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7,814,107 | 9 | 10 | 9. A computer system for determining a likelihood of a first and second document describing similar subject matter, the computer system comprising: a processor; and a memory; wherein the computer system is configured to: obtain a set of tokens for each of the first and second documents, wherein each set of tokens represents a series of characters found in its corresponding document; provide a matrix of token pairs, each token pair comprising a first token from the set of tokens corresponding to the first document and a second token from the set of tokens corresponding to the second document; generate a similarity score for each token pair in the matrix by: assigning each of the first token and the second token to one of a first type, a second type, or a third type based on the content of the tokens; setting the similarity score for the token pair to a floor value when the type of the first token is different from the type of the second token; setting the similarity score for the token pair based on a first calculation when the first token and the second token are of the first type; setting the similarity score for the token pair based on a second calculation different from the first calculation when the first token and the second token are of the second type; and setting the similarity score for the token pair based on a third calculation different from the first and second calculations when the first token and the second token are of the third type; identify those token pairs in the matrix with a similarity score above a threshold score and add the identified token pairs to a set of matched tokens; determine a similarity score for the first and second documents according to the scores of the token pairs in the set of matched tokens; and provide the determined similarity score as the likelihood of the first and second documents describing similar subject matter. | 9. A computer system for determining a likelihood of a first and second document describing similar subject matter, the computer system comprising: a processor; and a memory; wherein the computer system is configured to: obtain a set of tokens for each of the first and second documents, wherein each set of tokens represents a series of characters found in its corresponding document; provide a matrix of token pairs, each token pair comprising a first token from the set of tokens corresponding to the first document and a second token from the set of tokens corresponding to the second document; generate a similarity score for each token pair in the matrix by: assigning each of the first token and the second token to one of a first type, a second type, or a third type based on the content of the tokens; setting the similarity score for the token pair to a floor value when the type of the first token is different from the type of the second token; setting the similarity score for the token pair based on a first calculation when the first token and the second token are of the first type; setting the similarity score for the token pair based on a second calculation different from the first calculation when the first token and the second token are of the second type; and setting the similarity score for the token pair based on a third calculation different from the first and second calculations when the first token and the second token are of the third type; identify those token pairs in the matrix with a similarity score above a threshold score and add the identified token pairs to a set of matched tokens; determine a similarity score for the first and second documents according to the scores of the token pairs in the set of matched tokens; and provide the determined similarity score as the likelihood of the first and second documents describing similar subject matter. 10. The computer system of claim 9 , wherein the first type is an alphabetic type, the second type is an alpha-numeric type, and the third type is a numeric type. | 0.858392 |
8,532,333 | 10 | 16 | 10. A computer system, comprising: a non-transitory computer-readable storage medium comprising executable computer program code for: recognizing one or more text strings in each of a plurality of geo-tagged images, each of the plurality of geo-tagged images indicating a geographical location of its corresponding geo-tagged image, identifying one or more establishments near the geographical locations of the plurality of geo-tagged images, for each specific establishment of the one or more establishments: (i) extracting one or more phrases from information associated with the specific establishment, (ii) comparing the one or more text strings recognized in the plurality of geo-tagged images with the extracted one or more phrases to derive one or more matches, (iii) determining one or more image-establishment pairs based on the one or more matches, each image-establishment pair pairing a specific geo-tagged image with the specific establishment, and (iv) selecting a representative geo-tagged image for the specific establishment from among the plurality of geo-tagged images based on the one or more image-establishment pairs; and at least one processor for executing the executable computer program code. | 10. A computer system, comprising: a non-transitory computer-readable storage medium comprising executable computer program code for: recognizing one or more text strings in each of a plurality of geo-tagged images, each of the plurality of geo-tagged images indicating a geographical location of its corresponding geo-tagged image, identifying one or more establishments near the geographical locations of the plurality of geo-tagged images, for each specific establishment of the one or more establishments: (i) extracting one or more phrases from information associated with the specific establishment, (ii) comparing the one or more text strings recognized in the plurality of geo-tagged images with the extracted one or more phrases to derive one or more matches, (iii) determining one or more image-establishment pairs based on the one or more matches, each image-establishment pair pairing a specific geo-tagged image with the specific establishment, and (iv) selecting a representative geo-tagged image for the specific establishment from among the plurality of geo-tagged images based on the one or more image-establishment pairs; and at least one processor for executing the executable computer program code. 16. The computer system of claim 10 , wherein the identifying one or more establishments near the geographical locations of the plurality of geo-tagged images includes identifying establishments within a radius of the geographical location of each of the plurality of geo-tagged images. | 0.70021 |
8,456,679 | 1 | 7 | 1. A method for generating a remote job submission accelerator report, comprising: automatically generating a text representation with respect to a submission path and a spatial representation with respect to said text representation associated with said submission path; selecting said submission path via a panel menu in said multi-function device, wherein said selection is based on a policy governance application to render said text representation and said spatial representation in said network multi-function device; and generating an accelerator report based on said text representation and said spatial representation, wherein said accelerator report comprises a two-dimensional quick response code representative of a print job submission mechanism for rendering and further comprises information required to support an automated workflow, wherein said information comprises an Internet Protocol address and Uniform Resource Locator for automated submission of a job from a mobile communication device to said network multi-function device, to thereafter add said report to a cover page associated with said job, thereby enabling a client-less job submission with respect to said network multi-function device. | 1. A method for generating a remote job submission accelerator report, comprising: automatically generating a text representation with respect to a submission path and a spatial representation with respect to said text representation associated with said submission path; selecting said submission path via a panel menu in said multi-function device, wherein said selection is based on a policy governance application to render said text representation and said spatial representation in said network multi-function device; and generating an accelerator report based on said text representation and said spatial representation, wherein said accelerator report comprises a two-dimensional quick response code representative of a print job submission mechanism for rendering and further comprises information required to support an automated workflow, wherein said information comprises an Internet Protocol address and Uniform Resource Locator for automated submission of a job from a mobile communication device to said network multi-function device, to thereafter add said report to a cover page associated with said job, thereby enabling a client-less job submission with respect to said network multi-function device. 7. The method of claim 1 further comprising configuring said job submission path to comprise at least one of the following paths: a Web service; an electronic mail address; and a hot folder. | 0.590517 |
9,756,161 | 21 | 23 | 21. The control method according to claim 16 , wherein the creating of the phone number candidate group comprises: detecting a feature vector from the voice signal; and recognizing a phoneme string of the voice signal from an acoustic model according to the feature vector. | 21. The control method according to claim 16 , wherein the creating of the phone number candidate group comprises: detecting a feature vector from the voice signal; and recognizing a phoneme string of the voice signal from an acoustic model according to the feature vector. 23. The control method according to claim 21 , wherein the phone number candidate group has a degree of reliability that is higher than or equal to predetermined criteria with regard to the phoneme string. | 0.540359 |
8,930,817 | 1 | 2 | 1. A method for displaying photographs in a photographic slideshow, comprising: receiving with an electronic device contextual information; after the receiving: identifying with the electronic device at least one photograph that is associated with the received contextual information; and selecting with the electronic device at least one theme element that is associated with the received contextual information, after the identifying and after the selecting, generating with the electronic device the photographic slideshow, wherein the generated photographic slideshow comprises a first slideshow portion, and wherein the first slideshow portion comprises at least a portion of a first photograph, at least a portion of the identified at least one photograph, and the selected at least one theme element; and after the generating, displaying with the electronic device the first slideshow portion of the generated photographic slideshow by displaying each of the at least a portion of the first photograph, the at least a portion of the identified at least one photograph, and the selected at least one theme element, wherein during the displaying the first slideshow portion: the displayed at least a portion of the identified at least one photograph is within a boundary of the displayed at least one theme element; each of the displayed at least a portion of the identified at least one photograph and the displayed at least one theme element is at least partially overlaid on the displayed at least a portion of the first photograph; and each of the displayed at least a portion of the identified at least one photograph and the displayed at least one theme element moves relative to the displayed at least a portion of the first photograph. | 1. A method for displaying photographs in a photographic slideshow, comprising: receiving with an electronic device contextual information; after the receiving: identifying with the electronic device at least one photograph that is associated with the received contextual information; and selecting with the electronic device at least one theme element that is associated with the received contextual information, after the identifying and after the selecting, generating with the electronic device the photographic slideshow, wherein the generated photographic slideshow comprises a first slideshow portion, and wherein the first slideshow portion comprises at least a portion of a first photograph, at least a portion of the identified at least one photograph, and the selected at least one theme element; and after the generating, displaying with the electronic device the first slideshow portion of the generated photographic slideshow by displaying each of the at least a portion of the first photograph, the at least a portion of the identified at least one photograph, and the selected at least one theme element, wherein during the displaying the first slideshow portion: the displayed at least a portion of the identified at least one photograph is within a boundary of the displayed at least one theme element; each of the displayed at least a portion of the identified at least one photograph and the displayed at least one theme element is at least partially overlaid on the displayed at least a portion of the first photograph; and each of the displayed at least a portion of the identified at least one photograph and the displayed at least one theme element moves relative to the displayed at least a portion of the first photograph. 2. The method of claim 1 , wherein the receiving comprises receiving a user selection of the contextual information. | 0.766129 |
7,769,704 | 4 | 6 | 4. A non-transitory computer readable storage medium structured to store instructions executable by the processor to extract knowledge embedded in source code of an application an instructions when executed by the processor cause the processor to: receive the source code in a programming language; extract a plurality of knowledge elements from the source code based on predefined patterns; subdivide the knowledge elements using predefined decoding patterns; responsive to no predefined decoding pattern matching a knowledge element, create a decoding pattern using fuzzy rules and subdividing the knowledge element using the new decoding pattern; determine knowledge attributes for the extracted knowledge elements based on target specification attributes of a desired target architecture; generate an abstract representation of the source code in a format appropriate for the desired target architecture independent of the programming language of the source code, wherein the abstract representation includes the plurality of knowledge elements hatch a dynamic pattern when no predefined pattern matches a part of the source code, wherein the dynamic pattern is created using fuzzy-neural rules and dynamic rules and is determined to be stored in a store; and identify the knowledge attributes for the included knowledge elements in the abstract representation. | 4. A non-transitory computer readable storage medium structured to store instructions executable by the processor to extract knowledge embedded in source code of an application an instructions when executed by the processor cause the processor to: receive the source code in a programming language; extract a plurality of knowledge elements from the source code based on predefined patterns; subdivide the knowledge elements using predefined decoding patterns; responsive to no predefined decoding pattern matching a knowledge element, create a decoding pattern using fuzzy rules and subdividing the knowledge element using the new decoding pattern; determine knowledge attributes for the extracted knowledge elements based on target specification attributes of a desired target architecture; generate an abstract representation of the source code in a format appropriate for the desired target architecture independent of the programming language of the source code, wherein the abstract representation includes the plurality of knowledge elements hatch a dynamic pattern when no predefined pattern matches a part of the source code, wherein the dynamic pattern is created using fuzzy-neural rules and dynamic rules and is determined to be stored in a store; and identify the knowledge attributes for the included knowledge elements in the abstract representation. 6. The non-transitory computer readable storage medium of claim 4 , wherein each of the decoding patterns comprises a predefined pattern or a dynamic pattern. | 0.696154 |
5,488,727 | 1 | 2 | 1. A method, to be practiced at compile time by a data handling system that supports multimethod function selection on typed data, including subtypes with multiple inheritance, for enabling static-type checking to be performed at run time for overloaded functions, wherein said system includes (i) a set of type definitions, including specification of subtype relationships, (ii) function definitions referring to at least one of the type definitions, each function definition including a definition of arguments, including an argument order and argument positions, and (iii) precedence rules which, in combination with the function argument order, define an ordering of the confusable function instances, for a given set of arguments, the method comprising the steps of: (a) creating from said type definitions a first data structure for representing subtype relationships between data types, the subtype relationships including levels of specificity, such that, within a given subtype relation for a given set of the data types, there is a maximal static argument type which has a lowest level of specificity; (b) creating from said first data structure and said function definitions a partitioning of function instances into confusable sets; (c) ordering the function instances within each confusable set; (d) verifying consistency among the ordered function instances resulting from said step of ordering; (e) identifying any consistency errors with respect to said ordered function instances; (f) signaling an error condition upon the identification of any such consistency error; (g) extracting, for each confusable set, information as the maximal static argument types of the functions are for each of the argument positions; and identifying confusable sets of function instances as confusable sets which potentially contain all functions applicable to the function invocation, the applicable functions having arguments, the arguments having argument types which are supertypes or subtypes of the compile time argument types of the function invocation; whereby, one of the applicable functions is chosen for execution at run time, in accordance with actual types of the function arguments. | 1. A method, to be practiced at compile time by a data handling system that supports multimethod function selection on typed data, including subtypes with multiple inheritance, for enabling static-type checking to be performed at run time for overloaded functions, wherein said system includes (i) a set of type definitions, including specification of subtype relationships, (ii) function definitions referring to at least one of the type definitions, each function definition including a definition of arguments, including an argument order and argument positions, and (iii) precedence rules which, in combination with the function argument order, define an ordering of the confusable function instances, for a given set of arguments, the method comprising the steps of: (a) creating from said type definitions a first data structure for representing subtype relationships between data types, the subtype relationships including levels of specificity, such that, within a given subtype relation for a given set of the data types, there is a maximal static argument type which has a lowest level of specificity; (b) creating from said first data structure and said function definitions a partitioning of function instances into confusable sets; (c) ordering the function instances within each confusable set; (d) verifying consistency among the ordered function instances resulting from said step of ordering; (e) identifying any consistency errors with respect to said ordered function instances; (f) signaling an error condition upon the identification of any such consistency error; (g) extracting, for each confusable set, information as the maximal static argument types of the functions are for each of the argument positions; and identifying confusable sets of function instances as confusable sets which potentially contain all functions applicable to the function invocation, the applicable functions having arguments, the arguments having argument types which are supertypes or subtypes of the compile time argument types of the function invocation; whereby, one of the applicable functions is chosen for execution at run time, in accordance with actual types of the function arguments. 2. A method as set forth in claim 1, further comprising the step of storing said first data structure, the ordered function instances for each confusable set, and the extracted maximal type information. | 0.70977 |
9,141,853 | 11 | 12 | 11. The method of claim 10 , wherein using the extraction field template to identify the set of candidate prior blocks and the set of candidate post blocks comprises: searching the digital real estate document for a select token, wherein the select token is selected from a set of tokens associated with the specific field type and the set of tokens is from the extraction field template; identifying an example prior block or an example post block in the extraction field template that contains the select token; and adding the example prior block to the set of candidate prior blocks or adding the example post block to the set of candidate post blocks. | 11. The method of claim 10 , wherein using the extraction field template to identify the set of candidate prior blocks and the set of candidate post blocks comprises: searching the digital real estate document for a select token, wherein the select token is selected from a set of tokens associated with the specific field type and the set of tokens is from the extraction field template; identifying an example prior block or an example post block in the extraction field template that contains the select token; and adding the example prior block to the set of candidate prior blocks or adding the example post block to the set of candidate post blocks. 12. The method of claim 11 , wherein the example prior block is used to identify in the digital real estate document a candidate prior block, and wherein the example post block is used to identify in the digital real estate document a candidate post block. | 0.5 |
8,601,578 | 1 | 4 | 1. An apparatus for identifying potentially suspicious business listings for moderation, the apparatus comprising: a memory operative to store: a business listing database comprising a plurality of business listings; and a plurality of business listing configuration rules, each business listing configuration rule establishing whether a business listing is to be treated as a suspicious business listing; and a processor in communication with the memory, the processor being operative to: evaluate a selected business listing from the plurality of business listings with the plurality of business listing configuration rules; determine whether the selected business listing complies with a selected one of the plurality of business listing configuration rules, wherein: the selected business listing configuration rule comprises an authoritative source location; the authoritative source location identifies a trusted source of business information; and the processor is further operative to determine that the selected business listing does not comply with the selected business listing configuration rule when the selected business listing does not include the authoritative source location identified by the selected business listing configuration rule; identify the selected business listing as a potentially suspicious business listing when the business listing does not comply with the selected one of the plurality of the business listing configuration rules; assign the selected business listing a new business listing problem when the business listing is identified as being a potentially suspicious business listing but has not been previously assigned a business listing problem; and prioritize the selected business listing for moderation based on the assigned business listing problem to the selected business listing. | 1. An apparatus for identifying potentially suspicious business listings for moderation, the apparatus comprising: a memory operative to store: a business listing database comprising a plurality of business listings; and a plurality of business listing configuration rules, each business listing configuration rule establishing whether a business listing is to be treated as a suspicious business listing; and a processor in communication with the memory, the processor being operative to: evaluate a selected business listing from the plurality of business listings with the plurality of business listing configuration rules; determine whether the selected business listing complies with a selected one of the plurality of business listing configuration rules, wherein: the selected business listing configuration rule comprises an authoritative source location; the authoritative source location identifies a trusted source of business information; and the processor is further operative to determine that the selected business listing does not comply with the selected business listing configuration rule when the selected business listing does not include the authoritative source location identified by the selected business listing configuration rule; identify the selected business listing as a potentially suspicious business listing when the business listing does not comply with the selected one of the plurality of the business listing configuration rules; assign the selected business listing a new business listing problem when the business listing is identified as being a potentially suspicious business listing but has not been previously assigned a business listing problem; and prioritize the selected business listing for moderation based on the assigned business listing problem to the selected business listing. 4. The apparatus of claim 1 , wherein the selected one of the plurality of business listing configuration rules comprises a business matching expression for matching a business listing; and the processor is further operative to determine that the selected business listing is to comply with the selected business listing configuration rule when the selected business listing matches the business matching expression of the selected business listing configuration rule. | 0.597938 |
7,747,044 | 19 | 20 | 19. A system for performing multi-biometric fusion, comprising: means for configuring a Bayesian Belief Network (BBN) biometric fusion engine to receive biometric scoring and quality information regarding one or more subjects; means for computing parametric statistical conditional distributions corresponding to said biometric and quality information received by said BBN; means for computing, using said BBN, a probability of match and a global quality estimate for said biometric scoring and quality information based on said computed parametric statistical conditional distributions; and means for outputting from said BBN said computed probability of match and global quality estimate. | 19. A system for performing multi-biometric fusion, comprising: means for configuring a Bayesian Belief Network (BBN) biometric fusion engine to receive biometric scoring and quality information regarding one or more subjects; means for computing parametric statistical conditional distributions corresponding to said biometric and quality information received by said BBN; means for computing, using said BBN, a probability of match and a global quality estimate for said biometric scoring and quality information based on said computed parametric statistical conditional distributions; and means for outputting from said BBN said computed probability of match and global quality estimate. 20. The system of claim 19 , wherein said biometric scoring and quality information regarding one or more subjects comprises, for each subject: a match/no-match score for a first measured biometric characteristic; a quality value for said first measured biometric characteristic; a match/no-match score for a second measured biometric characteristic; and a quality value for said second measured biometric characteristic. | 0.5 |
8,521,845 | 1 | 4 | 1. A method of resolving a registered multilingual domain name, the method comprising: receiving, at a primary name server, a request to resolve the registered multilingual domain name that is identified by a sequence of numeric values, wherein the request that was received from a Web browser of a user is based on a specified URL that contains the domain name; determining that the primary name server is unable to identify, in a zone data file of the primary name server, an IP address associated with the sequence of numeric values; selecting a default IP address in response to a failure to identify an associated IP address, the default IP address corresponding to a multilingual domain name server that is able to resolve requests for domain names in multiple languages; determining appropriate response information for the multilingual domain name; and providing an indication of the appropriate response information to the Web browser of the user in response to the request. | 1. A method of resolving a registered multilingual domain name, the method comprising: receiving, at a primary name server, a request to resolve the registered multilingual domain name that is identified by a sequence of numeric values, wherein the request that was received from a Web browser of a user is based on a specified URL that contains the domain name; determining that the primary name server is unable to identify, in a zone data file of the primary name server, an IP address associated with the sequence of numeric values; selecting a default IP address in response to a failure to identify an associated IP address, the default IP address corresponding to a multilingual domain name server that is able to resolve requests for domain names in multiple languages; determining appropriate response information for the multilingual domain name; and providing an indication of the appropriate response information to the Web browser of the user in response to the request. 4. The method of claim 1 , wherein the response information that was determined includes an IP address corresponding to the multilingual domain name server that is configured to resolve requests that specify the multilingual domain name and respond in an appropriate manner. | 0.578462 |
9,208,776 | 12 | 15 | 12. The system of claim 11 , wherein the retrieved information describing media is a list of actors, directors, composers, titles, and locations. | 12. The system of claim 11 , wherein the retrieved information describing media is a list of actors, directors, composers, titles, and locations. 15. The system of claim 12 , wherein the graph further models relative popularity of each piece of information in the list. | 0.775547 |
7,711,573 | 423 | 424 | 423. The computer program product of claim 422 , wherein a context for each said at least one implied skill or experience-related phrase is the context of the implying said at least one skill or experience-related phrase. | 423. The computer program product of claim 422 , wherein a context for each said at least one implied skill or experience-related phrase is the context of the implying said at least one skill or experience-related phrase. 424. The computer program product of claim 423 , the computer readable medium further storing: program code for setting the term of experience to zero when the experience range is zero; program code for determining a start time for the experience range when the experience range is greater than zero; program code for determining an end time for the experience range when the experience range is greater than zero; program code for computing a time difference between the start time and the end time when the experience range is greater than zero; and program code for setting the term of experience to the time difference when the experience range is greater than zero, wherein the term of experience is rounded down to a unit of time. | 0.5 |
9,837,081 | 1 | 4 | 1. A computing device comprising: a processing unit; memory; and one or more microphones; the computing device configured with a voice-controlled digital personal assistant to perform operations for discovering capabilities of third-party voice-enabled resources, the operations comprising: receiving, via the one or more microphones, a digital voice input generated by a user; performing natural language processing using the digital voice input to determine a user voice request, wherein the user voice request is a request for available third-party voice-enabled resources installed on the computing device that are capable of performing a task; identifying one or more third-party voice-enabled resources that are capable of performing the task using voice input, wherein the one or more third-party voice-enabled resources are identified using a data structure that defines tasks supported by available third-party voice-enabled resources using voice input, wherein the data structure comprises: information identifying voice commands supported by the available third-party voice-enabled resources; information identifying voice command variations supported by the available third-party voice-enabled resources that define variations of user voice input that will perform the voice command, wherein at least one of the voice commands supports a plurality of different voice command variations; and information identifying voice command examples supported by the available third-party voice-enabled resources, wherein the one or more voice command examples are specific examples of user voice input that, if spoken by the user, will activate the voice command, wherein at least one of the voice commands has a plurality of different voice command examples that activate the voice command; providing a response to the user identifying the one or more third-party voice-enabled resources that are capable of performing the task; receiving a user-initiated command, wherein the user-initiated command identifies a specific third-party voice-enabled application from the one or more third-party voice-enabled resources, wherein the user-initiated command instructs the voice-controlled digital personal assistant to delete a voice command of the specific third-party voice-enabled application from the data structure, and to delete all of the voice command's corresponding voice command variations from the data structure that are associated with the voice command in the data structure, wherein the deleted voice command, and corresponding voice command variations, cannot be performed by user voice input; and performing the user-initiated command to delete the voice command of the specific third-party voice-enabled application from the data structure, and to delete all of the voice command's corresponding voice command variations from the data structure that are associated with the voice command in the data structure. | 1. A computing device comprising: a processing unit; memory; and one or more microphones; the computing device configured with a voice-controlled digital personal assistant to perform operations for discovering capabilities of third-party voice-enabled resources, the operations comprising: receiving, via the one or more microphones, a digital voice input generated by a user; performing natural language processing using the digital voice input to determine a user voice request, wherein the user voice request is a request for available third-party voice-enabled resources installed on the computing device that are capable of performing a task; identifying one or more third-party voice-enabled resources that are capable of performing the task using voice input, wherein the one or more third-party voice-enabled resources are identified using a data structure that defines tasks supported by available third-party voice-enabled resources using voice input, wherein the data structure comprises: information identifying voice commands supported by the available third-party voice-enabled resources; information identifying voice command variations supported by the available third-party voice-enabled resources that define variations of user voice input that will perform the voice command, wherein at least one of the voice commands supports a plurality of different voice command variations; and information identifying voice command examples supported by the available third-party voice-enabled resources, wherein the one or more voice command examples are specific examples of user voice input that, if spoken by the user, will activate the voice command, wherein at least one of the voice commands has a plurality of different voice command examples that activate the voice command; providing a response to the user identifying the one or more third-party voice-enabled resources that are capable of performing the task; receiving a user-initiated command, wherein the user-initiated command identifies a specific third-party voice-enabled application from the one or more third-party voice-enabled resources, wherein the user-initiated command instructs the voice-controlled digital personal assistant to delete a voice command of the specific third-party voice-enabled application from the data structure, and to delete all of the voice command's corresponding voice command variations from the data structure that are associated with the voice command in the data structure, wherein the deleted voice command, and corresponding voice command variations, cannot be performed by user voice input; and performing the user-initiated command to delete the voice command of the specific third-party voice-enabled application from the data structure, and to delete all of the voice command's corresponding voice command variations from the data structure that are associated with the voice command in the data structure. 4. The computing device of claim 1 wherein providing the response to the user comprises, for each of the one or more third-party voice-enabled resources that are capable of performing the task: displaying an indication of at least one voice command variation supported by the third-party voice-enabled resource that will perform the task; and displaying an indication of at least one voice command example for performing the task. | 0.5 |
8,395,705 | 14 | 15 | 14. The method according to claim 10 , wherein the external device includes a plurality of external devices connected to the TV. | 14. The method according to claim 10 , wherein the external device includes a plurality of external devices connected to the TV. 15. The method according to claim 14 , wherein the plurality of external devices are connected to the TV through a switch, the switch sequentially connecting the plurality of external devices to the TV. | 0.5 |
7,646,940 | 13 | 14 | 13. The method of claim 12 , wherein featurizing the input ink comprises: splitting the input ink into a plurality of segments; determining segments features based on the plurality of segments; and classifying the stroke features to mitigate entropy and variance to create a membership matrix for the input ink. | 13. The method of claim 12 , wherein featurizing the input ink comprises: splitting the input ink into a plurality of segments; determining segments features based on the plurality of segments; and classifying the stroke features to mitigate entropy and variance to create a membership matrix for the input ink. 14. The method of claim 13 further comprises creating a plurality of distorted versions of the input ink and creating membership matrices for the distorted versions. | 0.5 |
8,380,511 | 8 | 9 | 8. The system of claim 7 wherein the categorizer is configured to use a means for determining a category corresponding to said accepted statement based, at least in part, on said assigned lexical chaining confidence scores between said created word pairs as obtained from said database. | 8. The system of claim 7 wherein the categorizer is configured to use a means for determining a category corresponding to said accepted statement based, at least in part, on said assigned lexical chaining confidence scores between said created word pairs as obtained from said database. 9. The system of claim 8 further comprising the means for determining a category corresponding to said accepted statement based, at least in part, on said assigned lexical chaining confidence scores between said created word pairs as obtained from said database. | 0.5 |
6,119,114 | 31 | 32 | 31. The system of claim 29, wherein said ranking means comprises binary search means for identifying a first training document and a second training document having absolute relevance scores above and below said absolute relevance score of said newly-received document. | 31. The system of claim 29, wherein said ranking means comprises binary search means for identifying a first training document and a second training document having absolute relevance scores above and below said absolute relevance score of said newly-received document. 32. The system of claim 31, wherein said sorted list includes a most relevant document having an absolute relevance score higher than said absolute relevance scores of all other training documents in said sorted list and a least relevant document having an absolute relevance score lower than said absolute relevance scores of all other training documents in said sorted list, and wherein said binary search means comprises comparison means for comparing said absolute relevance score of said newly-received document with a statistical average of said absolute relevance scores of said most relevant document and said least relevant document. | 0.5 |
7,885,972 | 15 | 17 | 15. The method of claim 1 , all the limitations of which are incorporated herein by reference, wherein for each of said data attributes in said user query, said tagging process comprises checking the data attribute for grouping candidacy and for any available user defined ranges when no information is input as to how said data attribute is to be treated. | 15. The method of claim 1 , all the limitations of which are incorporated herein by reference, wherein for each of said data attributes in said user query, said tagging process comprises checking the data attribute for grouping candidacy and for any available user defined ranges when no information is input as to how said data attribute is to be treated. 17. The method of claim 15 , all the limitations of which are incorporated herein by reference, further comprising tagging said data attribute as a measure with default statistics when the checking process results in no identification of any of said grouping candidacy and said any available user defined ranges. | 0.5 |
8,886,520 | 3 | 33 | 3. The apparatus of claim 1 wherein the processor is further configured to (1) receive source data relating to a subject, (2) compute a plurality of derived features based at least in part on the received source data, wherein the data processed by the processing operation comprises the source data and the derived features, and (3) generate an evaluation indicator indicative of whether a narrative story relating to the processed data that incorporates a story angle of the angle set data structure whose applicability conditions were satisfied by the processed data is to be generated. | 3. The apparatus of claim 1 wherein the processor is further configured to (1) receive source data relating to a subject, (2) compute a plurality of derived features based at least in part on the received source data, wherein the data processed by the processing operation comprises the source data and the derived features, and (3) generate an evaluation indicator indicative of whether a narrative story relating to the processed data that incorporates a story angle of the angle set data structure whose applicability conditions were satisfied by the processed data is to be generated. 33. The apparatus of claim 3 wherein the processor is further configured to communicate the evaluation indicator to a remote processor. | 0.912565 |
8,706,475 | 11 | 14 | 11. An apparatus for identifying a table of contents in a document, the apparatus comprising: a computer programmed to perform a method including deriving an ordered sequence of text fragments from the document and selecting a table of contents as a contiguous sub-sequence of the ordered sequence of text fragments wherein the selecting employs the criteria: (i) entries defined by text fragments of the table of contents each have a link to a target text fragment having textual similarity with the entry, (ii) no target text fragment lies within the table of contents, and (iii) the target text fragments have an ascending ordering corresponding to an ascending ordering of the entries defining the target text fragments. | 11. An apparatus for identifying a table of contents in a document, the apparatus comprising: a computer programmed to perform a method including deriving an ordered sequence of text fragments from the document and selecting a table of contents as a contiguous sub-sequence of the ordered sequence of text fragments wherein the selecting employs the criteria: (i) entries defined by text fragments of the table of contents each have a link to a target text fragment having textual similarity with the entry, (ii) no target text fragment lies within the table of contents, and (iii) the target text fragments have an ascending ordering corresponding to an ascending ordering of the entries defining the target text fragments. 14. The apparatus as set forth in claim 11 , wherein the selecting of a table of contents includes: determining a plurality of textual similarity links associating pairs of text fragments, at least some text fragments being included in more than one link; determining a plurality of candidate tables of contents each defined by a contiguous sub-sequence of the ordered sequence of text fragments and each having at least one combination of links satisfying criteria (i), (ii), (iii); ranking each candidate table of contents based on the textual similarity links having source text fragments contained in the candidate table of contents; choosing the highest ranked candidate tables of contents as the table of contents; and optimizing the plurality of textual similarity links having source text fragments contained in the table of contents to select no more than a single link for each entry, the optimizing satisfying criteria (i), (ii), and (iii). | 0.5 |
7,849,032 | 8 | 9 | 8. A computer implemented system for performing training of a neural network data mining model, comprising: a processor operable to execute computer program instructions; and a memory operable to store computer program instructions executable by the processor, the computer program instructions for performing the steps of: a) providing a training dataset to a neural network for training an untrained neural network data mining model, the training dataset comprising a plurality of rows of data, wherein the neural network data mining model is trained by: b) selecting a row of data from the training dataset for performing training processing on the neural network data mining model; c) computing an estimate of a gradient or cost function of the neural network data mining model based on the selected row of data, wherein the cost function accounts for the cost of various nodal transitions; d) determining whether the gradient or cost function of the neural network data mining model has converged using the selected row of data, based on the computed estimate of the gradient or cost function of the neural network data mining model, wherein the computing an estimate is performed before the determining; e) repeating steps b)-d) using another row of data, if the gradient or cost function of the neural network data mining model has not converged; and f) updating weights of the neural network data mining model if the gradient or cost function of the neural network data mining model has converged and providing the number of rows of data that were used for performing training processing on the neural network data mining model, wherein the number of rows that were used is a subset of the total number of rows in the training dataset and wherein the neural network data mining model uses less than the entire training dataset to train the neural network data mining model; and g) performing additional training processing to the neural network data mining model using the training dataset, wherein the additional training processing is performed using a number of rows of data equal to the provided number of rows of data. | 8. A computer implemented system for performing training of a neural network data mining model, comprising: a processor operable to execute computer program instructions; and a memory operable to store computer program instructions executable by the processor, the computer program instructions for performing the steps of: a) providing a training dataset to a neural network for training an untrained neural network data mining model, the training dataset comprising a plurality of rows of data, wherein the neural network data mining model is trained by: b) selecting a row of data from the training dataset for performing training processing on the neural network data mining model; c) computing an estimate of a gradient or cost function of the neural network data mining model based on the selected row of data, wherein the cost function accounts for the cost of various nodal transitions; d) determining whether the gradient or cost function of the neural network data mining model has converged using the selected row of data, based on the computed estimate of the gradient or cost function of the neural network data mining model, wherein the computing an estimate is performed before the determining; e) repeating steps b)-d) using another row of data, if the gradient or cost function of the neural network data mining model has not converged; and f) updating weights of the neural network data mining model if the gradient or cost function of the neural network data mining model has converged and providing the number of rows of data that were used for performing training processing on the neural network data mining model, wherein the number of rows that were used is a subset of the total number of rows in the training dataset and wherein the neural network data mining model uses less than the entire training dataset to train the neural network data mining model; and g) performing additional training processing to the neural network data mining model using the training dataset, wherein the additional training processing is performed using a number of rows of data equal to the provided number of rows of data. 9. The system of claim 8 , wherein the selecting step comprises the step of: randomly selecting the row of data from the training dataset for performing training processing on the neural network data mining model. | 0.608456 |
8,804,921 | 4 | 6 | 4. The system according to claim 1 , wherein said browser is supported by Call Control eXtensible Markup Language (CCXML) and Voice eXtensible Markup Language (VXML) applications. | 4. The system according to claim 1 , wherein said browser is supported by Call Control eXtensible Markup Language (CCXML) and Voice eXtensible Markup Language (VXML) applications. 6. The system according to claim 4 , wherein said browser allows said multiple users to create applications and make edits and changes by navigating voice prompts. | 0.5 |
9,369,488 | 8 | 13 | 8. Apparatus comprising: a processor; and computer memory holding computer program instructions executed by the processor to identify a violation of a policy defined by a terms of use document that defines one or more permissible actions by a user using a computing entity, the computing entity being the apparatus, the computer program instructions comprising: code to detect an action associated with the computing entity; code to train a natural language processing (NLP)-based question and answer (Q&A) system to understand the terms of use document; code to implement a policy management application or functionality designed to interact with said natural language processing (NLP)-based question and answer (Q&A) system to identify a violation of said terms of use document; code to convert the action into a natural text query; code to provide the natural text query for analysis to determine whether the action constitutes a policy violation of the terms of use document because the action detected is not one of the permissible actions, the determination being made by a natural language comparison of the natural text query against one or more terms of use that define the policy; code to receive a response to the natural text query; and code to take a policy enforcement action based on the response that limits the computing entity's functionality. | 8. Apparatus comprising: a processor; and computer memory holding computer program instructions executed by the processor to identify a violation of a policy defined by a terms of use document that defines one or more permissible actions by a user using a computing entity, the computing entity being the apparatus, the computer program instructions comprising: code to detect an action associated with the computing entity; code to train a natural language processing (NLP)-based question and answer (Q&A) system to understand the terms of use document; code to implement a policy management application or functionality designed to interact with said natural language processing (NLP)-based question and answer (Q&A) system to identify a violation of said terms of use document; code to convert the action into a natural text query; code to provide the natural text query for analysis to determine whether the action constitutes a policy violation of the terms of use document because the action detected is not one of the permissible actions, the determination being made by a natural language comparison of the natural text query against one or more terms of use that define the policy; code to receive a response to the natural text query; and code to take a policy enforcement action based on the response that limits the computing entity's functionality. 13. The apparatus as described in claim 8 wherein the response to the natural text query includes information describing the policy violation. | 0.81016 |
8,081,824 | 13 | 14 | 13. The computer-readable storage device of claim 9 wherein the transform is a discrete cosine transform and the transformed coefficients do not include a DC coefficient. | 13. The computer-readable storage device of claim 9 wherein the transform is a discrete cosine transform and the transformed coefficients do not include a DC coefficient. 14. The computer-readable storage device of claim 13 wherein the transformed coefficients are selected in a zigzag pattern. | 0.5 |
8,661,046 | 1 | 2 | 1. A method for inferring activity-related context information from a message, comprising: scanning, by a computer, for a keyword in the message, wherein the keyword is associated with an activity category in a content database; determining that the keyword indicates the associated activity category; inferring message-related context information from the keyword in the message; and recommending an activity in the activity category based on the inferred message-related context information, wherein recommending the activity involves: identifying one or more content items associated with the keyword, wherein each content item corresponds to a recommendable activity; generating a combined model based on the message-related context information, wherein the combined model includes an activity model for one or more activities associated with the message-related context information, and includes a user preference model for the user; scoring the one or more content items using at least the activity model and the user preference model of the combined model; and returning a content item associated with a top score. | 1. A method for inferring activity-related context information from a message, comprising: scanning, by a computer, for a keyword in the message, wherein the keyword is associated with an activity category in a content database; determining that the keyword indicates the associated activity category; inferring message-related context information from the keyword in the message; and recommending an activity in the activity category based on the inferred message-related context information, wherein recommending the activity involves: identifying one or more content items associated with the keyword, wherein each content item corresponds to a recommendable activity; generating a combined model based on the message-related context information, wherein the combined model includes an activity model for one or more activities associated with the message-related context information, and includes a user preference model for the user; scoring the one or more content items using at least the activity model and the user preference model of the combined model; and returning a content item associated with a top score. 2. The method of claim 1 , wherein scanning for the keyword in the message involves using the content database for guidance and looking for surrounding text which indicates the presence of the activity-related keywords in the message. | 0.622581 |
8,909,594 | 12 | 13 | 12. The system of claim 8 , the operations further comprising identifying the correspondence between the search query and the aspect of the good or service and the correspondence between the search query and the value of the aspect based on a keyword included in the search query. | 12. The system of claim 8 , the operations further comprising identifying the correspondence between the search query and the aspect of the good or service and the correspondence between the search query and the value of the aspect based on a keyword included in the search query. 13. The system of claim 12 , wherein the data item pertaining to the listing of the good or service does not include the keyword. | 0.5 |
8,538,752 | 14 | 15 | 14. A non-transitory computer readable medium storing a software program, that when executed by a computer, causes the computer to perform operations, the operations comprising: obtaining an utterance in speech data, wherein the utterance comprises an actual word string; processing the utterance for generating an interpretation of the actual word string; processing the utterance to identify an utterance frame; and calculating a prediction of a word accuracy associated with the interpretation based on a stationary signal-to-noise ratio and a non-stationary signal-to-noise ratio, wherein the stationary signal-to-noise ratio and the non-stationary signal-to-noise ratio are determined according to a frame energy associated with the utterance frame, and wherein the calculating comprises: computing the stationary signal-to-noise ratio for the utterance; computing the non-stationary signal-to-noise ratio for the utterance; and computing the prediction of the word accuracy associated with the interpretation using the stationary signal-to-noise ratio and the non-stationary signal-to-noise ratio. | 14. A non-transitory computer readable medium storing a software program, that when executed by a computer, causes the computer to perform operations, the operations comprising: obtaining an utterance in speech data, wherein the utterance comprises an actual word string; processing the utterance for generating an interpretation of the actual word string; processing the utterance to identify an utterance frame; and calculating a prediction of a word accuracy associated with the interpretation based on a stationary signal-to-noise ratio and a non-stationary signal-to-noise ratio, wherein the stationary signal-to-noise ratio and the non-stationary signal-to-noise ratio are determined according to a frame energy associated with the utterance frame, and wherein the calculating comprises: computing the stationary signal-to-noise ratio for the utterance; computing the non-stationary signal-to-noise ratio for the utterance; and computing the prediction of the word accuracy associated with the interpretation using the stationary signal-to-noise ratio and the non-stationary signal-to-noise ratio. 15. The non-transitory computer readable medium of claim 14 , wherein the processing the utterance to generate the interpretation of the actual word string, comprises: obtaining an acoustic model; obtaining a language model; and applying the acoustic model and the language model to the utterance for generating a predicted word string. | 0.76 |
9,003,318 | 12 | 15 | 12. A computer implemented method, comprising: receiving from a user through a user interface, an adjustment input to move an icon on a screen to a position in which the icon is touching one or more other icons to form a first grouping, the first grouping comprises an icon of a first data indication predicate touching an icon of a first action predicate, wherein the first data indication predicate is positive or negative based on a position of a game character relative to an object in a computer game; receiving from the user through the user interface, another adjustment input to move another icon on the screen to a position in which the another icon is touching one or more other icons to form a second grouping separate from the first grouping, the second grouping comprises an icon of a second data indication predicate touching an icon of a second action predicate, the second data indication predicate is positive or negative based on the position of the game character relative to the object in the computer game, the second data indication predicate is positive when the first data indication predicate is negative, and negative when the first data indication predicate is positive; altering a declarative specification for controlling the game character in the computer game as a function of the first grouping and the second grouping, wherein: (a) the first grouping is a logical implication, based on a proximity of the icon of the first data indication predicate to the icon of the first action predicate, in which the game character performs a respective action identified by the icon of the first action predicate when the first data indication predicate is positive and (b) the second grouping is a logical implication, based on a proximity of the icon of the second data indication predicate to the icon of the second action predicate, in which the game character performs a respective action identified by the icon of the second action predicate when the second data indication predicate is positive; and during the computer game, in response to the declarative specification, allowing the game character to perform the respective action identified by the icon of the first action predicate when the first data indication predicate is positive and to perform the respective action identified by the icon of the second action predicate when the second data indication predicate is positive; wherein: one section of the screen comprises a declarative specification area, the adjustment input is received via the declarative specification area and displays the icon of the first data indication predicate and the icon of the first action predicate; and another section of the screen provides a view of a real time execution of the declarative specification, showing in real time, an effect of the adjustment input on the computer game as the declarative specification is altered. | 12. A computer implemented method, comprising: receiving from a user through a user interface, an adjustment input to move an icon on a screen to a position in which the icon is touching one or more other icons to form a first grouping, the first grouping comprises an icon of a first data indication predicate touching an icon of a first action predicate, wherein the first data indication predicate is positive or negative based on a position of a game character relative to an object in a computer game; receiving from the user through the user interface, another adjustment input to move another icon on the screen to a position in which the another icon is touching one or more other icons to form a second grouping separate from the first grouping, the second grouping comprises an icon of a second data indication predicate touching an icon of a second action predicate, the second data indication predicate is positive or negative based on the position of the game character relative to the object in the computer game, the second data indication predicate is positive when the first data indication predicate is negative, and negative when the first data indication predicate is positive; altering a declarative specification for controlling the game character in the computer game as a function of the first grouping and the second grouping, wherein: (a) the first grouping is a logical implication, based on a proximity of the icon of the first data indication predicate to the icon of the first action predicate, in which the game character performs a respective action identified by the icon of the first action predicate when the first data indication predicate is positive and (b) the second grouping is a logical implication, based on a proximity of the icon of the second data indication predicate to the icon of the second action predicate, in which the game character performs a respective action identified by the icon of the second action predicate when the second data indication predicate is positive; and during the computer game, in response to the declarative specification, allowing the game character to perform the respective action identified by the icon of the first action predicate when the first data indication predicate is positive and to perform the respective action identified by the icon of the second action predicate when the second data indication predicate is positive; wherein: one section of the screen comprises a declarative specification area, the adjustment input is received via the declarative specification area and displays the icon of the first data indication predicate and the icon of the first action predicate; and another section of the screen provides a view of a real time execution of the declarative specification, showing in real time, an effect of the adjustment input on the computer game as the declarative specification is altered. 15. The computer implemented method of claim 12 , wherein: the first data indication predicate is positive when the game character is close, within a distance threshold, to the object in the computer game; and the second data indication predicate is positive when the game character is not close to the object in the computer game. | 0.5 |
8,560,318 | 1 | 2 | 1. A computer implemented method for evaluating potential confusion within a grammar structure for a set of statements to be used in speech recognition during a computing event, comprising: receiving a plurality of statements from within a grammar structure, each of the plurality of statements formed by a number of word sets; identifying a number of alignment regions across the plurality of statements by aligning the plurality of statements on a word set basis, wherein each aligned word set represents an alignment region; identifying a number of potential confusion zones across the plurality of statements, wherein each potential confusion zone is defined by words from two or more of the plurality of statements at corresponding positions outside the number of alignment regions; for each of the identified potential confusion zones, analyzing using a computer phonetic pronunciations of the words within the potential confusion zone to determine a measure of confusion probability between the words when audibly processed by a speech recognition system during the computing event; and generating, using the computer, a report to convey an identity of the potential confusion zones across the plurality of statements and their corresponding measure of confusion probability. | 1. A computer implemented method for evaluating potential confusion within a grammar structure for a set of statements to be used in speech recognition during a computing event, comprising: receiving a plurality of statements from within a grammar structure, each of the plurality of statements formed by a number of word sets; identifying a number of alignment regions across the plurality of statements by aligning the plurality of statements on a word set basis, wherein each aligned word set represents an alignment region; identifying a number of potential confusion zones across the plurality of statements, wherein each potential confusion zone is defined by words from two or more of the plurality of statements at corresponding positions outside the number of alignment regions; for each of the identified potential confusion zones, analyzing using a computer phonetic pronunciations of the words within the potential confusion zone to determine a measure of confusion probability between the words when audibly processed by a speech recognition system during the computing event; and generating, using the computer, a report to convey an identity of the potential confusion zones across the plurality of statements and their corresponding measure of confusion probability. 2. A computer implemented method as recited in claim 1 , wherein the computer implemented method is performed without auditory input. | 0.89909 |
8,812,380 | 8 | 14 | 8. A computer-implemented method for presenting a tax preparation program, the method comprising the steps of: generating, via a computer processor, a graphical user interface (GUI) for a tax preparation program; enabling, via the computer processor and within the GUI, at least a first and a second user-selectable tab, with the first tab related to a first tax topic and containing a first set of accordions associated with the first tax topic, and the second tab related to a second tax topic and containing a second set of accordions associated with the second tax topic, wherein each accordion of the first and second sets of accordions may be expanded to enable a taxpayer user to enter in a plurality of fields tax-related information for completing a tax return; receiving, via the computer processor and from the taxpayer user, a selection of the first user-selectable tab; in response to the receiving a selection of the first user-selectable tab, presenting, via the computer processor and within the GUI, first and second accordions associated with the first user-selectable tab, wherein the first accordion presents a first tax sub-topic for selection by the taxpayer user, and the second accordion presents a second tax sub-topic for selection by the taxpayer user, wherein each of the first and second tax sub-topics is logically associated with the first tax topic related to the selected first user-selectable tab, and wherein the second user-selectable tab remains viewable by the taxpayer user on the GUI during the presenting of said first and second accordions; receiving, via the computer processor, a selection by the taxpayer user of the first accordion presenting the first tax sub-topic; presenting, via the computer processor and within the GUI, and in response to the taxpayer user's selection of the first accordion, at least one first field for entry of tax-related information by the taxpayer user, wherein during presenting of the at lest one first field, the second tax sub-topic presented by the second accordion remains viewable by the taxpayer on the GUI; receiving, via the computer processor and from the taxpayer user, entry of a first portion of the tax-related information in the at least one first field presented in response to the taxpayer user's selection of the first accordion; receiving, via the computer processor, a selection by the taxpayer user of the second accordion; presenting, via the computer processor and within the GUI, and in response to the taxpayer user's selection of the second accordion, at least one second field for entry of tax-related information by the taxpayer user, wherein during presenting of the at least one second field, the first tax sub-topic presented by the first accordion remains viewable by the taxpayer user on the GUI; receiving, via the computer processor and from the taxpayer user, entry of a second portion of the tax-related information in the at least one second field presented in response to the taxpayer user's selection of the second accordion; presenting, via the computer processor and within the GUI, a first accordion summary information that summarizes the first portion of the tax-related information entered in the at least one first field, and a second accordion summary information that summarizes the second portion of the tax-related information entered in the at least one second field; and presenting, via the computer processor and within the GUI, a first tab summary information that summarizes the first accordion summary information and the second accordion summary information, wherein the first tab summary information is on or proximate to the first tab, and wherein the first tab summary information, the first accordion summary information, and the second accordion summary information are simultaneously viewable during the selection of the first tab. | 8. A computer-implemented method for presenting a tax preparation program, the method comprising the steps of: generating, via a computer processor, a graphical user interface (GUI) for a tax preparation program; enabling, via the computer processor and within the GUI, at least a first and a second user-selectable tab, with the first tab related to a first tax topic and containing a first set of accordions associated with the first tax topic, and the second tab related to a second tax topic and containing a second set of accordions associated with the second tax topic, wherein each accordion of the first and second sets of accordions may be expanded to enable a taxpayer user to enter in a plurality of fields tax-related information for completing a tax return; receiving, via the computer processor and from the taxpayer user, a selection of the first user-selectable tab; in response to the receiving a selection of the first user-selectable tab, presenting, via the computer processor and within the GUI, first and second accordions associated with the first user-selectable tab, wherein the first accordion presents a first tax sub-topic for selection by the taxpayer user, and the second accordion presents a second tax sub-topic for selection by the taxpayer user, wherein each of the first and second tax sub-topics is logically associated with the first tax topic related to the selected first user-selectable tab, and wherein the second user-selectable tab remains viewable by the taxpayer user on the GUI during the presenting of said first and second accordions; receiving, via the computer processor, a selection by the taxpayer user of the first accordion presenting the first tax sub-topic; presenting, via the computer processor and within the GUI, and in response to the taxpayer user's selection of the first accordion, at least one first field for entry of tax-related information by the taxpayer user, wherein during presenting of the at lest one first field, the second tax sub-topic presented by the second accordion remains viewable by the taxpayer on the GUI; receiving, via the computer processor and from the taxpayer user, entry of a first portion of the tax-related information in the at least one first field presented in response to the taxpayer user's selection of the first accordion; receiving, via the computer processor, a selection by the taxpayer user of the second accordion; presenting, via the computer processor and within the GUI, and in response to the taxpayer user's selection of the second accordion, at least one second field for entry of tax-related information by the taxpayer user, wherein during presenting of the at least one second field, the first tax sub-topic presented by the first accordion remains viewable by the taxpayer user on the GUI; receiving, via the computer processor and from the taxpayer user, entry of a second portion of the tax-related information in the at least one second field presented in response to the taxpayer user's selection of the second accordion; presenting, via the computer processor and within the GUI, a first accordion summary information that summarizes the first portion of the tax-related information entered in the at least one first field, and a second accordion summary information that summarizes the second portion of the tax-related information entered in the at least one second field; and presenting, via the computer processor and within the GUI, a first tab summary information that summarizes the first accordion summary information and the second accordion summary information, wherein the first tab summary information is on or proximate to the first tab, and wherein the first tab summary information, the first accordion summary information, and the second accordion summary information are simultaneously viewable during the selection of the first tab. 14. The computer-implemented method of claim 8 , wherein the first field extends laterally from the first accordion. | 0.923179 |
8,001,551 | 1 | 4 | 1. At a Web server, the Web server including a script handler for providing client-side scripts and corresponding appropriately localized resources to a Web browser, a method for utilizing localized resources for client-side scripts, the method comprising: an act of receiving a Web page request from the Web browser, the Web page request indicating a user-interface culture of the Web browser, the user-interface culture including at least a language used by the Web browser; an act of accessing a server-side page that corresponds to the Web page; an act of executing a script manager that is referenced in the server-side page; an act of the script manager accessing a client-side script reference included in the server-side page, the client-side script reference referring to a client-side script that is to be executed at the Web browser, the client-side script including localization calls to external resources; an act of the script manager formulating an adapted client-side script reference to return to the Web browser, the adapted client-side script reference referring to the script handler and including a query portion that identifies at least the referenced client-side script and the user-interface culture of the Web browser; an act of returning the adapted client-side script reference to the Web browser in a Web page responsive to the Web page request; subsequent to returning the adapted client-side script reference to the Web browser, an act of receiving the adapted client-side script reference from the Web browser in response to the Web browser rendering the Web page, reception of the adapted client-side script reference being a request for the referenced client-side script; an act of dispatching the query portion of the adapted client-side script reference to the script handler; an act of the script handler identifying an appropriately localized resource set to use along with the referenced client-side script at the Web server based at least in part on the user-interface culture of the Web browser; an act of the script handler creating a resource set that can be used by the client-side script; and an act of returning the referenced client-side script along with the resource set to the Web browser in a single request such that execution of the client-side script at the Web browser can be localized in accordance with resources contained in the formatted localized resource set. | 1. At a Web server, the Web server including a script handler for providing client-side scripts and corresponding appropriately localized resources to a Web browser, a method for utilizing localized resources for client-side scripts, the method comprising: an act of receiving a Web page request from the Web browser, the Web page request indicating a user-interface culture of the Web browser, the user-interface culture including at least a language used by the Web browser; an act of accessing a server-side page that corresponds to the Web page; an act of executing a script manager that is referenced in the server-side page; an act of the script manager accessing a client-side script reference included in the server-side page, the client-side script reference referring to a client-side script that is to be executed at the Web browser, the client-side script including localization calls to external resources; an act of the script manager formulating an adapted client-side script reference to return to the Web browser, the adapted client-side script reference referring to the script handler and including a query portion that identifies at least the referenced client-side script and the user-interface culture of the Web browser; an act of returning the adapted client-side script reference to the Web browser in a Web page responsive to the Web page request; subsequent to returning the adapted client-side script reference to the Web browser, an act of receiving the adapted client-side script reference from the Web browser in response to the Web browser rendering the Web page, reception of the adapted client-side script reference being a request for the referenced client-side script; an act of dispatching the query portion of the adapted client-side script reference to the script handler; an act of the script handler identifying an appropriately localized resource set to use along with the referenced client-side script at the Web server based at least in part on the user-interface culture of the Web browser; an act of the script handler creating a resource set that can be used by the client-side script; and an act of returning the referenced client-side script along with the resource set to the Web browser in a single request such that execution of the client-side script at the Web browser can be localized in accordance with resources contained in the formatted localized resource set. 4. The method as recited in claim 1 , wherein the act of the script manager formulating an adapted client-side script reference to return to the Web browser comprises an act of to script manager applying script localization rules to the client-side script reference based on the indicated user-interface culture to formulate the query portion of the adapted client-side script reference. | 0.894608 |
8,965,771 | 18 | 27 | 18. A computer program product tangibly stored on a computer readable hardware storage device, the computer program product comprising instructions for causing a computer processor device to: receive one or more text inputs corresponding to transaction requests; analyze the text inputs using natural language processing to build added information from the one or more transaction requests; provide added information based on results of analyzing the transaction requests by the natural language processing, search a database in communication with the one or more computer systems for appropriate content to present to the user in response to analyzing the text in the transaction, with the response including one or words that represent a key concept associated with the response to trigger a facility to present additional information about the key concept; build by a conversational engine, a conversation based on the transaction requests and key concept; statistically analyze the information stored in a database to derive useful market data based on the added information; track interactions with the user; store information derived from tracking the interactions in the database for subsequent marketing to that person to produce information for market research; generate voice-synthesized follow-up responses in accordance with the transaction requests through an avatar, with the voice-synthesized, follow-up responses based on information stored in the database, including the statistically analyzed added information regarding the transactions; receive subsequent text inputs from the user in response to the voice-synthesized, follow-up responses; and analyze the subsequent text inputs and the voice-synthesized, follow-up responses to determine an action to take with respect to the user; and cause the determined action to occur. | 18. A computer program product tangibly stored on a computer readable hardware storage device, the computer program product comprising instructions for causing a computer processor device to: receive one or more text inputs corresponding to transaction requests; analyze the text inputs using natural language processing to build added information from the one or more transaction requests; provide added information based on results of analyzing the transaction requests by the natural language processing, search a database in communication with the one or more computer systems for appropriate content to present to the user in response to analyzing the text in the transaction, with the response including one or words that represent a key concept associated with the response to trigger a facility to present additional information about the key concept; build by a conversational engine, a conversation based on the transaction requests and key concept; statistically analyze the information stored in a database to derive useful market data based on the added information; track interactions with the user; store information derived from tracking the interactions in the database for subsequent marketing to that person to produce information for market research; generate voice-synthesized follow-up responses in accordance with the transaction requests through an avatar, with the voice-synthesized, follow-up responses based on information stored in the database, including the statistically analyzed added information regarding the transactions; receive subsequent text inputs from the user in response to the voice-synthesized, follow-up responses; and analyze the subsequent text inputs and the voice-synthesized, follow-up responses to determine an action to take with respect to the user; and cause the determined action to occur. 27. The computer program product of claim 18 wherein determined action is to produce a report for customer support to report a malfunctioning product, system, or service. | 0.604651 |
6,044,385 | 2 | 3 | 2. A method according to claim 1, wherein: said document comprises contents having predetermined relative horizontal positions; said first magnification level and said second magnification level each comprise a vertical magnification factor and a horizontal magnification factor; and said method further comprises utilizing substantially equal horizontal magnification factors for said first magnification level and said second magnification level, such that said predetermined relative horizontal positions of said contents are maintained throughout said window. | 2. A method according to claim 1, wherein: said document comprises contents having predetermined relative horizontal positions; said first magnification level and said second magnification level each comprise a vertical magnification factor and a horizontal magnification factor; and said method further comprises utilizing substantially equal horizontal magnification factors for said first magnification level and said second magnification level, such that said predetermined relative horizontal positions of said contents are maintained throughout said window. 3. A method according to claim 2, wherein said primary portion of said document is an original primary portion, said method further comprising: in response to operator input moving said elevator box from a first position to a second position, displaying a new primary portion of said document within said lens utilizing said first magnification level, and displaying all of said original primary portion that is not in said new primary portion utilizing said second magnification level. | 0.5 |
8,756,227 | 12 | 14 | 12. A computer readable medium comprising executable instructions that when executed perform a method comprising: tailoring user specific data of a user to generate tailored user specific data, the user specific data associated with an application and tailored based on one or more aesthetic preferences of the user as indicated by a template for the application; and extending a user profile of the user to comprise the tailored user specific data to generate an extended user profile. | 12. A computer readable medium comprising executable instructions that when executed perform a method comprising: tailoring user specific data of a user to generate tailored user specific data, the user specific data associated with an application and tailored based on one or more aesthetic preferences of the user as indicated by a template for the application; and extending a user profile of the user to comprise the tailored user specific data to generate an extended user profile. 14. The computer readable medium of claim 12 , the user specific data indicative of performance of the user with regard to the application. | 0.57362 |
9,756,161 | 6 | 11 | 6. A vehicle comprising: a context model created by modeling each name included in a phone book; a model creator configured to classify the phone book according to a length of syllables of each name, and to create a context model for each length of syllables; and a voice recognizer configured to create a phone number candidate group corresponding to a received voice signal based on an acoustic model and the context model for each length of syllables, calculate a length of speech based on a Begin of Speech (BoS) and an End of Speech (EoS), and to respectively apply different reliability weight values determined according to the length of speech to phone number candidates in the phone number candidate group. | 6. A vehicle comprising: a context model created by modeling each name included in a phone book; a model creator configured to classify the phone book according to a length of syllables of each name, and to create a context model for each length of syllables; and a voice recognizer configured to create a phone number candidate group corresponding to a received voice signal based on an acoustic model and the context model for each length of syllables, calculate a length of speech based on a Begin of Speech (BoS) and an End of Speech (EoS), and to respectively apply different reliability weight values determined according to the length of speech to phone number candidates in the phone number candidate group. 11. The vehicle according to claim 6 , wherein the model creator segments the name into a first name and a last name to create a segmented context model. | 0.752427 |
8,442,812 | 41 | 42 | 41. A non-transitory computer readable storage medium encoded with one or more computer programs executable by at least one processor, the one or more computer programs for creating a recognition grammar for use with an interactive user interface to human readable text data that is also machine readable, the interactive user interface being responsive to spoken input, the computer programs comprising: instructions for providing access to a phrase thesaurus database comprising a plurality of classes of phrases, wherein any two phrases that are semantic equivalent of each other are assigned to a same class; instructions for formulating an expression representing a part of the text data for each of one or more parts of the text data, wherein each formulated expression is constructed as one or more combinations of one or more phrases in the phrase thesaurus database; and instructions for automatically using the phrase thesaurus database to construct one or more equivalent expressions of each formulated expression based on assigned classes of the one or more phrases of each formulated expression, wherein the recognition grammar comprises the collection of all of the expressions. | 41. A non-transitory computer readable storage medium encoded with one or more computer programs executable by at least one processor, the one or more computer programs for creating a recognition grammar for use with an interactive user interface to human readable text data that is also machine readable, the interactive user interface being responsive to spoken input, the computer programs comprising: instructions for providing access to a phrase thesaurus database comprising a plurality of classes of phrases, wherein any two phrases that are semantic equivalent of each other are assigned to a same class; instructions for formulating an expression representing a part of the text data for each of one or more parts of the text data, wherein each formulated expression is constructed as one or more combinations of one or more phrases in the phrase thesaurus database; and instructions for automatically using the phrase thesaurus database to construct one or more equivalent expressions of each formulated expression based on assigned classes of the one or more phrases of each formulated expression, wherein the recognition grammar comprises the collection of all of the expressions. 42. The non-transitory computer readable storage medium as in claim 41 , wherein the instructions for formulating an expression representing a part of the text data further comprise instructions for formulating an expression representing an interactive part of the text data. | 0.826826 |
9,026,617 | 1 | 2 | 1. A method of utilizing document service preferences, the method comprising: storing, within a storage medium of a portable device, one or more document service preferences for use with a first computer system, wherein the first computer system is in communication with a first computer network; connecting the portable device to a second computer system, wherein the second computer system is in communication with a second computer network that is physically remote from the first computer network; automatically loading an installation application from the portable device on the second computer system to manage a document service application when the portable device is connected to the second computer system, automatically selecting a document service device on the second computer network based on at least the one or more document service preferences from the portable device; and performing a document service for an electronic document on the selected document service device. | 1. A method of utilizing document service preferences, the method comprising: storing, within a storage medium of a portable device, one or more document service preferences for use with a first computer system, wherein the first computer system is in communication with a first computer network; connecting the portable device to a second computer system, wherein the second computer system is in communication with a second computer network that is physically remote from the first computer network; automatically loading an installation application from the portable device on the second computer system to manage a document service application when the portable device is connected to the second computer system, automatically selecting a document service device on the second computer network based on at least the one or more document service preferences from the portable device; and performing a document service for an electronic document on the selected document service device. 2. The method of claim 1 wherein the first computer network comprises a first intranet and the second computer network comprises a second intranet. | 0.868515 |
7,958,109 | 8 | 18 | 8. A machine-implemented method of comprising: receiving a query from a user; based on the query, determining one or more potential intents of the user; based on the query, determining a plurality of matching resources; for a particular matching resource of the plurality of matching resources, selecting, based on the one or more potential intents, a first abstract template and a second abstract template from the plurality of abstract templates, wherein the first abstract template is different than the second abstract template; wherein each abstract template of the plurality of abstract templates: (a) corresponds to a different intent than any other intent to which any other abstract template of the plurality of abstract templates corresponds, and (b) dictates a different manner of displaying information about a resource than any other manner of displaying dictated by any other abstract template of the plurality of abstract templates; and generating a search results page that includes: for the particular matching resource, a first abstract that is displayed based on the first abstract template, and for the particular matching resource, a second abstract that is displayed based on the second abstract template; wherein the method is performed by one or more computing devices. | 8. A machine-implemented method of comprising: receiving a query from a user; based on the query, determining one or more potential intents of the user; based on the query, determining a plurality of matching resources; for a particular matching resource of the plurality of matching resources, selecting, based on the one or more potential intents, a first abstract template and a second abstract template from the plurality of abstract templates, wherein the first abstract template is different than the second abstract template; wherein each abstract template of the plurality of abstract templates: (a) corresponds to a different intent than any other intent to which any other abstract template of the plurality of abstract templates corresponds, and (b) dictates a different manner of displaying information about a resource than any other manner of displaying dictated by any other abstract template of the plurality of abstract templates; and generating a search results page that includes: for the particular matching resource, a first abstract that is displayed based on the first abstract template, and for the particular matching resource, a second abstract that is displayed based on the second abstract template; wherein the method is performed by one or more computing devices. 18. One or more storage media storing instructions which, when executed by one or more processors, cause the performance of the method of claim 8 . | 0.5 |
8,055,674 | 48 | 49 | 48. A non-transitory computer readable storage medium, storing one or more programs for querying a fact repository, for execution by one or more processors of a computer system, the one or more programs including instructions for: receiving a search query; retrieving at least one fact from the fact repository, the at least one fact corresponding to the received search query and having an attribute and a value, wherein the fact repository includes a plurality of facts associated with objects, wherein a respective fact in the fact repository includes a respective attribute and a respective value, wherein the respective value is a text string, and wherein the plurality of facts are extracted from a plurality of documents; retrieving at least one annotation associated with the at least one fact, the at least one annotation having a value corresponding to the value of the at least one fact, wherein an annotation includes additional information about a fact, and wherein a value of the annotation is indexed to a substring of a fact's value; and sending the attribute and value of the retrieved fact and the retrieved annotation in response to the query. | 48. A non-transitory computer readable storage medium, storing one or more programs for querying a fact repository, for execution by one or more processors of a computer system, the one or more programs including instructions for: receiving a search query; retrieving at least one fact from the fact repository, the at least one fact corresponding to the received search query and having an attribute and a value, wherein the fact repository includes a plurality of facts associated with objects, wherein a respective fact in the fact repository includes a respective attribute and a respective value, wherein the respective value is a text string, and wherein the plurality of facts are extracted from a plurality of documents; retrieving at least one annotation associated with the at least one fact, the at least one annotation having a value corresponding to the value of the at least one fact, wherein an annotation includes additional information about a fact, and wherein a value of the annotation is indexed to a substring of a fact's value; and sending the attribute and value of the retrieved fact and the retrieved annotation in response to the query. 49. The computer readable storage medium of claim 48 , wherein the annotation is a GeoPoint annotation. | 0.5 |
7,640,563 | 20 | 24 | 20. A system comprising: a description provider interface to receive a plurality of descriptions of a media content from a plurality of description providers, wherein each of the description providers has an associated trust level; and a composite generator to generate a composite description of the media content based on the plurality of descriptions of the media content and the trust levels associated with each of the plurality of description providers, the composite description comprising relative degrees to which the media content relates to each of a plurality of genres. | 20. A system comprising: a description provider interface to receive a plurality of descriptions of a media content from a plurality of description providers, wherein each of the description providers has an associated trust level; and a composite generator to generate a composite description of the media content based on the plurality of descriptions of the media content and the trust levels associated with each of the plurality of description providers, the composite description comprising relative degrees to which the media content relates to each of a plurality of genres. 24. The system as recited in claim 20 , further comprising a description provider data repository to associate a trust level with a description provider, and wherein the relative degrees are based on the trust level. | 0.78865 |
8,296,296 | 1 | 10 | 1. A method of formatting information from a searchable database using a research module, the research module configured to correlate search criteria to the searchable database for generating one or more matching items, the searchable database being in a directory tree structure including nodes comprising a collection of related data and branches comprising links between the nodes, the method comprising: performing, using the research module, a search of the searchable database to generate one or more matching items correlating to search criteria wherein each of the one or more matching items represents a node from within the directory tree structure; formatting a collection of related data corresponding to a node of one matching item from the one or more matching items into an encyclopedia-like entry; communicating, to a computing device, the encyclopedia-like entry corresponding to the node of the one matching item; saving an indication of the search and an indication of a notification method, the indication of the search comprising an indication of a navigation path through the directory tree structure to the node of the one matching item; determining, based on the saved indication of the search, that new information is associated with the node of the one matching item after communicating the encyclopedia-like entry to the computing device; and automatically sending, in response to determining that the new information is associated with the node of the one matching item, a notification of the new information via the notification method. | 1. A method of formatting information from a searchable database using a research module, the research module configured to correlate search criteria to the searchable database for generating one or more matching items, the searchable database being in a directory tree structure including nodes comprising a collection of related data and branches comprising links between the nodes, the method comprising: performing, using the research module, a search of the searchable database to generate one or more matching items correlating to search criteria wherein each of the one or more matching items represents a node from within the directory tree structure; formatting a collection of related data corresponding to a node of one matching item from the one or more matching items into an encyclopedia-like entry; communicating, to a computing device, the encyclopedia-like entry corresponding to the node of the one matching item; saving an indication of the search and an indication of a notification method, the indication of the search comprising an indication of a navigation path through the directory tree structure to the node of the one matching item; determining, based on the saved indication of the search, that new information is associated with the node of the one matching item after communicating the encyclopedia-like entry to the computing device; and automatically sending, in response to determining that the new information is associated with the node of the one matching item, a notification of the new information via the notification method. 10. The method of claim 1 , wherein the notification method is one selected from the group consisting of: posting to a bulletin board, sending an email, posting a news item, and displaying on a desktop interface. | 0.811723 |
9,939,980 | 1 | 4 | 1. A method comprising: receiving user input at a client device; analyzing the user input to detect a stress level or a mood; determining, based at least in part on the stress level or the mood, to output a push notification to the user; and presenting, by the client device, the push notification, wherein the push notification comprises at least one suggestion for phrasing a user input request corresponding to an application, and wherein the suggestion comprises feedback on how to fix an inaccurate interaction with the application. | 1. A method comprising: receiving user input at a client device; analyzing the user input to detect a stress level or a mood; determining, based at least in part on the stress level or the mood, to output a push notification to the user; and presenting, by the client device, the push notification, wherein the push notification comprises at least one suggestion for phrasing a user input request corresponding to an application, and wherein the suggestion comprises feedback on how to fix an inaccurate interaction with the application. 4. The method of claim 1 , wherein presenting the push notification comprises displaying a destination as an interstitial view. | 0.515267 |
7,526,059 | 1 | 10 | 1. A counting device, comprising: a memory comprising a set of memory cells, comprising multiple groups of the memory cells that are configured to store respective count words of a count code, the count words comprising at least a less significant word and a more significant word; and a controller, which is coupled to the memory cells so as to make a first assignment of the groups of the memory cells that are to store the respective count words, which includes assigning first and second groups of the memory cells to store the less significant word and the more significant word, respectively, and to increment, in response to occurrences of a count input, the less significant word from an initial value up to a first limit in each of a plurality of successive first iterations, and to increment, in response to reaching the first limit in each of the successive first iterations, the more significant word from an initial value up to a second limit in each of a plurality of successive second iterations, and upon reaching the second limit, to make a second assignment, different from the first assignment, of the groups of the memory cells that are to store the less significant word and the more significant word, respectively, and to continue the first and second iterations subject to the second assignment. | 1. A counting device, comprising: a memory comprising a set of memory cells, comprising multiple groups of the memory cells that are configured to store respective count words of a count code, the count words comprising at least a less significant word and a more significant word; and a controller, which is coupled to the memory cells so as to make a first assignment of the groups of the memory cells that are to store the respective count words, which includes assigning first and second groups of the memory cells to store the less significant word and the more significant word, respectively, and to increment, in response to occurrences of a count input, the less significant word from an initial value up to a first limit in each of a plurality of successive first iterations, and to increment, in response to reaching the first limit in each of the successive first iterations, the more significant word from an initial value up to a second limit in each of a plurality of successive second iterations, and upon reaching the second limit, to make a second assignment, different from the first assignment, of the groups of the memory cells that are to store the less significant word and the more significant word, respectively, and to continue the first and second iterations subject to the second assignment. 10. The device according to claim 1 , wherein the count code comprises, in addition to the less significant and more significant words, at least a third count word, which is stored in a third group of the memory cells in accordance with the first assignment, and wherein the less significant word, the more significant word, and the third count word are swapped among the groups of the memory cells upon making the second assignment. | 0.5 |
10,140,978 | 1 | 19 | 1. A method comprising: obtaining, by one or more computers, acoustic data for an utterance; determining, by the one or more computers, speech recognition candidates for the utterance based on the acoustic data; obtaining, by the one or more computers, a ranking of the speech recognition candidates determined by a speech recognizer; selecting, by the one or more computers, a transcription for the acoustic data from among the speech recognition candidates; determining, by the one or more computers, feature scores from the ranking of the speech recognition candidates; generating, by the one or more computers, a classifier output for each of at least some of the speech recognition candidates, wherein each of the classifier outputs is an output that a trained machine learning classifier provided in response to receiving at least one of the feature scores as input; selecting, by the one or more computers, a subset of the speech recognition candidates based on the classifier outputs of the trained machine learning classifier; and providing, by the one or more computers and for display at a client device, data indicating (i) the transcription for the utterance and (ii) the subset of the speech recognition candidates as a set of alternative transcriptions for the utterance, wherein the one or more computers are configured to provide different quantities of alternative transcriptions for different utterances. | 1. A method comprising: obtaining, by one or more computers, acoustic data for an utterance; determining, by the one or more computers, speech recognition candidates for the utterance based on the acoustic data; obtaining, by the one or more computers, a ranking of the speech recognition candidates determined by a speech recognizer; selecting, by the one or more computers, a transcription for the acoustic data from among the speech recognition candidates; determining, by the one or more computers, feature scores from the ranking of the speech recognition candidates; generating, by the one or more computers, a classifier output for each of at least some of the speech recognition candidates, wherein each of the classifier outputs is an output that a trained machine learning classifier provided in response to receiving at least one of the feature scores as input; selecting, by the one or more computers, a subset of the speech recognition candidates based on the classifier outputs of the trained machine learning classifier; and providing, by the one or more computers and for display at a client device, data indicating (i) the transcription for the utterance and (ii) the subset of the speech recognition candidates as a set of alternative transcriptions for the utterance, wherein the one or more computers are configured to provide different quantities of alternative transcriptions for different utterances. 19. The method of claim 1 , wherein the machine learning classifier comprises a maximum entropy or logistic regression classifier, an artificial neural network, or a support vector machine. | 0.893581 |
7,552,381 | 51 | 53 | 51. The computer readable storage medium of claim 34 , wherein the at least one action comprises transmitting the at least one document to a destination, the method further comprising determining a destination. | 51. The computer readable storage medium of claim 34 , wherein the at least one action comprises transmitting the at least one document to a destination, the method further comprising determining a destination. 53. The computer readable storage medium of claim 51 , wherein determining a destination comprises reading an indicator of a destination from the image of the document index. | 0.5 |
9,594,802 | 2 | 19 | 2. The method of claim 1 , further comprising: receiving a user edit to the graphical representation of the structure of database query statement; and in response to receiving the user edit to the graphical representation of the structure of the database query statement, updating the database query statement in accordance with the user edit to the graphical representation of the structure of the database query statement. | 2. The method of claim 1 , further comprising: receiving a user edit to the graphical representation of the structure of database query statement; and in response to receiving the user edit to the graphical representation of the structure of the database query statement, updating the database query statement in accordance with the user edit to the graphical representation of the structure of the database query statement. 19. The method of claim 2 , wherein the modifying of the database query statement in accordance with the user edit comprises: translating the graphical model to an Extensible Markup Language (XML) model; and converting the XML model to an updated database query statement. | 0.5 |
7,937,348 | 1 | 20 | 1. A computer program product comprising a computer useable medium having program logic stored thereon, the program logic comprising machine readable code executable by a computer, the machine readable code comprising a system for interrogating a user profile and reading a learning objective as a first input; a system for interrogating a software application and reading a learning objective as a second input; a calculation component for determining a relevance of the first input learning objective to the second input learning objective; and a system for adapting the software application in accordance with the determined relevance and updating the user profile in accordance with the determined relevance. | 1. A computer program product comprising a computer useable medium having program logic stored thereon, the program logic comprising machine readable code executable by a computer, the machine readable code comprising a system for interrogating a user profile and reading a learning objective as a first input; a system for interrogating a software application and reading a learning objective as a second input; a calculation component for determining a relevance of the first input learning objective to the second input learning objective; and a system for adapting the software application in accordance with the determined relevance and updating the user profile in accordance with the determined relevance. 20. The computer program product of claim 1 , executed on a client or user computer. | 0.913043 |
5,414,841 | 11 | 12 | 11. In a data processing system having a processor and a memory, a computerized token identification system using tokens generated by said computer system for uniquely representing a plurality of items, each of said tokens having a token structure consisting of a plurality of fields, said token structure comprising: a delimiter field containing a token recognition character, wherein said delimiter field is one of said plurality of fields; a version field following the delimiter field containing a version string of at least one character, identifying a unique token version, wherein said version field is one of said plurality of fields; and a variable field adjacent said version field, containing a variable string of at least one character, conforming to a format specification for said unique token version, each variable string being unique for a unique token version, wherein said variable field is one of said plurality of fields. | 11. In a data processing system having a processor and a memory, a computerized token identification system using tokens generated by said computer system for uniquely representing a plurality of items, each of said tokens having a token structure consisting of a plurality of fields, said token structure comprising: a delimiter field containing a token recognition character, wherein said delimiter field is one of said plurality of fields; a version field following the delimiter field containing a version string of at least one character, identifying a unique token version, wherein said version field is one of said plurality of fields; and a variable field adjacent said version field, containing a variable string of at least one character, conforming to a format specification for said unique token version, each variable string being unique for a unique token version, wherein said variable field is one of said plurality of fields. 12. The system of claim 11 wherein said version field is adjacent said delimiter field. | 0.918233 |
8,463,593 | 10 | 14 | 10. A computer storage medium having computer executable instructions that are not a signal stored thereon which, when executed by a computer, cause the computer to: identify a given word W to be entered into an index; determine a plurality of word senses S n associated with the word W; determine a plurality of hypernyms H n associated with the plurality of word senses S n , the plurality of hypernyms H n comprising a tree-like inheritance hierarchy of hypernyms associated with each of the plurality of word senses S n ; establish a word hypernym weight WHW(H n ,W) for each of the plurality of hypernyms H n based on
WHW ( H n W )=Σ p ( S n |W )f( H n ,S n ) where the word hypernym weight WHW(H n ,W) being equal to a sum, over the plurality of word senses S n , of the product of the probability p of the sense of given word S n |W and a function f(H n ,S n ) defined as having a value of one when a given hypernym H is an inherited hypernym of the plurality of word senses Sn, and having a value of zero otherwise; and store information associated with the hypernym H into the index based on the word hypernym weight WHW(H n W). | 10. A computer storage medium having computer executable instructions that are not a signal stored thereon which, when executed by a computer, cause the computer to: identify a given word W to be entered into an index; determine a plurality of word senses S n associated with the word W; determine a plurality of hypernyms H n associated with the plurality of word senses S n , the plurality of hypernyms H n comprising a tree-like inheritance hierarchy of hypernyms associated with each of the plurality of word senses S n ; establish a word hypernym weight WHW(H n ,W) for each of the plurality of hypernyms H n based on
WHW ( H n W )=Σ p ( S n |W )f( H n ,S n ) where the word hypernym weight WHW(H n ,W) being equal to a sum, over the plurality of word senses S n , of the product of the probability p of the sense of given word S n |W and a function f(H n ,S n ) defined as having a value of one when a given hypernym H is an inherited hypernym of the plurality of word senses Sn, and having a value of zero otherwise; and store information associated with the hypernym H into the index based on the word hypernym weight WHW(H n W). 14. The computer storage medium of claim 10 , further causing the computer to store the word hypernym weight WHW(H n ,W) into the index. | 0.56962 |
4,724,523 | 23 | 24 | 23. An apparatus according to claim 22 in which said interrelationship-representative signal storage means comprises means for storing a signal indicative of an addressable section of an interrelationship table, said table comprising means for storing a signal indicative of an address of at least one linguistically related stored entry. | 23. An apparatus according to claim 22 in which said interrelationship-representative signal storage means comprises means for storing a signal indicative of an addressable section of an interrelationship table, said table comprising means for storing a signal indicative of an address of at least one linguistically related stored entry. 24. An apparatus according to claim 23 in which said interrelationship-representative signal storage means comprises means for storing a signal representative of synonymy. | 0.5 |
7,584,183 | 4 | 5 | 4. The scoring method of claim 1 , further comprising: determining the characterization of topic incoherency associated with each of the at least one document linking to that particular document includes, for each of the at least one document linking to that particular document, processing an indication of topics associated with that linking document. | 4. The scoring method of claim 1 , further comprising: determining the characterization of topic incoherency associated with each of the at least one document linking to that particular document includes, for each of the at least one document linking to that particular document, processing an indication of topics associated with that linking document. 5. The scoring method of claim 4 , wherein: processing an indication of topics associated with that linking document includes determining the characterization of topic incoherency as a function of scores, with respect to a plurality of topics, for that linking document. | 0.5 |
8,924,419 | 6 | 10 | 6. A method of determining an authoritative author on a subject, the method comprising: receiving a set of documents for each of a plurality of authors, each document having a semantic footprint; receiving user usage data for each of the documents; assigning a rating to each of the documents using the respective semantic footprint and user usage data for each document; determining, when one of the plurality of authors has a plurality of highly rated documents, an intersecting semantic footprint of the plurality of highly rated documents to establish that the one of the plurality of authors is an authoritative author of a subject, determining which documents are highly rated documents is based upon the usage data associated with each of the plurality of documents; receiving a query from a user; determining a semantic footprint of the query; determining that the semantic footprint of the query intersects with the intersecting semantic footprint of the plurality of highly rated documents; determining an extent of the intersection between the semantic footprint of the query and the intersecting semantic footprint associated with the author based upon a ratio of a union of the semantic footprint of the query and the intersecting semantic footprint associated with the author; and providing the user with contact information for the authoritative author based on a determination that the semantic footprint of the query intersects with the semantic footprint of the plurality of highly rated documents, wherein each semantic footprint is a multi-dimensional coordinate based on one or more keywords, entities and annotations, and wherein the intersecting semantic footprint is determined based upon a volume of overlapping areas of the respective multi-dimensional coordinates. | 6. A method of determining an authoritative author on a subject, the method comprising: receiving a set of documents for each of a plurality of authors, each document having a semantic footprint; receiving user usage data for each of the documents; assigning a rating to each of the documents using the respective semantic footprint and user usage data for each document; determining, when one of the plurality of authors has a plurality of highly rated documents, an intersecting semantic footprint of the plurality of highly rated documents to establish that the one of the plurality of authors is an authoritative author of a subject, determining which documents are highly rated documents is based upon the usage data associated with each of the plurality of documents; receiving a query from a user; determining a semantic footprint of the query; determining that the semantic footprint of the query intersects with the intersecting semantic footprint of the plurality of highly rated documents; determining an extent of the intersection between the semantic footprint of the query and the intersecting semantic footprint associated with the author based upon a ratio of a union of the semantic footprint of the query and the intersecting semantic footprint associated with the author; and providing the user with contact information for the authoritative author based on a determination that the semantic footprint of the query intersects with the semantic footprint of the plurality of highly rated documents, wherein each semantic footprint is a multi-dimensional coordinate based on one or more keywords, entities and annotations, and wherein the intersecting semantic footprint is determined based upon a volume of overlapping areas of the respective multi-dimensional coordinates. 10. The method of claim 6 wherein the user usage data for each document is selected from the group consisting of ratings from users, a number of users who have viewed the document, and a number of links to the document. | 0.598901 |
7,668,888 | 62 | 63 | 62. The computer-readable medium of claim 53 , wherein the instructions are configured further to cause the processor to store the readable object as a permanently stored readable object. | 62. The computer-readable medium of claim 53 , wherein the instructions are configured further to cause the processor to store the readable object as a permanently stored readable object. 63. The computer-readable medium of claim 62 , wherein the instructions are configured further to cause the processor to provide an index from the permanently stored readable object. | 0.5 |
8,958,088 | 1 | 4 | 1. An image forming apparatus comprising: a language setting history storage section configured to store a history of language setting through which a language used is specified from among a plurality of languages; an evacuation guidance information storage section configured to store respective sets of evacuation guidance information described in a plurality of different languages; a disaster information acquiring section configured to acquire disaster information in the event of a disaster; a language selecting section configured to, when the disaster information acquiring section acquires the disaster information, select one or more languages based on the history of language setting stored in the language setting history storage section; an image forming section configured to form an image on a recording medium; and a processing section configured to allow the image forming section to print, out of the sets of evacuation guidance information stored in the evacuation guidance information storage section, one or more sets of evacuation guidance information described in the one or more languages selected by the language selecting section. | 1. An image forming apparatus comprising: a language setting history storage section configured to store a history of language setting through which a language used is specified from among a plurality of languages; an evacuation guidance information storage section configured to store respective sets of evacuation guidance information described in a plurality of different languages; a disaster information acquiring section configured to acquire disaster information in the event of a disaster; a language selecting section configured to, when the disaster information acquiring section acquires the disaster information, select one or more languages based on the history of language setting stored in the language setting history storage section; an image forming section configured to form an image on a recording medium; and a processing section configured to allow the image forming section to print, out of the sets of evacuation guidance information stored in the evacuation guidance information storage section, one or more sets of evacuation guidance information described in the one or more languages selected by the language selecting section. 4. The image forming apparatus according to claim 1 , further comprising a sorting section configured to sort printouts of the evacuation guidance information into different locations for each of the plurality of different languages. | 0.757292 |
5,576,755 | 42 | 43 | 42. A method for automatically verifying the integrity of the data contained in a database of television program schedule information for an electronic television program guide comprising: storing a database of television program schedule information, said database comprising a plurality of data fields for a plurality of television stations, selecting a station from said plurality of stations for verification of one or more of said data fields for said station, selecting a time range for said verification, automatically analyzing said data fields for said selected station to locate gaps in the schedule data for said television station included in said program schedule information, and displaying information identifying said gaps. | 42. A method for automatically verifying the integrity of the data contained in a database of television program schedule information for an electronic television program guide comprising: storing a database of television program schedule information, said database comprising a plurality of data fields for a plurality of television stations, selecting a station from said plurality of stations for verification of one or more of said data fields for said station, selecting a time range for said verification, automatically analyzing said data fields for said selected station to locate gaps in the schedule data for said television station included in said program schedule information, and displaying information identifying said gaps. 43. The method of claim 42 further comprising automatically locating schedule overlaps in said data fields for said selected station in said database and displaying information identifying said schedule overlaps. | 0.524664 |
6,056,549 | 5 | 6 | 5. A communication aid as recited in claim 4 wherein said plurality of support structures and said number of subject-related demonstration pieces have equivalent code means formed thereon which are representative of a common one of said plurality of categories. | 5. A communication aid as recited in claim 4 wherein said plurality of support structures and said number of subject-related demonstration pieces have equivalent code means formed thereon which are representative of a common one of said plurality of categories. 6. A communication aid as recited in claim 5 wherein said code means comprises color coding of said plurality of support structures and said plurality of demonstration pieces. | 0.502841 |
7,890,507 | 1 | 7 | 1. A method for performing a search of a virtual repository formed from a plurality of repositories, each repository of the virtual repository being associated with a separate database system, the method comprising: receiving a string-based search expression; generating an expression tree of nodes based on the string-based search expression, one or more of the nodes of the expression tree being an attribute node, each attribute node corresponding to an attribute included in the string-based search expression; adding repository-location information to the expression tree by associating metadata with each attribute node in the expression tree, the metadata associated with a given attribute node identifying one or more repositories of the virtual repository that support the attribute represented by that attribute node; generating, for each repository identified by the metadata associated with the one or more attribute nodes, a query expression specifically for that repository; and determining whether sub-trees of a particular node of the expression tree have attribute nodes associated with metadata identifying different types of repositories, and, if the metadata associated with the attribute nodes identify different types of repositories, constructing the particular node as a federation node for merging search results returned by the child sub-trees; searching each repository identified by the metadata associated with the one or more attribute nodes using the query expression specifically generated for that repository. | 1. A method for performing a search of a virtual repository formed from a plurality of repositories, each repository of the virtual repository being associated with a separate database system, the method comprising: receiving a string-based search expression; generating an expression tree of nodes based on the string-based search expression, one or more of the nodes of the expression tree being an attribute node, each attribute node corresponding to an attribute included in the string-based search expression; adding repository-location information to the expression tree by associating metadata with each attribute node in the expression tree, the metadata associated with a given attribute node identifying one or more repositories of the virtual repository that support the attribute represented by that attribute node; generating, for each repository identified by the metadata associated with the one or more attribute nodes, a query expression specifically for that repository; and determining whether sub-trees of a particular node of the expression tree have attribute nodes associated with metadata identifying different types of repositories, and, if the metadata associated with the attribute nodes identify different types of repositories, constructing the particular node as a federation node for merging search results returned by the child sub-trees; searching each repository identified by the metadata associated with the one or more attribute nodes using the query expression specifically generated for that repository. 7. The method of claim 1 , wherein the step of associating metadata with the attribute node includes accessing at least one configuration file to determine which of the repositories support the attribute corresponding to the attribute node. | 0.708738 |
5,537,630 | 22 | 23 | 22. A storage device readable by a data processing system and encoding data processing system executable instructions for the data storage device comprising: means for graphically displaying a plurality of objects, wherein said at least one object includes a method having a plurality of parameters; means for selectively displaying each parameter in said plurality of parameters for said at least one object in association with said at least one object, wherein said plurality of parameters are displayed using a tree structure; means for displaying a list of sources for a parameter within said plurality of parameters in response to a selection of said parameter; and means for permitting specification of said parameter using said list of sources, wherein said parameter specified using said list of parameters is propagated to said method in said language for said object, wherein said means are activated when said storage device is connected to and accessed by a data processing system. | 22. A storage device readable by a data processing system and encoding data processing system executable instructions for the data storage device comprising: means for graphically displaying a plurality of objects, wherein said at least one object includes a method having a plurality of parameters; means for selectively displaying each parameter in said plurality of parameters for said at least one object in association with said at least one object, wherein said plurality of parameters are displayed using a tree structure; means for displaying a list of sources for a parameter within said plurality of parameters in response to a selection of said parameter; and means for permitting specification of said parameter using said list of sources, wherein said parameter specified using said list of parameters is propagated to said method in said language for said object, wherein said means are activated when said storage device is connected to and accessed by a data processing system. 23. The storage device of claim 22, wherein said storage device is a hard disk drive. | 0.627193 |
8,666,741 | 18 | 23 | 18. A system for remote speech recognition, the system comprising; customer premise equipment remote from a host and configured to interface with the host; a speech recognition engine remotely located from the host and located at the customer premise equipment, wherein the speech recognition engine is configured to: recognize user speech from a user of the customer premise equipment; and convert the user speech into text data packets, wherein the text data packets indicate text corresponding to the user speech; and a communication engine associated with the speech recognition engine and located at the customer premise equipment, wherein the communication engine is configured to: transmit the text data packets to the host; and receive information from the host in response to transmitting the text data packets. | 18. A system for remote speech recognition, the system comprising; customer premise equipment remote from a host and configured to interface with the host; a speech recognition engine remotely located from the host and located at the customer premise equipment, wherein the speech recognition engine is configured to: recognize user speech from a user of the customer premise equipment; and convert the user speech into text data packets, wherein the text data packets indicate text corresponding to the user speech; and a communication engine associated with the speech recognition engine and located at the customer premise equipment, wherein the communication engine is configured to: transmit the text data packets to the host; and receive information from the host in response to transmitting the text data packets. 23. The system of claim 18 , wherein the speech recognition engine is further configured to: identify a user language from a plurality of spoken languages based, at least in part, on the user speech; and translate the user speech from the identified user language into a host language supported by the host, wherein the text included in the text data packets is written in the host language. | 0.5 |
9,501,506 | 22 | 25 | 22. A system comprising: distributed computing devices represented as leaf nodes and a root node; an index of documents, the index being distributed across the leaf nodes, the documents being assigned to respective leaf nodes, and wherein a first leaf node includes: memory storing document-sharded posting lists for some or all terms associated with documents in a first set of documents that are assigned to the first leaf node, and memory storing term-sharded posting lists for terms assigned to the first leaf node without regard to leaf node assignments for documents identified in the term-sharded posting lists, wherein the first leaf node includes: at least one processor, memory storing instructions that, when executed by the at least one processor, cause the first leaf node to: receive an update for documents in the first set of documents and, responsive to the receiving, update at least some of the document-sharded posting lists; receive an updated term-sharded posting list portion for a first term from a second leaf node, the first term being assigned to the first leaf node; receive an updated term-sharded posting list portion for the first term from a third leaf node; and generate a new term-sharded posting list for the first term using the portion from the third leaf node and the portion from the second leaf node. | 22. A system comprising: distributed computing devices represented as leaf nodes and a root node; an index of documents, the index being distributed across the leaf nodes, the documents being assigned to respective leaf nodes, and wherein a first leaf node includes: memory storing document-sharded posting lists for some or all terms associated with documents in a first set of documents that are assigned to the first leaf node, and memory storing term-sharded posting lists for terms assigned to the first leaf node without regard to leaf node assignments for documents identified in the term-sharded posting lists, wherein the first leaf node includes: at least one processor, memory storing instructions that, when executed by the at least one processor, cause the first leaf node to: receive an update for documents in the first set of documents and, responsive to the receiving, update at least some of the document-sharded posting lists; receive an updated term-sharded posting list portion for a first term from a second leaf node, the first term being assigned to the first leaf node; receive an updated term-sharded posting list portion for the first term from a third leaf node; and generate a new term-sharded posting list for the first term using the portion from the third leaf node and the portion from the second leaf node. 25. The system of claim 22 , wherein the portion from the second leaf node includes an identification of the second leaf node that is retained in the new term-sharded posting list. | 0.756757 |
7,869,996 | 10 | 11 | 10. The method of claim 1 , wherein (E)(5) comprises applying automatic speech recognition to the effective dictation to produce a transcript of the effective dictation. | 10. The method of claim 1 , wherein (E)(5) comprises applying automatic speech recognition to the effective dictation to produce a transcript of the effective dictation. 11. The method of claim 10 , wherein (E)(5) further comprises displaying the transcript to a user only after completion of (E)(4). | 0.5 |
9,858,051 | 24 | 25 | 24. The method of claim 23 , wherein adding an entry includes: determining whether there is sufficient memory to add the new entry; and if there is not sufficient memory, adding the new entry according to a replacement policy. | 24. The method of claim 23 , wherein adding an entry includes: determining whether there is sufficient memory to add the new entry; and if there is not sufficient memory, adding the new entry according to a replacement policy. 25. The method of claim 24 wherein the replacement policy adds the new entry by deleting a least recently used entry of the EC cache table. | 0.5 |
9,959,866 | 1 | 4 | 1. A computer implemented speech recognition method for responding to user's speech comprising: acquiring, by a processor, speech information indicating content of user's speech; identifying, by the processor, a primary node corresponding to the speech information from multiple nodes which are stored in a memory, the multiple nodes being necessary for performing a task of generating a response sentence to the user's speech while associating the multiple nodes with each other; determining, by the processor, whether each of weight values each related to multiple secondary nodes associated with the identified primary node is larger than a predetermined value or not; when a weight value related to one secondary node is determined to be larger than the predetermined value, selecting the one secondary node from the multiple secondary nodes, generating the response sentence which asks to a user whether a content corresponding to the selected one secondary node is needed or not, and outputting the response sentence to the user using a speaker; when each of weight values related to two or more secondary nodes is determined to be larger than the predetermined value, selecting the two or more secondary nodes from the multiple secondary nodes, generating the response sentence which asks to the user to select one of multiple contents, each of the multiple contents corresponding to each of the two or more secondary nodes, and outputting the response sentence to the user using the speaker; and when each of the weight values is determined not to be larger than the predetermined value, generating the response sentence which asks to the user what is needed related to the identified primary node, and outputting the response sentence to the user using the speaker. | 1. A computer implemented speech recognition method for responding to user's speech comprising: acquiring, by a processor, speech information indicating content of user's speech; identifying, by the processor, a primary node corresponding to the speech information from multiple nodes which are stored in a memory, the multiple nodes being necessary for performing a task of generating a response sentence to the user's speech while associating the multiple nodes with each other; determining, by the processor, whether each of weight values each related to multiple secondary nodes associated with the identified primary node is larger than a predetermined value or not; when a weight value related to one secondary node is determined to be larger than the predetermined value, selecting the one secondary node from the multiple secondary nodes, generating the response sentence which asks to a user whether a content corresponding to the selected one secondary node is needed or not, and outputting the response sentence to the user using a speaker; when each of weight values related to two or more secondary nodes is determined to be larger than the predetermined value, selecting the two or more secondary nodes from the multiple secondary nodes, generating the response sentence which asks to the user to select one of multiple contents, each of the multiple contents corresponding to each of the two or more secondary nodes, and outputting the response sentence to the user using the speaker; and when each of the weight values is determined not to be larger than the predetermined value, generating the response sentence which asks to the user what is needed related to the identified primary node, and outputting the response sentence to the user using the speaker. 4. A non-transitory medium having thereon a program for causing a processor to execute operations included in the method of claim 1 . | 0.909892 |
10,154,047 | 1 | 4 | 1. A method comprising: receiving event data associated with network activities, wherein the event data comprises machine data; evaluating event data based on a machine learning model utilizing historical data pertaining to evaluations of past events; identifying at least one anomaly automatically determined from machine learning on the event data; identifying at least one threat automatically determined from machine learning on the event data and the identified at least one anomaly, wherein a threat is associated with each identified anomaly that, individually or in combination, triggered the determination of the threat; and upon selection by a user, via a graphical user interface, of an identified threat, generating a kill chain view associated with the threat, wherein the kill chain view includes a plurality of stages, and, for each stage, the kill chain view lists each type of identified anomaly associated with each stage of the kill chain and the number of anomalies of each type, wherein the listing of comprises a link for each anomaly type; upon selection by the user, via a graphical user interface, of the link for a selected anomaly type, generating a listing of all anomalies of the selected type, including a link for each anomaly; upon selection by the user of the link for a selected anomaly, generating a prompt to tag the anomaly for subsequent tracking; and upon receiving input from the user regarding the identified threat based upon the anomalies in the generated kill chain view, providing feedback for training the machine learning model. | 1. A method comprising: receiving event data associated with network activities, wherein the event data comprises machine data; evaluating event data based on a machine learning model utilizing historical data pertaining to evaluations of past events; identifying at least one anomaly automatically determined from machine learning on the event data; identifying at least one threat automatically determined from machine learning on the event data and the identified at least one anomaly, wherein a threat is associated with each identified anomaly that, individually or in combination, triggered the determination of the threat; and upon selection by a user, via a graphical user interface, of an identified threat, generating a kill chain view associated with the threat, wherein the kill chain view includes a plurality of stages, and, for each stage, the kill chain view lists each type of identified anomaly associated with each stage of the kill chain and the number of anomalies of each type, wherein the listing of comprises a link for each anomaly type; upon selection by the user, via a graphical user interface, of the link for a selected anomaly type, generating a listing of all anomalies of the selected type, including a link for each anomaly; upon selection by the user of the link for a selected anomaly, generating a prompt to tag the anomaly for subsequent tracking; and upon receiving input from the user regarding the identified threat based upon the anomalies in the generated kill chain view, providing feedback for training the machine learning model. 4. The method of claim 1 , wherein the stages of the kill chain include intrusion, expansion, and exfiltration stages, and the kill chain view includes dates that the intrusion and expansion stages each began and concluded and the date that the exfiltration occurred. | 0.854417 |
9,092,485 | 1 | 4 | 1. A method comprising, by a computing device: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; generating a plurality of structured queries that each comprise references to one or more nodes of the plurality of nodes and one or more edges of the plurality of edges, wherein at least one of the structured queries is a dynamic query comprising a reference to one or more updates to the social graph; and sending one or more of the generated structured queries to the first user for display on a page currently accessed by the first user, wherein at least one of the sent structured queries is a dynamic query. | 1. A method comprising, by a computing device: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; generating a plurality of structured queries that each comprise references to one or more nodes of the plurality of nodes and one or more edges of the plurality of edges, wherein at least one of the structured queries is a dynamic query comprising a reference to one or more updates to the social graph; and sending one or more of the generated structured queries to the first user for display on a page currently accessed by the first user, wherein at least one of the sent structured queries is a dynamic query. 4. The method of claim 1 , wherein the one or more updates to the social graph comprise trending activity on the online social network. | 0.829114 |
7,792,883 | 11 | 12 | 11. The method of claim 1 , wherein the identifying of the geographical feature documents includes determining a score for each of the geographical feature documents. | 11. The method of claim 1 , wherein the identifying of the geographical feature documents includes determining a score for each of the geographical feature documents. 12. The method of claim 11 , wherein providing results includes providing a single geographical feature or location if a best score for a corresponding geographical feature document is greater than a pre-determined multiple of a next best score for a next geographical feature document in a top-N ranking of the geographical feature documents. | 0.5 |
8,805,781 | 1 | 2 | 1. A computerized method of presenting documents to an end user comprising: a) identifying in a source document, in a computerized system, at least one quoted text portion quoted by a quoting document, leaving a non-quoted text portion that was not quoted by any quoting document, wherein the quoted text portion and the non-quoted text portion both have a context in which each portion is found in the source document, and wherein the quoting document indicates that the source document is the source of the quote; b) storing in the computerized system, in association with the source document, the fact that the quoted text portion has been quoted by the quoting document along with the location of the quoted text portion in the source document; c) recalling the stored location of the quoted text portion when displaying the source document without accessing the quoting document; d) highlighting the quoted text portion, based on the stored location recalled in step c), during the display of the source document through a computerized interface to visually distinguish the quoted text portion as different than the non-quoted text portion, wherein a technique for the highlighting is selected from a set comprising changing a color of a font for displayed text, creating a different colored background for displayed text, and otherwise visually emphasizing the importance of displayed text; e) receiving a user selection of the quoted text portion; and f) displaying a list of quoting documents that quote the selected quoted text portion. | 1. A computerized method of presenting documents to an end user comprising: a) identifying in a source document, in a computerized system, at least one quoted text portion quoted by a quoting document, leaving a non-quoted text portion that was not quoted by any quoting document, wherein the quoted text portion and the non-quoted text portion both have a context in which each portion is found in the source document, and wherein the quoting document indicates that the source document is the source of the quote; b) storing in the computerized system, in association with the source document, the fact that the quoted text portion has been quoted by the quoting document along with the location of the quoted text portion in the source document; c) recalling the stored location of the quoted text portion when displaying the source document without accessing the quoting document; d) highlighting the quoted text portion, based on the stored location recalled in step c), during the display of the source document through a computerized interface to visually distinguish the quoted text portion as different than the non-quoted text portion, wherein a technique for the highlighting is selected from a set comprising changing a color of a font for displayed text, creating a different colored background for displayed text, and otherwise visually emphasizing the importance of displayed text; e) receiving a user selection of the quoted text portion; and f) displaying a list of quoting documents that quote the selected quoted text portion. 2. The method of claim 1 , wherein the step of visually indicating the quoted text portion is accomplished by: i) creating a list of all quoted text portions identified in the source document, and ii) displaying the list of all quoted text portions outside of the context of the source document while also displaying the entire source document including the quoted text portions in context. | 0.702744 |
8,126,887 | 11 | 17 | 11. A method implemented on a computer, comprising: storing a plurality of reports in a repository, wherein each report includes information automatically retrieved from a data source, where the information is structured in accordance with a report schema that specifies the form in which the information should be presented, wherein the report schema defines separate report elements as structural components found inside a report, the report interpreting the information from the data source and performs calculations based on at least one calculation model; extracting, from each report of the plurality of reports in the report repository, report element instance context metadata and report element instance context data to define indexed fields, wherein the report element instance context metadata specifies metadata that affects evaluation of a report element instance according to the at least one calculation model including context with information used to calculate a report element instance and the report element instance context data specifies data that affects evaluation of the report element instance; receiving a search query; applying the search query against the indexed fields; and compiling search query results to produce a list of relevant report element instances, wherein each report element instance is a single occurrence of a report element in a report and reports are ranked based on a composite ranking factor, the composite ranking factor being compiled from two or more ranking methods including a method based on a report element instance's level of hierarchy in a report or sub-report. | 11. A method implemented on a computer, comprising: storing a plurality of reports in a repository, wherein each report includes information automatically retrieved from a data source, where the information is structured in accordance with a report schema that specifies the form in which the information should be presented, wherein the report schema defines separate report elements as structural components found inside a report, the report interpreting the information from the data source and performs calculations based on at least one calculation model; extracting, from each report of the plurality of reports in the report repository, report element instance context metadata and report element instance context data to define indexed fields, wherein the report element instance context metadata specifies metadata that affects evaluation of a report element instance according to the at least one calculation model including context with information used to calculate a report element instance and the report element instance context data specifies data that affects evaluation of the report element instance; receiving a search query; applying the search query against the indexed fields; and compiling search query results to produce a list of relevant report element instances, wherein each report element instance is a single occurrence of a report element in a report and reports are ranked based on a composite ranking factor, the composite ranking factor being compiled from two or more ranking methods including a method based on a report element instance's level of hierarchy in a report or sub-report. 17. The method according to claim 11 wherein the search query is received from a user. | 0.768817 |
9,047,873 | 18 | 19 | 18. A method comprising: converting spoken words and informative sounds of a first user wearing a first self-contained breathing apparatus into a voice signal; converting the voice signal into a text message, wherein the text message includes text identifying the first user as originator of the voice signal; and transmitting the text message to a second user, the transmitted text message, being displayed for the second user on or adjacent to a protective facemask of a second self-contained breathing apparatus. | 18. A method comprising: converting spoken words and informative sounds of a first user wearing a first self-contained breathing apparatus into a voice signal; converting the voice signal into a text message, wherein the text message includes text identifying the first user as originator of the voice signal; and transmitting the text message to a second user, the transmitted text message, being displayed for the second user on or adjacent to a protective facemask of a second self-contained breathing apparatus. 19. The method of claim 18 , wherein: a microphone of the first self-contained breathing apparatus converts the spoken words and informative sounds of the first user into the voice signal; a voice-to-text processor of the first self-contained breathing apparatus converts the voice signal into the text message; and a transmitter of the first self-contained breathing apparatus transmits the text message to the second user. | 0.5 |
7,475,015 | 11 | 16 | 11. A system for speech recognition, comprising: a speech recognition engine configured to generate a set of likely hypotheses using a speech recognition method for recognizing speech; a unified language model including a semantic language model and a lexical language model configured for rescoring the likely hypotheses to improve recognition results by using sentence-based semantic content and lexical content wherein the unified language model is trained by including a unigram feature, a bigram feature, a trigram feature, a current active parent label (Li), a number of tokens (Ni) to the left since current parent label (Li) starts, a previous closed constituent label (Oi), a number of tokens (Mi) to the left after the previous closed constituent label finishes, and a number of questions to classify parser tree entries, wherein the questions include a default, (wj−1), (wj−1, wj−2), (Li), (Li,Ni), (Li,Ni, wj−1), and (Oi,Mi), where w represents a word and j is and index representing word position to compute word probabilities; and the speech recognition engine configured to score parse trees to identify a best sentence according to the sentences' parse tree by employing semantic information and lexical information in the parse tree to clarify the recognized speech. | 11. A system for speech recognition, comprising: a speech recognition engine configured to generate a set of likely hypotheses using a speech recognition method for recognizing speech; a unified language model including a semantic language model and a lexical language model configured for rescoring the likely hypotheses to improve recognition results by using sentence-based semantic content and lexical content wherein the unified language model is trained by including a unigram feature, a bigram feature, a trigram feature, a current active parent label (Li), a number of tokens (Ni) to the left since current parent label (Li) starts, a previous closed constituent label (Oi), a number of tokens (Mi) to the left after the previous closed constituent label finishes, and a number of questions to classify parser tree entries, wherein the questions include a default, (wj−1), (wj−1, wj−2), (Li), (Li,Ni), (Li,Ni, wj−1), and (Oi,Mi), where w represents a word and j is and index representing word position to compute word probabilities; and the speech recognition engine configured to score parse trees to identify a best sentence according to the sentences' parse tree by employing semantic information and lexical information in the parse tree to clarify the recognized speech. 16. The system as recited in claim 11 , wherein the semantic model is trained by including history parameters and history questions wherein the history parameters include a previous word (wj−1), a previous word of the previous word (wj−2), a parent constituent label (L), a number of tokens (N) to the left since L starts, a previous closed constituent label (O), a number of tokens (M) to the left after O finishes, and a grandparent label (G). | 0.5 |
7,668,888 | 60 | 61 | 60. The computer-readable medium of claim 53 , wherein the instructions are configured further to cause the processor to store the readable object as a non-permanently stored readable object. | 60. The computer-readable medium of claim 53 , wherein the instructions are configured further to cause the processor to store the readable object as a non-permanently stored readable object. 61. The computer-readable medium of claim 60 , wherein the instructions are configured further to cause the processor to provide an index from the non-permanently stored readable object. | 0.5 |
9,959,260 | 1 | 4 | 1. A method comprising: updating a grammar based on a searchable plurality of presentation source files stored on a storage device connected to a presentation device via a network, to yield an updated grammar, wherein the searchable plurality of presentation source files is processed by extracting content from each searchable presentation source file to generate: (1) a web-based form of each searchable presentation source file; (2) a list of key phrases; and (3) a corpus of all sentences that appear in all the searchable presentation source files; receiving, from a user, a spoken natural language content request for a presentation source file from the searchable plurality of presentation source files; identifying a list of presentation source files in the searchable plurality of presentation source files, wherein the list of presentation source files is identified by using the updated grammar; receiving, from the user, input identifying the presentation source file from the list of presentation source files, wherein the input is in a modality distinct from speech; and adding the presentation source file to a deck for use in a presentation using the presentation device. | 1. A method comprising: updating a grammar based on a searchable plurality of presentation source files stored on a storage device connected to a presentation device via a network, to yield an updated grammar, wherein the searchable plurality of presentation source files is processed by extracting content from each searchable presentation source file to generate: (1) a web-based form of each searchable presentation source file; (2) a list of key phrases; and (3) a corpus of all sentences that appear in all the searchable presentation source files; receiving, from a user, a spoken natural language content request for a presentation source file from the searchable plurality of presentation source files; identifying a list of presentation source files in the searchable plurality of presentation source files, wherein the list of presentation source files is identified by using the updated grammar; receiving, from the user, input identifying the presentation source file from the list of presentation source files, wherein the input is in a modality distinct from speech; and adding the presentation source file to a deck for use in a presentation using the presentation device. 4. The method of claim 1 , wherein the list of key phrases is used to populate a menu of key phrases available to the user. | 0.823276 |
8,068,008 | 8 | 13 | 8. A method for managing credentialing data for a plurality of agencies, each of the plurality of agencies providing an emergency response service, the method comprising: storing credentialing data via a data store; generating a skill comparison request at a credentialing terminal in response to input from a user associated with an agency within a first jurisdiction, the skill comparison request comprising identification data for a particular emergency responder associated with a second jurisdiction; retrieving credentialing data at a credentialing computing device from the data store; comparing the identification data to the retrieved credentialing data to verify the identity of the particular emergency responder; retrieving first credentialing data at the credentialing computing device from the data store for the particular emergency responder, the particular emergency responder associated with a particular skill category; retrieving second credentialing data at the credentialing computing device from the data store for other emergency responders in the first jurisdiction associated with the particular skill category; comparing the first credentialing data to the second credentialing data to identify discrepancies; and generating the discrepancies for display. | 8. A method for managing credentialing data for a plurality of agencies, each of the plurality of agencies providing an emergency response service, the method comprising: storing credentialing data via a data store; generating a skill comparison request at a credentialing terminal in response to input from a user associated with an agency within a first jurisdiction, the skill comparison request comprising identification data for a particular emergency responder associated with a second jurisdiction; retrieving credentialing data at a credentialing computing device from the data store; comparing the identification data to the retrieved credentialing data to verify the identity of the particular emergency responder; retrieving first credentialing data at the credentialing computing device from the data store for the particular emergency responder, the particular emergency responder associated with a particular skill category; retrieving second credentialing data at the credentialing computing device from the data store for other emergency responders in the first jurisdiction associated with the particular skill category; comparing the first credentialing data to the second credentialing data to identify discrepancies; and generating the discrepancies for display. 13. The method of claim 8 further comprising generating the skill comparison request at the administrative computing device. | 0.858447 |
7,519,568 | 1 | 3 | 1. A computer-implemented method comprising: selecting at least one rule included in an operational knowledge associated with an application being monitored; associating, one or more playbook-based tasks, playbook-based views, or playbook-based links with the at least one rule, the playbook-based tasks, playbook-based views, and playbook-based links being for one or more of diagnosing, resolving, and verifying a problem associated with the application; and generating an integrated management pack responsive to the selecting and the associating, the integrated management pack enabling sharing of information between the operational knowledge and the one or more playbook-based tasks, the playbook-based views, or the playbook-based links. | 1. A computer-implemented method comprising: selecting at least one rule included in an operational knowledge associated with an application being monitored; associating, one or more playbook-based tasks, playbook-based views, or playbook-based links with the at least one rule, the playbook-based tasks, playbook-based views, and playbook-based links being for one or more of diagnosing, resolving, and verifying a problem associated with the application; and generating an integrated management pack responsive to the selecting and the associating, the integrated management pack enabling sharing of information between the operational knowledge and the one or more playbook-based tasks, the playbook-based views, or the playbook-based links. 3. The method of claim 1 , wherein at least one task of the playbook-based tasks is a context aware task that executes in view of automatically provided context associated with the problem. | 0.560465 |
9,436,662 | 16 | 22 | 16. An apparatus comprising: one or more data processors; and a memory, coupled to the processor that includes code stored therein and executable by the one or more first data processors to configure a computer system into a machine for generating a computer readable document utilized for input into an application by: obtain a framework having definitions of a first set of rules for a first grammar level used for interpretation of binding specifications to bind a user interface object to an underlying object, wherein the application is incompatible with the first grammar level; perform a first transformation of the framework to generate the first set of rules for interpretation of the binding specifications in the first grammar level; perform a second transformation of the framework to generate a first presentation style for the first grammar level; obtain the binding specifications in the first grammar level, the binding specification conforming to the first set of rules; and apply the first set of rules and the first presentation style to the binding specification to generate the computer readable document having the output binding specifications in a second grammar level compatible with the application. | 16. An apparatus comprising: one or more data processors; and a memory, coupled to the processor that includes code stored therein and executable by the one or more first data processors to configure a computer system into a machine for generating a computer readable document utilized for input into an application by: obtain a framework having definitions of a first set of rules for a first grammar level used for interpretation of binding specifications to bind a user interface object to an underlying object, wherein the application is incompatible with the first grammar level; perform a first transformation of the framework to generate the first set of rules for interpretation of the binding specifications in the first grammar level; perform a second transformation of the framework to generate a first presentation style for the first grammar level; obtain the binding specifications in the first grammar level, the binding specification conforming to the first set of rules; and apply the first set of rules and the first presentation style to the binding specification to generate the computer readable document having the output binding specifications in a second grammar level compatible with the application. 22. The computer readable medium of claim 16 , wherein the binding specifications are user defined in extensible markup language (XML). | 0.78972 |
9,305,236 | 13 | 17 | 13. A computer-readable, non-transitory medium storing a computer program, wherein said computer program causes a computer to execute a process, the process comprising: acquiring an input image generated by reading a document; generating a histogram of valid pixels in the image; extracting continuous regions in the histogram and calculating a character string variance in the input image, based on a distance between a maximum value of classes of the histogram and a center of a continuous region closest to the maximum value, and distances between centers of the continuous regions adjacent to each other; and identifying, using a computer, a type of the document based on the character string variance. | 13. A computer-readable, non-transitory medium storing a computer program, wherein said computer program causes a computer to execute a process, the process comprising: acquiring an input image generated by reading a document; generating a histogram of valid pixels in the image; extracting continuous regions in the histogram and calculating a character string variance in the input image, based on a distance between a maximum value of classes of the histogram and a center of a continuous region closest to the maximum value, and distances between centers of the continuous regions adjacent to each other; and identifying, using a computer, a type of the document based on the character string variance. 17. The computer-readable, non-transitory medium according to claim 13 , the process further comprising identifying a text direction where characters printed in the document are aligned, wherein the type of the document is identified further based on the text direction. | 0.529617 |
9,754,591 | 6 | 7 | 6. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, obtaining first speech recognition results associated with a first user request; performing, using a first application, a first function responsive to the first user request based on the first speech recognition results, wherein performing the first function comprises presenting information in a first modality; generating, using the first application, contextual information regarding the first user request in a format associated with a second application, wherein the contextual information is not provided to the user in response to the first request; storing the contextual information and information regarding use of the contextual information in the format; obtaining second speech recognition results associated with a second user request; determining to perform a second function responsive to the second user request based on the second speech recognition results; and performing, using the second application, the second function based at least in part on the contextual information regarding the first user request and the information regarding use of the contextual information in the format, wherein performing the second function comprises presenting the contextual information in a second modality different than the first modality. | 6. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, obtaining first speech recognition results associated with a first user request; performing, using a first application, a first function responsive to the first user request based on the first speech recognition results, wherein performing the first function comprises presenting information in a first modality; generating, using the first application, contextual information regarding the first user request in a format associated with a second application, wherein the contextual information is not provided to the user in response to the first request; storing the contextual information and information regarding use of the contextual information in the format; obtaining second speech recognition results associated with a second user request; determining to perform a second function responsive to the second user request based on the second speech recognition results; and performing, using the second application, the second function based at least in part on the contextual information regarding the first user request and the information regarding use of the contextual information in the format, wherein performing the second function comprises presenting the contextual information in a second modality different than the first modality. 7. The computer-implemented method of claim 6 , wherein the contextual information comprises at least one of information regarding processing of the first user request, information regarding performance of the first function, information formatted for a different application; information formatted for a different modality; or metadata for consumption by a different application. | 0.732394 |
8,892,218 | 21 | 22 | 21. A method for distributed control of a process, comprising: accessing a multi-Boolean function block configured to receive a plurality of inputs, to perform multiple Boolean logical operations based on the inputs, and to output any one of a plurality of logical outputs based upon the Boolean logical operations, wherein the multi-Boolean function block comprises non-transitory code configured in an object oriented programming language, and wherein the plurality of inputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of inputs and as the plurality of individual inputs, and the plurality of logical outputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of logical outputs and as the plurality of individual logical outputs; configuring the multi-Boolean function block for a particular automation process, wherein configuring the multi-Boolean function block comprises: selectively configuring a plurality of memory registers from which the multi-Boolean function block reads the plurality of inputs as either the single bundle of the plurality of inputs or as the plurality of individual inputs based on input/output requirements of a low-level distributed automation device into which the multi-Boolean function block is to be downloaded; or selectively configuring a plurality of memory registers to which the multi-Boolean function block writes the plurality of logical outputs as either the single bundle of the plurality of logical outputs or as the plurality of individual logical output based on the input/output requirements of the low-level distributed automation device; and downloading the configured multi-Boolean function block into the low-level distributed automation device, wherein the low-level distributed automation device comprises an input/output terminal block, a push-button block, a relay, a motor drive, or a motor starter, and wherein the low-level distributed automation device is configured to control local operations of the low-level distributed automation device without communication with other automation devices. | 21. A method for distributed control of a process, comprising: accessing a multi-Boolean function block configured to receive a plurality of inputs, to perform multiple Boolean logical operations based on the inputs, and to output any one of a plurality of logical outputs based upon the Boolean logical operations, wherein the multi-Boolean function block comprises non-transitory code configured in an object oriented programming language, and wherein the plurality of inputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of inputs and as the plurality of individual inputs, and the plurality of logical outputs are accessible from the multi-Boolean function block as both a single bundle of the plurality of logical outputs and as the plurality of individual logical outputs; configuring the multi-Boolean function block for a particular automation process, wherein configuring the multi-Boolean function block comprises: selectively configuring a plurality of memory registers from which the multi-Boolean function block reads the plurality of inputs as either the single bundle of the plurality of inputs or as the plurality of individual inputs based on input/output requirements of a low-level distributed automation device into which the multi-Boolean function block is to be downloaded; or selectively configuring a plurality of memory registers to which the multi-Boolean function block writes the plurality of logical outputs as either the single bundle of the plurality of logical outputs or as the plurality of individual logical output based on the input/output requirements of the low-level distributed automation device; and downloading the configured multi-Boolean function block into the low-level distributed automation device, wherein the low-level distributed automation device comprises an input/output terminal block, a push-button block, a relay, a motor drive, or a motor starter, and wherein the low-level distributed automation device is configured to control local operations of the low-level distributed automation device without communication with other automation devices. 22. The method of claim 21 , comprising uploading the multi-Boolean function block from the low-level distributed automation device to a configuration station. | 0.5 |
6,161,092 | 26 | 27 | 26. A processor readable storage medium according to claim 25, wherein; said first audio file provides an entire description for said first value; and said second audio file provides a partial description for said first value. | 26. A processor readable storage medium according to claim 25, wherein; said first audio file provides an entire description for said first value; and said second audio file provides a partial description for said first value. 27. A processor readable storage medium according to claim 26, wherein said method further includes the steps of: building a program, said step of automatically presenting includes a step of presenting said program, said program includes said speech from said groups of files, said step of presenting said program includes displaying a map of roads, said map includes one or more incident markers, said step of presenting said program further includes playing said speech from said group of files while said map is displayed. | 0.514787 |
8,370,368 | 12 | 19 | 12. A computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising: defining one or more filter criteria based upon, at least in part, an organizational structure, a member of an organization associated with the organizational structure, and at least one tag that was at least one of added and edited by the member of the organization associated with the organizational structure, wherein the member of the organization associated with the organizational structure that at least one of added and edited the at least one tag is selected by a user; filtering a body of content based upon, at least in part, the defined filter criteria, wherein the body of content includes one or more of a document library, a tag repository, a threaded discussion, a wiki, and a blog, and wherein the tag repository includes a plurality of tags, each tag associated with at least one of web content, documents in the document library, and documents in a team space, wherein filtering includes selecting the at least one tag that was at least one of added and edited by the member of the organization associated with the organizational structure, and wherein the member meets the filter criteria based upon, at least in part, the organizational structure and the member that had at least one of added and edited the at least one tag; providing at least a portion of the filtered body of content, wherein the portion of the filtered body of content is associated with the member of the organization associated with the organizational structure that had at least one of added and edited the at least one tag, and wherein the member meets the filter criteria based upon, at least in part, the organizational structure and the at least one tag that was at least one of added and edited by the member of the organization associated with the organizational structure; and extracting contextually relevant information from the body of content filtered using the defined filter criteria. | 12. A computer program product residing on a non-transitory computer readable medium having a plurality of instructions stored thereon which, when executed by a processor, cause the processor to perform operations comprising: defining one or more filter criteria based upon, at least in part, an organizational structure, a member of an organization associated with the organizational structure, and at least one tag that was at least one of added and edited by the member of the organization associated with the organizational structure, wherein the member of the organization associated with the organizational structure that at least one of added and edited the at least one tag is selected by a user; filtering a body of content based upon, at least in part, the defined filter criteria, wherein the body of content includes one or more of a document library, a tag repository, a threaded discussion, a wiki, and a blog, and wherein the tag repository includes a plurality of tags, each tag associated with at least one of web content, documents in the document library, and documents in a team space, wherein filtering includes selecting the at least one tag that was at least one of added and edited by the member of the organization associated with the organizational structure, and wherein the member meets the filter criteria based upon, at least in part, the organizational structure and the member that had at least one of added and edited the at least one tag; providing at least a portion of the filtered body of content, wherein the portion of the filtered body of content is associated with the member of the organization associated with the organizational structure that had at least one of added and edited the at least one tag, and wherein the member meets the filter criteria based upon, at least in part, the organizational structure and the at least one tag that was at least one of added and edited by the member of the organization associated with the organizational structure; and extracting contextually relevant information from the body of content filtered using the defined filter criteria. 19. The computer program product of claim 12 , wherein the instructions for filtering the body of content include instructions for searching the body of content and prioritizing one or more search results based upon, at least in part, the filter criteria. | 0.592652 |
9,619,439 | 11 | 16 | 11. A non-transitory machine-readable medium comprising instructions stored therein, which when executed by a system, cause the system to perform operations comprising: receiving a request from a client device to download a font; accessing the requested font, wherein the accessed font comprises a corresponding character map and a corresponding glyph table; creating a supported character list and a modified font based on the corresponding character map, wherein the modified font comprises a modified character map and a modified glyph table, and wherein the modified character map comprises placeholder data for at least one character of the accessed font; compressing the modified font; sending the supported character list and the compressed modified font to the client device; sending, to the client device after sending the supported character list and the compressed modified font to the client device, character data comprising character map data for the at least one character, glyph data for the at least one character, and location data for the character map data and glyph data, wherein the character map data is for merging the at least one character into the modified font based on the location data to replace the placeholder data for the at least one character in the modified font. | 11. A non-transitory machine-readable medium comprising instructions stored therein, which when executed by a system, cause the system to perform operations comprising: receiving a request from a client device to download a font; accessing the requested font, wherein the accessed font comprises a corresponding character map and a corresponding glyph table; creating a supported character list and a modified font based on the corresponding character map, wherein the modified font comprises a modified character map and a modified glyph table, and wherein the modified character map comprises placeholder data for at least one character of the accessed font; compressing the modified font; sending the supported character list and the compressed modified font to the client device; sending, to the client device after sending the supported character list and the compressed modified font to the client device, character data comprising character map data for the at least one character, glyph data for the at least one character, and location data for the character map data and glyph data, wherein the character map data is for merging the at least one character into the modified font based on the location data to replace the placeholder data for the at least one character in the modified font. 16. The non-transitory machine-readable medium of claim 11 , wherein the character data for merging into the modified font based on the supported character list is merged based on positional offset data provided by a server, and wherein merging the characters into the modified font creates a font functionally identical to the accessed font for the characters which have been received by the client device. | 0.586382 |
8,122,021 | 6 | 9 | 6. The method of claim 1 further comprising: determining a selected site from said web browser session; determining an expert rating for said selected site; and updating said user expertise level based on said expert rating. | 6. The method of claim 1 further comprising: determining a selected site from said web browser session; determining an expert rating for said selected site; and updating said user expertise level based on said expert rating. 9. The method of claim 6 , said selected site being selected from said search results. | 0.794258 |
7,752,035 | 2 | 5 | 2. A method for exchanging medical information between an originating application and a recipient application, the method comprising converting the data to be exchanged from the data format of the originating application into one or more medical information message structures, each of said message structures comprising an optional storyline keyword that sets the context for one or more subsequent statements, each of which statements comprises: a genre selected from a set of genre keywords representing message categories; a subject, comprising either a natural language string of one or more words or a nested statement; and optionally, one or more parametrized predicates comprising: a context joiner selected from a set of context joiner keywords; and a parameter comprising a natural language string of one or more words or a nested statement, the method comprising the steps of: marshalling of stored data to be exchanged from the data format of the originating application into one or a series of propositions in stored memory; carrying out a preliminary mapping step of each proposition to a designated empty cast comprising of a genre pragmas notated in natural language and a series of conjunctive pragmas notated in natural language; instantiating the empty cast with the message contents by the mapping of medical codes and message content of the proposition into natural language equivalents; inserting said natural language proposition equivalents into the empty cast by inserting subject content of the proposition into a space between a genre pragma and a first conjunctive pragma, and inserting clausal content of the proposition into associated conjunctive pragmas, so as to return a human and computer readable health proposition; batching a plurality of said health propositions into a message cascade to eliminate repeating a pragma common genre pragma with multiple propositions, so to produce a human-and computer-readable medical message; cuing said message cascade by designated begin and end pragmas, to provide the required medical information message structure. | 2. A method for exchanging medical information between an originating application and a recipient application, the method comprising converting the data to be exchanged from the data format of the originating application into one or more medical information message structures, each of said message structures comprising an optional storyline keyword that sets the context for one or more subsequent statements, each of which statements comprises: a genre selected from a set of genre keywords representing message categories; a subject, comprising either a natural language string of one or more words or a nested statement; and optionally, one or more parametrized predicates comprising: a context joiner selected from a set of context joiner keywords; and a parameter comprising a natural language string of one or more words or a nested statement, the method comprising the steps of: marshalling of stored data to be exchanged from the data format of the originating application into one or a series of propositions in stored memory; carrying out a preliminary mapping step of each proposition to a designated empty cast comprising of a genre pragmas notated in natural language and a series of conjunctive pragmas notated in natural language; instantiating the empty cast with the message contents by the mapping of medical codes and message content of the proposition into natural language equivalents; inserting said natural language proposition equivalents into the empty cast by inserting subject content of the proposition into a space between a genre pragma and a first conjunctive pragma, and inserting clausal content of the proposition into associated conjunctive pragmas, so as to return a human and computer readable health proposition; batching a plurality of said health propositions into a message cascade to eliminate repeating a pragma common genre pragma with multiple propositions, so to produce a human-and computer-readable medical message; cuing said message cascade by designated begin and end pragmas, to provide the required medical information message structure. 5. A method according to claim 2 , further comprising the steps of: communicating the messages to the recipient application; and converting the messages to the data format of the recipient application. | 0.570513 |
9,720,974 | 9 | 10 | 9. A computerized system, comprising: memory that stores computer-executable instructions; and at least one processor configured to access the memory, the at least one processor configured to execute the computer-executable instructions to collectively at least: identify a query submitted by one or more users of an electronic marketplace and at least one first action taken with respect to the query; obtain a fingerprint information stored in a query classification database, the fingerprint information including information on relationships between actions performed in relation to a plurality of previous search sessions, as well as time information for each of the actions performed, wherein the time information comprises an average amount of time between the actions performed; determine a fingerprint for the query based at least in part on the fingerprint information and the at least one first action taken with respect to the query, the fingerprint for the query comprising a sequence of actions performed in relation to at least one previous search session; identify at least one second action from the determined fingerprint for the query, the at least one second action having been performed by a maximum number of the one or more users with respect to the query; generate one or more interactive regions configured to anticipate execution of the at least one second action; and modify, after passage of the average amount of time comprising the time information, a user experience to reflect the at least one second action by presenting the one or more interactive regions with the electronic marketplace. | 9. A computerized system, comprising: memory that stores computer-executable instructions; and at least one processor configured to access the memory, the at least one processor configured to execute the computer-executable instructions to collectively at least: identify a query submitted by one or more users of an electronic marketplace and at least one first action taken with respect to the query; obtain a fingerprint information stored in a query classification database, the fingerprint information including information on relationships between actions performed in relation to a plurality of previous search sessions, as well as time information for each of the actions performed, wherein the time information comprises an average amount of time between the actions performed; determine a fingerprint for the query based at least in part on the fingerprint information and the at least one first action taken with respect to the query, the fingerprint for the query comprising a sequence of actions performed in relation to at least one previous search session; identify at least one second action from the determined fingerprint for the query, the at least one second action having been performed by a maximum number of the one or more users with respect to the query; generate one or more interactive regions configured to anticipate execution of the at least one second action; and modify, after passage of the average amount of time comprising the time information, a user experience to reflect the at least one second action by presenting the one or more interactive regions with the electronic marketplace. 10. The system of claim 9 , wherein the at least one processor is configured to execute the computer-executable instructions to determine the fingerprint for the query by comparing the fingerprint information of a plurality of queries in the query classification database to one or more search terms identified in the query. | 0.5 |
6,012,367 | 2 | 3 | 2. A document trimming apparatus as defined in claim 1 including at least one actuator located underneath said table and operably connected to said document positioning mechanism for actuating said document positioning mechanism. | 2. A document trimming apparatus as defined in claim 1 including at least one actuator located underneath said table and operably connected to said document positioning mechanism for actuating said document positioning mechanism. 3. A document trimming apparatus as defined in claim 2 including a controller for controlling said at least one actuator. | 0.5 |
9,483,573 | 10 | 15 | 10. A computer program product for generating an audio summary of a portion of an electronic document, the computer program product comprising one or more computer-readable tangible storage devices and a plurality of program instructions stored on at least one of the one or more computer-readable tangible storage devices, the plurality of program instructions comprising: program instructions to receive an electronic document; program instructions to identify content and location of a plurality of document elements included in the electronic document; program instructions to create a Document Object Model (DOM) that hierarchically organizes the document elements; program instructions to classify one or more pluralities of the document elements into respective collections based on the hierarchical organization of each plurality of document elements in the DOM, each collection having an associated name; program instructions to generate of audio objects corresponding to the text information within each of the document elements and each collection name; program instructions to render the electronic document for display on a display screen, and displaying the rendered document on a display screen; program instructions to receive user input indicating a focus position within the displayed electronic document; program instructions to generate an audio signal that includes one or more of the based on the proximity to the focus position of the corresponding document elements within a predetermined range from the focus position, wherein if a collection of document elements is located near the boundary of the predetermined range, the audio object corresponding to the collection name will be included in the audio signal, and if the collection of document elements is in the immediate vicinity of the focus position, the audio objects corresponding to the document elements will be included in the audio signal; and program instructions to render the audio signal to the user. | 10. A computer program product for generating an audio summary of a portion of an electronic document, the computer program product comprising one or more computer-readable tangible storage devices and a plurality of program instructions stored on at least one of the one or more computer-readable tangible storage devices, the plurality of program instructions comprising: program instructions to receive an electronic document; program instructions to identify content and location of a plurality of document elements included in the electronic document; program instructions to create a Document Object Model (DOM) that hierarchically organizes the document elements; program instructions to classify one or more pluralities of the document elements into respective collections based on the hierarchical organization of each plurality of document elements in the DOM, each collection having an associated name; program instructions to generate of audio objects corresponding to the text information within each of the document elements and each collection name; program instructions to render the electronic document for display on a display screen, and displaying the rendered document on a display screen; program instructions to receive user input indicating a focus position within the displayed electronic document; program instructions to generate an audio signal that includes one or more of the based on the proximity to the focus position of the corresponding document elements within a predetermined range from the focus position, wherein if a collection of document elements is located near the boundary of the predetermined range, the audio object corresponding to the collection name will be included in the audio signal, and if the collection of document elements is in the immediate vicinity of the focus position, the audio objects corresponding to the document elements will be included in the audio signal; and program instructions to render the audio signal to the user. 15. The computer program product of claim 10 , wherein the predetermined range from the focus position is defined by a circle having a center at the focus position. | 0.848987 |
8,468,494 | 1 | 2 | 1. A method of editing textual displays of a web-based software application having multiple web pages and multiple text items, the method comprising: executing the web-based software application, the software application including a set of executable instructions for displaying web pages on a graphical user interface and allowing interaction therewith by a user, the software application including at least one secondary file providing resource bundles having a single key and text strings corresponding to text items, the executable instructions having an identifier for locating the single key and for calling the text strings for display on the web page; reading code for each text item which may be edited; receiving a selection of a text item to be edited by through a web page on which the text item is displayed; creating an edited text item based on edits to the text item on the web page; saving the edited text item to the secondary file, wherein the single key of the secondary file identifies text items that are displayed a plurality of times on the web page; and dynamically displaying the edited text item in place of the text item on the web page using the single key for a plurality of users across a distributed network without reloading or refreshing the web page by the users. | 1. A method of editing textual displays of a web-based software application having multiple web pages and multiple text items, the method comprising: executing the web-based software application, the software application including a set of executable instructions for displaying web pages on a graphical user interface and allowing interaction therewith by a user, the software application including at least one secondary file providing resource bundles having a single key and text strings corresponding to text items, the executable instructions having an identifier for locating the single key and for calling the text strings for display on the web page; reading code for each text item which may be edited; receiving a selection of a text item to be edited by through a web page on which the text item is displayed; creating an edited text item based on edits to the text item on the web page; saving the edited text item to the secondary file, wherein the single key of the secondary file identifies text items that are displayed a plurality of times on the web page; and dynamically displaying the edited text item in place of the text item on the web page using the single key for a plurality of users across a distributed network without reloading or refreshing the web page by the users. 2. The method of claim 1 further comprising overwriting the text strings in the resource bundle with the edited text item. | 0.828169 |
10,067,937 | 8 | 12 | 8. A system, comprising: a first computing device comprising at least one hardware processor; and program instructions stored in memory and executable in the first computing device that, when executed by the at least one hardware processor, cause the first computing device to: generate audio data and video data collected by a microphone and a camera coupled to the first computing device for transmission to a second computing device, wherein the audio data embodies human speech associated with a first language; communicate the audio data and video data to at least one computing device over a network that provides at least a portion of the audio data and the video data to the second computing device through a data stream, wherein the at least one computing device is configured to: perform a language translation using the audio data where the speech associated with the first language is translated to a translation output associated with a second language; determine a time delay needed for the at least one computing device to complete the language translation where the speech made in the first language is translated to the translation output; and impose the time delay in a video signal for transmission to the first computing device; toggle an indicator in a display of the first computing device that indicates that the at least one computing device is performing the language translation in response to a signal being received from the at least one computing device; determine that a predefined amount of the speech associated with the first language has been translated to the translation output associated with the second language sufficient to prevent a discontinuity in speech segments; and in response to the predefined amount of the speech having been translated to the translation output, render the translation output and the video data on the first computing device contemporaneously as the translation output and the video data are rendered on the second computing device using the video signal. | 8. A system, comprising: a first computing device comprising at least one hardware processor; and program instructions stored in memory and executable in the first computing device that, when executed by the at least one hardware processor, cause the first computing device to: generate audio data and video data collected by a microphone and a camera coupled to the first computing device for transmission to a second computing device, wherein the audio data embodies human speech associated with a first language; communicate the audio data and video data to at least one computing device over a network that provides at least a portion of the audio data and the video data to the second computing device through a data stream, wherein the at least one computing device is configured to: perform a language translation using the audio data where the speech associated with the first language is translated to a translation output associated with a second language; determine a time delay needed for the at least one computing device to complete the language translation where the speech made in the first language is translated to the translation output; and impose the time delay in a video signal for transmission to the first computing device; toggle an indicator in a display of the first computing device that indicates that the at least one computing device is performing the language translation in response to a signal being received from the at least one computing device; determine that a predefined amount of the speech associated with the first language has been translated to the translation output associated with the second language sufficient to prevent a discontinuity in speech segments; and in response to the predefined amount of the speech having been translated to the translation output, render the translation output and the video data on the first computing device contemporaneously as the translation output and the video data are rendered on the second computing device using the video signal. 12. The system of claim 8 , wherein the program instructions executable in the first computing device are associated with an instance of a video messaging application installed on the first computing device. | 0.733247 |
8,612,087 | 6 | 7 | 6. A computer readable medium embodying a computer program product, said computer program product comprising: a detection program for detection of a component malfunction along a life of an internal combustion engine, said internal combustion engine comprising a cylinder and controlled by an Electronic Control Unit (ECU), the detection program configured to: define a pre-determined component malfunction classifier at the start of engine life; setting said pre-determined component malfunction classifier as active classifier, define a validity condition for said active classifier, acquire in real time a set of relevant signals relating to the operation of a component during the life of said internal combustion engine, feed said signals to said active classifier in order to determine the occurrence or not of a malfunction of said component and in case the validity condition of an actual classifier is not satisfied; define a new classifier using the most recent relevant signals recorded by said ECU; and substitute the actual classifier with said new classifier, wherein a search for a new classifier is performed continuously by the ECU during the life of said internal combustion engine and said validity condition is satisfied if an absolute value of a difference between the original variance of the signals pertaining to a regular functioning of said component and the variance of the signals calculated using the most recent relevant signals pertaining to a regular functioning of said component is lower than a minimum drift threshold or higher than a maximum drift threshold. | 6. A computer readable medium embodying a computer program product, said computer program product comprising: a detection program for detection of a component malfunction along a life of an internal combustion engine, said internal combustion engine comprising a cylinder and controlled by an Electronic Control Unit (ECU), the detection program configured to: define a pre-determined component malfunction classifier at the start of engine life; setting said pre-determined component malfunction classifier as active classifier, define a validity condition for said active classifier, acquire in real time a set of relevant signals relating to the operation of a component during the life of said internal combustion engine, feed said signals to said active classifier in order to determine the occurrence or not of a malfunction of said component and in case the validity condition of an actual classifier is not satisfied; define a new classifier using the most recent relevant signals recorded by said ECU; and substitute the actual classifier with said new classifier, wherein a search for a new classifier is performed continuously by the ECU during the life of said internal combustion engine and said validity condition is satisfied if an absolute value of a difference between the original variance of the signals pertaining to a regular functioning of said component and the variance of the signals calculated using the most recent relevant signals pertaining to a regular functioning of said component is lower than a minimum drift threshold or higher than a maximum drift threshold. 7. The computer readable medium embodying the computer program product according to claim 6 , wherein said pre-determined classifier is defined with a training session in order to train said pre-determined component malfunction classifier to distinguish an occurrence of the malfunction of said component, said training session comprising an input into said pre-determined component malfunction classifier of a plurality of signals subdivided in signals pertaining to the malfunction of said component and signals pertaining to a regular functioning of said component. | 0.5 |
8,856,051 | 8 | 13 | 8. The computer-implemented method of claim 1 , wherein associating the first reduced cluster weight metadata as metadata of the second one of the videos comprises: obtaining the first reduced cluster weight metadata by scaling the cluster weights derived from user-supplied textual metadata of the first one of the videos by the degree of similarity; and responsive to the second one of the videos lacking user-supplied textual metadata, storing the first reduced cluster weight metadata in association with the second one of the videos. | 8. The computer-implemented method of claim 1 , wherein associating the first reduced cluster weight metadata as metadata of the second one of the videos comprises: obtaining the first reduced cluster weight metadata by scaling the cluster weights derived from user-supplied textual metadata of the first one of the videos by the degree of similarity; and responsive to the second one of the videos lacking user-supplied textual metadata, storing the first reduced cluster weight metadata in association with the second one of the videos. 13. The non-transitory computer-readable storage medium of claim 8 , wherein forming the training set for the object comprises: creating a similarity graph comprising: ones of the objects, and edges between pairs of the objects, the edges associated with the determined degrees of similarity of the pairs; computing path degrees of similarity between the object and other ones of the objects based on products of the degrees of similarity associated with the edges on a path between the object and the others one of the objects; and adding objects to the training set based on their computed path degrees of similarity with the object. | 0.5 |
7,545,758 | 12 | 13 | 12. A telecommunications server, comprising: a multimedia communication controller for interlacing multimedia conferences; and a collaboration controller operably coupled to said multimedia communication controller, said collaboration controller adapted to store a multimedia conference and play back selected portions of said multimedia conference according to user selected criteria based on user-defined recording cues and responsive to a user-defined index based on said user-defined and invocable recording cues, said recording cues being trainable to the collaboration controller by the user, the collaboration controller configured to mark a predetermined period around which the selected portions are recorded. | 12. A telecommunications server, comprising: a multimedia communication controller for interlacing multimedia conferences; and a collaboration controller operably coupled to said multimedia communication controller, said collaboration controller adapted to store a multimedia conference and play back selected portions of said multimedia conference according to user selected criteria based on user-defined recording cues and responsive to a user-defined index based on said user-defined and invocable recording cues, said recording cues being trainable to the collaboration controller by the user, the collaboration controller configured to mark a predetermined period around which the selected portions are recorded. 13. A telecommunications server in accordance with claim 12 , said collaboration controller adapted to select for storing a transcription of an audio portion of said multimedia conference. | 0.527638 |
8,838,435 | 8 | 11 | 8. Apparatus for processing a plurality of linguistic expressions, each linguistic expression originating from an originator, and each linguistic expression being a linguistic expression in which the originator of that linguistic expression expresses a respective sentiment with respect to one or more topics, the apparatus comprising one or more processors configured to: for each linguistic expression, detect one or more topics of interest addressed in that linguistic expression by the originator of that linguistic expression; for each linguistic expression, for each topic detected in that linguistic expression, assess a sentiment of the originator of that linguistic expression with respect to that topic; group the originators into one or more groups based on similarities between the originators' respective sets of detected topic-sentiment pairs; associate, with a given group, semantic information, wherein the semantic information associated with the given group relates to one or more feature selected from a group of features consisting of: properties of one or more members of that given group and the sets of topic-sentiment pairs of one or more of the members of that given group; and for a given originator, create or update a profile; wherein the given originator is a member of the given group; wherein the profile is created or updated such that it comprises attributes of the given originator; and wherein the attributes are dependent upon the given originator's membership in the given group and the semantic information associated with the given group. | 8. Apparatus for processing a plurality of linguistic expressions, each linguistic expression originating from an originator, and each linguistic expression being a linguistic expression in which the originator of that linguistic expression expresses a respective sentiment with respect to one or more topics, the apparatus comprising one or more processors configured to: for each linguistic expression, detect one or more topics of interest addressed in that linguistic expression by the originator of that linguistic expression; for each linguistic expression, for each topic detected in that linguistic expression, assess a sentiment of the originator of that linguistic expression with respect to that topic; group the originators into one or more groups based on similarities between the originators' respective sets of detected topic-sentiment pairs; associate, with a given group, semantic information, wherein the semantic information associated with the given group relates to one or more feature selected from a group of features consisting of: properties of one or more members of that given group and the sets of topic-sentiment pairs of one or more of the members of that given group; and for a given originator, create or update a profile; wherein the given originator is a member of the given group; wherein the profile is created or updated such that it comprises attributes of the given originator; and wherein the attributes are dependent upon the given originator's membership in the given group and the semantic information associated with the given group. 11. Apparatus according to claim 8 wherein associating the semantic information with the given group comprises using knowledge of a given topic and knowledge of a predominant sentiment with respect to that given topic of the members of the given group. | 0.701422 |
8,874,430 | 8 | 11 | 8. A method for communicating news content, comprising: receiving, by a computer processor, a multi-lingual text comprising Latin-based characters in a Latin-based language and non-Latin-based characters in a non-Latin-based language, wherein the multi-lingual text comprises information about a news content; converting, by the computer processor, the non-Latin-based characters in the multi-lingual text to index values to produce a pseudo text, wherein each of the non-Latin-based characters has a Unicode value two byte in length, wherein the index values are a single byte in length, wherein the conversion is based on a predefined mapping that converts the Unicode values of the non-Latin-based characters to index values having fewer digits than the corresponding Unicode values of the non-Latin-based characters, wherein the predefined mapping allocates at least 55 consecutive digital numbers for the index values, wherein the pseudo text includes the index values in co-existence with the Latin-based characters in a Latin-based language; encoding the pseudo text in a matrix-code symbol; enabling a tagline about the news content to be displayed on a TV screen; and enabling the display of the matrix-code symbol in conjunction with the description about the news content on the TV screen, wherein the matrix code is configured to be decoded to allow a user to find more detailed description than the tagline about the news content. | 8. A method for communicating news content, comprising: receiving, by a computer processor, a multi-lingual text comprising Latin-based characters in a Latin-based language and non-Latin-based characters in a non-Latin-based language, wherein the multi-lingual text comprises information about a news content; converting, by the computer processor, the non-Latin-based characters in the multi-lingual text to index values to produce a pseudo text, wherein each of the non-Latin-based characters has a Unicode value two byte in length, wherein the index values are a single byte in length, wherein the conversion is based on a predefined mapping that converts the Unicode values of the non-Latin-based characters to index values having fewer digits than the corresponding Unicode values of the non-Latin-based characters, wherein the predefined mapping allocates at least 55 consecutive digital numbers for the index values, wherein the pseudo text includes the index values in co-existence with the Latin-based characters in a Latin-based language; encoding the pseudo text in a matrix-code symbol; enabling a tagline about the news content to be displayed on a TV screen; and enabling the display of the matrix-code symbol in conjunction with the description about the news content on the TV screen, wherein the matrix code is configured to be decoded to allow a user to find more detailed description than the tagline about the news content. 11. The method of claim 8 , wherein the Latin-based language comprises English, French, Spanish, German, or Italian. | 0.778626 |
8,886,639 | 1 | 3 | 1. A computer-implemented method for performing a search of services, the method comprising: receiving a search string that includes multiple words and that a user inputs for searching services in a repository; searching a multi-document index using the search string, the multi-document index identifying, for each of the services, multiple documents that each reflect at least one aspect regarding the service; providing multiple results in response to the search of the multi-document index, each of the multiple results being associated with a corresponding service and the multiple documents identified in the multi-document index for the corresponding service; scoring the multiple results by providing, for each of the results: a first score that reflects an amount of the words from the search string that appear in any of the multiple documents that are associated with the result, and a second score that reflects a combination of: (i) one score that identifies an amount of the words from the search string that appear in a first one of the multiple documents that are associated with the result, and (ii) another score that identifies an amount of the words from the search string that appear in a second one of the multiple documents that are associated with the result; generating, for each of the results, a weighted score by weighting the first score and the second score for the result; ranking the results based on the weighted score that generated for each of the results; and presenting an outcome of the search of the multi-document index to the user in response to receiving the search string, wherein the ranked results are included in the outcome of the search. | 1. A computer-implemented method for performing a search of services, the method comprising: receiving a search string that includes multiple words and that a user inputs for searching services in a repository; searching a multi-document index using the search string, the multi-document index identifying, for each of the services, multiple documents that each reflect at least one aspect regarding the service; providing multiple results in response to the search of the multi-document index, each of the multiple results being associated with a corresponding service and the multiple documents identified in the multi-document index for the corresponding service; scoring the multiple results by providing, for each of the results: a first score that reflects an amount of the words from the search string that appear in any of the multiple documents that are associated with the result, and a second score that reflects a combination of: (i) one score that identifies an amount of the words from the search string that appear in a first one of the multiple documents that are associated with the result, and (ii) another score that identifies an amount of the words from the search string that appear in a second one of the multiple documents that are associated with the result; generating, for each of the results, a weighted score by weighting the first score and the second score for the result; ranking the results based on the weighted score that generated for each of the results; and presenting an outcome of the search of the multi-document index to the user in response to receiving the search string, wherein the ranked results are included in the outcome of the search. 3. The computer-implemented method of claim 1 , further comprising: parsing the search string to generate multiple words; using a first one of the multiple words parsed from the search string to generate a first list of results; using a second one of the multiple words parsed from the search string to generate a second list of results, wherein the second list of results is different from the first list of results; and combining the first list of results and the second list of results into a single result list. | 0.683661 |
8,335,791 | 42 | 44 | 42. One or more computer-readable storage media encoded with instructions that, when executed, cause a processor to perform acts comprising: receiving, via a network connection, a threshold parameter indicating a predetermined threshold similarity of subject matter and an input document associated with a new item available for purchase, the input document to be indexed into a search index file; comparing a subject matter of the input document to a subject matter of an existing document that relates to an item available for purchase and is already indexed into the search index file, wherein the structure of the input document includes at least two fields, the at least two fields each including content, and the predetermined threshold similarity of subject matter exists at least when a percentage of fields in a structure of the input document correspond to fields in a structure of the existing document; determining, based at least on the comparison, that the input document and the existing document meet the predetermined threshold similarity of subject matter; responsive to determining that the input document and the existing document meet the predetermined threshold similarity of subject matter, identifying text in the input document that is dissimilar to text in the existing document; designating any dissimilar text between the input document and the existing document as candidate synonyms; merging the candidate synonyms into the search index file, wherein the merging associates the dissimilar text as synonyms in the search index file; and indexing the input document into the search index file. | 42. One or more computer-readable storage media encoded with instructions that, when executed, cause a processor to perform acts comprising: receiving, via a network connection, a threshold parameter indicating a predetermined threshold similarity of subject matter and an input document associated with a new item available for purchase, the input document to be indexed into a search index file; comparing a subject matter of the input document to a subject matter of an existing document that relates to an item available for purchase and is already indexed into the search index file, wherein the structure of the input document includes at least two fields, the at least two fields each including content, and the predetermined threshold similarity of subject matter exists at least when a percentage of fields in a structure of the input document correspond to fields in a structure of the existing document; determining, based at least on the comparison, that the input document and the existing document meet the predetermined threshold similarity of subject matter; responsive to determining that the input document and the existing document meet the predetermined threshold similarity of subject matter, identifying text in the input document that is dissimilar to text in the existing document; designating any dissimilar text between the input document and the existing document as candidate synonyms; merging the candidate synonyms into the search index file, wherein the merging associates the dissimilar text as synonyms in the search index file; and indexing the input document into the search index file. 44. The one or more computer-readable storage media of claim 42 , wherein the comparing includes comparing text of the input document to text of the existing document. | 0.747734 |
9,779,728 | 11 | 12 | 11. A system for modifying a voice file comprising a plurality of words, the system comprising: a silence-detection module configured to detect silences in the voice file and to divide the voice file into multiple segments based on at least the detected silences, an identification module configured to: apply a language model to the voice file as a whole, the language model including a plurality of feature units, a preliminary punctuation state, and a preliminary weight of the preliminary punctuation state, each of the feature units including a word or phrase, a part of speech or sentence element of the word or phrase, the application of the language model to the voice file as a whole identifying in the voice file as a whole one or more first feature units of the plurality of feature units; and identifying in the segments one or more second feature units of the plurality of feature units; and a punctuation-addition module configured to: generate a first aggregate weight R1 based on a combination of the preliminary weights of the preliminary punctuation states corresponding to the identified one or more first feature units; apply the language model to the segments, the application of the language model to the segments to generate a second aggregate weight R2 including a combination of the preliminary weights of the preliminary punctuation states corresponding to the identified one or more second feature units; generate a third aggregate weight R3 determined according to R3=a×R1+(1−a)×R2 where 0<a<1; and modifying the voice file so as to include one or more final punctuations based on at least the third aggregate weight R3. | 11. A system for modifying a voice file comprising a plurality of words, the system comprising: a silence-detection module configured to detect silences in the voice file and to divide the voice file into multiple segments based on at least the detected silences, an identification module configured to: apply a language model to the voice file as a whole, the language model including a plurality of feature units, a preliminary punctuation state, and a preliminary weight of the preliminary punctuation state, each of the feature units including a word or phrase, a part of speech or sentence element of the word or phrase, the application of the language model to the voice file as a whole identifying in the voice file as a whole one or more first feature units of the plurality of feature units; and identifying in the segments one or more second feature units of the plurality of feature units; and a punctuation-addition module configured to: generate a first aggregate weight R1 based on a combination of the preliminary weights of the preliminary punctuation states corresponding to the identified one or more first feature units; apply the language model to the segments, the application of the language model to the segments to generate a second aggregate weight R2 including a combination of the preliminary weights of the preliminary punctuation states corresponding to the identified one or more second feature units; generate a third aggregate weight R3 determined according to R3=a×R1+(1−a)×R2 where 0<a<1; and modifying the voice file so as to include one or more final punctuations based on at least the third aggregate weight R3. 12. The system of claim 11 , wherein the punctuation-addition module includes: an aggregate-weight-determination component configured to determine the first aggregate weight R1 and the second aggregate weight R2; an aggregate-weight-integration component configured to generate the third aggregate weight R3; and a punctuation-addition component configured to modify the voice file. | 0.79011 |
9,026,701 | 30 | 31 | 30. The computer system of claim 27 , wherein the instructions further comprise: sending instructions for sending a response to the first request. | 30. The computer system of claim 27 , wherein the instructions further comprise: sending instructions for sending a response to the first request. 31. The computer system of claim 30 , wherein the response conforms to a response format defined in the first language. | 0.5 |
6,094,647 | 1 | 6 | 1. A document information search method for searching for specified text data containing a given search subject key word from a group of documents including document text data stored in advance, said method comprising the steps of: registering text data of said documents as a source file, generating a presearch file representative of component characters of the document text data in the source file, generating a search query component character file comprising character components of the given search subject key word, selecting as possible search documents for key word searching, selected ones of the documents having a presearch file including the character components of the search query component character file; and key word searching of the selected ones for the given search subject key word. | 1. A document information search method for searching for specified text data containing a given search subject key word from a group of documents including document text data stored in advance, said method comprising the steps of: registering text data of said documents as a source file, generating a presearch file representative of component characters of the document text data in the source file, generating a search query component character file comprising character components of the given search subject key word, selecting as possible search documents for key word searching, selected ones of the documents having a presearch file including the character components of the search query component character file; and key word searching of the selected ones for the given search subject key word. 6. The document information search method according to claim 1, wherein: generating a plurality of presearch files corresponding to a character string length extracted from said text file, and narrowing down an object text by presearching the presearch files for a short character string length extracted from said text file. | 0.767857 |
9,195,662 | 1 | 10 | 1. A method for displaying an associated informational entity on a computing device when producing a text document; wherein a set of informational entities is stored on the computing device; wherein the set of informational entities is stored with a corresponding plurality of association records; and wherein the association record corresponding to a first informational entity indicates an association and an association strength between the first informational entity and another informational entity; the method comprising: editing text of the text document on the computing device; automatically determining the first informational entity which is associated with a first portion of the edited text; and automatically displaying an indicia for the first informational entity on the display; wherein the step of determining the first informational entity comprises: determining a relevance score for at least two of the informational entities of the set of informational entities stored on the computing device; and determining the first informational entity as the informational entity having the highest relevance score; wherein the step of determining the first informational entity comprises: removing high frequency words from the first portion of the displayed text, thereby yielding a remaining text; determining the relevance score as a degree of overlap between the remaining text and a plurality of informational entities of the set of informational entities stored on the computing device; determining the first informational entity as the informational entity having the highest weighted degree of overlap; and wherein the high frequency words are stored in a list of high frequency words on the computing device; and/or the list of high frequency words comprises the words in a given language having a high frequency of occurrence within a text corpus of a given language. | 1. A method for displaying an associated informational entity on a computing device when producing a text document; wherein a set of informational entities is stored on the computing device; wherein the set of informational entities is stored with a corresponding plurality of association records; and wherein the association record corresponding to a first informational entity indicates an association and an association strength between the first informational entity and another informational entity; the method comprising: editing text of the text document on the computing device; automatically determining the first informational entity which is associated with a first portion of the edited text; and automatically displaying an indicia for the first informational entity on the display; wherein the step of determining the first informational entity comprises: determining a relevance score for at least two of the informational entities of the set of informational entities stored on the computing device; and determining the first informational entity as the informational entity having the highest relevance score; wherein the step of determining the first informational entity comprises: removing high frequency words from the first portion of the displayed text, thereby yielding a remaining text; determining the relevance score as a degree of overlap between the remaining text and a plurality of informational entities of the set of informational entities stored on the computing device; determining the first informational entity as the informational entity having the highest weighted degree of overlap; and wherein the high frequency words are stored in a list of high frequency words on the computing device; and/or the list of high frequency words comprises the words in a given language having a high frequency of occurrence within a text corpus of a given language. 10. The method of claim 1 , wherein the text document is an electronic mail being composed by a user of the computing device; and the displayed text is text from a “subject” line or a body portion of the electronic mail. | 0.789272 |
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