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8,090,080 | 2 | 3 | 2. The method of claim 1 , wherein disambiguating the received records includes identifying a single parent record associated with a first hierarchical category, and wherein the method further comprises: disambiguating a plurality of child records of the single parent record, wherein the plurality of child records are associated with a second hierarchical category. | 2. The method of claim 1 , wherein disambiguating the received records includes identifying a single parent record associated with a first hierarchical category, and wherein the method further comprises: disambiguating a plurality of child records of the single parent record, wherein the plurality of child records are associated with a second hierarchical category. 3. The method of claim 2 , wherein the first hierarchical category is associated with an entity and wherein the second hierarchical category is associated with a sub-entity within the entity. | 0.5 |
7,860,819 | 13 | 18 | 13. An apparatus, comprising: a processor; and a memory coupled to the processor and storing first data representing a semantic network, the semantic network representing a plurality of nodes, and a plurality of links interconnecting the nodes such that, for each of the links, one of the nodes is a subject node of the link, another of the nodes a target node of the link, and the respective link represents a verb between the corresponding subject and target nodes, at least some of the links each being conditioned by at least one variant, wherein the processor is configured to, in response to receiving second data representing one or more variants: determine a portion of the semantic network that contains fewer links than the semantic network depending upon which of the variants are included in the second data and which of the variants condition the at least some of the links, and generate third data based on the determined portion of the semantic network. | 13. An apparatus, comprising: a processor; and a memory coupled to the processor and storing first data representing a semantic network, the semantic network representing a plurality of nodes, and a plurality of links interconnecting the nodes such that, for each of the links, one of the nodes is a subject node of the link, another of the nodes a target node of the link, and the respective link represents a verb between the corresponding subject and target nodes, at least some of the links each being conditioned by at least one variant, wherein the processor is configured to, in response to receiving second data representing one or more variants: determine a portion of the semantic network that contains fewer links than the semantic network depending upon which of the variants are included in the second data and which of the variants condition the at least some of the links, and generate third data based on the determined portion of the semantic network. 18. The apparatus of claim 13 , wherein the semantic network further comprises a further link having one of the plurality of links as a subject of the further link and another of the plurality of links as a target of the further link. | 0.5 |
8,751,520 | 6 | 12 | 6. A method comprising receiving an initial query; selecting one or more additional queries relating to the initial query; determining a respective utility measure for each of the one or more additional queries, wherein the utility measure represents a likelihood that a respective additional query would be a final query submitted in a query session, wherein the utility measure is determined from a query graph that represents one or more query refinements from the initial query to one of the additional queries, wherein each particular query refinement in the graph has a respective associated weight that represents a likelihood of the particular query refinement being submitted in the query session; selecting an additional query from the one or more additional queries having a highest utility measure; and providing the selected additional query to a client device to be displayed along with search results associated with the initial query. | 6. A method comprising receiving an initial query; selecting one or more additional queries relating to the initial query; determining a respective utility measure for each of the one or more additional queries, wherein the utility measure represents a likelihood that a respective additional query would be a final query submitted in a query session, wherein the utility measure is determined from a query graph that represents one or more query refinements from the initial query to one of the additional queries, wherein each particular query refinement in the graph has a respective associated weight that represents a likelihood of the particular query refinement being submitted in the query session; selecting an additional query from the one or more additional queries having a highest utility measure; and providing the selected additional query to a client device to be displayed along with search results associated with the initial query. 12. The method of claim 6 , wherein each additional query includes at least a portion of the initial query. | 0.759009 |
8,090,157 | 1 | 3 | 1. A computer implemented eye detection system for detecting eyes in a digital image, the system comprising: a digital image capture device; and a processor, the processor including: a filter; a first eye candidate selector connected to the filter; a first profile validator connected to the eye candidate selector, the first profile validator including measurements of eye candidate pupil contours; a first eye candidate eliminator connected to the first profile validator and the first eye candidate selector; a second eye candidate selector connected to the first profile validator; a pair validator connected to the second eye candidate selector, the pair validator including a space measurer that determines if the first and second eye candidates are at an appropriate distance from each other; a second profile validator connected to the pair validator; and a second eye candidate eliminator connected to the second profile validator and the second eye candidate selector; wherein the first profile validator comprising a first profiler connected to the first eye candidate selector, and a first profile evaluator connected to the first profiler, the first eye candidate eliminator and the second eye candidate selector; wherein the second profile validator comprises a second profiler connected to the pair validator, and a second profile evaluator connected to the second profiler and the second eye candidate eliminator; wherein the first profiler comprises: a pupil region extractor connected to the first eye candidate selector; an adaptive thresholder connected to the pupil region extractor; a contours finder connected to the adaptive thresholder; a contour picker connected to the contours finder; a curve fitter connected to the contour picker; and a curve selector connected to the curve fitter and the first profile evaluator; and wherein the second profiler comprises: a pupil region extractor connected to the pair validator; an adaptive thresholder connected to the pupil region extractor; a contours finder connected to the adaptive thresholder; a contour picker connected to the contours finder; a curve fitter connected to the contour picker; and a curve selector connected to the curve fitter and the second profile evaluator. | 1. A computer implemented eye detection system for detecting eyes in a digital image, the system comprising: a digital image capture device; and a processor, the processor including: a filter; a first eye candidate selector connected to the filter; a first profile validator connected to the eye candidate selector, the first profile validator including measurements of eye candidate pupil contours; a first eye candidate eliminator connected to the first profile validator and the first eye candidate selector; a second eye candidate selector connected to the first profile validator; a pair validator connected to the second eye candidate selector, the pair validator including a space measurer that determines if the first and second eye candidates are at an appropriate distance from each other; a second profile validator connected to the pair validator; and a second eye candidate eliminator connected to the second profile validator and the second eye candidate selector; wherein the first profile validator comprising a first profiler connected to the first eye candidate selector, and a first profile evaluator connected to the first profiler, the first eye candidate eliminator and the second eye candidate selector; wherein the second profile validator comprises a second profiler connected to the pair validator, and a second profile evaluator connected to the second profiler and the second eye candidate eliminator; wherein the first profiler comprises: a pupil region extractor connected to the first eye candidate selector; an adaptive thresholder connected to the pupil region extractor; a contours finder connected to the adaptive thresholder; a contour picker connected to the contours finder; a curve fitter connected to the contour picker; and a curve selector connected to the curve fitter and the first profile evaluator; and wherein the second profiler comprises: a pupil region extractor connected to the pair validator; an adaptive thresholder connected to the pupil region extractor; a contours finder connected to the adaptive thresholder; a contour picker connected to the contours finder; a curve fitter connected to the contour picker; and a curve selector connected to the curve fitter and the second profile evaluator. 3. The system of claim 1 , wherein: the first eye candidate selector comprises: a ranking mechanism connected to the filter; an eye candidates extractor connected to the ranking mechanism; and a first eye candidate determiner connected to the eye candidate extractor, a first profiler and the first eye candidate eliminator; and the second eye candidate selector comprises: the ranking mechanism connected to the filter; the eye candidates extractor connected to the ranking mechanism; and a second eye candidate determiner connected to the first profile evaluator, the pair validator and the second eye candidate eliminator. | 0.5 |
9,633,002 | 1 | 4 | 1. A computer-implemented method, comprising: ingesting text data from a plurality of documents, the text data comprising a plurality of mentions corresponding to entities; determining a plurality of data features, comprising semantic features and syntactic features, for comparing a particular pair of mentions from the plurality of mentions; selectively activating a subset of features from the plurality of data features based on semantic and syntactic context of the particular pair of mentions within the text data; and determining, using weights associated with the activated subset of features and at least one computer implemented machine learning function, whether a first mention of the pair of mentions and second mention of the pair of mentions refer to the same real-world entity; responsive to determining that the first mention and second mention refer to the same real-world entity, resolving the first mention and second mention to the real-world entity; and outputting an indication that identifies the resolved first mention and second mention as being resolved to the real-world entity. | 1. A computer-implemented method, comprising: ingesting text data from a plurality of documents, the text data comprising a plurality of mentions corresponding to entities; determining a plurality of data features, comprising semantic features and syntactic features, for comparing a particular pair of mentions from the plurality of mentions; selectively activating a subset of features from the plurality of data features based on semantic and syntactic context of the particular pair of mentions within the text data; and determining, using weights associated with the activated subset of features and at least one computer implemented machine learning function, whether a first mention of the pair of mentions and second mention of the pair of mentions refer to the same real-world entity; responsive to determining that the first mention and second mention refer to the same real-world entity, resolving the first mention and second mention to the real-world entity; and outputting an indication that identifies the resolved first mention and second mention as being resolved to the real-world entity. 4. The method of claim 1 , wherein the semantic features comprise at least one of same-sentence, previous-sentence, next-sentence, and category match. | 0.810606 |
8,269,722 | 1 | 5 | 1. A gesture recognition system, comprising: an image pick-up device, for capturing an image data containing a hand image; a template database, for recording multiple gesture templates representing different gestures, wherein the gesture templates are classified by angles and are respectively stored in gesture template libraries of different angle classes; a processor, for communicating with the image pick-up device and obtaining the image data, finding out a skin part from the image data, producing a skin edge by using an edge detection means, and then classifying the skin edge into multiple edge parts of different angle classes according to angles of the skin edge; an operation engine, having multiple parallel operation units respectively for performing template matching at different angles, wherein the edge parts of different angle classes are respectively sent to different parallel operation units for template matching, so as to find out the gesture templates most resembling the edge parts in the corresponding gesture template libraries of different angle classes; an optimal template selection means, for further selecting an optimal gesture template from the resembling gesture templates found out by the parallel operation units; and a display terminal, for displaying a gesture image represented by the optimal gesture template. | 1. A gesture recognition system, comprising: an image pick-up device, for capturing an image data containing a hand image; a template database, for recording multiple gesture templates representing different gestures, wherein the gesture templates are classified by angles and are respectively stored in gesture template libraries of different angle classes; a processor, for communicating with the image pick-up device and obtaining the image data, finding out a skin part from the image data, producing a skin edge by using an edge detection means, and then classifying the skin edge into multiple edge parts of different angle classes according to angles of the skin edge; an operation engine, having multiple parallel operation units respectively for performing template matching at different angles, wherein the edge parts of different angle classes are respectively sent to different parallel operation units for template matching, so as to find out the gesture templates most resembling the edge parts in the corresponding gesture template libraries of different angle classes; an optimal template selection means, for further selecting an optimal gesture template from the resembling gesture templates found out by the parallel operation units; and a display terminal, for displaying a gesture image represented by the optimal gesture template. 5. The gesture recognition system according to claim 1 , wherein the skin part is filtered from the image by using a skin processing method, and the skin edge of the skin part is found out with an edge detector. | 0.889875 |
8,137,107 | 1 | 9 | 1. A system for interacting with team members of a virtual team, the system comprising: a computer processor coupled to computer readable memory, the computer readable memory configured to store collective qualifications of the virtual team based on the individual qualifications of the team members, the virtual team including a first team member having a first qualification and a second team member having a second qualification, the collective qualifications include the first qualification and the second qualification; and a team broker configured to present the collective qualifications to third parties; and wherein the collective qualifications include certification from an education service provider that the virtual team has collectively completed one or more educational objectives even if no individual team member has completed the one or more educational objectives. | 1. A system for interacting with team members of a virtual team, the system comprising: a computer processor coupled to computer readable memory, the computer readable memory configured to store collective qualifications of the virtual team based on the individual qualifications of the team members, the virtual team including a first team member having a first qualification and a second team member having a second qualification, the collective qualifications include the first qualification and the second qualification; and a team broker configured to present the collective qualifications to third parties; and wherein the collective qualifications include certification from an education service provider that the virtual team has collectively completed one or more educational objectives even if no individual team member has completed the one or more educational objectives. 9. The system of claim 1 , wherein the team broker is further configured to bill the team members based on access to the collective qualifications. | 0.762136 |
8,855,220 | 6 | 7 | 6. A method comprising: transmitting, by a computing device, a frame of data across a communication channel, wherein the frame of data comprises message data, a first control word, a second control word, and a third control word, wherein each of the first, second, and third control words has a unique bit pattern and is associated with a different time interval, and wherein each time interval individually indicates where or when the message data begins or began in the frame of data relative to the respective first, second, or third control word associated with the time interval; receiving, at the computing device, at least one of the first, second, or third control words and other data; and identifying, by the computing device, at least some of the other data as the message data based upon receipt of at least one of the first, second, or third control words, wherein only one of the first, second, or third control words needs to be received to identify the message data from the other data; and wherein the first, second, and third control words comprise at least one of i) a first start-of-frame control word and a second start-of-frame control word; or ii) a first end-of-frame control word and a second end-of-frame control word. | 6. A method comprising: transmitting, by a computing device, a frame of data across a communication channel, wherein the frame of data comprises message data, a first control word, a second control word, and a third control word, wherein each of the first, second, and third control words has a unique bit pattern and is associated with a different time interval, and wherein each time interval individually indicates where or when the message data begins or began in the frame of data relative to the respective first, second, or third control word associated with the time interval; receiving, at the computing device, at least one of the first, second, or third control words and other data; and identifying, by the computing device, at least some of the other data as the message data based upon receipt of at least one of the first, second, or third control words, wherein only one of the first, second, or third control words needs to be received to identify the message data from the other data; and wherein the first, second, and third control words comprise at least one of i) a first start-of-frame control word and a second start-of-frame control word; or ii) a first end-of-frame control word and a second end-of-frame control word. 7. The method of claim 6 , wherein at least one of the first, second, or third control words is transmitted before the message data in the frame of data. | 0.5 |
7,711,191 | 5 | 6 | 5. A secure document data capture system for generating a data structure, comprising a data field value associated with each of a plurality of identified data fields, from a document image comprising text representing each of such data field values, the secure document data capture system comprising: a character recognition system receiving the document image and recognizing characters within the text to generate, for each of the identified data fields, a data field value for association therewith; a validation engine for identifying suspect characters, each suspect character being a character which fails to comply with a validation rule thereby indicating that that character recognition system erred in recognizing such character; an exception handling system: providing an exception image to a first client system, the exception image comprising a portion of the document image which includes text of a suspect character with a context portion of the document image redacted, the context portion of the document image being a portion of the document image which comprises text which discloses a meaning of the suspect character; and receiving from the first client system, user input of a replacement character for the suspect character; and the secure data capture system generating the data structure utilizing, for each identified data field, the data field values generated by the character recognition system with substitution of the replacement character from the exception handling system for each suspect character. | 5. A secure document data capture system for generating a data structure, comprising a data field value associated with each of a plurality of identified data fields, from a document image comprising text representing each of such data field values, the secure document data capture system comprising: a character recognition system receiving the document image and recognizing characters within the text to generate, for each of the identified data fields, a data field value for association therewith; a validation engine for identifying suspect characters, each suspect character being a character which fails to comply with a validation rule thereby indicating that that character recognition system erred in recognizing such character; an exception handling system: providing an exception image to a first client system, the exception image comprising a portion of the document image which includes text of a suspect character with a context portion of the document image redacted, the context portion of the document image being a portion of the document image which comprises text which discloses a meaning of the suspect character; and receiving from the first client system, user input of a replacement character for the suspect character; and the secure data capture system generating the data structure utilizing, for each identified data field, the data field values generated by the character recognition system with substitution of the replacement character from the exception handling system for each suspect character. 6. The secure document data capture system of claim 5 , wherein: the exception handling system further: provides the exception image to a second client system; receives from the second client system, user input of a replacement character for the suspect character; and the secure data capture system substitutes the replacement character from the exception handling system for each suspect character only when the replacement character form the first client system and the replacement character from the second client system are the same. | 0.5 |
8,296,151 | 17 | 18 | 17. A processor readable storage device having instructions encoded thereon, the instructions for programming one or more processors to perform a method for controlling a multimedia system, comprising: displaying a group of one or more objects on a monitor; receiving body position data from a sensor; recognizing a gesture from the received body position data; updating the monitor display to list a set of sound commands available in response to the recognized gesture; receiving sound data from a microphone; recognizing a sound command from the set of sound commands based on the received sound data; selecting a set of sound commands associated with the recognized gesture to confirm that the sound command is properly recognized if a weighted confidence value associated with the recognized gesture is higher than a weighted confidence value associated with the recognized sound command; and executing an action associated with the recognized sound command. | 17. A processor readable storage device having instructions encoded thereon, the instructions for programming one or more processors to perform a method for controlling a multimedia system, comprising: displaying a group of one or more objects on a monitor; receiving body position data from a sensor; recognizing a gesture from the received body position data; updating the monitor display to list a set of sound commands available in response to the recognized gesture; receiving sound data from a microphone; recognizing a sound command from the set of sound commands based on the received sound data; selecting a set of sound commands associated with the recognized gesture to confirm that the sound command is properly recognized if a weighted confidence value associated with the recognized gesture is higher than a weighted confidence value associated with the recognized sound command; and executing an action associated with the recognized sound command. 18. A processor readable storage device as in claim 17 , wherein the gesture provides context for the sound commands thereby permitting a simpler and more limited set of contextual sound commands. | 0.581197 |
9,053,202 | 6 | 7 | 6. The method as recited in claim 5 , wherein the second translatable text string is associated with a variable and the second translation is based at least in part on a current value of the variable for the one or more web pages. | 6. The method as recited in claim 5 , wherein the second translatable text string is associated with a variable and the second translation is based at least in part on a current value of the variable for the one or more web pages. 7. The method as recited in claim 6 , wherein the response for presenting the second translation includes a plurality of alternative translation strings, a position and type indicator for the current value of the variable, and information that specifies which alternative translation string to present as the second translation based at least in part on the current value of the variable. | 0.5 |
9,529,917 | 1 | 7 | 1. A method for generating an information feed based on contextual data, the method comprising: retrieving, by a database system, user contextual data associated with a user, the user contextual data identifying one or more entities associated with the user; retrieving, from one or more data object sources by the database system, one or more data objects based on the retrieval of the user contextual data, wherein the only data objects retrieved are related to the retrieved user contextual data; retrieving, by the database system, data object contextual data based on the retrieval of the one or more data objects, the data object contextual data being associated with the one or more data objects; generating, by the database system, one or more feed items based, at least in part, on the one or more retrieved data objects and the retrieved data object contextual data; generating, by the database system, a weight associated with each of the one or more feed items, the weight being generated based on the retrieved user contextual data and the retrieved data object contextual data; and generating, by the database system, an information feed including at least some of the one or more feed items, the information feed arranging the at least some of the one or more feed items based on the generated weight associated with each of the at least some of the one or more feed items. | 1. A method for generating an information feed based on contextual data, the method comprising: retrieving, by a database system, user contextual data associated with a user, the user contextual data identifying one or more entities associated with the user; retrieving, from one or more data object sources by the database system, one or more data objects based on the retrieval of the user contextual data, wherein the only data objects retrieved are related to the retrieved user contextual data; retrieving, by the database system, data object contextual data based on the retrieval of the one or more data objects, the data object contextual data being associated with the one or more data objects; generating, by the database system, one or more feed items based, at least in part, on the one or more retrieved data objects and the retrieved data object contextual data; generating, by the database system, a weight associated with each of the one or more feed items, the weight being generated based on the retrieved user contextual data and the retrieved data object contextual data; and generating, by the database system, an information feed including at least some of the one or more feed items, the information feed arranging the at least some of the one or more feed items based on the generated weight associated with each of the at least some of the one or more feed items. 7. The method of claim 1 , wherein the at least some of the one or more feed items included in the information feed are paginated based on a target device. | 0.804293 |
8,037,084 | 7 | 8 | 7. The method of claim 1 wherein the one or more instructions are interpreted by a transcoding engine component of a computing device configured for transcoding web pages to a target format. | 7. The method of claim 1 wherein the one or more instructions are interpreted by a transcoding engine component of a computing device configured for transcoding web pages to a target format. 8. The method of claim 7 wherein the web site comprises an e-commerce web site and some of the web pages are for conducting a transaction. | 0.5 |
8,880,989 | 1 | 11 | 1. A computer-implemented method of disseminating a document, the method comprising: providing a user interface display, of an authoring application, to facilitate user generation of a new document; receiving user inputs through the user interface display of the authoring application that provide document content for the document; determining that the document is a sensitive document that is subject to a data dissemination policy; and modifying the user interface display of the authoring application, while the document is being displayed, to provide a description of why the document is subject to the data dissemination policy. | 1. A computer-implemented method of disseminating a document, the method comprising: providing a user interface display, of an authoring application, to facilitate user generation of a new document; receiving user inputs through the user interface display of the authoring application that provide document content for the document; determining that the document is a sensitive document that is subject to a data dissemination policy; and modifying the user interface display of the authoring application, while the document is being displayed, to provide a description of why the document is subject to the data dissemination policy. 11. The computer-implemented method of claim 1 wherein determining that the document is a sensitive document comprises: analyzing a location where the document is to be stored to determine whether the location indicates that the document is a sensitive document. | 0.639118 |
10,115,202 | 1 | 9 | 1. An apparatus that is configured to identify a moving object in spatial data, the apparatus comprising: a memory coupled to at least one processor; and the at least one processor, configured to: receive, from a spatial data source, a data structure that comprises spatial-temporal data, wherein spatial-temporal data comprises a combination of time series data and spatial data; convert the spatial-temporal data to a sequence of spatial data frames, where the sequence of spatial data frames represents the spatial data as a sequence of image-like objects; determine a location of one or more clusters in the sequence of spatial data frames at two or more of a plurality of time values, the sequence of spatial data frames defining one or more locations of the one or more clusters at the plurality of time values; determine that a first cluster of the one or more clusters in a first of the two or more time values corresponds to a second cluster of the one or more clusters in a second of the two or more time values; wherein, to determine that the first cluster corresponds to the second cluster, the processor is further configured to: determine a location of each cluster at the first of the two or more time values; determine a location of each cluster at the second of the two or more time values; compute a cluster similarity score for one or more of the clusters at the first time value with one or more of the clusters at the second time value; and associate the first cluster with the second cluster based on the similarity score; determine at least one motion vector between the first cluster and the second cluster; and determine a moving object based on information comprising the at least one motion vector, wherein the processor is further configured to generate an output text using a natural language generation system, the output text linguistically describing the moving object. | 1. An apparatus that is configured to identify a moving object in spatial data, the apparatus comprising: a memory coupled to at least one processor; and the at least one processor, configured to: receive, from a spatial data source, a data structure that comprises spatial-temporal data, wherein spatial-temporal data comprises a combination of time series data and spatial data; convert the spatial-temporal data to a sequence of spatial data frames, where the sequence of spatial data frames represents the spatial data as a sequence of image-like objects; determine a location of one or more clusters in the sequence of spatial data frames at two or more of a plurality of time values, the sequence of spatial data frames defining one or more locations of the one or more clusters at the plurality of time values; determine that a first cluster of the one or more clusters in a first of the two or more time values corresponds to a second cluster of the one or more clusters in a second of the two or more time values; wherein, to determine that the first cluster corresponds to the second cluster, the processor is further configured to: determine a location of each cluster at the first of the two or more time values; determine a location of each cluster at the second of the two or more time values; compute a cluster similarity score for one or more of the clusters at the first time value with one or more of the clusters at the second time value; and associate the first cluster with the second cluster based on the similarity score; determine at least one motion vector between the first cluster and the second cluster; and determine a moving object based on information comprising the at least one motion vector, wherein the processor is further configured to generate an output text using a natural language generation system, the output text linguistically describing the moving object. 9. The apparatus of claim 1 , wherein the processor is further configured to compare a first content of the first cluster with a second content of the second cluster, and wherein the information further comprises the results of the comparison. | 0.602941 |
7,801,759 | 1 | 12 | 1. A system for selecting a concept, comprising: a database to store information about an enterprise development concept to be funded; a memory component configured to store instructions defining a graphical user interface; a processor configured to execute instructions to implement at least one graphical user interface, the graphical interface comprising: an authoring component displayed on the graphical interface that enables a user to provide the information about the enterprise development concept to be funded, the information about the enterprise development concept including a concept definition that defines a plurality of attributes of the enterprise development concept, wherein the plurality of attributes include a strategic enterprise initiative with which the enterprise development concept is aligned, the authoring component in communication with the database; a scoring component displayed on the graphical interface that enables at least one scoring individual to score the enterprise development concept to be funded, wherein the score is calculated based on the plurality of attributes of the enterprise development concept, wherein the score is a measure of the quality of the concept and is not a measure of the performance or operational efficiency of the concept, and wherein the score of the concept by the at least one scoring individual is maintained by the database as part of the information about the enterprise development concept; a concept prioritization component displayed on the graphical user interface that enables a priority to be assigned to the enterprise development concept, wherein the concept prioritization component is configured to create a priority list of a plurality of enterprise development concepts with a corresponding score and assigned priority associated with each of the plurality of enterprise development concepts in the priority list, and wherein the enterprise development concept and the score of the enterprise development concept calculated by the scoring component are ordered in the priority list based upon the assigned priority; an initiative mapping component displayed on the graphical interface, wherein responsive to receiving a selection of the initiative mapping component, the initiative mapping component displays a concept initiative screen that includes a plurality of enterprise development concepts, each of the plurality of enterprise development concepts in the concept initiative screen is displayed with a corresponding score and priority, wherein the plurality of enterprise development concepts include the enterprise development concept to be funded displayed with the score of the enterprise development concept calculated by the scoring component and the assigned priority of the enterprise development concept, wherein the initiative mapping component groups the enterprise development concept with other enterprise development concepts of the plurality of enterprise development concepts in the concept initiative screen based on the strategic enterprise initiative with which the enterprise development concept is aligned; and an evaluation component displayed on the graphical interface which allows one or more evaluators to consider and designate a course of action, wherein the evaluators are enabled to analyze the enterprise development concept and use the concept initiative screen, the score of the enterprise development concept and the priority list to designate the course of action. | 1. A system for selecting a concept, comprising: a database to store information about an enterprise development concept to be funded; a memory component configured to store instructions defining a graphical user interface; a processor configured to execute instructions to implement at least one graphical user interface, the graphical interface comprising: an authoring component displayed on the graphical interface that enables a user to provide the information about the enterprise development concept to be funded, the information about the enterprise development concept including a concept definition that defines a plurality of attributes of the enterprise development concept, wherein the plurality of attributes include a strategic enterprise initiative with which the enterprise development concept is aligned, the authoring component in communication with the database; a scoring component displayed on the graphical interface that enables at least one scoring individual to score the enterprise development concept to be funded, wherein the score is calculated based on the plurality of attributes of the enterprise development concept, wherein the score is a measure of the quality of the concept and is not a measure of the performance or operational efficiency of the concept, and wherein the score of the concept by the at least one scoring individual is maintained by the database as part of the information about the enterprise development concept; a concept prioritization component displayed on the graphical user interface that enables a priority to be assigned to the enterprise development concept, wherein the concept prioritization component is configured to create a priority list of a plurality of enterprise development concepts with a corresponding score and assigned priority associated with each of the plurality of enterprise development concepts in the priority list, and wherein the enterprise development concept and the score of the enterprise development concept calculated by the scoring component are ordered in the priority list based upon the assigned priority; an initiative mapping component displayed on the graphical interface, wherein responsive to receiving a selection of the initiative mapping component, the initiative mapping component displays a concept initiative screen that includes a plurality of enterprise development concepts, each of the plurality of enterprise development concepts in the concept initiative screen is displayed with a corresponding score and priority, wherein the plurality of enterprise development concepts include the enterprise development concept to be funded displayed with the score of the enterprise development concept calculated by the scoring component and the assigned priority of the enterprise development concept, wherein the initiative mapping component groups the enterprise development concept with other enterprise development concepts of the plurality of enterprise development concepts in the concept initiative screen based on the strategic enterprise initiative with which the enterprise development concept is aligned; and an evaluation component displayed on the graphical interface which allows one or more evaluators to consider and designate a course of action, wherein the evaluators are enabled to analyze the enterprise development concept and use the concept initiative screen, the score of the enterprise development concept and the priority list to designate the course of action. 12. The system of claim 1 further comprising an enterprise development process system that maintains the strategic enterprise initiative, wherein the database associates the strategic enterprise initiative with the enterprise development concept. | 0.578767 |
5,587,823 | 1 | 3 | 1. A radio communication device for exchanging data with another radio communication device, comprising: image pattern data storage means for storing a plurality of image pattern data for each of parts of a face, the plurality of image pattern data corresponding respectively to a plurality of code data; image pattern data selecting means for designating code data to select image pattern data from among the image pattern data stored in said image pattern data storage means, and for combining the selected image pattern data to obtain image data of a face; image data storing means for storing image data of a face obtained by said image pattern data selecting means; conversation sentence data storage means for storing a plurality of conversation sentence data, which correspond respectively to a plurality of code data; conversation sentence selecting means for selecting one conversation sentence data from among the plurality of conversation sentence data stored in said conversation sentence data storage means; sending means for sending to the another radio communication device by means of radio signals, code data of image pattern data included in the image data obtained by said image pattern data selecting means and code data of the conversation sentence data selected by said conversation sentence selecting means; receiving means for receiving a radio signal of code data of image data and a radio signal of conversation sentence data, both sent from the another radio communication device; reading means for reading out from said image pattern data storage means image pattern data corresponding to code data of the image data which are included in the radio signal received by said receiving means, and for reading out from said conversation sentence data storage means conversation sentence data corresponding to code data of the conversation sentence data received by said receiving means; display means for displaying the image pattern data and the conversation sentence data, both read out by said reading means; and display control means for controlling said reading means to read out from said image pattern data storage means image pattern data different from the image pattern data previously read out by said reading means, when the conversation sentence data read out by said reading means is a previously determined conversation sentence data, and for controlling said display means to display the image pattern data last read out by said reading means. | 1. A radio communication device for exchanging data with another radio communication device, comprising: image pattern data storage means for storing a plurality of image pattern data for each of parts of a face, the plurality of image pattern data corresponding respectively to a plurality of code data; image pattern data selecting means for designating code data to select image pattern data from among the image pattern data stored in said image pattern data storage means, and for combining the selected image pattern data to obtain image data of a face; image data storing means for storing image data of a face obtained by said image pattern data selecting means; conversation sentence data storage means for storing a plurality of conversation sentence data, which correspond respectively to a plurality of code data; conversation sentence selecting means for selecting one conversation sentence data from among the plurality of conversation sentence data stored in said conversation sentence data storage means; sending means for sending to the another radio communication device by means of radio signals, code data of image pattern data included in the image data obtained by said image pattern data selecting means and code data of the conversation sentence data selected by said conversation sentence selecting means; receiving means for receiving a radio signal of code data of image data and a radio signal of conversation sentence data, both sent from the another radio communication device; reading means for reading out from said image pattern data storage means image pattern data corresponding to code data of the image data which are included in the radio signal received by said receiving means, and for reading out from said conversation sentence data storage means conversation sentence data corresponding to code data of the conversation sentence data received by said receiving means; display means for displaying the image pattern data and the conversation sentence data, both read out by said reading means; and display control means for controlling said reading means to read out from said image pattern data storage means image pattern data different from the image pattern data previously read out by said reading means, when the conversation sentence data read out by said reading means is a previously determined conversation sentence data, and for controlling said display means to display the image pattern data last read out by said reading means. 3. A radio communication device according to claim 1, wherein the plurality of conversation sentence data stored in said conversation sentence data storage means comprise question conversation data and response conversation data to the question conversation data. | 0.692757 |
6,026,361 | 40 | 43 | 40. The method according to claim 26, wherein each word consists of three speech sounds, wherein a first speech sound is a consonant speech sound, a second speech sound is a vowel speech sound and a third speech sound is a consonant speech sound. | 40. The method according to claim 26, wherein each word consists of three speech sounds, wherein a first speech sound is a consonant speech sound, a second speech sound is a vowel speech sound and a third speech sound is a consonant speech sound. 43. The method according to claim 40, said method further comprising the step of testing said contrasting speech sounds in said second speech sound of said words. | 0.5 |
7,536,547 | 1 | 10 | 1. A method for securely transmitting digital data relating to a document between a scanner, a printer and a host computer, interconnected by a digital network, the method comprising the steps of: at a sending station: generating a document file through a data source, receiving a session-specific user-defined character string from an operator, automatically forming an encryption key based on the user-defined character string, encrypting the document file to produce an encrypted document file, using the encryption key, while automatically leaving one or more predetermined specifying header items in the document file as unencrypted, forming a transmission file including the encrypted document file, and transmitting the transmission file towards a receiving station; and at the receiving station: storing the received transmission file, receiving the same user-defined character string by from operator, automatically forming a decryption key based on the user-defined character string, and decrypting the encrypted document file to a decrypted document file, using the decryption key, the method further comprising: at the sending station: forming an additional file containing metadata relevant for the document file but excluding any decryption clue, the additional file having a first part and a second part, and encrypting only one of the first and second parts of the additional file, using the same encryption key used for encrypting the document file, wherein in the step of forming the transmission file, the additional file is included in the transmission file. | 1. A method for securely transmitting digital data relating to a document between a scanner, a printer and a host computer, interconnected by a digital network, the method comprising the steps of: at a sending station: generating a document file through a data source, receiving a session-specific user-defined character string from an operator, automatically forming an encryption key based on the user-defined character string, encrypting the document file to produce an encrypted document file, using the encryption key, while automatically leaving one or more predetermined specifying header items in the document file as unencrypted, forming a transmission file including the encrypted document file, and transmitting the transmission file towards a receiving station; and at the receiving station: storing the received transmission file, receiving the same user-defined character string by from operator, automatically forming a decryption key based on the user-defined character string, and decrypting the encrypted document file to a decrypted document file, using the decryption key, the method further comprising: at the sending station: forming an additional file containing metadata relevant for the document file but excluding any decryption clue, the additional file having a first part and a second part, and encrypting only one of the first and second parts of the additional file, using the same encryption key used for encrypting the document file, wherein in the step of forming the transmission file, the additional file is included in the transmission file. 10. The method of claim 1 , wherein the receiving station is a printer having a local user interface for inputting, by an operator, the character string used to form the decryption key. | 0.748641 |
8,804,147 | 1 | 6 | 1. A print server including a cloud print service, comprising: at least one processor; a non-transitory computer-readable storage medium including instructions executable by the at least one processor, the instructions configured to implement, an application manager configured to receive a print request for content to be printed, over a network, from a user of an application associated with a device, and provide, over the network, a print dialog to the user, the print dialog configured to identify at least one available printer among a plurality of printers associated with the cloud print service; and an options translator configured to determine at least one printing option associated with the at least one available printer, and translate a native printer display format of the at least one printing option to a common protocol display format associated with the cloud print service, the options translator being configured to provide the common protocol display format for inclusion in the print dialog, the native printer display format being an original display format for the at least one printing option that is provided by printer capability information specific to the at least one available printer, the common protocol display format being a display format for the at least one printing option associated with the cloud print service such that the common protocol display format is the same across the plurality of printers associated with the cloud print service. | 1. A print server including a cloud print service, comprising: at least one processor; a non-transitory computer-readable storage medium including instructions executable by the at least one processor, the instructions configured to implement, an application manager configured to receive a print request for content to be printed, over a network, from a user of an application associated with a device, and provide, over the network, a print dialog to the user, the print dialog configured to identify at least one available printer among a plurality of printers associated with the cloud print service; and an options translator configured to determine at least one printing option associated with the at least one available printer, and translate a native printer display format of the at least one printing option to a common protocol display format associated with the cloud print service, the options translator being configured to provide the common protocol display format for inclusion in the print dialog, the native printer display format being an original display format for the at least one printing option that is provided by printer capability information specific to the at least one available printer, the common protocol display format being a display format for the at least one printing option associated with the cloud print service such that the common protocol display format is the same across the plurality of printers associated with the cloud print service. 6. The print server of claim 1 , wherein the options translator configured to translate a native printer display format of the at least one printing option to a common protocol display format associated with the cloud print service further includes: providing the common protocol display format in a language associated with the user. | 0.742284 |
8,832,589 | 1 | 18 | 1. A method comprising: outputting, by a computing device and for display at a presence-sensitive display, a graphical keyboard comprising a plurality of keys; receiving, by the computing device, an indication of at least one gesture to select at least one key of the plurality of keys; determining, by the computing device, a location at the presence-sensitive display at which the at least one gesture to select the at least one key is detected; modifying, by the computing device and based at least in part on a location of a next key of the plurality of keys relative to the location of the at least one gesture, a spatial model for the next key; determining, by the computing device, a candidate word based at least in part on data provided by the modified spatial model and a language model, wherein the modified spatial model provides a first portion of the data based at least in part on an indication of at least one subsequent gesture and wherein the language model provides a second portion of the data based at least in part on a lexicon; and outputting, by the computing device and for display at the presence-sensitive display, the candidate word. | 1. A method comprising: outputting, by a computing device and for display at a presence-sensitive display, a graphical keyboard comprising a plurality of keys; receiving, by the computing device, an indication of at least one gesture to select at least one key of the plurality of keys; determining, by the computing device, a location at the presence-sensitive display at which the at least one gesture to select the at least one key is detected; modifying, by the computing device and based at least in part on a location of a next key of the plurality of keys relative to the location of the at least one gesture, a spatial model for the next key; determining, by the computing device, a candidate word based at least in part on data provided by the modified spatial model and a language model, wherein the modified spatial model provides a first portion of the data based at least in part on an indication of at least one subsequent gesture and wherein the language model provides a second portion of the data based at least in part on a lexicon; and outputting, by the computing device and for display at the presence-sensitive display, the candidate word. 18. The method of claim 1 , wherein outputting the candidate word comprises: outputting, by the computing device and for display at the presence-sensitive display, characters of the candidate word associated with the at least one key in a first visual style; and outputting, by the computing device and for display at the presence-sensitive display; characters of the candidate word that are not associated with the at least one key in a second visual style. | 0.733721 |
9,153,229 | 1 | 5 | 1. A speech recognition method, comprising the steps of: providing a processor communicatively coupled to each of a local speech recognition engine and a server-based speech recognition engine; inputting a first speech input into the server-based speech recognition engine; receiving at the processor a first recognition result from the server-based speech recognition engine, the first recognition result being based on the first speech input; storing the first recognition result in a memory device, the first recognition result being stored in association with the first speech input; inputting a second speech input into the local speech recognition engine; retrieving the first recognition result from the memory device; producing a second recognition result by the local speech recognition engine, the second recognition result being based on the second speech input and being dependent upon the retrieved first recognition result; counting a number of times that the user confirms the correctness of the first recognition result, the second recognition result being dependent upon the retrieved first recognition result only if the number of times that the user has confirmed the correctness of the first recognition result is greater than a predetermined number. | 1. A speech recognition method, comprising the steps of: providing a processor communicatively coupled to each of a local speech recognition engine and a server-based speech recognition engine; inputting a first speech input into the server-based speech recognition engine; receiving at the processor a first recognition result from the server-based speech recognition engine, the first recognition result being based on the first speech input; storing the first recognition result in a memory device, the first recognition result being stored in association with the first speech input; inputting a second speech input into the local speech recognition engine; retrieving the first recognition result from the memory device; producing a second recognition result by the local speech recognition engine, the second recognition result being based on the second speech input and being dependent upon the retrieved first recognition result; counting a number of times that the user confirms the correctness of the first recognition result, the second recognition result being dependent upon the retrieved first recognition result only if the number of times that the user has confirmed the correctness of the first recognition result is greater than a predetermined number. 5. The method of claim 1 , wherein the producing step includes incorporating the first speech input into a grammar used in the server-based speech recognition engine. | 0.851521 |
8,271,256 | 1 | 7 | 1. A method of optimizing MOSFET device production comprising: defining, using a computer, key independent parameters; formulating key independent parameters into a canonical variational form, wherein the canonical variational form comprises a key independent parameter extracted at nominal, or target, device specifications plus a product of magnitude of a variation of the key independent parameter, relative to a skew of a distribution on device characteristics, and a selected distribution; calculating theoretical extracted parameters using at least one of key independent parameters in canonical variational form, physics-based analytical models, and corner models; calculating simulated characteristics of a device using at least one of key independent parameters in canonical form or theoretical extracted parameters using a variational model; extracting target data parameters based on at least one of measured data and predicted data; comparing the simulated characteristics to the target data parameters; modifying the theoretical extracted parameters based on the comparison to the target data parameters; modifying the key independent parameters in canonical form based on the modified theoretical extracted parameters; calculating and outputting the simulated characteristics based on the modified theoretical extracted parameters and the modified key independent parameters in canonical form; and modifying the key independent parameters in the device production using the simulated characteristics. | 1. A method of optimizing MOSFET device production comprising: defining, using a computer, key independent parameters; formulating key independent parameters into a canonical variational form, wherein the canonical variational form comprises a key independent parameter extracted at nominal, or target, device specifications plus a product of magnitude of a variation of the key independent parameter, relative to a skew of a distribution on device characteristics, and a selected distribution; calculating theoretical extracted parameters using at least one of key independent parameters in canonical variational form, physics-based analytical models, and corner models; calculating simulated characteristics of a device using at least one of key independent parameters in canonical form or theoretical extracted parameters using a variational model; extracting target data parameters based on at least one of measured data and predicted data; comparing the simulated characteristics to the target data parameters; modifying the theoretical extracted parameters based on the comparison to the target data parameters; modifying the key independent parameters in canonical form based on the modified theoretical extracted parameters; calculating and outputting the simulated characteristics based on the modified theoretical extracted parameters and the modified key independent parameters in canonical form; and modifying the key independent parameters in the device production using the simulated characteristics. 7. The method of claim 1 , wherein the variational model is implemented on BSIM4. | 0.939098 |
9,514,200 | 1 | 8 | 1. A method comprising: generating a table graph comprising: a first node associated with a first data table; a second node associated with a second data table; a first link between the first node and the second node, wherein the first link indicates a first field of the first data table is associated with a first field of the second data table; and a second link between the first node and the second node, wherein the second link indicates a second field of the first data table is associated with a second field of the second data table; executing a search query on the table graph by at least: looking up first information in the first data table, wherein the first information is associated with the search query; looking up second information in the second data table by reference to the first link, wherein the second information is associated with the first information, and wherein the first and second information together comprise a direct hit of the search query; and looking up third information in the first data table by reference to the second link, wherein the third information is different from the first information, and wherein the third information comprises an indirect hit of the search query; and providing, for display by a computing device: the third information, and an indication that the third information comprises the indirect hit of the search query. | 1. A method comprising: generating a table graph comprising: a first node associated with a first data table; a second node associated with a second data table; a first link between the first node and the second node, wherein the first link indicates a first field of the first data table is associated with a first field of the second data table; and a second link between the first node and the second node, wherein the second link indicates a second field of the first data table is associated with a second field of the second data table; executing a search query on the table graph by at least: looking up first information in the first data table, wherein the first information is associated with the search query; looking up second information in the second data table by reference to the first link, wherein the second information is associated with the first information, and wherein the first and second information together comprise a direct hit of the search query; and looking up third information in the first data table by reference to the second link, wherein the third information is different from the first information, and wherein the third information comprises an indirect hit of the search query; and providing, for display by a computing device: the third information, and an indication that the third information comprises the indirect hit of the search query. 8. The method if claim 1 further comprising: providing, for display by the computing device: the second information, and a second indication that the second information comprises the direct hit of the search query. | 0.826016 |
7,912,700 | 1 | 15 | 1. A computer-implemented method for providing context-based word prediction, comprising: parsing documents associated with different applications and obtaining words contained in the documents; creating context-based data sources for the words including creating a context-based data source for each different application, each context-based data source comprising an instance of an application defined candidate provider and an application defined data store for storing the words for an associated application; receiving a text input in a document having an associated context-based data source; retrieving one or more words associated with the text input received in the document from the associated context-based data source by utilizing words stored in the associated context-based data source before utilizing words from an existing text prediction data source as part of prediction of candidates using the text input; and displaying the one or more words retrieved from the associated context-based data source in the document and allowing selection of one of the one or more words displayed in the document for automatically completing the text input received in the document. | 1. A computer-implemented method for providing context-based word prediction, comprising: parsing documents associated with different applications and obtaining words contained in the documents; creating context-based data sources for the words including creating a context-based data source for each different application, each context-based data source comprising an instance of an application defined candidate provider and an application defined data store for storing the words for an associated application; receiving a text input in a document having an associated context-based data source; retrieving one or more words associated with the text input received in the document from the associated context-based data source by utilizing words stored in the associated context-based data source before utilizing words from an existing text prediction data source as part of prediction of candidates using the text input; and displaying the one or more words retrieved from the associated context-based data source in the document and allowing selection of one of the one or more words displayed in the document for automatically completing the text input received in the document. 15. The method of claim 1 , wherein receiving a text input in the document includes receiving a text input in a second document that is related to the document; and wherein displaying the one or more words retrieved from the associated context-based data source in the document and allowing selection of one of the one or more words displayed in the document for automatically completing the text input received in the document includes displaying the one or more words retrieved from the associated context-based data source in the second document and allowing selection of one of the one or more words displayed in the second document for automatically completing the text input received in the second document. | 0.5 |
9,948,595 | 1 | 6 | 1. A computer-implemented method comprising: identifying, by a processor, first text content on a first conversation medium; identifying, by the processor, a plurality of available templates, each of the plurality of available templates including second text content; identifying, by the processor, a plurality of available target sites, each of the plurality of available target sites including third text content; identifying, by the processor, a first combination including a first template of the available templates, and a first target site of the available target sites; identifying, by the processor, a second combination including a second template of the available templates, and a second target site of the available target sites; determining, by the processor, a first score based on a comparison of the second and third text contents of the first combination, against the first text content of the conversation; determining, by the processor, a second score based on a comparison of the second and third text contents of the second combination, against the first text content of the conversation; selecting, by the processor, one of the first or second combinations based on the first and second scores; and providing, by the processor, in the first conversation medium, the second text of a selected template of the first and second templates corresponding to the selected combination, and a link to a selected target site of the first and second target sites corresponding to the selected combination. | 1. A computer-implemented method comprising: identifying, by a processor, first text content on a first conversation medium; identifying, by the processor, a plurality of available templates, each of the plurality of available templates including second text content; identifying, by the processor, a plurality of available target sites, each of the plurality of available target sites including third text content; identifying, by the processor, a first combination including a first template of the available templates, and a first target site of the available target sites; identifying, by the processor, a second combination including a second template of the available templates, and a second target site of the available target sites; determining, by the processor, a first score based on a comparison of the second and third text contents of the first combination, against the first text content of the conversation; determining, by the processor, a second score based on a comparison of the second and third text contents of the second combination, against the first text content of the conversation; selecting, by the processor, one of the first or second combinations based on the first and second scores; and providing, by the processor, in the first conversation medium, the second text of a selected template of the first and second templates corresponding to the selected combination, and a link to a selected target site of the first and second target sites corresponding to the selected combination. 6. The method of claim 1 , wherein the selected target site provides information relevant to the first text content. | 0.776923 |
7,779,003 | 10 | 13 | 10. A system according to claim 1 , further comprising: at least one repository of term substitution information comprising mapping information associating a term with a corresponding term; and said search processor parses a search term in the one or more search terms and substitutes an associated corresponding term for said search term by applying said mapping information. | 10. A system according to claim 1 , further comprising: at least one repository of term substitution information comprising mapping information associating a term with a corresponding term; and said search processor parses a search term in the one or more search terms and substitutes an associated corresponding term for said search term by applying said mapping information. 13. A system according to claim 10 , wherein said search processor excludes short terms that potentially map to multiple irrelevant terms. | 0.682028 |
9,679,155 | 1 | 2 | 1. A method for performing prefix search of encrypted cloud stored data comprising: receiving, at a network intermediary, a search request with a search term directed to encrypted files stored in a cloud storage service, the cloud stored encrypted files being encrypted using an order-preserving encryption algorithm; generating a minimum possible plaintext string using the search term as prefix and padding the search term to a first character length using one or more trailing characters indicative of a minimum possible value related to the search term; generating a maximum possible plaintext string using the search term as prefix and padding the search term to the first character length using one or more trailing characters indicative of a maximum possible value related to the search term; encrypting the minimum possible plaintext string and the maximum possible plaintext string using the order-preserving encryption algorithm used to encrypt the cloud stored encrypted files; generating a minimum ciphertext from the minimum possible plaintext string and a maximum ciphertext from the maximum possible plaintext string; determining a set of common leading digits from the minimum ciphertext and the maximum ciphertext; generating a cloud service search request including the set of common leading digits as an encrypted prefix search term; sending the cloud service search request with the encrypted prefix search term to the cloud storage service; and receiving a search result from the cloud storage service. | 1. A method for performing prefix search of encrypted cloud stored data comprising: receiving, at a network intermediary, a search request with a search term directed to encrypted files stored in a cloud storage service, the cloud stored encrypted files being encrypted using an order-preserving encryption algorithm; generating a minimum possible plaintext string using the search term as prefix and padding the search term to a first character length using one or more trailing characters indicative of a minimum possible value related to the search term; generating a maximum possible plaintext string using the search term as prefix and padding the search term to the first character length using one or more trailing characters indicative of a maximum possible value related to the search term; encrypting the minimum possible plaintext string and the maximum possible plaintext string using the order-preserving encryption algorithm used to encrypt the cloud stored encrypted files; generating a minimum ciphertext from the minimum possible plaintext string and a maximum ciphertext from the maximum possible plaintext string; determining a set of common leading digits from the minimum ciphertext and the maximum ciphertext; generating a cloud service search request including the set of common leading digits as an encrypted prefix search term; sending the cloud service search request with the encrypted prefix search term to the cloud storage service; and receiving a search result from the cloud storage service. 2. The method of claim 1 , wherein receiving the search result from the cloud storage service comprises: receiving the search result including a listing of document indexes identifying one or more encrypted files in the cloud storage service having an encrypted text with a prefix matching the encrypted prefix search term; and providing the search result to a requesting user device. | 0.609756 |
7,680,334 | 1 | 8 | 1. A method performed by a handwriting recognition device for presenting a recognized handwritten symbol, the recognition device having a processor and detection means for detecting entry of a handwritten symbol, the method comprising the steps of: detecting, by the detection means, a handwritten pattern that is entered by a user, recognizing, by the processor, the detected handwritten pattern, wherein said step of recognizing comprises: comparing the handwritten pattern to a plurality of templates, wherein each of the plurality of templates represents at least one of a plurality of handwriting symbol patterns of handwritten ways of hand writing symbols, and returning a best template selected from the plurality of templates that represents one of the plurality of handwriting symbol patterns as a best handwriting symbol pattern which, according to a predefined rule, is most similar to the handwritten pattern, wherein at least two of the plurality of templates comprise different ones of the plurality of handwriting symbol patterns which represent different handwritten ways of handwriting a single symbol; and presenting the best handwriting symbol pattern of the best template. | 1. A method performed by a handwriting recognition device for presenting a recognized handwritten symbol, the recognition device having a processor and detection means for detecting entry of a handwritten symbol, the method comprising the steps of: detecting, by the detection means, a handwritten pattern that is entered by a user, recognizing, by the processor, the detected handwritten pattern, wherein said step of recognizing comprises: comparing the handwritten pattern to a plurality of templates, wherein each of the plurality of templates represents at least one of a plurality of handwriting symbol patterns of handwritten ways of hand writing symbols, and returning a best template selected from the plurality of templates that represents one of the plurality of handwriting symbol patterns as a best handwriting symbol pattern which, according to a predefined rule, is most similar to the handwritten pattern, wherein at least two of the plurality of templates comprise different ones of the plurality of handwriting symbol patterns which represent different handwritten ways of handwriting a single symbol; and presenting the best handwriting symbol pattern of the best template. 8. The method according to claim 1 , wherein the handwritten pattern is entered on an input area on the screen and the best handwriting symbol pattern of the best template is presented in a presentation area on the screen, wherein said presentation area overlaps the input area. | 0.5 |
9,569,527 | 8 | 13 | 8. A computer-implemented method comprising: identifying a plurality of queries in a query log, and for each query, one or more search results associated with the query, wherein each search result identifies a corresponding resource and comprises a search result snippet that includes text from the corresponding resource identified by the search result; generating a plurality of query-snippet pairs, wherein each pair associates a respective query of the plurality of queries with a particular search result snippet from one of the search results associated with the query in the query log; training a statistical machine translation model using the plurality of query-snippet pairs, including using each query of each query-snippet pair as a source language input, and a corresponding snippet of the query-snippet pair as a target language input, wherein each query and the search result snippet of each query-snippet pair are in the same natural language; translating, using the statistical machine translation model trained on the plurality of query-snippet pairs and search result snippet pairs, a phrase into one or more corresponding translated phrases; and determining one or more synonym pairs including comparing the phrase with the one or more corresponding translated phrases. | 8. A computer-implemented method comprising: identifying a plurality of queries in a query log, and for each query, one or more search results associated with the query, wherein each search result identifies a corresponding resource and comprises a search result snippet that includes text from the corresponding resource identified by the search result; generating a plurality of query-snippet pairs, wherein each pair associates a respective query of the plurality of queries with a particular search result snippet from one of the search results associated with the query in the query log; training a statistical machine translation model using the plurality of query-snippet pairs, including using each query of each query-snippet pair as a source language input, and a corresponding snippet of the query-snippet pair as a target language input, wherein each query and the search result snippet of each query-snippet pair are in the same natural language; translating, using the statistical machine translation model trained on the plurality of query-snippet pairs and search result snippet pairs, a phrase into one or more corresponding translated phrases; and determining one or more synonym pairs including comparing the phrase with the one or more corresponding translated phrases. 13. The method of claim 8 , further comprising: receiving an initial search query including one or more terms; determining that a first term in the search query occurs in a synonym pair of the one or more synonym pairs; in response to determining that the first term in the search query occurs in a synonym pair of the one or more synonym pairs, generating an expanded search query that includes a second term of the synonym pair; obtaining search results using the expanded search query to search a collection of documents; and providing the search results in response to the initial search query. | 0.5 |
9,275,639 | 1 | 10 | 1. A system having a client-server architecture for Automatic Speech Recognition (ASR) applications, comprising: a) client-side including: a.1) a client being part of distributed front end for converting acoustic waves to feature vectors representing the properties of said acoustic waves using Digital Signal Processing (DSP); a.2) Voice Activity Detection for separating between speech and non-speech acoustic signals and for environmental compensation; a.3) adaptor for WebSockets to pipeline chunked feature vectors to the server side; b) a server side including: b.1) A web layer utilizing HTTP protocols and including a Web Server having a Servlet Container which contains dedicated servlet for managing voice recognition sessions that include transferring WebSockets' packets to messages and returning responses and diagnostic message to client, said layer being an access point for corporate information systems, and a point of integration with another web application, which are used for load balancing and. authentication and authorization of clients; b.2) an intermediate layer for transport based on Message-Oriented Middleware (MOM) being a message broker, to which all other server parts are connected, for feature vector streaming, for communication and integration, and for load balancing between said client side and said server side; b.3) a recognition server and an adaptation server both connected to said intermediate layer, said adaptation server being connected via an adaptation channel, said recognition server interacts with said client side via a recognition channel and a Distributed Frontend (DFE); b.4) a Speech processing server consisting of a server part of distributed front end, a Recognition Server and an Adaptation Server; b.5) a Recognition Server for instantiation of a recognition channel per client; b.6)an Adaptation Server for adaptation acoustic and linguistic models for each speaker; b.7) a Bidirectional communication channel between Speech processing server and client side via distributed frontend said recognition channel; and b.8) a Persistent layer for storing, a Language Knowledge Base connected to said Speech processing server, and includes a dictionary, acoustic models, statistical language models and language patterns. | 1. A system having a client-server architecture for Automatic Speech Recognition (ASR) applications, comprising: a) client-side including: a.1) a client being part of distributed front end for converting acoustic waves to feature vectors representing the properties of said acoustic waves using Digital Signal Processing (DSP); a.2) Voice Activity Detection for separating between speech and non-speech acoustic signals and for environmental compensation; a.3) adaptor for WebSockets to pipeline chunked feature vectors to the server side; b) a server side including: b.1) A web layer utilizing HTTP protocols and including a Web Server having a Servlet Container which contains dedicated servlet for managing voice recognition sessions that include transferring WebSockets' packets to messages and returning responses and diagnostic message to client, said layer being an access point for corporate information systems, and a point of integration with another web application, which are used for load balancing and. authentication and authorization of clients; b.2) an intermediate layer for transport based on Message-Oriented Middleware (MOM) being a message broker, to which all other server parts are connected, for feature vector streaming, for communication and integration, and for load balancing between said client side and said server side; b.3) a recognition server and an adaptation server both connected to said intermediate layer, said adaptation server being connected via an adaptation channel, said recognition server interacts with said client side via a recognition channel and a Distributed Frontend (DFE); b.4) a Speech processing server consisting of a server part of distributed front end, a Recognition Server and an Adaptation Server; b.5) a Recognition Server for instantiation of a recognition channel per client; b.6)an Adaptation Server for adaptation acoustic and linguistic models for each speaker; b.7) a Bidirectional communication channel between Speech processing server and client side via distributed frontend said recognition channel; and b.8) a Persistent layer for storing, a Language Knowledge Base connected to said Speech processing server, and includes a dictionary, acoustic models, statistical language models and language patterns. 10. A system according to claim 1 , in which the Language Knowledge Base (LKB) consists of: an Acoustic Model Database that is constructed hierarchically according to language, accent, gender and the speaker's ID; a Language Model Database that is constructed according to a statistic model of n-grams per domain and to language patterns; a dictionary which contains multiple phonetic transcription for all available for recognition vocabularies. It serves as a connection between the Language and Acoustic Model Databases. | 0.5 |
9,027,001 | 4 | 7 | 4. The system of claim 1 , wherein the comparison model is source code; and wherein the second operand is a variable. | 4. The system of claim 1 , wherein the comparison model is source code; and wherein the second operand is a variable. 7. The system of claim 4 , wherein the processing unit is further configured to access an operator template library to identify acceptable matches between the second operator of the source code and the plurality of first operators of the first expressions. | 0.825613 |
8,463,782 | 22 | 23 | 22. The medium of claim 21 , wherein the operations comprise selecting a subset of documents in the corpus, wherein the first value represents a quantity of documents in the subset that include a list that contains both terms of the pair, and wherein the second value represents a quantity of the documents in the subset that include a list that contains at least one of the terms of the pair. | 22. The medium of claim 21 , wherein the operations comprise selecting a subset of documents in the corpus, wherein the first value represents a quantity of documents in the subset that include a list that contains both terms of the pair, and wherein the second value represents a quantity of the documents in the subset that include a list that contains at least one of the terms of the pair. 23. The medium of claim 22 , wherein selecting a subset of documents in the corpus comprises: determining an author for each document in the corpus; and selecting a subset of documents in the corpus that each have a different author. | 0.5 |
8,918,320 | 1 | 5 | 1. A method comprising: determining one or more locations of a device and one or more times that the locations were determined in response to capturing voice data of speech content associated with one or more spoken reviews of one or more entities; analyzing textual data and acoustic data corresponding to the voice data to detect whether the textual data or the acoustic data comprises one or more words indicating at least one sentiment of a user that spoke the speech content; and generating, via a processor, a review of at least one of the entities corresponding to one of the spoken reviews based in part on assigning at least one predefined sentiment to at least one of the words in response to detecting that the word indicates the sentiment of the user. | 1. A method comprising: determining one or more locations of a device and one or more times that the locations were determined in response to capturing voice data of speech content associated with one or more spoken reviews of one or more entities; analyzing textual data and acoustic data corresponding to the voice data to detect whether the textual data or the acoustic data comprises one or more words indicating at least one sentiment of a user that spoke the speech content; and generating, via a processor, a review of at least one of the entities corresponding to one of the spoken reviews based in part on assigning at least one predefined sentiment to at least one of the words in response to detecting that the word indicates the sentiment of the user. 5. The method of claim 1 , further comprising: generating at least one profile on behalf of the user, the profile comprises information indicating the locations, the times and the spoken reviews. | 0.824007 |
9,946,798 | 4 | 5 | 4. The method of claim 2 , wherein adjusting the at least one semantic similarity value of a relationship between the user-stated concept of interest and the concept tag in the weighted semantic graph comprises: determining an adjustment rate, AR, for the at least one semantic similarity value based on the action; and determining an adjustment increment for a given edge in the relationship between the given user-stated concept of interest and the given concept tag as: A = 1 + AR k + 1 , where k is a number of edges in the relationship between the given user-stated concept of interest and the given concept tag; and determining a new weight for the given edge as follows:
Y i =min( A×W i ,1), where Y i is the new weight for the given edge and W i is the previous weight for the given edge. | 4. The method of claim 2 , wherein adjusting the at least one semantic similarity value of a relationship between the user-stated concept of interest and the concept tag in the weighted semantic graph comprises: determining an adjustment rate, AR, for the at least one semantic similarity value based on the action; and determining an adjustment increment for a given edge in the relationship between the given user-stated concept of interest and the given concept tag as: A = 1 + AR k + 1 , where k is a number of edges in the relationship between the given user-stated concept of interest and the given concept tag; and determining a new weight for the given edge as follows:
Y i =min( A×W i ,1), where Y i is the new weight for the given edge and W i is the previous weight for the given edge. 5. The method of claim 4 , wherein adjusting the at least one semantic similarity value of a relationship between the given user-stated concept of interest and the given concept tag in the weighted semantic graph further comprises: determining a new semantic similarity value for the given edge as: W i ′ = C i ⨯ W i + Y i C i + 1 , where W i ′ is the new semantic similarity value and C i is an adjustment count associated with the given edge representing a number of times the semantic similarity value of the given edge has been adjusted. | 0.5 |
8,826,282 | 1 | 9 | 1. A computer-implemented method for managing a project schedule with a Web-based client-server based project schedule system, the method comprising: receiving, from a client, a request to access a particular editor that is one of a task assignment editor, a project schedule editor and a member schedule editor, wherein the request includes project identification data that indicates a particular project and member identification data that corresponds to a particular member and wherein: the task assignment editor is accessible only by project managers and allows project tasks to be defined and assigned to project members, the project schedule editor is accessible only by project managers and allows schedule data to be defined and updated for defined project tasks, the member schedule editor is accessible by project members to which one or more project tasks have been assigned, allows the particular member to edit schedule data for one or more uncompleted project tasks assigned to at least the particular member and the client-server based project schedule system supports at least the task assignment editor, the project schedule editor and the member schedule editor; a server verifying the member identification data with respect to the project identification data and the particular editor specified in the request to determine whether the particular member that corresponds to the member identification data is authorized to access the particular project using the particular editor specified in the request; and in response to determining that the particular member that corresponds to the member identification data is authorized to access the particular project using the particular editor specified in the request, then the server accessing first schedule-related information from a database, the server generating first client-executable code for execution by the client for displaying the particular editor and displaying the first schedule-related information in the particular editor and for managing the particular editor by the client, the server passing the first client-executable code and the first schedule-related information to the client, and the client executing at least a portion of the first client-executable code to display the particular editor and display the first schedule-related information in the particular editor and to manage the editor. | 1. A computer-implemented method for managing a project schedule with a Web-based client-server based project schedule system, the method comprising: receiving, from a client, a request to access a particular editor that is one of a task assignment editor, a project schedule editor and a member schedule editor, wherein the request includes project identification data that indicates a particular project and member identification data that corresponds to a particular member and wherein: the task assignment editor is accessible only by project managers and allows project tasks to be defined and assigned to project members, the project schedule editor is accessible only by project managers and allows schedule data to be defined and updated for defined project tasks, the member schedule editor is accessible by project members to which one or more project tasks have been assigned, allows the particular member to edit schedule data for one or more uncompleted project tasks assigned to at least the particular member and the client-server based project schedule system supports at least the task assignment editor, the project schedule editor and the member schedule editor; a server verifying the member identification data with respect to the project identification data and the particular editor specified in the request to determine whether the particular member that corresponds to the member identification data is authorized to access the particular project using the particular editor specified in the request; and in response to determining that the particular member that corresponds to the member identification data is authorized to access the particular project using the particular editor specified in the request, then the server accessing first schedule-related information from a database, the server generating first client-executable code for execution by the client for displaying the particular editor and displaying the first schedule-related information in the particular editor and for managing the particular editor by the client, the server passing the first client-executable code and the first schedule-related information to the client, and the client executing at least a portion of the first client-executable code to display the particular editor and display the first schedule-related information in the particular editor and to manage the editor. 9. The method of claim 1 , wherein the step of generating comprises the server executing Hypertext Preprocessor (PHP) code to generate the first client-executable code as JavaScript code and to generate structures in the JavaScript code for storing and passing the first schedule-related information to the client. | 0.658696 |
9,934,775 | 24 | 27 | 24. A non-transitory computer-readable storage medium comprising computer-readable instructions which, when executed by one or more processors, cause the one or more processors to: receive text to be converted to speech; generate a sequence of target units representing a spoken pronunciation of the text; determine, based on a plurality of linguistic features associated with each target unit of the sequence of target units, predicted statistical parameters for each of a plurality of acoustic features associated with each target unit, wherein a second acoustic feature of the plurality of acoustic features represents a change of a first acoustic feature of the plurality of acoustic features across a portion of a respective target unit of the sequence of target units; select, based on the plurality of linguistic features associated with each target unit, a plurality of candidate speech segments corresponding to the sequence of target units; for each candidate speech segment of the plurality of candidate speech segments: determine a target cost based on the predicted statistical parameters of the first acoustic feature associated with the respective target unit of the sequence of target units; and determine a plurality of concatenation costs with respect to a plurality of subsequent candidate speech segments, the plurality of concatenation costs determined based on the predicted statistical parameters of the second acoustic feature associated with the respective target unit of the sequence of target units; select from the plurality of candidate speech segments a subset of candidate speech segments for speech synthesis, the selecting based on a combined cost associated with the subset of candidate speech segments, wherein the combined cost is determined based on the target cost and the plurality of concatenation costs of each candidate speech segment; and generate speech corresponding to the received text using the subset of candidate speech segments. | 24. A non-transitory computer-readable storage medium comprising computer-readable instructions which, when executed by one or more processors, cause the one or more processors to: receive text to be converted to speech; generate a sequence of target units representing a spoken pronunciation of the text; determine, based on a plurality of linguistic features associated with each target unit of the sequence of target units, predicted statistical parameters for each of a plurality of acoustic features associated with each target unit, wherein a second acoustic feature of the plurality of acoustic features represents a change of a first acoustic feature of the plurality of acoustic features across a portion of a respective target unit of the sequence of target units; select, based on the plurality of linguistic features associated with each target unit, a plurality of candidate speech segments corresponding to the sequence of target units; for each candidate speech segment of the plurality of candidate speech segments: determine a target cost based on the predicted statistical parameters of the first acoustic feature associated with the respective target unit of the sequence of target units; and determine a plurality of concatenation costs with respect to a plurality of subsequent candidate speech segments, the plurality of concatenation costs determined based on the predicted statistical parameters of the second acoustic feature associated with the respective target unit of the sequence of target units; select from the plurality of candidate speech segments a subset of candidate speech segments for speech synthesis, the selecting based on a combined cost associated with the subset of candidate speech segments, wherein the combined cost is determined based on the target cost and the plurality of concatenation costs of each candidate speech segment; and generate speech corresponding to the received text using the subset of candidate speech segments. 27. The computer-readable storage medium of claim 24 , wherein a concatenation cost of the plurality of concatenation costs for a respective candidate speech segment includes a second weighted difference between an actual value of the second acoustic feature for the respective candidate speech segment with respect to a subsequent candidate speech segment of the plurality of subsequent candidate speech segments and a first predicted statistical parameter of the predicted statistical parameters of the second acoustic feature for the respective target unit, and wherein the second weighted difference is weighted by a second predicted statistical parameter of the predicted statistical parameters of the second acoustic feature for the respective target unit. | 0.5 |
7,984,032 | 2 | 3 | 2. The storage medium of claim 1 , further comprising instructions for defining at least a further term occurrence-level constraints applicable to the input query. | 2. The storage medium of claim 1 , further comprising instructions for defining at least a further term occurrence-level constraints applicable to the input query. 3. The storage medium of claim 2 , further comprising instructions for applying the further term occurrence-level constraint to at least the term occurrence. | 0.5 |
5,394,471 | 3 | 5 | 3. An improved method for password validation according to claim 2, wherein said step of comparing is comprised of the steps of (i) computing BAp using the equation ##EQU6## where l-x is a numeric value related to the number of validation password characters; (ii) establishing a validation threshold value; and (iii) accepting or rejecting said validation password based upon the correspondence between BAp and the validation threshold value. | 3. An improved method for password validation according to claim 2, wherein said step of comparing is comprised of the steps of (i) computing BAp using the equation ##EQU6## where l-x is a numeric value related to the number of validation password characters; (ii) establishing a validation threshold value; and (iii) accepting or rejecting said validation password based upon the correspondence between BAp and the validation threshold value. 5. An improved method for password validation according to claim 3 further comprising the step of electronically storing the means .mu., the standard deviation .sigma., the probability of occurrence T and the threshold valve. | 0.512987 |
7,995,723 | 9 | 10 | 9. A tangible computer readable medium storing instructions, which instructions when executed on a computer, cause the computer to perform a method, the method comprising: hosting a web site and receiving on the web site from an advertiser an advertisement, a telephone number of the advertiser, a schedule for the advertiser to receive telephone calls at the telephone number, and a price; performing a search based on a search request received by voice in a telephone call from a user to identify the advertiser, the search being based upon the search request and the schedule; providing the advertisement to the user in the telephone call, in response to the user making a connection request in the telephone call, causing the telephone call to be connected to the telephone number of the advertiser; and charging the advertiser based on the price after the telephone call is connected to the telephone number of the advertiser. | 9. A tangible computer readable medium storing instructions, which instructions when executed on a computer, cause the computer to perform a method, the method comprising: hosting a web site and receiving on the web site from an advertiser an advertisement, a telephone number of the advertiser, a schedule for the advertiser to receive telephone calls at the telephone number, and a price; performing a search based on a search request received by voice in a telephone call from a user to identify the advertiser, the search being based upon the search request and the schedule; providing the advertisement to the user in the telephone call, in response to the user making a connection request in the telephone call, causing the telephone call to be connected to the telephone number of the advertiser; and charging the advertiser based on the price after the telephone call is connected to the telephone number of the advertiser. 10. The medium of claim 9 , wherein the price is a flat fee. | 0.912791 |
8,930,490 | 1 | 10 | 1. A method for collecting information, enriching said information and linking said enriched information, comprising: (a) on a computer device providing a lifestream data function to allow a user to collect a plurality of lifestreams, wherein said lifestream data function comprises: (i) a note taking function to allow said user to create a plurality of notes on said computer device, (ii) a recording function for collecting, recording or storing a plurality of recordings on said computer device, wherein said recordings are, in any combination, audio data recordings, video data recordings, or audio-video data recordings, and (iii) an annotation function for collecting, recording or storing a plurality of annotation data elements on said computer device, wherein said annotation data elements are externally sensed data of the environment of said user or physiological sensed data of said user, whereby said sensed data is either captured by said user or from said user using a data capture device; (b) on said computer device, or by a computer server or an online service each of them communicatively coupled with said computer device enriching each of said lifestreams and therewith creating a linked network of enriched lifestreams available to said user on said computer device by, in any combination: (j) linking one or more segments in each of said recordings with one or more annotation data elements, one or more notes, or a combination thereof, (jj) linking each of said notes with one or more annotation data elements, one or more segments of said recordings, or a combination thereof, or (jjj) linking each of said annotation data elements with one or more notes, one or more segments of said recordings, or a combination thereof; and (c) said computer device providing a filter or search function to said user for filtering or searching said enriched lifestreams or aspects of said enriched lifestreams on said computer device. | 1. A method for collecting information, enriching said information and linking said enriched information, comprising: (a) on a computer device providing a lifestream data function to allow a user to collect a plurality of lifestreams, wherein said lifestream data function comprises: (i) a note taking function to allow said user to create a plurality of notes on said computer device, (ii) a recording function for collecting, recording or storing a plurality of recordings on said computer device, wherein said recordings are, in any combination, audio data recordings, video data recordings, or audio-video data recordings, and (iii) an annotation function for collecting, recording or storing a plurality of annotation data elements on said computer device, wherein said annotation data elements are externally sensed data of the environment of said user or physiological sensed data of said user, whereby said sensed data is either captured by said user or from said user using a data capture device; (b) on said computer device, or by a computer server or an online service each of them communicatively coupled with said computer device enriching each of said lifestreams and therewith creating a linked network of enriched lifestreams available to said user on said computer device by, in any combination: (j) linking one or more segments in each of said recordings with one or more annotation data elements, one or more notes, or a combination thereof, (jj) linking each of said notes with one or more annotation data elements, one or more segments of said recordings, or a combination thereof, or (jjj) linking each of said annotation data elements with one or more notes, one or more segments of said recordings, or a combination thereof; and (c) said computer device providing a filter or search function to said user for filtering or searching said enriched lifestreams or aspects of said enriched lifestreams on said computer device. 10. The method as set forth in claim 1 , further comprising on said computer device, by said computer server or by said online service ranking of said enriched lifestreams or aspects of said enriched lifestreams in said network of enriched lifestreams. | 0.64507 |
9,195,937 | 3 | 5 | 3. The apparatus of claim 1 , wherein the flow processing module determines whether the state exists in a translation dictionary for the state request, and wherein the state is reproduced if it is not in the dictionary and a new state is added to the dictionary. | 3. The apparatus of claim 1 , wherein the flow processing module determines whether the state exists in a translation dictionary for the state request, and wherein the state is reproduced if it is not in the dictionary and a new state is added to the dictionary. 5. The apparatus of claim 3 , wherein the state represents a final state such that a descriptor is added to the state. | 0.791519 |
7,792,832 | 18 | 19 | 18. A system for identifying products potentially infringing a patent, the system comprising: a processor; an input device coupled to the processor, the input device being capable of providing information to the processor; and an output device coupled to the processor; wherein the processor is configured to receive through the input device data sufficient to obtain text of the patent; obtain the text of the patent; identify a plurality of key terms of a first claim of the patent by performing steps comprising: determining frequencies of occurrence within the text of the patent of each word of a plurality of words in a claim of the patent to obtain a plurality of first frequencies, determining frequencies of occurrence of said each word in a neutral text unrelated to the patent and to technology of the patent to obtain a plurality of second frequencies, for said each word, calculating a ratio of (1) the first frequency of the plurality of first frequencies associated with said each word to (2) the second frequency of the plurality of second frequencies associated with said each word, thereby obtaining a plurality of ratios, a ratio of the plurality of ratios per said each word, and comparing each ratio of the plurality of ratios to a first parameter to obtain a plurality of key terms, each key term of the plurality of key terms corresponding to a ratio of the plurality of ratios that exceeds the first parameter; formulate at least one query to search for data items that include the key terms; launch the at least one query; receive search results responsive to the at least one query; and organize the search results according to a criterion of relevance to the patent. | 18. A system for identifying products potentially infringing a patent, the system comprising: a processor; an input device coupled to the processor, the input device being capable of providing information to the processor; and an output device coupled to the processor; wherein the processor is configured to receive through the input device data sufficient to obtain text of the patent; obtain the text of the patent; identify a plurality of key terms of a first claim of the patent by performing steps comprising: determining frequencies of occurrence within the text of the patent of each word of a plurality of words in a claim of the patent to obtain a plurality of first frequencies, determining frequencies of occurrence of said each word in a neutral text unrelated to the patent and to technology of the patent to obtain a plurality of second frequencies, for said each word, calculating a ratio of (1) the first frequency of the plurality of first frequencies associated with said each word to (2) the second frequency of the plurality of second frequencies associated with said each word, thereby obtaining a plurality of ratios, a ratio of the plurality of ratios per said each word, and comparing each ratio of the plurality of ratios to a first parameter to obtain a plurality of key terms, each key term of the plurality of key terms corresponding to a ratio of the plurality of ratios that exceeds the first parameter; formulate at least one query to search for data items that include the key terms; launch the at least one query; receive search results responsive to the at least one query; and organize the search results according to a criterion of relevance to the patent. 19. The system of claim 18 , wherein: the processor is further configured to determine number of distinct search results; the processor is further configured to compare the number of distinct search results to a limit of quantity of search results; and the processor is further configured to formulate a second query, launch the second query, and receive search results responsive to the second query before organizing the search results if the number of distinct search results responsive to the at least one query exceeds the limit of quantity of search results. | 0.5 |
9,396,185 | 11 | 20 | 11. A non-transitory computer readable medium containing program instructions, which when executed, perform a method for providing a contextual description of an object, the computer readable medium comprising program instructions for: receiving a first object having a first object type representing a person, the first object associated with a first user and including a first attribute associated with the respective person; identifying a second object having a second attribute related to the first attribute, the second object having a second object type representing an event; retrieving, from a data store, a first pre-defined phrase template corresponding to the first object type and a second pre-defined phrase template corresponding to the second object type; determining automatically a temporal phrase template including a temporal expression based on a time related to the event, the temporal phrase template selected from a plurality of phrase templates based on an interval of the time related to the event such that different phrase templates are associated with different intervals; dynamically combining the first pre-defined phrase template with the second pre-defined phrase template and with the temporal phrase template to form a linguistic prompt related to the person representing the first object, wherein the linguistic prompt comprises the first pre-defined phrase template, the second pre-defined phrase template, and the temporal phrase template; and presenting the linguistic prompt. | 11. A non-transitory computer readable medium containing program instructions, which when executed, perform a method for providing a contextual description of an object, the computer readable medium comprising program instructions for: receiving a first object having a first object type representing a person, the first object associated with a first user and including a first attribute associated with the respective person; identifying a second object having a second attribute related to the first attribute, the second object having a second object type representing an event; retrieving, from a data store, a first pre-defined phrase template corresponding to the first object type and a second pre-defined phrase template corresponding to the second object type; determining automatically a temporal phrase template including a temporal expression based on a time related to the event, the temporal phrase template selected from a plurality of phrase templates based on an interval of the time related to the event such that different phrase templates are associated with different intervals; dynamically combining the first pre-defined phrase template with the second pre-defined phrase template and with the temporal phrase template to form a linguistic prompt related to the person representing the first object, wherein the linguistic prompt comprises the first pre-defined phrase template, the second pre-defined phrase template, and the temporal phrase template; and presenting the linguistic prompt. 20. The computer readable medium of claim 11 wherein prior to presenting the linguistic prompt to the one of the first and second users, the computer readable medium comprises instructions for: analyzing the linguistic prompt to detect grammatical errors in the linguistic prompt; and correcting any detected grammatical errors. | 0.770629 |
9,508,028 | 7 | 13 | 7. At least one machine-readable storage medium, excluding a transitory propagating signal, and containing a set of instructions, which when executed by one or more processors, cause a data processor to: automatically detect at least two number words from a user-input set of text; convert the detected number words into a digit string; analyze context associated with the detected number words; automatically modify a format of the digit string based on the analyzed context, wherein automatically modifying a format of the digit string includes adding at least a punctuation character, a symbol character, or a space to the digit string based on the analyzed context associated with the detected number words. | 7. At least one machine-readable storage medium, excluding a transitory propagating signal, and containing a set of instructions, which when executed by one or more processors, cause a data processor to: automatically detect at least two number words from a user-input set of text; convert the detected number words into a digit string; analyze context associated with the detected number words; automatically modify a format of the digit string based on the analyzed context, wherein automatically modifying a format of the digit string includes adding at least a punctuation character, a symbol character, or a space to the digit string based on the analyzed context associated with the detected number words. 13. The machine-readable storage medium of claim 7 , wherein analyzing the context includes: determining a time of day, automatically determining a language associated with the text string, or determining a location of the device. | 0.600694 |
9,098,546 | 2 | 3 | 2. A computer program product as in claim 1 , wherein the query language architecture is implemented in a business software programming language as part of a business software architecture. | 2. A computer program product as in claim 1 , wherein the query language architecture is implemented in a business software programming language as part of a business software architecture. 3. A computer program product as in claim 2 , wherein the business software programming language comprises an advanced business application programming (ABAP) language. | 0.5 |
8,423,526 | 1 | 7 | 1. A system for comparing two or more phrases to determine a most common one of the two or more phrases, comprising: a linguistic interface for simultaneously submitting each of the two or more phrases as a search string to a search engine; and a linguistic analysis tool for receiving search results from the search engine for each of the two or more phrases, the linguistic analysis tool comparing the search results to determine the most common one of the two or more phrases; wherein the linguistic interface communicates with the linguistic analysis tool and displays the most common one of the two or more phrases to a user; and wherein the search results comprise a hit value that specifies the number of hits found by the search engine for the search string; wherein the linguistic interface and the linguistic analysis tool operate on a computer device. | 1. A system for comparing two or more phrases to determine a most common one of the two or more phrases, comprising: a linguistic interface for simultaneously submitting each of the two or more phrases as a search string to a search engine; and a linguistic analysis tool for receiving search results from the search engine for each of the two or more phrases, the linguistic analysis tool comparing the search results to determine the most common one of the two or more phrases; wherein the linguistic interface communicates with the linguistic analysis tool and displays the most common one of the two or more phrases to a user; and wherein the search results comprise a hit value that specifies the number of hits found by the search engine for the search string; wherein the linguistic interface and the linguistic analysis tool operate on a computer device. 7. The system of claim 1 , the linguistic analysis tool operating within the at least one search engine. | 0.73057 |
8,050,928 | 1 | 7 | 1. A method of speech to DTMF generation using sampling rate independent speech recognition, comprising: (a) receiving speech from a DTMF-controlled telecommunications system; (b) recognizing the speech received from the DTMF-controlled telecommunications system using sampling rate independent speech recognition; (c) identifying a speech segment contained in the speech received from the DTMF-controlled telecommunications system that corresponds with at least one keyword associated with user-defined data; and (d) transmitting at least one DTMF signal to the DTMF-controlled telecommunications system in response to the speech received from the DTMF-controlled telecommunications system using the user-defined data. | 1. A method of speech to DTMF generation using sampling rate independent speech recognition, comprising: (a) receiving speech from a DTMF-controlled telecommunications system; (b) recognizing the speech received from the DTMF-controlled telecommunications system using sampling rate independent speech recognition; (c) identifying a speech segment contained in the speech received from the DTMF-controlled telecommunications system that corresponds with at least one keyword associated with user-defined data; and (d) transmitting at least one DTMF signal to the DTMF-controlled telecommunications system in response to the speech received from the DTMF-controlled telecommunications system using the user-defined data. 7. The method of claim 1 , wherein the at least one keyword of step (a) describes user-defined data. | 0.803922 |
8,838,554 | 15 | 18 | 15. A system for altering confidential and non-confidential document content, the system comprising: a processor device configured to function as a rules server, said rules server comprising a set of expressions, said expressions that define predetermined confidential information that includes a social security number; machine-executable instructions comprising a communication plugin stored on one or more machine-readable media that provides a platform for incorporating the set of expressions into a document-producing application; machine-executable instructions comprising an inline document monitor module stored on one or more machine-readable media that forms part of the document-producing application, the inline document monitor for monitoring for the occurrence of a threshold number of social security numbers in the document; and in response to the occurrence of the threshold number of social security numbers in the document, the processor device is configured to: alter the entire document whereby: e-mail transmittal of confidential and non-confidential portions of the document is restricted; the confidential and non-confidential portions of the document are only available via a laptop computer when the laptop computer is docked at a predetermined docking station; and a watermark is attached to the document that identifies the confidential and non-confidential portions of the document as being confidential; monitor patterns of use of the document content; select the watermark based on a number of social security numbers in the document above the threshold; determine whether the patterns of use correspond to fraudulent activity; and whitelist the document when the number of social security numbers in the document is below the threshold number. | 15. A system for altering confidential and non-confidential document content, the system comprising: a processor device configured to function as a rules server, said rules server comprising a set of expressions, said expressions that define predetermined confidential information that includes a social security number; machine-executable instructions comprising a communication plugin stored on one or more machine-readable media that provides a platform for incorporating the set of expressions into a document-producing application; machine-executable instructions comprising an inline document monitor module stored on one or more machine-readable media that forms part of the document-producing application, the inline document monitor for monitoring for the occurrence of a threshold number of social security numbers in the document; and in response to the occurrence of the threshold number of social security numbers in the document, the processor device is configured to: alter the entire document whereby: e-mail transmittal of confidential and non-confidential portions of the document is restricted; the confidential and non-confidential portions of the document are only available via a laptop computer when the laptop computer is docked at a predetermined docking station; and a watermark is attached to the document that identifies the confidential and non-confidential portions of the document as being confidential; monitor patterns of use of the document content; select the watermark based on a number of social security numbers in the document above the threshold; determine whether the patterns of use correspond to fraudulent activity; and whitelist the document when the number of social security numbers in the document is below the threshold number. 18. The system of claim 15 wherein the inline document monitor is adapted to redact the set of expressions. | 0.643333 |
9,405,749 | 17 | 19 | 17. A non-transitory computer readable medium encoded with program instructions which are executed by a computer to provide a method of generating internal citations for a formatted document, the instructions comprising the steps of: a) obtaining graphic representations of each page of the formatted document, wherein the formatted document is a patent document, b) optically recognizing characters on each page of the formatted document, and determining the position of the characters on each page, c) obtaining a separate and distinct text version of the formatted document, d) parsing text from the text version, the parsed text being separate and distinct from the recognized characters, e) correlating the recognized characters with the parsed text to determine an internal citation for each sentence, wherein the internal citation identifies the document and a citation location inside the document where the corresponding sentence is found, f) creating a data structure storing data determined in the correlating step, and g) generating a patent corpus report using the correlation data structure, the patent corpus report comprising rows comprising: i) prior context, ii) a word or phrase, iii) subsequent context, and iv) an internal citation. | 17. A non-transitory computer readable medium encoded with program instructions which are executed by a computer to provide a method of generating internal citations for a formatted document, the instructions comprising the steps of: a) obtaining graphic representations of each page of the formatted document, wherein the formatted document is a patent document, b) optically recognizing characters on each page of the formatted document, and determining the position of the characters on each page, c) obtaining a separate and distinct text version of the formatted document, d) parsing text from the text version, the parsed text being separate and distinct from the recognized characters, e) correlating the recognized characters with the parsed text to determine an internal citation for each sentence, wherein the internal citation identifies the document and a citation location inside the document where the corresponding sentence is found, f) creating a data structure storing data determined in the correlating step, and g) generating a patent corpus report using the correlation data structure, the patent corpus report comprising rows comprising: i) prior context, ii) a word or phrase, iii) subsequent context, and iv) an internal citation. 19. The computer readable medium of claim 17 wherein the patent corpus report is based on one of the group of: a) a phrase, and b) a set of related words. | 0.564972 |
8,073,331 | 5 | 6 | 5. An optical system as in claim 1 , further comprising a plurality of lasers and detectors. | 5. An optical system as in claim 1 , further comprising a plurality of lasers and detectors. 6. An optical system as in claim 5 , further comprising a plurality of wavelength-stabilized lasers. | 0.813433 |
8,799,096 | 1 | 2 | 1. A computer-based method of scoring recommendations for potential purchase by a customer, comprising: executing code in a computer system to cause the computer system to perform: receiving a recommendation context from a customer; using the recommendation context to identify a plurality of candidate recommendations that match the recommendation context, where each candidate recommendation recommends at least one recommended item; determining a score for each candidate recommendation by subtracting a first expected margin value factor for the recommended item that is based on the candidate recommendation not being displayed from a second expected margin value factor for the recommended item that is based on the candidate recommendation being displayed; and ranking the plurality of candidate recommendations using the score for each candidate recommendation to identify at least a highest ranking candidate recommendation. | 1. A computer-based method of scoring recommendations for potential purchase by a customer, comprising: executing code in a computer system to cause the computer system to perform: receiving a recommendation context from a customer; using the recommendation context to identify a plurality of candidate recommendations that match the recommendation context, where each candidate recommendation recommends at least one recommended item; determining a score for each candidate recommendation by subtracting a first expected margin value factor for the recommended item that is based on the candidate recommendation not being displayed from a second expected margin value factor for the recommended item that is based on the candidate recommendation being displayed; and ranking the plurality of candidate recommendations using the score for each candidate recommendation to identify at least a highest ranking candidate recommendation. 2. The method of claim 1 , further comprising using a Bayesian network to determine the score for each candidate recommendation. | 0.93361 |
8,073,835 | 1 | 9 | 1. A method of building a custom word list for use in text operations on an electronic device, comprising the steps of: scanning a collection of text items associated with a user of the electronic device to identify words in the text items; assigning a weighting to each identified word; storing each identified word and its corresponding weighting; and determining a source of each text item in the collection of text items; wherein the step of assigning a weighting comprises the step of calculating the weighting for each identified word based on the source of the text item in which the word was identified. | 1. A method of building a custom word list for use in text operations on an electronic device, comprising the steps of: scanning a collection of text items associated with a user of the electronic device to identify words in the text items; assigning a weighting to each identified word; storing each identified word and its corresponding weighting; and determining a source of each text item in the collection of text items; wherein the step of assigning a weighting comprises the step of calculating the weighting for each identified word based on the source of the text item in which the word was identified. 9. The method of claim 1 , further comprising the steps of: categorizing the identified words into categories; and storing an indicator of the category of each identified word with the word and its corresponding weighting. | 0.73445 |
9,430,445 | 1 | 9 | 1. A document editor configured to display status and metadata for an object embedded in a document, the document editor comprising: a dispatcher for identifying the object, an identifier of the object, and an address of a remote service implemented in a computing apparatus and corresponding to the object in a user interface according to an object definition, and for providing object information to the user interface, wherein the object information includes the status and the metadata; the user interface for editing and displaying document information, wherein the user interface displays the status and the metadata of the object together with an object link, at least one of the status and the metadata being displayed with a special effect indicating a change detected in the status or the metadata of the object; and at least one connector for communicating with the remote service using the identifier and the address and for exchanging the status and the metadata with the remote service, and for transferring the status and the metadata to the dispatcher; the document editor being configured to determine whether the remote service is available or unavailable; wherein the user interface is configured to display the object as plain text if said document editor determines the remote service to be unavailable; wherein said at least one connector periodically communicates with the remote service to exchange the object information, the special effect indicating the change detected since a previous periodic communication between said at least one connector and the remote service. | 1. A document editor configured to display status and metadata for an object embedded in a document, the document editor comprising: a dispatcher for identifying the object, an identifier of the object, and an address of a remote service implemented in a computing apparatus and corresponding to the object in a user interface according to an object definition, and for providing object information to the user interface, wherein the object information includes the status and the metadata; the user interface for editing and displaying document information, wherein the user interface displays the status and the metadata of the object together with an object link, at least one of the status and the metadata being displayed with a special effect indicating a change detected in the status or the metadata of the object; and at least one connector for communicating with the remote service using the identifier and the address and for exchanging the status and the metadata with the remote service, and for transferring the status and the metadata to the dispatcher; the document editor being configured to determine whether the remote service is available or unavailable; wherein the user interface is configured to display the object as plain text if said document editor determines the remote service to be unavailable; wherein said at least one connector periodically communicates with the remote service to exchange the object information, the special effect indicating the change detected since a previous periodic communication between said at least one connector and the remote service. 9. The document editor of claim 1 , wherein the dispatcher, upon identifying the object and before embedding the object, is configured to check whether the editor can process the object and whether the editor has a corresponding connector for communicating with the remote service. | 0.630263 |
7,873,657 | 1 | 7 | 1. A computer implemented method of processing user input to an information retrieval component within a computer wherein the computer implemented method includes a defining session between a user and an information retrieval component and an execution session between the user and an information retrieval component, the computer implemented method comprising: during the defining session: (a) receiving and storing a user generated definition of an expression type wherein the expression type is capable of being characterized as a (i) query seeking information from the information retrieval component, (ii) a statement seeking to add new information to the information retrieval component, and (iii) a command to perform an action, wherein the definition of the expression type specifies an expression format having a semantic structure, a response type, and a display format; during the execution session: (b) receiving a user generated expression having a semantic structure that matches a semantic structure that was received and stored during the defining session; (c) identifying an expression type for the received expression by determining: (i) whether the received expression semantically matches a command; (ii) whether the received expression is an answer to a question; (iii) whether a query of the information retrieval component using the received expression exactly as phrased results in identification of stored information associated with the received expression; and (iv) whether the received expression is an implicit command to add data to the information retrieval component; (d) processing the received expression according to the response type specified by the definition of the expression type for the received expression; and (e) causing a response to the received expression to be displayed to the user according to the display format specified by the definition of the identified expression type for the received expression. | 1. A computer implemented method of processing user input to an information retrieval component within a computer wherein the computer implemented method includes a defining session between a user and an information retrieval component and an execution session between the user and an information retrieval component, the computer implemented method comprising: during the defining session: (a) receiving and storing a user generated definition of an expression type wherein the expression type is capable of being characterized as a (i) query seeking information from the information retrieval component, (ii) a statement seeking to add new information to the information retrieval component, and (iii) a command to perform an action, wherein the definition of the expression type specifies an expression format having a semantic structure, a response type, and a display format; during the execution session: (b) receiving a user generated expression having a semantic structure that matches a semantic structure that was received and stored during the defining session; (c) identifying an expression type for the received expression by determining: (i) whether the received expression semantically matches a command; (ii) whether the received expression is an answer to a question; (iii) whether a query of the information retrieval component using the received expression exactly as phrased results in identification of stored information associated with the received expression; and (iv) whether the received expression is an implicit command to add data to the information retrieval component; (d) processing the received expression according to the response type specified by the definition of the expression type for the received expression; and (e) causing a response to the received expression to be displayed to the user according to the display format specified by the definition of the identified expression type for the received expression. 7. The computer implemented method of claim 1 , wherein the received expression comprises a plurality of words having a semantic structure. | 0.705508 |
8,560,436 | 5 | 6 | 5. The method of claim 1 wherein the assessment score further comprises a credit worthiness score which is determined comprising a profile criteria score, a lending history score, the base score and the endorsement score wherein each score has an associated weighting to determine the assessment score. | 5. The method of claim 1 wherein the assessment score further comprises a credit worthiness score which is determined comprising a profile criteria score, a lending history score, the base score and the endorsement score wherein each score has an associated weighting to determine the assessment score. 6. The method of claim 5 wherein the profile criteria score further comprises a score for verified identification and a retrieved credit bureau score for the borrowing party. | 0.5 |
7,783,620 | 16 | 19 | 16. A system for determining a relevancy ranking score, comprising: a processor; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to: receive a query including one or more constraints, wherein one of the one or more constraints includes an operator, wherein the operator comprises one or more of the following: CONTAINS, DOES_NOT_CONTAIN, BEGINS_WITH, ENDS_WITH, ALWAYS_WITHIN, AND, OR, NOT, EQUALS, NOT_EQUALS, GREATER_THAN, LESS_THAN, GREATER_THAN_OR_EQUAL_TO, LESS_THAN_OR_EQUAL_TO; receive a search result based on the query; and determine the relevancy ranking score for the received search result based at least in part on the operator associated with the one or more constraints of the query, wherein the relevancy ranking score comprises a sum of three or more feature scores each multiplied by a separate weight, wherein the three or more feature scores comprise a scope or depth score, an accuracy or validity score, a clarity score, a currency score, or a source score, and wherein the scope or depth score comprises a score indicating satisfied constraints, and wherein the accuracy or validity score comprises a score indicating constraints improving query precision, and wherein the clarity score comprises a score indicating information presented in a clear manner, and wherein the currency score comprises a score indicating more recent results, and wherein the source score comprises a score indicating source quality, wherein presented in the clear manner for the clarity score comprises having a higher score in an event in which a title, an abstract, or a date is present. | 16. A system for determining a relevancy ranking score, comprising: a processor; and a memory coupled with the processor, wherein the memory is configured to provide the processor with instructions which when executed cause the processor to: receive a query including one or more constraints, wherein one of the one or more constraints includes an operator, wherein the operator comprises one or more of the following: CONTAINS, DOES_NOT_CONTAIN, BEGINS_WITH, ENDS_WITH, ALWAYS_WITHIN, AND, OR, NOT, EQUALS, NOT_EQUALS, GREATER_THAN, LESS_THAN, GREATER_THAN_OR_EQUAL_TO, LESS_THAN_OR_EQUAL_TO; receive a search result based on the query; and determine the relevancy ranking score for the received search result based at least in part on the operator associated with the one or more constraints of the query, wherein the relevancy ranking score comprises a sum of three or more feature scores each multiplied by a separate weight, wherein the three or more feature scores comprise a scope or depth score, an accuracy or validity score, a clarity score, a currency score, or a source score, and wherein the scope or depth score comprises a score indicating satisfied constraints, and wherein the accuracy or validity score comprises a score indicating constraints improving query precision, and wherein the clarity score comprises a score indicating information presented in a clear manner, and wherein the currency score comprises a score indicating more recent results, and wherein the source score comprises a score indicating source quality, wherein presented in the clear manner for the clarity score comprises having a higher score in an event in which a title, an abstract, or a date is present. 19. A system as in claim 16 , wherein the processor is further configured to calculate a relevancy ranking based at least in part on the relevancy ranking score for a plurality of search results resulting from the search query. | 0.70288 |
8,635,340 | 16 | 17 | 16. The method of claim 12 , further comprising selecting a domain name registration provider from a plurality of domain name registration providers to process the domain name registration request. | 16. The method of claim 12 , further comprising selecting a domain name registration provider from a plurality of domain name registration providers to process the domain name registration request. 17. The method of claim 16 , wherein the domain name registration provider comprises at least one of a domain name registrar, domain name reseller, or domain name affiliate. | 0.671103 |
8,041,730 | 1 | 21 | 1. A computer-implemented method, comprising: receiving a query term and a possible synonym for the query term; accessing a geographic data set that associates geographic location names with corresponding positions in a tree structure, wherein different positions in the tree structure that share a same level correspond to different geographic locations that share a same geographic region type; identifying a first position in the tree structure of the query term and identifying a second position in the tree structure of the possible synonym for the query term; determining that the query term and the possible synonym for the query term are problem synonyms based at least on a relative position of the first position in the tree structure with respect to the second position in the tree structure wherein the problem synonyms are two terms that have related geographic contexts according to the tree structure; and notifying a search engine that the query term and the possible synonym for the query term are problem synonyms. | 1. A computer-implemented method, comprising: receiving a query term and a possible synonym for the query term; accessing a geographic data set that associates geographic location names with corresponding positions in a tree structure, wherein different positions in the tree structure that share a same level correspond to different geographic locations that share a same geographic region type; identifying a first position in the tree structure of the query term and identifying a second position in the tree structure of the possible synonym for the query term; determining that the query term and the possible synonym for the query term are problem synonyms based at least on a relative position of the first position in the tree structure with respect to the second position in the tree structure wherein the problem synonyms are two terms that have related geographic contexts according to the tree structure; and notifying a search engine that the query term and the possible synonym for the query term are problem synonyms. 21. The method of claim 1 , wherein when the query term occurs at multiple positions in the tree structure, the method further comprising repeating the determining that the query term and the possible synonym for the query term are problem synonyms for each of the multiple positions in the tree structure. | 0.719266 |
9,349,097 | 1 | 2 | 1. A data-processing device ( 1 ) comprising: a memory ( 10 ) organized into two spaces, a first space containing attributes describing the stored data, and a second space containing connexity links among the stored data, and, according to one or more dimensions respectively associated with the attributes and divided into one or more hierarchized segments, the data being inputted by creating, deleting or modifying the values of the attributes characterizing said segments; an integrator ( 11 ) for integrating one or more incoming information streams, which analyzes said streams to determine the data constituting said streams and to structure said data and the attributes thereof according to the organization of said memory ( 10 ); an inference engine ( 14 ) implementing, in parallel or in series, inference rules ( 141 ) grouped together in libraries ( 15 ), said rules ( 141 ) being programmed to regenerate a sequence including at least one segment of the memory, by creating, deleting or modifying at least one of a datum, an attribute value, and a connexity link during the implementation thereof in the at least one space of the memory, a resources allocator ( 13 ), which activates or deactivates the inference rules ( 141 ) on the basis of a priority rule, a data extractor ( 12 ), which identifies data by programming and by at least one of a selected attribute value and a selected connexity link, located in one or more selected segments of the memory ( 10 ), and providing identified data in one or more outgoing information streams. | 1. A data-processing device ( 1 ) comprising: a memory ( 10 ) organized into two spaces, a first space containing attributes describing the stored data, and a second space containing connexity links among the stored data, and, according to one or more dimensions respectively associated with the attributes and divided into one or more hierarchized segments, the data being inputted by creating, deleting or modifying the values of the attributes characterizing said segments; an integrator ( 11 ) for integrating one or more incoming information streams, which analyzes said streams to determine the data constituting said streams and to structure said data and the attributes thereof according to the organization of said memory ( 10 ); an inference engine ( 14 ) implementing, in parallel or in series, inference rules ( 141 ) grouped together in libraries ( 15 ), said rules ( 141 ) being programmed to regenerate a sequence including at least one segment of the memory, by creating, deleting or modifying at least one of a datum, an attribute value, and a connexity link during the implementation thereof in the at least one space of the memory, a resources allocator ( 13 ), which activates or deactivates the inference rules ( 141 ) on the basis of a priority rule, a data extractor ( 12 ), which identifies data by programming and by at least one of a selected attribute value and a selected connexity link, located in one or more selected segments of the memory ( 10 ), and providing identified data in one or more outgoing information streams. 2. The device according to claim 1 , wherein the memory ( 10 ) is organized in at least three dimensions, of which at least one time dimension associating with the data one or more attributes making it possible to date the memorization of the data, an idiosyncratic dimension associating with the data one or more attributes making it possible to determine the relative specificity of the data, a conceptual dimension associating with the data one or more attributes making it possible to hierarchize the data according to levels of abstraction ( 100 ). | 0.5 |
8,654,682 | 10 | 14 | 10. An apparatus in a group manager of a central service node for enabling services or media in a communication network, comprising: a monitoring unit adapted to detect activities and conditions of communication devices in the network, a context collecting unit adapted to, for each of a plurality of entities, collect individual context data relating to the entity, the individual context data comprising a first data value corresponding to a first behavioral context parameter, and a second data value corresponding to a first environmental context parameter, wherein first behavioral context parameter is separate and distinct from the first environmental context parameter, a context vector unit adapted to, for each of the plurality of said entities, create an individual context vector for said entity from said collected individual context data related to said entity wherein each of said plurality of context vectors identifies a point in a logical, as opposed to a physical, N-dimensional space, where N is greater than or equal to two, the context vector unit further adapted to create a master context vector comprising a third data value corresponding to the first behavioral context parameter, and a fourth data value corresponding to the first environmental context parameter, wherein the master context vector identifies a centroid point in the logical N-dimensional space, a distance calculating unit adapted to determine, for each of the plurality of said individual context vectors, the distance between the centroid point and the point identified by said individual context vector, and a group defining unit adapted to define a group of correlated entities that are found to be correlated or similar with respect to one or more features or characteristics based on the collected individual context data by including an entity in the group in response to determining that the distance between the centroid point and the point identified by said individual context vector corresponding to said entity is less than a threshold. | 10. An apparatus in a group manager of a central service node for enabling services or media in a communication network, comprising: a monitoring unit adapted to detect activities and conditions of communication devices in the network, a context collecting unit adapted to, for each of a plurality of entities, collect individual context data relating to the entity, the individual context data comprising a first data value corresponding to a first behavioral context parameter, and a second data value corresponding to a first environmental context parameter, wherein first behavioral context parameter is separate and distinct from the first environmental context parameter, a context vector unit adapted to, for each of the plurality of said entities, create an individual context vector for said entity from said collected individual context data related to said entity wherein each of said plurality of context vectors identifies a point in a logical, as opposed to a physical, N-dimensional space, where N is greater than or equal to two, the context vector unit further adapted to create a master context vector comprising a third data value corresponding to the first behavioral context parameter, and a fourth data value corresponding to the first environmental context parameter, wherein the master context vector identifies a centroid point in the logical N-dimensional space, a distance calculating unit adapted to determine, for each of the plurality of said individual context vectors, the distance between the centroid point and the point identified by said individual context vector, and a group defining unit adapted to define a group of correlated entities that are found to be correlated or similar with respect to one or more features or characteristics based on the collected individual context data by including an entity in the group in response to determining that the distance between the centroid point and the point identified by said individual context vector corresponding to said entity is less than a threshold. 14. The apparatus according to claim 10 , wherein updating the group includes excluding or adding an entity from/to the group. | 0.856492 |
9,646,611 | 4 | 15 | 4. The computing system of claim 3 , wherein the instructions, when executed, configure the computing system to provide: a relevancy generator configured to a relevancy measure for each of the different search results to obtain a given search result. | 4. The computing system of claim 3 , wherein the instructions, when executed, configure the computing system to provide: a relevancy generator configured to a relevancy measure for each of the different search results to obtain a given search result. 15. The computing system of claim 4 wherein the action identifier is configured to identify the action as one of send, open, schedule a meeting, create, attach, email, set a reminder, share, present, launch and display. | 0.800909 |
4,015,087 | 14 | 15 | 14. The invention as set forth in claim 12 including switch means connected between said heterodyne detector means and said display means for enabling and inhibiting the application of said video signals thereto, means operated by said first and second pulses for providing a control signal level which enables said switch means in the interval between said first and second pulses and inhibits said switch means in the interval between said second and first pulses whereby to blank said display in the latter interval. | 14. The invention as set forth in claim 12 including switch means connected between said heterodyne detector means and said display means for enabling and inhibiting the application of said video signals thereto, means operated by said first and second pulses for providing a control signal level which enables said switch means in the interval between said first and second pulses and inhibits said switch means in the interval between said second and first pulses whereby to blank said display in the latter interval. 15. The invention as set forth in claim 14 wherein said vertical sweep generator includes a first digital to analog converter connected to said second counter for providing as a vertical sweep signal a staircase voltage which increases with increasing counts in said second counter, said fast horizontal sweep generator comprises circuit means for generating a ramp wave which increases in amplitude in the interval between said first and second pulses, and said slow horizontal sweep generator includes a second digital to analog converter connected to said third counter. | 0.5 |
4,841,441 | 1 | 11 | 1. A method of constructing a data model of an organizational structure and the operation thereof which comprises the stages of analysing data provided by the customer organization (analysis), designing application software (procedure design), writing programs which collectively enable control of the operating procedures of the organization (programming) and testing the individual programs characterized by performing the stage of analysis with a data processing machine, wherein the analysis stage comprises: storing in memory of the machine a source series of questions which are presentable in conversational language concerning the entities in the organizational structure, the attributes of those entities, and the relationship between the entities; and constructing a data model from the answers. | 1. A method of constructing a data model of an organizational structure and the operation thereof which comprises the stages of analysing data provided by the customer organization (analysis), designing application software (procedure design), writing programs which collectively enable control of the operating procedures of the organization (programming) and testing the individual programs characterized by performing the stage of analysis with a data processing machine, wherein the analysis stage comprises: storing in memory of the machine a source series of questions which are presentable in conversational language concerning the entities in the organizational structure, the attributes of those entities, and the relationship between the entities; and constructing a data model from the answers. 11. A method of constructing a data model as claimed in claim 1 including the further steps of determining the nature of the attribute by asking; 1. Can there be more than one attribute for each entity? 2. Can the attribute have a limited set of values? 3. Can the attribute have an attribute of its own? and in response to the answers provided by the user either entering the attribute in a table in the memory containing spaces for the reception of subsequent qualifying information or presenting further questions to determine the precise nature of the attribute. | 0.5 |
9,418,281 | 19 | 20 | 19. The system of claim 18 , wherein the operations further comprise: determining, by the computing device, that a beginning point of a third stroke of the sequence of strokes that immediately follows the second stroke occurs between the left edge of the second stroke and the right edge of the second stroke. | 19. The system of claim 18 , wherein the operations further comprise: determining, by the computing device, that a beginning point of a third stroke of the sequence of strokes that immediately follows the second stroke occurs between the left edge of the second stroke and the right edge of the second stroke. 20. The system of claim 19 , wherein the operations further comprise: determining, by the computing device, that a distance between the beginning point of the third stroke and the left edge of the second stroke satisfies a threshold distance. | 0.5 |
7,536,408 | 10 | 11 | 10. A method of indexing documents in a document collection, each document having an associated identifier, the method comprising: providing a list of valid phrases, wherein each phrase on the list appears a minimum number of times in the document collection, and predicts at least one other phrase, wherein for each phrase g j , g k predicts g j where an information gain I of g k with respect to g j exceeds a predetermined threshold, the information gain I being a function of A(j,k) and E(j,k), where A(j,k) is a measure of an actual co-occurrence rate of g j and g k , and E(j,k) is an expected co-occurrence rate g j and g k ; accessing a plurality of documents in the document collection; for each accessed document, identifying, by operation of a processor adapted to manipulate data within a computer system, phrases from the list of valid phrases that are present in the document; and for each identified phrase in the document, indexing, by operation of a processor adapted to manipulate data within a computer system, the document by storing the identifier of the document in a posting list of the phrase. | 10. A method of indexing documents in a document collection, each document having an associated identifier, the method comprising: providing a list of valid phrases, wherein each phrase on the list appears a minimum number of times in the document collection, and predicts at least one other phrase, wherein for each phrase g j , g k predicts g j where an information gain I of g k with respect to g j exceeds a predetermined threshold, the information gain I being a function of A(j,k) and E(j,k), where A(j,k) is a measure of an actual co-occurrence rate of g j and g k , and E(j,k) is an expected co-occurrence rate g j and g k ; accessing a plurality of documents in the document collection; for each accessed document, identifying, by operation of a processor adapted to manipulate data within a computer system, phrases from the list of valid phrases that are present in the document; and for each identified phrase in the document, indexing, by operation of a processor adapted to manipulate data within a computer system, the document by storing the identifier of the document in a posting list of the phrase. 11. The method of claim 10 , wherein the predetermined threshold is about 1.5. | 0.5 |
8,725,492 | 1 | 7 | 1. A method to be executed at least in part in a computing device for recognizing multiple semantic items from a single utterance, the method comprising: receiving a single utterance including at least two semantically distinct items from a user; performing a speech recognition operation on the single utterance to recognize a first item of the at least two semantically distinct items; determining a constraint based on the recognition of the first item; performing another speech recognition operation on the single utterance to recognize a second item of the at least two semantically distinct items based on the determined constraint, wherein performing the speech recognition operation includes obtaining a plurality of alternative values for the first item; providing the alternative values for the first item to the user; and receiving a user selection for one of the alternative values, wherein providing the alternative values to the user includes one of: a single step presentation that includes a combination of an alternative value for the first item and a value for the second item based on the alternative value for the first item selected according to a statistical language model; and a visual menu presentation that includes a listing of combinations of the alternative values for the first item and values for the second item based on the alternative values for the first item selected according to the statistical language model. | 1. A method to be executed at least in part in a computing device for recognizing multiple semantic items from a single utterance, the method comprising: receiving a single utterance including at least two semantically distinct items from a user; performing a speech recognition operation on the single utterance to recognize a first item of the at least two semantically distinct items; determining a constraint based on the recognition of the first item; performing another speech recognition operation on the single utterance to recognize a second item of the at least two semantically distinct items based on the determined constraint, wherein performing the speech recognition operation includes obtaining a plurality of alternative values for the first item; providing the alternative values for the first item to the user; and receiving a user selection for one of the alternative values, wherein providing the alternative values to the user includes one of: a single step presentation that includes a combination of an alternative value for the first item and a value for the second item based on the alternative value for the first item selected according to a statistical language model; and a visual menu presentation that includes a listing of combinations of the alternative values for the first item and values for the second item based on the alternative values for the first item selected according to the statistical language model. 7. The method of claim 1 , further comprising: providing the recognized first item to the user; receiving one of a user correction and a user confirmation for the provided first item; and determining the constraint based on one of the user corrected and user confirmed first item. | 0.556962 |
9,558,400 | 1 | 4 | 1. A computer-implemented method comprising: identifying, using one or more computing devices, a field in a set of forms and strokes included in the field; determining, using the one or more computing devices, distance metrics between the strokes; creating, using the one or more computing devices, a hierarchical cluster for the strokes included in the field based on the distance metrics; receiving a search query from a first user, the search query including a first stroke extracted from the field of a form filled out by a second user; retrieving, using the one or more computing devices, a cluster from the hierarchical cluster and example strokes of the cluster similar to the search query; providing the example strokes to the first user; receiving, from the first user, a selection of a first example stroke from the provided example strokes; and responsive to receiving, from the first user, the selection of the first example stroke, retrieving a table listing a number of forms in the set of forms that were filled out by the second user and have strokes similar to the first example stroke. | 1. A computer-implemented method comprising: identifying, using one or more computing devices, a field in a set of forms and strokes included in the field; determining, using the one or more computing devices, distance metrics between the strokes; creating, using the one or more computing devices, a hierarchical cluster for the strokes included in the field based on the distance metrics; receiving a search query from a first user, the search query including a first stroke extracted from the field of a form filled out by a second user; retrieving, using the one or more computing devices, a cluster from the hierarchical cluster and example strokes of the cluster similar to the search query; providing the example strokes to the first user; receiving, from the first user, a selection of a first example stroke from the provided example strokes; and responsive to receiving, from the first user, the selection of the first example stroke, retrieving a table listing a number of forms in the set of forms that were filled out by the second user and have strokes similar to the first example stroke. 4. The method of claim 1 , wherein determining the distance metrics between the strokes further comprises: performing feature extraction on the strokes included in the field; and determining a feature distance between pairs of strokes. | 0.667139 |
9,558,267 | 8 | 9 | 8. The method as claimed in claim 1 , wherein said combining comprises assigning weights to the classified plurality of representational variations of the user related content information from each of the plurality of analyzers. | 8. The method as claimed in claim 1 , wherein said combining comprises assigning weights to the classified plurality of representational variations of the user related content information from each of the plurality of analyzers. 9. The method as claimed in claim 8 , wherein said combining further comprises summing the weighted classified plurality of representational variations of the user related content information from each of the plurality of analyzers. | 0.5 |
9,881,053 | 17 | 21 | 17. A processor readable non-transitory storage media that includes instructions for managing data, wherein execution of the instructions by one or more hardware processors performs actions, comprising: providing a principal data set and another data set, wherein the principal data set includes a plurality of principal objects and the other data set includes a plurality of other objects; instantiating a first engine to perform actions including: associating each of the plurality of principal objects with one or more other objects that are selected from the plurality of other objects, wherein the one or more other objects are selected as potential matches to one or more of the principal objects; selecting one or more principal objects of the plurality of principal objects based on one or more heuristics and the one or more selected principal objects association with selected other objects; and labeling one or more of the selected other objects as either a match or a non-match of their associated principal object; and instantiating a second engine to perform actions, including: training a ranker to identify a selected other object that is top-ranked in similarity to its association with the one or more principal objects based on the labeling of the one or more selected other objects; and employing the trained ranker to indicate a match among the plurality of principal objects and the plurality of other objects; and instantiating a third engine to selectively filter the plurality of other objects to rank each matched other object higher than other objects associated with a same principal object, wherein geolocation information from a GPS device is employed to localize a display of the ranked other objects including one or more of time zone or language, and wherein a hardware security module is used to provide tamper resistant safeguarding of cryptographic information. | 17. A processor readable non-transitory storage media that includes instructions for managing data, wherein execution of the instructions by one or more hardware processors performs actions, comprising: providing a principal data set and another data set, wherein the principal data set includes a plurality of principal objects and the other data set includes a plurality of other objects; instantiating a first engine to perform actions including: associating each of the plurality of principal objects with one or more other objects that are selected from the plurality of other objects, wherein the one or more other objects are selected as potential matches to one or more of the principal objects; selecting one or more principal objects of the plurality of principal objects based on one or more heuristics and the one or more selected principal objects association with selected other objects; and labeling one or more of the selected other objects as either a match or a non-match of their associated principal object; and instantiating a second engine to perform actions, including: training a ranker to identify a selected other object that is top-ranked in similarity to its association with the one or more principal objects based on the labeling of the one or more selected other objects; and employing the trained ranker to indicate a match among the plurality of principal objects and the plurality of other objects; and instantiating a third engine to selectively filter the plurality of other objects to rank each matched other object higher than other objects associated with a same principal object, wherein geolocation information from a GPS device is employed to localize a display of the ranked other objects including one or more of time zone or language, and wherein a hardware security module is used to provide tamper resistant safeguarding of cryptographic information. 21. The media of claim 17 , wherein labeling the one or more selected other objects, further comprises: communicating each of the one or more principal objects and their associated selected other objects to a user; and displaying each of the one or more principal objects and their associated selected other objects to the user; and enabling the user to identify a match with the one or more principal data objects from among the displayed selected other objects. | 0.74837 |
8,064,576 | 7 | 9 | 7. The integrated messaging system of claim 6 , wherein the filter/transcribe module is further configured to generate an email message containing the rough transcription and the priority flag. | 7. The integrated messaging system of claim 6 , wherein the filter/transcribe module is further configured to generate an email message containing the rough transcription and the priority flag. 9. The integrated messaging system of claim 7 , wherein the filter/transcribe module is further configured to send the email message to at least one user device. | 0.616667 |
8,364,470 | 13 | 14 | 13. A computer program product comprising a computer useable storage device having a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: provide a list of reference terms; break down text and a list of reference terms into tokens; generate at least one acronym candidate in the text for mapping to at least one of the reference terms; compare characters of the acronym candidate to characters of the reference term according to one or more mapping rules; generate a confidence value of the mapping based on said comparison of characters; and rank acronym candidates according to their confidence value. | 13. A computer program product comprising a computer useable storage device having a computer readable program, wherein the computer readable program when executed on a computer causes the computer to: provide a list of reference terms; break down text and a list of reference terms into tokens; generate at least one acronym candidate in the text for mapping to at least one of the reference terms; compare characters of the acronym candidate to characters of the reference term according to one or more mapping rules; generate a confidence value of the mapping based on said comparison of characters; and rank acronym candidates according to their confidence value. 14. The computer program product of claim 13 , wherein the computer readable program when executed on a computer further causes the computer to: determine a number of characters of the acronym candidate which map to characters of the reference term; determine an order of the characters in the acronym candidate which map to characters of the reference term; and determine the confidence value of the mapping based on said number and order of characters. | 0.701316 |
7,664,313 | 1 | 6 | 1. A computer-implemented method of generating a set of tuple-term pairs from a corpus of text, comprising: compiling via a processor a set of concordance lines for a set of terms in the corpus; storing a first set of verb-argument tuples and associated terms from the set of concordance lines; computing via the processor a numerical quantification of a strength of association between each verb-argument tuple and associated term in the first set; selecting, from the first set, each verb-argument tuple and associated term whose numerical quantification of strength of association is greater than a predetermined threshold, wherein the selected verb-argument tuples and associated terms form the set of the tuple-term pairs representing most likely actions associated with the set of terms; identifying each tuple-term pair in the set of tuple-term pairs having a verb that matches a verb in a sentence input to a text-to-scene conversion system that constructs an arbitrary three-dimensional scene from input text without using previously stored images; and storing the identified tuple-term pairs in a database. | 1. A computer-implemented method of generating a set of tuple-term pairs from a corpus of text, comprising: compiling via a processor a set of concordance lines for a set of terms in the corpus; storing a first set of verb-argument tuples and associated terms from the set of concordance lines; computing via the processor a numerical quantification of a strength of association between each verb-argument tuple and associated term in the first set; selecting, from the first set, each verb-argument tuple and associated term whose numerical quantification of strength of association is greater than a predetermined threshold, wherein the selected verb-argument tuples and associated terms form the set of the tuple-term pairs representing most likely actions associated with the set of terms; identifying each tuple-term pair in the set of tuple-term pairs having a verb that matches a verb in a sentence input to a text-to-scene conversion system that constructs an arbitrary three-dimensional scene from input text without using previously stored images; and storing the identified tuple-term pairs in a database. 6. The method of claim 1 , further comprising deleting duplicate concordance lines from the set of concordance lines. | 0.913589 |
8,311,848 | 1 | 4 | 1. An electronic medical records system, comprising: a processor; a computer readable storage media that comprises instructions stored in the computer readable storage media that are executable with the processor, the instructions comprising: instructions to prompt a user to select one of a selection view and an anatomical view; instructions to display a first list of pre-defined medical conditions in response to receipt of a view selection command indicative of a user selection of the selection view; instructions to retrieve and display an anatomical human image in response to the view selection command being indicative of selection of the anatomical view; instructions to display a second list of pre-defined medical conditions for an area of the anatomical human image in response to an area command indicative of selection by the user of the area of the anatomical human image; instructions to display a list of blue prints that are associated with a selected one of the pre-defined medical conditions, each of the listed blue prints including control variables, at least some of which appear in multiple of the listed blue prints; instructions to launch a blue print in response to receipt of a signal indicative of a selection of the blue print from the list of blue prints; instructions to retrieve and display any one of a blue print template, a key questions list, or an interactive question series that correspond to the launched blue print associated with the one of the pre-defined medical conditions associated with either the selection view or the anatomical human image; instructions to receive user entry of patient specific data into a selected one of the blue print template, the key questions list, or the interactive question series for a particular patient to populate the launched blue print; and instructions responsive to user entry of the patient specific data to generate a predetermined sentence structure having one or more fillable data locations mapped to receive respective control variables, the one or more fillable data locations positioned within predetermined sentences forming a paragraph that is stored in connection with the launched blue print, at least some of the one or more respective control variables also mapped to fillable data locations included in other blueprints associated with the one of the pre-defined medical conditions and used to generate the predetermined sentence structure in connection with the other blueprints. | 1. An electronic medical records system, comprising: a processor; a computer readable storage media that comprises instructions stored in the computer readable storage media that are executable with the processor, the instructions comprising: instructions to prompt a user to select one of a selection view and an anatomical view; instructions to display a first list of pre-defined medical conditions in response to receipt of a view selection command indicative of a user selection of the selection view; instructions to retrieve and display an anatomical human image in response to the view selection command being indicative of selection of the anatomical view; instructions to display a second list of pre-defined medical conditions for an area of the anatomical human image in response to an area command indicative of selection by the user of the area of the anatomical human image; instructions to display a list of blue prints that are associated with a selected one of the pre-defined medical conditions, each of the listed blue prints including control variables, at least some of which appear in multiple of the listed blue prints; instructions to launch a blue print in response to receipt of a signal indicative of a selection of the blue print from the list of blue prints; instructions to retrieve and display any one of a blue print template, a key questions list, or an interactive question series that correspond to the launched blue print associated with the one of the pre-defined medical conditions associated with either the selection view or the anatomical human image; instructions to receive user entry of patient specific data into a selected one of the blue print template, the key questions list, or the interactive question series for a particular patient to populate the launched blue print; and instructions responsive to user entry of the patient specific data to generate a predetermined sentence structure having one or more fillable data locations mapped to receive respective control variables, the one or more fillable data locations positioned within predetermined sentences forming a paragraph that is stored in connection with the launched blue print, at least some of the one or more respective control variables also mapped to fillable data locations included in other blueprints associated with the one of the pre-defined medical conditions and used to generate the predetermined sentence structure in connection with the other blueprints. 4. The electronic medical records system of claim 1 , wherein the control variables comprise an automatic control variable populated by the system with pre-existing patient specific data, a manual control variable populated with the user entry of the patient specific data in response to a user selection of the patient specific data from a predetermined choice list of variables, and a semi-automatic control variable automatically populated by the system with additional patient specific data in response to receipt by the system of the user entry of the patient specific data. | 0.5 |
8,910,130 | 12 | 13 | 12. The method according to claim 1 , wherein the 4GL identifier is a 4GL program header transforming the 3GL and/or Assembler program into a 4GL executable without modifying the 3GL and/or Assembler program. | 12. The method according to claim 1 , wherein the 4GL identifier is a 4GL program header transforming the 3GL and/or Assembler program into a 4GL executable without modifying the 3GL and/or Assembler program. 13. The method according to claim 12 , wherein the 4GL program header includes Natural Optimization Code parameters identifying the 3GL and/or Assembler program as Natural Optimization Code to be executed in the 4GL runtime environment. | 0.5 |
10,114,897 | 13 | 14 | 13. The apparatus of claim 8 , wherein the processor is further configured to create alias keyword terms from the most recent interest, and apply the alias keyword terms to the combined query. | 13. The apparatus of claim 8 , wherein the processor is further configured to create alias keyword terms from the most recent interest, and apply the alias keyword terms to the combined query. 14. The apparatus of claim 13 , wherein the processor is further configured to access a third party website application programming interface and applying the alias keyword terms to content included in the application programming interface, and populate the table with relevant content retrieved from the application programming interface. | 0.5 |
9,640,179 | 15 | 16 | 15. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform acts comprising: measuring a value of an acoustic characteristic of an environment, the measuring comprising: instructing a speaker to emit a known sound in the environment; capturing reflected sound, the reflected sound corresponding to reflection of the known sound by the environment; and comparing characteristics of the known sound to characteristics of the reflected sound at least in part to identify the acoustic characteristic; capturing speech uttered by a user within the environment; generating an audio signal that includes the speech; processing the audio signal by applying a set of beamformer coefficients to the audio signal to generate a processed audio signal that represents a beampattern, the beampattern having multiple lobes each focused on a region within the environment; determining a portion of the processed audio signal corresponding to one or more lobes of the beampattern focused on one or more regions from which user speech was previously determined to have originated from; comparing the value of the acoustic characteristic to a previously measured value of the acoustic characteristic of the environment; and at least partly in response to determining that the value and the previously measured value differ by less than a threshold amount, applying relatively more processing resources to the portion of the processed audio signal and relatively less processing resources to a remainder of the processed audio signal. | 15. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform acts comprising: measuring a value of an acoustic characteristic of an environment, the measuring comprising: instructing a speaker to emit a known sound in the environment; capturing reflected sound, the reflected sound corresponding to reflection of the known sound by the environment; and comparing characteristics of the known sound to characteristics of the reflected sound at least in part to identify the acoustic characteristic; capturing speech uttered by a user within the environment; generating an audio signal that includes the speech; processing the audio signal by applying a set of beamformer coefficients to the audio signal to generate a processed audio signal that represents a beampattern, the beampattern having multiple lobes each focused on a region within the environment; determining a portion of the processed audio signal corresponding to one or more lobes of the beampattern focused on one or more regions from which user speech was previously determined to have originated from; comparing the value of the acoustic characteristic to a previously measured value of the acoustic characteristic of the environment; and at least partly in response to determining that the value and the previously measured value differ by less than a threshold amount, applying relatively more processing resources to the portion of the processed audio signal and relatively less processing resources to a remainder of the processed audio signal. 16. One or more non-transitory computer-readable media as recited in claim 15 , the acts further comprising applying substantially equal processing resources to the portion of the processed audio signal and the remainder of the processed audio signal at least partly in response to determining that value and the previously measured value do not differ by less than the threshold amount. | 0.5 |
9,865,251 | 1 | 6 | 1. A text-to-speech method executed by a processor for processing a multi-lingual text message in a mixture of a first language and a second language into a multi-lingual voice message, cooperated with a first language model database having a plurality of first language phoneme labels and first language cognate connection tone information and a second language model database having a plurality of second language phoneme labels and second language cognate connection tone information, the text-to-speech method comprising: separating the multi-lingual text message into at least one first language section and at least one second language section; converting the at least one first language section into at least one first language phoneme label and converting the at least one second language section into at least one second language phoneme label; looking up the first language model database using the at least one first language phoneme label thereby obtaining at least one first language phoneme label sequence, and looking up the second language database model using the at least one second language phoneme label thereby obtaining at least one second language phoneme label sequence; assembling the at least one first language phoneme label sequence and at least one second language phoneme label sequence into a multi-lingual phoneme label sequence according to an order of words in the multi-lingual text message; dividing the multi-lingual phoneme label sequence into a plurality of first pronunciation units, each of the plurality of first pronunciation units is in a single language and includes consecutive phoneme labels of a corresponding one of the at least one first language phoneme label sequence and the at least one second language phoneme label sequence; for each of the first pronunciation units, determining whether a number of available candidates for a corresponding one of the first pronunciation units in a corresponding one of the first language model database and the second language model database is equal to or more than a predetermined number corresponding to the one of the first pronunciation units; when the number of available candidates for each of the first pronunciation units in the corresponding one of the first language model database and the second language model database is equal to or more than the corresponding predetermined number, calculating a join cost of each candidate path, wherein each candidate path passes through one of the available candidates of each of the first pronunciation units; determining a connecting path between every two immediately adjacent first pronunciation units based on the join cost of each candidate path; producing inter-lingual connection tone information at a boundary between every two immediately adjacent phoneme label sequences; combining the multi-lingual phoneme label sequence, the first language cognate connection tone information at a boundary between every two immediately adjacent phoneme label of the at least one first language phoneme label sequence, the second language cognate connection tone information at a boundary between every two immediately adjacent phoneme labels of the at least one second language phoneme label sequence, and inter-lingual connection tone information to obtain the multi-lingual voice message, and outputting the multi-lingual voice message. | 1. A text-to-speech method executed by a processor for processing a multi-lingual text message in a mixture of a first language and a second language into a multi-lingual voice message, cooperated with a first language model database having a plurality of first language phoneme labels and first language cognate connection tone information and a second language model database having a plurality of second language phoneme labels and second language cognate connection tone information, the text-to-speech method comprising: separating the multi-lingual text message into at least one first language section and at least one second language section; converting the at least one first language section into at least one first language phoneme label and converting the at least one second language section into at least one second language phoneme label; looking up the first language model database using the at least one first language phoneme label thereby obtaining at least one first language phoneme label sequence, and looking up the second language database model using the at least one second language phoneme label thereby obtaining at least one second language phoneme label sequence; assembling the at least one first language phoneme label sequence and at least one second language phoneme label sequence into a multi-lingual phoneme label sequence according to an order of words in the multi-lingual text message; dividing the multi-lingual phoneme label sequence into a plurality of first pronunciation units, each of the plurality of first pronunciation units is in a single language and includes consecutive phoneme labels of a corresponding one of the at least one first language phoneme label sequence and the at least one second language phoneme label sequence; for each of the first pronunciation units, determining whether a number of available candidates for a corresponding one of the first pronunciation units in a corresponding one of the first language model database and the second language model database is equal to or more than a predetermined number corresponding to the one of the first pronunciation units; when the number of available candidates for each of the first pronunciation units in the corresponding one of the first language model database and the second language model database is equal to or more than the corresponding predetermined number, calculating a join cost of each candidate path, wherein each candidate path passes through one of the available candidates of each of the first pronunciation units; determining a connecting path between every two immediately adjacent first pronunciation units based on the join cost of each candidate path; producing inter-lingual connection tone information at a boundary between every two immediately adjacent phoneme label sequences; combining the multi-lingual phoneme label sequence, the first language cognate connection tone information at a boundary between every two immediately adjacent phoneme label of the at least one first language phoneme label sequence, the second language cognate connection tone information at a boundary between every two immediately adjacent phoneme labels of the at least one second language phoneme label sequence, and inter-lingual connection tone information to obtain the multi-lingual voice message, and outputting the multi-lingual voice message. 6. The text-to-speech method of claim 1 , wherein the join cost of each candidate path is a weighted sum of a target cost of each candidate audio frequency data in each of the first pronunciation units, an acoustic spectrum cost of each connection between the candidate audio frequency data in every two immediately adjacent first pronunciation units, a tone cost of each connection between the candidate audio frequency data in every two immediately adjacent first pronunciation units, a pacemaking cost of each connection between the candidate audio frequency data in every two immediately adjacent first pronunciation units, and an intensity cost of each connection between the candidate audio frequency data in every two immediately adjacent first pronunciation units. | 0.73795 |
8,564,541 | 1 | 12 | 1. An interface for entering electronic text on a touch-sensitive display device, comprising: a virtual keyboard that includes a first key plane and a second, alternate key plane that replaces display of the first key plane, wherein: the first key plane comprises a set of initial phonetic symbols of a single phonetic alphabet; the second key plane comprises a set of final phonetic symbols of the single phonetic alphabet; the first key plane and the second key plane are touch-sensitive and operable to receive user input directed toward each of the phonetic symbols to generate electronic text input; and the virtual keyboard switches between displaying the first key plane and displaying the second key plane in response to predetermined user input triggers received through the virtual keyboard. | 1. An interface for entering electronic text on a touch-sensitive display device, comprising: a virtual keyboard that includes a first key plane and a second, alternate key plane that replaces display of the first key plane, wherein: the first key plane comprises a set of initial phonetic symbols of a single phonetic alphabet; the second key plane comprises a set of final phonetic symbols of the single phonetic alphabet; the first key plane and the second key plane are touch-sensitive and operable to receive user input directed toward each of the phonetic symbols to generate electronic text input; and the virtual keyboard switches between displaying the first key plane and displaying the second key plane in response to predetermined user input triggers received through the virtual keyboard. 12. The interface of claim 1 , wherein the predetermined user input triggers include user selecting a shift key on the first or the second key plane that is operable to trigger key plane switching in the virtual keyboard between the first and the second key planes. | 0.5 |
7,778,469 | 1 | 9 | 1. A computer implemented method for discriminatively selecting keyframes representative of segments of a source digital media, comprising the steps of: obtaining said source digital media for which keyframes are to be selected, wherein said source digital media comprises a plurality of segments, wherein said plurality of segments comprises a plurality of frames, said plurality of frames comprising candidate keyframes; pre-processing said source digital media to obtain a plurality of feature vectors, said feature vectors being representative of the candidate keyframes; determining in-class similarity values for said candidate keyframes, wherein the in-class similarity values are determined by comparing the feature vectors for the candidate keyframes to other feature vectors found solely within the same segment the candidate keyframes come from; determining out-of-class similarity values for said candidate keyframes, wherein the out-of-class similarity values are determined by comparing the feature vectors for the candidate keyframes to other feature vectors found solely outside of the segment the candidate keyframes come from; discriminatively selecting a keyframe for each segment based on both the in-class similarity values and the out-of-class similarity values of the candidate keyframes, wherein each selected keyframe is both representative of the segment the selected keyframe originates from and distinguishable from other selected keyframes which are representative of the remaining plurality of segments; wherein the chronological order of the selected keyframes as they appear within the source digital media is maintained during the step of discriminatively selecting a keyframe for each segment; and wherein the method steps are done by at least one processor. | 1. A computer implemented method for discriminatively selecting keyframes representative of segments of a source digital media, comprising the steps of: obtaining said source digital media for which keyframes are to be selected, wherein said source digital media comprises a plurality of segments, wherein said plurality of segments comprises a plurality of frames, said plurality of frames comprising candidate keyframes; pre-processing said source digital media to obtain a plurality of feature vectors, said feature vectors being representative of the candidate keyframes; determining in-class similarity values for said candidate keyframes, wherein the in-class similarity values are determined by comparing the feature vectors for the candidate keyframes to other feature vectors found solely within the same segment the candidate keyframes come from; determining out-of-class similarity values for said candidate keyframes, wherein the out-of-class similarity values are determined by comparing the feature vectors for the candidate keyframes to other feature vectors found solely outside of the segment the candidate keyframes come from; discriminatively selecting a keyframe for each segment based on both the in-class similarity values and the out-of-class similarity values of the candidate keyframes, wherein each selected keyframe is both representative of the segment the selected keyframe originates from and distinguishable from other selected keyframes which are representative of the remaining plurality of segments; wherein the chronological order of the selected keyframes as they appear within the source digital media is maintained during the step of discriminatively selecting a keyframe for each segment; and wherein the method steps are done by at least one processor. 9. The method of claim 1 , further comprising the step of: determining, subsequent to said step of obtaining, if said source digital media includes more than one item of digital media. | 0.729412 |
9,311,057 | 8 | 11 | 8. A method comprising: importing, by one or more processors, in a text-based format, a model that describes software or a system in a modeling language into a graphical modeling environment, wherein the modeling language does not define a formal, executable semantic capable of describing a dynamic behavior of the software or system, and wherein the model comprises model components; generating, by the one or more processors, executable elements, in the graphical modeling environment, that represent the model components, wherein at least some of the executable elements comply with standards of a domain or a platform, and wherein the domain or platform comprises CORBA, CORBA-RT, Advanced Architecture Description Language (AADL), AUTOSAR, Software Communication Architecture (SCA) as defined by the Department of Defense, or one or more derivatives of any one of the above; generating, by the one or more processors, an executable model in the graphical modeling environment, the executable model comprising the executable elements and corresponding to the model that describes the software or system; and updating, by the one or more processors, the model that describes the software or system, based on changes made to the executable model; or updating, by the one or more processors, the executable model, based on changes made to the model that describes the software or system. | 8. A method comprising: importing, by one or more processors, in a text-based format, a model that describes software or a system in a modeling language into a graphical modeling environment, wherein the modeling language does not define a formal, executable semantic capable of describing a dynamic behavior of the software or system, and wherein the model comprises model components; generating, by the one or more processors, executable elements, in the graphical modeling environment, that represent the model components, wherein at least some of the executable elements comply with standards of a domain or a platform, and wherein the domain or platform comprises CORBA, CORBA-RT, Advanced Architecture Description Language (AADL), AUTOSAR, Software Communication Architecture (SCA) as defined by the Department of Defense, or one or more derivatives of any one of the above; generating, by the one or more processors, an executable model in the graphical modeling environment, the executable model comprising the executable elements and corresponding to the model that describes the software or system; and updating, by the one or more processors, the model that describes the software or system, based on changes made to the executable model; or updating, by the one or more processors, the executable model, based on changes made to the model that describes the software or system. 11. The method of claim 8 , wherein updating the model that describes the software or system or updating the executable model comprises synchronizing updating the model that describes the software or system and the executable model. | 0.573529 |
9,009,134 | 9 | 10 | 9. The method of claim 5 , further comprising generating training data, the generating comprising: scanning a data source for a first search query having the seed named entity; collecting the first search query having the seed named entity; identifying an associated context of the first search query having the seed named entity; scanning the data source for a second search query having the associated context; collecting the second search query having the associated context; and extracting a new named entity from the second search query having the associated context. | 9. The method of claim 5 , further comprising generating training data, the generating comprising: scanning a data source for a first search query having the seed named entity; collecting the first search query having the seed named entity; identifying an associated context of the first search query having the seed named entity; scanning the data source for a second search query having the associated context; collecting the second search query having the associated context; and extracting a new named entity from the second search query having the associated context. 10. The method of claim 9 , wherein the data source is a click-through data set comprising queries received and selected Uniform Resource Locators (URLs) associated with the queries received. | 0.696825 |
9,658,735 | 6 | 12 | 6. The system of claim 3 , wherein one or more of the aspects of the user interface pertain to any of priority of fields, color contrast, whitespace, alignment, field labels, element labels, redundancy, tool tips, progress indicators, and display resolution. | 6. The system of claim 3 , wherein one or more of the aspects of the user interface pertain to any of priority of fields, color contrast, whitespace, alignment, field labels, element labels, redundancy, tool tips, progress indicators, and display resolution. 12. The system of claim 6 , wherein the one or more requirements pertain to a navigational path of portions of the user interface, and wherein the conforming user interface includes a feature reflecting the navigational path compared to the non-conforming user interface otherwise resulting from execution of the one or more rules. | 0.5 |
4,812,966 | 10 | 12 | 10. A word block searcher according to claim 8, further comprising: means for displaying said word block found by said searching means. | 10. A word block searcher according to claim 8, further comprising: means for displaying said word block found by said searching means. 12. A word block searcher according to claim 10, wherein said searching means is provided with: means for repeating said word block searching to find a plurality of word blocks having said corresponding head portion and said corresponding trailing portion, said displaying means displaying each of said found word blocks. | 0.5 |
8,458,189 | 14 | 15 | 14. The computer readable storage medium of claim 7 , wherein the second object is a document object that has attributes comprising a document identifier, a document title, a creation date, and document content. | 14. The computer readable storage medium of claim 7 , wherein the second object is a document object that has attributes comprising a document identifier, a document title, a creation date, and document content. 15. The computer readable storage medium of claim 14 , wherein each instance of the document object comprises a value of the document identifier attribute and corresponding values of the other attributes of the document object. | 0.5 |
9,972,308 | 9 | 13 | 9. A computer program product for building a classifier, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform a method comprising: preparing, by a processor, a plurality of pairs for an information retrieval task, each of the plurality of pairs including (i) a training-stage speech recognition result for a respective sequence of training words and (ii) an answer label corresponding to the training-stage speech recognition result; obtaining, by the processor using a search engine, a respective rank for the answer label included in each of the plurality of pairs to obtain a set of ranks; determining, by the processor, for each of the plurality of pairs, an end of question part in the training-stage speech recognition result based on the set of ranks; building, by the processor, the classifier such that the classifier receives a recognition-stage speech recognition result and returns a corresponding end of question part for the recognition-stage speech recognition result, based on the end of question part determined for the plurality of pairs; splitting, by the processor, the recognition-stage speech recognition result at the corresponding end of question part of the recognition-stage speech recognition result; generating, by the processor, a set of answer candidates for replying to the corresponding end of question part for the recognition-stage speech recognition result; and providing, by a display device, the set of answer candidates to a user. | 9. A computer program product for building a classifier, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer to cause the computer to perform a method comprising: preparing, by a processor, a plurality of pairs for an information retrieval task, each of the plurality of pairs including (i) a training-stage speech recognition result for a respective sequence of training words and (ii) an answer label corresponding to the training-stage speech recognition result; obtaining, by the processor using a search engine, a respective rank for the answer label included in each of the plurality of pairs to obtain a set of ranks; determining, by the processor, for each of the plurality of pairs, an end of question part in the training-stage speech recognition result based on the set of ranks; building, by the processor, the classifier such that the classifier receives a recognition-stage speech recognition result and returns a corresponding end of question part for the recognition-stage speech recognition result, based on the end of question part determined for the plurality of pairs; splitting, by the processor, the recognition-stage speech recognition result at the corresponding end of question part of the recognition-stage speech recognition result; generating, by the processor, a set of answer candidates for replying to the corresponding end of question part for the recognition-stage speech recognition result; and providing, by a display device, the set of answer candidates to a user. 13. The computer program product of claim 9 , wherein a first encountered word in the training-stage speech recognition result that results in a correct answer label for the training stage speech recognition result is determined as the end of question part in the training-stage speech recognition result. | 0.608974 |
8,121,845 | 19 | 24 | 19. A method of monitoring audio data transmitted over a computer network, said method comprising the steps of: processing input audio data using an access control module having a speech recogniser to produce index data representative of the likelihood of matches of portions of the input audio data to a set of predefined phones, wherein a user accesses the audio data via the access control module; searching the index data for a match to any one of a set of phone sequences corresponding to predefined threat words or phrases in order to detect any of the set of pre-defined threat words or phrases within the audio data; and initiating a threat detection response by the access control module on detection of one or more said threat words or phrases, by varying the ability of a user to access the audio data via the user device, wherein the set of pre-defined threat words or phrases are categorised into one or more categories according to a level of perceived offensiveness for the threat words or phrases, wherein a level of threat is determined for the threat words or phrases detected in the input audio data based on the category in which the threat word or phrase is categorised according to the user, wherein the threat detection response is based on the determined level of threat and the ability of the user to access the audio data via the access control module is varied according to the threat detection response, said method steps implemented on a data processor. | 19. A method of monitoring audio data transmitted over a computer network, said method comprising the steps of: processing input audio data using an access control module having a speech recogniser to produce index data representative of the likelihood of matches of portions of the input audio data to a set of predefined phones, wherein a user accesses the audio data via the access control module; searching the index data for a match to any one of a set of phone sequences corresponding to predefined threat words or phrases in order to detect any of the set of pre-defined threat words or phrases within the audio data; and initiating a threat detection response by the access control module on detection of one or more said threat words or phrases, by varying the ability of a user to access the audio data via the user device, wherein the set of pre-defined threat words or phrases are categorised into one or more categories according to a level of perceived offensiveness for the threat words or phrases, wherein a level of threat is determined for the threat words or phrases detected in the input audio data based on the category in which the threat word or phrase is categorised according to the user, wherein the threat detection response is based on the determined level of threat and the ability of the user to access the audio data via the access control module is varied according to the threat detection response, said method steps implemented on a data processor. 24. A method as claimed in claim 19 wherein the perceived level of offensiveness of the threat words or phrases is dependent upon the user characteristics such as age. | 0.711073 |
8,959,480 | 11 | 12 | 11. A method of unifying one or more declarative rules and a plurality of procedural instructions in a procedural computational system, the method comprising: upon execution, within said procedural computational system, of a procedural instruction that changes one or more variables, detecting said changes to said one or more variables and notifying a declarative computational system that is in communicative coupling with said procedural computational system using a change tracking system that is in communicative coupling with said procedural computational system and said declarative computational system, and updating, within said change tracking system, one or more other variables participating in one or more declarative rules so as to maintain relationships imposed by said one or more rules among said variables, wherein said updating of said one or more other variables is performed prior to execution of other procedural instructions, and wherein said updating of said one or more other variables includes identifying, within said declarative computational system, one or more other declarative rules in which said one or more other variables participate, and propagating, within said declarative computational system, said updating of said one or more other variables to said one or more other declarative rules so as to maintain relationships imposed by said one or more other declarative rules among said variables. | 11. A method of unifying one or more declarative rules and a plurality of procedural instructions in a procedural computational system, the method comprising: upon execution, within said procedural computational system, of a procedural instruction that changes one or more variables, detecting said changes to said one or more variables and notifying a declarative computational system that is in communicative coupling with said procedural computational system using a change tracking system that is in communicative coupling with said procedural computational system and said declarative computational system, and updating, within said change tracking system, one or more other variables participating in one or more declarative rules so as to maintain relationships imposed by said one or more rules among said variables, wherein said updating of said one or more other variables is performed prior to execution of other procedural instructions, and wherein said updating of said one or more other variables includes identifying, within said declarative computational system, one or more other declarative rules in which said one or more other variables participate, and propagating, within said declarative computational system, said updating of said one or more other variables to said one or more other declarative rules so as to maintain relationships imposed by said one or more other declarative rules among said variables. 12. The method of claim 11 , further comprising characterizing said declarative rules by a dependency network. | 0.727723 |
8,615,442 | 7 | 8 | 7. The method of claim 1 , further comprising generating content for the user based on the interest graph associated with the user. | 7. The method of claim 1 , further comprising generating content for the user based on the interest graph associated with the user. 8. The method of claim 7 , wherein generating content for the user comprises: generating a content recommendation for the user based on the interest graph associated with the user. | 0.845626 |
9,454,706 | 6 | 7 | 6. The method of claim 1 , wherein the fuzzy models are generated based on directional features obtained from training samples of handwritten Arabic like alphanumeric characters. | 6. The method of claim 1 , wherein the fuzzy models are generated based on directional features obtained from training samples of handwritten Arabic like alphanumeric characters. 7. The method of claim 6 , wherein the training samples are obtained from a plurality of different users. | 0.5 |
6,067,348 | 4 | 7 | 4. The apparatus of claim 1, wherein said plurality of personal greeting root name segments includes a generic greeting that can be used when no first or last name can be matched to an intended recipient. | 4. The apparatus of claim 1, wherein said plurality of personal greeting root name segments includes a generic greeting that can be used when no first or last name can be matched to an intended recipient. 7. The apparatus of claim 4, wherein said storage area contains a group message. | 0.803922 |
7,587,319 | 61 | 62 | 61. A speech recognition circuit according to claim 50 , wherein said control processor identifies lexical data in said lexical memories required for processing next words at word recognition events, and controls said processors to process the speech parameters using the identified lexical data. | 61. A speech recognition circuit according to claim 50 , wherein said control processor identifies lexical data in said lexical memories required for processing next words at word recognition events, and controls said processors to process the speech parameters using the identified lexical data. 62. A speech recognition circuit according to claim 61 , wherein said control processor prunes the identified lexical data. | 0.5 |
8,473,489 | 31 | 33 | 31. A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: determining that a first search query includes a respective text reference to each of one or more predetermined attributes, wherein each attribute is associated with a first entity type; generating a second search query including the first search query and one or more terms that refer to the first entity type; and evaluating search results obtained for the second search query to select one or more names of entities of the first entity type to include in a response to the first search query, wherein each search result identifies a respective search result resource, and wherein evaluating the search results comprises: identifying occurrences of references to entities of the first entity type in the same search result resource as one or more terms from the first search query; and selecting the names of entities based on the identified occurrences. | 31. A system comprising one or more computers and one or more storage devices storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: determining that a first search query includes a respective text reference to each of one or more predetermined attributes, wherein each attribute is associated with a first entity type; generating a second search query including the first search query and one or more terms that refer to the first entity type; and evaluating search results obtained for the second search query to select one or more names of entities of the first entity type to include in a response to the first search query, wherein each search result identifies a respective search result resource, and wherein evaluating the search results comprises: identifying occurrences of references to entities of the first entity type in the same search result resource as one or more terms from the first search query; and selecting the names of entities based on the identified occurrences. 33. The system of claim 31 , wherein determining that the first search query includes a respective text reference to each of one or more predetermined attributes comprises: determining, only from text of the search query, that the first search query includes a respective text reference to each of one or more predetermined attributes. | 0.517291 |
7,636,768 | 1 | 3 | 1. A data structure embodied on one or more computer-storage media, the data structure comprising: an abstract content model that represents content that can be requested by a content requester, the abstract model comprising a directional graph that features a top-down hierarchical structure having nodes that represent components of the content and edges that represent relationships between the nodes, the nodes being configured to have a node status that defines dynamic statuses of the nodes during content delivery, wherein the node status comprises one or more of the following: an activable status wherein an active condition of the node is satisfied but the node is not yet included in a delivery plan, the active condition is satisfied when an automatically activable condition is present, an OR condition such that an input edge of the node is an ignition edge is present, or an AND condition such that all input edges of the node are ignition edges is present; or an activated status wherein the node is included in the delivery plan; the abstract content model being configured for processing so that the delivery plan for delivering the content corresponding to the nodes having an activated status can be selected. | 1. A data structure embodied on one or more computer-storage media, the data structure comprising: an abstract content model that represents content that can be requested by a content requester, the abstract model comprising a directional graph that features a top-down hierarchical structure having nodes that represent components of the content and edges that represent relationships between the nodes, the nodes being configured to have a node status that defines dynamic statuses of the nodes during content delivery, wherein the node status comprises one or more of the following: an activable status wherein an active condition of the node is satisfied but the node is not yet included in a delivery plan, the active condition is satisfied when an automatically activable condition is present, an OR condition such that an input edge of the node is an ignition edge is present, or an AND condition such that all input edges of the node are ignition edges is present; or an activated status wherein the node is included in the delivery plan; the abstract content model being configured for processing so that the delivery plan for delivering the content corresponding to the nodes having an activated status can be selected. 3. The data structure of claim 1 , wherein the node status further comprises a delivered status wherein the node has been delivered successfully to a content receiver. | 0.520115 |
9,690,850 | 7 | 8 | 7. A computer-readable, non-transitory storage medium having computer executable instructions stored thereon, which when the instructions are executed are operable to: retrieve a plurality of text relating to a recipe from a client device in communication with a server device; analyze individual words comprising the plurality of text relating to the recipe to determine whether each may be found within one of three keyword databases of known words, the three keyword databases comprising: a database of known ingredient-related words, a database of known measurement-related words, and a database of known instruction-related words; extract nutrition information associated with individual ones of the words identified in the known ingredient-related keyword database; organize the extracted nutrition information and the analyzed individual ones of the words into a second recipe comprising at least three sections related to the keyword database to which each word of the plurality of text of the recipe is associated; and enable a user of the client device to log the second recipe data via a nutrition logging program executed thereat. | 7. A computer-readable, non-transitory storage medium having computer executable instructions stored thereon, which when the instructions are executed are operable to: retrieve a plurality of text relating to a recipe from a client device in communication with a server device; analyze individual words comprising the plurality of text relating to the recipe to determine whether each may be found within one of three keyword databases of known words, the three keyword databases comprising: a database of known ingredient-related words, a database of known measurement-related words, and a database of known instruction-related words; extract nutrition information associated with individual ones of the words identified in the known ingredient-related keyword database; organize the extracted nutrition information and the analyzed individual ones of the words into a second recipe comprising at least three sections related to the keyword database to which each word of the plurality of text of the recipe is associated; and enable a user of the client device to log the second recipe data via a nutrition logging program executed thereat. 8. The computer readable storage media of claim 7 , wherein the ingredient keyword database comprises text information related to ingredients or nutrient information of food and beverages, wherein the measurement keyword database comprises text information related to measurements and/or serving sizes for food and beverages, and wherein the instruction keyword database comprises text information related to preparation techniques for food and beverages. | 0.587862 |
8,091,067 | 1 | 23 | 1. A method for hosting a programming environment and processing user input, the method comprising the step of: (a) receiving, during a first session between a user and an interaction environment, via one of a plurality of media gateways, a definition of an expression type, the definition specifying an expression format and a response type; (b) storing the definition of the expression type; (c) receiving, during a second session between a second user and the interaction environment, via one of a plurality of media gateways, from the second user, an expression having a semantic structure; (d) evaluating the semantic structure of the expression; (e) identifying an expression format of the received expression as the expression format specified by the definition of the expression type, responsive to the evaluation of the semantic structure; and (f) generating a response to the expression based on the identified expression format and responsive to an execution of a computer program associated with the response type specified by the definition of the expression type. | 1. A method for hosting a programming environment and processing user input, the method comprising the step of: (a) receiving, during a first session between a user and an interaction environment, via one of a plurality of media gateways, a definition of an expression type, the definition specifying an expression format and a response type; (b) storing the definition of the expression type; (c) receiving, during a second session between a second user and the interaction environment, via one of a plurality of media gateways, from the second user, an expression having a semantic structure; (d) evaluating the semantic structure of the expression; (e) identifying an expression format of the received expression as the expression format specified by the definition of the expression type, responsive to the evaluation of the semantic structure; and (f) generating a response to the expression based on the identified expression format and responsive to an execution of a computer program associated with the response type specified by the definition of the expression type. 23. The method of claim 1 , wherein step (e) further comprises identifying the expression as a request for stored data. | 0.850126 |
10,157,224 | 10 | 11 | 10. The method of claim 1 , further comprising sending, to a client system of a first user of the online social network, the quotations-module for display to the first user. | 10. The method of claim 1 , further comprising sending, to a client system of a first user of the online social network, the quotations-module for display to the first user. 11. The method of claim 10 , wherein the cluster-score is further based on demographic information associated with the first user. | 0.664948 |
7,657,458 | 10 | 14 | 10. A method implemented on a computer system having a reviews database for collecting reviews, comprising: receiving by a review submission subsystem of the computer system a locator code wherein said locator code is used to retrieve a locator record associated with one or more subjects to be reviewed, and further wherein said locator code references a unique transaction; receiving by the review submission subsystem of the computer system one or more reviews pertaining to said one or more subjects; and storing said one or more reviews in said reviews database of the computer system only if a valid locator code has been received. | 10. A method implemented on a computer system having a reviews database for collecting reviews, comprising: receiving by a review submission subsystem of the computer system a locator code wherein said locator code is used to retrieve a locator record associated with one or more subjects to be reviewed, and further wherein said locator code references a unique transaction; receiving by the review submission subsystem of the computer system one or more reviews pertaining to said one or more subjects; and storing said one or more reviews in said reviews database of the computer system only if a valid locator code has been received. 14. A method as recited in claim 10 wherein information relating to an author of said one or more reviews is stored. | 0.752137 |
9,047,563 | 1 | 5 | 1. A method comprising: identifying, by one or more devices, one or more particular topics based on one or more particular documents; identifying, by the one or more devices, one or more portions, of a target document, that correspond to a particular topic of the one or more particular topics; determining, by the one or more devices, a measure of credibility of the target document based on the one or more portions that correspond to the particular topic; receiving, by the one or more devices, information regarding a selection of a sentiment score that affects the measure of credibility of the target document; and providing, by the one or more devices and for display, at least one particular portion, of the one or more portions of the target document, corresponding to the sentiment score based on the selection of the sentiment score. | 1. A method comprising: identifying, by one or more devices, one or more particular topics based on one or more particular documents; identifying, by the one or more devices, one or more portions, of a target document, that correspond to a particular topic of the one or more particular topics; determining, by the one or more devices, a measure of credibility of the target document based on the one or more portions that correspond to the particular topic; receiving, by the one or more devices, information regarding a selection of a sentiment score that affects the measure of credibility of the target document; and providing, by the one or more devices and for display, at least one particular portion, of the one or more portions of the target document, corresponding to the sentiment score based on the selection of the sentiment score. 5. The method of claim 1 , where determining the measure of credibility comprises: determining one or more sentiment scores based on the one or more portions of the target document, the one or more sentiment scores including the sentiment score, and determining the measure of credibility based on the one or more sentiment scores. | 0.558667 |
7,899,816 | 9 | 10 | 9. The method of claim 1 , wherein the lexicon is dynamic. | 9. The method of claim 1 , wherein the lexicon is dynamic. 10. The method of claim 9 , wherein the lexicon is initialized with a set of one or more fixed lexicon terms. | 0.5 |
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