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8,126,832 | 1 | 7 | 1. A method for a computer system to interpret an input from a user and generate a response, comprising: receiving a user input; converting the user input into an input array comprising rows and columns having a plurality of concepts; determining if any of the plurality of concepts in the input array is derived from a root concept; if any of the plurality of concepts is derived from a root concept, replacing each such derived concept with the corresponding root concept, identifying one or more related concepts that relate to the root concept, and generating a multi-dimensional array based on the input array that includes the one or more related concepts; generating one or more additional multi-dimensional arrays, based on the input, containing any composite concepts, each derived from two or more concepts contained in the original array; marking one or more concepts in the multi-dimensional arrays as essential based on application-specific criteria; correlating a plurality of concepts in the multi-dimensional array to a plurality of first elements in a database by comparing a plurality of linear arrays derived from the multidimensional array to the plurality of elements in the database, wherein the first elements in the database includes a link to a second element in the database do not comprise possible responses; determining a plurality of possible responses to the user input based on the correlation of the multi-dimensional array and the plurality of elements in the database; and generating a response to the user input. | 1. A method for a computer system to interpret an input from a user and generate a response, comprising: receiving a user input; converting the user input into an input array comprising rows and columns having a plurality of concepts; determining if any of the plurality of concepts in the input array is derived from a root concept; if any of the plurality of concepts is derived from a root concept, replacing each such derived concept with the corresponding root concept, identifying one or more related concepts that relate to the root concept, and generating a multi-dimensional array based on the input array that includes the one or more related concepts; generating one or more additional multi-dimensional arrays, based on the input, containing any composite concepts, each derived from two or more concepts contained in the original array; marking one or more concepts in the multi-dimensional arrays as essential based on application-specific criteria; correlating a plurality of concepts in the multi-dimensional array to a plurality of first elements in a database by comparing a plurality of linear arrays derived from the multidimensional array to the plurality of elements in the database, wherein the first elements in the database includes a link to a second element in the database do not comprise possible responses; determining a plurality of possible responses to the user input based on the correlation of the multi-dimensional array and the plurality of elements in the database; and generating a response to the user input. 7. The method of claim 1 , wherein the multi-dimensional array comprises a plurality of tokens and wherein each token corresponds to a concept. | 0.76634 |
7,885,793 | 11 | 14 | 11. A process for supporting computing infrastructure, said process comprising providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer-readable code in a computing system, wherein the code in combination with the computing system is capable of performing a method of developing an information technology solution via development of a conceptual model, said method comprising: defining, by one or more business stakeholders associated with a business, a plurality of requirements of an information technology (IT) solution owned by said business, wherein said requirements indicate a plurality of functions of said business to be supported by said IT solution; said one or more business stakeholders and one or more IT stakeholders associated with said business developing a conceptual model by developing a conceptual structure and subsequently developing a plurality of operational concepts, said conceptual model including said conceptual structure and said plurality of operational concepts and providing a representation of said IT solution, said conceptual structure including a plurality of conceptual components, said plurality of conceptual components being icons, forms, shapes and/or figures determined by outlines that modularly represent one or more IT systems, one or more hardware components of said one or more IT systems and one or more software components of said one or more IT systems, said one or more IT systems, said one or more hardware components and said one or more IT systems being manifestations (manifested conceptual components) of said plurality of conceptual components in an implementation of said IT solution, and said plurality of operational concepts indicating interactions among said manifested conceptual components to perform said plurality of functions of said business, wherein said developing said conceptual structure includes: defining said conceptual structure based on a functional analysis of said plurality of functions of said business by said one or more business stakeholders and said one or more IT stakeholders; and subsequent to said defining said conceptual structure, refining said conceptual structure by: refining said conceptual structure based on a first analysis of interactions of one or more users with said IT solution; refining said conceptual structure based on a second analysis of a business model of said business; refining said conceptual structure based on a third analysis of how said manifested conceptual components interact with each other to support a business operational model of said business, said business operational model being a description by said one or more business stakeholders of how said business operates to attain one or more operational goals of said business; refining said conceptual structure based on a fourth analysis of one or more internal processes and one or more algorithms, said one or more internal processes associated with an operation of a set of manifested conceptual components included in said manifested conceptual components and with interactions therebetween, and said one or more algorithms associated with said operation of said set of manifested conceptual components and with said interactions therebetween; refining said conceptual structure based on a fifth analysis of one or more requirements for communication among said manifested conceptual components, between said IT solution and one or more systems of said IT solution, and between said IT solution and one or more systems external to said IT solution; refining said conceptual structure based on a sixth analysis of one or more requirements for capturing, storing, retrieving and managing information internal to said one or more systems of said IT solution; and refining said conceptual structure based on a seventh analysis of non-functional requirements of said IT solution, wherein a result of said refining said conceptual structure is a refinement of said conceptual structure, wherein said refinement includes a new conceptual component added to said plurality of conceptual components, wherein said refinement further includes a partition of a conceptual component of said plurality of conceptual components into two or more conceptual components that are added to said plurality of conceptual components and/or an aggregation of at least two conceptual components of said plurality of conceptual components into a new composite conceptual component added to said plurality of conceptual components, wherein said subsequently developing said plurality of operational concepts includes: prior to developing an architecture and a design of said IT solution, generating a description of said plurality of operational concepts based on said refinement of said conceptual structure, said description including: a first description of said plurality of conceptual components included in said refinement of said conceptual structure, a second description of said plurality of functions, said one or more internal processes, and said one or more algorithms supported by said manifested conceptual components represented by said plurality of conceptual components included in said refinement of said conceptual structure, a third description of information management needs of said manifested conceptual components represented by said plurality of conceptual components included in said refinement of said conceptual structure, a fourth description of how said manifested conceptual components represented by said plurality of conceptual components included in said refinement of said conceptual structure interact among themselves to perform said plurality of functions of said business, a fifth description of how said business model relates to an organization of said plurality of conceptual components included in said refinement of said conceptual structure, and a sixth description of how said non-functional requirements are addressed by said IT solution and by said manifested conceptual components represented by said plurality of components included in said refinement of said conceptual structure; and generating a diagram representing an overview of said IT solution and including said refinement of said conceptual structure; a computing system retrieving said diagram representing said overview of said IT solution and including said refinement of said conceptual structure and generating a documentation that includes said diagram and said description of said plurality of operational concepts; developing said architecture and said design of said IT solution by said one or more IT stakeholders based on said developed conceptual model and said documentation that includes said diagram representing said overview of said IT solution and said description of said plurality of operational concepts, wherein said description of said plurality of operational concepts included in said documentation that is a basis for said architecture and said design of said IT solution indicates said interactions among said manifested conceptual components to perform said plurality of functions of said business; and generating, by said one or more IT stakeholders, a second documentation of said architecture and said design of said IT solution. | 11. A process for supporting computing infrastructure, said process comprising providing at least one support service for at least one of creating, integrating, hosting, maintaining, and deploying computer-readable code in a computing system, wherein the code in combination with the computing system is capable of performing a method of developing an information technology solution via development of a conceptual model, said method comprising: defining, by one or more business stakeholders associated with a business, a plurality of requirements of an information technology (IT) solution owned by said business, wherein said requirements indicate a plurality of functions of said business to be supported by said IT solution; said one or more business stakeholders and one or more IT stakeholders associated with said business developing a conceptual model by developing a conceptual structure and subsequently developing a plurality of operational concepts, said conceptual model including said conceptual structure and said plurality of operational concepts and providing a representation of said IT solution, said conceptual structure including a plurality of conceptual components, said plurality of conceptual components being icons, forms, shapes and/or figures determined by outlines that modularly represent one or more IT systems, one or more hardware components of said one or more IT systems and one or more software components of said one or more IT systems, said one or more IT systems, said one or more hardware components and said one or more IT systems being manifestations (manifested conceptual components) of said plurality of conceptual components in an implementation of said IT solution, and said plurality of operational concepts indicating interactions among said manifested conceptual components to perform said plurality of functions of said business, wherein said developing said conceptual structure includes: defining said conceptual structure based on a functional analysis of said plurality of functions of said business by said one or more business stakeholders and said one or more IT stakeholders; and subsequent to said defining said conceptual structure, refining said conceptual structure by: refining said conceptual structure based on a first analysis of interactions of one or more users with said IT solution; refining said conceptual structure based on a second analysis of a business model of said business; refining said conceptual structure based on a third analysis of how said manifested conceptual components interact with each other to support a business operational model of said business, said business operational model being a description by said one or more business stakeholders of how said business operates to attain one or more operational goals of said business; refining said conceptual structure based on a fourth analysis of one or more internal processes and one or more algorithms, said one or more internal processes associated with an operation of a set of manifested conceptual components included in said manifested conceptual components and with interactions therebetween, and said one or more algorithms associated with said operation of said set of manifested conceptual components and with said interactions therebetween; refining said conceptual structure based on a fifth analysis of one or more requirements for communication among said manifested conceptual components, between said IT solution and one or more systems of said IT solution, and between said IT solution and one or more systems external to said IT solution; refining said conceptual structure based on a sixth analysis of one or more requirements for capturing, storing, retrieving and managing information internal to said one or more systems of said IT solution; and refining said conceptual structure based on a seventh analysis of non-functional requirements of said IT solution, wherein a result of said refining said conceptual structure is a refinement of said conceptual structure, wherein said refinement includes a new conceptual component added to said plurality of conceptual components, wherein said refinement further includes a partition of a conceptual component of said plurality of conceptual components into two or more conceptual components that are added to said plurality of conceptual components and/or an aggregation of at least two conceptual components of said plurality of conceptual components into a new composite conceptual component added to said plurality of conceptual components, wherein said subsequently developing said plurality of operational concepts includes: prior to developing an architecture and a design of said IT solution, generating a description of said plurality of operational concepts based on said refinement of said conceptual structure, said description including: a first description of said plurality of conceptual components included in said refinement of said conceptual structure, a second description of said plurality of functions, said one or more internal processes, and said one or more algorithms supported by said manifested conceptual components represented by said plurality of conceptual components included in said refinement of said conceptual structure, a third description of information management needs of said manifested conceptual components represented by said plurality of conceptual components included in said refinement of said conceptual structure, a fourth description of how said manifested conceptual components represented by said plurality of conceptual components included in said refinement of said conceptual structure interact among themselves to perform said plurality of functions of said business, a fifth description of how said business model relates to an organization of said plurality of conceptual components included in said refinement of said conceptual structure, and a sixth description of how said non-functional requirements are addressed by said IT solution and by said manifested conceptual components represented by said plurality of components included in said refinement of said conceptual structure; and generating a diagram representing an overview of said IT solution and including said refinement of said conceptual structure; a computing system retrieving said diagram representing said overview of said IT solution and including said refinement of said conceptual structure and generating a documentation that includes said diagram and said description of said plurality of operational concepts; developing said architecture and said design of said IT solution by said one or more IT stakeholders based on said developed conceptual model and said documentation that includes said diagram representing said overview of said IT solution and said description of said plurality of operational concepts, wherein said description of said plurality of operational concepts included in said documentation that is a basis for said architecture and said design of said IT solution indicates said interactions among said manifested conceptual components to perform said plurality of functions of said business; and generating, by said one or more IT stakeholders, a second documentation of said architecture and said design of said IT solution. 14. The process of claim 11 , wherein said refining said conceptual structure includes generating said plurality of conceptual components as a plurality of modular representations that are independent of any technology used to implement said one or more IT systems represented by said plurality of conceptual components. | 0.828877 |
8,886,519 | 13 | 20 | 13. A text processing method for performing an analysis process by contrasting a first text set constituted by first texts and a second text set constituted by second texts corresponding to the first texts, with a computer, the first texts and the second texts corresponding thereto being generated around a same event through mutually different generation processes, the text processing method comprising the steps of: (a) determining by the computer, with respect to a homogeneous segment that is similar to a plurality of segments constituting a first text which is set as an analysis target and that is included in another first text, whether a content thereof is included in the second texts; and (b) determining by the computer, based on a result of the determination in the (a) step, whether each segment constituting the first text which is set as the analysis target should be described in the second text corresponding to the first text which is set as the analysis target. | 13. A text processing method for performing an analysis process by contrasting a first text set constituted by first texts and a second text set constituted by second texts corresponding to the first texts, with a computer, the first texts and the second texts corresponding thereto being generated around a same event through mutually different generation processes, the text processing method comprising the steps of: (a) determining by the computer, with respect to a homogeneous segment that is similar to a plurality of segments constituting a first text which is set as an analysis target and that is included in another first text, whether a content thereof is included in the second texts; and (b) determining by the computer, based on a result of the determination in the (a) step, whether each segment constituting the first text which is set as the analysis target should be described in the second text corresponding to the first text which is set as the analysis target. 20. The text processing method according to claim 13 , wherein the (a) step includes the steps of: (x) determining, for the plurality of segments respectively constituting all of the first texts, whether a content of each segment is included in the second text corresponding to the first text which includes the segment, and (y) specifying, by contrasting each of the plurality of segments constituting the first text which is set as the analysis target and a segment that is determined in the (x) step to be included in the second text and that is included in another first text, a segment similar to any of the plurality of segments constituting the first text which is set as the analysis target, and setting the specified segment as a homogeneous segment. | 0.5 |
8,938,394 | 1 | 3 | 1. A method comprising: determining, by a first computing device, a context of the first computing device, the context including an indication that a second computing device is proximate to the first computing device; determining, by the first computing device, based at least in part on the context, a subset of contextual audio triggers from a plurality of contextual audio triggers, each contextual audio trigger from the plurality of contextual audio triggers usable to initiate interaction with the first computing device, wherein each contextual audio trigger from the subset of contextual audio triggers is associated with a respective operation of the first computing device and with the context of the computing device, and wherein one of the subset of contextual audio triggers is associated with a first operation to cause the second computing device to perform a second operation; receiving, by the first computing device, audio data; and responsive to determining that a portion of the audio data corresponds to a particular contextual audio trigger from the subset of contextual audio triggers, performing, by the first computing device, the respective operation associated with the particular contextual audio trigger. | 1. A method comprising: determining, by a first computing device, a context of the first computing device, the context including an indication that a second computing device is proximate to the first computing device; determining, by the first computing device, based at least in part on the context, a subset of contextual audio triggers from a plurality of contextual audio triggers, each contextual audio trigger from the plurality of contextual audio triggers usable to initiate interaction with the first computing device, wherein each contextual audio trigger from the subset of contextual audio triggers is associated with a respective operation of the first computing device and with the context of the computing device, and wherein one of the subset of contextual audio triggers is associated with a first operation to cause the second computing device to perform a second operation; receiving, by the first computing device, audio data; and responsive to determining that a portion of the audio data corresponds to a particular contextual audio trigger from the subset of contextual audio triggers, performing, by the first computing device, the respective operation associated with the particular contextual audio trigger. 3. The method of claim 1 , wherein determining the subset of contextual audio triggers comprises: sending, by the first computing device, to a computing system, at least an indication of the context; and receiving, by the first computing device and from the computing system, an indication of at least one candidate audio command, wherein the at least one candidate audio command was previously used at least at a threshold frequency in the context. | 0.693306 |
9,892,096 | 1 | 5 | 1. A method for identifying and inserting hyperlinks within a software application, the method comprising: receiving a request, from a sender, for one or more recommended hyperlinks, wherein: the request includes a keyword, a search requirement, and corresponds to a location for a hyperlink insertion in a first communication with a first contact using a software application; the search requirement is that information to be searched is exclusively contents of websites stored within an Internet browsing history; and the first communication with the first contact utilizes a first method of communication; receiving contextual information about the request, wherein the contextual information includes a first hyperlink previously inserted into a second communication with the first contact, and wherein the second communication with the first contact utilizes a second method of communication; determining, by one or more processors, that the keyword is within contents of a first website accessible by the first hyperlink and that the first website is stored within the Internet browsing history; presenting, by one or more processors, one or more hyperlinks, including the first hyperlink, for selection by the sender, corresponding to the contextual information, the keyword, and the search requirement, based on the previous insertion of the first hyperlink into the second communication with the first contact and presence of the keyword within contents of the first website accessible by the first hyperlink; receiving a selected hyperlink from the one or more hyperlinks; and inserting the selected hyperlink at the location in the first communication with the first contact. | 1. A method for identifying and inserting hyperlinks within a software application, the method comprising: receiving a request, from a sender, for one or more recommended hyperlinks, wherein: the request includes a keyword, a search requirement, and corresponds to a location for a hyperlink insertion in a first communication with a first contact using a software application; the search requirement is that information to be searched is exclusively contents of websites stored within an Internet browsing history; and the first communication with the first contact utilizes a first method of communication; receiving contextual information about the request, wherein the contextual information includes a first hyperlink previously inserted into a second communication with the first contact, and wherein the second communication with the first contact utilizes a second method of communication; determining, by one or more processors, that the keyword is within contents of a first website accessible by the first hyperlink and that the first website is stored within the Internet browsing history; presenting, by one or more processors, one or more hyperlinks, including the first hyperlink, for selection by the sender, corresponding to the contextual information, the keyword, and the search requirement, based on the previous insertion of the first hyperlink into the second communication with the first contact and presence of the keyword within contents of the first website accessible by the first hyperlink; receiving a selected hyperlink from the one or more hyperlinks; and inserting the selected hyperlink at the location in the first communication with the first contact. 5. The method of claim 1 , wherein the step of receiving contextual information about the request further comprises: retrieving textual information near the location in the first communication with the first contact; and analyzing, by one or more processors, the text of the textual information near the location in the first communication with the first contact to determine contextual information. | 0.5 |
8,954,465 | 19 | 20 | 19. The method of claim 17 , further comprising sending an unmodified partial query suggestion request for the partial query, the unmodified partial query suggestion request containing the descriptive term. | 19. The method of claim 17 , further comprising sending an unmodified partial query suggestion request for the partial query, the unmodified partial query suggestion request containing the descriptive term. 20. The method of claim 19 , wherein the step of sending the unmodified partial query suggestion request generates at least one unmodified suggestion result. | 0.644796 |
7,788,248 | 84 | 87 | 84. A machine-implemented method comprising: receiving, through a hardware input device, a first search input within a search field of a web browser application; determining, based on characteristics of the first search input, whether the first search input triggers an automatic submission of a first query to a search engine; determining, based on characteristics of the first search input, whether to delay the trigger for automatic transmission, wherein the first query is automatically submitted to the search engine if the first search input satisfies a temporal trigger, wherein the temporal trigger is based upon a connection speed to the search engine; automatically submitting the first query to the search engine, the first query based on the received first search input; and determining whether a first results web page returned by the search engine based on the submitted first query includes a suggestion for an alternate spelling of a term within the first search input. | 84. A machine-implemented method comprising: receiving, through a hardware input device, a first search input within a search field of a web browser application; determining, based on characteristics of the first search input, whether the first search input triggers an automatic submission of a first query to a search engine; determining, based on characteristics of the first search input, whether to delay the trigger for automatic transmission, wherein the first query is automatically submitted to the search engine if the first search input satisfies a temporal trigger, wherein the temporal trigger is based upon a connection speed to the search engine; automatically submitting the first query to the search engine, the first query based on the received first search input; and determining whether a first results web page returned by the search engine based on the submitted first query includes a suggestion for an alternate spelling of a term within the first search input. 87. The method of claim 84 , further comprising: automatically displaying at least a portion of a suggestion within the search field; wherein said suggestion is for an alternative spelling of a term within the first search input. | 0.704134 |
8,005,823 | 1 | 2 | 1. A system, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises program instructions executable by the processor to: group users into a plurality of distinct communities according to one or more grouping criteria, such that for each particular one of the communities, members of the particular community share at least one grouping criterion in common, and wherein membership of at least some of the communities does not completely overlap; store indications of membership of each of the communities; receive a query from a member of one or more of the communities, and in response to the query: obtain results of the query; determine one or more of the plurality of communities to associate with the query, wherein the determining comprises comparing the query to queries entered by other members of the one or more of the plurality of communities such that the member from which the query is received is a member of the determined one or more communities, and the determined one or more communities are distinct from others of the plurality of communities; identify other results from only the determined one or more communities, wherein the other results are for at least one other query from at least one other member of the determined one or more communities, and wherein the other results reflect user feedback from the at least one other member of the determined one or more communities; compare the results to the other results from the determined one or more communities to determine a measure of similarity between the results and the other results; and modify the results according to the other results in response to determining that the measure of similarity is above a predetermined threshold, wherein the results are not modified according to the other results if the measure of similarity is not above the predetermined threshold. | 1. A system, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises program instructions executable by the processor to: group users into a plurality of distinct communities according to one or more grouping criteria, such that for each particular one of the communities, members of the particular community share at least one grouping criterion in common, and wherein membership of at least some of the communities does not completely overlap; store indications of membership of each of the communities; receive a query from a member of one or more of the communities, and in response to the query: obtain results of the query; determine one or more of the plurality of communities to associate with the query, wherein the determining comprises comparing the query to queries entered by other members of the one or more of the plurality of communities such that the member from which the query is received is a member of the determined one or more communities, and the determined one or more communities are distinct from others of the plurality of communities; identify other results from only the determined one or more communities, wherein the other results are for at least one other query from at least one other member of the determined one or more communities, and wherein the other results reflect user feedback from the at least one other member of the determined one or more communities; compare the results to the other results from the determined one or more communities to determine a measure of similarity between the results and the other results; and modify the results according to the other results in response to determining that the measure of similarity is above a predetermined threshold, wherein the results are not modified according to the other results if the measure of similarity is not above the predetermined threshold. 2. The system of claim 1 , wherein the program instructions are further executable to receive user feedback regarding the modified results from the community member, wherein the feedback specifies a level of correctness for at least one of the results, and wherein the feedback comprises feedback explicitly indicated by the community member selecting a positive or negative indication from among a plurality of indications. | 0.5 |
8,126,715 | 1 | 3 | 1. One or more processor-accessible tangible storage media storing processor-executable instructions for facilitating multimodal interaction, wherein the processor-executable instructions, when executed by a processor, perform a method comprising: receiving a spoken utterance including two or more terms, the two or more terms not being recognized as a permissible phrase that is in-grammar for a grammar-based speech application; recognizing one or more acceptable terms that are in-vocabulary from among the two or more terms of the spoken utterance; searching an index using the one or more acceptable terms as query terms; producing, from the searching of the index, at least one permissible phrase that is in-grammar and that includes the one or more acceptable terms; the index comprising a searchable data structure that represents multiple possible grammar paths that are ascertainable based on acceptable values for each term position of the grammar-based speech application; and presenting at least one permissible phrase to a user as at least one option that may be selected to conduct multimodal interaction with the device. | 1. One or more processor-accessible tangible storage media storing processor-executable instructions for facilitating multimodal interaction, wherein the processor-executable instructions, when executed by a processor, perform a method comprising: receiving a spoken utterance including two or more terms, the two or more terms not being recognized as a permissible phrase that is in-grammar for a grammar-based speech application; recognizing one or more acceptable terms that are in-vocabulary from among the two or more terms of the spoken utterance; searching an index using the one or more acceptable terms as query terms; producing, from the searching of the index, at least one permissible phrase that is in-grammar and that includes the one or more acceptable terms; the index comprising a searchable data structure that represents multiple possible grammar paths that are ascertainable based on acceptable values for each term position of the grammar-based speech application; and presenting at least one permissible phrase to a user as at least one option that may be selected to conduct multimodal interaction with the device. 3. The one or more processor-accessible tangible storage media as recited in claim 1 , wherein the method comprises: traversing the multiple possible grammar paths of the grammar-based speech application based on the acceptable values for each term position of the grammar-based speech application; ascertaining, from the traversing of the multiple possible grammar paths, phrases that are permissible in accordance with the grammar-based speech application; and creating the index from the phrases that are permissible in accordance with the grammar-based speech application. | 0.5 |
8,760,726 | 12 | 18 | 12. The method of claim 11 , additionally comprising after step (e), the steps of: d1. identifying a thin line in said digital image; d2. determining said line width; d3. using a lookup table to determine a percentage of polymer pixels reduction for said identified line width; and d4. creating a raster image for a polymer overlayer to be printed over the printed area of said line, wherein said creating a raster image file additionally comprises stochastically removing said determined percentage of pixels from the overlay area concurrent with each said identified thin lines. | 12. The method of claim 11 , additionally comprising after step (e), the steps of: d1. identifying a thin line in said digital image; d2. determining said line width; d3. using a lookup table to determine a percentage of polymer pixels reduction for said identified line width; and d4. creating a raster image for a polymer overlayer to be printed over the printed area of said line, wherein said creating a raster image file additionally comprises stochastically removing said determined percentage of pixels from the overlay area concurrent with each said identified thin lines. 18. The method of claim 12 , wherein said digital image is a PDF file and wherein identifying thin lines and determining the line widths comprises extracting objects from said PDF file dictionary. | 0.5 |
7,548,934 | 1 | 7 | 1. A computer-implemented method of generating a list, comprising: receiving a candidate item comprising at least one of an artist name or a title of the candidate item; for each reference item of a plurality of reference items, comparing at least a portion of respective characters of the at least one of the artist name or the title of the candidate item to at least a portion of respective reference-item characters of at least one of a reference-item artist name or a reference-item title of the reference item to facilitate determining a respective matching score, relating to each of the at least one of the artist name or the title of the candidate item, for each reference item based at least in part on a respective number of matches between the at least a portion of the respective characters and the at least a portion of the respective reference-item characters for each reference item; identifying the candidate item based at least in part on a best reference item, the best reference item is a reference item of the plurality of reference items having a matching score that at least meets a predetermined threshold amount and has a highest matching score as compared to other reference items of the plurality of reference items; associating a plurality of metadata relating to the best reference item with the candidate item, wherein the associated plurality of metadata is a plurality of candidate item metadata relating to the candidate item, to facilitate comparing similarity between the candidate item and a seed item; retrieving a plurality of seed item metadata relating to the seed item identified by a received seed item identifier; comparing the plurality of seed item metadata to the plurality of candidate item metadata; computing a similarity score between the seed item and the candidate item based at least in part on a similarity of the plurality of seed item metadata to the plurality of candidate item metadata, wherein the similarity score is computed using a list-generation computer system; determining whether to add the candidate item to the list based at least in part on the similarity score; and generating the list, which is provided to a user. | 1. A computer-implemented method of generating a list, comprising: receiving a candidate item comprising at least one of an artist name or a title of the candidate item; for each reference item of a plurality of reference items, comparing at least a portion of respective characters of the at least one of the artist name or the title of the candidate item to at least a portion of respective reference-item characters of at least one of a reference-item artist name or a reference-item title of the reference item to facilitate determining a respective matching score, relating to each of the at least one of the artist name or the title of the candidate item, for each reference item based at least in part on a respective number of matches between the at least a portion of the respective characters and the at least a portion of the respective reference-item characters for each reference item; identifying the candidate item based at least in part on a best reference item, the best reference item is a reference item of the plurality of reference items having a matching score that at least meets a predetermined threshold amount and has a highest matching score as compared to other reference items of the plurality of reference items; associating a plurality of metadata relating to the best reference item with the candidate item, wherein the associated plurality of metadata is a plurality of candidate item metadata relating to the candidate item, to facilitate comparing similarity between the candidate item and a seed item; retrieving a plurality of seed item metadata relating to the seed item identified by a received seed item identifier; comparing the plurality of seed item metadata to the plurality of candidate item metadata; computing a similarity score between the seed item and the candidate item based at least in part on a similarity of the plurality of seed item metadata to the plurality of candidate item metadata, wherein the similarity score is computed using a list-generation computer system; determining whether to add the candidate item to the list based at least in part on the similarity score; and generating the list, which is provided to a user. 7. The computer-implemented method of claim 1 , further comprising: retrieving a plurality of candidate item metadata relating to at least one other candidate item; comparing the plurality of seed item metadata to the plurality of candidate item metadata relating to the at least one other candidate item; computing a similarity score between the seed item and the at least one other candidate item based at least in part on a similarity of the plurality of seed item metadata to the plurality of candidate item metadata relating to the at least one other candidate item; and determining whether to add the at least one other candidate item to the list based at least in part on the similarity score to facilitate adding at least a predetermined threshold number of candidate items to the list. | 0.5 |
9,991,929 | 3 | 4 | 3. The method of claim 2 wherein uncompressed words are periodically transmitted with compressed word blocks according to a predetermined formula. | 3. The method of claim 2 wherein uncompressed words are periodically transmitted with compressed word blocks according to a predetermined formula. 4. The method of claim 3 wherein the predetermined formula comprises transmitting an alternating set of eight words in uncompressed format over a time period of one second. | 0.5 |
9,471,605 | 1 | 3 | 1. A computer program product, the computer program product comprising: a non-transitory computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code configured to: recognize an identifier in a user communication, wherein the identifier describes a person in the user communication; identify at least two names in a name database based on the identifier; determine an order of the at least two names based on ranking data associated with each of the at least two names, wherein the ranking data comprises at least one of a keyword, a length of time each of the at least two matched names have been stored in the name database, a frequency that one of the at least two matched names matches a name of the person in the user communication, a frequency that one of the at least two names is selected, and a helpfulness rating of each of the at least two names; transmit the at least two names to be displayed in the determined order; after transmitting the ordered names, receive a selected name that is one of the ordered names; and transmit contact information associated with the selected name. | 1. A computer program product, the computer program product comprising: a non-transitory computer-readable storage medium having computer-readable program code embodied therewith, the computer-readable program code configured to: recognize an identifier in a user communication, wherein the identifier describes a person in the user communication; identify at least two names in a name database based on the identifier; determine an order of the at least two names based on ranking data associated with each of the at least two names, wherein the ranking data comprises at least one of a keyword, a length of time each of the at least two matched names have been stored in the name database, a frequency that one of the at least two matched names matches a name of the person in the user communication, a frequency that one of the at least two names is selected, and a helpfulness rating of each of the at least two names; transmit the at least two names to be displayed in the determined order; after transmitting the ordered names, receive a selected name that is one of the ordered names; and transmit contact information associated with the selected name. 3. The computer program product of claim 1 , wherein the identifier is the name of the person in the user communication and further comprising recognizing an identifying keyword associated with the name of the person in the user communication. | 0.5 |
7,680,307 | 10 | 14 | 10. An image processing system configured to process a medical image data set for a patient, comprising: a memory configured to store a medical image data set; and a processor configured to apply a first classifier to the medical image data set, the first classifier having a sensitivity configured to identify a first subset of the medical image data set with one or more characteristics similar to a plaque region and configured to pass the identified subset to a second classifier and to apply the second classifier to the first subset the second classifier having a specificity configured to confirm the presence, or absence, of the plaque region in one or more portions of the first subset, wherein the plaque region is selected from an occlusive plague region and a vulnerable plague region, and wherein each of the first classifier and the second classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof, the processor further configured to apply a third classifier to the medical image data set, the third classifier having a sensitivity configured to identify a second subset of the medical image data set with one or more characteristics similar to a second specified distinctive region, pass the identified second subset to a fourth classifier and further apply the fourth classifier to the second subset, the fourth classifier having a specificity configured to confirm the presence, or absence, of the second specified distinctive region, wherein each of the third classifier and the fourth classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof, wherein the second specified distinctive region is a different type of region than the plaque region. | 10. An image processing system configured to process a medical image data set for a patient, comprising: a memory configured to store a medical image data set; and a processor configured to apply a first classifier to the medical image data set, the first classifier having a sensitivity configured to identify a first subset of the medical image data set with one or more characteristics similar to a plaque region and configured to pass the identified subset to a second classifier and to apply the second classifier to the first subset the second classifier having a specificity configured to confirm the presence, or absence, of the plaque region in one or more portions of the first subset, wherein the plaque region is selected from an occlusive plague region and a vulnerable plague region, and wherein each of the first classifier and the second classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof, the processor further configured to apply a third classifier to the medical image data set, the third classifier having a sensitivity configured to identify a second subset of the medical image data set with one or more characteristics similar to a second specified distinctive region, pass the identified second subset to a fourth classifier and further apply the fourth classifier to the second subset, the fourth classifier having a specificity configured to confirm the presence, or absence, of the second specified distinctive region, wherein each of the third classifier and the fourth classifier uses a Bayesian classification methodology, k-nearest neighbor classification methodology, neural network classification methodology, or any combination thereof, wherein the second specified distinctive region is a different type of region than the plaque region. 14. The image processing system of claim 10 , wherein the processor is further configured to format the medical image data set for display with a visual indication of the location of the distinctive region in the medical image data set. | 0.566176 |
9,020,271 | 1 | 2 | 1. A non-transitory computer readable medium storing machine executable instructions to perform a method for clustering data comprising a plurality of feature vectors, the instructions executable by an associated processor to: perform a hierarchical clustering algorithm on the plurality of feature vectors to provide a plurality of clusters and a cluster similarity measure for each cluster representing the quality of the cluster, the quality of the cluster being defined by feature vectors within the cluster having at least one of a small distance metric or a large similarity metric relative to the overall similarity among the plurality of feature vectors of all clusters; accept each cluster of the plurality of clusters having a cluster similarity measure meeting a threshold value; perform a clustering algorithm on each cluster that fails to meet the threshold value to provide a set of subclusters each having an associated cluster similarity measure; and accept each subcluster having a cluster similarity measure meeting the threshold value. | 1. A non-transitory computer readable medium storing machine executable instructions to perform a method for clustering data comprising a plurality of feature vectors, the instructions executable by an associated processor to: perform a hierarchical clustering algorithm on the plurality of feature vectors to provide a plurality of clusters and a cluster similarity measure for each cluster representing the quality of the cluster, the quality of the cluster being defined by feature vectors within the cluster having at least one of a small distance metric or a large similarity metric relative to the overall similarity among the plurality of feature vectors of all clusters; accept each cluster of the plurality of clusters having a cluster similarity measure meeting a threshold value; perform a clustering algorithm on each cluster that fails to meet the threshold value to provide a set of subclusters each having an associated cluster similarity measure; and accept each subcluster having a cluster similarity measure meeting the threshold value. 2. The non-transitory computer readable medium of claim 1 , the instructions being further executable to prune each feature vector that does not belong to one of an accepted cluster and an accepted subcluster by removing the feature vector from further processing. | 0.62069 |
8,938,438 | 7 | 12 | 7. A system, comprising a server computer communicatively coupled to a network and comprising: a website; a web page within the website; and a content within the web page; and at least one software module running on the server computer and configured to: receive: a selection of the web page for a page-level content analysis and optimization; and at least one keyword topically relevant to the content; identify at least one instance of the at least one keyword within the content; request, from a search engine: a first metric comprising a quantity of times, during a time period, that the at least one keyword has appeared in a search query along with at least one question keyword; and a second metric comprising a probability of receiving a high search engine rank associated with the at least one keyword and the at least one question keyword; receive, from the search engine, the first metric and the second metric; calculate, from the first metric and the second metric, a keyword effectiveness index wherein the keyword effectiveness index: identifies at least one most often searched keyword or question searched in the search engine; is utilized by the server computer to: generate, organize and sequence a recommended keyword list; and calculate an assigned effectiveness ranking for each of at least one request result as reflected in the recommended keyword list; and comprises: a logarithm of the first metric multiplied by the difference of the second metric subtracted from 1; and a recommendation score for each of the at least one request result; generate: at least one recommendation to include a high ranked suggested content, according to the keyword effectiveness index, on the web page; a keyword count comprising a list of instances, within the content, of the at least one keyword; a keyword percentage comparing the at least one keyword to a total of words within the content; a keyword grouping count comprising a list of instances of at least one grouping of content words within the content; and a keyword grouping percentage comparing the at least one grouping to the total of words; assign a favorability to a request result, wherein: a favorable result comprises the request result higher than a first number; a non-favorable result comprises the request result lower than a second number; and an ideal or neutral result comprises the request result between the first number and the second number; associate with the favorability a visual indicator, comprising a color, an interface element or a graphic, wherein: a first visual indicator is associated with the favorable result; a second visual indicator is associated with the non-favorable result; and a third visual indicator is associated with the ideal or neutral result; transmit, to a client computer communicatively coupled to the network: the at least one recommendation; the favorability; and the visual indicator. | 7. A system, comprising a server computer communicatively coupled to a network and comprising: a website; a web page within the website; and a content within the web page; and at least one software module running on the server computer and configured to: receive: a selection of the web page for a page-level content analysis and optimization; and at least one keyword topically relevant to the content; identify at least one instance of the at least one keyword within the content; request, from a search engine: a first metric comprising a quantity of times, during a time period, that the at least one keyword has appeared in a search query along with at least one question keyword; and a second metric comprising a probability of receiving a high search engine rank associated with the at least one keyword and the at least one question keyword; receive, from the search engine, the first metric and the second metric; calculate, from the first metric and the second metric, a keyword effectiveness index wherein the keyword effectiveness index: identifies at least one most often searched keyword or question searched in the search engine; is utilized by the server computer to: generate, organize and sequence a recommended keyword list; and calculate an assigned effectiveness ranking for each of at least one request result as reflected in the recommended keyword list; and comprises: a logarithm of the first metric multiplied by the difference of the second metric subtracted from 1; and a recommendation score for each of the at least one request result; generate: at least one recommendation to include a high ranked suggested content, according to the keyword effectiveness index, on the web page; a keyword count comprising a list of instances, within the content, of the at least one keyword; a keyword percentage comparing the at least one keyword to a total of words within the content; a keyword grouping count comprising a list of instances of at least one grouping of content words within the content; and a keyword grouping percentage comparing the at least one grouping to the total of words; assign a favorability to a request result, wherein: a favorable result comprises the request result higher than a first number; a non-favorable result comprises the request result lower than a second number; and an ideal or neutral result comprises the request result between the first number and the second number; associate with the favorability a visual indicator, comprising a color, an interface element or a graphic, wherein: a first visual indicator is associated with the favorable result; a second visual indicator is associated with the non-favorable result; and a third visual indicator is associated with the ideal or neutral result; transmit, to a client computer communicatively coupled to the network: the at least one recommendation; the favorability; and the visual indicator. 12. The system of claim 7 , wherein the server computer is further configured to: receive a selection of: the web page to be optimized for search engine optimization; at least one optimization option; and a filter for at least one request result, the filter comprising: the at least one question keyword; at least one geographical area; or at least one language; responsive to the selection of the filter, filter the at least one request result; and receive the at least one request result comprising the first metric and the second metric according to the filter. | 0.5 |
7,739,263 | 16 | 17 | 16. The medium of claim 15 , wherein the computer program, when executed, further performs the method comprising: transforming the query block from a parent block into a child block during compilation of the statement. | 16. The medium of claim 15 , wherein the computer program, when executed, further performs the method comprising: transforming the query block from a parent block into a child block during compilation of the statement. 17. The medium of claim 16 , wherein the computer program, when executed, further performs the method comprising: determining a name for the child block based on a transformation applied to the parent block and a name of the parent block. | 0.5 |
8,775,923 | 9 | 10 | 9. The method of claim 1 , wherein storing includes serializing the object identifiers and associated properties into the queue of objects according to a first object graph. | 9. The method of claim 1 , wherein storing includes serializing the object identifiers and associated properties into the queue of objects according to a first object graph. 10. The method of claim 9 , further comprising: deserializing the object identifiers and associated properties from the queue of objects into a second object graph similar to the first object graph. | 0.5 |
9,361,282 | 5 | 7 | 5. A user interface device comprising: a speech rendering module for performing speech synthesis on a text; an audio output unit for outputting synthesized speech data corresponding to the text processed by the speech rendering module; a speech recognition module for recognizing a first speech command of a user for indicating the start of a first selected range of the text and a second speech command of the user for indicating the end of the first selected range during output of the synthesized speech data; a speech interpretation module for interpreting the first speech command and the second speech command received from the speech recognition module; and a controller for executing an application including the text, specifying the first selected range according to the first speech command and the second speech command interpreted by the speech interpretation module, wherein a word or a phrase, which is determined according to an attribute of the executed application, included in the output speech-synthesized text is sequentially highlighted, wherein the speech recognition module further recognizes: a third speech command for repeatedly outputting the specified first selected range, a fourth speech command indicating the start of a second selected range, and a fifth speech command indicating the end of the first second selected range, wherein the controller re-specifies the second selected range within the specified first selected range after specifying the first selected range in response to the third speech command through the fifth speech command. | 5. A user interface device comprising: a speech rendering module for performing speech synthesis on a text; an audio output unit for outputting synthesized speech data corresponding to the text processed by the speech rendering module; a speech recognition module for recognizing a first speech command of a user for indicating the start of a first selected range of the text and a second speech command of the user for indicating the end of the first selected range during output of the synthesized speech data; a speech interpretation module for interpreting the first speech command and the second speech command received from the speech recognition module; and a controller for executing an application including the text, specifying the first selected range according to the first speech command and the second speech command interpreted by the speech interpretation module, wherein a word or a phrase, which is determined according to an attribute of the executed application, included in the output speech-synthesized text is sequentially highlighted, wherein the speech recognition module further recognizes: a third speech command for repeatedly outputting the specified first selected range, a fourth speech command indicating the start of a second selected range, and a fifth speech command indicating the end of the first second selected range, wherein the controller re-specifies the second selected range within the specified first selected range after specifying the first selected range in response to the third speech command through the fifth speech command. 7. The user interface device according to claim 5 , wherein the speech rendering module performs speech synthesis on the selected range of the text and outputs synthesized speech, and wherein the speech interpretation module interprets the third speech command to the fifth speech command. | 0.568657 |
8,799,336 | 18 | 19 | 18. The medium of claim 14 , wherein to limit the type of operation that may be performed on the second electronic document includes prohibiting the user from modifying the second electronic document. | 18. The medium of claim 14 , wherein to limit the type of operation that may be performed on the second electronic document includes prohibiting the user from modifying the second electronic document. 19. The medium of claim 18 , further comprising creating a working copy of the second electronic document modifiable by the user. | 0.5 |
8,112,486 | 1 | 9 | 1. A method for processing electronic-mail messages, the method comprising: storing information in memory regarding a message previously classified as an unsolicited message, the message including a collection of words, wherein the collection of words is not helpful for the purpose of distinguishing the message, the collection of words including a plurality of words that can be found in a dictionary; executing instructions stored in memory, wherein execution of the instructions by a processor: identifies from the collection of words one or more dictionary words known to be commonly occurring or known to be associated with spam, removes the identified one or more dictionary words from the message, replaces one or more remaining words in the message with an associated canonical equivalent to generate a resulting summary, and generates a signature based on the resulting summary, and storing the generated signature in memory for use in classifying and processing subsequently received messages, wherein a subsequently received message is classified based on the signature and processed based on the classification. | 1. A method for processing electronic-mail messages, the method comprising: storing information in memory regarding a message previously classified as an unsolicited message, the message including a collection of words, wherein the collection of words is not helpful for the purpose of distinguishing the message, the collection of words including a plurality of words that can be found in a dictionary; executing instructions stored in memory, wherein execution of the instructions by a processor: identifies from the collection of words one or more dictionary words known to be commonly occurring or known to be associated with spam, removes the identified one or more dictionary words from the message, replaces one or more remaining words in the message with an associated canonical equivalent to generate a resulting summary, and generates a signature based on the resulting summary, and storing the generated signature in memory for use in classifying and processing subsequently received messages, wherein a subsequently received message is classified based on the signature and processed based on the classification. 9. The method of claim 1 , wherein the signature is generated using a transform function. | 0.787081 |
9,141,602 | 13 | 14 | 13. A handheld electronic device structured to identify a proposed spelling correction for a word that has been determined to at least potentially be misspelled, the handheld electronic device comprising: a processor apparatus comprising a processor and a memory and having available thereto a data source comprising a plurality of words; an input apparatus structured to provide input to the processor apparatus, the input apparatus comprising a plurality of input keys, at least some of the input keys each having a plurality of characters assigned thereto; an output apparatus structured to receive output signals from the processor apparatus; the memory having stored therein a number of routines which, when executed on the processor, cause the handheld electronic device to perform operations comprising: receiving a group of characters of a candidate spelling correction; determining a canonical version of the word, comprising mapping each character in the word to a corresponding input key assigned to that character and generating, for each corresponding input key, a character set, including characters assigned to that corresponding input key, wherein the canonical version of the word comprises a string of the character sets in a same order as the characters in the word; determining for each character of at least a portion of the group of characters of the candidate spelling correction that at least one of: the character validly corresponds with a predetermined portion of the canonical version of the word, or the character is, according to at least one spell check algorithm from among a number of spell check algorithms, within a predetermined edit distance from a predetermined portion of the canonical version of the word; and outputting at least a portion of the candidate spelling correction as a proposed spelling correction. | 13. A handheld electronic device structured to identify a proposed spelling correction for a word that has been determined to at least potentially be misspelled, the handheld electronic device comprising: a processor apparatus comprising a processor and a memory and having available thereto a data source comprising a plurality of words; an input apparatus structured to provide input to the processor apparatus, the input apparatus comprising a plurality of input keys, at least some of the input keys each having a plurality of characters assigned thereto; an output apparatus structured to receive output signals from the processor apparatus; the memory having stored therein a number of routines which, when executed on the processor, cause the handheld electronic device to perform operations comprising: receiving a group of characters of a candidate spelling correction; determining a canonical version of the word, comprising mapping each character in the word to a corresponding input key assigned to that character and generating, for each corresponding input key, a character set, including characters assigned to that corresponding input key, wherein the canonical version of the word comprises a string of the character sets in a same order as the characters in the word; determining for each character of at least a portion of the group of characters of the candidate spelling correction that at least one of: the character validly corresponds with a predetermined portion of the canonical version of the word, or the character is, according to at least one spell check algorithm from among a number of spell check algorithms, within a predetermined edit distance from a predetermined portion of the canonical version of the word; and outputting at least a portion of the candidate spelling correction as a proposed spelling correction. 14. The handheld electronic device of claim 13 , wherein the operations further comprise: determining that a particular character of the group is equivalent to an immediately preceding character of the group, and responsive to the determining, considering the particular character to validly correspond with a predetermined portion of the canonical version of the word. | 0.771941 |
8,954,319 | 1 | 6 | 1. A method comprising: at each turn in a dialog, nominating via a processor, using a partially observable Markov decision process in parallel with a conventional dialog state, a set of allowed dialog actions and a set of contextual features; and generating a response based on the set of contextual features and a dialog action selected, via a machine learning algorithm, from the set of allowed dialog actions. | 1. A method comprising: at each turn in a dialog, nominating via a processor, using a partially observable Markov decision process in parallel with a conventional dialog state, a set of allowed dialog actions and a set of contextual features; and generating a response based on the set of contextual features and a dialog action selected, via a machine learning algorithm, from the set of allowed dialog actions. 6. The method of claim 1 , wherein a lower-dimensional feature vector represents one of the set of allowed dialog actions. | 0.730088 |
9,087,204 | 15 | 16 | 15. A decryption system for decrypting user information encrypted on a storage device associated with an identity document of a user, the system comprising: a server configured to collect user identity document data and user identification information from the user and to construct a token comprising the user identity document data, wherein the server is further configured to send the token to a mobile device associated with the user for storing the token at the mobile device and wherein the mobile device is physically separate from said storage device; a machine reader configured to read the data from the token by radio frequency identification communication with the mobile device, wherein the reader uses the user identity document data read from the token, stored on the mobile device, to decrypt the user information stored on said storage device; a comparator for comparing the data read from the token stored on the mobile device and the user information decrypted from said storage device associated with the user identity document; and authentication means for authenticating the user depending upon the result of the comparison. | 15. A decryption system for decrypting user information encrypted on a storage device associated with an identity document of a user, the system comprising: a server configured to collect user identity document data and user identification information from the user and to construct a token comprising the user identity document data, wherein the server is further configured to send the token to a mobile device associated with the user for storing the token at the mobile device and wherein the mobile device is physically separate from said storage device; a machine reader configured to read the data from the token by radio frequency identification communication with the mobile device, wherein the reader uses the user identity document data read from the token, stored on the mobile device, to decrypt the user information stored on said storage device; a comparator for comparing the data read from the token stored on the mobile device and the user information decrypted from said storage device associated with the user identity document; and authentication means for authenticating the user depending upon the result of the comparison. 16. A decryption system according to claim 15 wherein the reader is a portable reader or scanner or a mobile telephone. | 0.76938 |
7,697,494 | 19 | 20 | 19. A method for prioritizing the assignment of unique words from a base station, comprising: storing a set of unique words that are useful in implementing an SDMA (Spatial Division Multiple Access) communication process, the unique words each being for use by the base station in directing an antenna, a subset of the set of unique words including a set of assignable unique words; receiving a request message that is indicative of a first unique word; determining that the first unique word is in use at an adjacent base station; comparing the first unique word to at least some of the unique words in the set of available unique words; and adjusting priority of the unique words in the set of unique words according to the comparison, the adjusting including replacing one of the unique words in the set of assignable unique words, and placing the replaced unique word at a lower priority in the set of unique words. | 19. A method for prioritizing the assignment of unique words from a base station, comprising: storing a set of unique words that are useful in implementing an SDMA (Spatial Division Multiple Access) communication process, the unique words each being for use by the base station in directing an antenna, a subset of the set of unique words including a set of assignable unique words; receiving a request message that is indicative of a first unique word; determining that the first unique word is in use at an adjacent base station; comparing the first unique word to at least some of the unique words in the set of available unique words; and adjusting priority of the unique words in the set of unique words according to the comparison, the adjusting including replacing one of the unique words in the set of assignable unique words, and placing the replaced unique word at a lower priority in the set of unique words. 20. The method according to claim 19 , wherein the request message is generated by a mobile device, and the mobile device is operating as a PHS personal station and the base station is operating as a PHS cell station. | 0.5 |
8,825,630 | 1 | 5 | 1. A method for executing a query, the method comprising: receiving, by an application having a first user interface, a request to execute a query by the application, the request including selection criteria for the query that includes a business object (BO) instance to be queried; determining whether to execute the query by the application or a search engine having a second user interface that is separate and distinct from the application that executes queries independent of the application, the determining based on metadata associated with the BO instance referenced in the request to execute the query, the metadata including an indication of a type of query method to provide for the BO instance; sending the selection criteria to the search engine to execute the query in response to the determination that the query is to be executed by the search engine; receiving, by the application, a result of the query execution from the search engine; and providing an output of the query result. | 1. A method for executing a query, the method comprising: receiving, by an application having a first user interface, a request to execute a query by the application, the request including selection criteria for the query that includes a business object (BO) instance to be queried; determining whether to execute the query by the application or a search engine having a second user interface that is separate and distinct from the application that executes queries independent of the application, the determining based on metadata associated with the BO instance referenced in the request to execute the query, the metadata including an indication of a type of query method to provide for the BO instance; sending the selection criteria to the search engine to execute the query in response to the determination that the query is to be executed by the search engine; receiving, by the application, a result of the query execution from the search engine; and providing an output of the query result. 5. The method of claim 1 , further comprising providing the metadata attributes associated with the at least one query to be executed by the search engine to a user interface. | 0.746377 |
8,898,294 | 1 | 12 | 1. A method performed by a device associated with an apparatus to report a state of the apparatus to a remote computer, the method comprising: detecting the state of the apparatus; generating a message that reports the state of the apparatus to the remote computer, the message comprising a HyperText Transfer Protocol (HTTP) command, and the message containing a code that is unique to the device or apparatus, wherein generating is performed periodically or in response to a deviation in the state; and sending the message comprising the HTTP command to the remote computer, the HTTP command comprising a command that is configured to report the state of the apparatus using eXtensible Markup Language (XML); wherein the device is on an internal network and the remote computer is on an external network that is separate from the internal network, and wherein, as a result, the remote computer cannot initiate communication to an address of the device on the internal network; and wherein the state of the apparatus comprises values of two or more variables associated with the apparatus, one or more of the variables being flagged if one or more of the variables corresponds to an error condition associated with the apparatus. | 1. A method performed by a device associated with an apparatus to report a state of the apparatus to a remote computer, the method comprising: detecting the state of the apparatus; generating a message that reports the state of the apparatus to the remote computer, the message comprising a HyperText Transfer Protocol (HTTP) command, and the message containing a code that is unique to the device or apparatus, wherein generating is performed periodically or in response to a deviation in the state; and sending the message comprising the HTTP command to the remote computer, the HTTP command comprising a command that is configured to report the state of the apparatus using eXtensible Markup Language (XML); wherein the device is on an internal network and the remote computer is on an external network that is separate from the internal network, and wherein, as a result, the remote computer cannot initiate communication to an address of the device on the internal network; and wherein the state of the apparatus comprises values of two or more variables associated with the apparatus, one or more of the variables being flagged if one or more of the variables corresponds to an error condition associated with the apparatus. 12. The method of claim 1 , further comprising queuing the message in the device prior to sending the message, the message being sent following a failure condition in a system comprising the device and/or the apparatus. | 0.662037 |
9,275,021 | 1 | 9 | 1. A computer-implemented method for building and viewing an interactive multimedia document comprising: determining metadata describing a location for a media file portion within a media file; embedding a reference within a text portion of the interactive multimedia document, the reference including the metadata; interpreting the metadata upon selection of the reference; and displaying the media file portion over the interactive multimedia document based on the interpreted metadata. | 1. A computer-implemented method for building and viewing an interactive multimedia document comprising: determining metadata describing a location for a media file portion within a media file; embedding a reference within a text portion of the interactive multimedia document, the reference including the metadata; interpreting the metadata upon selection of the reference; and displaying the media file portion over the interactive multimedia document based on the interpreted metadata. 9. The computer-implemented method of claim 1 , wherein the text portion is in a vector format. | 0.75641 |
8,442,834 | 9 | 12 | 9. The system of claim 8 , the computer-readable storage medium having additional instructions stored which result in the operations further comprising: extracting from the website a linguistic item; and wherein the level of incorporation is further based on the linguistic item. | 9. The system of claim 8 , the computer-readable storage medium having additional instructions stored which result in the operations further comprising: extracting from the website a linguistic item; and wherein the level of incorporation is further based on the linguistic item. 12. The system of claim 9 , wherein the linguistic item comprises one of a named-entity, a nominal phrase, a verbal phrase, and an adjectival phrase. | 0.706693 |
10,140,370 | 12 | 15 | 12. A system for maintaining encrypted dynamic search indexes on third party storage systems, the system comprising: a search-index identifying module, stored in memory, that identifies, as part of a plugin of a search engine, a dynamic search index used by the search engine, wherein: the dynamic search index comprises a plurality of data chunks; each of the plurality of data chunks comprises one or more data blocks; each of the plurality of data chunks has been encrypted using a unique nonce; and a search-index initialization vector is designated and stored for encrypting the dynamic search index; a decrypting module, stored in memory, that enables a single data chunk in the plurality of data chunks to be accessed by decrypting, as part of the plugin of the search engine, the single data chunk by: calculating a chunk initialization vector for decrypting the single data chunk by: identifying the unique nonce used to encrypt the single data chunk; and deriving the chunk initialization vector by summing the search-index initialization vector with a product of the unique nonce and a number of the one or more data blocks; and using the chunk initialization vector to decrypt the single data chunk; a search-index encrypting module, stored in memory, that reencrypts, as part of the plugin of the search engine after the single data chunk has been accessed, the single data chunk by: calculating a new chunk initialization vector for encrypting the single data chunk such that no two data chunks in the plurality of data chunks have identical initialization vectors by: calculating a new unique nonce for the single data chunk; and deriving the new chunk initialization vector by summing the search-index initialization vector with a product of the new unique nonce and the number of the one or more data blocks; and using the new chunk initialization vector to encrypt the single data chunk; and at least one processor that executes the search-index identifying module and the search-index encrypting module. | 12. A system for maintaining encrypted dynamic search indexes on third party storage systems, the system comprising: a search-index identifying module, stored in memory, that identifies, as part of a plugin of a search engine, a dynamic search index used by the search engine, wherein: the dynamic search index comprises a plurality of data chunks; each of the plurality of data chunks comprises one or more data blocks; each of the plurality of data chunks has been encrypted using a unique nonce; and a search-index initialization vector is designated and stored for encrypting the dynamic search index; a decrypting module, stored in memory, that enables a single data chunk in the plurality of data chunks to be accessed by decrypting, as part of the plugin of the search engine, the single data chunk by: calculating a chunk initialization vector for decrypting the single data chunk by: identifying the unique nonce used to encrypt the single data chunk; and deriving the chunk initialization vector by summing the search-index initialization vector with a product of the unique nonce and a number of the one or more data blocks; and using the chunk initialization vector to decrypt the single data chunk; a search-index encrypting module, stored in memory, that reencrypts, as part of the plugin of the search engine after the single data chunk has been accessed, the single data chunk by: calculating a new chunk initialization vector for encrypting the single data chunk such that no two data chunks in the plurality of data chunks have identical initialization vectors by: calculating a new unique nonce for the single data chunk; and deriving the new chunk initialization vector by summing the search-index initialization vector with a product of the new unique nonce and the number of the one or more data blocks; and using the new chunk initialization vector to encrypt the single data chunk; and at least one processor that executes the search-index identifying module and the search-index encrypting module. 15. The system of claim 12 , wherein the plugin of the search engine comprises at least one of: an addon; and an extention. | 0.795 |
9,737,813 | 8 | 11 | 8. A method for determining semantic ability of a subject, the method being performed by a computer, the method comprising: displaying a linguistic task to the subject on a display of the computer, said linguistic task comprising providing one or more words by the subject to the computer; providing at least one linguistic clue to the subject, through the display of the computer, said at least one linguistic clue comprising content capable of activating concepts related to said one or more words but wherein i) said content does not include said one or more words or synonyms thereof, or ii) when said content does include said one or more words or synonyms thereof, said content does not comprise written text, wherein said linguistic clue comprises an image, audio, video, text or a combination thereof, and wherein said linguistic clues are selected such that the subject integrates said at least one to solve said linguistic task; receiving a solution to said linguistic task by the subject through the computer; and analyzing said solution to determine the semantic ability of the subject; wherein said analyzing said solution further comprises analyzing a correctness of said solution and one or more of a time required to complete said solution or a number of clues provided to the subject before said solution is submitted. | 8. A method for determining semantic ability of a subject, the method being performed by a computer, the method comprising: displaying a linguistic task to the subject on a display of the computer, said linguistic task comprising providing one or more words by the subject to the computer; providing at least one linguistic clue to the subject, through the display of the computer, said at least one linguistic clue comprising content capable of activating concepts related to said one or more words but wherein i) said content does not include said one or more words or synonyms thereof, or ii) when said content does include said one or more words or synonyms thereof, said content does not comprise written text, wherein said linguistic clue comprises an image, audio, video, text or a combination thereof, and wherein said linguistic clues are selected such that the subject integrates said at least one to solve said linguistic task; receiving a solution to said linguistic task by the subject through the computer; and analyzing said solution to determine the semantic ability of the subject; wherein said analyzing said solution further comprises analyzing a correctness of said solution and one or more of a time required to complete said solution or a number of clues provided to the subject before said solution is submitted. 11. The method of claim 8 , wherein said selecting said linguistic clues further comprises selecting a game world for the subject, said game world having a plurality of characteristic features, including at least one or more of instructions, incentives, type of clues, penalty on display of previous clues, sequence of clues and time of exposure of a given clue; and selecting said linguistic clues also according to said game world. | 0.5 |
8,280,434 | 12 | 19 | 12. A mobile wireless communications device, comprising: a transceiver configured to transmit and receive radio frequency (RF) signals carrying communications data of speech; a keyboard; a display; an adjunct comprising at least one of a speaker, LED, camera and video module; a processor coupled to the adjunct, keyboard, display and transceiver and configured to: process the communications data of speech that is transmitted and received to and from the transceiver; convert communications data as speech received from the transceiver to text that is displayed on the display; convert text that is received at the keyboard into communications data of speech to be transmitted from the transceiver as an RF signal; configure the adjunct to supplement the speech-to-text and text-to-speech conversion; and wherein said display provides an interface and the processor is configured for displaying a set up screen on the display having a handicap option that is user selected for enabling the speech-to-text and text-to-speech module. | 12. A mobile wireless communications device, comprising: a transceiver configured to transmit and receive radio frequency (RF) signals carrying communications data of speech; a keyboard; a display; an adjunct comprising at least one of a speaker, LED, camera and video module; a processor coupled to the adjunct, keyboard, display and transceiver and configured to: process the communications data of speech that is transmitted and received to and from the transceiver; convert communications data as speech received from the transceiver to text that is displayed on the display; convert text that is received at the keyboard into communications data of speech to be transmitted from the transceiver as an RF signal; configure the adjunct to supplement the speech-to-text and text-to-speech conversion; and wherein said display provides an interface and the processor is configured for displaying a set up screen on the display having a handicap option that is user selected for enabling the speech-to-text and text-to-speech module. 19. The mobile wireless communications device according to claim 12 , wherein said adjunct comprises a light emitting diode (LED) carried by the housing and coupled to the processor, wherein said processor is configured for generating a signal to the LED for activating the LED and displaying a light pattern indicative of speech. | 0.5 |
8,495,143 | 1 | 6 | 1. A computer-implemented method comprising: maintaining a user profile for each of a plurality of users of a social networking system, each user profile comprising a set of attributes; selecting a user from the plurality of users; receiving user profile information for at least one user of a set of users in the social networking system who are connected to the selected user in the social networking system; inferring a value of one or more attributes of the user profile for the selected user based on information describing the set of users who are connected to the selected user in the social networking system; comparing a confidence score value for an inferred user profile attribute to a threshold value; storing, responsive to the confidence score being above the threshold value, the inferred value of the user profile attribute with the user profile for the selected user; determining relevant information for the selected user based on the inferred user profile attribute; and sending the relevant information to the selected user. | 1. A computer-implemented method comprising: maintaining a user profile for each of a plurality of users of a social networking system, each user profile comprising a set of attributes; selecting a user from the plurality of users; receiving user profile information for at least one user of a set of users in the social networking system who are connected to the selected user in the social networking system; inferring a value of one or more attributes of the user profile for the selected user based on information describing the set of users who are connected to the selected user in the social networking system; comparing a confidence score value for an inferred user profile attribute to a threshold value; storing, responsive to the confidence score being above the threshold value, the inferred value of the user profile attribute with the user profile for the selected user; determining relevant information for the selected user based on the inferred user profile attribute; and sending the relevant information to the selected user. 6. The computer-implemented method of claim 1 , wherein inferring the value of the attribute for the selected user comprises determining an aggregate value by weighting the attribute for each user of the set of users based on a metric describing a closeness of the user with the selected user. | 0.640049 |
9,323,720 | 1 | 11 | 1. A method for unifying a fragmented document comprising: identifying structural information elements of a root document, wherein the structural information elements comprise at least one reference to a discrete document other than the root document; presenting to a user, the identified structural information elements within a rapid selection interface for selective acquisition of content from the discrete document; receiving at the rapid selection interface, a user initiated unification command including a user selection of one or more of the presented structural information elements; responsive to said unification command, acquiring content represented by the at least one reference from the discrete document without presenting the discrete document within a user interface window; and adding the acquired content to the root document. | 1. A method for unifying a fragmented document comprising: identifying structural information elements of a root document, wherein the structural information elements comprise at least one reference to a discrete document other than the root document; presenting to a user, the identified structural information elements within a rapid selection interface for selective acquisition of content from the discrete document; receiving at the rapid selection interface, a user initiated unification command including a user selection of one or more of the presented structural information elements; responsive to said unification command, acquiring content represented by the at least one reference from the discrete document without presenting the discrete document within a user interface window; and adding the acquired content to the root document. 11. The method of claim 1 , further comprising: formatting the acquired content in accordance with the root document before adding the acquired content to the root document. | 0.915774 |
9,015,160 | 1 | 5 | 1. A system, comprising: one or more memory units; and one or more processing units operable to: access text; identify a plurality of terms from the text; determine a plurality of term vectors associated with the identified plurality of terms; calculate a weight of each of the determined plurality of term vectors; cluster the determined plurality of term vectors into a plurality of clusters, the plurality of clusters comprising a first cluster related to a first concept of the text and a second cluster related to a second concept of the text, the first concept being distinct from the second concept, the first and second clusters each comprising two or more of the determined term vectors, the clustering comprising grouping two or more of the determined term vectors together based on the determined weights of the two or more term vectors and a distance between the two or more term vectors; create a first pseudo-document according to the first cluster; create a second pseudo-document according to the second cluster; identify, using latent semantic analysis (LSA) of the first pseudo-document, a first set of terms associated with the first cluster; identify, using LSA of the second pseudo-document, a second set of terms associated with the second cluster; determine a first weight associated with the first cluster and a second weight associated with the second cluster, wherein the first weight is based at least on the determined weights of the term vectors of the first cluster, and wherein the second weight is based at least on the determined weights of the term vectors of the second cluster; determine a first percentage of a list of output terms that should come from the first cluster and a second percentage of the list of output terms that should come from the second cluster, the first percentage based on a ratio of the first weight to a sum of the first and second weights, the second percentage based on a ratio of the second weight to the sum of the first and second weights; select one or more terms from the first set of terms according to the determined first percentage; select one or more terms from the second set of terms according to the determined second percentage; combine the selected terms from the first and second sets of terms into the list of output terms, the list of output terms having the first and second concepts of the text; and store the list of output terms in the one or more memory units. | 1. A system, comprising: one or more memory units; and one or more processing units operable to: access text; identify a plurality of terms from the text; determine a plurality of term vectors associated with the identified plurality of terms; calculate a weight of each of the determined plurality of term vectors; cluster the determined plurality of term vectors into a plurality of clusters, the plurality of clusters comprising a first cluster related to a first concept of the text and a second cluster related to a second concept of the text, the first concept being distinct from the second concept, the first and second clusters each comprising two or more of the determined term vectors, the clustering comprising grouping two or more of the determined term vectors together based on the determined weights of the two or more term vectors and a distance between the two or more term vectors; create a first pseudo-document according to the first cluster; create a second pseudo-document according to the second cluster; identify, using latent semantic analysis (LSA) of the first pseudo-document, a first set of terms associated with the first cluster; identify, using LSA of the second pseudo-document, a second set of terms associated with the second cluster; determine a first weight associated with the first cluster and a second weight associated with the second cluster, wherein the first weight is based at least on the determined weights of the term vectors of the first cluster, and wherein the second weight is based at least on the determined weights of the term vectors of the second cluster; determine a first percentage of a list of output terms that should come from the first cluster and a second percentage of the list of output terms that should come from the second cluster, the first percentage based on a ratio of the first weight to a sum of the first and second weights, the second percentage based on a ratio of the second weight to the sum of the first and second weights; select one or more terms from the first set of terms according to the determined first percentage; select one or more terms from the second set of terms according to the determined second percentage; combine the selected terms from the first and second sets of terms into the list of output terms, the list of output terms having the first and second concepts of the text; and store the list of output terms in the one or more memory units. 5. The system of claim 1 , wherein: the one or more processing units are further operable to: create a query pseudo-document from the determined plurality of term vectors; create a first leaned pseudo-document using the first pseudo-document and the query pseudo-document; and create a second leaned pseudo-document using the second pseudo-document and the query pseudo-document; wherein: identifying the first set of terms associated with the first cluster comprises using LSA of the first leaned pseudo-document; and identifying the second set of terms associated with the second cluster comprises using LSA of the second leaned pseudo-document. | 0.5 |
9,378,288 | 1 | 5 | 1. A computer-implemented method comprising: obtaining a set of search results that a search engine identifies as responsive to a search query; providing, for display, first multiple search results from among the set of search results; receiving data indicating a refinement to the search query; in response to receiving the data indicating the refinement to the search query, obtaining a subset of the set of search results that satisfy the refinement without instructing the search engine to perform a subsequent search; for each respective search result of second multiple search results selected from among the subset of the set of search results, obtaining a respective portion from a respective resource referenced by the respective search result, wherein the respective portion is responsive to the refinement; and providing, for display, the second multiple search results and the respective portion from the respective resource referenced by each of the second multiple search results. | 1. A computer-implemented method comprising: obtaining a set of search results that a search engine identifies as responsive to a search query; providing, for display, first multiple search results from among the set of search results; receiving data indicating a refinement to the search query; in response to receiving the data indicating the refinement to the search query, obtaining a subset of the set of search results that satisfy the refinement without instructing the search engine to perform a subsequent search; for each respective search result of second multiple search results selected from among the subset of the set of search results, obtaining a respective portion from a respective resource referenced by the respective search result, wherein the respective portion is responsive to the refinement; and providing, for display, the second multiple search results and the respective portion from the respective resource referenced by each of the second multiple search results. 5. The method of claim 1 , wherein the first multiple search results and the second multiple search results both include a particular search result, and wherein a ranking of the particular search result in the first multiple search results is different from a ranking of the particular search result in the second multiple search results. | 0.617647 |
9,965,574 | 1 | 9 | 1. A computer implemented method of designing a real-world physical object in a computer-aided design (CAD) system, the method comprising: obtaining in memory of a processor of a computer-aided engineering (CAE) system, a first finite element model and a first CAD model that the first finite element model represents, the CAD model representing at least one or more curved surface of a real-world physical object; by the processor, performing a finite element simulation of contact involving the real-world physical object by using both the first finite element model and the first CAD model within the simulation, said performing the finite element simulation including the CAE system determining contact behavior of the one or more curved surface of the real-world physical object, determining one or more variations between the first finite element model and the first CAD model, and using these determined variations in determining the contact behavior of the one or more curved surface of the real-world physical object to correct one or more errors in the contact behavior determined; and modifying the first CAD model in the CAD system based on a result of performing the finite element simulation in the CAE system such that the modified first CAD model more accurately represents real-world contact behavior of the physical object. | 1. A computer implemented method of designing a real-world physical object in a computer-aided design (CAD) system, the method comprising: obtaining in memory of a processor of a computer-aided engineering (CAE) system, a first finite element model and a first CAD model that the first finite element model represents, the CAD model representing at least one or more curved surface of a real-world physical object; by the processor, performing a finite element simulation of contact involving the real-world physical object by using both the first finite element model and the first CAD model within the simulation, said performing the finite element simulation including the CAE system determining contact behavior of the one or more curved surface of the real-world physical object, determining one or more variations between the first finite element model and the first CAD model, and using these determined variations in determining the contact behavior of the one or more curved surface of the real-world physical object to correct one or more errors in the contact behavior determined; and modifying the first CAD model in the CAD system based on a result of performing the finite element simulation in the CAE system such that the modified first CAD model more accurately represents real-world contact behavior of the physical object. 9. The method of claim 1 wherein: the first finite element model represents at least two parts; and the finite element simulation simulates contact between the at least two parts. | 0.850334 |
9,753,908 | 11 | 14 | 11. A system for transferring data from a receipt image directly into a spreadsheet, comprising: a scanner adapted to acquire the receipt image; a document memory; optical character recognition software that acquires textual data from the receipt image and stores the textual data in the document memory; and a processor programmed to: enable a user to select an XML map that maps types of expense data and associated expense data from the receipt to one or more cells in the spreadsheet in accordance with pre-designated mapping preferences of the user that map the types of expense data and associated expense data to XML data elements based on the types of expense data in the receipt; parse the textual data to identify the types of expense data and associated expense data for each type of expense data and to extract the types of expense data and associated expense data of each type of expense data from the textual data; and for each type of expense data extracted, determine if the each type of expense data is mapped in the selected XML map to one or more cells in the spreadsheet and, for each type of expense data found in the selected XML map, using the selected XML map to automatically transfer the extracted associated expense data to the cells in the spreadsheet designated for the types of extracted expense data with which the extracted associated expense data is associated. | 11. A system for transferring data from a receipt image directly into a spreadsheet, comprising: a scanner adapted to acquire the receipt image; a document memory; optical character recognition software that acquires textual data from the receipt image and stores the textual data in the document memory; and a processor programmed to: enable a user to select an XML map that maps types of expense data and associated expense data from the receipt to one or more cells in the spreadsheet in accordance with pre-designated mapping preferences of the user that map the types of expense data and associated expense data to XML data elements based on the types of expense data in the receipt; parse the textual data to identify the types of expense data and associated expense data for each type of expense data and to extract the types of expense data and associated expense data of each type of expense data from the textual data; and for each type of expense data extracted, determine if the each type of expense data is mapped in the selected XML map to one or more cells in the spreadsheet and, for each type of expense data found in the selected XML map, using the selected XML map to automatically transfer the extracted associated expense data to the cells in the spreadsheet designated for the types of extracted expense data with which the extracted associated expense data is associated. 14. The system of claim 11 wherein the processor is further programmed to pre-designate mapping preferences of the user by using a wizard to guide the user through the creation of a custom map that associates types of expense data of the receipt to desired cells in the spreadsheet. | 0.5 |
9,189,548 | 8 | 9 | 8. The method of claim 1 , where associating the visual cue with the one of the generated links includes: associating the visual cue with the one of the generated links further based on a relationship between the click through rate and a threshold value associated with a relevance score, associated with the particular document. | 8. The method of claim 1 , where associating the visual cue with the one of the generated links includes: associating the visual cue with the one of the generated links further based on a relationship between the click through rate and a threshold value associated with a relevance score, associated with the particular document. 9. The method of claim 8 , where the threshold value associated with the relevance score is lowered when the click through rate associated with the particular document is higher than a particular value. | 0.5 |
8,521,528 | 11 | 19 | 11. A method for distributed speech recognition, comprising: obtaining audio data from a caller participating in a call with an agent; receiving on a main recognizer, a main grammar template and the audio data; receiving on each of a plurality of secondary recognizers, the audio data and a reference that identifies a secondary grammar, wherein each secondary grammar is a non-overlapping section of the main grammar template; performing speech recognition on each of the secondary recognizers, comprising: identifying speech recognition results by applying the secondary grammar to the audio data; and selecting an n number of most likely speech recognition results; constructing by the main recognizer, a new grammar using the speech recognition results from each of the secondary recognizers as a new vocabulary based on the main grammar template; and identifying further speech recognition results by applying the new grammar to the audio data. | 11. A method for distributed speech recognition, comprising: obtaining audio data from a caller participating in a call with an agent; receiving on a main recognizer, a main grammar template and the audio data; receiving on each of a plurality of secondary recognizers, the audio data and a reference that identifies a secondary grammar, wherein each secondary grammar is a non-overlapping section of the main grammar template; performing speech recognition on each of the secondary recognizers, comprising: identifying speech recognition results by applying the secondary grammar to the audio data; and selecting an n number of most likely speech recognition results; constructing by the main recognizer, a new grammar using the speech recognition results from each of the secondary recognizers as a new vocabulary based on the main grammar template; and identifying further speech recognition results by applying the new grammar to the audio data. 19. A method according to claim 11 , wherein each of the secondary recognizers is directly interfaced to the main recognizer as a second level of recognition hierarchy. | 0.876652 |
7,945,438 | 27 | 28 | 27. The non-transitory computer readable medium according to claim 21 , wherein the program further comprises instructions for: assigning the at least one semantic class, including the identified syntactic structure, to at least one of the plurality of glossary items. | 27. The non-transitory computer readable medium according to claim 21 , wherein the program further comprises instructions for: assigning the at least one semantic class, including the identified syntactic structure, to at least one of the plurality of glossary items. 28. The non-transitory computer readable medium according to claim 27 , wherein the program further comprises instructions for: using parsing rules to assign at least one additional semantic class to at least one of a phrase and a clause in the second information source. | 0.5 |
8,626,588 | 12 | 19 | 12. A computer-implemented method comprising: a) receiving, with an advertising system including at least one computer, relevance information for an advertisement; b) determining, with the advertising system, at least one audio document using the received relevance information; c) generating, with the advertising system, information about the at least one audio document for presentation to an advertiser associated with the advertisement; and d) receiving, with the advertising system, from the advertiser, an offer to have its advertisement served with the at least one audio document accepted by the advertiser. | 12. A computer-implemented method comprising: a) receiving, with an advertising system including at least one computer, relevance information for an advertisement; b) determining, with the advertising system, at least one audio document using the received relevance information; c) generating, with the advertising system, information about the at least one audio document for presentation to an advertiser associated with the advertisement; and d) receiving, with the advertising system, from the advertiser, an offer to have its advertisement served with the at least one audio document accepted by the advertiser. 19. The computer-implemented method of claim 12 wherein the audio document is a segment of an audio conversation. | 0.83284 |
9,542,933 | 2 | 3 | 2. The method of claim 1 , further comprising outputting the buffered audio signals received subsequent to the buffered audio signals that correspond to the recognized speech element. | 2. The method of claim 1 , further comprising outputting the buffered audio signals received subsequent to the buffered audio signals that correspond to the recognized speech element. 3. The method of claim 2 , further comprising: performing second speech recognition on the outputted buffered audio signals, both those corresponding to the recognized speech element and those received subsequent to the buffered audio signals that correspond to the recognized speech element, wherein the second speech recognition is more sophisticated than the speech recognition performed using the locally-stored vocabulary. | 0.5 |
5,537,622 | 1 | 3 | 1. A database coprocessor for use with a computer system, comprising: an internal control bus; an internal data bus; a control processor in communication with the internal control bus and the internal data bus; an internal memory in communication with the internal data bus; a system memory interface in communication with the internal control bus and the internal data bus; a hasher in communication with the internal control bus and the internal data bus; a Predicate Evaluator in communication with the internal control bus and the internal data bus; a sort-merge unit in communication with the internal control bus and the internal data bus; and an extractor for receiving a plurality of database commands from said computer system and for assembling final result data, said extractor in communication with said internal control bus and said internal data bus, said database commands corresponding to a plurality of database processing functions, said database processing functions being performable by said hasher, said Predicate Evaluator, said sort-merge unit and said extractor, a single invocation of said coprocessor being for executing said plurality of database functions, wherein the sort-merge unit, the Predicate Evaluator, the extractor, and the hasher are responsive to commands from the control processor and utilize said internal memory in common, said commands from said control processor being communicated via the internal control bus. | 1. A database coprocessor for use with a computer system, comprising: an internal control bus; an internal data bus; a control processor in communication with the internal control bus and the internal data bus; an internal memory in communication with the internal data bus; a system memory interface in communication with the internal control bus and the internal data bus; a hasher in communication with the internal control bus and the internal data bus; a Predicate Evaluator in communication with the internal control bus and the internal data bus; a sort-merge unit in communication with the internal control bus and the internal data bus; and an extractor for receiving a plurality of database commands from said computer system and for assembling final result data, said extractor in communication with said internal control bus and said internal data bus, said database commands corresponding to a plurality of database processing functions, said database processing functions being performable by said hasher, said Predicate Evaluator, said sort-merge unit and said extractor, a single invocation of said coprocessor being for executing said plurality of database functions, wherein the sort-merge unit, the Predicate Evaluator, the extractor, and the hasher are responsive to commands from the control processor and utilize said internal memory in common, said commands from said control processor being communicated via the internal control bus. 3. The coprocessor of claim 1 wherein said computer system includes a plurality of memories, the system memory interface is coupled to said plurality of memories in said computer system and wherein the system memory interface further comprises means for directly addressing data stored in said plurality of memories. | 0.568306 |
9,275,021 | 4 | 5 | 4. The computer-implemented method of claim 1 , wherein the media file includes a file type including a PowerPoint® presentation, a portable document, a Word® document, and a Windows® Media file. | 4. The computer-implemented method of claim 1 , wherein the media file includes a file type including a PowerPoint® presentation, a portable document, a Word® document, and a Windows® Media file. 5. The computer-implemented method of claim 4 , further comprising visually formatting the media file portion and displaying the visually formatted media file portion upon selection of the reference. | 0.5 |
9,075,619 | 1 | 12 | 1. A method for creating a dialog system, the method comprising: providing a framework for creating a multi-modal dialog application configurable to perform pipeline operations on dialog during a runtime mode in a server; including runtime media contained within a Runtime Application Package (RAP) and files of properties associated with the runtime media in the framework, the properties including runtime and non-runtime properties for the runtime media, the RAP supporting the multi-modal dialog application created; enabling customization of the RAP in the server accessible by a client via a computer network by enabling modification of the runtime media and the runtime and non-runtime properties of the runtime media via the computer network; and enabling activation of the RAP customized to specialize support of the multi-modal dialog application created. | 1. A method for creating a dialog system, the method comprising: providing a framework for creating a multi-modal dialog application configurable to perform pipeline operations on dialog during a runtime mode in a server; including runtime media contained within a Runtime Application Package (RAP) and files of properties associated with the runtime media in the framework, the properties including runtime and non-runtime properties for the runtime media, the RAP supporting the multi-modal dialog application created; enabling customization of the RAP in the server accessible by a client via a computer network by enabling modification of the runtime media and the runtime and non-runtime properties of the runtime media via the computer network; and enabling activation of the RAP customized to specialize support of the multi-modal dialog application created. 12. The method of claim 1 further comprising: enabling utilization of the RAP customized by multiple service instances of the multi-modal dialog application created wherein the multi-modal dialog application is a web service application on the server. | 0.570205 |
5,473,367 | 44 | 47 | 44. The apparatus of claim 39 wherein chair person video terminal includes a display for displaying information concerning the video conference and indicators for controlling the video conference and the means for requesting comprises means for displaying the identity of the requesting one of the video terminals onto the display of the chair person video terminal; and the means for inserting comprises means for responding to actuation of one of the indicators to select the identity of the requesting one of the video terminals from the display to use the identity to generate the third control information for inserting the video picture from the requesting one of the video terminals into the chair view picture. | 44. The apparatus of claim 39 wherein chair person video terminal includes a display for displaying information concerning the video conference and indicators for controlling the video conference and the means for requesting comprises means for displaying the identity of the requesting one of the video terminals onto the display of the chair person video terminal; and the means for inserting comprises means for responding to actuation of one of the indicators to select the identity of the requesting one of the video terminals from the display to use the identity to generate the third control information for inserting the video picture from the requesting one of the video terminals into the chair view picture. 47. The apparatus of claim 44 wherein the indicators are icons on the display. | 0.5 |
8,705,141 | 5 | 6 | 5. The method of claim 1 wherein the at least one control structure provides control information regarding the simple data in the non-complex PDL format, the control information indicating at least one location of portions of the simple data in the non-complex PDL format and providing a method for constructing at least one image of the simple data and wherein processing the complex datastream further comprises: assembling the portions of the simple data in the non-complex PDL format to form the at least one image. | 5. The method of claim 1 wherein the at least one control structure provides control information regarding the simple data in the non-complex PDL format, the control information indicating at least one location of portions of the simple data in the non-complex PDL format and providing a method for constructing at least one image of the simple data and wherein processing the complex datastream further comprises: assembling the portions of the simple data in the non-complex PDL format to form the at least one image. 6. The method of claim 5 wherein the portions of the simple data in the non-complex PDL format include data relating to a plurality of tiles and wherein the assembling further includes: obtaining the data for the plurality of tiles; constructing the plurality of tiles; and processing the plurality of tiles to provide the at least one image. | 0.5 |
9,928,233 | 7 | 19 | 7. The method of claim 1 , further comprising ranking the clusters. | 7. The method of claim 1 , further comprising ranking the clusters. 19. The method of claim 7 , wherein the clusters are ranked based on a plurality of factors. | 0.708861 |
8,250,018 | 1 | 2 | 1. An expert system for aiding engineering personnel in a contact lens manufacturing, comprising: a user interface for receiving a query from a user regarding an element of business entity's industrial environment in which the user works in a contact lens manufacturing related capacity; a database containing information describing aspects of elements of the business entity's industrial environment; the inference engine subsystem receives the query via the user interface and obtains solution information from the database by matching keyterms in the query, wherein the user interface outputs the solution information to the user; an inference engine matches keyterms in the query with keyterms associated with rules to select a rule from the database; and the inference engine obtains a further question from the database associated with the selected rule; the user interface prompts the user to answer the further question; and the inference engine determines if solution information associated with a user's answer to the further question is available in the database. | 1. An expert system for aiding engineering personnel in a contact lens manufacturing, comprising: a user interface for receiving a query from a user regarding an element of business entity's industrial environment in which the user works in a contact lens manufacturing related capacity; a database containing information describing aspects of elements of the business entity's industrial environment; the inference engine subsystem receives the query via the user interface and obtains solution information from the database by matching keyterms in the query, wherein the user interface outputs the solution information to the user; an inference engine matches keyterms in the query with keyterms associated with rules to select a rule from the database; and the inference engine obtains a further question from the database associated with the selected rule; the user interface prompts the user to answer the further question; and the inference engine determines if solution information associated with a user's answer to the further question is available in the database. 2. The expert system claimed in claim 1 , further comprising a kiosk operable by the user through the user interface. | 0.732877 |
9,576,249 | 1 | 2 | 1. A computer-implemented method of measuring a user's comprehension of subject matter of a text, the method comprising: receiving a summary generated by the user, the summary being a constructed response that summarizes a text; parsing the summary with a processing system to identify a number of sentences contained in the summary and to identify in the summary a plurality of multi-word sequences; processing the summary and a reference summary with the processing system to determine a first numerical measure indicative of a similarity between the summary and a reference summary, the reference summary having been designated as representative of the subject matter of the text; processing the summary with the processing system to determine a second numerical measure indicative of a degree to which a single sentence of the summary summarizes an entirety of the text; processing the summary and the text with the processing system to determine a third numerical measure indicative of a degree of copying in the summary of multi-word sequences present in the text; and applying a numerical model to the first numerical measure, the second numerical measure and the third numerical measure to determine a score for the summary indicative of the user's comprehension of the subject matter of the text, the numerical model including a first variable and an associated first weighting factor, the first variable receiving a value of the first numerical measure, a second variable and an associated second weighting factor, the first variable receiving a value of the second numerical measure, and a third variable and an associated third weighting factor, the third variable receiving a value of the third numerical measure. | 1. A computer-implemented method of measuring a user's comprehension of subject matter of a text, the method comprising: receiving a summary generated by the user, the summary being a constructed response that summarizes a text; parsing the summary with a processing system to identify a number of sentences contained in the summary and to identify in the summary a plurality of multi-word sequences; processing the summary and a reference summary with the processing system to determine a first numerical measure indicative of a similarity between the summary and a reference summary, the reference summary having been designated as representative of the subject matter of the text; processing the summary with the processing system to determine a second numerical measure indicative of a degree to which a single sentence of the summary summarizes an entirety of the text; processing the summary and the text with the processing system to determine a third numerical measure indicative of a degree of copying in the summary of multi-word sequences present in the text; and applying a numerical model to the first numerical measure, the second numerical measure and the third numerical measure to determine a score for the summary indicative of the user's comprehension of the subject matter of the text, the numerical model including a first variable and an associated first weighting factor, the first variable receiving a value of the first numerical measure, a second variable and an associated second weighting factor, the first variable receiving a value of the second numerical measure, and a third variable and an associated third weighting factor, the third variable receiving a value of the third numerical measure. 2. The computer-implemented method of claim 1 , wherein the determining of the third numerical measure includes: determining a first metric for the summary, the first metric being a ratio between a first value and a second value, wherein the first value is a sum of lengths of all three-word or longer phrases from the text that are included in the summary, and wherein the second value is a length of the summary; determining a second metric for the summary, the second metric being a ratio between the first value and a third value, wherein the third value is a length of the text; and determining a third metric for the summary, the third metric being a length of a longest word sequence from the text that is included in the summary. | 0.5 |
6,032,116 | 33 | 34 | 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. | 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. 34. The apparatus of claim 33 wherein the quantizer is a fuzzy matrix quantizer further for generating an observation sequence of indices indicating the relative closeness between the respective speech input signal and reference speech signal P line spectral pair frequencies; and wherein the second speech classifier is u hidden Markov models and a fuzzy Viterbi algorithm module for determining a respective probability for each of the u hidden Markov models that the respective hidden Markov model produced the observation sequence. | 0.5 |
7,739,294 | 1 | 5 | 1. A method for creating an ordered reading list of pre-determined length of relevant topics from a hyperlinked database source of information website based on a user's input, the method comprising: determining at least one topic of interest; choosing a topic ordering algorithm from a plurality of topic ordering algorithms including a top-down schematic algorithm, a bottom-up schematic algorithm, and a horizontal schematic algorithm, said top-down schematic algorithm comprises a page rank calculation performed by iterating until a convergence, said bottom-up schematic algorithm comprises a ratio of a combined weight from a plurality of source topics to a plurality of sink topics of an article, said bottom-up schematic algorithm linearly parameterizes an ordering from said source topics to said sink topics of an article k, wherein a ratio is Π i v source(i) → k /Π j v source(j) → k of a rank of said source topics to a rank of said sink topics, wherein a point where relevance of said topics is cutoff is calculated by multiplying Π i v source(i) → k by Π j v sink(j) → k , wherein a comparison is found by graphing a distance from said seed topics, ordered by a difference of distances, calculated by [Σ ij |(d source(i) → k )−(d sink(j) → k )|], and is cutoff by a sum of distances calculated by Σ i d source(i) → k +Σ j d sink(j) → k , and said horizontal schematic algorithm comprises an order parameterization by absolute differences of a log of a plurality of ranks and an absolute difference of a plurality of distances with analogous cutoff methods, wherein said sink topic is where said reading list terminates and said source topic is where said reading list begins; calculating one of a plurality of topics ordering algorithms based on said topic of interest and a user; updating said hyperlinked database source of information; forming a reading list and ranking said reading list based on said topic ordering algorithm; and outputting said ranking and said reading list to an interface depending on an outcome of said topic ordering algorithm. | 1. A method for creating an ordered reading list of pre-determined length of relevant topics from a hyperlinked database source of information website based on a user's input, the method comprising: determining at least one topic of interest; choosing a topic ordering algorithm from a plurality of topic ordering algorithms including a top-down schematic algorithm, a bottom-up schematic algorithm, and a horizontal schematic algorithm, said top-down schematic algorithm comprises a page rank calculation performed by iterating until a convergence, said bottom-up schematic algorithm comprises a ratio of a combined weight from a plurality of source topics to a plurality of sink topics of an article, said bottom-up schematic algorithm linearly parameterizes an ordering from said source topics to said sink topics of an article k, wherein a ratio is Π i v source(i) → k /Π j v source(j) → k of a rank of said source topics to a rank of said sink topics, wherein a point where relevance of said topics is cutoff is calculated by multiplying Π i v source(i) → k by Π j v sink(j) → k , wherein a comparison is found by graphing a distance from said seed topics, ordered by a difference of distances, calculated by [Σ ij |(d source(i) → k )−(d sink(j) → k )|], and is cutoff by a sum of distances calculated by Σ i d source(i) → k +Σ j d sink(j) → k , and said horizontal schematic algorithm comprises an order parameterization by absolute differences of a log of a plurality of ranks and an absolute difference of a plurality of distances with analogous cutoff methods, wherein said sink topic is where said reading list terminates and said source topic is where said reading list begins; calculating one of a plurality of topics ordering algorithms based on said topic of interest and a user; updating said hyperlinked database source of information; forming a reading list and ranking said reading list based on said topic ordering algorithm; and outputting said ranking and said reading list to an interface depending on an outcome of said topic ordering algorithm. 5. The method of claim 1 further comprising inputting said topic of interest. | 0.880062 |
7,783,637 | 12 | 13 | 12. The method of claim 9 further comprising: receiving a selection of a label from the list of existing labels; and comparing the indicated use of the selected label against the indicated use of the new label. | 12. The method of claim 9 further comprising: receiving a selection of a label from the list of existing labels; and comparing the indicated use of the selected label against the indicated use of the new label. 13. The method of claim 12 comprising: determining that the indicated use of the selected label is not the same as the indicated use of the new label; and duplicating the selected label to the new label in the label database. | 0.5 |
7,853,594 | 6 | 8 | 6. The computer implemented method of claim 1 wherein at least one of the weighting factors includes activity in a threaded discussion database. | 6. The computer implemented method of claim 1 wherein at least one of the weighting factors includes activity in a threaded discussion database. 8. The computer implemented method of claim 6 wherein the activity includes modifications to at least one of the plurality of documents. | 0.5 |
8,214,215 | 5 | 6 | 5. The speech recognition system of claim 4 , wherein the initializer component initializes an additive distortion mean vector using sample estimates from at least a first plurality of frames from the received distorted speech utterance, wherein the updater component updates the parameters of the second model based at least in part upon the additive distortion mean vector. | 5. The speech recognition system of claim 4 , wherein the initializer component initializes an additive distortion mean vector using sample estimates from at least a first plurality of frames from the received distorted speech utterance, wherein the updater component updates the parameters of the second model based at least in part upon the additive distortion mean vector. 6. The speech recognition system of claim 5 , wherein the initializer component initializes a diagonal covariance matrix by using the sample estimates from the first plurality of frames from the received distorted speech utterance, wherein the updater component updates the parameters of the second model based at least in part upon the diagonal covariance matrix. | 0.5 |
7,715,032 | 1 | 5 | 1. A computer implemented method for bulk communication of information to recipients via multiple delivery media including facsimile, email, and SMS messaging, said method including the steps of: receiving and processing information for distribution including information regarding recipients and including information on the recipients' delivery preferences; forming a plurality of documents from the information for distribution by merging the information for distribution with a template document specific to a delivery media, wherein a different template document is used for each delivery media, bundling the plurality of documents together into a plurality of bundles, each bundle containing a plurality of documents and each bundle formed of documents to be delivered over a specified delivery media of the multiple delivery media, wherein the specified delivery media is determined based on the recipients' delivery preferences; transmitting the plurality of bundles; receiving and processing a report for each bundle of the plurality of bundles indicating whether transmission of documents in the bundle over said specified delivery media has failed; and escalating transmission of the plurality of documents using a different delivery media of the multiple delivery media for each of said recipients for whom transmission by said specified delivery media has failed, wherein the different delivery media is determined based on the recipients' delivery preferences and the plurality of documents are formed again by merging the information for distribution with a template document specific to said different delivery media. | 1. A computer implemented method for bulk communication of information to recipients via multiple delivery media including facsimile, email, and SMS messaging, said method including the steps of: receiving and processing information for distribution including information regarding recipients and including information on the recipients' delivery preferences; forming a plurality of documents from the information for distribution by merging the information for distribution with a template document specific to a delivery media, wherein a different template document is used for each delivery media, bundling the plurality of documents together into a plurality of bundles, each bundle containing a plurality of documents and each bundle formed of documents to be delivered over a specified delivery media of the multiple delivery media, wherein the specified delivery media is determined based on the recipients' delivery preferences; transmitting the plurality of bundles; receiving and processing a report for each bundle of the plurality of bundles indicating whether transmission of documents in the bundle over said specified delivery media has failed; and escalating transmission of the plurality of documents using a different delivery media of the multiple delivery media for each of said recipients for whom transmission by said specified delivery media has failed, wherein the different delivery media is determined based on the recipients' delivery preferences and the plurality of documents are formed again by merging the information for distribution with a template document specific to said different delivery media. 5. The method according to claim 1 , wherein said delivery media includes one or more new delivery media types. | 0.888778 |
8,903,813 | 1 | 3 | 1. A computer hardware-implemented method of identifying non-synthetic event elements in electronic files, the computer hardware-implemented method comprising: receiving, from a requesting computer, a first set of binary data that describes a synthetic event, wherein the synthetic event is a non-executable descriptor of a set of context-related factors; performing a context-based search of a database of electronic files to identify a relevant electronic file, wherein the relevant electronic file comprises the synthetic event; searching the relevant electronic file for at least one non-synthetic event element, wherein the non-synthetic event element is absent from the synthetic event; in response to determining that the relevant electronic file comprises said at least one non-synthetic event element, transmitting a second set of binary data to the requesting computer, wherein the second set of binary data comprises the relevant electronic file and a description of an identified non-synthetic event element within the relevant electronic file; limiting the context-based search to search only files that are not related to activities that generated the synthetic event, wherein an activity that generated the synthetic event was medical disease research, and wherein the context-based search is limited to searching non-medical literature; and establishing a connection between the synthetic event and non-synthetic event elements found in the non-medical literature. | 1. A computer hardware-implemented method of identifying non-synthetic event elements in electronic files, the computer hardware-implemented method comprising: receiving, from a requesting computer, a first set of binary data that describes a synthetic event, wherein the synthetic event is a non-executable descriptor of a set of context-related factors; performing a context-based search of a database of electronic files to identify a relevant electronic file, wherein the relevant electronic file comprises the synthetic event; searching the relevant electronic file for at least one non-synthetic event element, wherein the non-synthetic event element is absent from the synthetic event; in response to determining that the relevant electronic file comprises said at least one non-synthetic event element, transmitting a second set of binary data to the requesting computer, wherein the second set of binary data comprises the relevant electronic file and a description of an identified non-synthetic event element within the relevant electronic file; limiting the context-based search to search only files that are not related to activities that generated the synthetic event, wherein an activity that generated the synthetic event was medical disease research, and wherein the context-based search is limited to searching non-medical literature; and establishing a connection between the synthetic event and non-synthetic event elements found in the non-medical literature. 3. The computer hardware-implemented method of claim 1 , wherein the synthetic event is an occurrence of a set of words in a single document, wherein a factor in the set of context-related factors is the occurrence of all words in the set of words, and wherein a context of the set of context-related factors is the single document containing all of the words in the set of words. | 0.818008 |
9,031,898 | 33 | 38 | 33. A method performed by one or more server devices, the method comprising: identifying, by a processor of the one or more server devices, a document that is relevant to a search term, the document comprising structural elements, where the structural elements comprise the document, a set of parts of the document, and a set of pages of the document; identifying, by a processor of the one or more server devices, a tree representation of the document, where the pages of the document correspond to leaf nodes, the parts of the document correspond to higher level nodes, and the document corresponds to a root node; assigning, by a processor of the one or more server devices, scores to the leaf nodes based on whether the leaf nodes contain occurrences of the search term; determining, by a processor of the one or more server devices, scores for the higher level nodes based on the scores of associated ones of the leaf nodes; determining, by a processor of the one or more server devices, a score for the root node based on the scores of the higher level nodes; providing, by a processor of the one or more server devices, a threshold, where the threshold is based on at least one of: a number of pages associated with one of the leaf nodes, a number of pages associated with one of the higher level nodes, or a number of pages associated with the root node; selecting, by a processor of the one or more server devices, one of the leaf nodes, one of the higher level nodes, or the root node, as a selected node, based on the scores and the threshold; and providing, by a processor of the one or more server devices, information relating to the selected node. | 33. A method performed by one or more server devices, the method comprising: identifying, by a processor of the one or more server devices, a document that is relevant to a search term, the document comprising structural elements, where the structural elements comprise the document, a set of parts of the document, and a set of pages of the document; identifying, by a processor of the one or more server devices, a tree representation of the document, where the pages of the document correspond to leaf nodes, the parts of the document correspond to higher level nodes, and the document corresponds to a root node; assigning, by a processor of the one or more server devices, scores to the leaf nodes based on whether the leaf nodes contain occurrences of the search term; determining, by a processor of the one or more server devices, scores for the higher level nodes based on the scores of associated ones of the leaf nodes; determining, by a processor of the one or more server devices, a score for the root node based on the scores of the higher level nodes; providing, by a processor of the one or more server devices, a threshold, where the threshold is based on at least one of: a number of pages associated with one of the leaf nodes, a number of pages associated with one of the higher level nodes, or a number of pages associated with the root node; selecting, by a processor of the one or more server devices, one of the leaf nodes, one of the higher level nodes, or the root node, as a selected node, based on the scores and the threshold; and providing, by a processor of the one or more server devices, information relating to the selected node. 38. The method of claim 33 , where the information related to the selected node is a title page of the document when the document is the selected node. | 0.851961 |
8,713,054 | 12 | 15 | 12. A computer-implemented method to assist an information security classification process of an organization for security classification and marking of an electronic document on a computer system, said method comprising: a. performing on at least one computer system, b. establishing an electronic document security regimen comprising at least one criterion of an information security classification process, c. displaying a user classification dialogue for at least one informational portion of an electronic document, where said user classification dialogue comprising a menu of choices, where said menu of choices comprising at least one element for selection, and where said at least one element is associated with said at least one criterion of said electronic document security regimen, d. retrieving said at least one element where said at least one element is selected, e. establishing a classification mark from said at least one criterion associated with the retrieved said at least one element, and f. inserting said classification mark into said electronic document. | 12. A computer-implemented method to assist an information security classification process of an organization for security classification and marking of an electronic document on a computer system, said method comprising: a. performing on at least one computer system, b. establishing an electronic document security regimen comprising at least one criterion of an information security classification process, c. displaying a user classification dialogue for at least one informational portion of an electronic document, where said user classification dialogue comprising a menu of choices, where said menu of choices comprising at least one element for selection, and where said at least one element is associated with said at least one criterion of said electronic document security regimen, d. retrieving said at least one element where said at least one element is selected, e. establishing a classification mark from said at least one criterion associated with the retrieved said at least one element, and f. inserting said classification mark into said electronic document. 15. The method of claim 12 , further comprising inserting a location storage path for said electronic document into said electronic document. | 0.855533 |
8,687,210 | 1 | 6 | 1. A method, comprising: obtaining an electronic document conforming to one of a plurality of print formats; parsing the electronic document according to the one of the plurality of print formats to generate an intermediate data structure conforming to an intermediate format such that the electronic document is converted to the intermediate format, wherein the intermediate format is different from the plurality of print formats; applying one or more rules to obtain data for a plurality of regions of the electronic document from the intermediate data structure; and storing or providing the data for the plurality of regions of the electronic document that has been obtained from the intermediate data structure, thereby enabling a report to be generated using at least a portion of the data for the plurality of regions that has been stored or provided. | 1. A method, comprising: obtaining an electronic document conforming to one of a plurality of print formats; parsing the electronic document according to the one of the plurality of print formats to generate an intermediate data structure conforming to an intermediate format such that the electronic document is converted to the intermediate format, wherein the intermediate format is different from the plurality of print formats; applying one or more rules to obtain data for a plurality of regions of the electronic document from the intermediate data structure; and storing or providing the data for the plurality of regions of the electronic document that has been obtained from the intermediate data structure, thereby enabling a report to be generated using at least a portion of the data for the plurality of regions that has been stored or provided. 6. The method as recited in claim 1 , wherein storing or providing the data for the plurality of regions of the electronic document that has been obtained from the intermediate data structure comprises: generating a document data structure that contains the data for the plurality of regions of the electronic document. | 0.683532 |
9,047,383 | 11 | 16 | 11. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: identifying websites with which users of a social networking service have established an affiliation; filtering the identified websites by removing websites in which a count of users who have established an affiliation with the website exceeds a threshold, the filtering producing a plurality of filtered websites; producing a list of valid affiliations for each filtered website, comprising: generating a validity score for each of the established affiliations with the respective filtered website, determining whether each of the established affiliations with the respective filtered website is valid based on the corresponding validity score, and ranking the users who established valid affiliations with the respective filtered website based on the corresponding validity scores; and providing the list of the valid affiliations ordered by the ranking. | 11. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: identifying websites with which users of a social networking service have established an affiliation; filtering the identified websites by removing websites in which a count of users who have established an affiliation with the website exceeds a threshold, the filtering producing a plurality of filtered websites; producing a list of valid affiliations for each filtered website, comprising: generating a validity score for each of the established affiliations with the respective filtered website, determining whether each of the established affiliations with the respective filtered website is valid based on the corresponding validity score, and ranking the users who established valid affiliations with the respective filtered website based on the corresponding validity scores; and providing the list of the valid affiliations ordered by the ranking. 16. The system of claim 11 , wherein generating the validity score comprises determining a number of times a respective user links to the respective filtered website on posts generated by the respective user. | 0.585657 |
9,652,456 | 1 | 4 | 1. A method for managing links in a Darwin Information Typing Architecture (DITA), comprising: selecting in a graphical user interface an information unit file comprising a plurality of topics; displaying in the graphical user interface the plurality of topics included in the selected information unit file; selecting a topic from the plurality of topics; selecting in the graphical user interface a relationship management file comprising a DITA map comprising a relationship table comprising a multiplicity of links each of the links relating one of the topics in the selected information unit file to another of the topics in the selected information unit file; displaying in the graphical user interface all links included in the selected relationship management file for the selected topic, wherein each link comprises a reference to and/or from a second topic; and adding a link to the relationship management file by iterating through each topic of the selected information unit file in the relationship table of the selected relationship management file and adding a corresponding reference to an appropriate cell of the relationship table. | 1. A method for managing links in a Darwin Information Typing Architecture (DITA), comprising: selecting in a graphical user interface an information unit file comprising a plurality of topics; displaying in the graphical user interface the plurality of topics included in the selected information unit file; selecting a topic from the plurality of topics; selecting in the graphical user interface a relationship management file comprising a DITA map comprising a relationship table comprising a multiplicity of links each of the links relating one of the topics in the selected information unit file to another of the topics in the selected information unit file; displaying in the graphical user interface all links included in the selected relationship management file for the selected topic, wherein each link comprises a reference to and/or from a second topic; and adding a link to the relationship management file by iterating through each topic of the selected information unit file in the relationship table of the selected relationship management file and adding a corresponding reference to an appropriate cell of the relationship table. 4. The method of claim 1 , wherein displaying the plurality of topics comprises: displaying a title for each of the plurality of topics. | 0.745318 |
8,498,871 | 10 | 12 | 10. A method of providing transcribed spoken text among users, the method comprising: generating a speech information request using a user interface device capable of bi-directional communication with the system transaction manager and supporting dictation applications including prompts to direct user dictation in response to user system protocol commands and system transaction manager commands, the user interface being in bi-directional communication with the systems transaction manager wherein the speech information request is comprised of spoken text obtained through a first user legacy protocol; transmitting the speech information request to a speech recognition and/or transcription engine via a Systems Transaction Manager, the Systems Transaction Manager using a uniform system protocol; generating a response to the speech information request using the speech recognition and/or transcription engine, the response comprised of a transcription sending the response to a user via the system transaction manager; and providing the user with a transcription of the spoken text that is compatible with a second user legacy protocol that is different than the first legacy protocol; wherein the transmitting step and the sending step includes translating between the first user legacy protocol and the uniform system protocol and between the second user legacy protocol and the uniform system protocol, respectively. | 10. A method of providing transcribed spoken text among users, the method comprising: generating a speech information request using a user interface device capable of bi-directional communication with the system transaction manager and supporting dictation applications including prompts to direct user dictation in response to user system protocol commands and system transaction manager commands, the user interface being in bi-directional communication with the systems transaction manager wherein the speech information request is comprised of spoken text obtained through a first user legacy protocol; transmitting the speech information request to a speech recognition and/or transcription engine via a Systems Transaction Manager, the Systems Transaction Manager using a uniform system protocol; generating a response to the speech information request using the speech recognition and/or transcription engine, the response comprised of a transcription sending the response to a user via the system transaction manager; and providing the user with a transcription of the spoken text that is compatible with a second user legacy protocol that is different than the first legacy protocol; wherein the transmitting step and the sending step includes translating between the first user legacy protocol and the uniform system protocol and between the second user legacy protocol and the uniform system protocol, respectively. 12. The method of claim 10 wherein the transmitting step includes using a virtual sound driver in communication with the system transaction manager and the speech recognition and/or transcription engine for streaming a free form dictation speech information request to the speech recognition and/or transcription engine wherein the virtual sound driver outputs the speech information request in a data format which is compatible with the speech recognition and/or transcription engine input format, regardless of the actual originating source format. | 0.5 |
8,972,388 | 17 | 18 | 17. The system of claim 12 , further comprising instructions to: receive one or more further characters entered into the search field upon display of the refined second list, wherein the second partial query and the further characters represent a third partial query; obtain a third list of query completions for the third partial query; identify one or more query completions in the third list that appear in the refined second list; calculate demotion scores for the identified query completions in the third list, wherein a demotion score for a given identified query completion in the third list is based at least in part on a second period of time between when the refined second list was displayed and when the further characters were entered; use the demotion scores for the identified completions in the third list to demote one or more of the identified query completions to a lesser position in the third list, thereby forming a refined third list; and provide the refined third list of query completions for display on the computing device. | 17. The system of claim 12 , further comprising instructions to: receive one or more further characters entered into the search field upon display of the refined second list, wherein the second partial query and the further characters represent a third partial query; obtain a third list of query completions for the third partial query; identify one or more query completions in the third list that appear in the refined second list; calculate demotion scores for the identified query completions in the third list, wherein a demotion score for a given identified query completion in the third list is based at least in part on a second period of time between when the refined second list was displayed and when the further characters were entered; use the demotion scores for the identified completions in the third list to demote one or more of the identified query completions to a lesser position in the third list, thereby forming a refined third list; and provide the refined third list of query completions for display on the computing device. 18. The system of claim 17 , wherein the given identified query completion in the third list further appears in the first list, and the demotion score for the given identified query completion is further based on the period of time between when the first list was displayed and when the additional characters were entered. | 0.5 |
8,234,259 | 12 | 14 | 12. A computerized method of adjudicating text against a policy comprising: receiving one or more system policies, each system policy comprising: one or more prohibited words; one or more groups of associated prohibited words; a first hit value for each prohibited word, the hit value indicating the significance of the prohibited word; a second hit value for each associated prohibited word, the hit value indicating the significance of the associated prohibited word; a proximity value corresponding to each associated prohibited word; and a threshold value for each group of associated prohibited words, the threshold value indicating a limit on the hit values for the associated prohibited words in the group; creating a system datastructure for each received system policy, each system datastructure comprising a hash table, the hash table comprising a plurality of linked lists corresponding the letters of the alphabet; receiving an input message comprising a text to be adjudicated; selecting a system policy from the one or more received system policies based on the input message; and determining whether the text contains any prohibited associated words from the one or more prohibited associated words by processing the text and the system datastructure corresponding to the selected system policy, wherein the determining whether the text contains any prohibited associated words from the one or more prohibited associated words by processing the text and the system datastructure corresponding to the selected system policy comprises: creating a temporary datastructure by duplicating the system datastructure corresponding to the selected system policy; selecting a word from the text to be adjudicated; identifying a linked list in the temporary datastructure that corresponds to the first letter of the selected word; searching the identified linked list for the selected word; recording the selected word as a found prohibited word in a head linked list of the temporary datastructure if the selected word is found in the identified linked list; recording a proximity string of text associated with each prohibited word in the head linked list of the temporary datastructure if the selected word is found in the identified linked list; searching the proximity string of text for the associated prohibited word; and determining whether the proximity string of text comprises the associated prohibited word. | 12. A computerized method of adjudicating text against a policy comprising: receiving one or more system policies, each system policy comprising: one or more prohibited words; one or more groups of associated prohibited words; a first hit value for each prohibited word, the hit value indicating the significance of the prohibited word; a second hit value for each associated prohibited word, the hit value indicating the significance of the associated prohibited word; a proximity value corresponding to each associated prohibited word; and a threshold value for each group of associated prohibited words, the threshold value indicating a limit on the hit values for the associated prohibited words in the group; creating a system datastructure for each received system policy, each system datastructure comprising a hash table, the hash table comprising a plurality of linked lists corresponding the letters of the alphabet; receiving an input message comprising a text to be adjudicated; selecting a system policy from the one or more received system policies based on the input message; and determining whether the text contains any prohibited associated words from the one or more prohibited associated words by processing the text and the system datastructure corresponding to the selected system policy, wherein the determining whether the text contains any prohibited associated words from the one or more prohibited associated words by processing the text and the system datastructure corresponding to the selected system policy comprises: creating a temporary datastructure by duplicating the system datastructure corresponding to the selected system policy; selecting a word from the text to be adjudicated; identifying a linked list in the temporary datastructure that corresponds to the first letter of the selected word; searching the identified linked list for the selected word; recording the selected word as a found prohibited word in a head linked list of the temporary datastructure if the selected word is found in the identified linked list; recording a proximity string of text associated with each prohibited word in the head linked list of the temporary datastructure if the selected word is found in the identified linked list; searching the proximity string of text for the associated prohibited word; and determining whether the proximity string of text comprises the associated prohibited word. 14. The computerized method of adjudicating text against a policy of claim 12 , wherein: each linked list in the system datastructure comprises the prohibited words from the system policy that begin with a corresponding letter of the alphabet and the first hit value associated with each prohibited word; and each system datastructure further comprises the associated prohibited words, the second hit values, and the threshold values. | 0.505695 |
7,873,642 | 13 | 14 | 13. The computer program product of claim 9 , further comprising: seventh instructions for using the stored representation of the input media data to access the input media data. | 13. The computer program product of claim 9 , further comprising: seventh instructions for using the stored representation of the input media data to access the input media data. 14. The computer program product of claim 13 , wherein the seventh instructions for using the stored representation of the input media data to access the input media data includes: instructions for receiving a search query; instructions for determining if terms in the search query match terms in the stored representation of the input media data; and instructions for accessing the input media data if the terms in the search query match terms in the stored representation of the input media data. | 0.5 |
10,160,251 | 19 | 20 | 19. The one or more computer-readable media of claim 18 , wherein the physical object is a tangible version of a document. | 19. The one or more computer-readable media of claim 18 , wherein the physical object is a tangible version of a document. 20. The one or more computer-readable media of claim 19 , the operations further comprising employing the source identifier to verify that a signature of the document is that of the source user. | 0.5 |
10,038,786 | 1 | 8 | 1. A computer-implemented method, comprising: determining, by a processor, one or more mood metrics in each of two or more chat stages of a real-time textual conversation between an agent and a customer, wherein said determining the one or more mood metrics for a chat stage of the real-time textual conversation, by the processor, further comprises determining an overall mood for the chat stage based on a polarity based approach by: assigning polarity labels to features present in the chat stage; assigning polarity strength scores for the polarity labels assigned to the features present in the chat stage; calculating weighted polarity scores for the features based on aggregation of the polarity labels and the polarity strength scores to determine the overall mood for the chat stage; and determining the overall mood, by the processor, based on a subjectivity-based approach by removing terms classified as objective from the real-time textual conversation prior to assigning the polarity labels and the polarity strength scores; tracking, by the processor, changes in the one or more mood metrics across the two or more chat stages of the real-time textual conversation between the agent and the customer; and determining, by the processor, at least one action associated with the real-time textual conversation based on the changes in the one or more mood metrics; performing, by the processor, the at least one action associated with the real-time textual conversation, wherein performing the at least one action comprises any of: displaying, by the processor, information associated with the at least one action to a supervisor monitoring the real-time textual conversation and providing, by the processor, the information associated with the at least one action to the agent engaged in the real-time textual conversation based on an input received from the supervisor so as to enable the agent to perform the at least one action thereby causing a target outcome of the real-time textual conversation; monitoring an agent engagement score associated with the two or more chat stages of the real-time textual conversation; storing the real-time textual conversation with a timestamp of the real-time textual conversation; and displaying one or more textual recommendations to the agent so as to enable the agent to use the one or more textual recommendations in the real-time textual conversation to thereby cause a target outcome of the real-time textual conversation. | 1. A computer-implemented method, comprising: determining, by a processor, one or more mood metrics in each of two or more chat stages of a real-time textual conversation between an agent and a customer, wherein said determining the one or more mood metrics for a chat stage of the real-time textual conversation, by the processor, further comprises determining an overall mood for the chat stage based on a polarity based approach by: assigning polarity labels to features present in the chat stage; assigning polarity strength scores for the polarity labels assigned to the features present in the chat stage; calculating weighted polarity scores for the features based on aggregation of the polarity labels and the polarity strength scores to determine the overall mood for the chat stage; and determining the overall mood, by the processor, based on a subjectivity-based approach by removing terms classified as objective from the real-time textual conversation prior to assigning the polarity labels and the polarity strength scores; tracking, by the processor, changes in the one or more mood metrics across the two or more chat stages of the real-time textual conversation between the agent and the customer; and determining, by the processor, at least one action associated with the real-time textual conversation based on the changes in the one or more mood metrics; performing, by the processor, the at least one action associated with the real-time textual conversation, wherein performing the at least one action comprises any of: displaying, by the processor, information associated with the at least one action to a supervisor monitoring the real-time textual conversation and providing, by the processor, the information associated with the at least one action to the agent engaged in the real-time textual conversation based on an input received from the supervisor so as to enable the agent to perform the at least one action thereby causing a target outcome of the real-time textual conversation; monitoring an agent engagement score associated with the two or more chat stages of the real-time textual conversation; storing the real-time textual conversation with a timestamp of the real-time textual conversation; and displaying one or more textual recommendations to the agent so as to enable the agent to use the one or more textual recommendations in the real-time textual conversation to thereby cause a target outcome of the real-time textual conversation. 8. The method of claim 1 , wherein determination of the at least one action is performed further based on historical information associated with one or more completed textual conversations. | 0.674138 |
9,900,632 | 17 | 19 | 17. A non-transitory computer readable storage medium comprising instructions that, when executed by one or more processors, cause the one or more processors to perform operations including: receiving video content using an inactive tuner of a television receiver; obtaining text data corresponding to an audio portion of the video content; evaluating the text data to identify frequencies of words appearing in the text data; receiving input corresponding to determination of one or more user-designated keywords; storing the one or more user-designated keywords to a word list, wherein the word list includes at least a first keyword; determining that the first keyword appears in the text data with a first frequency greater than a first threshold frequency; and generating a first interface for display on a display device in real-time upon determining that the first frequency is greater than the first threshold frequency, wherein the first interface includes a notification identifying a match of the first keyword. | 17. A non-transitory computer readable storage medium comprising instructions that, when executed by one or more processors, cause the one or more processors to perform operations including: receiving video content using an inactive tuner of a television receiver; obtaining text data corresponding to an audio portion of the video content; evaluating the text data to identify frequencies of words appearing in the text data; receiving input corresponding to determination of one or more user-designated keywords; storing the one or more user-designated keywords to a word list, wherein the word list includes at least a first keyword; determining that the first keyword appears in the text data with a first frequency greater than a first threshold frequency; and generating a first interface for display on a display device in real-time upon determining that the first frequency is greater than the first threshold frequency, wherein the first interface includes a notification identifying a match of the first keyword. 19. The non-transitory computer readable storage medium of claim 17 , wherein obtaining the text data includes decoding a closed caption portion of the video content to generate the text data, decoding a subtitle portion of the video content to generate the text data, retrieving the text data from a network location, processing the audio portion of the video content using a speech-to-text algorithm to generate the text data, or rendering the video content with embedded closed captions or subtitles and generating the text data by performing character recognition on the embedded closed captions or subtitles. | 0.534901 |
8,713,117 | 3 | 5 | 3. The method of claim 1 , further comprising the steps of: receiving a responsive message at the MCMS from the respective chat agent utilizing the respective chat platform, wherein the responsive message includes responsive message content and responsive message identifying information, and wherein the responsive message is in the format acceptable to the respective chat platform; parsing the responsive message via the MCMS to extract a particular chat session identifier from the responsive message identifying information; using the particular chat session identifier, retrieving information associated with the particular chat session; retrieving a unique identifier of the specific mobile device user to which the responsive message is directed from the particular chat session information; associating the responsive message with the unique identifier of the specific mobile device user via the MCMS; generating via the MCMS a responsive mobile chat message in a format acceptable to a specific mobile device of the specific mobile device user, wherein the responsive mobile chat message includes the responsive message content and is based on the responsive message identifying information; and transmitting the responsive mobile chat message from the MCMS to the specific mobile device user via the respective mobile carrier network. | 3. The method of claim 1 , further comprising the steps of: receiving a responsive message at the MCMS from the respective chat agent utilizing the respective chat platform, wherein the responsive message includes responsive message content and responsive message identifying information, and wherein the responsive message is in the format acceptable to the respective chat platform; parsing the responsive message via the MCMS to extract a particular chat session identifier from the responsive message identifying information; using the particular chat session identifier, retrieving information associated with the particular chat session; retrieving a unique identifier of the specific mobile device user to which the responsive message is directed from the particular chat session information; associating the responsive message with the unique identifier of the specific mobile device user via the MCMS; generating via the MCMS a responsive mobile chat message in a format acceptable to a specific mobile device of the specific mobile device user, wherein the responsive mobile chat message includes the responsive message content and is based on the responsive message identifying information; and transmitting the responsive mobile chat message from the MCMS to the specific mobile device user via the respective mobile carrier network. 5. The method of claim 3 , further comprising the steps of: identifying the respective mobile carrier network associated with the specific mobile device user; identifying an optimal carrier-specific route for message delivery based on predetermined optimizing criteria; and routing the responsive mobile chat message to the specific mobile device user via the optimal carrier-specific route. | 0.5 |
9,026,432 | 1 | 7 | 1. A computer-assisted language generation system comprising: sentence retrieval functionality, operative on the basis of an input text containing words, to retrieve from an internet corpus a plurality of sentences containing words which correspond to said words in the input text; and sentence generation functionality operative using said plurality of sentences to generate at least one correct sentence giving expression to the input text, said sentence generation functionality comprising: sentence simplification functionality operative to simplify said sentences retrieved from said internet corpus; simplified sentence grouping functionality for grouping similar simplified sentences provided by said sentence simplification functionality; simplified sentence group ranking functionality for ranking groups of said similar simplified sentences; and sentence selection functionality operative to select at least one of said similar simplified sentences as said at least one correct sentence based on said ranking; said simplified sentence group ranking functionality operates using an extent to which the group includes words which do not correspond to the words in an independent phrase and their alternatives. | 1. A computer-assisted language generation system comprising: sentence retrieval functionality, operative on the basis of an input text containing words, to retrieve from an internet corpus a plurality of sentences containing words which correspond to said words in the input text; and sentence generation functionality operative using said plurality of sentences to generate at least one correct sentence giving expression to the input text, said sentence generation functionality comprising: sentence simplification functionality operative to simplify said sentences retrieved from said internet corpus; simplified sentence grouping functionality for grouping similar simplified sentences provided by said sentence simplification functionality; simplified sentence group ranking functionality for ranking groups of said similar simplified sentences; and sentence selection functionality operative to select at least one of said similar simplified sentences as said at least one correct sentence based on said ranking; said simplified sentence group ranking functionality operates using an extent to which the group includes words which do not correspond to the words in an independent phrase and their alternatives. 7. A computer-assisted language generation system according to claim 1 and wherein said simplified sentence group ranking functionality includes calculating a Positive Match Rank corresponding to a degree to which the word stems of the words in the group correspond to the word stems in an independent phrase and their alternatives. | 0.718644 |
9,836,520 | 11 | 17 | 11. A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions configured for: performing a classification operation on a plurality of data objects to provide a plurality of classified data objects; performing a classification validation operation on a plurality of classified data objects, the classification validation operation automatically validating whether each of the plurality of classified data objects were correctly classified, the classification validation operation automatically identifying outliers, the outliers corresponding to data objects which are likely to require reclassification, the automatically identifying outliers being performed using a similarity matrix operation, the similarity matrix operation making use of a plurality of similarity matrices, each of the plurality of similarity matrices corresponding to a given category of data objects; identifying misclassified data objects based upon the classification validation operation; performing a reclassification operation on the misclassified data objects, the reclassification operation using information derived from the classification validation operation to correctly classify the misclassified data objects; and wherein the similarity matrix operation comprises calculating a similarity value for each data object against all other data objects in a given category to determine elements of the similarity matrix; and, a similarity measure is used to generate the similarity value for the plurality of data objects, the similarity measure comprising at least one of a cosine similarity measure and a Levenshtein distance measure. | 11. A non-transitory, computer-readable storage medium embodying computer program code, the computer program code comprising computer executable instructions configured for: performing a classification operation on a plurality of data objects to provide a plurality of classified data objects; performing a classification validation operation on a plurality of classified data objects, the classification validation operation automatically validating whether each of the plurality of classified data objects were correctly classified, the classification validation operation automatically identifying outliers, the outliers corresponding to data objects which are likely to require reclassification, the automatically identifying outliers being performed using a similarity matrix operation, the similarity matrix operation making use of a plurality of similarity matrices, each of the plurality of similarity matrices corresponding to a given category of data objects; identifying misclassified data objects based upon the classification validation operation; performing a reclassification operation on the misclassified data objects, the reclassification operation using information derived from the classification validation operation to correctly classify the misclassified data objects; and wherein the similarity matrix operation comprises calculating a similarity value for each data object against all other data objects in a given category to determine elements of the similarity matrix; and, a similarity measure is used to generate the similarity value for the plurality of data objects, the similarity measure comprising at least one of a cosine similarity measure and a Levenshtein distance measure. 17. The non-transitory, computer-readable storage medium of claim 11 , wherein the computer executable instructions are provided by a service provider to a user on an on-demand basis. | 0.714953 |
9,685,158 | 3 | 4 | 3. The method of claim 2 , further comprising causing presentation of the first prior communication on the display. | 3. The method of claim 2 , further comprising causing presentation of the first prior communication on the display. 4. The method of claim 3 , wherein the transcribed message and the first prior communication are presented in a common display screen. | 0.5 |
8,694,560 | 17 | 18 | 17. The computer-implemented method of claim 16 , comprising generating the subsequent table definition language by applying an inheritance chain, comprising a plurality of table definition language fragments to the first table definition language. | 17. The computer-implemented method of claim 16 , comprising generating the subsequent table definition language by applying an inheritance chain, comprising a plurality of table definition language fragments to the first table definition language. 18. The computer-implemented method of claim 17 , comprising generating a specific version of the subsequent table definition language by applying a subset of the plurality of table definition language fragments associated with the specific version. | 0.5 |
8,352,855 | 1 | 11 | 1. A non-transitory computer readable medium storing a computer program which when executed by at least one processor defines a selection of text in a document, the computer program comprising sets of instructions for: receiving an unstructured document comprising a plurality of unassociated glyphs; associating sets of glyphs into a plurality of columns; creating a structured document from the unstructured document comprising a plurality of layouts and a flow of reading through the plurality of layouts, each particular layout comprising at least one of the plurality of columns and a reading order for the columns within the particular layout; displaying the structured document; receiving a start point in a first column in a first layout and an end point in a second column in a second, different layout, the second layout having an order value after the first layout; and defining a selection of text from the start point to the end point by using the structured document, the selection including (i) all glyphs after the start point in the first column in the first layout according to the reading order for the columns in the first layout, (ii) all glyphs of the columns of the intervening layouts between the first and second layouts according to the flow of reading through the layouts, and (iii) all glyphs that precede the end point in the second layout according to the reading order for the columns in the second layout. | 1. A non-transitory computer readable medium storing a computer program which when executed by at least one processor defines a selection of text in a document, the computer program comprising sets of instructions for: receiving an unstructured document comprising a plurality of unassociated glyphs; associating sets of glyphs into a plurality of columns; creating a structured document from the unstructured document comprising a plurality of layouts and a flow of reading through the plurality of layouts, each particular layout comprising at least one of the plurality of columns and a reading order for the columns within the particular layout; displaying the structured document; receiving a start point in a first column in a first layout and an end point in a second column in a second, different layout, the second layout having an order value after the first layout; and defining a selection of text from the start point to the end point by using the structured document, the selection including (i) all glyphs after the start point in the first column in the first layout according to the reading order for the columns in the first layout, (ii) all glyphs of the columns of the intervening layouts between the first and second layouts according to the flow of reading through the layouts, and (iii) all glyphs that precede the end point in the second layout according to the reading order for the columns in the second layout. 11. The non-transitory computer readable medium of claim 1 , wherein the unstructured document is a vector graphics document. | 0.842965 |
9,218,334 | 1 | 15 | 1. A computer-implemented method of generating pronounceable domain names, comprising: providing a list of character strings; determining a first probability that a character string in the list of character strings is pronounceable based on a phonetic model; determining a second probability that a character string in the list of character strings is pronounceable based on a character order model; filtering the list of character strings through a first filter based on the first probability to produce a first filtered list of character strings; filtering the list of character strings through a second filter based on the second probability to produce a second filtered list of character strings; and generating, by a processor, a list of pronounceable domain names based on the first filtered list of character strings and the second filtered list of character strings. | 1. A computer-implemented method of generating pronounceable domain names, comprising: providing a list of character strings; determining a first probability that a character string in the list of character strings is pronounceable based on a phonetic model; determining a second probability that a character string in the list of character strings is pronounceable based on a character order model; filtering the list of character strings through a first filter based on the first probability to produce a first filtered list of character strings; filtering the list of character strings through a second filter based on the second probability to produce a second filtered list of character strings; and generating, by a processor, a list of pronounceable domain names based on the first filtered list of character strings and the second filtered list of character strings. 15. The computer-implemented method of claim 1 , further comprising; determining a combined probability based on the first probability and the second probability that the input character string is pronounceable; comparing the combined probability with a pronounceability threshold to determine whether the input character string is likely to be pronounceable; and providing the input character string as the list of pronounceable domain names. | 0.5 |
9,472,184 | 1 | 4 | 1. In a computing device and at a speech recognition problem detection program executed on the computing device, a method for identifying a cross-language speech recognition problem, comprising: receiving a target word from a target application; acquiring a phonetic transcription of the target word comprising one or more target phonetic units; determining that at least one of the target phonetic units is not found in a plurality of native phonetic units associated with a native language; in response to determining that the at least one target phonetic unit is not found in the plurality of native phonetic units, outputting a warning of the cross-language speech recognition problem for display on a display device, wherein the warning comprises the target word; receiving feedback comprising performance statistics related to a recognition accuracy by a speech detection program of the target word, wherein the target word has been previously evaluated by the speech recognition problem detection program; utilizing the feedback to determine that the recognition accuracy of the target word is below a predetermined threshold; and in response to determining that the recognition accuracy of the target word is below a predetermined threshold, adding the target word to a black list comprising a plurality of words having a recognition accuracy below the predetermined threshold. | 1. In a computing device and at a speech recognition problem detection program executed on the computing device, a method for identifying a cross-language speech recognition problem, comprising: receiving a target word from a target application; acquiring a phonetic transcription of the target word comprising one or more target phonetic units; determining that at least one of the target phonetic units is not found in a plurality of native phonetic units associated with a native language; in response to determining that the at least one target phonetic unit is not found in the plurality of native phonetic units, outputting a warning of the cross-language speech recognition problem for display on a display device, wherein the warning comprises the target word; receiving feedback comprising performance statistics related to a recognition accuracy by a speech detection program of the target word, wherein the target word has been previously evaluated by the speech recognition problem detection program; utilizing the feedback to determine that the recognition accuracy of the target word is below a predetermined threshold; and in response to determining that the recognition accuracy of the target word is below a predetermined threshold, adding the target word to a black list comprising a plurality of words having a recognition accuracy below the predetermined threshold. 4. The method of claim 1 , wherein the one or more target phonetic units and the plurality of native phonetic units comprise phonemic units and syllabic units, and determining that at least one target phonetic unit is not found in the plurality of native phonetic units further comprises: determining that a target phonemic unit of the target word is not found in the plurality of native phonemic units associated with the native language; and determining that a target syllabic unit of the target word is not found in the plurality of native syllabic units associated with the native language. | 0.5 |
8,527,868 | 4 | 5 | 4. The method of claim 1 , wherein the user-defined and customizable script comprises code that is configured to interact with a person viewing the document. | 4. The method of claim 1 , wherein the user-defined and customizable script comprises code that is configured to interact with a person viewing the document. 5. The method of claim 4 , wherein the code tracks a location of a pointing device. | 0.5 |
9,898,580 | 1 | 6 | 1. A method comprising: extracting, from a text documenting a clinician's encounter with a single patient, a set of one or more clinical facts representing one or more abstract semantic concepts, wherein the extracting comprises analyzing the text, via a natural language understanding engine, to identify a set of one or more features of at least a portion of the text, and correlating the set of features to the one or more abstract semantic concepts; wherein the one or more abstract semantic concepts comprise a first diagnosis that the clinician, in the text, indicated that the patient exhibited; wherein the first diagnosis is a generic diagnosis representing a class of a plurality of more specific subdiagnoses of the first diagnosis; wherein the method further comprises: analyzing a history record comprising data indicative of the patient's history to determine an additional fact without needing to request input of the additional fact; analyzing the set of one or more clinical facts and the additional fact, using at least one processor, to generate one or more hypotheses for a second diagnosis, exhibited by the patient and not documented in the text, the second diagnosis being a particular one of the plurality of more specific subdiagnoses of the first diagnosis that the clinician indicated that the patient exhibited; and presenting, to a user, the generated at least one of the one or more hypotheses. | 1. A method comprising: extracting, from a text documenting a clinician's encounter with a single patient, a set of one or more clinical facts representing one or more abstract semantic concepts, wherein the extracting comprises analyzing the text, via a natural language understanding engine, to identify a set of one or more features of at least a portion of the text, and correlating the set of features to the one or more abstract semantic concepts; wherein the one or more abstract semantic concepts comprise a first diagnosis that the clinician, in the text, indicated that the patient exhibited; wherein the first diagnosis is a generic diagnosis representing a class of a plurality of more specific subdiagnoses of the first diagnosis; wherein the method further comprises: analyzing a history record comprising data indicative of the patient's history to determine an additional fact without needing to request input of the additional fact; analyzing the set of one or more clinical facts and the additional fact, using at least one processor, to generate one or more hypotheses for a second diagnosis, exhibited by the patient and not documented in the text, the second diagnosis being a particular one of the plurality of more specific subdiagnoses of the first diagnosis that the clinician indicated that the patient exhibited; and presenting, to a user, the generated at least one of the one or more hypotheses. 6. The method of claim 1 , wherein the alerting comprises presenting one or more options corresponding to the one or more hypotheses, and allowing the user to choose among the one or more options. | 0.662069 |
9,280,777 | 2 | 5 | 2. The method of claim 1 , wherein the one or more solutions to the selected at least one new business challenge of the selected operational unit each have a corresponding recommendation score that relates to an expected efficacy of the one or more solutions. | 2. The method of claim 1 , wherein the one or more solutions to the selected at least one new business challenge of the selected operational unit each have a corresponding recommendation score that relates to an expected efficacy of the one or more solutions. 5. The method of claim 2 , wherein the corresponding recommendation score is calculated based on a likelihood of the one or more solutions to solve the selected at least one new business challenge and a projected cost to implement a solution. | 0.5 |
7,536,634 | 12 | 18 | 12. A machine-based method for converting data from a first form associated with a data source to a second form for use by a target data system, comprising the steps of: receiving content associated with said data source; obtaining first information from said content; wherein said first information identifies a subject matter context of said content; obtaining second information from said content; wherein said first information identifies a subject matter context of said content obtaining second information from a location, external to said content, using said first information, wherein said obtaining second information comprises accessing conversion rules specific to said subject matter context where said conversion rules are included in a private schema, established based on external knowledge of a subject matter area independent of analysis of a particular data set to be converted, and specific to an entity or group of entities less than the public as a whole, and the private schema establishes a structure for understanding at least a portion of the subject matter area; and converting said content from said first form to said second form using said first information and said second information. | 12. A machine-based method for converting data from a first form associated with a data source to a second form for use by a target data system, comprising the steps of: receiving content associated with said data source; obtaining first information from said content; wherein said first information identifies a subject matter context of said content; obtaining second information from said content; wherein said first information identifies a subject matter context of said content obtaining second information from a location, external to said content, using said first information, wherein said obtaining second information comprises accessing conversion rules specific to said subject matter context where said conversion rules are included in a private schema, established based on external knowledge of a subject matter area independent of analysis of a particular data set to be converted, and specific to an entity or group of entities less than the public as a whole, and the private schema establishes a structure for understanding at least a portion of the subject matter area; and converting said content from said first form to said second form using said first information and said second information. 18. A method as set forth in claim 12 , wherein said rules are operative for identifying an impermissible attribute or attribute value based on said subject matter context. | 0.846429 |
9,063,924 | 20 | 24 | 20. A computer system comprising a processor coupled to a memory, wherein the memory is encoded with computer executable instructions that when executed cause the processor to: identify a propagating attribute associated with a parse item of a plurality of parse items, the plurality of parse items arranged in an ordered data structure; determine a direction of propagation of the propagating attribute within the ordered data structure; and selectively associate the propagating attribute with each parse item of the plurality of parse items located in the direction of propagation within the ordered data structure. | 20. A computer system comprising a processor coupled to a memory, wherein the memory is encoded with computer executable instructions that when executed cause the processor to: identify a propagating attribute associated with a parse item of a plurality of parse items, the plurality of parse items arranged in an ordered data structure; determine a direction of propagation of the propagating attribute within the ordered data structure; and selectively associate the propagating attribute with each parse item of the plurality of parse items located in the direction of propagation within the ordered data structure. 24. The computer system of claim 20 , wherein the instructions to identify a propagating attribute associated with a parse item of a plurality of parse items, the plurality of parse items arranged in an ordered data structure further cause the processor to: identify at least one boundary marker to provide the plurality of parse items; and identify a modifier associated with the parse item of the plurality of parse items. | 0.56998 |
8,631,048 | 10 | 11 | 10. The system of claim 9 , wherein the one or more new sets of data comprise a plurality of new data sets, and wherein the electronic processor is configured to: extract a plurality of schemas, wherein each of the plurality of schemas corresponds to one of the plurality of new data sets; determine one or more schema ontology assertions based on each of the plurality of schemas using the common schema ontology; align the determined schema ontology assertions to generate a set of aligned schema ontology assertions; and modify the at least one existing final ontology based on the set of aligned schema ontology assertions. | 10. The system of claim 9 , wherein the one or more new sets of data comprise a plurality of new data sets, and wherein the electronic processor is configured to: extract a plurality of schemas, wherein each of the plurality of schemas corresponds to one of the plurality of new data sets; determine one or more schema ontology assertions based on each of the plurality of schemas using the common schema ontology; align the determined schema ontology assertions to generate a set of aligned schema ontology assertions; and modify the at least one existing final ontology based on the set of aligned schema ontology assertions. 11. The system of claim 10 , wherein the electronic processor is configured to align the determined ontology assertions to generate a set of aligned ontology assertions by: determining the existence of one or more semantically equivalent elements between the schema ontology assertions; generating one or more new schema ontology assertions based on the schema ontology assertions containing the semantically equivalent elements; and generating the set of aligned schema ontology assertions based on the one or more new ontology assertions. | 0.5 |
8,504,427 | 18 | 19 | 18. The apparatus of claim 17 , further comprising: a scanner adapted to read information from one or more items, wherein the first language is selected based on the information read from the one or more items. | 18. The apparatus of claim 17 , further comprising: a scanner adapted to read information from one or more items, wherein the first language is selected based on the information read from the one or more items. 19. The apparatus of claim 18 , wherein the one or more items comprise one or more of a bank card, a credit card, a debit card, a loyalty card, a membership card, a key card, a smart card, a memory card, an access card, and a government issued identification. | 0.529091 |
9,729,717 | 14 | 15 | 14. A system, comprising at least one automatic speech recognition component configured to analyze at least one voice interaction by at least one agent that follows at least one script in at least one of a plurality of panels and to determine whether the at least one agent has adequately followed the at least one script using confidence level thresholds assigned to each of the plurality of panels. | 14. A system, comprising at least one automatic speech recognition component configured to analyze at least one voice interaction by at least one agent that follows at least one script in at least one of a plurality of panels and to determine whether the at least one agent has adequately followed the at least one script using confidence level thresholds assigned to each of the plurality of panels. 15. The system of claim 14 , wherein each of the plurality of panels is related to the at least one automatic speech recognition component. | 0.5 |
8,296,679 | 1 | 6 | 1. A method of enabling input on an electronic device having stored therein a plurality of objects that comprise a number of raw inputs, a number of characters, and a number of segments, each raw input having one or more of the characters associated therewith, each segment comprising a plurality of the characters, the method comprising: receiving a string of reference characters; obtaining the raw inputs with which the reference characters are associated; generating a proposed character interpretation of the obtained raw inputs; determining that at least a portion of the proposed character interpretation and a corresponding at least portion of the string of reference characters differ; and responsive to the determining, storing the at least portion of the string of reference characters as an object of the plurality of objects. | 1. A method of enabling input on an electronic device having stored therein a plurality of objects that comprise a number of raw inputs, a number of characters, and a number of segments, each raw input having one or more of the characters associated therewith, each segment comprising a plurality of the characters, the method comprising: receiving a string of reference characters; obtaining the raw inputs with which the reference characters are associated; generating a proposed character interpretation of the obtained raw inputs; determining that at least a portion of the proposed character interpretation and a corresponding at least portion of the string of reference characters differ; and responsive to the determining, storing the at least portion of the string of reference characters as an object of the plurality of objects. 6. The method of claim 1 wherein the plurality of objects further comprise a number of candidates and a number of combination objects, each combination object comprising a segment plus one of a character and a segment, and wherein the number of segments comprise a number of generic segments and a number of learned segments, and further comprising consulting one or more of the number of raw inputs, the number of characters, the number of combination objects, the number of generic segments, the number of learned segments, and the number of candidates in the generating of the proposed character interpretation. | 0.5 |
7,756,341 | 3 | 4 | 3. The method according to claim 2 , further comprising defining each class vocabulary by merging a general vocabulary and an adapted vocabulary for each class. | 3. The method according to claim 2 , further comprising defining each class vocabulary by merging a general vocabulary and an adapted vocabulary for each class. 4. The method according to claim 3 , wherein the histogram computed for each of the plurality of classes indicates whether the input image is better described by the general vocabulary or the adapted vocabulary of its corresponding class. | 0.5 |
8,359,312 | 1 | 6 | 1. A method for generating, by a monitoring program, a list of relevant documents, related to a first search query, comprising: tracking activities of a first user pursuant to retrieval of a first list of primary documents resulting from the first search query; monitoring a secondary document the first user interacts with, the secondary document whose identifier is referenced within the contents of a primary document or another secondary document; assigning a user interest score to the secondary document whose identifier is referenced within the contents of a primary document or another secondary document, and wherein the user interest score is based on measuring user interactions with the secondary document; adding the identifier of each such secondary document whose identifier is referenced within the contents of a primary document or another secondary document and the user interest score of each such secondary document, whose identifier is referenced within the contents of a primary or another secondary document, to a new list of relevant documents; persisting said new list of relevant documents to storage in a manner so that each such persisted said new list, submitted by said first user, is only accessible to said first user and is associated with said first search query; returning said persisted said new list of relevant documents as said list of relevant documents, in response to a second query, by said first user, if and only if, said second query matches said associated first query. | 1. A method for generating, by a monitoring program, a list of relevant documents, related to a first search query, comprising: tracking activities of a first user pursuant to retrieval of a first list of primary documents resulting from the first search query; monitoring a secondary document the first user interacts with, the secondary document whose identifier is referenced within the contents of a primary document or another secondary document; assigning a user interest score to the secondary document whose identifier is referenced within the contents of a primary document or another secondary document, and wherein the user interest score is based on measuring user interactions with the secondary document; adding the identifier of each such secondary document whose identifier is referenced within the contents of a primary document or another secondary document and the user interest score of each such secondary document, whose identifier is referenced within the contents of a primary or another secondary document, to a new list of relevant documents; persisting said new list of relevant documents to storage in a manner so that each such persisted said new list, submitted by said first user, is only accessible to said first user and is associated with said first search query; returning said persisted said new list of relevant documents as said list of relevant documents, in response to a second query, by said first user, if and only if, said second query matches said associated first query. 6. The method of claim 1 wherein the user interest score in the secondary document is based on cumulative actions taken by said first user each time said first user handles said secondary document pursuant to substantially a similar query. | 0.880857 |
9,087,106 | 12 | 13 | 12. A tangible, non-transitory processor-readable medium having processor-executable code encoded therein, which when executed by one or more processors, enables actions, comprising: for each user of a plurality of users accessing a user profile index to determine at least one reading interest of the user; gathering publishing data of the plurality of users from publicly available content generated by the plurality of users; indexing publishing interests of the plurality of users based on gathered publishing data from the plurality of users, such that the publishing interests include topics generated from key words in the publishing behavior information and latent semantic topics inferred from the publishing behavior information; performing based on the indexing, relevance matching to determine matching users from the plurality of users such that each matching user has at least one publishing interest that is relevant at least one reading interest of the user; ranking the matching users; based on the ranking, determining one or more top ranked matching users; and providing suggestions for a social recommendation for each of the one or more top ranked matching users to be made to the user, each of the suggestions for the top ranked matching users comprises respective representative publishing content pieces of each of the top ranked matching users. | 12. A tangible, non-transitory processor-readable medium having processor-executable code encoded therein, which when executed by one or more processors, enables actions, comprising: for each user of a plurality of users accessing a user profile index to determine at least one reading interest of the user; gathering publishing data of the plurality of users from publicly available content generated by the plurality of users; indexing publishing interests of the plurality of users based on gathered publishing data from the plurality of users, such that the publishing interests include topics generated from key words in the publishing behavior information and latent semantic topics inferred from the publishing behavior information; performing based on the indexing, relevance matching to determine matching users from the plurality of users such that each matching user has at least one publishing interest that is relevant at least one reading interest of the user; ranking the matching users; based on the ranking, determining one or more top ranked matching users; and providing suggestions for a social recommendation for each of the one or more top ranked matching users to be made to the user, each of the suggestions for the top ranked matching users comprises respective representative publishing content pieces of each of the top ranked matching users. 13. The tangible, non-transitory processor-readable medium of claim 12 , wherein ranking the matching users is done based on at least one of: freshness of published content of the matching user, popularity of the published content of the matching user, relevance of the published content of the matching user, expertise of the matching user, demographic information of the user, or at least one descriptive statistic of the user. | 0.5 |
8,549,394 | 10 | 15 | 10. A method for helping in a reading of an electronic message exchanged between multiple users, the method comprising the steps of: a chat room or instant message utility sending an electronic message between users; extracting a word from the electronic message sent to a particular user; acquiring history information on the word being extracted, wherein the history information includes a viewing of the word by the particular user, a usage of the word by the particular user, and a consultation of an electronic dictionary for the meaning of the word by the particular user; determining, based on the acquired history information, whether a meaning of the extracted word needs to be presented to the particular user on a display, wherein the determining is based on a criteria related to a viewing of the word by the particular user, a criteria related to a usage of the word by the particular user, and a criteria related to a consultation of an electronic dictionary for the meaning of the word by the particular user; and displaying the meaning of the word in a case in which the determining results in a determination that the meaning of the word needs to be presented to the user. | 10. A method for helping in a reading of an electronic message exchanged between multiple users, the method comprising the steps of: a chat room or instant message utility sending an electronic message between users; extracting a word from the electronic message sent to a particular user; acquiring history information on the word being extracted, wherein the history information includes a viewing of the word by the particular user, a usage of the word by the particular user, and a consultation of an electronic dictionary for the meaning of the word by the particular user; determining, based on the acquired history information, whether a meaning of the extracted word needs to be presented to the particular user on a display, wherein the determining is based on a criteria related to a viewing of the word by the particular user, a criteria related to a usage of the word by the particular user, and a criteria related to a consultation of an electronic dictionary for the meaning of the word by the particular user; and displaying the meaning of the word in a case in which the determining results in a determination that the meaning of the word needs to be presented to the user. 15. The method according to claim 10 , wherein the acquiring step acquires the history information on the usage of the word, and if the history information on the usage of the word meets a criterion that is related to the usage of the word and predetermined as a criterion for presuming that the particular user knows the meaning of the word, the determining step determines that the meaning of the word need not be presented to the particular user. | 0.737119 |
9,298,943 | 1 | 14 | 1. A system for controlling metadata associated with content items as directed by a user of an electronic device, the system comprising: a user interface comprising interface screens displayed on a display of the electronic device; an input mechanism on the electronic device, the input mechanism receiving user instructions through the user interface; a plurality of content items accessible by the electronic device, one or more of the plurality of content items having metadata associated therewith, the plurality of content items comprising original content items and modified content items; an overlay component that places a geolocation overlay indicator on each of the plurality of content items having associated geolocation metadata; a content selection component that displays one or more of the plurality of content items on the display of the electronic device, and enables selection of one or more of the plurality of displayed content items; the content selection component displays the geolocation overlay indicator with each content items having associated geolocation metadata; a plurality of content sharing mechanisms on the electronic device, each of the plurality of content sharing mechanisms for at least one of receiving content items and sending content items over a network accessible by the electronic device; a geotag profile accessible by the electronic device, the geotag profile including profile instructions regarding geolocation metadata control and being directed to at least one of the plurality of content sharing mechanisms; a sharing selection component for selecting a selected content item of the plurality of content items, and for selecting a selected content sharing mechanism of the plurality of content sharing mechanisms, the selected content item having selected content metadata associated therewith; a metadata modification component for modifying metadata associated with the plurality of content items including modifying the selected content metadata before sharing the selected content items, the metadata modification component selecting the geotag profile based on the selected content item and the selected content sharing mechanism, and modifying geolocation metadata of the selected content metadata in accordance with the profile instructions of the geotag profile when the geotag profile is selected; a sharing component for sharing a sharing version of the selected content item with a sharing version of the selected content metadata over a network accessible by the electronic device through the selected content sharing mechanism; wherein metadata associated with the original content items has not been modified by the metadata modification component and metadata associated with the modified content items has been modified by the metadata modification component, and wherein when the metadata modification component modifies selected content metadata before sharing a selected content item and the geotag profile is selected, the metadata modification component modifies the selected content metadata associated with the selected content item in accordance with the profile instructions of the geotag profile to generate the sharing version of the selected content metadata, and the metadata modification component does not modify the selected content metadata associated with the selected content item. | 1. A system for controlling metadata associated with content items as directed by a user of an electronic device, the system comprising: a user interface comprising interface screens displayed on a display of the electronic device; an input mechanism on the electronic device, the input mechanism receiving user instructions through the user interface; a plurality of content items accessible by the electronic device, one or more of the plurality of content items having metadata associated therewith, the plurality of content items comprising original content items and modified content items; an overlay component that places a geolocation overlay indicator on each of the plurality of content items having associated geolocation metadata; a content selection component that displays one or more of the plurality of content items on the display of the electronic device, and enables selection of one or more of the plurality of displayed content items; the content selection component displays the geolocation overlay indicator with each content items having associated geolocation metadata; a plurality of content sharing mechanisms on the electronic device, each of the plurality of content sharing mechanisms for at least one of receiving content items and sending content items over a network accessible by the electronic device; a geotag profile accessible by the electronic device, the geotag profile including profile instructions regarding geolocation metadata control and being directed to at least one of the plurality of content sharing mechanisms; a sharing selection component for selecting a selected content item of the plurality of content items, and for selecting a selected content sharing mechanism of the plurality of content sharing mechanisms, the selected content item having selected content metadata associated therewith; a metadata modification component for modifying metadata associated with the plurality of content items including modifying the selected content metadata before sharing the selected content items, the metadata modification component selecting the geotag profile based on the selected content item and the selected content sharing mechanism, and modifying geolocation metadata of the selected content metadata in accordance with the profile instructions of the geotag profile when the geotag profile is selected; a sharing component for sharing a sharing version of the selected content item with a sharing version of the selected content metadata over a network accessible by the electronic device through the selected content sharing mechanism; wherein metadata associated with the original content items has not been modified by the metadata modification component and metadata associated with the modified content items has been modified by the metadata modification component, and wherein when the metadata modification component modifies selected content metadata before sharing a selected content item and the geotag profile is selected, the metadata modification component modifies the selected content metadata associated with the selected content item in accordance with the profile instructions of the geotag profile to generate the sharing version of the selected content metadata, and the metadata modification component does not modify the selected content metadata associated with the selected content item. 14. The system of claim 1 , wherein when the selected content sharing mechanism is a text message, the metadata modification component generates the sharing version of the selected content metadata from the selected content metadata, and when the geotag profile is selected and the selected content metadata includes geolocation information the metadata modification component removes the geolocation information from the sharing version of the selected content metadata; and the sharing component prepares the sharing version of the selected content item and the sharing version of the selected content metadata for sending in a text message over a network. | 0.519708 |
8,547,329 | 4 | 5 | 4. The method of claim 3 , further comprising outputting an indication that the text output is a proposed spelling correction. | 4. The method of claim 3 , further comprising outputting an indication that the text output is a proposed spelling correction. 5. The method of claim 4 , further comprising outputting as the indication a visual indication that the text output is a proposed spelling correction. | 0.5 |
10,019,640 | 11 | 12 | 11. A system comprising: a communication interface configured to receive: a candidate license plate identification associated with an image of a vehicle proximate to a current toll collection point during a current toll event, and an identification confidence level associated with the candidate license plate identification; behavioral analysis circuitry coupled to the communication interface, the behavioral analysis circuitry configured to: perform a behavioral analysis of geospatial vehicle positioning data related to the candidate license plate identification to generate behavioral information; search for a related toll event occurring at a related toll collection point with respect to the current toll collection point and having a license plate identification matching the candidate license plate identification; determine a current travel time from a time difference between the current toll event and the related toll event; determine an average travel time between the current toll collection point and the related toll collection point; and determine a degree of difference between the current travel time and the average travel time; and probability evaluation circuitry configured to: determine an overall confidence level associated with the candidate license plate identification responsive to the candidate license plate identification, the identification confidence level, and the behavioral information; compare the overall confidence level to a minimum confidence threshold; and if the determined overall confidence level is above the minimum confidence threshold, control the communication interface to communicate the candidate license plate information as a correctly identified license plate identification to a transaction processing system to thereby facilitate billing and collection of a toll associated with the current toll collection point. | 11. A system comprising: a communication interface configured to receive: a candidate license plate identification associated with an image of a vehicle proximate to a current toll collection point during a current toll event, and an identification confidence level associated with the candidate license plate identification; behavioral analysis circuitry coupled to the communication interface, the behavioral analysis circuitry configured to: perform a behavioral analysis of geospatial vehicle positioning data related to the candidate license plate identification to generate behavioral information; search for a related toll event occurring at a related toll collection point with respect to the current toll collection point and having a license plate identification matching the candidate license plate identification; determine a current travel time from a time difference between the current toll event and the related toll event; determine an average travel time between the current toll collection point and the related toll collection point; and determine a degree of difference between the current travel time and the average travel time; and probability evaluation circuitry configured to: determine an overall confidence level associated with the candidate license plate identification responsive to the candidate license plate identification, the identification confidence level, and the behavioral information; compare the overall confidence level to a minimum confidence threshold; and if the determined overall confidence level is above the minimum confidence threshold, control the communication interface to communicate the candidate license plate information as a correctly identified license plate identification to a transaction processing system to thereby facilitate billing and collection of a toll associated with the current toll collection point. 12. The system of claim 11 wherein the probability evaluation circuitry further comprises a statistical model of random variables. | 0.921212 |
10,084,915 | 7 | 11 | 7. A non-transitory, computer-readable medium comprising computer-executable instructions for determining whether a call has reached a live party or a machine, that when executed, cause a call handler that is handling the call to: analyze a cadence of audio of the call; make a first determination that the call has reached the live party or the machine based on the cadence of the audio; receive an event from a speech analytics system analyzing the audio of the call to detect one or more keywords as a result of the speech analytics system detecting a particular keyword in the audio of the call; upon receiving the event, make a second determination that the call has reached the live party or the machine based on the event; and connect the call with a second live party so that the second live party can converse with the live party reached on the call in response to the first and second determinations indicating the call has reached the live party. | 7. A non-transitory, computer-readable medium comprising computer-executable instructions for determining whether a call has reached a live party or a machine, that when executed, cause a call handler that is handling the call to: analyze a cadence of audio of the call; make a first determination that the call has reached the live party or the machine based on the cadence of the audio; receive an event from a speech analytics system analyzing the audio of the call to detect one or more keywords as a result of the speech analytics system detecting a particular keyword in the audio of the call; upon receiving the event, make a second determination that the call has reached the live party or the machine based on the event; and connect the call with a second live party so that the second live party can converse with the live party reached on the call in response to the first and second determinations indicating the call has reached the live party. 11. The non-transitory, computer-readable medium of claim 7 , wherein the computer-executable instructions are configured to cause the call handler to have a message played over the call in response to the first determination indicating the call has reached the machine and the second determination indicating the call has reached the live party. | 0.603211 |
7,975,019 | 13 | 14 | 13. The method of claim 10 , wherein the web site is an affiliate web site that is registered in an affiliate marketing program of a merchant site that hosts the electronic catalog, and the link points to a product detail page of said electronic catalog, said link encoded with an affiliate identifier to enable tracking of user referrals. | 13. The method of claim 10 , wherein the web site is an affiliate web site that is registered in an affiliate marketing program of a merchant site that hosts the electronic catalog, and the link points to a product detail page of said electronic catalog, said link encoded with an affiliate identifier to enable tracking of user referrals. 14. The method of claim 13 , wherein the overlay display object, as added to the web page of the affiliate web site, provides functionality for a user to interactively browse and make purchases from said electronic catalog via communications with the content server. | 0.5 |
8,515,934 | 1 | 5 | 1. A computer-implemented method comprising: receiving a search query in a first language; receiving a plurality of search results responsive to the search query, wherein the search results comprise one or more first search results and a plurality of second search results, wherein each first result identifies a respective document in the first language and a corresponding respective document in a different second language, and wherein the second search results each identify a respective document in the first language; ordering the search results based on, at least, a respective number of documents identified by each of the search results; and providing the ordered search results in response to the search query. | 1. A computer-implemented method comprising: receiving a search query in a first language; receiving a plurality of search results responsive to the search query, wherein the search results comprise one or more first search results and a plurality of second search results, wherein each first result identifies a respective document in the first language and a corresponding respective document in a different second language, and wherein the second search results each identify a respective document in the first language; ordering the search results based on, at least, a respective number of documents identified by each of the search results; and providing the ordered search results in response to the search query. 5. The method of claim 1 , further comprising generating a visual alert for a particular first search result wherein the visual alert includes a snippet for the particular first search result's document in the second language. | 0.5 |
9,727,976 | 12 | 13 | 12. The method of claim 11 , wherein the search query comprises a graph template, the graph template having characteristics comprising: a first number of nodes of a first type; a second number of nodes of a second type; and a first number of edges connecting pairs of nodes; wherein identifying the feature of interest in the scene comprises identifying a subgraph of the GTS graph matching the characteristics of the graph template. | 12. The method of claim 11 , wherein the search query comprises a graph template, the graph template having characteristics comprising: a first number of nodes of a first type; a second number of nodes of a second type; and a first number of edges connecting pairs of nodes; wherein identifying the feature of interest in the scene comprises identifying a subgraph of the GTS graph matching the characteristics of the graph template. 13. The method of claim 12 , wherein nodes of the first type correspond to respective trajectories, the characteristics of the graph template further comprising a first edge connecting a node of the first type and a node of the second type, the first edge assigned data indicative of a distance relationship between the node of the first type and the node of the second type over a first window of time in the window of time. | 0.5 |
8,638,363 | 1 | 8 | 1. A system, comprising: a detection component configured to make a prediction that text is within proximity of a capture component based on proximity measurements from a proximity sub-component of the detection component and duration measurements related to the proximity measurements, wherein the prediction is based on a proximity and a minimum duration related to the proximity, and wherein the detection component is further configured to modify at least one of the proximity and the minimum duration based on the proximity measurements and the duration measurements; a device operation component, configured to generate information to modify a mode of operation in response to receiving the prediction that text is within proximity of the capture component based on the capture component being within the proximity to information to be captured for at least the minimum duration; the capture component, configured to capture an image of the information to be captured in response to receiving the information to modify the mode of operation; an identification component, wherein the identification component is configured to identify text within the captured image; and an action component, wherein the action component is programmed to perform an action associated with the identified text. | 1. A system, comprising: a detection component configured to make a prediction that text is within proximity of a capture component based on proximity measurements from a proximity sub-component of the detection component and duration measurements related to the proximity measurements, wherein the prediction is based on a proximity and a minimum duration related to the proximity, and wherein the detection component is further configured to modify at least one of the proximity and the minimum duration based on the proximity measurements and the duration measurements; a device operation component, configured to generate information to modify a mode of operation in response to receiving the prediction that text is within proximity of the capture component based on the capture component being within the proximity to information to be captured for at least the minimum duration; the capture component, configured to capture an image of the information to be captured in response to receiving the information to modify the mode of operation; an identification component, wherein the identification component is configured to identify text within the captured image; and an action component, wherein the action component is programmed to perform an action associated with the identified text. 8. The system of claim 1 , wherein the identification component is configured to identify at least one feature of text within the captured image. | 0.804582 |
7,546,242 | 10 | 11 | 10. Method of reproduction according to claim 1 ; wherein the reproduction of each of the documents representative of this group is performed sequentially during a determined period. | 10. Method of reproduction according to claim 1 ; wherein the reproduction of each of the documents representative of this group is performed sequentially during a determined period. 11. The method of reproduction according to claim 10 ; wherein the method comprises an introducing step of the determined period. | 0.5 |
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