keyword from the stored processed plurality of keywords according to the dimension data in the keyword database. 16. The article of manufacture as claimed in claim 9 being further operable to prune keywords from the keyword database that are not likely to be valuable. | 0.709738 |
9,251,180 | 8 | 13 | 8. A computer program product for supplementing structured information within a data system for entities based on unstructured data comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising computer readable program code configured to: analyze documents with unstructured data specifying two or more entities of the structured information and interactions between those two or more entities; identify from the interactions within the unstructured data of the documents one or more relationships between entities of the structured information; extract attribute values from the unstructured data for one or more entities of the structured information based on a comparison of the unstructured data with one or more dictionaries each including values for a corresponding attribute of an entity within the data system, wherein extracting attribute values from the unstructured data includes: generating tokens from the unstructured data and comparing the tokens to the values within the one or more dictionaries, wherein at least one value within a dictionary includes a plurality of tokens; retrieve entity records with structured information from the data system based on the extracted attribute values; construct entity references for corresponding one or more entities of the data system based on a comparison of the retrieved entity records and the extracted attribute values; link the entity references to the corresponding one or more entities within the data system to supplement the structured information for the corresponding one or more entities with information extracted from the unstructured data, wherein the entity references include extracted attributes from the unstructured data for corresponding linked entities; and link entities of the structured information to each other within the structured information to indicate related entities based on the one or more relationships between those entities identified from the interactions specified within the unstructured data of the documents. | 8. A computer program product for supplementing structured information within a data system for entities based on unstructured data comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising computer readable program code configured to: analyze documents with unstructured data specifying two or more entities of the structured information and interactions between those two or more entities; identify from the interactions within the unstructured data of the documents one or more relationships between entities of the structured information; extract attribute values from the unstructured data for one or more entities of the structured information based on a comparison of the unstructured data with one or more dictionaries each including values for a corresponding attribute of an entity within the data system, wherein extracting attribute values from the unstructured data includes: generating tokens from the unstructured data and comparing the tokens to the values within the one or more dictionaries, wherein at least one value within a dictionary includes a plurality of tokens; retrieve entity records with structured information from the data system based on the extracted attribute values; construct entity references for corresponding one or more entities of the data system based on a comparison of the retrieved entity records and the extracted attribute values; link the entity references to the corresponding one or more entities within the data system to supplement the structured information for the corresponding one or more entities with information extracted from the unstructured data, wherein the entity references include extracted attributes from the unstructured data for corresponding linked entities; and link entities of the structured information to each other within the structured information to indicate related entities based on the one or more relationships between those entities identified from the interactions specified within the unstructured data of the documents. 13. The computer program product of claim 8 , wherein linking the entity references includes: merging the entity references with records of the corresponding one or more entities within the data system. | 0.712251 |
8,527,446 | 6 | 9 | 6. An information handling system comprising: one or more processors; a memory accessible by at least one of the processors; a nonvolatile storage area accessible by at least one of the processors; a set of instructions stored in the memory and executed by at least one of the processors in order to perform actions for managing a plurality of rules, wherein the plurality of rules include one or more native rules and one or more canonical rules, the actions including: selecting one or more business terms, wherein each of the one or more selected business terms corresponds to one or more standardized business definitions; identifying one or more data structures utilized by a first enforcement system that are equivalent to the one or more selected business terms; identifying one of the one or more native rules utilized by the first enforcement system that includes at least one of the one or more equivalent data structures, the identified native rule written in a first enforcement system-specific format; and creating a mapping entry that maps the identified native rule to a selected one of the canonical rules, wherein the selected canonical rule includes one or more of the one more selected business terms, and wherein the selected canonical rule is written in a canonical format that is independent from the first enforcement system-specific format. | 6. An information handling system comprising: one or more processors; a memory accessible by at least one of the processors; a nonvolatile storage area accessible by at least one of the processors; a set of instructions stored in the memory and executed by at least one of the processors in order to perform actions for managing a plurality of rules, wherein the plurality of rules include one or more native rules and one or more canonical rules, the actions including: selecting one or more business terms, wherein each of the one or more selected business terms corresponds to one or more standardized business definitions; identifying one or more data structures utilized by a first enforcement system that are equivalent to the one or more selected business terms; identifying one of the one or more native rules utilized by the first enforcement system that includes at least one of the one or more equivalent data structures, the identified native rule written in a first enforcement system-specific format; and creating a mapping entry that maps the identified native rule to a selected one of the canonical rules, wherein the selected canonical rule includes one or more of the one more selected business terms, and wherein the selected canonical rule is written in a canonical format that is independent from the first enforcement system-specific format. 9. The information handling system of claim 6 wherein the set of instructions further performs actions that include: analyzing a data pattern at the first enforcement system; generating a proposed rule based upon the analyzing, wherein the proposed rule is not included in a rule repository corresponding to the first enforcement system; and including the proposed rule in the plurality of rules. | 0.832629 |
9,948,663 | 1 | 5 | 1. A computer-implemented method for predicting security threat attacks, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying candidate security threat targets with latent attributes that describe features of the candidate security threat targets; identifying historical attack data that describes which of the candidate security threat targets experienced an actual security threat attack; determining, by a software security prediction program, a similarity relationship between latent attributes of at least one specific candidate security threat target and latent attributes of the candidate security threat targets that experienced the actual security threat attack according to the historical attack data by analyzing a matrix that indicates that the actual security threat attack targeted the candidate security threat targets by populating a respective entry of the matrix at each intersection between a vector of the matrix that corresponds to the actual security threat attack and each vector of the matrix that corresponds to the candidate security threat targets that experienced the actual security threat attack; predicting by the software security prediction program based on the determined similarity relationship, that the specific candidate security threat target will experience a future security threat attack; and performing, by the software security prediction program, at least one remedial action to protect the specific candidate security threat target in response to predicting the future security threat attack, wherein the candidate security threat targets comprise enterprise organizations that include customers of a vendor of the software security prediction program. | 1. A computer-implemented method for predicting security threat attacks, at least a portion of the method being performed by a computing device comprising at least one processor, the method comprising: identifying candidate security threat targets with latent attributes that describe features of the candidate security threat targets; identifying historical attack data that describes which of the candidate security threat targets experienced an actual security threat attack; determining, by a software security prediction program, a similarity relationship between latent attributes of at least one specific candidate security threat target and latent attributes of the candidate security threat targets that experienced the actual security threat attack according to the historical attack data by analyzing a matrix that indicates that the actual security threat attack targeted the candidate security threat targets by populating a respective entry of the matrix at each intersection between a vector of the matrix that corresponds to the actual security threat attack and each vector of the matrix that corresponds to the candidate security threat targets that experienced the actual security threat attack; predicting by the software security prediction program based on the determined similarity relationship, that the specific candidate security threat target will experience a future security threat attack; and performing, by the software security prediction program, at least one remedial action to protect the specific candidate security threat target in response to predicting the future security threat attack, wherein the candidate security threat targets comprise enterprise organizations that include customers of a vendor of the software security prediction program. 5. The method of claim 1 , wherein determining the similarity relationship comprises: identifying an additional candidate security threat target that stored a cluster of benign files and that experienced a same security threat attack as the predicted future security threat attack; and determining that the specific candidate security threat target also stored the cluster of benign files. | 0.637127 |
9,710,435 | 11 | 12 | 11. The apparatus of claim 2 and wherein: the objects comprise host objects and guest objects; the single computer readable data structure is capable of representation by an object-field diagram comprising a primary sequence of said objects, subsequences of which are organized into the fields, and for each non-primitive object its fields are ordered with respect to an infix entry sequence; the object field diagram further identifies the slots; indices are assigned to the objects which give the order of the objects as entered by the user using the infix entry sequence; and the infix entry process defines a slot sequence of the slots. | 11. The apparatus of claim 2 and wherein: the objects comprise host objects and guest objects; the single computer readable data structure is capable of representation by an object-field diagram comprising a primary sequence of said objects, subsequences of which are organized into the fields, and for each non-primitive object its fields are ordered with respect to an infix entry sequence; the object field diagram further identifies the slots; indices are assigned to the objects which give the order of the objects as entered by the user using the infix entry sequence; and the infix entry process defines a slot sequence of the slots. 12. The apparatus of claim 11 and wherein: each object has an associated object slot, an object and its associated object slot defining an object segment; for each field there is a field slot at one end of the field; and for any object in the field the object slot is on the side of the object segment that is facing away from the field slot. | 0.729858 |
8,606,806 | 3 | 4 | 3. The computer-implemented method of claim 1 , further comprising, for a path expression with an explicit name test entering into a wildcard section, identifying whether the path selects an element or attribute that is known in a static typing context, or the path selects an element or attribute that is considered as any type. | 3. The computer-implemented method of claim 1 , further comprising, for a path expression with an explicit name test entering into a wildcard section, identifying whether the path selects an element or attribute that is known in a static typing context, or the path selects an element or attribute that is considered as any type. 4. The computer implemented method of claim 3 further comprising supplying type information and type inference rules. | 0.5 |
8,939,837 | 1 | 8 | 1. A system comprising: a memory to store computer instructions; and a processor coupled with the memory, wherein the processor, responsive to executing the computer instructions performs operations comprising: receiving a signal generated in response to a user input at a first accessory operably coupled with a first computing device, wherein the first computing device is programmed to present a video game; identifying matching words between the signal and a plurality of words stored in a multi-lingual library; and providing an audio signal to a second accessory for presentation to an intended recipient, wherein the audio signal is generated based on the received signal using the identified matching words, and wherein the audio signal is associated with the video game. | 1. A system comprising: a memory to store computer instructions; and a processor coupled with the memory, wherein the processor, responsive to executing the computer instructions performs operations comprising: receiving a signal generated in response to a user input at a first accessory operably coupled with a first computing device, wherein the first computing device is programmed to present a video game; identifying matching words between the signal and a plurality of words stored in a multi-lingual library; and providing an audio signal to a second accessory for presentation to an intended recipient, wherein the audio signal is generated based on the received signal using the identified matching words, and wherein the audio signal is associated with the video game. 8. The system of claim 1 , wherein the second accessory is operably coupled with the first computing device, and wherein the audio signal is presented as synthesized voice content. | 0.759358 |
8,041,120 | 1 | 8 | 1. A computer-readable storage medium having computer-executable instructions, which when executed perform steps, comprising: a) extracting features from a selected sample of a plurality of samples of digital ink training data, wherein the digital ink training data corresponds to digital ink representative of at least two different types of digital ink input, each of the plurality of samples belong to one of a plurality of classes having combined feature data, and each of the plurality of samples is associated with a label comprising a recognition value; b) processing a feature dataset of the selected sample into a recognition model by adjusting the combined feature data of the class to which the selected sample belongs and maintaining data representative of the features extracted from the selected sample in association with the recognition value associated with the selected sample; c) selecting another sample from the plurality of samples and repeating steps a) and b) until each sample of the plurality of samples has been processed; and d) providing a unified recognizer that recognizes an input item of one of the at least two different types of digital ink input without mode selection or recognition parameter input, the input item being recognized by extracting features of the input item and determining a matching class having combined feature data that best match features of the input item, and outputting a matching recognition value associated with the matching class. | 1. A computer-readable storage medium having computer-executable instructions, which when executed perform steps, comprising: a) extracting features from a selected sample of a plurality of samples of digital ink training data, wherein the digital ink training data corresponds to digital ink representative of at least two different types of digital ink input, each of the plurality of samples belong to one of a plurality of classes having combined feature data, and each of the plurality of samples is associated with a label comprising a recognition value; b) processing a feature dataset of the selected sample into a recognition model by adjusting the combined feature data of the class to which the selected sample belongs and maintaining data representative of the features extracted from the selected sample in association with the recognition value associated with the selected sample; c) selecting another sample from the plurality of samples and repeating steps a) and b) until each sample of the plurality of samples has been processed; and d) providing a unified recognizer that recognizes an input item of one of the at least two different types of digital ink input without mode selection or recognition parameter input, the input item being recognized by extracting features of the input item and determining a matching class having combined feature data that best match features of the input item, and outputting a matching recognition value associated with the matching class. 8. The computer-readable storage medium of claim 1 having further computer-executable instructions, which when executed perform steps, comprising: defining a dataset of items the unified recognizer will recognize, including customized data items. | 0.75 |
8,589,162 | 1 | 14 | 1. A method for speech recognition, the method comprising: for an expected input string comprising a plurality of expected string segments comprising a first expected string segment and a second expected string segment, receiving a first speech segment for the first expected string segment and a second speech segment for the second expected string segment, wherein the first speech segment is different from the second speech segment; performing speech recognition separately on the first speech segment and the second speech segment, wherein said performing speech recognition comprises generating a first segment n-best list and a second segment n-best list, the first segment n-best list comprising n highest confidence score results of said speech recognition on the first speech segment and the second segment n-best list comprising n highest confidence score results of said speech recognition on the second speech segment, where n comprises at least one integer; generating a global n-best list corresponding to said expected input string, wherein the global n-best list comprises a plurality of results each generated at least in part by combining a result from said first segment n-best list with a result from said second segment n-best list; and determining a final global speech recognition result corresponding to said expected input string, wherein said determining said final global speech recognition result comprises pruning results of said global n-best list utilizing a pruning criterion. | 1. A method for speech recognition, the method comprising: for an expected input string comprising a plurality of expected string segments comprising a first expected string segment and a second expected string segment, receiving a first speech segment for the first expected string segment and a second speech segment for the second expected string segment, wherein the first speech segment is different from the second speech segment; performing speech recognition separately on the first speech segment and the second speech segment, wherein said performing speech recognition comprises generating a first segment n-best list and a second segment n-best list, the first segment n-best list comprising n highest confidence score results of said speech recognition on the first speech segment and the second segment n-best list comprising n highest confidence score results of said speech recognition on the second speech segment, where n comprises at least one integer; generating a global n-best list corresponding to said expected input string, wherein the global n-best list comprises a plurality of results each generated at least in part by combining a result from said first segment n-best list with a result from said second segment n-best list; and determining a final global speech recognition result corresponding to said expected input string, wherein said determining said final global speech recognition result comprises pruning results of said global n-best list utilizing a pruning criterion. 14. The method according to claim 1 , wherein generating a global n-best list comprises: generating a first result of the global n-best list by concatenating a first result of the first segment n-best list with a second result of the second segment n-best list; and generating a second result of the global n-best list by concatenating the first result of the first segment n-list with a third result of the second segment n-best list. | 0.557927 |
9,122,950 | 13 | 14 | 13. The method of claim 1 , wherein each atlas image comprises a plurality of points, each atlas image point is associated with a label indicative of whether the associated atlas image point is classified as the at least one structure; and wherein registering the subject image with the plurality of the atlas images associates the registered subject image points with the labels that are associated with the atlas image points that were mapped to the registered subject image points; and wherein generating the first data comprises combining the labels associated with the registered subject image points according to a label fusion technique. | 13. The method of claim 1 , wherein each atlas image comprises a plurality of points, each atlas image point is associated with a label indicative of whether the associated atlas image point is classified as the at least one structure; and wherein registering the subject image with the plurality of the atlas images associates the registered subject image points with the labels that are associated with the atlas image points that were mapped to the registered subject image points; and wherein generating the first data comprises combining the labels associated with the registered subject image points according to a label fusion technique. 14. The method of claim 13 wherein the generated first data comprises a plurality of first data labels associated with a plurality of the subject image points, each first data label is indicative whether its associated subject image point belongs to the at least one structure, the generated second data comprises a plurality of second data labels associated with a plurality of the subject image points, and each second data label is indicative whether its associated subject image point belongs to the at least one structure, and wherein combining the labels associated with the registered subject image points comprises combining, for at least the subject image points for which their associated first data labels and second data labels are in disagreement as to whether the associated subject image points belong to the at least one structure, the associated first data and second data labels according to a label fusion technique. | 0.5 |
8,639,679 | 1 | 3 | 1. A computer-implemented method, comprising: receiving an input entered in a search engine query input field by a user; selecting one or more second query suggestions, wherein the second query suggestions are search queries previously submitted by other users of the search engine and not by the user; selecting one or more first query suggestions, wherein the first query suggestions are search queries previously submitted by the user; determining a respective score for each first query suggestion and each second query suggestion, wherein determining a respective score for each first query suggestion comprises determining the respective score for each first query suggestion based on one or more of the following: a number of times the first query suggestion was submitted as a query by the user, a frequency of submission of the first query suggestion as a query in a specified time period by the user before receiving the input, a time of the most recent submission of the first query suggestion as a query by the user, or a multiplication of the number of times the first query suggestion was submitted as a query by the user with the frequency of submission of the first query suggestion as a query in a specified time period by the user before receiving the input; ranking the first query suggestions and the second query suggestions according to the respective scores; identifying from the first query suggestions and second query suggestions one or more selectable suggestions to the input based on the ranking; and providing the one or more selectable suggestions for display in a user interface for possible selection by the user, wherein the first query suggestions in the selectable suggestions are rendered in the user interface with visual features distinct from visual features of the second query suggestions in the selectable suggestions. | 1. A computer-implemented method, comprising: receiving an input entered in a search engine query input field by a user; selecting one or more second query suggestions, wherein the second query suggestions are search queries previously submitted by other users of the search engine and not by the user; selecting one or more first query suggestions, wherein the first query suggestions are search queries previously submitted by the user; determining a respective score for each first query suggestion and each second query suggestion, wherein determining a respective score for each first query suggestion comprises determining the respective score for each first query suggestion based on one or more of the following: a number of times the first query suggestion was submitted as a query by the user, a frequency of submission of the first query suggestion as a query in a specified time period by the user before receiving the input, a time of the most recent submission of the first query suggestion as a query by the user, or a multiplication of the number of times the first query suggestion was submitted as a query by the user with the frequency of submission of the first query suggestion as a query in a specified time period by the user before receiving the input; ranking the first query suggestions and the second query suggestions according to the respective scores; identifying from the first query suggestions and second query suggestions one or more selectable suggestions to the input based on the ranking; and providing the one or more selectable suggestions for display in a user interface for possible selection by the user, wherein the first query suggestions in the selectable suggestions are rendered in the user interface with visual features distinct from visual features of the second query suggestions in the selectable suggestions. 3. The method of claim 1 , wherein determining the respective score for each of the second query suggestions comprises: determining the respective score for each second query suggestions based on one or more of the following: a number of times the second query suggestion was submitted as a query, a frequency of submission of the second query suggestion as a query in a specified time period before receiving the input, a time of the most recent submission of the second query suggestion as a query, or a multiplication of the number of times the second query suggestion was submitted as a query with the frequency of submission of the second query suggestion as a query in a specified time period before receiving the input. | 0.5 |
8,539,061 | 1 | 2 | 1. A computer-based web service registry system comprising: a web service registry that, based on a knowledge base comprising a plurality of knowledge base models, registers and discovers a plurality of web services, and rejects for publication each of a plurality of non-compliant web services failing to comply with the plurality of knowledge base models, wherein each of the knowledge base models comprises both a semantic specification providing a semantic meaning for an associated web service and a syntactic specification for the associated web service separate from the semantic specification, and wherein the web service registry provides service discovery based on the semantic specifications of the plurality of knowledge base models, and provides dynamic service invocation based on the syntactic specifications of the plurality of knowledge base models; a control system with a computer processor that identifies the plurality of non-compliant web services before they publish to the web service registry; and an interface that receives a request from a service provider to develop a new web service not complying with the plurality of knowledge base models, wherein the web service registry updates the knowledge base in response to the request by including in the knowledge base a new knowledge base model for the new web service, the new knowledge base model comprising a new semantic specification and a new syntactic specification, wherein the interface presents the service provider with the new knowledge base model upon updating the knowledge base. | 1. A computer-based web service registry system comprising: a web service registry that, based on a knowledge base comprising a plurality of knowledge base models, registers and discovers a plurality of web services, and rejects for publication each of a plurality of non-compliant web services failing to comply with the plurality of knowledge base models, wherein each of the knowledge base models comprises both a semantic specification providing a semantic meaning for an associated web service and a syntactic specification for the associated web service separate from the semantic specification, and wherein the web service registry provides service discovery based on the semantic specifications of the plurality of knowledge base models, and provides dynamic service invocation based on the syntactic specifications of the plurality of knowledge base models; a control system with a computer processor that identifies the plurality of non-compliant web services before they publish to the web service registry; and an interface that receives a request from a service provider to develop a new web service not complying with the plurality of knowledge base models, wherein the web service registry updates the knowledge base in response to the request by including in the knowledge base a new knowledge base model for the new web service, the new knowledge base model comprising a new semantic specification and a new syntactic specification, wherein the interface presents the service provider with the new knowledge base model upon updating the knowledge base. 2. The computer-based web service registry system of claim 1 , the control system that further identifies and removes inoperative web services from the web service registry. | 0.729688 |
8,624,898 | 14 | 16 | 14. A method of defining a component including a plurality of digital assets, the method comprising: receiving a specification of digital assets; receiving a set of graph link types defining a set of types of links between digital assets; parsing the specification of digital assets to identify digital assets associated with a component; creating graph nodes corresponding with the identified digital assets; parsing the specification of digital assets to identify digital asset relationships between the identified digital assets; classifying the identified digital asset relationships using the set of graph link types, such that each of the identified digital asset relationships is associated with at least one of the set of graph link types; and creating, by operation of one or more computer processors, a typed dependency graph representing the component, wherein the typed dependency graph includes typed graph links connecting the graph nodes and corresponding with the identified digital asset links between the identified digital assets; wherein the typed graph links are associated with the graph link types of their corresponding identified digital asset relationships; wherein the typed dependency graph includes a root graph node representing the component and connected with a set of typed graph links associated with each of the set of graph link types; wherein each digital asset is associated with a type mapping that is selected from a group consisting of reference-based mapping, structure-based mapping, and software tool-based mapping; and wherein each graph link type within the set of graph link types is selected from a group consisting of one-way digital asset dependencies, two-way digital asset dependencies, digital asset version relationships, digital asset aggregation relationships, and tool/digital asset dependencies. | 14. A method of defining a component including a plurality of digital assets, the method comprising: receiving a specification of digital assets; receiving a set of graph link types defining a set of types of links between digital assets; parsing the specification of digital assets to identify digital assets associated with a component; creating graph nodes corresponding with the identified digital assets; parsing the specification of digital assets to identify digital asset relationships between the identified digital assets; classifying the identified digital asset relationships using the set of graph link types, such that each of the identified digital asset relationships is associated with at least one of the set of graph link types; and creating, by operation of one or more computer processors, a typed dependency graph representing the component, wherein the typed dependency graph includes typed graph links connecting the graph nodes and corresponding with the identified digital asset links between the identified digital assets; wherein the typed graph links are associated with the graph link types of their corresponding identified digital asset relationships; wherein the typed dependency graph includes a root graph node representing the component and connected with a set of typed graph links associated with each of the set of graph link types; wherein each digital asset is associated with a type mapping that is selected from a group consisting of reference-based mapping, structure-based mapping, and software tool-based mapping; and wherein each graph link type within the set of graph link types is selected from a group consisting of one-way digital asset dependencies, two-way digital asset dependencies, digital asset version relationships, digital asset aggregation relationships, and tool/digital asset dependencies. 16. The method of claim 14 , wherein the specification of digital assets includes digital asset database records. | 0.581481 |
5,546,107 | 7 | 27 | 7. A method according to claim 1 wherein said matching step b comprises the step of: building an isomorphism between two subsets of 0-cells by several successive runs of different filtering procedures which reject certain potential matches if they are recognized as invalid. | 7. A method according to claim 1 wherein said matching step b comprises the step of: building an isomorphism between two subsets of 0-cells by several successive runs of different filtering procedures which reject certain potential matches if they are recognized as invalid. 27. A method according to claim 7 comprising the step of: a. determining which factor-2-cells are isomorphic; and b. storing isomorphic factor-2-cells in a so-called file of wards. | 0.827916 |
7,694,272 | 7 | 8 | 7. The method of claim 2 , wherein: some of said process models further contain a reference to a database table (process table); at least some of the sub data models of data models of said process models are marked as interesting fields; and each of said interesting fields further contains a reference to a column of said process table. | 7. The method of claim 2 , wherein: some of said process models further contain a reference to a database table (process table); at least some of the sub data models of data models of said process models are marked as interesting fields; and each of said interesting fields further contains a reference to a column of said process table. 8. The method of claim 7 , wherein: a selection condition of an SQL query (addressing clause) can be attached to an input slot of said process models to select matching instances of said process models each time data is to be received by said instances through said input slot; said addressing clause is defined in terms of a matching condition between the interesting fields of said process models and the data models of said data to be received through said input slot. | 0.5 |
8,001,469 | 1 | 10 | 1. A method comprising: receiving a task flow that describes operations of a dialog system that provides synthesized speech responses to spoken user input by a caller; generating a script that is a formal description of the task flow; automatically generating a graphical user interface (GUI) from the script, the GUI consisting of templates for control of the dialog system, generation of context-dependent synthesized speech prompts, and real-time collection and annotating of dialog data during a live dialog between only the dialog system and the caller to the dialog system, the GUI comprising a first portion for input of caller provided information, a second portion comprising an output control panel for control of the synthesized speech prompts by a human operator, a third portion providing status of a current task within the task flow, and a fourth portion providing an graphical representation of the task flow; and detecting the presence of an abnormality in speech processing during the task flow and automatically switching control to the human operator to allow direct interaction with the caller to correct the abnormality. | 1. A method comprising: receiving a task flow that describes operations of a dialog system that provides synthesized speech responses to spoken user input by a caller; generating a script that is a formal description of the task flow; automatically generating a graphical user interface (GUI) from the script, the GUI consisting of templates for control of the dialog system, generation of context-dependent synthesized speech prompts, and real-time collection and annotating of dialog data during a live dialog between only the dialog system and the caller to the dialog system, the GUI comprising a first portion for input of caller provided information, a second portion comprising an output control panel for control of the synthesized speech prompts by a human operator, a third portion providing status of a current task within the task flow, and a fourth portion providing an graphical representation of the task flow; and detecting the presence of an abnormality in speech processing during the task flow and automatically switching control to the human operator to allow direct interaction with the caller to correct the abnormality. 10. The method of claim 1 , wherein the formal description includes memory allocations for maintaining state of the interactive system. | 0.72561 |
7,765,208 | 1 | 4 | 1. A method implemented at a computing device having a processor, the method comprising: processing, by the processor of the computing device, a plurality of items to extract a plurality of keywords contained in the items, the processing including forming two or more of the plurality of keywords into keyword phrases, wherein the processing is performed at least in part based on a relative closeness of the plurality of keywords, one to another, the relative closeness partially defining a relevancy of one of said items to another of said items; forming a plurality of groupings of the keywords based on the relative closeness; combining the plurality of groupings to build balanced keyword hierarchies that comprise a predetermined number of balanced top-level islands, the combining comprising: organizing the plurality of groupings to create a plurality of small islands based on the relative closeness of the plurality of groupings; reducing number of the plurality of small islands to form the predetermined number of top-level hierarchical islands, the reducing comprising: combining the plurality of small islands to multiple high-level islands each having a hierarchy of a subset of the plurality of small islands, the multiple high-level islands having at least a first high-level island and a second high-level island; determining that a set of small islands to be combined to the first high-level island will cause the first high-level island to include an unbalanced number of small islands; maintaining the first high-level island balanced by moving the set of small islands to be combined to the second high-level island, wherein the second high-level island has less closeness value than the first high-level island, and repeating the combining, determining and maintaining until the predetermined number of top-level hierarchical islands are formed; outputting one or more of the predetermined number of top-level hierarchical islands for display on a display device as arranged in one or more hierarchies such that at least one of the plurality of keywords is selectable on the display device, wherein the one or more of the predetermined number of top-level hierarchical islands include the keyword phrases; receiving, from a user input via an input device, a selection of one of the plurality of keyword phrases; and navigating, at the computing device based on the selection, to a subset of the plurality of items that: are configured as emails; and include or relate to the one of the plurality of keywords. | 1. A method implemented at a computing device having a processor, the method comprising: processing, by the processor of the computing device, a plurality of items to extract a plurality of keywords contained in the items, the processing including forming two or more of the plurality of keywords into keyword phrases, wherein the processing is performed at least in part based on a relative closeness of the plurality of keywords, one to another, the relative closeness partially defining a relevancy of one of said items to another of said items; forming a plurality of groupings of the keywords based on the relative closeness; combining the plurality of groupings to build balanced keyword hierarchies that comprise a predetermined number of balanced top-level islands, the combining comprising: organizing the plurality of groupings to create a plurality of small islands based on the relative closeness of the plurality of groupings; reducing number of the plurality of small islands to form the predetermined number of top-level hierarchical islands, the reducing comprising: combining the plurality of small islands to multiple high-level islands each having a hierarchy of a subset of the plurality of small islands, the multiple high-level islands having at least a first high-level island and a second high-level island; determining that a set of small islands to be combined to the first high-level island will cause the first high-level island to include an unbalanced number of small islands; maintaining the first high-level island balanced by moving the set of small islands to be combined to the second high-level island, wherein the second high-level island has less closeness value than the first high-level island, and repeating the combining, determining and maintaining until the predetermined number of top-level hierarchical islands are formed; outputting one or more of the predetermined number of top-level hierarchical islands for display on a display device as arranged in one or more hierarchies such that at least one of the plurality of keywords is selectable on the display device, wherein the one or more of the predetermined number of top-level hierarchical islands include the keyword phrases; receiving, from a user input via an input device, a selection of one of the plurality of keyword phrases; and navigating, at the computing device based on the selection, to a subset of the plurality of items that: are configured as emails; and include or relate to the one of the plurality of keywords. 4. A method as described in claim 1 , wherein the plurality of items include instant messages, contacts, appointments and documents which are accessible on the client device. | 0.800915 |
9,672,467 | 10 | 12 | 10. The method of claim 9 , further comprising the steps of: creating and maintaining an object file for each of the at least one communicating entity; and upon the target personality receiving an initial conversational input from a one of the at least one communicating entity: determining whether the communicating entity has been encountered before by the target personality; upon determining that the communicating entity is new: creating a new object file for the communicating entity; prompting the communicating entity for relevant information related to said entity; and populating the new object file with any relevant information obtained from the communicating entity; upon determining that the communicating entity has been encountered before: accessing the object file associated with the communicating entity; and verifying the identity of the communicating entity; and updating the object file associated with the communicating entity as needed with any relevant information contained in at least one conversational input. | 10. The method of claim 9 , further comprising the steps of: creating and maintaining an object file for each of the at least one communicating entity; and upon the target personality receiving an initial conversational input from a one of the at least one communicating entity: determining whether the communicating entity has been encountered before by the target personality; upon determining that the communicating entity is new: creating a new object file for the communicating entity; prompting the communicating entity for relevant information related to said entity; and populating the new object file with any relevant information obtained from the communicating entity; upon determining that the communicating entity has been encountered before: accessing the object file associated with the communicating entity; and verifying the identity of the communicating entity; and updating the object file associated with the communicating entity as needed with any relevant information contained in at least one conversational input. 12. The method of claim 10 , further comprising the steps of: encrypting the relevant information contained in the at least one object file associated with the at least one communicating entity using a unique encryption key; upon verifying the identity of the communicating entity, determining whether the communicating entity is in possession of a corresponding decryption key; and using the decryption key to decrypt the relevant information contained in the associated object file in order to utilize that information as appropriate while interacting with the communicating entity. | 0.5 |
9,298,700 | 1 | 8 | 1. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: identifying a first set of phrases that exist within a corpus of text, individual ones of the first set of phrases including a substitute word that replaces one word of a source phrase comprising multiple words; generating a second set of phrases by combining substitute words from the first set of phrases with one another such that individual ones of the second set of phrases include a first substitute word from a first phrase of the first set of phrases and a second substitute word from a second phrase of the first set of phrases; generating a personalized user interface including at least a portion of the second set of phrases and at least one rule selector associated with a corresponding rule for using the at least the portion of the second set of phrases; and receiving a user selection of the at least the portion of the second set of phrases and the at least one rule selector associated with the corresponding rule for using the at least the portion of the second set of phrases. | 1. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed, cause one or more processors to perform acts comprising: identifying a first set of phrases that exist within a corpus of text, individual ones of the first set of phrases including a substitute word that replaces one word of a source phrase comprising multiple words; generating a second set of phrases by combining substitute words from the first set of phrases with one another such that individual ones of the second set of phrases include a first substitute word from a first phrase of the first set of phrases and a second substitute word from a second phrase of the first set of phrases; generating a personalized user interface including at least a portion of the second set of phrases and at least one rule selector associated with a corresponding rule for using the at least the portion of the second set of phrases; and receiving a user selection of the at least the portion of the second set of phrases and the at least one rule selector associated with the corresponding rule for using the at least the portion of the second set of phrases. 8. One or more non-transitory computer-readable media as recited in claim 1 , wherein individual phrases of the portion of the second set of phrases are grammatically correct and comprise two or more words. | 0.823024 |
10,061,846 | 1 | 6 | 1. A method comprising, by one or more computing devices: receiving, from a client system of a first user, a search query requesting objects of a first object type, the search query comprising an inner query requesting objects of a second object type, wherein the requested objects are structured documents stored on a plurality of data stores storing objects of a plurality of object types, respectively, wherein each data store only stores objects of a single object type, and wherein each data store comprises an index server coupled to the data store for processing query requests for objects of the particular object type stored on the data store; retrieving, by an index server of a second data store that only stores objects of the second object type, identifiers of one or more objects of the second object type requested by the inner query using an inverted index of the second data store, wherein the index server of the second data store maintains one or more search indices of the objects of the second object type stored on the second data store, and wherein one of the search indices is the inverted index of the second data store; retrieving, by an index server of a first data store that only stores objects of the first object type, for each of the identified one or more objects of the second object type, identifiers of one or more objects of the first object type requested by the search query, the one or more objects of the first object type being identified using an inverted index of the first data store, wherein the index server of the first data store maintains one or more search indices of the objects of the first object type stored on the first data store, and wherein one of the search indices is the inverted index of the first data store; aggregating a plurality of search results responsive to the search query, each search result corresponding to an identified object of the first object type; and sending, to the client system of the first user, one or more of the aggregated search results. | 1. A method comprising, by one or more computing devices: receiving, from a client system of a first user, a search query requesting objects of a first object type, the search query comprising an inner query requesting objects of a second object type, wherein the requested objects are structured documents stored on a plurality of data stores storing objects of a plurality of object types, respectively, wherein each data store only stores objects of a single object type, and wherein each data store comprises an index server coupled to the data store for processing query requests for objects of the particular object type stored on the data store; retrieving, by an index server of a second data store that only stores objects of the second object type, identifiers of one or more objects of the second object type requested by the inner query using an inverted index of the second data store, wherein the index server of the second data store maintains one or more search indices of the objects of the second object type stored on the second data store, and wherein one of the search indices is the inverted index of the second data store; retrieving, by an index server of a first data store that only stores objects of the first object type, for each of the identified one or more objects of the second object type, identifiers of one or more objects of the first object type requested by the search query, the one or more objects of the first object type being identified using an inverted index of the first data store, wherein the index server of the first data store maintains one or more search indices of the objects of the first object type stored on the first data store, and wherein one of the search indices is the inverted index of the first data store; aggregating a plurality of search results responsive to the search query, each search result corresponding to an identified object of the first object type; and sending, to the client system of the first user, one or more of the aggregated search results. 6. The method of claim 1 , wherein retrieving identifiers of the one or more objects of the second object type comprises: accessing the inverted index of the second data store corresponding to the second object type, wherein the inverted index of the second data store maps a user node of a social graph to one or more concept nodes of the social graph in accordance with a second relationship; and retrieving identifiers of the one or more objects of the second object type requested by the inner query using the inverted index of the second data store corresponding to the second object type, wherein the one or more objects of the second object type correspond to one or more concept nodes of the social graph in an online social network, and the one or more concept nodes are related, by the second relationship, to a user specified in the inner query. | 0.5 |
9,406,030 | 13 | 23 | 13. A computerized method for electronic document classification, the method comprising: providing training documents sorted into a plurality of classes; using a processor to perform linear programming including selecting input values which maximize an output value, given specific constraints on the input values, wherein the output value maximized is a difference between: a. a first estimated probability that a document instance will be correctly classified, by a given classifier corresponding to given input values, as belonging to its own class, and b. a second estimated probability that the document instance will be classified, by the given classifier, as belonging to a class other than its own class; and classifying electronic document instances into the plurality of classes, using at least one preferred classifier corresponding to the input values selected by said linear programming including storing an indication of said classifying in computer memory; and electronically determining whether each of a stream of electronic document instances are forgeries, by performing electronic forgery tests specific to individual classes from among said plurality of classes, on individual electronic document instances in said stream which have been classified by said preferred classifier, as belonging to said individual classes respectively. | 13. A computerized method for electronic document classification, the method comprising: providing training documents sorted into a plurality of classes; using a processor to perform linear programming including selecting input values which maximize an output value, given specific constraints on the input values, wherein the output value maximized is a difference between: a. a first estimated probability that a document instance will be correctly classified, by a given classifier corresponding to given input values, as belonging to its own class, and b. a second estimated probability that the document instance will be classified, by the given classifier, as belonging to a class other than its own class; and classifying electronic document instances into the plurality of classes, using at least one preferred classifier corresponding to the input values selected by said linear programming including storing an indication of said classifying in computer memory; and electronically determining whether each of a stream of electronic document instances are forgeries, by performing electronic forgery tests specific to individual classes from among said plurality of classes, on individual electronic document instances in said stream which have been classified by said preferred classifier, as belonging to said individual classes respectively. 23. A method according to claim 13 , wherein said classes include versions of individual document types and forgery testing is differentially performed for different versions. | 0.5 |
7,478,370 | 1 | 3 | 1. A method for validating a relationships table, comprising: generating a relational schema of symbols in the program code file based on a framework for models in the integrated development environment, the schema comprising two related tables, wherein said two related tables comprise a public symbols table and a referenced symbols table; determining a relationship between the two tables in the relational schema; adding definitions from the program code file for symbols in the relational schema to a definition set retaining definitions of symbols; and producing proxy definitions for use with the definition set for each symbol in the program code file without a definition in the definition set: generating the relationships table in the relational schema containing the relationship between the two tables; and validating the relationships table by matching the symbols definitions and references, wherein the validation removes public symbols and referenced symbols from the relationships table. | 1. A method for validating a relationships table, comprising: generating a relational schema of symbols in the program code file based on a framework for models in the integrated development environment, the schema comprising two related tables, wherein said two related tables comprise a public symbols table and a referenced symbols table; determining a relationship between the two tables in the relational schema; adding definitions from the program code file for symbols in the relational schema to a definition set retaining definitions of symbols; and producing proxy definitions for use with the definition set for each symbol in the program code file without a definition in the definition set: generating the relationships table in the relational schema containing the relationship between the two tables; and validating the relationships table by matching the symbols definitions and references, wherein the validation removes public symbols and referenced symbols from the relationships table. 3. The method according to claim 1 wherein the program code file contains the public symbols having a definition in the program code file and the referenced symbols being only referred to in the program code file, and wherein the step of adding definitions comprises: parsing the program code file to extract definitions for the public symbols therein; and adding the extracted definitions to the definition set. | 0.69927 |
9,798,980 | 16 | 20 | 16. A system, comprising: a processor; and a memory storing one or more application programs configured to perform an operation for inferring user interests based on metadata of a plurality of multimedia objects captured by a plurality of users, the operation comprising: receiving, for each of the users, metadata describing each multimedia object in the plurality of objects associated with that user, wherein each multimedia object includes one or more attributes imputed to that object based on the metadata; identifying one or more concepts from the one or more attributes, wherein each concept includes at least a first attribute that co-occurs with a second attribute imputed to a first multimedia object; and associating a first one of the plurality of users with at least one of the concepts based on the attributes imputed to multimedia objects associated with the first one of the plurality of users by determining a correlation measure between the first one of the plurality of users to each of the concepts based on the attributes imputed to multimedia objects in the plurality of multimedia objects associated with the first one of the plurality of users. | 16. A system, comprising: a processor; and a memory storing one or more application programs configured to perform an operation for inferring user interests based on metadata of a plurality of multimedia objects captured by a plurality of users, the operation comprising: receiving, for each of the users, metadata describing each multimedia object in the plurality of objects associated with that user, wherein each multimedia object includes one or more attributes imputed to that object based on the metadata; identifying one or more concepts from the one or more attributes, wherein each concept includes at least a first attribute that co-occurs with a second attribute imputed to a first multimedia object; and associating a first one of the plurality of users with at least one of the concepts based on the attributes imputed to multimedia objects associated with the first one of the plurality of users by determining a correlation measure between the first one of the plurality of users to each of the concepts based on the attributes imputed to multimedia objects in the plurality of multimedia objects associated with the first one of the plurality of users. 20. The system of claim 16 , wherein the first one of the plurality of users is associated with the at least one of the one or more concepts based on the correlation measure associated with that concept. | 0.746883 |
8,209,663 | 16 | 19 | 16. A system for manipulating a block diagram, the system comprising: a processor to: receive an indication of at least one desired set operation, receive an indication of a selected group of entities of a software environment, the selected group comprising a plurality of entities, the entities: being associated with one or more properties, including at least one entity from a first object, and including at least one entity from a second object, determine a group of properties of the plurality of entities based at least in part on the at least one set operation, where the group of properties is at least one of: common properties associated with each of the entities of the selected group of entities, properties associated with at least one of the entities of the selected group of entities, or properties that are associated with only one of the entities of the selected group of entities; a display element to: display a representation of the group of properties; and an input device to: provide an instruction to perform an edit operation on at least one of the properties of the group of properties, wherein the edit operation is applied to the entities associated with the at least one property. | 16. A system for manipulating a block diagram, the system comprising: a processor to: receive an indication of at least one desired set operation, receive an indication of a selected group of entities of a software environment, the selected group comprising a plurality of entities, the entities: being associated with one or more properties, including at least one entity from a first object, and including at least one entity from a second object, determine a group of properties of the plurality of entities based at least in part on the at least one set operation, where the group of properties is at least one of: common properties associated with each of the entities of the selected group of entities, properties associated with at least one of the entities of the selected group of entities, or properties that are associated with only one of the entities of the selected group of entities; a display element to: display a representation of the group of properties; and an input device to: provide an instruction to perform an edit operation on at least one of the properties of the group of properties, wherein the edit operation is applied to the entities associated with the at least one property. 19. The system of claim 16 , wherein providing the representation of the group includes providing a user interface for editing the group of properties. | 0.522152 |
9,275,051 | 10 | 13 | 10. The method of claim 1 , wherein the supplemental content includes a user interface to a communications forum for interacting with users about the rendered document. | 10. The method of claim 1 , wherein the supplemental content includes a user interface to a communications forum for interacting with users about the rendered document. 13. The method of claim 10 , further comprising determining, by the computing device, a topic of the rendered document, wherein the communications forum includes information related to the topic. | 0.5 |
8,909,594 | 5 | 6 | 5. The method of claim 1 , further comprising identifying the correspondence between the search query and the aspect of the good or service and the correspondence between the search query and the value of the aspect based on a keyword included in the search query. | 5. The method of claim 1 , further comprising identifying the correspondence between the search query and the aspect of the good or service and the correspondence between the search query and the value of the aspect based on a keyword included in the search query. 6. The method of claim 5 , wherein the data item pertaining to the listing does not include the keyword. | 0.5 |
8,626,706 | 1 | 2 | 1. A method comprising: generating a new message in response to a command, wherein the new message relates to a message thread; storing words found in messages associated with the message thread as language objects in a dictionary of language objects associated with the message thread; and associating frequency values with the language objects in the dictionary to prioritize the language objects in the dictionary over words not contained in the dictionary. | 1. A method comprising: generating a new message in response to a command, wherein the new message relates to a message thread; storing words found in messages associated with the message thread as language objects in a dictionary of language objects associated with the message thread; and associating frequency values with the language objects in the dictionary to prioritize the language objects in the dictionary over words not contained in the dictionary. 2. The method of claim 1 , further comprising generating the dictionary of language objects upon determining that the message thread dictionary does not exist. | 0.577128 |
7,880,730 | 23 | 27 | 23. The system of claim 22 , wherein objects in memory are further associated with at least one module, wherein said module comprises a set of objects having at least one common characteristic or that is generated by a common process/algorithm or alternate method of interpreting said current input sequence. | 23. The system of claim 22 , wherein objects in memory are further associated with at least one module, wherein said module comprises a set of objects having at least one common characteristic or that is generated by a common process/algorithm or alternate method of interpreting said current input sequence. 27. The system of claim 23 , wherein said module employs templates of valid symbol or sub-object sequences to determine which symbols around an interaction point are possible given preceding interactions and the objects being considered. | 0.916842 |
8,271,351 | 50 | 51 | 50. A computer-implemented method implemented by one or more computing devices for automatically generating a naturally reading narrative product summary including assertions about a specific product selected by a user, said method comprising: receiving, by at least one of the one or more computing devices, the selection of a first product from the user, the first product associated with a plurality of attributes; identifying, by at least one of the one or more computing devices, at least one attribute of the plurality of attributes for the first product; selecting, by at least one of the one or more computing devices, a second product based on the at least one attribute, the second product being the product having the high value rating for the at least one attribute; and generating, by at least one of the one or more computing devices, the naturally reading narrative product summary including assertions about the first product and a recommendation of the second product. | 50. A computer-implemented method implemented by one or more computing devices for automatically generating a naturally reading narrative product summary including assertions about a specific product selected by a user, said method comprising: receiving, by at least one of the one or more computing devices, the selection of a first product from the user, the first product associated with a plurality of attributes; identifying, by at least one of the one or more computing devices, at least one attribute of the plurality of attributes for the first product; selecting, by at least one of the one or more computing devices, a second product based on the at least one attribute, the second product being the product having the high value rating for the at least one attribute; and generating, by at least one of the one or more computing devices, the naturally reading narrative product summary including assertions about the first product and a recommendation of the second product. 51. The method of claim 50 , wherein the second product is a comparable product. | 0.512195 |
7,615,768 | 4 | 7 | 4. A document original size detecting device comprising: a plurality of sensors each including a light emitting portion and a light receiving portion and respectively disposed as corresponding to different sizes of document originals to be placed on a transparent document platen, the light emitting portion and the light receiving portion being positioned above and below the transparent document platen, respectively; and a detecting section which determines a document original size based on outputs of the sensors; wherein the light emitting portion of each of the sensors emits light to illuminate at least two positions on a document placing region of the document platen on which a document original to be subjected to size detection is placed, and the detecting section determines the document original size based on whether or not the light receiving portion of each of the sensors detects the document original blocking the light in at least one of the two positions, wherein the light emitting portion of each of the sensors includes a light emitting element which emits a light beam on the document platen, and an illumination position moving section which moves an illumination position at which the light beam emitted from the light emitting element is incident on the document platen to the at least two positions, the at least two positions being aligned parallel to a reference line along which one edge of the document original is positioned on the document platen, and wherein the light receiving portion of each of the sensors includes a light receiving element which receives the light beam emitted from the light emitting element. | 4. A document original size detecting device comprising: a plurality of sensors each including a light emitting portion and a light receiving portion and respectively disposed as corresponding to different sizes of document originals to be placed on a transparent document platen, the light emitting portion and the light receiving portion being positioned above and below the transparent document platen, respectively; and a detecting section which determines a document original size based on outputs of the sensors; wherein the light emitting portion of each of the sensors emits light to illuminate at least two positions on a document placing region of the document platen on which a document original to be subjected to size detection is placed, and the detecting section determines the document original size based on whether or not the light receiving portion of each of the sensors detects the document original blocking the light in at least one of the two positions, wherein the light emitting portion of each of the sensors includes a light emitting element which emits a light beam on the document platen, and an illumination position moving section which moves an illumination position at which the light beam emitted from the light emitting element is incident on the document platen to the at least two positions, the at least two positions being aligned parallel to a reference line along which one edge of the document original is positioned on the document platen, and wherein the light receiving portion of each of the sensors includes a light receiving element which receives the light beam emitted from the light emitting element. 7. A document original size detecting device as set forth in claim 4 , wherein the illumination position moving section includes a mirror which reflects a light beam emitted from the light emitting element, and a movement mechanism which moves the mirror by driving means. | 0.507246 |
9,785,670 | 6 | 7 | 6. The method of claim 1 , further comprising: receiving, by one or more processors, a test statement, wherein the test statement is an instruction to access or manipulate a database that is governed by the revised policy; and in response to receiving the test statement, one or more processors presenting to the user a result of applying rules in the revised policy to said test statement. | 6. The method of claim 1 , further comprising: receiving, by one or more processors, a test statement, wherein the test statement is an instruction to access or manipulate a database that is governed by the revised policy; and in response to receiving the test statement, one or more processors presenting to the user a result of applying rules in the revised policy to said test statement. 7. The method of claim 6 , wherein the test statement comprises multiple terms, and wherein the method further comprises: in response to receiving the test statement, presenting to a user a result of applying the revised policy to the all the terms in the given test query or statement. | 0.5 |
9,058,174 | 3 | 4 | 3. The computer-implemented method of claim 2 , wherein the semantic tags are selected from a predefined ontology of semantic tags, wherein the ontology of semantic tags is used for determining compatible resources, and wherein wiring the plurality of web widgets comprises: wiring a first web widget and a second web widget based on the web widget registry and the ontology of semantic tags. | 3. The computer-implemented method of claim 2 , wherein the semantic tags are selected from a predefined ontology of semantic tags, wherein the ontology of semantic tags is used for determining compatible resources, and wherein wiring the plurality of web widgets comprises: wiring a first web widget and a second web widget based on the web widget registry and the ontology of semantic tags. 4. The computer-implemented method of claim 3 , wherein wiring the plurality of web widgets comprises: creating a plurality of wirings, wherein each wiring connects: (i) a respective first web widget producing a resource and (ii) a respective second web widget consuming a compatible resource, as determined based on the ontology of semantic tags. | 0.5 |
8,346,548 | 18 | 19 | 18. An aural similarity measuring server as claimed in claim 13 , wherein the processor is adapted to identify aligned phonemes which differ; to allocate predetermined phoneme scores for each pair of differing aligned phonemes; and to summing the individual phoneme scores to thereby assign a score to the reference text. | 18. An aural similarity measuring server as claimed in claim 13 , wherein the processor is adapted to identify aligned phonemes which differ; to allocate predetermined phoneme scores for each pair of differing aligned phonemes; and to summing the individual phoneme scores to thereby assign a score to the reference text. 19. An aural similarity measuring server as claimed in claim 18 , wherein the processor is adapted to weight the phoneme scores in dependence upon the position of the pair of phonemes in the phoneme strings. | 0.691964 |
9,710,543 | 3 | 4 | 3. The method of claim 1 , further comprising: comparing each said first substitutability metric to a first pre-defined threshold. | 3. The method of claim 1 , further comprising: comparing each said first substitutability metric to a first pre-defined threshold. 4. The method of claim 3 , wherein at least one of said substitute expressions is chosen upon determining that said first substitutability metric for said at least one of said substitute expressions meets said first pre-defined threshold. | 0.67036 |
9,037,610 | 1 | 4 | 1. A method of providing access control (AC) in respect of a database storing information in tables and columns and being accessible from a user interface, which is configured to accept a database query and return information extracted from the database, the method being implemented at least in part at a policy enforcement point (PEP), which is located between the database and the user interface, and comprising i) intercepting, at the PEP, a database query; ii) assigning attribute values by performing at least one of the following: ii-a) assigning a resource attribute value based on at least one target table or target column appearing in the query; ii-b) assigning an action attribute value based on a construct type appearing in the query; and ii-c) assigning a subject and/or environment attribute value based on an identity of the user or on environment data; iii) providing an attributed-based AC policy defined in terms of said attributes iv) deriving an access condition, for which the AC policy, when evaluated for the attribute value(s) assigned in step ii), evaluates to permit access; and v) amending the database query by imposing said access condition and vi) transmitting the amended query to the database. | 1. A method of providing access control (AC) in respect of a database storing information in tables and columns and being accessible from a user interface, which is configured to accept a database query and return information extracted from the database, the method being implemented at least in part at a policy enforcement point (PEP), which is located between the database and the user interface, and comprising i) intercepting, at the PEP, a database query; ii) assigning attribute values by performing at least one of the following: ii-a) assigning a resource attribute value based on at least one target table or target column appearing in the query; ii-b) assigning an action attribute value based on a construct type appearing in the query; and ii-c) assigning a subject and/or environment attribute value based on an identity of the user or on environment data; iii) providing an attributed-based AC policy defined in terms of said attributes iv) deriving an access condition, for which the AC policy, when evaluated for the attribute value(s) assigned in step ii), evaluates to permit access; and v) amending the database query by imposing said access condition and vi) transmitting the amended query to the database. 4. The method of claim 1 , wherein: step ii-a) includes assigning resource attribute values based on at least two target columns; and a sequence of steps iii) and iv) is performed once for each resource attribute value thus assigned. | 0.844459 |
8,060,841 | 9 | 14 | 9. A portable media device comprising a controller element that emits ultrasonic waveforms from ultrasonic transducers to reflect off a finger in a three-dimensional touchless sensing space; digitally samples the reflected ultrasonic waveforms off the finger to produce a sampled reflected ultrasonic waveform; tracks a relative location and movement of the finger in the three-dimensional ultrasonic sensing space from differential time of flight waveform analysis of the sampled reflected ultrasonic waveforms; suppressing a ringing portion of the emitted ultrasonic waveforms that overlaps with the sampled reflected ultrasonic waveform during the tracking; minimizing a distortion associated with ultrasonic transducer ring-down during generation of a high-resolution touchless finger signing from the suppressing; receives a search string from the touchless finger signing and presents at least one media that corresponds to at least a portion of the search string, wherein the search string includes at least one finger gesture generated in a touchless sensory field of the touchless sensing device. | 9. A portable media device comprising a controller element that emits ultrasonic waveforms from ultrasonic transducers to reflect off a finger in a three-dimensional touchless sensing space; digitally samples the reflected ultrasonic waveforms off the finger to produce a sampled reflected ultrasonic waveform; tracks a relative location and movement of the finger in the three-dimensional ultrasonic sensing space from differential time of flight waveform analysis of the sampled reflected ultrasonic waveforms; suppressing a ringing portion of the emitted ultrasonic waveforms that overlaps with the sampled reflected ultrasonic waveform during the tracking; minimizing a distortion associated with ultrasonic transducer ring-down during generation of a high-resolution touchless finger signing from the suppressing; receives a search string from the touchless finger signing and presents at least one media that corresponds to at least a portion of the search string, wherein the search string includes at least one finger gesture generated in a touchless sensory field of the touchless sensing device. 14. The portable media device of claim 9 , wherein the controller elements alphabetizes a list of media to produce an alphabetic list, and presents a section of the alphabetic list corresponding to the search string. | 0.789883 |
8,065,134 | 1 | 7 | 1. An information display system, comprising a large screen display device; an information display unit which displays information in the screen display device in a predetermined standard language; a user information input unit which inputs user information including information of a language desired by a user; and a language switch display unit which, when the user desired language input by the user information input unit is different from the standard language, switches all or part of the standard language of the screen display device to and displays the desired language of the user, and wherein the information display unit displays guide information, which comprises a public area common to all users and a plurality of individual areas dependent on respective users, in the standard language, when the input user desired language is different from the standard language, the language switch display unit displays the public area by time division by the standard language and the user desired language or displays the standard language and the user desired language in parallel by the area division and switches an individual area corresponding to the user desired language, and wherein the language switch display unit displays accompanying information relevant to the user in the language of the user so as to correspond to the individual area switched to and displayed in the user desired language. | 1. An information display system, comprising a large screen display device; an information display unit which displays information in the screen display device in a predetermined standard language; a user information input unit which inputs user information including information of a language desired by a user; and a language switch display unit which, when the user desired language input by the user information input unit is different from the standard language, switches all or part of the standard language of the screen display device to and displays the desired language of the user, and wherein the information display unit displays guide information, which comprises a public area common to all users and a plurality of individual areas dependent on respective users, in the standard language, when the input user desired language is different from the standard language, the language switch display unit displays the public area by time division by the standard language and the user desired language or displays the standard language and the user desired language in parallel by the area division and switches an individual area corresponding to the user desired language, and wherein the language switch display unit displays accompanying information relevant to the user in the language of the user so as to correspond to the individual area switched to and displayed in the user desired language. 7. The information display system according to claim 1 , wherein the information display unit displays a list of departure information of an airport as the guide information, displays item names including, for example, departure time, flight number, route, destination, company name, and gate number as a public area of the list display, and displays a plurality of arrays of item values corresponding to the item names of the public area in the order of departure time as individual areas of the list display. | 0.561102 |
9,866,675 | 2 | 3 | 2. The wireless communications device of claim 1 , further operations comprising determining whether the available voicemail comprises the keyword. | 2. The wireless communications device of claim 1 , further operations comprising determining whether the available voicemail comprises the keyword. 3. The wireless communications device of claim 2 , further operations comprising detecting an indicator of the keyword based on the notification. | 0.661215 |
8,126,837 | 20 | 26 | 20. A method, comprising: receiving at least a portion of text from a document in response to a policy update request; determining that the document has a changed portion based on a version of the document stored in a database and based on the portion of text from the document; and analyzing the changed portion of the document based on a document template, the document template being selected from a plurality of document templates based on a document type associated with the document. | 20. A method, comprising: receiving at least a portion of text from a document in response to a policy update request; determining that the document has a changed portion based on a version of the document stored in a database and based on the portion of text from the document; and analyzing the changed portion of the document based on a document template, the document template being selected from a plurality of document templates based on a document type associated with the document. 26. The method of claim 20 , wherein the analyzing includes analyzing based on a set of semantic rules selected based on the document type and an ontology having at least a portion associated with the document type. | 0.768817 |
9,620,106 | 1 | 6 | 1. A method comprising: identifying a speaker providing speech; identifying a microphone type of a microphone receiving the speech; selecting a user profile from a plurality of user profiles based on the microphone type and a current location of the speaker, wherein each user profile in the plurality of user profiles is associated with the speaker; and performing, via a processor, speech recognition on the speech received from the speaker using the user profile. | 1. A method comprising: identifying a speaker providing speech; identifying a microphone type of a microphone receiving the speech; selecting a user profile from a plurality of user profiles based on the microphone type and a current location of the speaker, wherein each user profile in the plurality of user profiles is associated with the speaker; and performing, via a processor, speech recognition on the speech received from the speaker using the user profile. 6. The method of claim 1 , further comprising presenting a query to a user, wherein the query presented to the user comprises a request regarding acoustics in a current location of the speaker. | 0.5 |
9,886,500 | 8 | 14 | 8. A method, comprising: building a document map for a plurality of documents within a data store of a document system using a topic-related generative model for the plurality of documents; selecting a control set of documents from the plurality of documents, wherein the control set of documents is selected from a first strata of the plurality of documents and a second strata of the plurality of documents; sending the control set of documents to a user; receiving a control set metric regarding the control set of documents from the user, wherein the control set metric includes an indicator of responsiveness for each of the documents of the control set of documents; performing, by the document system, the steps of: a) determining a responsiveness score for each of the plurality of documents based on a scoring algorithm; b) determining a set of responsive documents and a set of non-responsive documents of the plurality of documents based on the responsiveness score determined for each of the plurality of documents and a decision boundary score; c) determining a confidence score for the document system using the responsiveness score for each of the documents of the control set and the indicator of responsiveness for each of the control set documents received from the user; d) selecting one or more of the plurality of documents based on the responsiveness scores of the plurality of documents, wherein the responsiveness score of each of the one or more selected documents is at or near the decision boundary score; e) presenting the one or more selected documents to the user; f) receiving an indicator of responsiveness from the user for each of the selected documents; g) refining the scoring algorithm based on the indicator of responsiveness for each of the selected document; and h) generating a desired confidence score for the document system, and presenting the set of responsive documents to the user when the desired confidence score for the document system is achieved, wherein the confidence score for the document system is an F1 score determined by comparing the responsiveness score for the documents of the control set to the indicator of responsiveness for the documents of the control set received from the user. | 8. A method, comprising: building a document map for a plurality of documents within a data store of a document system using a topic-related generative model for the plurality of documents; selecting a control set of documents from the plurality of documents, wherein the control set of documents is selected from a first strata of the plurality of documents and a second strata of the plurality of documents; sending the control set of documents to a user; receiving a control set metric regarding the control set of documents from the user, wherein the control set metric includes an indicator of responsiveness for each of the documents of the control set of documents; performing, by the document system, the steps of: a) determining a responsiveness score for each of the plurality of documents based on a scoring algorithm; b) determining a set of responsive documents and a set of non-responsive documents of the plurality of documents based on the responsiveness score determined for each of the plurality of documents and a decision boundary score; c) determining a confidence score for the document system using the responsiveness score for each of the documents of the control set and the indicator of responsiveness for each of the control set documents received from the user; d) selecting one or more of the plurality of documents based on the responsiveness scores of the plurality of documents, wherein the responsiveness score of each of the one or more selected documents is at or near the decision boundary score; e) presenting the one or more selected documents to the user; f) receiving an indicator of responsiveness from the user for each of the selected documents; g) refining the scoring algorithm based on the indicator of responsiveness for each of the selected document; and h) generating a desired confidence score for the document system, and presenting the set of responsive documents to the user when the desired confidence score for the document system is achieved, wherein the confidence score for the document system is an F1 score determined by comparing the responsiveness score for the documents of the control set to the indicator of responsiveness for the documents of the control set received from the user. 14. The method of claim 8 , wherein generating a desired confidence score for the document system comprises: repeating steps a-g until the determined confidence score for the document system is the desired confidence score for the document system. | 0.5 |
8,694,385 | 17 | 18 | 17. A system, comprising: at least one device processor; and memory including instructions that, when executed by the at least one device processor, enable the system to: receive a first query from a first user, the first query including one or more query terms; generate a first query result including one or more items corresponding to the first query; for each respective item in the first query result, determine a ranking value using one or more rating scores, each rating score corresponding to a respective query term and depending at least in part on a first frequency with which selection actions are performed by previous users with respect to the respective item, the selection actions being performed against previous query results generated in response to previous queries that include the respective query term; and present at least a portion of the first query result for display to the first user according to the ranking values. | 17. A system, comprising: at least one device processor; and memory including instructions that, when executed by the at least one device processor, enable the system to: receive a first query from a first user, the first query including one or more query terms; generate a first query result including one or more items corresponding to the first query; for each respective item in the first query result, determine a ranking value using one or more rating scores, each rating score corresponding to a respective query term and depending at least in part on a first frequency with which selection actions are performed by previous users with respect to the respective item, the selection actions being performed against previous query results generated in response to previous queries that include the respective query term; and present at least a portion of the first query result for display to the first user according to the ranking values. 18. The system of claim 17 , wherein each rating score further depends at least in part on a type of selection action performed by a previous user. | 0.776596 |
7,805,424 | 1 | 2 | 1. A method to query a compound XML document, the method comprising: receiving a compound XML document comprising a primary document, a first nested document, and a second nested document that is nested within the first nested document; determining a first encoding type associated with the first nested document and a second encoding type associated with the second nested document; generating a single query against the compound XML document, the query comprising an attribute and a first query element specifying the first encoding type, a first search term, and a first root node of the first nested document, the query further comprising a second query element specifying the second encoding type, a second search term, and a second root node of the second nested document; executing the query and decoding the first nested document and the second nested document; and receiving a first rowset from the first nested document and a second rowset from the second nested document, wherein executing the query comprises decoding the first nested document associated with the first encoding type to reveal contents of the first nested document and decoding the second nested document associated with the second encoding type to reveal contents of the second nested document and querying the contents of both revealed documents. | 1. A method to query a compound XML document, the method comprising: receiving a compound XML document comprising a primary document, a first nested document, and a second nested document that is nested within the first nested document; determining a first encoding type associated with the first nested document and a second encoding type associated with the second nested document; generating a single query against the compound XML document, the query comprising an attribute and a first query element specifying the first encoding type, a first search term, and a first root node of the first nested document, the query further comprising a second query element specifying the second encoding type, a second search term, and a second root node of the second nested document; executing the query and decoding the first nested document and the second nested document; and receiving a first rowset from the first nested document and a second rowset from the second nested document, wherein executing the query comprises decoding the first nested document associated with the first encoding type to reveal contents of the first nested document and decoding the second nested document associated with the second encoding type to reveal contents of the second nested document and querying the contents of both revealed documents. 2. The method of claim 1 , wherein receiving a compound XML document comprises receiving an XML document with multiple levels of nested documents. | 0.710317 |
10,089,388 | 5 | 6 | 5. The method of claim 2 , wherein obtaining the user request to adjust the amount of contextual content that is rendered for the search results comprises detecting a second gesture using the gesture-enabled input device. | 5. The method of claim 2 , wherein obtaining the user request to adjust the amount of contextual content that is rendered for the search results comprises detecting a second gesture using the gesture-enabled input device. 6. The method of claim 5 , wherein the second gesture comprises a screen press having a time duration, and wherein the adjusted amount of contextual content for the search term corresponds to the time duration of the screen press. | 0.5 |
7,689,554 | 25 | 27 | 25. A system for identifying one or more queries related to a given query, the system comprising: a data store comprising a storage medium for storing a searchable query set; a search engine comprising one or more processing elements for receiving a query written according to one or more writing systems of a language with multiple writing systems, and identifying a candidate set of one or more queries in the data store, the candidate set of queries written according to one or more writing systems of the language with multiple writing systems; a conversion component comprising one or more processing elements for converting the received query and the one or more queries in the candidate set into one or more written formats; a similarity component comprising one or more processing elements for calculating a number of common characters in a given candidate query before disagreement with the query received, the similarity component further calculating a number of total common characters between the given candidate query and the query received and calculating a quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs; and a similarity score component comprising one or more processing elements for calculating a similarity score on the basis of the number of common characters before disagreement, the total number of characters for the one or more queries in the candidate set and the quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs indicating the similarity of the one or more queries with respect to the received query. | 25. A system for identifying one or more queries related to a given query, the system comprising: a data store comprising a storage medium for storing a searchable query set; a search engine comprising one or more processing elements for receiving a query written according to one or more writing systems of a language with multiple writing systems, and identifying a candidate set of one or more queries in the data store, the candidate set of queries written according to one or more writing systems of the language with multiple writing systems; a conversion component comprising one or more processing elements for converting the received query and the one or more queries in the candidate set into one or more written formats; a similarity component comprising one or more processing elements for calculating a number of common characters in a given candidate query before disagreement with the query received, the similarity component further calculating a number of total common characters between the given candidate query and the query received and calculating a quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs; and a similarity score component comprising one or more processing elements for calculating a similarity score on the basis of the number of common characters before disagreement, the total number of characters for the one or more queries in the candidate set and the quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs indicating the similarity of the one or more queries with respect to the received query. 27. The system of claim 25 wherein the search engine identifies a candidate set comprised of one or more queries related to the received query. | 0.870236 |
5,493,608 | 9 | 10 | 9. The method according to claim 8, wherein said adjusting step includes increasing said subsequent speaking rate of said subsequent voice message if said caller response time measured in said measuring step was shorter in duration than a first predetermined amount of time. | 9. The method according to claim 8, wherein said adjusting step includes increasing said subsequent speaking rate of said subsequent voice message if said caller response time measured in said measuring step was shorter in duration than a first predetermined amount of time. 10. The method according to claim 9, wherein said adjusting step includes decreasing said subsequent speaking rate of said subsequent voice message if said caller response time measured in said measuring step was longer in duration than a second predetermined amount of time. | 0.5 |
9,467,436 | 1 | 5 | 1. A computer system configured to validate homophone CAPTCHAs, the computer system comprising: one or more hardware processors programmed, via executable code instructions, to implement: a CAPTCHA generator module configured to: determine a phrase of words that, when perceived together, comprises one or more meanings associated with the phrase of words that assist human perception of the phrase of words, and further comprises a homophone having a particular meaning, of multiple possible meanings for the homophone, in conjunction with use in the phrase of words; and generate a homophone CAPTCHA user interface depicting: the phrase of words including the homophone, wherein the homophone is configured for human perception as to the particular meaning of the homophone based on context of the homophone within the phrase of words, and at least two options associated with respective two or more meanings for the homophone, wherein at least one of the options is associated with the particular meaning of the homophone within the phrase of words and at least one of the options is associated with an incorrect meaning of the homophone within the phrase of words; a human validator module configured to: receive a selection of at least one of the options associated with the homophone CAPTCHA user interface; determine whether the selected option is the option associated with the particular meaning of the homophone within the phrase of words; generate an indication of whether the selected option was provided by a human based on said determination; and transmit the generated indication. | 1. A computer system configured to validate homophone CAPTCHAs, the computer system comprising: one or more hardware processors programmed, via executable code instructions, to implement: a CAPTCHA generator module configured to: determine a phrase of words that, when perceived together, comprises one or more meanings associated with the phrase of words that assist human perception of the phrase of words, and further comprises a homophone having a particular meaning, of multiple possible meanings for the homophone, in conjunction with use in the phrase of words; and generate a homophone CAPTCHA user interface depicting: the phrase of words including the homophone, wherein the homophone is configured for human perception as to the particular meaning of the homophone based on context of the homophone within the phrase of words, and at least two options associated with respective two or more meanings for the homophone, wherein at least one of the options is associated with the particular meaning of the homophone within the phrase of words and at least one of the options is associated with an incorrect meaning of the homophone within the phrase of words; a human validator module configured to: receive a selection of at least one of the options associated with the homophone CAPTCHA user interface; determine whether the selected option is the option associated with the particular meaning of the homophone within the phrase of words; generate an indication of whether the selected option was provided by a human based on said determination; and transmit the generated indication. 5. The computer system of claim 1 , wherein the homophone CAPTCHA user interface is delivered via a text message to a user computing device. | 0.611111 |
7,496,746 | 2 | 3 | 2. The apparatus of claim 1 , the output device is coupled to the processing device, the processing device further operative to provide the list of user configuration documents to the output device; and wherein the apparatus further comprises an input device coupled to the processing device, the processing device operative to receive a selection command selecting the at least one user configuration document from the list. | 2. The apparatus of claim 1 , the output device is coupled to the processing device, the processing device further operative to provide the list of user configuration documents to the output device; and wherein the apparatus further comprises an input device coupled to the processing device, the processing device operative to receive a selection command selecting the at least one user configuration document from the list. 3. The apparatus of claim 2 , wherein the processing device is further operative to: prompt the user with a configuration query, using the output device; and receive configuration responses from the input device. | 0.5 |
9,779,723 | 15 | 17 | 15. The method of claim 14 , further comprising: adaptively updating the first confidence level based on user feedback received at the microphone or received at a user input device. | 15. The method of claim 14 , further comprising: adaptively updating the first confidence level based on user feedback received at the microphone or received at a user input device. 17. The method of claim 15 , wherein adaptively updating comprises lowering the first confidence level in response to the user feedback indicating that results of the first passes were correct. | 0.5 |
7,752,195 | 2 | 6 | 2. The computer-implemented method of claim 1 , further comprising: determining a query index association for each of the plurality of search indexes. | 2. The computer-implemented method of claim 1 , further comprising: determining a query index association for each of the plurality of search indexes. 6. The computer-implemented method of claim 2 , wherein computing an allocation score includes: computing an allocation score for each of the plurality of search indexes based further on the query index association determined for the search index. | 0.75641 |
7,640,498 | 30 | 39 | 30. A computer-readable storage medium that includes data and instructions for enabling actions to be performed on a remote platform, comprising: a first component for enabling a request for a document from the remote platform, a type of the platform including a type of an operating system and type of a native browser that are employed to display the document; a second component for enabling a determination of the type of the remote platform and selectively associating a size ratio between a plurality of font sizes with the determined type of the remote platform, the enabling the determination of the type of the remote platform comprising enabling a determination of the type of the operating system and the determination of the type of the native browser, and the selective association being based on the determination of the type of the operating system and the determination of the type of the native browser; a third component for enabling the document with a plurality of font sizes for the document to be provided to the remote platform for display, the document is being locally scaled for display by the operation of the native browser with the size ratio for the plurality of font sizes; and a fourth component for enabling the plurality of font sizes to be changed by an execution of a script included with the document using at least one control of the native browser operating on the remote platform, the size ratio between the plurality of font sizes being determined by the native browser and maintained for a change to a size of at least one font displayed in the document at the remote platform, the execution changes the at least one font for at least one markup language text element displayed within the document. | 30. A computer-readable storage medium that includes data and instructions for enabling actions to be performed on a remote platform, comprising: a first component for enabling a request for a document from the remote platform, a type of the platform including a type of an operating system and type of a native browser that are employed to display the document; a second component for enabling a determination of the type of the remote platform and selectively associating a size ratio between a plurality of font sizes with the determined type of the remote platform, the enabling the determination of the type of the remote platform comprising enabling a determination of the type of the operating system and the determination of the type of the native browser, and the selective association being based on the determination of the type of the operating system and the determination of the type of the native browser; a third component for enabling the document with a plurality of font sizes for the document to be provided to the remote platform for display, the document is being locally scaled for display by the operation of the native browser with the size ratio for the plurality of font sizes; and a fourth component for enabling the plurality of font sizes to be changed by an execution of a script included with the document using at least one control of the native browser operating on the remote platform, the size ratio between the plurality of font sizes being determined by the native browser and maintained for a change to a size of at least one font displayed in the document at the remote platform, the execution changes the at least one font for at least one markup language text element displayed within the document. 39. The computer-readable storage medium of claim 30 , further comprising a component for enabling at least one size for each of a small font, a default font and a big font to be provided for displaying with the document. | 0.717391 |
6,032,116 | 31 | 33 | 31. The apparatus of claim 27 further comprising: a quantizer having a codebook having C codewords for generating the distance measure between each of the P line spectral pair frequencies of the speech input signal and each of a plurality of reference speech signals; a first speech classifier to receive output data based on the distance measures and generate speech classification output data to classify the speech input signal as one of u vocabulary words; and a second speech classifier to receive output data from the first speech classifier and classify the speech input signal as one of the u vocabulary words. | 31. The apparatus of claim 27 further comprising: a quantizer having a codebook having C codewords for generating the distance measure between each of the P line spectral pair frequencies of the speech input signal and each of a plurality of reference speech signals; a first speech classifier to receive output data based on the distance measures and generate speech classification output data to classify the speech input signal as one of u vocabulary words; and a second speech classifier to receive output data from the first speech classifier and classify the speech input signal as one of the u vocabulary words. 33. The apparatus of claim 31 wherein the quantizer is a fuzzy matrix quantizer further for generating respective fuzzy distance measures between the respective speech input signal and reference speech signal P line spectral pair frequencies using the corresponding generated distance measures; and wherein the second speech classifier is a neural network and the output data is a fuzzy distance measure proportional to a combination of the generated fuzzy distance measures. | 0.5 |
9,516,388 | 13 | 14 | 13. The EPG generating apparatus according to claim 12 , wherein the maximum clique set comprises a maximum clique whose node must be greater than or equal to a node threshold, and the maximum clique corresponds to an optimum keyword group. | 13. The EPG generating apparatus according to claim 12 , wherein the maximum clique set comprises a maximum clique whose node must be greater than or equal to a node threshold, and the maximum clique corresponds to an optimum keyword group. 14. The EPG generating apparatus according to claim 13 , wherein the processor compares the optimum keyword group with the program description to generate an occurrence frequency of a keyword of the optimum keyword group in the program description, and divides the occurrence frequency by the keyword count of the optimum keyword group to generate the match score. | 0.5 |
9,412,394 | 18 | 19 | 18. The system for operating interactive audio communications using the communication network of claim 14 , wherein the second computing device further comprises an interface device being designed to communicate with the second computing device via a wireless network, the interface device comprising: a sub-microphone; a sub-talk button for starting recording of the audio inputs from the user via the sub-microphone into the second memory when the sub-talk button is pushed and for stopping recording of the audio inputs when the sub-talk button is next pushed. | 18. The system for operating interactive audio communications using the communication network of claim 14 , wherein the second computing device further comprises an interface device being designed to communicate with the second computing device via a wireless network, the interface device comprising: a sub-microphone; a sub-talk button for starting recording of the audio inputs from the user via the sub-microphone into the second memory when the sub-talk button is pushed and for stopping recording of the audio inputs when the sub-talk button is next pushed. 19. The system for operating interactive audio communications using the communication network of claim 18 , wherein the interface device further comprises: a bookmark button for bookmarking an item from the information provided by the first computing device, the tag information including a text string constituting a resource associated with the bookmarked item; and a sub-speaker, wherein the second operation of the second processor further comprises the steps of: downloading the information provided by said the first computing device; reading out loud the information via the sub-speaker; determining whether the bookmark button is pushed while or after the item to be bookmarked from the information is read out loud via the sub-speaker; and extracting the tag information from the bookmarked item and memorizing the tag information into said at least one server if the bookmark button bookmarks the item from the information while or after the information is being read out loud via the sub-speaker. | 0.5 |
5,404,319 | 19 | 20 | 19. The translator of claim 17 wherein said analysis module (34) includes a behavior specific normalizer (32b) for determining a specific character of the components from the behavior description thereof from among a predetermined character set for converting the behavior to a simplified normal form. | 19. The translator of claim 17 wherein said analysis module (34) includes a behavior specific normalizer (32b) for determining a specific character of the components from the behavior description thereof from among a predetermined character set for converting the behavior to a simplified normal form. 20. The translator of claim 19 wherein said predetermined character set is taken from the group consisting of: a set of nonlinear algebraic and differential equations with respect to time; a Laplace transform expressed as the product of rational polynomials in S; a Z domain transform expressed as the product of rational polynomials in Z; a set of poles and zeros in S representing the roots of the numerator and denominator of the associated transfer function in S; a set of poles and zeros in Z representing the roots of the numerator and denominator of the associated transfer function in Z; and a frequency response expressed as a list of frequency, magnitude and phase triplets. | 0.5 |
7,933,908 | 1 | 5 | 1. One or more non-transitory computer-readable media holding computer-executable instructions, the computer-executable instructions comprising one or more instructions for: receiving a single command to access a dataset stored in memory, the single command being compatible with a matrix-based programming language, the dataset having at least a first variable, a second variable, a plurality of subjects, and information relating to at least the first variable, the second variable, and the plurality of subjects, the first variable having two or more elements of a first data type and the second variable having two or more elements of a second data type, the second data type being different from the first data type, and the elements of the first variable and the second variable being measured or collected data that relates to the plurality of subjects; and modifying at least one element of the first data type and at least one element of the second data type in the dataset based on the single command. | 1. One or more non-transitory computer-readable media holding computer-executable instructions, the computer-executable instructions comprising one or more instructions for: receiving a single command to access a dataset stored in memory, the single command being compatible with a matrix-based programming language, the dataset having at least a first variable, a second variable, a plurality of subjects, and information relating to at least the first variable, the second variable, and the plurality of subjects, the first variable having two or more elements of a first data type and the second variable having two or more elements of a second data type, the second data type being different from the first data type, and the elements of the first variable and the second variable being measured or collected data that relates to the plurality of subjects; and modifying at least one element of the first data type and at least one element of the second data type in the dataset based on the single command. 5. The one or more non-transitory computer-readable media of claim 1 , wherein the first data type is at least one or a combination of: a logical array, a character array, a numeric array, a cell array, a categorical array, a time series object, an array of structures, an array of Java classes, an array of function handles, or an array created using an object-oriented class definition. | 0.5 |
4,511,758 | 1 | 5 | 1. A message communication process between a transmission side and a reception side comprising the steps of: at the transmission side, comparing for all of the characters in a message, a character string of the message to be transmitted with a dictionary, and encoding all of said character string into a variable length compact code according to the content of the dictionary, sending the encoded compact code to the reception side, at the reception side, decoding the encoded compact code with a dictionary having the same content as the dictionary of the transmission side, wherein said dictionary is an electronically controlled dictionary with a memory. | 1. A message communication process between a transmission side and a reception side comprising the steps of: at the transmission side, comparing for all of the characters in a message, a character string of the message to be transmitted with a dictionary, and encoding all of said character string into a variable length compact code according to the content of the dictionary, sending the encoded compact code to the reception side, at the reception side, decoding the encoded compact code with a dictionary having the same content as the dictionary of the transmission side, wherein said dictionary is an electronically controlled dictionary with a memory. 5. A message communication process according to claim 1, wherein said compact code is selected according to a statistical nature of a document so that the length of a compact code is selected according to the appearance frequency of a string. | 0.595318 |
8,868,592 | 1 | 6 | 1. A computer-implemented method, comprising: obtaining first profile data for a first user that is associated with a computing device; obtaining second profile data for second users that submitted search queries, the second users being different from the first user; determining, based on the first profile data and the second profile data, similarity scores that are each indicative of a degree of similarity between the first user and at least one of the second users; selecting a proper subset of the search queries based on the similarity scores; generating an update for an autocomplete cache of the computing device associated with the first user using the selected subset of the search queries; and providing the update to the computing device associated with the first user. | 1. A computer-implemented method, comprising: obtaining first profile data for a first user that is associated with a computing device; obtaining second profile data for second users that submitted search queries, the second users being different from the first user; determining, based on the first profile data and the second profile data, similarity scores that are each indicative of a degree of similarity between the first user and at least one of the second users; selecting a proper subset of the search queries based on the similarity scores; generating an update for an autocomplete cache of the computing device associated with the first user using the selected subset of the search queries; and providing the update to the computing device associated with the first user. 6. The computer-implemented method of claim 1 , wherein: obtaining the first profile data for the first user comprises obtaining current profile data for the first user; and obtaining the second profile data for the second comprises obtaining profile data corresponding to times when the search queries were submitted. | 0.743134 |
8,701,032 | 9 | 10 | 9. The method of claim 7 , wherein determining the respective lexical cost values for each of at least the first key, the second key, and the third key comprises comparing each of at least the first key, the second key, and the third key with a language model. | 9. The method of claim 7 , wherein determining the respective lexical cost values for each of at least the first key, the second key, and the third key comprises comparing each of at least the first key, the second key, and the third key with a language model. 10. The method of claim 9 , wherein the language model comprises an n-gram language model. | 0.526316 |
9,773,499 | 12 | 14 | 12. The medium of claim 10 , the operations comprising: determining a candidate transcription of the utterance, the candidate transcription including a type term corresponding to the first term and a name term corresponding to the second term; determining a geographic location corresponding to the utterance; and determining that the name term does not match a reference name of an entity (i) of the entity type corresponding to the type term and (ii) in a geographic location matching the geographic location, wherein determining that, among the phonetic representations indicated in the records in the entity-type specific, geo-localized entity database for the particular geographic area, a phonetic representation of the second term matches a particular phonetic representation of a particular canonical name of a set of canonical names associated with a particular entity is in response to determining that the name term does not match the reference name of the entity (i) of the entity type corresponding to the type term and (ii) in the geographic location matching the geographic location. | 12. The medium of claim 10 , the operations comprising: determining a candidate transcription of the utterance, the candidate transcription including a type term corresponding to the first term and a name term corresponding to the second term; determining a geographic location corresponding to the utterance; and determining that the name term does not match a reference name of an entity (i) of the entity type corresponding to the type term and (ii) in a geographic location matching the geographic location, wherein determining that, among the phonetic representations indicated in the records in the entity-type specific, geo-localized entity database for the particular geographic area, a phonetic representation of the second term matches a particular phonetic representation of a particular canonical name of a set of canonical names associated with a particular entity is in response to determining that the name term does not match the reference name of the entity (i) of the entity type corresponding to the type term and (ii) in the geographic location matching the geographic location. 14. The medium of claim 12 , wherein determining a geographic location corresponding to the utterance, comprises: determining a location in which the utterance was said. | 0.692727 |
9,265,931 | 1 | 7 | 1. An implantable responsive neurostimulator for treating a language disorder in a patient, comprising: at least one first electrode configured to be implanted in a first region of the patient's brain, the first region being related to the language disorder; at least one second electrode configured to be implanted in a second region of the patient's brain, the second region of the patient's brain for treating the language disorder; at least one third electrode configured to be implanted in a third region of the patient's brain for treating the language disorder, wherein the third region is different from both the first region and the second region; a detection subsystem coupled to the at least one first electrode, and configured to: continuously monitor one or more electrical signals sensed from the first region of the patient's brain during a selected period when the patient is experiencing a stage of sleep; detect in the one or more electrical signals an occurrence of a neurological event that causes a language disorder; and a therapy subsystem coupled to the at least one second electrode, and the at least one third electrode, and configured to, in response to a detection of an occurrence of a neurological event: apply neurostimulation through the at least one second electrode to the second region of the patient's brain; and apply neurostimulation through the at least one third electrode to the third region of the patient's brain. | 1. An implantable responsive neurostimulator for treating a language disorder in a patient, comprising: at least one first electrode configured to be implanted in a first region of the patient's brain, the first region being related to the language disorder; at least one second electrode configured to be implanted in a second region of the patient's brain, the second region of the patient's brain for treating the language disorder; at least one third electrode configured to be implanted in a third region of the patient's brain for treating the language disorder, wherein the third region is different from both the first region and the second region; a detection subsystem coupled to the at least one first electrode, and configured to: continuously monitor one or more electrical signals sensed from the first region of the patient's brain during a selected period when the patient is experiencing a stage of sleep; detect in the one or more electrical signals an occurrence of a neurological event that causes a language disorder; and a therapy subsystem coupled to the at least one second electrode, and the at least one third electrode, and configured to, in response to a detection of an occurrence of a neurological event: apply neurostimulation through the at least one second electrode to the second region of the patient's brain; and apply neurostimulation through the at least one third electrode to the third region of the patient's brain. 7. The neurostimulator of claim 1 , wherein the neurological event comprises at least one of epileptiform activity that causes a language disorder, and an electrographic seizure that causes a language disorder. | 0.788306 |
7,873,622 | 1 | 4 | 1. A system for presenting a graphical user interface (GUI) for displaying search results, the system comprising: a processor; and memory storing instructions that, when executed by the processor, cause the system to generate the graphical user interface on a display device, the graphical user interface comprising: a window having at least two panes arranged as adjacent columns and separated by at least one adjustable column delimiter that visibly marks the boundaries between adjacent panes, a search element that enables a user to submit a search query; said at least two panes configured to collectively, responsive to submission of the search query, each display search results information from a different respective search category in each of said at least two panes, the different respective search category selected from the group consisting of: general web search results, image search results, book search results, movie search results, map search results, local area search results, reference search results, dictionary search results, address based search results, news search results, diary search results, bookmark search results, search history search results and tracking number search results, and each pane being user configurable to be in either an open state suitable for displaying search results information from a particular search category or a closed state in which a column width of the pane is narrowed to a display identifying the particular search category, wherein moving the at least one adjustable column delimiter to a position where a non-zero column width of an adjacent open pane in the open state is below a designated threshold for closing the open pane causes the open pane to automatically be configured in the closed state. | 1. A system for presenting a graphical user interface (GUI) for displaying search results, the system comprising: a processor; and memory storing instructions that, when executed by the processor, cause the system to generate the graphical user interface on a display device, the graphical user interface comprising: a window having at least two panes arranged as adjacent columns and separated by at least one adjustable column delimiter that visibly marks the boundaries between adjacent panes, a search element that enables a user to submit a search query; said at least two panes configured to collectively, responsive to submission of the search query, each display search results information from a different respective search category in each of said at least two panes, the different respective search category selected from the group consisting of: general web search results, image search results, book search results, movie search results, map search results, local area search results, reference search results, dictionary search results, address based search results, news search results, diary search results, bookmark search results, search history search results and tracking number search results, and each pane being user configurable to be in either an open state suitable for displaying search results information from a particular search category or a closed state in which a column width of the pane is narrowed to a display identifying the particular search category, wherein moving the at least one adjustable column delimiter to a position where a non-zero column width of an adjacent open pane in the open state is below a designated threshold for closing the open pane causes the open pane to automatically be configured in the closed state. 4. The system of claim 1 , the graphical user interface further comprising at least one tab, each tab being arranged to mark an associated pane in the closed state and wherein the selection by a user of a tab causes a pane associated with the tab to be configured to be in the open state without closing any already open panes. | 0.531519 |
9,251,138 | 1 | 19 | 1. A computer system for analyzing natural language comprising: a phrase database configured to store phrases; and a phrase analysis engine coupled with the phrase database and configured to: obtain a corpus comprising a plurality of phrases; extract phrases from the corpus; determine a degree of similarity among the phrases based on phrase contexts associated with the phrases and on overlaps among phrase contexts determined by surrounding phrases in the corpus proximate to the phrases; and cluster the phrases into classes within the phrase database based on the degree of similarity among the phrase; and a user interface configured to present a response generated from phrases obtained from the phrase database to a user. | 1. A computer system for analyzing natural language comprising: a phrase database configured to store phrases; and a phrase analysis engine coupled with the phrase database and configured to: obtain a corpus comprising a plurality of phrases; extract phrases from the corpus; determine a degree of similarity among the phrases based on phrase contexts associated with the phrases and on overlaps among phrase contexts determined by surrounding phrases in the corpus proximate to the phrases; and cluster the phrases into classes within the phrase database based on the degree of similarity among the phrase; and a user interface configured to present a response generated from phrases obtained from the phrase database to a user. 19. The system of claim 1 , wherein the phrases relate to a genre. | 0.792453 |
9,946,790 | 7 | 11 | 7. A system, comprising: at least one computing device; and an item categorizing service executable in the at least one computing device, wherein, when executed, the item categorizing service causes the at least one computing device to at least: generate a user interface to facilitate creation of a plurality of user-created item lists via a plurality of client devices; receive the plurality of user-created item lists from the plurality of client devices via the user interface rendered on the plurality of client devices; maintain the plurality of user-created item lists in an item list registry, individual user-created item lists of the plurality of user-created item lists including a plurality of items available for purchase, lease, or download via an electronic commerce system, and the individual user-created item lists being identified by a respective item list title that includes a title term; obtain a particular item list of the plurality of user-created item lists from the item list registry; compare the title term of the particular item list with a plurality of predefined keywords; assign a keyword tag associated with a particular predefined keyword of the plurality of predefined keywords to individual items of the plurality of items included in the particular item list in response to the title term matching the particular predefined keyword; create an item category associated with the particular predefined keyword; and populate the item category associated with the particular predefined keyword with a particular item of the plurality of items based at least in part upon a number of keyword tags assigned to the particular item reaching a predefined threshold. | 7. A system, comprising: at least one computing device; and an item categorizing service executable in the at least one computing device, wherein, when executed, the item categorizing service causes the at least one computing device to at least: generate a user interface to facilitate creation of a plurality of user-created item lists via a plurality of client devices; receive the plurality of user-created item lists from the plurality of client devices via the user interface rendered on the plurality of client devices; maintain the plurality of user-created item lists in an item list registry, individual user-created item lists of the plurality of user-created item lists including a plurality of items available for purchase, lease, or download via an electronic commerce system, and the individual user-created item lists being identified by a respective item list title that includes a title term; obtain a particular item list of the plurality of user-created item lists from the item list registry; compare the title term of the particular item list with a plurality of predefined keywords; assign a keyword tag associated with a particular predefined keyword of the plurality of predefined keywords to individual items of the plurality of items included in the particular item list in response to the title term matching the particular predefined keyword; create an item category associated with the particular predefined keyword; and populate the item category associated with the particular predefined keyword with a particular item of the plurality of items based at least in part upon a number of keyword tags assigned to the particular item reaching a predefined threshold. 11. The system of claim 7 , wherein, when executed, the item categorizing service further causes the at least one computing device to at least determine a number of the plurality of user-created item lists having a respective title term that matches the particular predefined keyword. | 0.735075 |
10,146,747 | 1 | 7 | 1. In an automobile, a text display arrangement comprising: a text display, positioned in the automobile without impairing forward visual attention of a driver, for displaying to the driver a cursor and a subsequence of a sequence of words, the subsequence having a maximum length and including an active word, the cursor for indicating either the active word or a boundary thereof; a control for providing a control input by an occupant of the automobile; and a text processing application in communication with the text display and the control, the text processing application for controlling the display of words by: in response to receiving from the control an input to adjust the cursor: (a) updating the cursor to indicate a new active word within the sequence, or a boundary thereof, and (b) displaying by the text display the cursor and a second subsequence of the sequence of words, the second subsequence determined based upon the new active word and the maximum length; and in response to receiving from the control an input comprising at least one new word, either: (a) replacing the active word with the at least one new word, if the cursor indicates the active word, or (b) inserting the at least one new word between the active word and an adjacent word, if the cursor indicates a boundary between the active word and the adjacent word. | 1. In an automobile, a text display arrangement comprising: a text display, positioned in the automobile without impairing forward visual attention of a driver, for displaying to the driver a cursor and a subsequence of a sequence of words, the subsequence having a maximum length and including an active word, the cursor for indicating either the active word or a boundary thereof; a control for providing a control input by an occupant of the automobile; and a text processing application in communication with the text display and the control, the text processing application for controlling the display of words by: in response to receiving from the control an input to adjust the cursor: (a) updating the cursor to indicate a new active word within the sequence, or a boundary thereof, and (b) displaying by the text display the cursor and a second subsequence of the sequence of words, the second subsequence determined based upon the new active word and the maximum length; and in response to receiving from the control an input comprising at least one new word, either: (a) replacing the active word with the at least one new word, if the cursor indicates the active word, or (b) inserting the at least one new word between the active word and an adjacent word, if the cursor indicates a boundary between the active word and the adjacent word. 7. A text display arrangement according to claim 1 , wherein the control comprises a multifunction knob or a speech recognition system. | 0.810924 |
8,331,739 | 16 | 17 | 16. The computer system of claim 14 , wherein the user interface displays a snippet of text adjacent to the original segment of text and highlights the original segment of text, wherein the user interface further displays options allowing the human operator to select the correct answer from among a set of answers, wherein the set of answers include the first segment of text, the second segment of text, and a text entry box the human operator can use to provide the correct answer. | 16. The computer system of claim 14 , wherein the user interface displays a snippet of text adjacent to the original segment of text and highlights the original segment of text, wherein the user interface further displays options allowing the human operator to select the correct answer from among a set of answers, wherein the set of answers include the first segment of text, the second segment of text, and a text entry box the human operator can use to provide the correct answer. 17. The computer system of claim 16 , wherein portions of the first segment of text and portions of the second segment of text that differ are highlighted in the user interface. | 0.5 |
8,463,782 | 1 | 11 | 1. A computer-implemented method comprising: traversing a corpus of documents to identify a plurality of lists within the documents, wherein each list comprises structured data delimited from other data in a document, and wherein each list specifies an enumeration of elements; selecting a pair of terms based on determining that both terms of the pair are contained in a first quantity of lists that are included in the documents in the corpus, wherein the first quantity is more than a first predetermined quantity, and wherein each list in the first quantity of lists includes more than a second predetermined quantity of terms; determining a first value that represents a quantity of documents in the corpus that include a list that contains both terms of the pair; determining a second value that represents a quantity of the documents in the set corpus that include a list that contains at least one of the terms of the pair; when both terms of the pair are contained in the first quantity of lists that are included in the documents in the corpus, determining a correlation value from the first value and the second value; determining that the correlation value satisfies a threshold; and designating, by one or more computers, the pair of terms as potentially non-synonymous terms by adding the pair of terms to a blacklist, based on determining that the correlation value satisfies the threshold, wherein the blacklist is accessed for synonym determination. | 1. A computer-implemented method comprising: traversing a corpus of documents to identify a plurality of lists within the documents, wherein each list comprises structured data delimited from other data in a document, and wherein each list specifies an enumeration of elements; selecting a pair of terms based on determining that both terms of the pair are contained in a first quantity of lists that are included in the documents in the corpus, wherein the first quantity is more than a first predetermined quantity, and wherein each list in the first quantity of lists includes more than a second predetermined quantity of terms; determining a first value that represents a quantity of documents in the corpus that include a list that contains both terms of the pair; determining a second value that represents a quantity of the documents in the set corpus that include a list that contains at least one of the terms of the pair; when both terms of the pair are contained in the first quantity of lists that are included in the documents in the corpus, determining a correlation value from the first value and the second value; determining that the correlation value satisfies a threshold; and designating, by one or more computers, the pair of terms as potentially non-synonymous terms by adding the pair of terms to a blacklist, based on determining that the correlation value satisfies the threshold, wherein the blacklist is accessed for synonym determination. 11. The method of claim 1 , wherein one or more lists in the plurality of lists comprise structured data consisting of enumerated pieces of information within a HyperText Markup Language (HTML) page. | 0.810115 |
8,438,032 | 12 | 13 | 12. The method in accordance with claim 11 , wherein highlighting further includes receiving a user selection of the highlighted portion to convert said synthesized speech to a SSML representation. | 12. The method in accordance with claim 11 , wherein highlighting further includes receiving a user selection of the highlighted portion to convert said synthesized speech to a SSML representation. 13. The method in accordance with claim 12 , further comprising: adding a paralinguistic as SSML codes to said user supplied text. | 0.5 |
8,818,092 | 14 | 15 | 14. The system of claim 13 further comprising: an assembler configured to generate, based on the composited image bitmap, a resultant image comprising the rendering of the text block on the source image, wherein the alpha-numeric string for each text segment is rendered based on its corresponding formatting information. | 14. The system of claim 13 further comprising: an assembler configured to generate, based on the composited image bitmap, a resultant image comprising the rendering of the text block on the source image, wherein the alpha-numeric string for each text segment is rendered based on its corresponding formatting information. 15. The system of claim 14 wherein the segmenter is configured to determine the image bitmap of the source image, based on a decompression of the source image from an image file-type, and the assembler is configured to compress the composited image bitmap into a resultant image, wherein the resultant image is of the image file-type. | 0.5 |
8,498,906 | 1 | 16 | 1. A method comprising: receiving at least two sets of attributes and values for a product through a communications network, each set of attributes representing quantifiable properties of the product and each set of values representing numerical quantities of the respective properties, wherein there is at least one difference between each of the sets of attributes and values; forming a collaborative component taxonomy instantiation, the taxonomy instantiation comprising a union of distinct attributes and values obtained from the at least two sets of attributes and values; associating a unique identifier with the formed collaborative component taxonomy instantiation; comparing the union of product attributes and values in the collaborative component taxonomy instantiation to product catalog information received from different computing systems through a communications network; associating the unique identifier with those matching products included in the received product catalog information based on the comparing; and distributing the unique identifier and the association with a corresponding matching product to each computing system having product catalog information containing the corresponding matching product through the communications network, wherein the unique identifier is associated with each matching product at each computing system through the distributing. | 1. A method comprising: receiving at least two sets of attributes and values for a product through a communications network, each set of attributes representing quantifiable properties of the product and each set of values representing numerical quantities of the respective properties, wherein there is at least one difference between each of the sets of attributes and values; forming a collaborative component taxonomy instantiation, the taxonomy instantiation comprising a union of distinct attributes and values obtained from the at least two sets of attributes and values; associating a unique identifier with the formed collaborative component taxonomy instantiation; comparing the union of product attributes and values in the collaborative component taxonomy instantiation to product catalog information received from different computing systems through a communications network; associating the unique identifier with those matching products included in the received product catalog information based on the comparing; and distributing the unique identifier and the association with a corresponding matching product to each computing system having product catalog information containing the corresponding matching product through the communications network, wherein the unique identifier is associated with each matching product at each computing system through the distributing. 16. The method of claim 1 , further comprising searching a set of form, fit and function characteristics in the taxonomy instantiation to identify an actual product. | 0.671315 |
5,559,969 | 14 | 18 | 14. An improvement according to claim 10 wherein said first control means further controls which of the plurality of sub-packets of each of said plurality of first data packets are assembled into each of the plurality of groups. | 14. An improvement according to claim 10 wherein said first control means further controls which of the plurality of sub-packets of each of said plurality of first data packets are assembled into each of the plurality of groups. 18. An improvement according to claim 14 wherein said first control means is instruction programmable, such instruction having control bits for programmable control such that any predetermined one of the plurality of sub-packets the plurality of first data packets may be assembled together with any other predetermined one of the plurality of sub-packets the plurality of first data packets to form one of the plurality of groups. | 0.5 |
8,392,270 | 1 | 11 | 1. A method comprising: receiving a search request including at least one keyword, from a first user, to search for an item offered for sale in item listings from a network-based marketplace of a network-based social platform via an interface provided by a social networking website of the network-based social platform, the network-based social platform being a platform that allows the first user to communicatively couple with at least a second user with whom the first user has a pre-established relationship that is stored in a user profile of the first user at the network-based social platform; performing a search using the at least one keyword on the network-based marketplace of the social networking platform to retrieve a plurality of listings of items offered for sale on the network-based marketplace of the network-based social platform; providing a search result, based on the performing of the search, that indicates the plurality of listing of items offered for sale on the network-based marketplace of the network-based social platform to the interface associated with the first user for display; receiving a selection of one of the plurality of listings of items form the search result from the first user to share information concerning the item selected from the search result to at least the second user; and sharing, using at least one processor, the information concerning the item to at least the second user. | 1. A method comprising: receiving a search request including at least one keyword, from a first user, to search for an item offered for sale in item listings from a network-based marketplace of a network-based social platform via an interface provided by a social networking website of the network-based social platform, the network-based social platform being a platform that allows the first user to communicatively couple with at least a second user with whom the first user has a pre-established relationship that is stored in a user profile of the first user at the network-based social platform; performing a search using the at least one keyword on the network-based marketplace of the social networking platform to retrieve a plurality of listings of items offered for sale on the network-based marketplace of the network-based social platform; providing a search result, based on the performing of the search, that indicates the plurality of listing of items offered for sale on the network-based marketplace of the network-based social platform to the interface associated with the first user for display; receiving a selection of one of the plurality of listings of items form the search result from the first user to share information concerning the item selected from the search result to at least the second user; and sharing, using at least one processor, the information concerning the item to at least the second user. 11. The method of claim 1 , further comprising determining whether the first user is allowed to share the information to the second user based on the pre-established relationship. | 0.627083 |
9,436,951 | 1 | 6 | 1. A computer-implemented method of presenting additional content for a term presented by a first mobile communication device, the computer-implemented method comprising: receiving, by the first mobile communication device, a first utterance; transmitting, by the first mobile communication device, a first identifier of the first mobile communication device and the first utterance to a server; receiving, by the first mobile communication device from the server, text representing a transcription of the first utterance; receiving, by the first mobile communication device from the server, an indicator that first additional content is available for a term identified within the text by the indicator, wherein the term is associated at the server with the first identifier of the first mobile communication device and a second identifier of a second mobile communication device, and wherein the first additional content for the term is associated with the first identifier and the second identifier; presenting, on the first mobile communication device, the text with an emphasis on the term identified by the indicator; after presenting the text on the first mobile communication device, receiving, by the first mobile communication device, a second utterance that includes the term; transmitting, by the first mobile communication device, the first identifier and the second utterance to the server; receiving, by the first mobile communication device from the server, in response to transmitting the second utterance and the first identifier, the first additional content; presenting, on the first mobile communication device the first additional content for the term; transmitting, by the first mobile communication device, the second identifier to the server, the server configured to send the text as well as the indicator that first additional content is available for the term to the second mobile communication device using the second identifier of the second mobile communication device; and receiving, by the first mobile communication device from the server, a message including a transcribed third utterance received by the second communication device in response to the text. | 1. A computer-implemented method of presenting additional content for a term presented by a first mobile communication device, the computer-implemented method comprising: receiving, by the first mobile communication device, a first utterance; transmitting, by the first mobile communication device, a first identifier of the first mobile communication device and the first utterance to a server; receiving, by the first mobile communication device from the server, text representing a transcription of the first utterance; receiving, by the first mobile communication device from the server, an indicator that first additional content is available for a term identified within the text by the indicator, wherein the term is associated at the server with the first identifier of the first mobile communication device and a second identifier of a second mobile communication device, and wherein the first additional content for the term is associated with the first identifier and the second identifier; presenting, on the first mobile communication device, the text with an emphasis on the term identified by the indicator; after presenting the text on the first mobile communication device, receiving, by the first mobile communication device, a second utterance that includes the term; transmitting, by the first mobile communication device, the first identifier and the second utterance to the server; receiving, by the first mobile communication device from the server, in response to transmitting the second utterance and the first identifier, the first additional content; presenting, on the first mobile communication device the first additional content for the term; transmitting, by the first mobile communication device, the second identifier to the server, the server configured to send the text as well as the indicator that first additional content is available for the term to the second mobile communication device using the second identifier of the second mobile communication device; and receiving, by the first mobile communication device from the server, a message including a transcribed third utterance received by the second communication device in response to the text. 6. The method of claim 1 , wherein presenting the text on the first mobile communication device with an emphasis on the term identified by the indicator comprises displaying the text on the first mobile communication device such that the term is highlighted. | 0.715859 |
8,976,946 | 1 | 5 | 1. A communication apparatus, comprising: a communication portion for communicating with an external device; a transmitter information acquiring portion for acquiring predetermined transmitter information for identifying a transmitter at a time of an incoming call of communication; a storage portion for storing a registered name in association with the transmitter information in advance; a registered name retrieval portion for, based on the transmitter information acquired by the transmitter information acquiring portion at the time of the incoming call of the communication, retrieving the registered name stored in the storage portion corresponding to the acquired transmitter information; a common part extraction portion for, in a case where a plurality of registered names are retrieved with respect to the transmitter information acquired by the transmitter information acquiring portion when the registered name is retrieved by the registered name retrieval portion, extracting a common part among the plurality of registered names; and an output portion for outputting the common part of the registered names which is extracted by the common part extraction portion, in a predetermined system. | 1. A communication apparatus, comprising: a communication portion for communicating with an external device; a transmitter information acquiring portion for acquiring predetermined transmitter information for identifying a transmitter at a time of an incoming call of communication; a storage portion for storing a registered name in association with the transmitter information in advance; a registered name retrieval portion for, based on the transmitter information acquired by the transmitter information acquiring portion at the time of the incoming call of the communication, retrieving the registered name stored in the storage portion corresponding to the acquired transmitter information; a common part extraction portion for, in a case where a plurality of registered names are retrieved with respect to the transmitter information acquired by the transmitter information acquiring portion when the registered name is retrieved by the registered name retrieval portion, extracting a common part among the plurality of registered names; and an output portion for outputting the common part of the registered names which is extracted by the common part extraction portion, in a predetermined system. 5. The communication apparatus as defined in claim 1 , wherein the output portion causes a predetermined display portion to display and output the information including the common part among the registered names. | 0.57085 |
7,957,954 | 4 | 5 | 4. The computer program product of claim 1 , wherein the method determines that no translation in the multi-language property file includes a label that comprises the ascertained language identifier and the ascertained locale identifier, and wherein the label of the selected translation comprises the ascertained language identifier but not the ascertained locale identifier. | 4. The computer program product of claim 1 , wherein the method determines that no translation in the multi-language property file includes a label that comprises the ascertained language identifier and the ascertained locale identifier, and wherein the label of the selected translation comprises the ascertained language identifier but not the ascertained locale identifier. 5. The computer program product of claim 4 , wherein the class pertaining to the selected translation is buttons, wherein the key value is select and pertains to a select button that is a member of the class of buttons, wherein the language identified by the ascertained language identifier is English, and wherein the locale identified by the ascertained locale identifier is Sweden. | 0.5 |
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