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10,007,863 | 13 | 14 | 13. The apparatus of claim 11 , wherein saliency detection comprises: applying a discrete cosine transform (DCT) on the segmented likely logo regions of an image in a selected video frame to determine spectral saliency of each likely logo region; and measuring multi-scale similarity at two higher scales and a smaller scale of the spectral saliency of each likely logo region. | 13. The apparatus of claim 11 , wherein saliency detection comprises: applying a discrete cosine transform (DCT) on the segmented likely logo regions of an image in a selected video frame to determine spectral saliency of each likely logo region; and measuring multi-scale similarity at two higher scales and a smaller scale of the spectral saliency of each likely logo region. 14. The apparatus of claim 13 , wherein the multi-scale similarity measures include orientation gradient histograms, hue, saturation, value (HSV) histograms, and stroke width transform (SWT) statistics which include total number of strokes, number of horizontal strokes, number of vertical strokes, stroke density, and number of loops. | 0.5 |
7,801,909 | 37 | 44 | 37. An apparatus for analyzing potential patent infringement, comprising: a receiver for receiving information regarding a patent; a processing device configured to: identify at least one claim of the patent, parse the at least one claim to identify at least one term in the at least one claim, automatically generate a natural language question for use in obtaining information from an on-line bulletin board, transmit the natural language question to the on-line bulletin board, obtain information regarding at least one of a product and a service from the on-line bulletin board in response to the natural language question, formulate a search query comprising the at least one term, generate a claim chart, and perform a search of the information regarding at least one of a product and a service using the query; and a transmitter for transmitting the information contained in the claim chart to a user communication device in order to display the claim chart. | 37. An apparatus for analyzing potential patent infringement, comprising: a receiver for receiving information regarding a patent; a processing device configured to: identify at least one claim of the patent, parse the at least one claim to identify at least one term in the at least one claim, automatically generate a natural language question for use in obtaining information from an on-line bulletin board, transmit the natural language question to the on-line bulletin board, obtain information regarding at least one of a product and a service from the on-line bulletin board in response to the natural language question, formulate a search query comprising the at least one term, generate a claim chart, and perform a search of the information regarding at least one of a product and a service using the query; and a transmitter for transmitting the information contained in the claim chart to a user communication device in order to display the claim chart. 44. The apparatus of claim 37 , wherein the apparatus is programmed for automatic operation. | 0.891509 |
9,406,089 | 1 | 19 | 1. A computer-implemented method for populating an electronic tax return, the computer-implemented method being executed by a mobile communication device comprising a data store comprising a tax return preparation application operable to prepare an electronic tax return, a first camera that is a front facing camera, a second camera that is a rear facing camera, a microphone and a video/voice processor, each of the data store, the first camera, the second camera and the microphone being in communication with the video/voice processor, the method comprising: the mobile communication device, by the first camera, recording a video of a tax document, the recorded video comprising a plurality of video frames and voice data generated based on a user of the mobile communication device speaking into the microphone during recording of the video, the voice data comprising a user-spoken description of how the tax document is relevant to the electronic tax return; converting, by the video/voice processor of the mobile communication device, the voice data from a voice format into a text format; analyzing, by the video/voice processor, at least one video frame of the video and the voice data in the text format to determine a document type and tax data contained within the at least one video frame; identifying, by the tax return preparation application executed by a processor of the mobile communication device, a field of the electronic tax return to be populated with determined tax data of the determined document type; populating, by the tax return preparation application, the field of the electronic tax return with the determined tax data to prepare at least a portion of the electronic tax return without the user typing tax data of the tax document that was captured in the video into the field of the electronic tax return; detecting, by the second camera, a facial expression or gesture of the user during preparation of the electronic tax return; determining, by the video/voice processor, a first response based at least in part on the detected facial expression or gesture; and presenting, by the tax return preparation application, the first response to the user during preparation of the electronic tax return. | 1. A computer-implemented method for populating an electronic tax return, the computer-implemented method being executed by a mobile communication device comprising a data store comprising a tax return preparation application operable to prepare an electronic tax return, a first camera that is a front facing camera, a second camera that is a rear facing camera, a microphone and a video/voice processor, each of the data store, the first camera, the second camera and the microphone being in communication with the video/voice processor, the method comprising: the mobile communication device, by the first camera, recording a video of a tax document, the recorded video comprising a plurality of video frames and voice data generated based on a user of the mobile communication device speaking into the microphone during recording of the video, the voice data comprising a user-spoken description of how the tax document is relevant to the electronic tax return; converting, by the video/voice processor of the mobile communication device, the voice data from a voice format into a text format; analyzing, by the video/voice processor, at least one video frame of the video and the voice data in the text format to determine a document type and tax data contained within the at least one video frame; identifying, by the tax return preparation application executed by a processor of the mobile communication device, a field of the electronic tax return to be populated with determined tax data of the determined document type; populating, by the tax return preparation application, the field of the electronic tax return with the determined tax data to prepare at least a portion of the electronic tax return without the user typing tax data of the tax document that was captured in the video into the field of the electronic tax return; detecting, by the second camera, a facial expression or gesture of the user during preparation of the electronic tax return; determining, by the video/voice processor, a first response based at least in part on the detected facial expression or gesture; and presenting, by the tax return preparation application, the first response to the user during preparation of the electronic tax return. 19. The computer-implemented method of claim 1 , further comprising engaging, by the video/voice processor, in an electronic dialogue with the user in response to at least one of the determined document type and determined tax data. | 0.820155 |
9,495,443 | 8 | 9 | 8. The system of claim 7 , where the one or more processors further execute instructions to: normalize the generated term vector for each document in the first set of documents; and normalize the generated term vector for each document in the second set of documents. | 8. The system of claim 7 , where the one or more processors further execute instructions to: normalize the generated term vector for each document in the first set of documents; and normalize the generated term vector for each document in the second set of documents. 9. The system of claim 8 , where the one or more processors further execute instructions to: create, based on normalizing the generated term vector for each document in the first set of documents and normalizing the generated term vector for each document in the second set of documents, a composite term vector. | 0.5 |
9,275,554 | 23 | 26 | 23. The method according to claim 16 , wherein the automatically selecting step of the one or more selected keywords is based on a search term; and wherein the search term comprises at least one search filter. | 23. The method according to claim 16 , wherein the automatically selecting step of the one or more selected keywords is based on a search term; and wherein the search term comprises at least one search filter. 26. The method according to claim 23 , wherein the one or more automatically selected keywords of the textual information for testing are one or more words following the search term. | 0.5 |
8,954,500 | 27 | 29 | 27. The method of claim 1 , further comprising: identifying at least one of relationships or interactions in a second network, wherein the second network is one of the other networks; identifying at least one of relationships or interactions in a third network, wherein the third network is another one of the other networks; determining that an identity of an individual in one of the relationships or interactions in the second network corresponds to the same individual in one of the relationships or interactions in the third network; and aggregating the vitality events for the individual across the second network and the third network. | 27. The method of claim 1 , further comprising: identifying at least one of relationships or interactions in a second network, wherein the second network is one of the other networks; identifying at least one of relationships or interactions in a third network, wherein the third network is another one of the other networks; determining that an identity of an individual in one of the relationships or interactions in the second network corresponds to the same individual in one of the relationships or interactions in the third network; and aggregating the vitality events for the individual across the second network and the third network. 29. The method of claim 27 , wherein the relationship or interaction in the third network is not with the first user. | 0.5 |
8,949,878 | 15 | 17 | 15. A parental control system for an electronic device to filter objectionable material from a multimedia program including plural segments, comprising: a learning module to generate filter criteria learned based on user instructions by examples of objectionable content; a splitting mechanism that splits the multimedia program into plural components; a transcript analysis module that extracts first audible features and text from a transcript analysis component within the plural components; a visual analysis module that extracts video features from a visual analysis component within the plural components; an audio analysis module that extracts second audible features from an audio analysis component within the plural components; an analyzer which processes each segment amongst the segments, according to the learned filter criteria generated by the learning module and the extracted features, and generates a numeric ranking corresponding to the filter criteria learned based on the user instructions by examples of objectionable content and applied to the segment, and which generates a respective control signal when the numeric ranking exceeds a threshold; and a filter, which processes one of the segments of the multimedia program in response to a received respective control signal. | 15. A parental control system for an electronic device to filter objectionable material from a multimedia program including plural segments, comprising: a learning module to generate filter criteria learned based on user instructions by examples of objectionable content; a splitting mechanism that splits the multimedia program into plural components; a transcript analysis module that extracts first audible features and text from a transcript analysis component within the plural components; a visual analysis module that extracts video features from a visual analysis component within the plural components; an audio analysis module that extracts second audible features from an audio analysis component within the plural components; an analyzer which processes each segment amongst the segments, according to the learned filter criteria generated by the learning module and the extracted features, and generates a numeric ranking corresponding to the filter criteria learned based on the user instructions by examples of objectionable content and applied to the segment, and which generates a respective control signal when the numeric ranking exceeds a threshold; and a filter, which processes one of the segments of the multimedia program in response to a received respective control signal. 17. The parental control system as recited in claim 15 , wherein the filter modifies the video feature of the respective segment. | 0.851382 |
9,684,871 | 1 | 10 | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically analyzing target information from an entity; b. automatically fact checking the target information by comparing the target information with source information to generate a result, wherein comparing includes at least one of: i. searching for an exact match of the target information in the source information and returning the result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; c. automatically presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information; and d. analyzing a validity rating of the entity, wherein if the validity rating of the entity is below a threshold, then the source information is limited to sources with a rating above a reliability threshold, wherein searching for the exact match begins searching the source information located in a designated fact checking database and then goes to a broader set of source information; wherein utilizing pattern matching begins utilizing the source information located in the designated fact checking database, then goes to the broader set of source information; and wherein the natural language search begins searching the source information located in the designated fact checking database, then goes to the broader set of source information. | 1. A method programmed in a non-transitory memory of a device comprising: a. automatically analyzing target information from an entity; b. automatically fact checking the target information by comparing the target information with source information to generate a result, wherein comparing includes at least one of: i. searching for an exact match of the target information in the source information and returning the result of the exact match search if the exact match is found; ii. utilizing pattern matching for fact checking and returning the result of the pattern matching fact check if a pattern matching result confidence score is above a pattern matching result confidence threshold; and iii. utilizing a natural language search for fact checking and returning the result of the natural language fact check if a natural language result confidence score is above a natural language result confidence threshold; c. automatically presenting a status of the target information in real-time based on the result of the comparison of the target information with the source information; and d. analyzing a validity rating of the entity, wherein if the validity rating of the entity is below a threshold, then the source information is limited to sources with a rating above a reliability threshold, wherein searching for the exact match begins searching the source information located in a designated fact checking database and then goes to a broader set of source information; wherein utilizing pattern matching begins utilizing the source information located in the designated fact checking database, then goes to the broader set of source information; and wherein the natural language search begins searching the source information located in the designated fact checking database, then goes to the broader set of source information. 10. The method of claim 1 further comprising parsing the target information into phrases, parsing the phrases into words, counting the number of words in each phrase, and comparing each phrase with the source information containing one more word than the number of words in the phrase being compared. | 0.867725 |
8,892,734 | 1 | 19 | 1. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender; using the second activity information to identify a second node in the social graph as being representative of the recipient; determining a category for the first link as a first category type; and in the social graph, creating a first edge between the first and second nodes, wherein the first edge is representative of the first category type. | 1. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender; using the second activity information to identify a second node in the social graph as being representative of the recipient; determining a category for the first link as a first category type; and in the social graph, creating a first edge between the first and second nodes, wherein the first edge is representative of the first category type. 19. The method of claim 1 wherein the receiving first activity information for a sender of a first link to at least one recipient comprises: sending of an e-mail including the first link by the sender via a nonmobile device. | 0.801418 |
8,887,055 | 12 | 19 | 12. A method of recording a user-viewable stimulus, the method comprising: recording a user-viewable stimulus at a first time, the recording comprising: detecting a visual event; receiving information specifying the detected visual event; observing one or more visual characteristics of the visual event; verifying that the visual characteristics involve one or more parameters that affect how the visual event is displayed; recording at least one of the one or more parameters; and recreating, at a second time different from the first time, at least a portion of the user-viewable stimulus by: reading one or more of the recorded parameters; and reconstructing at least a part of the visual event wherein the visual characteristics corresponding to the recorded parameters are included in the reconstructed part of the visual event. | 12. A method of recording a user-viewable stimulus, the method comprising: recording a user-viewable stimulus at a first time, the recording comprising: detecting a visual event; receiving information specifying the detected visual event; observing one or more visual characteristics of the visual event; verifying that the visual characteristics involve one or more parameters that affect how the visual event is displayed; recording at least one of the one or more parameters; and recreating, at a second time different from the first time, at least a portion of the user-viewable stimulus by: reading one or more of the recorded parameters; and reconstructing at least a part of the visual event wherein the visual characteristics corresponding to the recorded parameters are included in the reconstructed part of the visual event. 19. The method of claim 12 wherein one or more of the parameters contain information relating to a property of at least one browser object, the property being one of: a horizontal position, a vertical position, a size of a window, and a network address. | 0.5 |
7,752,152 | 8 | 9 | 8. The system of claim 1 , the predictive model comprises a conditional model. | 8. The system of claim 1 , the predictive model comprises a conditional model. 9. The system of claim 8 , the conditional model is a decision tree. | 0.881944 |
9,368,114 | 4 | 5 | 4. The method of claim 1 , wherein the device is a telephone, and wherein determining if the device is currently receiving speech input from the user comprises determining if the user is participating in a telephone conversation with a remote user. | 4. The method of claim 1 , wherein the device is a telephone, and wherein determining if the device is currently receiving speech input from the user comprises determining if the user is participating in a telephone conversation with a remote user. 5. The method of claim 4 , wherein upon determining that the device is not currently receiving speech input from the user, audio data received from the remote user and the speech output to the user are provided contemporaneously without staying provision of the speech output due to the received audio data. | 0.5 |
9,965,502 | 8 | 12 | 8. A method for an apparatus which manages a plurality of objects, each object including content data and metadata, the method comprising: generating an index for the objects using a plurality of content properties including a first content property and a second content property, the first content property having a first name of the first content property and first expression information for extracting values from fields in the metadata of one or more of the objects, and the second content property having the first name and second expression information for extracting values from the fields in the metadata of one or more of the objects so that at least a portion of the index is deduplicated such that values for multiple relevant expressions are able to be returned for a single search request; and searching, upon receipt of a search request including the first name and a first value, the index for one or more objects that have at least one of: the first value in at least one of the fields identified based on the first expression information in the metadata, or the first value in at least one of the fields identified based on the second expression information in the metadata; and based on finding at least one match, returning an indication of at least one of the objects determined to include the first value in at least one of the fields identified in the metadata based on the first expression information or in at least one of the fields identified in the metadata based on the second expression information. | 8. A method for an apparatus which manages a plurality of objects, each object including content data and metadata, the method comprising: generating an index for the objects using a plurality of content properties including a first content property and a second content property, the first content property having a first name of the first content property and first expression information for extracting values from fields in the metadata of one or more of the objects, and the second content property having the first name and second expression information for extracting values from the fields in the metadata of one or more of the objects so that at least a portion of the index is deduplicated such that values for multiple relevant expressions are able to be returned for a single search request; and searching, upon receipt of a search request including the first name and a first value, the index for one or more objects that have at least one of: the first value in at least one of the fields identified based on the first expression information in the metadata, or the first value in at least one of the fields identified based on the second expression information in the metadata; and based on finding at least one match, returning an indication of at least one of the objects determined to include the first value in at least one of the fields identified in the metadata based on the first expression information or in at least one of the fields identified in the metadata based on the second expression information. 12. A method according to claim 8 , wherein the metadata includes a plurality of annotations of the content data, the annotations including a first annotation generated by a first application and a second annotation generated by a second application. | 0.5 |
5,583,988 | 1 | 14 | 1. A method for performing runtime checking operations in a compiled programming development environment, comprising the steps of: a) compiling a source code file into executable object code comprising machine language instructions, wherein said source code file includes aggregate data items and pointers and also includes expressions which manipulate said aggregate data items and pointers, wherein said step of compiling comprises: creating data structures for aggregate data items and pointers in the source code file; and inserting calls to runtime checking functions for one or more expressions in the source code file which manipulate said aggregate data items and pointers; and b) executing the executable object code, wherein said step of executing comprises: executing one or more of said runtime checking functions to determine if invalid operations occur in said expressions which manipulate said aggregate data items and pointers; and reporting an error to the user if an invalid operation is found to occur after said step of executing one or more of said runtime checking functions. | 1. A method for performing runtime checking operations in a compiled programming development environment, comprising the steps of: a) compiling a source code file into executable object code comprising machine language instructions, wherein said source code file includes aggregate data items and pointers and also includes expressions which manipulate said aggregate data items and pointers, wherein said step of compiling comprises: creating data structures for aggregate data items and pointers in the source code file; and inserting calls to runtime checking functions for one or more expressions in the source code file which manipulate said aggregate data items and pointers; and b) executing the executable object code, wherein said step of executing comprises: executing one or more of said runtime checking functions to determine if invalid operations occur in said expressions which manipulate said aggregate data items and pointers; and reporting an error to the user if an invalid operation is found to occur after said step of executing one or more of said runtime checking functions. 14. The method of claim 1, wherein said step of executing the executable object code comprises: accessing a data structure associated with a pointer; determining if said data structure associated with said pointer indicates that runtime checking functions for said pointer should be ignored; not performing runtime checking functions for said pointer if said data structure indicates said runtime checking functions for said pointer should be ignored. | 0.726998 |
9,390,725 | 6 | 9 | 6. A method to manufacture a system using a user device in communication with a stored data repository, that reduces the background noise from a speech audio signal generated by a user, comprising: providing a user device, with a processor and a memory, receiving a speech audio signal; and providing a noise reduction device, in communication with a stored data repository, and in communication with said user device, is configured to: convert said received speech audio signal to text; generate synthetic speech based on a speech data corpus or speech model data of the user stored in said stored data repository and said converted text; determine the predicted subjective quality of the received speech audio signal if that signal were to be transmitted to a far end listener; determine the predicted subjective quality of said synthetic speech; and transmit, selectively, said speech audio signal or said synthetic speech, whichever has higher predicted quality based on a comparison between the value of objective quality metrics computed for the speech audio signal and the synthetic speech signal. | 6. A method to manufacture a system using a user device in communication with a stored data repository, that reduces the background noise from a speech audio signal generated by a user, comprising: providing a user device, with a processor and a memory, receiving a speech audio signal; and providing a noise reduction device, in communication with a stored data repository, and in communication with said user device, is configured to: convert said received speech audio signal to text; generate synthetic speech based on a speech data corpus or speech model data of the user stored in said stored data repository and said converted text; determine the predicted subjective quality of the received speech audio signal if that signal were to be transmitted to a far end listener; determine the predicted subjective quality of said synthetic speech; and transmit, selectively, said speech audio signal or said synthetic speech, whichever has higher predicted quality based on a comparison between the value of objective quality metrics computed for the speech audio signal and the synthetic speech signal. 9. The claim according to claim 6 , wherein said step of receiving said speech audio signal by said user device further comprises pre-processing said speech audio signal based on using a predetermined noise reduction algorithm. | 0.5 |
8,394,127 | 1 | 9 | 1. A spinal stabilization device comprising: a centering rod having a first end, a second end and a flexible section connecting the first end and the second end; a deflectable rod including a retainer; a first bore extending along a longitudinal axis of the deflectable rod and opening through the retainer opposite the deflectable rod, wherein the first end of the centering rod is received in the first bore; a housing extending from a threaded bone anchor; a socket within the housing, wherein the socket at least partially encloses the retainer to form a joint; a channel extending from the socket out of the housing, wherein the deflectable rod extends through the channel out of the housing; and a second bore in the housing extending from the socket opposite the channel, wherein the second end of the centering rod is received in the second bore; whereby deflection of the rod bends the flexible section of the centering rod and the centering rod exerts a restoring force to center the rod within the channel. | 1. A spinal stabilization device comprising: a centering rod having a first end, a second end and a flexible section connecting the first end and the second end; a deflectable rod including a retainer; a first bore extending along a longitudinal axis of the deflectable rod and opening through the retainer opposite the deflectable rod, wherein the first end of the centering rod is received in the first bore; a housing extending from a threaded bone anchor; a socket within the housing, wherein the socket at least partially encloses the retainer to form a joint; a channel extending from the socket out of the housing, wherein the deflectable rod extends through the channel out of the housing; and a second bore in the housing extending from the socket opposite the channel, wherein the second end of the centering rod is received in the second bore; whereby deflection of the rod bends the flexible section of the centering rod and the centering rod exerts a restoring force to center the rod within the channel. 9. The spine stabilization device of claim 1 , wherein the first bore further comprises an enlarged portion within the retainer, wherein the flexible section of the centering rod is received in the enlarged portion of the first bore. | 0.526423 |
7,908,325 | 27 | 31 | 27. A computer accessible medium, comprising program instructions configured to implement: executing on a first computer system, a first collaboration framework and an instance of an application, wherein executing the instance of the application comprises displaying an instance of a graphical user interface of the application; intercepting, via an operating system event handling mechanism executing on the first computer system, a local user input event targeted to the instance of the application, wherein the instance of the application applies a modification to the instance of the graphical user interface in response to receiving the user input event; in response to said intercepting, the first collaboration framework sending a message including the user input event to each of one or more other collaboration frameworks each executing on one of a respective one or more other computer systems that are each executing a respective other instance of the application, wherein said executing each respective other instance of the application comprises displaying a respective other instance of the graphical user interface of the application on the respective other computer system; wherein the message includes information usable by each of the one or more other collaboration frameworks to deliver the user input event, via an operating system event handling mechanism executing on the respective other computer system, to the respective other instance of the application executing on the respective other device as if the user input event originated locally from the respective other user interface displayed by the respective other application on the respective other device; and wherein the delivered user input event causes each of the respective other application instances to apply the modification to the respective instance of the graphical user interface. | 27. A computer accessible medium, comprising program instructions configured to implement: executing on a first computer system, a first collaboration framework and an instance of an application, wherein executing the instance of the application comprises displaying an instance of a graphical user interface of the application; intercepting, via an operating system event handling mechanism executing on the first computer system, a local user input event targeted to the instance of the application, wherein the instance of the application applies a modification to the instance of the graphical user interface in response to receiving the user input event; in response to said intercepting, the first collaboration framework sending a message including the user input event to each of one or more other collaboration frameworks each executing on one of a respective one or more other computer systems that are each executing a respective other instance of the application, wherein said executing each respective other instance of the application comprises displaying a respective other instance of the graphical user interface of the application on the respective other computer system; wherein the message includes information usable by each of the one or more other collaboration frameworks to deliver the user input event, via an operating system event handling mechanism executing on the respective other computer system, to the respective other instance of the application executing on the respective other device as if the user input event originated locally from the respective other user interface displayed by the respective other application on the respective other device; and wherein the delivered user input event causes each of the respective other application instances to apply the modification to the respective instance of the graphical user interface. 31. The computer accessible medium of claim 27 , wherein the program instructions are further configured to implement the first collaboration framework translating the input event to a non-platform-specific format prior to said sending a message. | 0.635015 |
8,949,225 | 8 | 12 | 8. A computer system for accessing an RDF repository through a SPARQL gateway, comprising: a computer processor to execute a set of program code instructions; and a memory to hold the program code instructions, in which the program code instructions comprises program code to perform, receiving, by a SPARQL gateway, a database query, the database query received in a first query language format; converting the database query into a SPARQL query format; submitting the converted query to a SPARQL endpoint; receiving by the SPARQL gateway, SPARQL query results from the SPARQL endpoint; and transforming the SPARQL query results into a format corresponding to the first query language format, wherein the format is not an XML format. | 8. A computer system for accessing an RDF repository through a SPARQL gateway, comprising: a computer processor to execute a set of program code instructions; and a memory to hold the program code instructions, in which the program code instructions comprises program code to perform, receiving, by a SPARQL gateway, a database query, the database query received in a first query language format; converting the database query into a SPARQL query format; submitting the converted query to a SPARQL endpoint; receiving by the SPARQL gateway, SPARQL query results from the SPARQL endpoint; and transforming the SPARQL query results into a format corresponding to the first query language format, wherein the format is not an XML format. 12. The computer system of claim 8 , wherein transforming the SPARQL query results uses an XSLT processor. | 0.819728 |
9,830,633 | 11 | 12 | 11. An apparatus comprising a processor to: receive a search query by a user that is to include a stated expectation with respect to a general product to be identified in the search query by a general product type; parse the search query to identify an intensifier that is to indicate a quality of interest to the user for the product and to distinguish between the product and the stated expectation; dynamically define an attribute for the product distinguished by the parse or a synonym thereof, wherein the defined attribute is to include the stated expectation distinguished by the parse or a synonym thereof; filter consumer generated content using the defined attribute to obtain one or more specific products to be identified in the search results by a manufacturer of the one or more specific products; rate the one or more specific products based on one or more opinions that are to mention the defined attribute to be expressed in the consumer generated content to identify in the search results closest matching specific products for the general product; and present the search results to the user including the closest matching specific products identified by the manufacturer. | 11. An apparatus comprising a processor to: receive a search query by a user that is to include a stated expectation with respect to a general product to be identified in the search query by a general product type; parse the search query to identify an intensifier that is to indicate a quality of interest to the user for the product and to distinguish between the product and the stated expectation; dynamically define an attribute for the product distinguished by the parse or a synonym thereof, wherein the defined attribute is to include the stated expectation distinguished by the parse or a synonym thereof; filter consumer generated content using the defined attribute to obtain one or more specific products to be identified in the search results by a manufacturer of the one or more specific products; rate the one or more specific products based on one or more opinions that are to mention the defined attribute to be expressed in the consumer generated content to identify in the search results closest matching specific products for the general product; and present the search results to the user including the closest matching specific products identified by the manufacturer. 12. The apparatus of claim 11 , wherein the processor is to assign a rank specific to the defined attribute to the one or more specific products based on the one or more opinions expressed in the consumer generated content. | 0.5 |
9,720,982 | 1 | 5 | 1. An apparatus for performing a natural language search, the apparatus comprising: a processor configured to search an index, said index contains information which references a domain model, using key words from a user's natural language question and the context of the user's question, and to save a plurality of documents obtained in response to the search of the index; the processor further configured to map each of the documents as a node into an object graph, wherein each node is associated with a parent node, except when the node is a root node; the processor further configured to identify the root node of each document; the processor further configured to identify the path of each node from the node to the node's root node, wherein said path comprises a plurality of nodes that connect the node to the root node; the processor further configured to identify a plurality of matching paths, each of said matching paths, wherein each matching path provides an answer to the user's natural language question, each of said plurality of paths that comprises a discrete path of nodes; the processor further configured to filter out paths depending on a set of the user's pre-specified criterion, said criterion including a weighting factor specifying a relative level of importance associated with receiving accurate information; the processor further configured to rank the remaining paths; and a display configured to display, in response to the filtering and ranking, a selected answer to the user. | 1. An apparatus for performing a natural language search, the apparatus comprising: a processor configured to search an index, said index contains information which references a domain model, using key words from a user's natural language question and the context of the user's question, and to save a plurality of documents obtained in response to the search of the index; the processor further configured to map each of the documents as a node into an object graph, wherein each node is associated with a parent node, except when the node is a root node; the processor further configured to identify the root node of each document; the processor further configured to identify the path of each node from the node to the node's root node, wherein said path comprises a plurality of nodes that connect the node to the root node; the processor further configured to identify a plurality of matching paths, each of said matching paths, wherein each matching path provides an answer to the user's natural language question, each of said plurality of paths that comprises a discrete path of nodes; the processor further configured to filter out paths depending on a set of the user's pre-specified criterion, said criterion including a weighting factor specifying a relative level of importance associated with receiving accurate information; the processor further configured to rank the remaining paths; and a display configured to display, in response to the filtering and ranking, a selected answer to the user. 5. The apparatus of claim 1 , wherein the processor is further configured to display more than one answer if the processor is unable to determine a specific answer to the user's question. | 0.615226 |
8,852,239 | 1 | 5 | 1. In a spinal implant with a bone screw having a shank for implanting into bone, the bone screw capturing a longitudinal connecting member at an adjustable angle with respect to the shank, the improvement comprising: a) a receiver having a pair of spaced upstanding arms forming a channel for receiving the longitudinal connecting member, the receiver being integral with the shank, the receiver forming a cavity communicating with the channel, the cavity partially defined by a curved seating surface having a first radius, the receiver further having an arcuate pivot track formed in an inner surface of one of the upstanding arms, the pivot track being spaced from the seating surface, the pivot track having a second radius, the second radius originating at a pivot axis disposed perpendicular to and intersecting with a central axis of rotation of the shank; and b) an insert having a bottom curved surface sized and shaped for slidable engagement with the receiver seating surface, a projection in slidable engagement with the pivot track and a top surface sized and shaped for closely receiving the longitudinal connecting member. | 1. In a spinal implant with a bone screw having a shank for implanting into bone, the bone screw capturing a longitudinal connecting member at an adjustable angle with respect to the shank, the improvement comprising: a) a receiver having a pair of spaced upstanding arms forming a channel for receiving the longitudinal connecting member, the receiver being integral with the shank, the receiver forming a cavity communicating with the channel, the cavity partially defined by a curved seating surface having a first radius, the receiver further having an arcuate pivot track formed in an inner surface of one of the upstanding arms, the pivot track being spaced from the seating surface, the pivot track having a second radius, the second radius originating at a pivot axis disposed perpendicular to and intersecting with a central axis of rotation of the shank; and b) an insert having a bottom curved surface sized and shaped for slidable engagement with the receiver seating surface, a projection in slidable engagement with the pivot track and a top surface sized and shaped for closely receiving the longitudinal connecting member. 5. The improvement of claim 1 wherein the receiver seating surface first radius also originates at the pivot axis. | 0.940314 |
9,015,581 | 12 | 13 | 12. The system of claim 11 , wherein the at least one user-content component comprises a text component. | 12. The system of claim 11 , wherein the at least one user-content component comprises a text component. 13. The system of claim 12 , wherein the text component allows text-wrapping. | 0.5 |
9,003,265 | 1 | 3 | 1. A method for processing a non-volatile memory designed to store words containing data bits and control bits allowing error correction with an error correction code, the method comprising: storing information in a memory plane including writing in the memory plane at least one modified digital word modified with respect to at least one initial digital word not having any erroneous bit, said at least one modified digital word containing a bit at a position and having a modified value with respect to the value of a corresponding bit in the at least one initial digital word, other bits of the at least one modified digital word having values identical to corresponding bits in the initial digital word, the position of the modified bit in said at least one modified digital word defining a value of digital information. | 1. A method for processing a non-volatile memory designed to store words containing data bits and control bits allowing error correction with an error correction code, the method comprising: storing information in a memory plane including writing in the memory plane at least one modified digital word modified with respect to at least one initial digital word not having any erroneous bit, said at least one modified digital word containing a bit at a position and having a modified value with respect to the value of a corresponding bit in the at least one initial digital word, other bits of the at least one modified digital word having values identical to corresponding bits in the initial digital word, the position of the modified bit in said at least one modified digital word defining a value of digital information. 3. The method according to claim 1 , in which storing information in the memory plane comprises writing in the memory plane a plurality of modified digital words respectively modified with respect to a plurality of initial digital words not having any erroneous bit, each modified digital word containing a bit having a modified value with respect to the value of a corresponding bit in the corresponding initial digital word, other bits of the modified digital word having values identical to those of corresponding bits in the corresponding initial digital word, the respective positions of the modified bits in the modified digital words defining together a value of digital information. | 0.5 |
4,868,879 | 2 | 6 | 2. An apparatus according to claim 1, wherein said means for detecting a minimum dissimilarity and storing the number of the corresponding reference template updates and stores the number of the reference template corresponding to the minimum dissimilarity each time said speech frame is updated; and the number of said matching paths for each of said reference templates is 3. | 2. An apparatus according to claim 1, wherein said means for detecting a minimum dissimilarity and storing the number of the corresponding reference template updates and stores the number of the reference template corresponding to the minimum dissimilarity each time said speech frame is updated; and the number of said matching paths for each of said reference templates is 3. 6. An apparatus according to claim 2, wherein said means for updating a speech frame number continues to update said speech frame number even in the silent condition after the start point of the input speech has been detected until the end point thereof is detected; and said means for detecting a minimum dissimilarity and storing the number of the corresponding reference template, stops the detection of the minimum dissimilarity under the silent condition. | 0.824427 |
8,966,465 | 1 | 4 | 1. A method for customizing a software application, the method comprising: retrieving a first metadata document via a software component configured to enable creation and/or update of XML documents, wherein: the first metadata document is based at least in part on Extensible Markup Language (XML); content of the first metadata document at least partially defines one or more characteristics of at least a portion of a software application; and at least one of the one or more characteristics corresponds to one or more of content, behavior, and/or appearance; in response to retrieving the first metadata document, creating in memory, a metadata object to represent the first metadata document; receiving, from the software component, one or more modifications to the metadata object, wherein the one or more modifications: are expressed as method calls performed on the metadata object; and comprise a modification to a source element in the first metadata document; translating the one or more method calls into one or more customization instructions, wherein the one or more customization instructions, when executed, cause at least the portion of the software application to change at least one of the one or more characteristics, the translating comprising: checking whether each of a plurality of elements is associated with a respective unique identifier, the plurality of elements comprising a sibling element, a parent element, and the source element; selecting a unique identifier based on a predetermined order comprising determining whether the source element is associated with a globally unique identifier and, if the source element is not associated with the globally unique identifier, determining whether the source element is associated with a locally unique identifier; and generating at least one customization instruction of the one or more customization instructions to reference the modification to the source element based at least in part on the checking and the selecting; and storing in a second metadata document the one or more customization instructions as a first customization for the first metadata document, wherein the first customization is stored separately from the first metadata document. | 1. A method for customizing a software application, the method comprising: retrieving a first metadata document via a software component configured to enable creation and/or update of XML documents, wherein: the first metadata document is based at least in part on Extensible Markup Language (XML); content of the first metadata document at least partially defines one or more characteristics of at least a portion of a software application; and at least one of the one or more characteristics corresponds to one or more of content, behavior, and/or appearance; in response to retrieving the first metadata document, creating in memory, a metadata object to represent the first metadata document; receiving, from the software component, one or more modifications to the metadata object, wherein the one or more modifications: are expressed as method calls performed on the metadata object; and comprise a modification to a source element in the first metadata document; translating the one or more method calls into one or more customization instructions, wherein the one or more customization instructions, when executed, cause at least the portion of the software application to change at least one of the one or more characteristics, the translating comprising: checking whether each of a plurality of elements is associated with a respective unique identifier, the plurality of elements comprising a sibling element, a parent element, and the source element; selecting a unique identifier based on a predetermined order comprising determining whether the source element is associated with a globally unique identifier and, if the source element is not associated with the globally unique identifier, determining whether the source element is associated with a locally unique identifier; and generating at least one customization instruction of the one or more customization instructions to reference the modification to the source element based at least in part on the checking and the selecting; and storing in a second metadata document the one or more customization instructions as a first customization for the first metadata document, wherein the first customization is stored separately from the first metadata document. 4. The method of claim 1 , wherein the first metadata document is retrieved as a Document Object Model (DOM) object, and wherein the one or modifications are expressed as standard DOM method calls. | 0.738032 |
8,060,507 | 12 | 20 | 12. An article of manufacture comprising a computer-readable storage device storing computer-readable instructions which, when executed, cause one or more processing devices to perform the following: access information indicating which documents in a set of documents were selected by a user for viewing and which documents in the set of documents were not selected by the user for viewing; generate at least one positive word vector using words contained in at least a segment of at least one of the documents that was selected by the user for viewing; generate at least one negative word vector using words contained in at least a segment of at least one of the documents that was not selected by the user for viewing; generate document word vectors for at least some of the documents that were selected by the user for viewing; perform, using at least one processor, a vector space relationship analysis of the positive word vector, the negative word vector, and the document word vectors; establish, using at least one processor, a document rank order of the documents selected by the user for viewing based on the performed vector space relationship analysis; classify the documents selected by the user for viewing in predetermined categories; rank the predetermined categories based on the document rank order; send the ranked categories to an ad server; and receive advertisements associated with the ranked categories from the ad server in a selected context. | 12. An article of manufacture comprising a computer-readable storage device storing computer-readable instructions which, when executed, cause one or more processing devices to perform the following: access information indicating which documents in a set of documents were selected by a user for viewing and which documents in the set of documents were not selected by the user for viewing; generate at least one positive word vector using words contained in at least a segment of at least one of the documents that was selected by the user for viewing; generate at least one negative word vector using words contained in at least a segment of at least one of the documents that was not selected by the user for viewing; generate document word vectors for at least some of the documents that were selected by the user for viewing; perform, using at least one processor, a vector space relationship analysis of the positive word vector, the negative word vector, and the document word vectors; establish, using at least one processor, a document rank order of the documents selected by the user for viewing based on the performed vector space relationship analysis; classify the documents selected by the user for viewing in predetermined categories; rank the predetermined categories based on the document rank order; send the ranked categories to an ad server; and receive advertisements associated with the ranked categories from the ad server in a selected context. 20. The manufacture of claim 12 , wherein the instructions further comprise instructions that cause the one or more processing devices to: train a support vector machine by inputting documents labeled with the predetermined categories; and wherein, to classify the documents selected by the user for viewing, the instructions include instructions that cause the one or more processing devices to use the trained support vector machine to label the documents with the predetermined categories. | 0.664393 |
8,103,873 | 1 | 3 | 1. A method of enforcing compliance, comprising: receiving, by a computer system, a VoIP communication; comparing, by a computer system, at least a first portion of the communication to a lexicon stored in a storage device comprising a plurality of auditory representations to determine if a first auditory representation is absent from the first portion of the communication, wherein the comparison of the first portion of the communication to the lexicon occurs at the time the auditory VoIP communication is being received; storing, by a computer system, the determination in a storage device if the first auditory representation is absent from the first portion of the communication; generating, by a computer system, metadata based on the VoIP communication, wherein the metadata is stored in the storage device; and quarantining, by a computer system, the communication if the first auditory representation is absent from the first portion of the communication, wherein the absence indicates that the communication is not compliant. | 1. A method of enforcing compliance, comprising: receiving, by a computer system, a VoIP communication; comparing, by a computer system, at least a first portion of the communication to a lexicon stored in a storage device comprising a plurality of auditory representations to determine if a first auditory representation is absent from the first portion of the communication, wherein the comparison of the first portion of the communication to the lexicon occurs at the time the auditory VoIP communication is being received; storing, by a computer system, the determination in a storage device if the first auditory representation is absent from the first portion of the communication; generating, by a computer system, metadata based on the VoIP communication, wherein the metadata is stored in the storage device; and quarantining, by a computer system, the communication if the first auditory representation is absent from the first portion of the communication, wherein the absence indicates that the communication is not compliant. 3. The method as recited in claim 1 , further comprising comparing the first portion of the communication to the lexicon to determine if there is a positive match to a second auditory representation from the lexicon. | 0.5 |
8,761,499 | 13 | 15 | 13. A method for detecting a global harmful video, the method comprising: determining harmfulness of learning video segments from video learning information; analyzing, executed by a processor, occurrence information of harmful learning video segments among the learning video segments based on the harmfulness determination results of the learning video segments; generating a global harmfulness determination policy based on the occurrence information of the harmful learning video segments; determining harmfulness of input video segments from information of an input video; analyzing occurrence information of the harmful input video segments among the input video segments based on the harmfulness determination results of the input video segments; and finally determining global harmfulness of the input video based on the analyzed occurrence information of the harmful input video segments and the generated global harmfulness determination policy, wherein said analyzing the occurrence information of the harmful learning video segments includes: calculating occurrence frequencies of the harmful learning video segments and locations of the occurrences; assigning occurrence continuities to the harmful learning video segments which successively appear; and calculating occurrence probability values of the harmful learning video segments by combining harmfulness probability values of the harmful learning video segments with the occurrence continuities. | 13. A method for detecting a global harmful video, the method comprising: determining harmfulness of learning video segments from video learning information; analyzing, executed by a processor, occurrence information of harmful learning video segments among the learning video segments based on the harmfulness determination results of the learning video segments; generating a global harmfulness determination policy based on the occurrence information of the harmful learning video segments; determining harmfulness of input video segments from information of an input video; analyzing occurrence information of the harmful input video segments among the input video segments based on the harmfulness determination results of the input video segments; and finally determining global harmfulness of the input video based on the analyzed occurrence information of the harmful input video segments and the generated global harmfulness determination policy, wherein said analyzing the occurrence information of the harmful learning video segments includes: calculating occurrence frequencies of the harmful learning video segments and locations of the occurrences; assigning occurrence continuities to the harmful learning video segments which successively appear; and calculating occurrence probability values of the harmful learning video segments by combining harmfulness probability values of the harmful learning video segments with the occurrence continuities. 15. The method of claim 13 , wherein said determining the harmfulness of the learning video segments and the input video segments is performed by using a content-based discrimination method. | 0.90961 |
8,667,414 | 1 | 8 | 1. A method comprising: receiving, by a device, an indication of a gesture input at a portion of a presence-sensitive surface associated with a virtual keyboard, the virtual keyboard comprising a set of virtual keys, each virtual key from the set of virtual keys being associated with a region of the presence-sensitive surface; defining, by the device, a series of input points that represent a path of the gesture input across the virtual keyboard; defining, by the device, respective sets of anchor points corresponding to respective words in a set of candidate words, each of the anchor points corresponding to a location of the presence-sensitive surface associated with a virtual key from the set of virtual keys; identifying, by the device, for each respective anchor point in each of the sets of anchor points, a respective relevant input point in the series of input points; determining, by the device, a respective distance score for each respective anchor point in the sets of anchor points, wherein for each respective anchor point in the sets of anchor points, the respective distance score for the respective anchor point is based at least in part on a distance on the presence-sensitive surface between the respective anchor point and the respective relevant input point for the respective anchor point, wherein determining the respective distance score for each respective anchor point in each respective set of anchor points comprises adjusting, by the device, the respective distance score for the respective anchor point in response to determining that the respective anchor point is not a closest one of the anchor points in the respective set of anchor points to the respective relevant input point for the respective anchor point; and identifying, by the device, based at least in part on the respective distance scores for the respective anchor points, a word in the set of candidate words that corresponds to the gesture input. | 1. A method comprising: receiving, by a device, an indication of a gesture input at a portion of a presence-sensitive surface associated with a virtual keyboard, the virtual keyboard comprising a set of virtual keys, each virtual key from the set of virtual keys being associated with a region of the presence-sensitive surface; defining, by the device, a series of input points that represent a path of the gesture input across the virtual keyboard; defining, by the device, respective sets of anchor points corresponding to respective words in a set of candidate words, each of the anchor points corresponding to a location of the presence-sensitive surface associated with a virtual key from the set of virtual keys; identifying, by the device, for each respective anchor point in each of the sets of anchor points, a respective relevant input point in the series of input points; determining, by the device, a respective distance score for each respective anchor point in the sets of anchor points, wherein for each respective anchor point in the sets of anchor points, the respective distance score for the respective anchor point is based at least in part on a distance on the presence-sensitive surface between the respective anchor point and the respective relevant input point for the respective anchor point, wherein determining the respective distance score for each respective anchor point in each respective set of anchor points comprises adjusting, by the device, the respective distance score for the respective anchor point in response to determining that the respective anchor point is not a closest one of the anchor points in the respective set of anchor points to the respective relevant input point for the respective anchor point; and identifying, by the device, based at least in part on the respective distance scores for the respective anchor points, a word in the set of candidate words that corresponds to the gesture input. 8. The method of claim 1 , wherein the word is a first word and the method comprises: determining, by the device, respective anchor scores for respective words in the set of candidate words, the respective anchor scores for the respective words based at least in part on the distance scores for the anchor points that correspond to the respective words; pruning, by the device, one or more words from the set of candidate words based at least in part on the respective anchor scores for the respective words; after pruning the one or more words from the set of candidate words based at least in part on the respective anchor scores for the respective words, determining, by the device, respective shape scores for respective words remaining in the set of candidate words, the respective shape scores for the respective words remaining in the set of candidate words being based at least in part on distances between the input points and closest points on shape templates for the respective words remaining in the set of candidate words; and identifying, by the device, based at least in part on the respective anchor scores and the respective shape scores for the respective words remaining in the set of candidate words, that the first word corresponds to the gesture input. | 0.5 |
8,818,795 | 6 | 13 | 6. A method for analyzing a linguistic input comprising, at a computing device: receiving the linguistic input, the linguistic input comprising at least one word; accessing prestored language data for a language corresponding to the linguistic input; converting the linguistic input into a text possibility based on the received language data; determining a meaning of the text possibility based on the prestored language data, including: selecting a subset of the text possibility; generating at least one new language construction and at least one new lexeme based on the subset of the text possibility; identifying a known language construction that matches the at least one new language construction; combining the known language construction that matches the subset of the text possibility with another language construction to generate a meaning possibility; generating a semantic structure for the meaning possibility of the text possibility; modifying the semantic structure for the meaning possibility based on the prestored language data; and determining the action to perform based on the modified semantic structure for the meaning possibility. | 6. A method for analyzing a linguistic input comprising, at a computing device: receiving the linguistic input, the linguistic input comprising at least one word; accessing prestored language data for a language corresponding to the linguistic input; converting the linguistic input into a text possibility based on the received language data; determining a meaning of the text possibility based on the prestored language data, including: selecting a subset of the text possibility; generating at least one new language construction and at least one new lexeme based on the subset of the text possibility; identifying a known language construction that matches the at least one new language construction; combining the known language construction that matches the subset of the text possibility with another language construction to generate a meaning possibility; generating a semantic structure for the meaning possibility of the text possibility; modifying the semantic structure for the meaning possibility based on the prestored language data; and determining the action to perform based on the modified semantic structure for the meaning possibility. 13. The method of claim 6 , wherein generating the meaning possibility is based on at least one of the combined language constructions, a pronoun binding in the subset, a conjunction in the subset, and an ellipsis in the subset. | 0.5 |
7,668,888 | 44 | 49 | 44. A computer for providing at least one readable object that is readable by a search engine from at least one structured data object stored in a database, the computer comprising a processor for: extracting the structured data object from the database, wherein the structured data object includes a hierarchical sequence of nodes related by at least one link and a plurality of content, and wherein at least one content of the plurality of content is nonreadable content that cannot be read by the search engine; mapping the structured data object into a generic data model according to the hierarchical sequence of nodes and content; and creating the readable object from the generic data model, wherein creating includes converting the nonreadable content of the structured data object into readable content for the search engine. | 44. A computer for providing at least one readable object that is readable by a search engine from at least one structured data object stored in a database, the computer comprising a processor for: extracting the structured data object from the database, wherein the structured data object includes a hierarchical sequence of nodes related by at least one link and a plurality of content, and wherein at least one content of the plurality of content is nonreadable content that cannot be read by the search engine; mapping the structured data object into a generic data model according to the hierarchical sequence of nodes and content; and creating the readable object from the generic data model, wherein creating includes converting the nonreadable content of the structured data object into readable content for the search engine. 49. The computer of claim 44 , further comprising an interface for access of the search engine to the readable object. | 0.5 |
5,546,575 | 35 | 38 | 35. A compaction method, which comprises: selecting a first group of fields from a database; reading a first group of data values from a record of the database, each individual data value being read from a separate field from within the first group of fields to form a first data value combination; assigning a numeric equivalent to the first data value combination, such that the numeric equivalent uniquely determines the first data value combination; replacing the first data value combination with a representation of the numeric equivalent to create a compacted data value only if a field combining criterion based on the first group of fields, and dependent on a concentration level of unique data value combinations, is satisfied, the compacted data value being a reduced storage equivalent of the first data value combination; and creating a translation table which contains an entry that equates the data value combination with the assigned numeric equivalent, to provide for retranslation from the numeric equivalent to the data value combination. | 35. A compaction method, which comprises: selecting a first group of fields from a database; reading a first group of data values from a record of the database, each individual data value being read from a separate field from within the first group of fields to form a first data value combination; assigning a numeric equivalent to the first data value combination, such that the numeric equivalent uniquely determines the first data value combination; replacing the first data value combination with a representation of the numeric equivalent to create a compacted data value only if a field combining criterion based on the first group of fields, and dependent on a concentration level of unique data value combinations, is satisfied, the compacted data value being a reduced storage equivalent of the first data value combination; and creating a translation table which contains an entry that equates the data value combination with the assigned numeric equivalent, to provide for retranslation from the numeric equivalent to the data value combination. 38. A compaction method according to claim 35 wherein said first group of fields comprises three separate fields of the database. | 0.921245 |
9,762,387 | 1 | 2 | 1. A method comprising: generating, at a first device, at least one query identifier based on a first set of keywords, wherein each query identifier comprises a first hash of an identified keyword from the first set of keywords; transmitting, to at least a second device, a query comprising the at least one query identifier, wherein the query is transmitted via an ad hoc network; receiving, from the second device, a response comprising at least one match identifier and an encrypted message, wherein each match identifier comprises a second hash of the identified keyword that the second device is able to identify based on the at least one query identifier; determining, at the first device, one or more keywords from the first set of keywords that corresponds to the at least one match identifier; generating an encryption key based on the one or more keywords identified by the at least one match identifier; and decrypting the encrypted message using the encryption key. | 1. A method comprising: generating, at a first device, at least one query identifier based on a first set of keywords, wherein each query identifier comprises a first hash of an identified keyword from the first set of keywords; transmitting, to at least a second device, a query comprising the at least one query identifier, wherein the query is transmitted via an ad hoc network; receiving, from the second device, a response comprising at least one match identifier and an encrypted message, wherein each match identifier comprises a second hash of the identified keyword that the second device is able to identify based on the at least one query identifier; determining, at the first device, one or more keywords from the first set of keywords that corresponds to the at least one match identifier; generating an encryption key based on the one or more keywords identified by the at least one match identifier; and decrypting the encrypted message using the encryption key. 2. The method of claim 1 , further comprising: generating, by the first device, a first cryptographic nonce; and generating the query to include the first cryptographic nonce. | 0.836142 |
9,628,873 | 1 | 5 | 1. A computer-implemented method comprising: receiving, by a media content trend analysis system comprising at least one physical processor, a plurality of media content streams representative of a plurality of media programs; detecting, by the media content trend analysis system during the receiving of the plurality of media content streams, caption data included in the plurality of media content streams and associated with the plurality of media programs; identifying, by the media content trend analysis system based on the detected caption data, a trending topic; and identifying, by the media content trend analysis system, a media program clip associated with the trending topic, the identifying of the media program clip associated with the trending topic comprising: detecting, within caption data included in a media content stream representative of a media program, one or more keywords associated with the trending topic, identifying, within the media content stream based on the detected one or more keywords, a first timestamp corresponding to the one or more keywords associated with the trending topic and a second timestamp corresponding to the one or more keywords associated with the trending topic, determining a start timestamp based on the first timestamp and an end timestamp based on the second timestamp, and designating a portion of the media content stream defined by the start timestamp and the end timestamp as the media program clip associated with the trending topic. | 1. A computer-implemented method comprising: receiving, by a media content trend analysis system comprising at least one physical processor, a plurality of media content streams representative of a plurality of media programs; detecting, by the media content trend analysis system during the receiving of the plurality of media content streams, caption data included in the plurality of media content streams and associated with the plurality of media programs; identifying, by the media content trend analysis system based on the detected caption data, a trending topic; and identifying, by the media content trend analysis system, a media program clip associated with the trending topic, the identifying of the media program clip associated with the trending topic comprising: detecting, within caption data included in a media content stream representative of a media program, one or more keywords associated with the trending topic, identifying, within the media content stream based on the detected one or more keywords, a first timestamp corresponding to the one or more keywords associated with the trending topic and a second timestamp corresponding to the one or more keywords associated with the trending topic, determining a start timestamp based on the first timestamp and an end timestamp based on the second timestamp, and designating a portion of the media content stream defined by the start timestamp and the end timestamp as the media program clip associated with the trending topic. 5. The method of claim 1 , wherein the media content stream is received subsequent to the receiving of the plurality of media content streams. | 0.835267 |
10,162,315 | 1 | 2 | 1. A process control configuration method for developing a process control strategy in a process plant, comprising: selecting, by one or more processors, a typical component template from a library of typical component templates that defines an implementation of a process control loop function that may be utilized by a plurality of plant equipment devices within a process plant; selecting, by one or more processors, a first and a second adapter component template from a library of adapter component templates, the first and the second adapter component templates having one or more configurable logical expressions or one or more configurable logic algorithms; configuring, by one or more processors, the first and the second adapter component templates based on a specific process control operation associated with each of a first and a second plant equipment device, respectively, from among the plurality of plant equipment devices, wherein configuring the first and the second adapter component templates includes defining the one or more configurable logical expressions or the one or more configurable logic algorithms to specify how the first and the second adapter component templates interact with the typical component template and signals to or from the first and the second plant equipment devices to define for the first and the second plant equipment devices, respectively, the specific process control operation utilizing the process control loop function defined by the typical component template, wherein the process control loop function includes one or more of: (i) a proportional-integral-derivative control operation, (ii) a proportional-integral control operation, (iii) a start permit control operation, (iv) an alarm control operation, or (v) a native control component operation; instantiating, by one or more processors, the typical component template with each of the first and the second adapter component templates, respectively, to generate a first and a second native control component, respectively; and executing, by one or more processors associated with one or more process controllers communicatively coupled to one or more host work stations and the plurality of plant equipment devices, the first and second native control components for the first and the second plant equipment devices, respectively, wherein the first native control component, when executed, performs the specific process control operation for the first plant equipment device utilizing the process control loop function defined by the typical component template in accordance with the configured first adapter component template, and wherein the second native control component, when executed, performs the specific process control operation for the second plant equipment device utilizing the process control loop function defined by the typical component template in accordance with the configured second adapter component template. | 1. A process control configuration method for developing a process control strategy in a process plant, comprising: selecting, by one or more processors, a typical component template from a library of typical component templates that defines an implementation of a process control loop function that may be utilized by a plurality of plant equipment devices within a process plant; selecting, by one or more processors, a first and a second adapter component template from a library of adapter component templates, the first and the second adapter component templates having one or more configurable logical expressions or one or more configurable logic algorithms; configuring, by one or more processors, the first and the second adapter component templates based on a specific process control operation associated with each of a first and a second plant equipment device, respectively, from among the plurality of plant equipment devices, wherein configuring the first and the second adapter component templates includes defining the one or more configurable logical expressions or the one or more configurable logic algorithms to specify how the first and the second adapter component templates interact with the typical component template and signals to or from the first and the second plant equipment devices to define for the first and the second plant equipment devices, respectively, the specific process control operation utilizing the process control loop function defined by the typical component template, wherein the process control loop function includes one or more of: (i) a proportional-integral-derivative control operation, (ii) a proportional-integral control operation, (iii) a start permit control operation, (iv) an alarm control operation, or (v) a native control component operation; instantiating, by one or more processors, the typical component template with each of the first and the second adapter component templates, respectively, to generate a first and a second native control component, respectively; and executing, by one or more processors associated with one or more process controllers communicatively coupled to one or more host work stations and the plurality of plant equipment devices, the first and second native control components for the first and the second plant equipment devices, respectively, wherein the first native control component, when executed, performs the specific process control operation for the first plant equipment device utilizing the process control loop function defined by the typical component template in accordance with the configured first adapter component template, and wherein the second native control component, when executed, performs the specific process control operation for the second plant equipment device utilizing the process control loop function defined by the typical component template in accordance with the configured second adapter component template. 2. The process control configuration method of claim 1 , wherein the acts of selecting the typical component template, selecting the first and the second adapter component templates, configuring the first and the second adapter component templates, and instantiating the typical component template with the first and the second adapter component templates are performed via a graphical programming interface. | 0.627737 |
9,135,653 | 118 | 137 | 118. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender further comprising: extracting a user identifier from the first activity data; and if a match for the user identifier is not found in the social graph, attempting to match a plurality of mobile device identifiers in a selected geo-vicinity and selected time interval; using the second activity information to identify a second node in the social graph as being representative of the recipient; determining a category for the first link as a first category type; in the social graph, identifying a first edge between the first and second nodes as being representative of the first category type; determining a first value associated with the first edge based on at least one of the first or second activity information; and adjusting the first value to create a second value associated with the first edge based on a passage of time from at least one of the first or second activity information. | 118. A method comprising: receiving first activity information for a sender of a first link to at least one recipient collected by a collection resource at a Web site, wherein no personally identifiable information of the sender is collected in the first activity information; storing the first activity information at a storage server; receiving second activity information when a recipient accesses the first link sent by the sender corresponding to the first activity information stored at the storage server, wherein no personally identifiable information of the recipient is collected in the second activity information; using at least one processor, using the first activity information to identify a first node in a social graph as being representative of the sender further comprising: extracting a user identifier from the first activity data; and if a match for the user identifier is not found in the social graph, attempting to match a plurality of mobile device identifiers in a selected geo-vicinity and selected time interval; using the second activity information to identify a second node in the social graph as being representative of the recipient; determining a category for the first link as a first category type; in the social graph, identifying a first edge between the first and second nodes as being representative of the first category type; determining a first value associated with the first edge based on at least one of the first or second activity information; and adjusting the first value to create a second value associated with the first edge based on a passage of time from at least one of the first or second activity information. 137. The method of claim 118 wherein the receiving first activity information for a sender of a first link to at least one recipient comprises: sending of an e-mail including the first link by the sender via a mobile device. | 0.506608 |
8,732,630 | 15 | 16 | 15. An article of manufacture comprising a non-transitory computer accessible storage medium having stored thereupon a sequence of instructions which, when executed by at least one processor or at least one processor core executing one or more threads, causes the at least one processor or the at least one processor core to perform a method for implementing analog behavioral modeling and IP (intellectual property) integration using a Hardware Description Language, the method comprising: at least one processor or at least one processor core executing a process, the process comprising: detecting an incompatible connection that interacts with a wire that is represented using digital signals in the digital modeling environment; representing a real-valued net of a built-in nettype in the digital modeling environment with 4-state logic signals; correlating the real-valued net with a corresponding resolution function that is defined natively in the digital modeling environment; and coercing the incompatible connection to the wire in the digital modeling environment based at least in part upon the corresponding resolution function. | 15. An article of manufacture comprising a non-transitory computer accessible storage medium having stored thereupon a sequence of instructions which, when executed by at least one processor or at least one processor core executing one or more threads, causes the at least one processor or the at least one processor core to perform a method for implementing analog behavioral modeling and IP (intellectual property) integration using a Hardware Description Language, the method comprising: at least one processor or at least one processor core executing a process, the process comprising: detecting an incompatible connection that interacts with a wire that is represented using digital signals in the digital modeling environment; representing a real-valued net of a built-in nettype in the digital modeling environment with 4-state logic signals; correlating the real-valued net with a corresponding resolution function that is defined natively in the digital modeling environment; and coercing the incompatible connection to the wire in the digital modeling environment based at least in part upon the corresponding resolution function. 16. The article of manufacture of claim 15 , the process further comprising: determining a system function natively in the digital modeling environment to sample a continuous signal into a discrete real-valued signal; identifying an input parameter to the system function; identifying or determining a time point to initiate the system function; and performing real signal sampling based at least in part upon the time point and the input parameter, wherein the input parameter comprises at least one of a voltage tolerance, a voltage differential, a time tolerance, a rise time, and a fall time. | 0.564964 |
8,275,792 | 9 | 15 | 9. A computer-readable storage medium that stores a document type identifying program for identifying a document type of a document having word information on word strings and ruled line information on ruled lines written thereon, the document type identifying program causing a computer to execute a process comprising: receiving inputs regarding the word information on the word strings and the ruled line information on the ruled lines written on the document; storing a plurality of keywords used as keys that identify document types in a storage unit in association with each document type; generating, for each keyword, a plurality of word-sets, which are new combinations of a plurality of words obtained by decomposing keywords consisted of a plurality of words into each word composing the keywords and further extracting a plurality of words from the each word, to be checked for matching with the word strings written on the document by using the keywords stored in the storage unit at the storing; generating, based on the received inputs regarding the word information and the ruled line information at the receiving, grouped word strings by grouping the words written on the document and overlapping each other in terms of height when seen from a lateral direction, and aligning each of the generated grouped word strings; checking matching of each of the grouped word strings aligned at the aligning with each of the word-sets generated at the generating, obtaining, for each of the keywords, number of matched words with a highest matching rate between each of the grouped word strings and each of the word-sets, and calculating an evaluation value for each document type by using each of the obtained number of matched words, each evaluation value evaluating a possibility of each document type to be the type of the document; and determining, based on each evaluation value calculated for each document type at the calculating, the document type of the document having the word information and the ruled line information written thereon. | 9. A computer-readable storage medium that stores a document type identifying program for identifying a document type of a document having word information on word strings and ruled line information on ruled lines written thereon, the document type identifying program causing a computer to execute a process comprising: receiving inputs regarding the word information on the word strings and the ruled line information on the ruled lines written on the document; storing a plurality of keywords used as keys that identify document types in a storage unit in association with each document type; generating, for each keyword, a plurality of word-sets, which are new combinations of a plurality of words obtained by decomposing keywords consisted of a plurality of words into each word composing the keywords and further extracting a plurality of words from the each word, to be checked for matching with the word strings written on the document by using the keywords stored in the storage unit at the storing; generating, based on the received inputs regarding the word information and the ruled line information at the receiving, grouped word strings by grouping the words written on the document and overlapping each other in terms of height when seen from a lateral direction, and aligning each of the generated grouped word strings; checking matching of each of the grouped word strings aligned at the aligning with each of the word-sets generated at the generating, obtaining, for each of the keywords, number of matched words with a highest matching rate between each of the grouped word strings and each of the word-sets, and calculating an evaluation value for each document type by using each of the obtained number of matched words, each evaluation value evaluating a possibility of each document type to be the type of the document; and determining, based on each evaluation value calculated for each document type at the calculating, the document type of the document having the word information and the ruled line information written thereon. 15. The computer-readable storage medium according to claim 9 , wherein the determining includes narrowing down the possible document types based on each evaluation value each time each evaluation value is calculated for each document type, and replacing a keyword among the keywords stored in the storage unit depending on the narrowed possible document types each time the possible document types are narrowed down, the generating the word-sets includes generating the word-sets by using the modified keyword each time the keyword is replaced at the replacing, and the checking includes checking matching of each of the grouped word strings aligned at the aligning with each of the word-sets generated at the generating to calculate each evaluation value for each document type, the evaluation values evaluating a degree of matching between word strings of each of the grouped word strings and each of the word-sets, each time the word-sets are generated. | 0.5 |
9,588,962 | 9 | 10 | 9. The method of claim 1 , wherein the definition of the instance comprises an identifier of the concept associated with the instance, wherein the instance structure further comprises the identifier of the concept, and wherein the method further comprises using the identifier of the concept in the instance structure to determine, from the user ontological model, the concept that is associated with the instance. | 9. The method of claim 1 , wherein the definition of the instance comprises an identifier of the concept associated with the instance, wherein the instance structure further comprises the identifier of the concept, and wherein the method further comprises using the identifier of the concept in the instance structure to determine, from the user ontological model, the concept that is associated with the instance. 10. The method of claim 9 , wherein the main ontological model comprises the concept. | 0.816017 |
9,355,178 | 24 | 35 | 24. A system comprising: a) a Web server computer configured to present web page search results related to terms of a search query initiated by a user, wherein the web page search results include a results list comprising a list of web pages related to the terms of the search query, the order in which the web pages are presented in response to the search query being influenced by relevance feedback provided by multiple users prior to the search query, and wherein the relevance feedback is different from selection of a link to a web page in the results list; b) a search engine for querying a database and providing the web page search results in response to user queries; and c) a content manager for managing the supplemental information in response to user input, wherein the user input comprises the relevance feedback. | 24. A system comprising: a) a Web server computer configured to present web page search results related to terms of a search query initiated by a user, wherein the web page search results include a results list comprising a list of web pages related to the terms of the search query, the order in which the web pages are presented in response to the search query being influenced by relevance feedback provided by multiple users prior to the search query, and wherein the relevance feedback is different from selection of a link to a web page in the results list; b) a search engine for querying a database and providing the web page search results in response to user queries; and c) a content manager for managing the supplemental information in response to user input, wherein the user input comprises the relevance feedback. 35. The system of claim 24 , wherein the order in which the web pages are to be initially presented in the results list in response to the search query initiated by the user is influenced by relevance feedback received in the context of a previous search query. | 0.599693 |
8,279,464 | 1 | 4 | 1. A method of processing a print job in a print shop, comprising: in a computer-readable memory, maintaining a semantic knowledge base comprising data in a web ontology form that describes a plurality of product intents, wherein each product intent includes at least one of parameter requirements and parameter restrictions for a finished print job; via a user interface, receiving a product description, wherein the product description includes a plurality of desired properties of a proposed print job; inferring, by a controller, using a semantic reasoning system, which of the product intents in the semantic knowledge base corresponds to the product description; and by the controller, automatically identifying a workflow in a print shop for the proposed print job based on the inferred product intent; and by a print engine, processing the proposed print job in the print shop according to the identified workflow; wherein: for each product intent that includes at least one parameter requirement, the inferring comprises determining that the product intent does not correspond to the product description if the product description does not include each included parameter requirement, and for each product intent that includes at least one parameter restriction, the inferring comprises determining that the product intent does not correspond to the product description if the product description includes a parameter that conflicts with any included parameter restriction. | 1. A method of processing a print job in a print shop, comprising: in a computer-readable memory, maintaining a semantic knowledge base comprising data in a web ontology form that describes a plurality of product intents, wherein each product intent includes at least one of parameter requirements and parameter restrictions for a finished print job; via a user interface, receiving a product description, wherein the product description includes a plurality of desired properties of a proposed print job; inferring, by a controller, using a semantic reasoning system, which of the product intents in the semantic knowledge base corresponds to the product description; and by the controller, automatically identifying a workflow in a print shop for the proposed print job based on the inferred product intent; and by a print engine, processing the proposed print job in the print shop according to the identified workflow; wherein: for each product intent that includes at least one parameter requirement, the inferring comprises determining that the product intent does not correspond to the product description if the product description does not include each included parameter requirement, and for each product intent that includes at least one parameter restriction, the inferring comprises determining that the product intent does not correspond to the product description if the product description includes a parameter that conflicts with any included parameter restriction. 4. The method of claim 1 wherein, before automatically identifying a workflow, the method further comprises: providing a user with the ability to override the inferred product intent with a user-selected product intent; and thereafter using the user-selected product intent as the inferred product intent. | 0.717069 |
8,435,038 | 30 | 51 | 30. A non-transitory computer-readable medium comprising program code for causing a computer to perform a method, comprising: receiving, for each learner, a video feed generated by a camera at the learner's location, the video feed at least partially depicting both the learner and a subject on which the learner is demonstrating the practical skill; simultaneously displaying two or more of the video feeds for the plurality of learners at a location of the teacher; receiving and displaying one or more private questions to the teacher from one or more learners, the private questions not being conveyed to the other learners unless authorized by the teacher; and allowing the teacher to select one of the learners for individualized instruction by selecting an indication of the corresponding displayed private question; wherein the private questions can be submitted by one or more selected learners via a text message, an audio or a video; wherein the teacher responds to the one or more selected learners by a text message, audio or video by establishing a private video and/or audio communication channel between the teacher's computer system and the selected learner; wherein the teacher broadcasts the text, audio or video messages to a group of the selected learners by allowing the communication channel to be non-private for the group of selected learners to receive the instruction provided by the teacher; wherein allowing the teacher to store the video feed, annotating the stored video feed and selectively transmit the annotated stored video feed to one or more selected learners. | 30. A non-transitory computer-readable medium comprising program code for causing a computer to perform a method, comprising: receiving, for each learner, a video feed generated by a camera at the learner's location, the video feed at least partially depicting both the learner and a subject on which the learner is demonstrating the practical skill; simultaneously displaying two or more of the video feeds for the plurality of learners at a location of the teacher; receiving and displaying one or more private questions to the teacher from one or more learners, the private questions not being conveyed to the other learners unless authorized by the teacher; and allowing the teacher to select one of the learners for individualized instruction by selecting an indication of the corresponding displayed private question; wherein the private questions can be submitted by one or more selected learners via a text message, an audio or a video; wherein the teacher responds to the one or more selected learners by a text message, audio or video by establishing a private video and/or audio communication channel between the teacher's computer system and the selected learner; wherein the teacher broadcasts the text, audio or video messages to a group of the selected learners by allowing the communication channel to be non-private for the group of selected learners to receive the instruction provided by the teacher; wherein allowing the teacher to store the video feed, annotating the stored video feed and selectively transmit the annotated stored video feed to one or more selected learners. 51. The non-transitory computer-readable medium of claim 30 , further comprising program code for causing a computer to perform a method comprising: allowing the teacher to store one or more of the video feeds. | 0.79 |
9,754,230 | 8 | 12 | 8. A computer program product for processing Business Intelligence (BI) reports, the computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, when executed by a processor of a computer system, configured to: use a database to generate information for consumption by a BI tool by: creating a description of data in one or more data tables, stored in the database, that identifies each column in each of the one or more data tables, wherein each column has multiple values; using the description of the data in the one or more data tables to create a new table, stored in the database, that includes a row for each value of the multiple values for each column in each of the one or more data tables and new columns for statistics about the data in the one or more data tables; generating BI meta information based on the description of the data in the one or more data tables and based on a schema and data of the new table that describes the columns for the statistics; generating a BI report specification that describes how a first BI report is to be rendered based on the schema and the data of the new table by describing a layout of data in the columns in each of the one or more data tables and in the columns for the statistics; deploying the BI meta information and the BI report specification to a BI server for use in generating the first BI report using the BI tool at the BI server; in response to a request for the first BI report, generating the first BI report dynamically with the BI tool at the BI server that dynamically invokes a stored procedure stored, in the database, with one or more parameters and that uses the BI meta information and the BI report specification to provide the statistics about the data in the one or more data tables; and displaying one or more graphs for the first BI report in a second screen; in response to another request for the first BI report after data in the one or more data tables has changed, using the new table to generate new BI meta information and a new BI report specification for use in generating a new BI report dynamically; and displaying one or more graphs for the new BI report in a second screen; in response to a request for a second BI report, using the new table to generate new BI meta information and another new BI report specification for use in generating a second BI report dynamically; and displaying one or more different graphs for the second BI report in a third screen. | 8. A computer program product for processing Business Intelligence (BI) reports, the computer program product comprising: a computer readable storage medium having computer readable program code embodied therewith, the computer readable program code, when executed by a processor of a computer system, configured to: use a database to generate information for consumption by a BI tool by: creating a description of data in one or more data tables, stored in the database, that identifies each column in each of the one or more data tables, wherein each column has multiple values; using the description of the data in the one or more data tables to create a new table, stored in the database, that includes a row for each value of the multiple values for each column in each of the one or more data tables and new columns for statistics about the data in the one or more data tables; generating BI meta information based on the description of the data in the one or more data tables and based on a schema and data of the new table that describes the columns for the statistics; generating a BI report specification that describes how a first BI report is to be rendered based on the schema and the data of the new table by describing a layout of data in the columns in each of the one or more data tables and in the columns for the statistics; deploying the BI meta information and the BI report specification to a BI server for use in generating the first BI report using the BI tool at the BI server; in response to a request for the first BI report, generating the first BI report dynamically with the BI tool at the BI server that dynamically invokes a stored procedure stored, in the database, with one or more parameters and that uses the BI meta information and the BI report specification to provide the statistics about the data in the one or more data tables; and displaying one or more graphs for the first BI report in a second screen; in response to another request for the first BI report after data in the one or more data tables has changed, using the new table to generate new BI meta information and a new BI report specification for use in generating a new BI report dynamically; and displaying one or more graphs for the new BI report in a second screen; in response to a request for a second BI report, using the new table to generate new BI meta information and another new BI report specification for use in generating a second BI report dynamically; and displaying one or more different graphs for the second BI report in a third screen. 12. The computer program product of claim 8 , wherein the computer readable program code is configured to: generate the stored procedure that is invoked to dynamically and repeatedly create the description of the data in the one or more data tables by modeling data in one or more data tables and to extract content of the description of the data in the one or more data tables into the new table. | 0.5 |
8,788,487 | 15 | 17 | 15. The computer program product of claim 12 , wherein: the feature manager is further configured to maintain, by the online system, a second incremental feature store; mark the first incremental feature store as inactive at a subsequent time point and updating features of the second incremental feature store responsive to user actions received by the online system after the subsequent time point; and the request processor module is further configured to responsive to receiving the request, receiving a third partial result from the second incremental feature store. | 15. The computer program product of claim 12 , wherein: the feature manager is further configured to maintain, by the online system, a second incremental feature store; mark the first incremental feature store as inactive at a subsequent time point and updating features of the second incremental feature store responsive to user actions received by the online system after the subsequent time point; and the request processor module is further configured to responsive to receiving the request, receiving a third partial result from the second incremental feature store. 17. The computer program product of claim 15 , wherein the weighted combination weighs the third partial result by a second decay factor. | 0.5 |
9,384,408 | 1 | 2 | 1. A method of obtaining contextual information for an image published on a digital medium, the method comprising: obtaining, by an image recognition engine, a set of image tags from an image published on a digital medium, wherein each of the image tags is an object identified in the image; obtaining, by a text recognition engine, a set of textual tags from text published proximate to the image, wherein each of the textual tags is a subject identified in the text; and matching, by a matching engine, the set of textual tags with the set of image tags based on object-type matching to obtain contextual information for objects identified in the image. | 1. A method of obtaining contextual information for an image published on a digital medium, the method comprising: obtaining, by an image recognition engine, a set of image tags from an image published on a digital medium, wherein each of the image tags is an object identified in the image; obtaining, by a text recognition engine, a set of textual tags from text published proximate to the image, wherein each of the textual tags is a subject identified in the text; and matching, by a matching engine, the set of textual tags with the set of image tags based on object-type matching to obtain contextual information for objects identified in the image. 2. The method of claim 1 , wherein the method further comprises identifying the image published on a digital medium. | 0.576642 |
8,495,073 | 1 | 2 | 1. A method operable on a computer for processing a financially related document to identify, classify and index first level concepts contained therein, the method comprising the steps of: (a) receiving said financially related document as input; (b) parsing the received financially related document to identify structural zones including: a chapter, a section, a page or a paragraph; logical zones including: a text, an image or a chart; and first level concepts within concept zones including key-words and financial entity symbols excluding said key-words, said parsing comprising: i) identifying a format type of said financially related document; ii) using the identified format type to identify structural identifiers within said document; iii) identifying structural zones using said identified structural identifiers; iv) processing digital data within each identified structural zones and evaluating the processed digital data to identify anticipated logical zones; v) parsing each of said identified logical zones to identify said first level concepts and concept zones, comprising: a) identifying first level concepts by counting a frequency of a predetermined number of keywords and their proximity to one another relative to the structural and logical zones within the document; b) identifying a concept zone as a region within a particular structural or logical zone that includes a higher frequency of a particular predetermined keyword relative to other keywords in said region; vi) parsing each of said identified logical zones using a hierarchical high-level concept parser to identify first level concepts within said concept zones; (c) creating a content description meta-document concurrently with parsing the received financially related document in step (b) by mapping the identified structural zones and logical zones into said meta-document to derive a fully normalized structural description of the content of the financially related document which is independent of the format of the original financially related document to identify the structural zones, logical zones, and concept zones identified within the financially related document; (d) processing the concept zones of the data description meta-document to identify sub-concepts contained therein by searching the concept zones for sub-concept keywords identified in a key-word directory as being subservient to a concept; and (e) using the data description meta-document to create one or more user indices of the identified first level concepts and sub-concepts identified with the financially related document. | 1. A method operable on a computer for processing a financially related document to identify, classify and index first level concepts contained therein, the method comprising the steps of: (a) receiving said financially related document as input; (b) parsing the received financially related document to identify structural zones including: a chapter, a section, a page or a paragraph; logical zones including: a text, an image or a chart; and first level concepts within concept zones including key-words and financial entity symbols excluding said key-words, said parsing comprising: i) identifying a format type of said financially related document; ii) using the identified format type to identify structural identifiers within said document; iii) identifying structural zones using said identified structural identifiers; iv) processing digital data within each identified structural zones and evaluating the processed digital data to identify anticipated logical zones; v) parsing each of said identified logical zones to identify said first level concepts and concept zones, comprising: a) identifying first level concepts by counting a frequency of a predetermined number of keywords and their proximity to one another relative to the structural and logical zones within the document; b) identifying a concept zone as a region within a particular structural or logical zone that includes a higher frequency of a particular predetermined keyword relative to other keywords in said region; vi) parsing each of said identified logical zones using a hierarchical high-level concept parser to identify first level concepts within said concept zones; (c) creating a content description meta-document concurrently with parsing the received financially related document in step (b) by mapping the identified structural zones and logical zones into said meta-document to derive a fully normalized structural description of the content of the financially related document which is independent of the format of the original financially related document to identify the structural zones, logical zones, and concept zones identified within the financially related document; (d) processing the concept zones of the data description meta-document to identify sub-concepts contained therein by searching the concept zones for sub-concept keywords identified in a key-word directory as being subservient to a concept; and (e) using the data description meta-document to create one or more user indices of the identified first level concepts and sub-concepts identified with the financially related document. 2. The method of claim 1 , wherein said financially related document is a source of content that is capable of being parsed and processed in accordance with the steps of claim 1 . | 0.863775 |
9,836,482 | 14 | 19 | 14. A system comprising: a computer readable medium having a program product stored thereon; and data processing apparatus programmed to execute the program product and perform operations comprising: obtaining images from first image results responsive to a first query, wherein each of a plurality of the obtained images is associated with a score and user behavior data wherein the user behavior data represents interactions of users with the obtained image when the obtained image was presented as a search result for the first query; selecting a plurality of the obtained images as a plurality of selected images, each image of the plurality of selected images having respective user behavior data that satisfies a threshold; associating each image of the plurality of the selected images with one or more annotations based on analysis of content of the selected image, the associating comprising: providing the plurality of the selected images to each of a plurality of different computer image annotators that each visually analyze an image to identify particular visual features in the images; receiving, from the plurality of computer image annotators, the annotations derived from visual analysis of the images to identify particular visual features in the images; and providing the first query and the annotations to a plurality of different machine learning system generated classifiers to associate the first query with one or more categories wherein a respective plurality of the annotations is provided as input to each of the classifiers, and wherein at least one of the categories specifies a presence of one of the particular visual features in an image; receiving a second query, wherein the second query is the same or similar to the first query; obtaining second images responsive to the second query, wherein each of the second images is associated with a respective first rank so that the second images are arranged according to a first order; modifying the respective first rank of one or more of the second images based on one or more of the categories associated with the first query so that the second images are re-ordered according to a second order. | 14. A system comprising: a computer readable medium having a program product stored thereon; and data processing apparatus programmed to execute the program product and perform operations comprising: obtaining images from first image results responsive to a first query, wherein each of a plurality of the obtained images is associated with a score and user behavior data wherein the user behavior data represents interactions of users with the obtained image when the obtained image was presented as a search result for the first query; selecting a plurality of the obtained images as a plurality of selected images, each image of the plurality of selected images having respective user behavior data that satisfies a threshold; associating each image of the plurality of the selected images with one or more annotations based on analysis of content of the selected image, the associating comprising: providing the plurality of the selected images to each of a plurality of different computer image annotators that each visually analyze an image to identify particular visual features in the images; receiving, from the plurality of computer image annotators, the annotations derived from visual analysis of the images to identify particular visual features in the images; and providing the first query and the annotations to a plurality of different machine learning system generated classifiers to associate the first query with one or more categories wherein a respective plurality of the annotations is provided as input to each of the classifiers, and wherein at least one of the categories specifies a presence of one of the particular visual features in an image; receiving a second query, wherein the second query is the same or similar to the first query; obtaining second images responsive to the second query, wherein each of the second images is associated with a respective first rank so that the second images are arranged according to a first order; modifying the respective first rank of one or more of the second images based on one or more of the categories associated with the first query so that the second images are re-ordered according to a second order. 19. The system of claim 14 , wherein the user behavior data is a count of times users selected the obtained image in search results for the first query. | 0.730496 |
8,333,792 | 18 | 20 | 18. An implantable spine stabilization device comprising: an elongated bone anchor having a distal end and a proximal end; a post having a distal end and a proximal end; a joint which secures the distal end of the post to the proximal end of the bone anchor such that the post may pivot relative to the bone anchor; a tubular extension of the bone anchor which extends over a distal portion of the post; and a compliant member disposed between the distal portion of the post and the tubular extension of the bone anchor whereby the compliant member biases the post into alignment with the bone anchor; and wherein said compliant member is a polymer disc having an outer diameter sized to fit with the tubular extension and a central aperture sized to receive the post. | 18. An implantable spine stabilization device comprising: an elongated bone anchor having a distal end and a proximal end; a post having a distal end and a proximal end; a joint which secures the distal end of the post to the proximal end of the bone anchor such that the post may pivot relative to the bone anchor; a tubular extension of the bone anchor which extends over a distal portion of the post; and a compliant member disposed between the distal portion of the post and the tubular extension of the bone anchor whereby the compliant member biases the post into alignment with the bone anchor; and wherein said compliant member is a polymer disc having an outer diameter sized to fit with the tubular extension and a central aperture sized to receive the post. 20. The spine stabilization device of claim 18 , wherein: the post is aligned with a longitudinal axis of the bone anchor when unloaded; and wherein application of a load on the proximal end of the post causes the post to pivot away from alignment with a longitudinal axis of the bone anchor thereby compressing the compliant member between the post and the tubular extension. | 0.5 |
8,566,095 | 7 | 8 | 7. The method of claim 1 , further comprising: identifying lesser order n-grams, the lesser order n-grams being derived from the first n-gram; and identifying a respective scaled probability of each of the lesser order n-grams identifying a word, the scaled probability for a particular lesser order n-gram composed of a particular number of atomic units identifying a word being determined by adjusting an initial probability of the lesser order n-gram identifying a word based at least in part on the particular number of atomic units. | 7. The method of claim 1 , further comprising: identifying lesser order n-grams, the lesser order n-grams being derived from the first n-gram; and identifying a respective scaled probability of each of the lesser order n-grams identifying a word, the scaled probability for a particular lesser order n-gram composed of a particular number of atomic units identifying a word being determined by adjusting an initial probability of the lesser order n-gram identifying a word based at least in part on the particular number of atomic units. 8. The method of claim 7 , wherein segmenting the plurality of tokens into one or more words comprises: when a product of the respective scaled probabilities of the lesser order n-grams derived from the first n-gram identifying a word exceeds the scaled probability of the first n-gram identifying a word, segmenting the first n-gram such that each of the lesser order n-grams identifies a respective word. | 0.5 |
7,610,227 | 1 | 9 | 1. A processor-based method for creating a set of work papers with cross-reference links to tax documents comprising: receiving, at a computer, a tax document; displaying, on a display screen, a page of the tax document; receiving, at the computer, a form type corresponding to the page of the tax document; receiving, at the computer, a form name corresponding to the page of the tax document; displaying, on the display screen, a plurality of categories related to the form type; providing, at the computer, a category selection from the plurality of categories; providing, at the computer, a link corresponding to the selected category; receiving, at the computer, a number or a description corresponding to the link; providing, at the computer, a tax return reconciliation template that includes a tax item description field and a tax page identifier field; providing, at the computer, a tax return reconciliation page by populating the tax item description field and the tax page identifier field with information from the tax document; and displaying, on the display screen, the tax return reconciliation page, wherein the tax page identifier field includes a clickable link to the page of the tax document containing a value corresponding to the tax item description field. | 1. A processor-based method for creating a set of work papers with cross-reference links to tax documents comprising: receiving, at a computer, a tax document; displaying, on a display screen, a page of the tax document; receiving, at the computer, a form type corresponding to the page of the tax document; receiving, at the computer, a form name corresponding to the page of the tax document; displaying, on the display screen, a plurality of categories related to the form type; providing, at the computer, a category selection from the plurality of categories; providing, at the computer, a link corresponding to the selected category; receiving, at the computer, a number or a description corresponding to the link; providing, at the computer, a tax return reconciliation template that includes a tax item description field and a tax page identifier field; providing, at the computer, a tax return reconciliation page by populating the tax item description field and the tax page identifier field with information from the tax document; and displaying, on the display screen, the tax return reconciliation page, wherein the tax page identifier field includes a clickable link to the page of the tax document containing a value corresponding to the tax item description field. 9. The method of claim 1 further comprising storing, on a storage device, link information related to the link. | 0.673529 |
9,275,117 | 7 | 8 | 7. A non-transitory computer readable medium storing software for performing dependency mining, the software comprising: executable code that determines a block data source access sequence; executable code that splits the block data source access sequence into a plurality of subsequences that represent a sequence of block accesses; executable code that determines an access pattern for each of the plurality of subsequences; executable code that constructs at least one search tree based on the access pattern of each of the plurality of subsequences; executable code that performs a search task using the at least one search tree; executable code that determines dependent blocks using the at least one search tree and based on block dependency criteria, wherein each access pattern is an activity vector that identifies occurrences of a particular block in the plurality of subsequences; executable code that outputs a dependency mining search result based on the search task and the block dependency criteria; and executable code that uses the dependency mining search result in a storage management process in connection with at least one of the determined dependent blocks, wherein the block dependency criteria includes a second block being dependent on a first block in response to a confidence factor being greater than a predetermined threshold, the confidence factor corresponding to a number of occurrences where both the first block and second block are active divided by a number of occurrences where the first block is active, wherein subsets of the plurality of subsequences are grouped into a plurality of subset groups according to weighting characteristics of the block dependency criteria for each access pattern of the plurality of subsequences. | 7. A non-transitory computer readable medium storing software for performing dependency mining, the software comprising: executable code that determines a block data source access sequence; executable code that splits the block data source access sequence into a plurality of subsequences that represent a sequence of block accesses; executable code that determines an access pattern for each of the plurality of subsequences; executable code that constructs at least one search tree based on the access pattern of each of the plurality of subsequences; executable code that performs a search task using the at least one search tree; executable code that determines dependent blocks using the at least one search tree and based on block dependency criteria, wherein each access pattern is an activity vector that identifies occurrences of a particular block in the plurality of subsequences; executable code that outputs a dependency mining search result based on the search task and the block dependency criteria; and executable code that uses the dependency mining search result in a storage management process in connection with at least one of the determined dependent blocks, wherein the block dependency criteria includes a second block being dependent on a first block in response to a confidence factor being greater than a predetermined threshold, the confidence factor corresponding to a number of occurrences where both the first block and second block are active divided by a number of occurrences where the first block is active, wherein subsets of the plurality of subsequences are grouped into a plurality of subset groups according to weighting characteristics of the block dependency criteria for each access pattern of the plurality of subsequences. 8. The non-transitory computer readable medium according to claim 7 , wherein each of the plurality of subset groups includes access patterns of blocks having a same weight. | 0.847173 |
8,280,601 | 1 | 7 | 1. A system for classifying a driver's driving style of a vehicle, said system comprising: a plurality of vehicle sensors providing sensor measurement signals; a maneuver identification processor responsive to the sensor signals from the plurality of vehicle sensors, said maneuver identification processor identifying different characteristic maneuvers of the vehicle and providing maneuver identifier signals identifying the characteristic maneuvers; and a style characterization processor responsive to the maneuver identifier signals and the sensor measurement signals, said style characterization processor including separate classifiers for each different type of maneuver, said classifiers being selected based on the maneuver identifier signal to classify driving style using sensor signals corresponding to a particular maneuver, each classifier providing a driver style classification signal that identifies the type of driver driving the vehicle for the particular maneuver, said style characterization processor further including a first combiner that receives and combines the style classification signals from each of the selected classifiers and provides a combined style classification signal for a single one of several different maneuvers. | 1. A system for classifying a driver's driving style of a vehicle, said system comprising: a plurality of vehicle sensors providing sensor measurement signals; a maneuver identification processor responsive to the sensor signals from the plurality of vehicle sensors, said maneuver identification processor identifying different characteristic maneuvers of the vehicle and providing maneuver identifier signals identifying the characteristic maneuvers; and a style characterization processor responsive to the maneuver identifier signals and the sensor measurement signals, said style characterization processor including separate classifiers for each different type of maneuver, said classifiers being selected based on the maneuver identifier signal to classify driving style using sensor signals corresponding to a particular maneuver, each classifier providing a driver style classification signal that identifies the type of driver driving the vehicle for the particular maneuver, said style characterization processor further including a first combiner that receives and combines the style classification signals from each of the selected classifiers and provides a combined style classification signal for a single one of several different maneuvers. 7. The system according to claim 1 further comprising a traffic and road condition recognition processor responsive to the sensor signals, said traffic and road condition recognition processor providing traffic and road condition signals to the style characterization processor. | 0.675234 |
9,299,035 | 12 | 15 | 12. A system for mining a process model, comprising: a mining module configured to a process model from a set of execution traces; a predictive model module configured to learn a predictive model to predict an outcome from the execution traces; and a model refinement module comprising a processor configured to determine whether the process model is too dense or too sparse, to modify the predictive model responsive to said determination, and to trigger the mining module to mine a refined process model from updated traces based on attributes present in the modified predictive model, wherein the model refinement module is configured to make the predictive model more specific if it is determined that the process model is too dense and to making the predictive model more general if it is determined that the process model is too sparse. | 12. A system for mining a process model, comprising: a mining module configured to a process model from a set of execution traces; a predictive model module configured to learn a predictive model to predict an outcome from the execution traces; and a model refinement module comprising a processor configured to determine whether the process model is too dense or too sparse, to modify the predictive model responsive to said determination, and to trigger the mining module to mine a refined process model from updated traces based on attributes present in the modified predictive model, wherein the model refinement module is configured to make the predictive model more specific if it is determined that the process model is too dense and to making the predictive model more general if it is determined that the process model is too sparse. 15. The system of claim 12 , wherein the predictive model is represented as a binary decision tree. | 0.856936 |
8,555,180 | 18 | 19 | 18. A peripheral device, comprising: a memory storing instructions comprising steps for: connecting to a portable media player; and transmitting to the portable media player a user interface (UI) document defining layout and functionality of a UI for the peripheral device, wherein the UI document identifies a widget and an update rate for the widget, and a UI presentation program executed by a microprocessor of the portable media player generates and displays the UI based on the UI document. | 18. A peripheral device, comprising: a memory storing instructions comprising steps for: connecting to a portable media player; and transmitting to the portable media player a user interface (UI) document defining layout and functionality of a UI for the peripheral device, wherein the UI document identifies a widget and an update rate for the widget, and a UI presentation program executed by a microprocessor of the portable media player generates and displays the UI based on the UI document. 19. The peripheral device of claim 18 , wherein the steps of the instructions further comprises: transmitting an output to the portable media player, wherein the UI presentation program updates the UI with the output. | 0.547917 |
6,016,486 | 1 | 5 | 1. A method for creating a presentation, comprising the steps of: (a) receiving information indicative of a goal; (b) integrating information that motivates accomplishment of the goal for use in the presentation; (c) managing information flow utilizing a linked list; and (d) evaluating progress toward the goal and providing feedback that further motivates accomplishment of the goal. | 1. A method for creating a presentation, comprising the steps of: (a) receiving information indicative of a goal; (b) integrating information that motivates accomplishment of the goal for use in the presentation; (c) managing information flow utilizing a linked list; and (d) evaluating progress toward the goal and providing feedback that further motivates accomplishment of the goal. 5. A method for creating a presentation as recited in claim 1, including the step of allowing controlling the presentation based on the progress of a student. | 0.610837 |
8,380,731 | 4 | 5 | 4. The computer-based searching method according to claim 3 wherein determining a set of semantically similar words comprises creating at least one sub rule where each sub rule is a disjunction of the set of semantically similar words. | 4. The computer-based searching method according to claim 3 wherein determining a set of semantically similar words comprises creating at least one sub rule where each sub rule is a disjunction of the set of semantically similar words. 5. The computer-based searching method according to claim 4 wherein calculating a degree of membership comprises combining at least one rule and one sub rule. | 0.5 |
8,930,178 | 11 | 12 | 11. The one or more non-transitory memory devices of claim 10 , wherein the computer instructions are further configured to perform the steps of comparing the at least one semantic concept and the additional concepts to a list of known relevant concepts to generate a list of identified relevant concepts; and providing an output based on at least one of a number and a significance of the identified relevant concepts. | 11. The one or more non-transitory memory devices of claim 10 , wherein the computer instructions are further configured to perform the steps of comparing the at least one semantic concept and the additional concepts to a list of known relevant concepts to generate a list of identified relevant concepts; and providing an output based on at least one of a number and a significance of the identified relevant concepts. 12. The one or more non-transitory memory devices of claim 11 , wherein the output pertains to a probability of a particular occurrence. | 0.5 |
7,912,860 | 9 | 11 | 9. One or more computer-readable storage media devices having computer-readable instructions thereon which, when executed, implement a method comprising: providing an application that is not primarily an instant messaging application or email application; providing, through the application, one or more objects having at least one strongly typed tag and at least one changeable property, the at least one changeable property being a name, wherein different names associated with a same unique ID are automatically resolved to the same unique ID independent of a user resolving the different names, wherein strongly typed tags uniquely associate tags with an individual or group of people; presenting, through the application, a navigation tree comprising a tag node that is expandable to expose a list of previously created tags which are usable to tag the one or more objects; and using one or more strongly typed tags from within the application to provide at least an instant messaging functionality or an email functionality for the user, wherein provision of the instant messaging functionality or the email functionality is accomplished by presenting a user interface element that gives the user a choice to select between functionalities including the instant messaging functionality or the email functionality. | 9. One or more computer-readable storage media devices having computer-readable instructions thereon which, when executed, implement a method comprising: providing an application that is not primarily an instant messaging application or email application; providing, through the application, one or more objects having at least one strongly typed tag and at least one changeable property, the at least one changeable property being a name, wherein different names associated with a same unique ID are automatically resolved to the same unique ID independent of a user resolving the different names, wherein strongly typed tags uniquely associate tags with an individual or group of people; presenting, through the application, a navigation tree comprising a tag node that is expandable to expose a list of previously created tags which are usable to tag the one or more objects; and using one or more strongly typed tags from within the application to provide at least an instant messaging functionality or an email functionality for the user, wherein provision of the instant messaging functionality or the email functionality is accomplished by presenting a user interface element that gives the user a choice to select between functionalities including the instant messaging functionality or the email functionality. 11. The one or more computer-readable storage media devices of claim 9 , wherein the act of using is performed by providing the user with an option to initiate an instant messaging session. | 0.534483 |
9,385,972 | 10 | 14 | 10. An apparatus for generating a suggested personalized reaction, the apparatus comprising: a first module for determining interaction items associated with a first user of an electronic communication system, for determining interaction items associated with at least one other user, the first module coupled to receive interaction items from the electronic communication system, the interaction items associated with the first user including an online user post and the electronic communication system including an online service; a suggestion module for generating a suggested personalized reaction using interaction items associated with the first user and interaction items associated with at least one other user using a decision tree based on the content of the interaction items associated with the at least one other user, the suggestion module coupled to the first module to receive determined interaction items, the suggestion module configured to process user input associated with the suggested personalized reaction to update the decision tree; and a user interface module for presenting the suggested personalized reaction and related information and for receiving input from the first user, the user interface module coupled to receive the suggested personalized reaction from the suggestion module, the user interface module configured to receive input from the first user. | 10. An apparatus for generating a suggested personalized reaction, the apparatus comprising: a first module for determining interaction items associated with a first user of an electronic communication system, for determining interaction items associated with at least one other user, the first module coupled to receive interaction items from the electronic communication system, the interaction items associated with the first user including an online user post and the electronic communication system including an online service; a suggestion module for generating a suggested personalized reaction using interaction items associated with the first user and interaction items associated with at least one other user using a decision tree based on the content of the interaction items associated with the at least one other user, the suggestion module coupled to the first module to receive determined interaction items, the suggestion module configured to process user input associated with the suggested personalized reaction to update the decision tree; and a user interface module for presenting the suggested personalized reaction and related information and for receiving input from the first user, the user interface module coupled to receive the suggested personalized reaction from the suggestion module, the user interface module configured to receive input from the first user. 14. The apparatus of claim 10 wherein the first module is adapted to retrieve any information in the electronic communication system accessible to the first user whether the information is private or public. | 0.681538 |
8,078,463 | 1 | 3 | 1. A computerized method for spotting an at least one call interaction out of a multiplicity of call interactions, in which an at least one target speaker participates, the method comprising: capturing at least one target speaker speech sample of the at least one target speaker by a speech capture device; generating by a computerized engine a multiplicity of speaker models based on a multiplicity of speaker speech samples from the at least one call interaction; matching by a computerized server the at least one target speaker speech sample with speaker models the multiplicity of speaker models to determine a target speaker model; determining a score for each call interaction of the multiplicity of call interactions according to a comparison between the target speaker model and the multiplicity of speaker models; and based on scores that are higher than a predetermined threshold, determining call interactions, of the multiplicity of call interactions, in which the at least one target speaker participates. | 1. A computerized method for spotting an at least one call interaction out of a multiplicity of call interactions, in which an at least one target speaker participates, the method comprising: capturing at least one target speaker speech sample of the at least one target speaker by a speech capture device; generating by a computerized engine a multiplicity of speaker models based on a multiplicity of speaker speech samples from the at least one call interaction; matching by a computerized server the at least one target speaker speech sample with speaker models the multiplicity of speaker models to determine a target speaker model; determining a score for each call interaction of the multiplicity of call interactions according to a comparison between the target speaker model and the multiplicity of speaker models; and based on scores that are higher than a predetermined threshold, determining call interactions, of the multiplicity of call interactions, in which the at least one target speaker participates. 3. The method of claim 1 wherein the step of generating further comprises pre-processing the at least one target speaker speech sample; and extracting an at least one feature vector from the at least one speaker speech sample. | 0.727711 |
9,852,728 | 15 | 20 | 15. A text to speech system comprising: one or more processors configured to identify a word or phrase as a named entity, the one or more processors further configured to identify a language of origin associated with the named entity and transliterate the named entity to a script associated with the language of origin, if the TTS system is operating in the language of origin, the one or more processors further configured to pass the transliterated script to the TTS system, and if the TTS system is not operating in the language of origin, the one or more processors further configured to generate a phoneme sequence in the language of origin using a grapheme to phoneme (G2P) converter. | 15. A text to speech system comprising: one or more processors configured to identify a word or phrase as a named entity, the one or more processors further configured to identify a language of origin associated with the named entity and transliterate the named entity to a script associated with the language of origin, if the TTS system is operating in the language of origin, the one or more processors further configured to pass the transliterated script to the TTS system, and if the TTS system is not operating in the language of origin, the one or more processors further configured to generate a phoneme sequence in the language of origin using a grapheme to phoneme (G2P) converter. 20. The system of claim 15 , further comprising: augmenting a text to speech dictionary based upon, at least in part, the phoneme sequence. | 0.654229 |
8,832,804 | 14 | 15 | 14. A computer implemented method for password pre-verification comprising: (a) executing a translation module on a processor that causes the processor to translate user input, in the form of a character string that can represent a password, to obtain a symbolic representation of the user input; (b) executing an output module on the processor that causes the processor to receive the symbolic representation from the translation module and, based on the user input, provide output to the user in the form of visual, audio or haptic cues, wherein the visual, audio or haptic cues alert a user as to whether the input character string is correctly or incorrectly entered based upon a variance or similarity of the cue as compared to a previous cue provided to the user during a previous attempt to enter the input character, without providing an objective indicator, that allows an unauthorized user to discover the password, as to whether or not the password has been entered correctly if the user is unfamiliar with the variance, and wherein the output does not change until after a predetermined number of characters has been input and thereafter changes in a distinguishable way with the entry of each successive character that is input. | 14. A computer implemented method for password pre-verification comprising: (a) executing a translation module on a processor that causes the processor to translate user input, in the form of a character string that can represent a password, to obtain a symbolic representation of the user input; (b) executing an output module on the processor that causes the processor to receive the symbolic representation from the translation module and, based on the user input, provide output to the user in the form of visual, audio or haptic cues, wherein the visual, audio or haptic cues alert a user as to whether the input character string is correctly or incorrectly entered based upon a variance or similarity of the cue as compared to a previous cue provided to the user during a previous attempt to enter the input character, without providing an objective indicator, that allows an unauthorized user to discover the password, as to whether or not the password has been entered correctly if the user is unfamiliar with the variance, and wherein the output does not change until after a predetermined number of characters has been input and thereafter changes in a distinguishable way with the entry of each successive character that is input. 15. The method of claim 14 , further comprising using a hash function to translate user input into a symbolic representation. | 0.75 |
8,886,587 | 11 | 12 | 11. A system comprising: a user device; and one or more computers operable to interact with the user device, the one or more computers being further operable to perform operations including: providing data that cause presentation of a model development user interface; receiving first model rule data through the user interface, the first model rule data specifying a first model rule that specifies a first characteristic of a violating resource and a threshold score for the first characteristic, wherein the first model rule data specifies a phrase and a threshold number of instances of the phrase that, when included in resource, are indicative of the resource being a violating resource; receiving additional model rule data through the user interface, the additional model rule data specifying one or more additional model rules, each of the additional model rules specifying an additional characteristic of the violating resource and an additional threshold for the additional characteristic; receiving, for each of the additional model rules, relationship data through the user interface, the relationship data specifying sets of the additional model rules that violating resources satisfy; and providing data that cause a hierarchical presentation of the first model rule and the additional model rules, the first model rule being presented at a highest hierarchical position and each of the additional model rules being presented at a descendent hierarchical position based on the relationship data, the data further causing presentation of a relationship indicator for each of the additional model rules, the relationship indicator specifying the sets of additional model rules that must be satisfied to classify a resource as a violating resource. | 11. A system comprising: a user device; and one or more computers operable to interact with the user device, the one or more computers being further operable to perform operations including: providing data that cause presentation of a model development user interface; receiving first model rule data through the user interface, the first model rule data specifying a first model rule that specifies a first characteristic of a violating resource and a threshold score for the first characteristic, wherein the first model rule data specifies a phrase and a threshold number of instances of the phrase that, when included in resource, are indicative of the resource being a violating resource; receiving additional model rule data through the user interface, the additional model rule data specifying one or more additional model rules, each of the additional model rules specifying an additional characteristic of the violating resource and an additional threshold for the additional characteristic; receiving, for each of the additional model rules, relationship data through the user interface, the relationship data specifying sets of the additional model rules that violating resources satisfy; and providing data that cause a hierarchical presentation of the first model rule and the additional model rules, the first model rule being presented at a highest hierarchical position and each of the additional model rules being presented at a descendent hierarchical position based on the relationship data, the data further causing presentation of a relationship indicator for each of the additional model rules, the relationship indicator specifying the sets of additional model rules that must be satisfied to classify a resource as a violating resource. 12. The system of claim 11 , wherein the one or more computers are further operable to perform operations including: receiving additional model rule data that specify one or more rule subsets that each include two or more different model rules; receiving, for each rule subset, relationship data specifying a set of the two or more different model rules in the rule subset that are satisfied by the violating resource; and providing data that cause presentation of each rule subset and a relationship indicator for the model rules in the rule subset, the relationship indicator specifying combinations of the model rules in the rule subset that must be satisfied to classify a resource as a violating resource. | 0.5 |
8,429,161 | 1 | 3 | 1. A computer implemented method, comprising: receiving a query from a user device, the query being one or more query terms; identifying content items that are responsive to the query as unfiltered content items; determining that the query includes a filtering term, the determining comprising: comparing the query terms to a list of filtering terms; and determining, in response to a match of one or more of the query terms to at least one of the filtering terms, that the query includes a filtering term; and in response to the determination that the query includes the filtering term: identifying filtered content items based on the query and the filtering term; providing search results for the filtered content items to the user device, each search result referencing a filtered content item; providing the user device access to a verification service that provides access approval or access denial for search results for the unfiltered content items that are responsive to the query, determining whether access approval or access denial is received from the verification service in response to user identification data provided to the verification service; if access approval is received from the verification service, then providing search results for the unfiltered content items to the user device; and if access denial is received from the verification service, then precluding the provisioning of search results for the unfiltered content items to the user device. | 1. A computer implemented method, comprising: receiving a query from a user device, the query being one or more query terms; identifying content items that are responsive to the query as unfiltered content items; determining that the query includes a filtering term, the determining comprising: comparing the query terms to a list of filtering terms; and determining, in response to a match of one or more of the query terms to at least one of the filtering terms, that the query includes a filtering term; and in response to the determination that the query includes the filtering term: identifying filtered content items based on the query and the filtering term; providing search results for the filtered content items to the user device, each search result referencing a filtered content item; providing the user device access to a verification service that provides access approval or access denial for search results for the unfiltered content items that are responsive to the query, determining whether access approval or access denial is received from the verification service in response to user identification data provided to the verification service; if access approval is received from the verification service, then providing search results for the unfiltered content items to the user device; and if access denial is received from the verification service, then precluding the provisioning of search results for the unfiltered content items to the user device. 3. The method of claim 1 , wherein providing the user device access to a verification service comprises providing a user identification data input interface to the user device. | 0.839122 |
8,688,749 | 1 | 7 | 1. A method comprising: modeling for implementing object-centric data models; obtaining, at an importing site, an exporting site ontology and a set of one or more database changes associated with an exporting site; wherein the exporting site ontology defines one or more first object types and one or more first link types relating two or more objects of the one or more first object types in a first object-centric data model; obtaining an ontology map comprising at least one object rule for mapping the one or more first object types of the first object-centric data model one or more second object types in a second object-centric data model defined by an importing site ontology and at least one link rule for mapping the one or more first link types of the first object-centric data model to one or more second link types in the second object-centric data model; incorporating the set of one or more database changes into a database at the importing site based on the at least one object rule and the at least one link rule, wherein at least one link represented in the set of one or more database changes is reversed based on the at least one link rule; wherein object data for at least one object is represented by different object types in the first object-centric data model and the second object-centric data model; wherein the method is performed by one or more computing devices. | 1. A method comprising: modeling for implementing object-centric data models; obtaining, at an importing site, an exporting site ontology and a set of one or more database changes associated with an exporting site; wherein the exporting site ontology defines one or more first object types and one or more first link types relating two or more objects of the one or more first object types in a first object-centric data model; obtaining an ontology map comprising at least one object rule for mapping the one or more first object types of the first object-centric data model one or more second object types in a second object-centric data model defined by an importing site ontology and at least one link rule for mapping the one or more first link types of the first object-centric data model to one or more second link types in the second object-centric data model; incorporating the set of one or more database changes into a database at the importing site based on the at least one object rule and the at least one link rule, wherein at least one link represented in the set of one or more database changes is reversed based on the at least one link rule; wherein object data for at least one object is represented by different object types in the first object-centric data model and the second object-centric data model; wherein the method is performed by one or more computing devices. 7. The method of claim 1 , wherein the ontology map specifies a list of data types to be dropped when exporting database changes from the exporting site. | 0.894918 |
9,652,478 | 1 | 2 | 1. A method for generating a schema for data asset information, the method comprising: accessing complex type information corresponding to a logical relational data model that defines an organization of the data asset information, the logical relational data model including a parent entity and child entities corresponding to the parent entity; treating the complex type information to produce scrubbed complex type information, said treating of the complex type information including removing at least one foreign key from at least one of the child entities; translating the scrubbed complex type information to produce a hierarchical data model corresponding to the logical relational data model, the hierarchical data model including a plurality of containers respectively corresponding to the child entities of the logical relational data model, the treating and translating being carried out such that the at least one foreign key removed from the at least one child entity is omitted from a first level container in the hierarchical data model and is present in a second level container in the hierarchical data model, the first level container paralleling the child entity from which the foreign key is removed, the second level container being at a higher level in the hierarchical data model than that of the first level container; and generating a schema for the data asset information based upon the hierarchical data model. | 1. A method for generating a schema for data asset information, the method comprising: accessing complex type information corresponding to a logical relational data model that defines an organization of the data asset information, the logical relational data model including a parent entity and child entities corresponding to the parent entity; treating the complex type information to produce scrubbed complex type information, said treating of the complex type information including removing at least one foreign key from at least one of the child entities; translating the scrubbed complex type information to produce a hierarchical data model corresponding to the logical relational data model, the hierarchical data model including a plurality of containers respectively corresponding to the child entities of the logical relational data model, the treating and translating being carried out such that the at least one foreign key removed from the at least one child entity is omitted from a first level container in the hierarchical data model and is present in a second level container in the hierarchical data model, the first level container paralleling the child entity from which the foreign key is removed, the second level container being at a higher level in the hierarchical data model than that of the first level container; and generating a schema for the data asset information based upon the hierarchical data model. 2. The method of claim 1 , wherein said treating of the complex type information comprises replacing data types in the complex type information corresponding to the logical relational data model. | 0.5 |
9,195,646 | 23 | 25 | 23. The non-transitory computer-readable storage medium according to claim 22 , wherein in Step (b), the training data candidates assigned a specified label in the cluster containing the specified label at or above a predetermined percentage are used as the training data having the specified label. | 23. The non-transitory computer-readable storage medium according to claim 22 , wherein in Step (b), the training data candidates assigned a specified label in the cluster containing the specified label at or above a predetermined percentage are used as the training data having the specified label. 25. The non-transitory computer-readable storage medium according to claim 23 , wherein in Step (b), the degree of cluster membership is obtained for training data candidates that are not assigned the specified label in the cluster containing the specified label at or above a predetermined percentage, and the training data candidates for which the obtained degree is not lower than a threshold value are used as training data, while the training data candidates for which the obtained degree is less than the threshold value are deleted from the entire set of training data candidates. | 0.5 |
8,903,858 | 2 | 3 | 2. The computer implemented method as claimed in claim 1 , wherein the providing further comprises ordering the plurality of keyword results based on relevance with the one or more textual characters. | 2. The computer implemented method as claimed in claim 1 , wherein the providing further comprises ordering the plurality of keyword results based on relevance with the one or more textual characters. 3. The computer implemented method as claimed in claim 2 , wherein the relevance is determined based on an ordering criteria, wherein the ordering criteria include one of popularity of terms, relative importance of terms, location of a user, current time, terms from past search queries, and past terms selected by the user. | 0.5 |
8,024,652 | 1 | 6 | 1. A method, comprising: creating a note with a first application program; generating a context reference for a document for a second application program, the context reference comprising context information useable to recreate a user context for the document; displaying the context reference; and associating the context reference with the note. | 1. A method, comprising: creating a note with a first application program; generating a context reference for a document for a second application program, the context reference comprising context information useable to recreate a user context for the document; displaying the context reference; and associating the context reference with the note. 6. The method of claim 1 , comprising generating a context reference view to display the context reference. | 0.643333 |
8,554,558 | 1 | 4 | 1. An automated speech processing method comprising: using a speech-to-text (STT) engine for receiving an audio input and for converting the audio input to text data in a source language; using a machine translation (MT) engine for receiving the text data from the STT engine and for translating the text data to text data in a target language; using a caption engine for rendering the text data in the target language on a display device, including receiving metadata from the STT engine and the MT engine identifying defined characteristics of specific portions of the rendered text data in the target language including a defined confidence value representing the accuracy of the rendered text data based on both the accuracy of the converting the audio input to text data in the source language and the accuracy of translating the text data including interactions between the STT engine and MT engine comprising alignment information, and determining specific portions of the text data in the target language to which said defined characteristics, identified by the metadata from the STT engine, apply; and applying different visualization schemes based on color, font, size, underlining and italicization to different parts of the rendered text data based on the defined characteristics of the metadata. | 1. An automated speech processing method comprising: using a speech-to-text (STT) engine for receiving an audio input and for converting the audio input to text data in a source language; using a machine translation (MT) engine for receiving the text data from the STT engine and for translating the text data to text data in a target language; using a caption engine for rendering the text data in the target language on a display device, including receiving metadata from the STT engine and the MT engine identifying defined characteristics of specific portions of the rendered text data in the target language including a defined confidence value representing the accuracy of the rendered text data based on both the accuracy of the converting the audio input to text data in the source language and the accuracy of translating the text data including interactions between the STT engine and MT engine comprising alignment information, and determining specific portions of the text data in the target language to which said defined characteristics, identified by the metadata from the STT engine, apply; and applying different visualization schemes based on color, font, size, underlining and italicization to different parts of the rendered text data based on the defined characteristics of the metadata. 4. The method according to claim 1 , wherein: the applying different visualization schemes includes applying a selected one of the visualization schemes to a selected part of the rendered text data that corresponds to one or more of the words in the source language that have a STT confidence value above a given threshold value. | 0.5 |
9,813,879 | 23 | 24 | 23. The mobile face-to-face interaction monitoring method according to claim 20 , wherein: the creating the volume topography based on the sound signals is performed during a training period; and the determining the turn by using the volume topography comprises determining current turn by matching current sound signals with the volume topography, after the training period. | 23. The mobile face-to-face interaction monitoring method according to claim 20 , wherein: the creating the volume topography based on the sound signals is performed during a training period; and the determining the turn by using the volume topography comprises determining current turn by matching current sound signals with the volume topography, after the training period. 24. The mobile face-to-face interaction monitoring method according to claim 23 , wherein the creating the volume topography based on the sound signals is performed by using a feature vector P(t), wherein the feature vector P(t) is defined as P(t)=(p(t,1), p(t,2), . . . , p(t,np)), where p(t, i) is an average of a square of the sound signals in each mobile device i of the mobile devices at a given time t, and where np is a quantity of the mobile devices in the conversation group. | 0.5 |
9,049,314 | 3 | 4 | 3. A method as recited in claim 1 , wherein the regulated requirement that precludes release of the first business document to the requestor based on the content of the first business document is at least one of (i) a federal regulation; (ii) a state regulation; (iii) a local regulation; (iv) an internal regulation; (v) a regulated retention time period; (vi) a professional requirement; and (vii) an ethical requirement. | 3. A method as recited in claim 1 , wherein the regulated requirement that precludes release of the first business document to the requestor based on the content of the first business document is at least one of (i) a federal regulation; (ii) a state regulation; (iii) a local regulation; (iv) an internal regulation; (v) a regulated retention time period; (vi) a professional requirement; and (vii) an ethical requirement. 4. A method as recited in claim 3 , further comprising comparing, by the computing system, a pre-established retention time deadline of the holder of the first business document with a retention time deadline of whom the content of the first business document pertains; and releasing the first business document to the requestor if the content of the first business document is not subject to the requirement and the retention time deadline of whom the content of the first business document pertains has not expired. | 0.5 |
9,740,731 | 13 | 16 | 13. A method of automatically sorting disaster and/or accident related news stories by their temporal characteristics using a computing system comprising: a) identifying a first news vent involving a disaster and/or accident related event; wherein said first news event is associated by the computing system with a plurality of corresponding event status states defined for a progress template for such first news event; wherein said event status states are associated by the computing system with content for the first news event which is distinctive to different temporal periods within said progress template; b) analyzing a first electronic document describing said first event with the computing system to identify first content snippets determinative of a first status state of said first news event relative to said event status states defined for said progress template; c) analyzing a second electronic document with second content snippets describing a second status state for said first news event with the computing system; and d) determining which of said first and second electronic documents contains content describing a more current status state of said first event by comparing said first status state to said second status state and generating an output with the computing system indicating which of said electronic documents describes the more current status state; wherein changes in corresponding content snippets relating to one of least property damage, loss of lives, injuries survivors and/or an absolute time of such first event are tracked between documents and used by the computing system to derive a relative temporal relationship between said first electronic document and second electronic document. | 13. A method of automatically sorting disaster and/or accident related news stories by their temporal characteristics using a computing system comprising: a) identifying a first news vent involving a disaster and/or accident related event; wherein said first news event is associated by the computing system with a plurality of corresponding event status states defined for a progress template for such first news event; wherein said event status states are associated by the computing system with content for the first news event which is distinctive to different temporal periods within said progress template; b) analyzing a first electronic document describing said first event with the computing system to identify first content snippets determinative of a first status state of said first news event relative to said event status states defined for said progress template; c) analyzing a second electronic document with second content snippets describing a second status state for said first news event with the computing system; and d) determining which of said first and second electronic documents contains content describing a more current status state of said first event by comparing said first status state to said second status state and generating an output with the computing system indicating which of said electronic documents describes the more current status state; wherein changes in corresponding content snippets relating to one of least property damage, loss of lives, injuries survivors and/or an absolute time of such first event are tracked between documents and used by the computing system to derive a relative temporal relationship between said first electronic document and second electronic document. 16. The method of claim 13 wherein said steps are implemented as one or more computer software routines stored in a tangible media and adapted to cause one or more computing systems to perform the operations recited therein. | 0.588235 |
9,420,355 | 11 | 12 | 11. A computer program product comprising a non-transitory computer readable storage medium having instructions stored thereon, the instructions when executed by a processor cause the processor to: receive social object data including a plurality of metadata tags; receive electronic program guide information including a plurality of television program identifiers; generate a graph data structure comprising a plurality of nodes and plurality of edges, each node representing a metadata tag of the plurality of metadata tags or a television program identifier of the plurality of television program identifiers, each edge connecting two nodes, each edge including a timestamp based on the social object data; receive information about user-selected television shows; query the graph data structure with a selected metadata tag of the plurality of metadata tags corresponding to a social object of the social object data; receive a set of television program identifiers associated with the selected metadata tag by traversing, with a timestamp within a predetermined timeframe, at least a portion of the plurality of edges of the graph data structure; select a subset of the set of television program identifiers most closely related to the selected metadata tag by comparing the set of television program identifiers with the information about user-selected television shows; and responsive to one of the television program identifiers of the subset corresponding to at least one of the user-selected television shows, select the social object for removal from the social object data. | 11. A computer program product comprising a non-transitory computer readable storage medium having instructions stored thereon, the instructions when executed by a processor cause the processor to: receive social object data including a plurality of metadata tags; receive electronic program guide information including a plurality of television program identifiers; generate a graph data structure comprising a plurality of nodes and plurality of edges, each node representing a metadata tag of the plurality of metadata tags or a television program identifier of the plurality of television program identifiers, each edge connecting two nodes, each edge including a timestamp based on the social object data; receive information about user-selected television shows; query the graph data structure with a selected metadata tag of the plurality of metadata tags corresponding to a social object of the social object data; receive a set of television program identifiers associated with the selected metadata tag by traversing, with a timestamp within a predetermined timeframe, at least a portion of the plurality of edges of the graph data structure; select a subset of the set of television program identifiers most closely related to the selected metadata tag by comparing the set of television program identifiers with the information about user-selected television shows; and responsive to one of the television program identifiers of the subset corresponding to at least one of the user-selected television shows, select the social object for removal from the social object data. 12. The computer program product of claim 11 , wherein the instructions to generate a graph data structure further comprise instructions to generate edges of the plurality of edges based on data from the electronic program guide information indicating associations between metadata tags of the plurality of metadata tags and television program identifiers of the plurality of television program identifiers. | 0.558568 |
6,035,061 | 19 | 22 | 19. A title extracting apparatus for recognizing and extracting a required partial region from a document image of a document that has been converted into image data, comprising: character region generating means for generating character regions, including black pixel connected regions composed of connected black pixels of the document image; character string region generating means for unifying one or more character regions generated by said character region generating means, and for generating character string regions including one or more character regions; and title extracting means for extracting a particular character string region of the character string regions, according to attributes of a plurality of character string regions generated by said character string region generating means, as a title region, wherein said title extracting means is adapted for extracting an underline attribute or a frame attribute as an attribute of the character string regions, assigning a number of points to each of the character string regions corresponding to the extracted underline attribute or frame attribute, a position of each character string regions, and a relative position relation between the character string regions, and treating a character string region having the greatest number of assigned points as the particular character string region. | 19. A title extracting apparatus for recognizing and extracting a required partial region from a document image of a document that has been converted into image data, comprising: character region generating means for generating character regions, including black pixel connected regions composed of connected black pixels of the document image; character string region generating means for unifying one or more character regions generated by said character region generating means, and for generating character string regions including one or more character regions; and title extracting means for extracting a particular character string region of the character string regions, according to attributes of a plurality of character string regions generated by said character string region generating means, as a title region, wherein said title extracting means is adapted for extracting an underline attribute or a frame attribute as an attribute of the character string regions, assigning a number of points to each of the character string regions corresponding to the extracted underline attribute or frame attribute, a position of each character string regions, and a relative position relation between the character string regions, and treating a character string region having the greatest number of assigned points as the particular character string region. 22. The title extracting apparatus as set forth in claim 19, wherein said title extracting means is adapted for assigning predetermined points to a character string region that is disposed between and spaced apart from an upper and a lower character string region. | 0.7 |
8,407,211 | 8 | 12 | 8. A method performed by data processing apparatus, the method comprising: one or more computers configured to perform operations comprising: storing a respective plurality of category-location relevance scores for each location of a plurality of geographic locations, wherein each category-location relevance score for each location estimates a relevance of a respective category to the location, and wherein a category-location relevance score is based on a plurality of category-entity-location relevance scores for a plurality of entities associated with the category at the location, wherein storing a category-location relevance score for a location comprises storing a plurality of Taylor coefficients for a function at the location, wherein an evaluation of the function for a location provides a category-location relevance score for the category, and wherein an evaluation of the function at a location is determined by evaluating a sub-function for each of the plurality of entities, and wherein an evaluation of the sub-function for an entity provides a category-entity-location relevance score for the entity and the location; determining a first category-location relevance score for a first geographic location that is not one of the plurality of geographic locations, including: selecting a second geographic location in the plurality of geographic locations, and calculating the first category-location relevance score based on a second category-location relevance score for the second geographic location and a physical distance between the first geographic location and the second geographic location; and selecting an item from a plurality of candidate items using the first category location relevance score, wherein each candidate item is associated with a respective category, and wherein selecting the item comprises: ranking the plurality of candidate items using the first category location relevance score, and selecting a highest ranked candidate item. | 8. A method performed by data processing apparatus, the method comprising: one or more computers configured to perform operations comprising: storing a respective plurality of category-location relevance scores for each location of a plurality of geographic locations, wherein each category-location relevance score for each location estimates a relevance of a respective category to the location, and wherein a category-location relevance score is based on a plurality of category-entity-location relevance scores for a plurality of entities associated with the category at the location, wherein storing a category-location relevance score for a location comprises storing a plurality of Taylor coefficients for a function at the location, wherein an evaluation of the function for a location provides a category-location relevance score for the category, and wherein an evaluation of the function at a location is determined by evaluating a sub-function for each of the plurality of entities, and wherein an evaluation of the sub-function for an entity provides a category-entity-location relevance score for the entity and the location; determining a first category-location relevance score for a first geographic location that is not one of the plurality of geographic locations, including: selecting a second geographic location in the plurality of geographic locations, and calculating the first category-location relevance score based on a second category-location relevance score for the second geographic location and a physical distance between the first geographic location and the second geographic location; and selecting an item from a plurality of candidate items using the first category location relevance score, wherein each candidate item is associated with a respective category, and wherein selecting the item comprises: ranking the plurality of candidate items using the first category location relevance score, and selecting a highest ranked candidate item. 12. The method of claim 8 , wherein each Taylor coefficient for the function at the location is derived from an evaluation of the function or an evaluation of the derivative of the function at the location. | 0.696165 |
8,121,904 | 31 | 32 | 31. A computer system for generating a customized proposal to facilitate a sale of a tangible product, the system comprising: a memory system having stored therein images of a tangible product for sale, images of environments in which the tangible product is to be used, and text segments comprising descriptions of product specifications and performances; and a processing system, operatively coupled to the memory system, said processing system configured to automatically select, in response to receipt of at least one answer to one or more questions related to a desired feature and desired use of the product posed to a customer, one of the images of the tangible product, one of the images of the environment in which the tangible product is to be used, and one of the text segments comprised of a description of product specifications and performances that are of particular interest to the customer from those stored in the memory system, and to integrate the selected images and the selected text segment into a proposal for the sale of the product customized to the customer's interests such that a single composite output representing the tangible product in the environment in which it is to be used along with said selected text segment can be generated, wherein the single composite customized output is generated by a selection device operatively connected to (i) an active database configured to electronically store customer information, and (ii) a static database electronically storing at least one of (a) text, (b) pictures, or (c) text and pictures relating to the tangible product; and the computer system dynamically builds a template utilizing the selection device to fill in the template to produce the single composite output. | 31. A computer system for generating a customized proposal to facilitate a sale of a tangible product, the system comprising: a memory system having stored therein images of a tangible product for sale, images of environments in which the tangible product is to be used, and text segments comprising descriptions of product specifications and performances; and a processing system, operatively coupled to the memory system, said processing system configured to automatically select, in response to receipt of at least one answer to one or more questions related to a desired feature and desired use of the product posed to a customer, one of the images of the tangible product, one of the images of the environment in which the tangible product is to be used, and one of the text segments comprised of a description of product specifications and performances that are of particular interest to the customer from those stored in the memory system, and to integrate the selected images and the selected text segment into a proposal for the sale of the product customized to the customer's interests such that a single composite output representing the tangible product in the environment in which it is to be used along with said selected text segment can be generated, wherein the single composite customized output is generated by a selection device operatively connected to (i) an active database configured to electronically store customer information, and (ii) a static database electronically storing at least one of (a) text, (b) pictures, or (c) text and pictures relating to the tangible product; and the computer system dynamically builds a template utilizing the selection device to fill in the template to produce the single composite output. 32. The system of claim 31 wherein the processing system is further configured to provide a user interface to present the single composite output as a visual output to a user of the computer system. | 0.788009 |
8,976,839 | 1 | 2 | 1. A method for configuring codebooks, which is applied in a Long Term Evolution Advanced (LTE-A) system and comprises: a transmitting end selecting a code word restricted sub-set and informing a receiving end of the code word restricted sub-set by sending to the receiving end a signaling carrying a restricted sub-set bitmap, wherein each information bit in the restricted sub-set bitmap is associated with a code word for indicating whether the associated code word belongs to the code word restricted sub-set; the code word restricted sub-set containing part or all of code words in a first codebook and/or a second codebook; and the receiving end selecting an optimal pre-coded code word from the code word restricted sub-set and informing the transmitting end of an index of the optimal pre-coded code word; wherein in the step of the transmitting end selecting the code word restricted sub-set and informing the receiving end of the code word restricted sub-set, the transmitting end configures the restricted sub-set bitmap in one of the following ways: (1) performing sub-set restriction on the code words in the first codebook and the second codebook jointly, wherein a code word in the first codebook and a code word in the second codebook are taken as a code word combination, each code word combination is associated with one information bit in the restricted sub-set bitmap, and the code word restricted sub-set contains code words extracted from the first codebook and code words extracted from the second codebook; (2) performing sub-set restriction only on the code words in the first codebook, wherein each code word in the first codebook is associated with one information bit in the restricted sub-set bitmap, and the code word restricted sub-set contains code words extracted from the first codebook and all code words in the second codebook; (3) performing sub-set restriction only on the code words in the second codebook, wherein each code word in the second codebook is associated with one information bit in the restricted sub-set bitmap, and the code word restricted sub-set contains code words extracted from the second codebook and all code words in the first codebook; and (4) performing sub-set restriction on the code words in the first codebook and the second codebook separately, wherein, each code word in the first codebook and the second codebook is associated with one information bit in the restricted sub-set bitmap, and the code word restricted sub-set contains code words extracted from the first codebook and code words extracted from the second codebook. | 1. A method for configuring codebooks, which is applied in a Long Term Evolution Advanced (LTE-A) system and comprises: a transmitting end selecting a code word restricted sub-set and informing a receiving end of the code word restricted sub-set by sending to the receiving end a signaling carrying a restricted sub-set bitmap, wherein each information bit in the restricted sub-set bitmap is associated with a code word for indicating whether the associated code word belongs to the code word restricted sub-set; the code word restricted sub-set containing part or all of code words in a first codebook and/or a second codebook; and the receiving end selecting an optimal pre-coded code word from the code word restricted sub-set and informing the transmitting end of an index of the optimal pre-coded code word; wherein in the step of the transmitting end selecting the code word restricted sub-set and informing the receiving end of the code word restricted sub-set, the transmitting end configures the restricted sub-set bitmap in one of the following ways: (1) performing sub-set restriction on the code words in the first codebook and the second codebook jointly, wherein a code word in the first codebook and a code word in the second codebook are taken as a code word combination, each code word combination is associated with one information bit in the restricted sub-set bitmap, and the code word restricted sub-set contains code words extracted from the first codebook and code words extracted from the second codebook; (2) performing sub-set restriction only on the code words in the first codebook, wherein each code word in the first codebook is associated with one information bit in the restricted sub-set bitmap, and the code word restricted sub-set contains code words extracted from the first codebook and all code words in the second codebook; (3) performing sub-set restriction only on the code words in the second codebook, wherein each code word in the second codebook is associated with one information bit in the restricted sub-set bitmap, and the code word restricted sub-set contains code words extracted from the second codebook and all code words in the first codebook; and (4) performing sub-set restriction on the code words in the first codebook and the second codebook separately, wherein, each code word in the first codebook and the second codebook is associated with one information bit in the restricted sub-set bitmap, and the code word restricted sub-set contains code words extracted from the first codebook and code words extracted from the second codebook. 2. The method according to claim 1 , wherein in the step of the transmitting end selecting the code word restricted sub-set and informing the receiving end of the code word restricted sub-set, the transmitting end informs the receiving end of the selected code word restricted sub-set through a high-layer signaling. | 0.782069 |
8,064,295 | 5 | 10 | 5. A method of providing motivation to a user to perform a selected activity, comprising the steps of: (a) providing an integrated motivational alarm system comprising a timekeeping device comprising an alarm programming/alert setting mechanism capable of being programmed to produce one or more alarm signals when one or more pre-set programmed alarm settings is reached; a storage device operatively connected to said timekeeping device and comprising a plurality of specially structured, sequentially programmed recorded messages; said messages comprising a recorded, human, spoken voice and having a selected topic; and playback means incorporated within said timekeeping device and capable of converting one or more of said plurality of recorded messages into an audible signal upon receipt of each of one or more of said alarm signals; (b) programming one or more alarm settings to produce one or more alarm signals as each of said one or more alarm settings is reached by way of the alarm programming mechanism; and (c) playing one or more of said converted plurality of recorded messages in a sequential preprogrammed order upon receipt of each of one or more said alarm signals by way of the playback means. | 5. A method of providing motivation to a user to perform a selected activity, comprising the steps of: (a) providing an integrated motivational alarm system comprising a timekeeping device comprising an alarm programming/alert setting mechanism capable of being programmed to produce one or more alarm signals when one or more pre-set programmed alarm settings is reached; a storage device operatively connected to said timekeeping device and comprising a plurality of specially structured, sequentially programmed recorded messages; said messages comprising a recorded, human, spoken voice and having a selected topic; and playback means incorporated within said timekeeping device and capable of converting one or more of said plurality of recorded messages into an audible signal upon receipt of each of one or more of said alarm signals; (b) programming one or more alarm settings to produce one or more alarm signals as each of said one or more alarm settings is reached by way of the alarm programming mechanism; and (c) playing one or more of said converted plurality of recorded messages in a sequential preprogrammed order upon receipt of each of one or more said alarm signals by way of the playback means. 10. The method of claim 5 further comprising the step of the user periodically acquiring a replacement storage device having a second plurality of recorded messages. | 0.5 |
8,296,666 | 1 | 14 | 1. A computer-implemented visualization system for information analysis, the system comprising: a user interface; a processor and a memory coupled thereto, the memory storing instructions and data therein to configure the execution of the processor to configure a space on the user interface for marshalling evidence therein, the processor further configured to: visually represent a plurality of information excerpts from at least one information source in a spatial arrangement in the space on the user interface; and receive user input to manipulate the spatial arrangement of the plurality of information excerpts with respect to one another on the user interface as directed by the user for defining the evidence; receive analysis content on the user interface for associating with the plurality of information excerpts to facilitate visual cognition of the evidence in accordance with the manipulated spatial arrangement. | 1. A computer-implemented visualization system for information analysis, the system comprising: a user interface; a processor and a memory coupled thereto, the memory storing instructions and data therein to configure the execution of the processor to configure a space on the user interface for marshalling evidence therein, the processor further configured to: visually represent a plurality of information excerpts from at least one information source in a spatial arrangement in the space on the user interface; and receive user input to manipulate the spatial arrangement of the plurality of information excerpts with respect to one another on the user interface as directed by the user for defining the evidence; receive analysis content on the user interface for associating with the plurality of information excerpts to facilitate visual cognition of the evidence in accordance with the manipulated spatial arrangement. 14. The visualization system of claim 1 wherein the processor is further configured to represent the information on the user interface as data objects movable in said space and to visualize a first portion of said space and float a selected data object over data objects not selected to float in said space, whereby, while moving along a path to visualize a second portion of said space, said data objects not selected to float and located along the path are visualized under said selected data object. | 0.687811 |
7,664,717 | 3 | 4 | 3. The method of claim 1 , wherein said presenting the page, said asking, said textually presenting the plurality of answers, said requiring, and said determining composes performing a trial in stage 1. | 3. The method of claim 1 , wherein said presenting the page, said asking, said textually presenting the plurality of answers, said requiring, and said determining composes performing a trial in stage 1. 4. The method of claim 3 , where a level comprises a specified set of trials directed to a specified set of stimulus passages; and wherein said repeating said performing for each stimulus passage in the stimulus passage set comprises: performing trials in each level of a plurality of levels in said specified order. | 0.5 |
4,675,840 | 15 | 16 | 15. A computer system as defined in claim 14 wherein said means for generating a data read signal includes: means for decoding to coincidence of a read control signal from said computer and a speech memory select signal from said computer. | 15. A computer system as defined in claim 14 wherein said means for generating a data read signal includes: means for decoding to coincidence of a read control signal from said computer and a speech memory select signal from said computer. 16. A computer system as defined in claim 15 wherein said speech memory is dynamic random access memory and said memory address signal generating means includes: means responsive to said clock signal from said computer for generating a row address strobe followed by a column address strobe to enable single locations of said speech memory. | 0.5 |
9,971,746 | 1 | 10 | 1. A computer-implemented method, comprising: accessing a first resource belonging to a particular domain; selecting an anchor in the first resource linking to a second resource belonging to the particular domain to which the first resource belongs; identifying particular text content in the first resource that is subordinate to and proximate to the anchor; determining, by one or more computers, whether the second resource includes the particular text content that is subordinate to and proximate to the anchor in the first resource linking to the second resource belonging to the particular domain; in response to determining that the second resource includes the particular text content that is subordinate to and proximate to the anchor in the first resource linking to the second resource belonging to the particular domain, generating a domain template for the particular domain to which the first resource and the second resource belong and that specifies, a location of the particular text content in the second resource; determining one or more resources belonging to the particular domain that have a structure matching the domain template; determining, for each respective resource belonging to the particular domain having a structure matching the domain template, respective text content that is subordinate to the anchor for the respective resource; determining that a particular one of the respective resources is responsive to a search query; and in response to determining that the particular one of the respective resources is responsive to a search query, providing the respective text content that is subordinate to the anchor for the respective resource in response to the search query in a form of a snippet for the particular one of the respective resources in a search results page. | 1. A computer-implemented method, comprising: accessing a first resource belonging to a particular domain; selecting an anchor in the first resource linking to a second resource belonging to the particular domain to which the first resource belongs; identifying particular text content in the first resource that is subordinate to and proximate to the anchor; determining, by one or more computers, whether the second resource includes the particular text content that is subordinate to and proximate to the anchor in the first resource linking to the second resource belonging to the particular domain; in response to determining that the second resource includes the particular text content that is subordinate to and proximate to the anchor in the first resource linking to the second resource belonging to the particular domain, generating a domain template for the particular domain to which the first resource and the second resource belong and that specifies, a location of the particular text content in the second resource; determining one or more resources belonging to the particular domain that have a structure matching the domain template; determining, for each respective resource belonging to the particular domain having a structure matching the domain template, respective text content that is subordinate to the anchor for the respective resource; determining that a particular one of the respective resources is responsive to a search query; and in response to determining that the particular one of the respective resources is responsive to a search query, providing the respective text content that is subordinate to the anchor for the respective resource in response to the search query in a form of a snippet for the particular one of the respective resources in a search results page. 10. The method of claim 1 , wherein the particular text content includes text content that is proximate to anchor-text of the anchor. | 0.925698 |
4,852,172 | 1 | 5 | 1. A speech recognition system for recognizing the content of an input speech signal comprising: a reference pattern memory for storing reference patterns each being time-serial feature vectors of groups comprising at least first through third formant frequency information for a plurality of analysis frames; first means for developing LPC coefficients for each one of a predetermined plurality of analysis degrees, in each of said plurality of analysis frames, from an input pattern of said input speech signal; second means for developing first through third formant frequencies, for each of said plurality of analysis degrees in each of said plurality of analysis frames, from the developed LFC coefficients; third means for determining distances between said reference patterns and said input pattern, said input pattern being comprised of time-serially connected feature vectors for a plurality of groups of first through third formant frequency information for said plurality of frames, and each of said, groups being one of the groups of first through third formant frequency information developed for said plurality of analysis degrees in each frame; and fourth means for determining the reference pattern having the shortest distance from said input pattern on the basis of the distance determined by said third means as said input pattern. | 1. A speech recognition system for recognizing the content of an input speech signal comprising: a reference pattern memory for storing reference patterns each being time-serial feature vectors of groups comprising at least first through third formant frequency information for a plurality of analysis frames; first means for developing LPC coefficients for each one of a predetermined plurality of analysis degrees, in each of said plurality of analysis frames, from an input pattern of said input speech signal; second means for developing first through third formant frequencies, for each of said plurality of analysis degrees in each of said plurality of analysis frames, from the developed LFC coefficients; third means for determining distances between said reference patterns and said input pattern, said input pattern being comprised of time-serially connected feature vectors for a plurality of groups of first through third formant frequency information for said plurality of frames, and each of said, groups being one of the groups of first through third formant frequency information developed for said plurality of analysis degrees in each frame; and fourth means for determining the reference pattern having the shortest distance from said input pattern on the basis of the distance determined by said third means as said input pattern. 5. A speech recognition system according to claim 1, wherein said plurality of analysis frames is variable. | 0.600746 |
8,103,691 | 1 | 5 | 1. A method for dynamically generating a survey result(s) comprising: storing and managing each registered user's one or more profile(s), preferences and relational connections or dynamic relationships at a central server; allowing each user to manage a Human Operating System (HOS) including one or more profiles, activities, applications, services, actions, transactions, groups, searching, sharing, communication, contents and connections; presenting one or more domain or subject or taxonomy specific survey forms to user; receiving, via categories survey forms, a plurality of categories survey data or selections from the user, wherein survey data or selections relate or map, for each of plurality of different categories of user data for sharing with one or more other connected users who can access that category of user data and customization, personalization and configuration data utilize for customization of the user's Human Operating System (HOS) including dynamically creating one or more social networks, establishing communication and sharing selective one or more user resources or profiles with one or more other connected users, customize searching and matching, e-commerce, receiving customized advertisements, applications and services lists and contents; updating survey data and survey analysis to the related categories profile(s) of the user for applying or use the survey data for customization, personalization and configuration of each user's Human Operating System (HOS); and generating and presenting a survey results to the user, wherein survey results comprises a details of customization, personalization and configuration of each user's Human Operating System (HOS) and which other connected users can access which categories of user data based on the survey data or selections. | 1. A method for dynamically generating a survey result(s) comprising: storing and managing each registered user's one or more profile(s), preferences and relational connections or dynamic relationships at a central server; allowing each user to manage a Human Operating System (HOS) including one or more profiles, activities, applications, services, actions, transactions, groups, searching, sharing, communication, contents and connections; presenting one or more domain or subject or taxonomy specific survey forms to user; receiving, via categories survey forms, a plurality of categories survey data or selections from the user, wherein survey data or selections relate or map, for each of plurality of different categories of user data for sharing with one or more other connected users who can access that category of user data and customization, personalization and configuration data utilize for customization of the user's Human Operating System (HOS) including dynamically creating one or more social networks, establishing communication and sharing selective one or more user resources or profiles with one or more other connected users, customize searching and matching, e-commerce, receiving customized advertisements, applications and services lists and contents; updating survey data and survey analysis to the related categories profile(s) of the user for applying or use the survey data for customization, personalization and configuration of each user's Human Operating System (HOS); and generating and presenting a survey results to the user, wherein survey results comprises a details of customization, personalization and configuration of each user's Human Operating System (HOS) and which other connected users can access which categories of user data based on the survey data or selections. 5. The method as claimed in claim 1 , wherein survey forms data comprising user provided or user generated domain or subject specific information, selections, preferences, resource offerings, dynamically or auto updated data and attributes, auto sensing of user's needs and interest, recorded user's behaviors, wants, needs and multiple attributes in the network and domain specific search preferences, for customized and highly relevant and real time searching, privacy settings or customization, personalization and configuration data. | 0.691734 |
10,146,816 | 4 | 5 | 4. The system of claim 1 , wherein the processor is operative with the program to execute the program for: adding node identifiers to nodes of the topic tree. | 4. The system of claim 1 , wherein the processor is operative with the program to execute the program for: adding node identifiers to nodes of the topic tree. 5. The system of claim 4 , wherein the adding of node identifiers to nodes of the topic tree is performed before the retrieving of the content in the topic tree for matching topics. | 0.599558 |
9,305,092 | 12 | 14 | 12. The computer storage medium of claim 11 , wherein each ranking score is determined based on at least one of a frequency, an interaction score, an endorsement score and a selection score that are specific to a respective query auto-completion. | 12. The computer storage medium of claim 11 , wherein each ranking score is determined based on at least one of a frequency, an interaction score, an endorsement score and a selection score that are specific to a respective query auto-completion. 14. The computer storage medium of claim 12 , wherein: the frequency reflects a frequency at which the respective query auto-completion is used as a search query, the interaction score reflects user interaction with search results that had been previously generated based on the respective query auto-completion, the endorsement score reflects endorsements users have provided to search results that had been previously generated based on the respective query auto-completion, and the selection score reflects selections of the respective query auto-completion as a search query from a list of query auto-completions. | 0.5 |
7,593,843 | 16 | 17 | 16. The method of claim 15 wherein calculating a score for each of the set of transfer mappings comprises calculating a score for a tree of transfer mappings through steps comprises: recursively calculating a score for each level of nested subtrees, wherein calculating a score for a subtree comprises recursively scoring the subtrees of the subtree, calculating a score for the root transfer mapping of the subtree, and combining the scores for the subtrees of the subtree with the score for the root transfer mapping of the subtree; calculating a score for the root transfer mapping; and combining the score for each subtree with the score for the root transfer mapping. | 16. The method of claim 15 wherein calculating a score for each of the set of transfer mappings comprises calculating a score for a tree of transfer mappings through steps comprises: recursively calculating a score for each level of nested subtrees, wherein calculating a score for a subtree comprises recursively scoring the subtrees of the subtree, calculating a score for the root transfer mapping of the subtree, and combining the scores for the subtrees of the subtree with the score for the root transfer mapping of the subtree; calculating a score for the root transfer mapping; and combining the score for each subtree with the score for the root transfer mapping. 17. The method of claim 16 wherein computing a score for a root transfer mapping comprises computing a size score for the root transfer mapping based on a number of nodes in the input semantic side of the root transfer mapping. | 0.630293 |
8,311,838 | 18 | 19 | 18. A method for defining input windows to associate with provided prompts, comprising: at an electronic device with at least one processor and memory: identifying a plurality of prompts to provide in sequence, wherein each prompt is associated with a distinct electronic device operation; defining an offset relative to at least one of a start time and an end time for providing each of the plurality of prompts; and determining, for each of the plurality of prompts, an input window defined by an initial time and a final time for determining which provided prompt of the plurality of prompts to associate with a received voice input, wherein at least one of the initial time and the final time are offset from the start time and end time by the defined offset. | 18. A method for defining input windows to associate with provided prompts, comprising: at an electronic device with at least one processor and memory: identifying a plurality of prompts to provide in sequence, wherein each prompt is associated with a distinct electronic device operation; defining an offset relative to at least one of a start time and an end time for providing each of the plurality of prompts; and determining, for each of the plurality of prompts, an input window defined by an initial time and a final time for determining which provided prompt of the plurality of prompts to associate with a received voice input, wherein at least one of the initial time and the final time are offset from the start time and end time by the defined offset. 19. The method of claim 18 , further comprising: determining the importance of each prompt; and varying the defined offset for each prompt based on the importance of the prompt. | 0.662214 |
9,047,488 | 21 | 23 | 21. An apparatus, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive a request for data, wherein the request specifies a relational context corresponding to a selected group of selected persons selected from a global group of persons based on the relational context, and wherein the relational context specifies one or more attributes of selected persons in the selected group that establishes a relationship between the selected persons and distinguishes the selected persons from non-selected persons in the global group that are not in the selected group; determine, for the relational context corresponding to the selected group, based on a corpus of personal information data corresponding to the selected persons in the selected group, one or more key attributes in the personal information data; determine a rarity value for each key attribute of the one or more key attributes within the relational context of the selected group; and anonymize selected key attributes in the one or more key attributes based on the determined rarity value for each of the key attributes within the relational context of the selected group, wherein the instructions cause the processor to determine the rarity value of each key attribute of the one or more key attributes at least by generating a relative rarity matrix data structure that identifies the one or more key attributes and their corresponding related relative rarity measures. | 21. An apparatus, comprising: a processor; and a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to: receive a request for data, wherein the request specifies a relational context corresponding to a selected group of selected persons selected from a global group of persons based on the relational context, and wherein the relational context specifies one or more attributes of selected persons in the selected group that establishes a relationship between the selected persons and distinguishes the selected persons from non-selected persons in the global group that are not in the selected group; determine, for the relational context corresponding to the selected group, based on a corpus of personal information data corresponding to the selected persons in the selected group, one or more key attributes in the personal information data; determine a rarity value for each key attribute of the one or more key attributes within the relational context of the selected group; and anonymize selected key attributes in the one or more key attributes based on the determined rarity value for each of the key attributes within the relational context of the selected group, wherein the instructions cause the processor to determine the rarity value of each key attribute of the one or more key attributes at least by generating a relative rarity matrix data structure that identifies the one or more key attributes and their corresponding related relative rarity measures. 23. The apparatus of claim 21 , wherein the one or more key attributes are textual terms, and wherein determining the one or more key attributes in the personal information data comprises determining deep semantic relationships between textual terms in the personal information data and identifying uncommon deep semantic relationships between textual terms in the personal information data. | 0.5 |
8,427,509 | 18 | 22 | 18. A method for embedding a message into a document, comprising: representing at least part of a document as a distance field including distance values; representing a symbol in a message to be embedded in the document as a modification of a subset of the values in the distance field; and modifying the subset of the values in the distance field according to the modification to produce a modified document, wherein the symbol in the message is embedded in the modified document, wherein steps of the method are performed by a processor. | 18. A method for embedding a message into a document, comprising: representing at least part of a document as a distance field including distance values; representing a symbol in a message to be embedded in the document as a modification of a subset of the values in the distance field; and modifying the subset of the values in the distance field according to the modification to produce a modified document, wherein the symbol in the message is embedded in the modified document, wherein steps of the method are performed by a processor. 22. The method of claim 18 , further comprising: selecting the subset of values in the distance field according to a key. | 0.79698 |
9,251,139 | 5 | 6 | 5. The method of claim 1 , comprising: obtaining, with one or more processors, a training set of conveyance records and documents from which the conveyance records were manually populated; and training, with one or more processors, at least in part, a language processing model based on the training set. | 5. The method of claim 1 , comprising: obtaining, with one or more processors, a training set of conveyance records and documents from which the conveyance records were manually populated; and training, with one or more processors, at least in part, a language processing model based on the training set. 6. The method of claim 5 , comprising: subsampling, with one or more processors, into a plurality of subsamples, the training set of conveyance records and documents from which the conveyance records were manually populated; training, with one or more processors, a plurality of language processing models on respective ones of the subsamples; and aggregating the plurality of language processing models into a single aggregate language processing model. | 0.5 |
8,793,612 | 13 | 14 | 13. The processing device of claim 12 where the control symbol is used by the processor to navigate through the GUI to the destination text based input field associated with the control symbol such that a first parsed segment of the sequence of characters is associated with a hierarchically higher level in the GUI than a different parsed segment of the sequence of characters. | 13. The processing device of claim 12 where the control symbol is used by the processor to navigate through the GUI to the destination text based input field associated with the control symbol such that a first parsed segment of the sequence of characters is associated with a hierarchically higher level in the GUI than a different parsed segment of the sequence of characters. 14. The processing device of claim 13 where the first parsed segment is associated with a first page of said at least one GUI page and the different parsed segment is associated with one of a plurality of text based input fields in the first page. | 0.5 |
8,082,151 | 1 | 3 | 1. A method of generating a response to a text-based natural language message, comprising: identifying a sentence in the text-based natural language message; identifying an input clause in the sentence; comparing the input clause to a previously received clause, the previously received clause being correlated with a previously generated response message; and generating an output response message based on the previously generated response message, the output response message being derived from a plurality of previously generated response clauses. | 1. A method of generating a response to a text-based natural language message, comprising: identifying a sentence in the text-based natural language message; identifying an input clause in the sentence; comparing the input clause to a previously received clause, the previously received clause being correlated with a previously generated response message; and generating an output response message based on the previously generated response message, the output response message being derived from a plurality of previously generated response clauses. 3. A method according to claim 1 , further comprising parsing the input clause, thereby defining a relationship between words in the input clause. | 0.821516 |
9,396,412 | 1 | 6 | 1. A method for person re-identification, the method comprising: mapping color values separately for different regions from first and second images to first and second probability distributions over a plurality of colors, the plurality of colors in a first color space different than a second color space of the color values; calculating separately, with a processor, for the different regions a similarity score between the first and second probability distributions; determining an affinity score as a function of the similarity scores from the different regions, and different weights applied to different similarity scores, the weight being a rank-boosted machine-learnt value; and identifying a person in the second image as a person in the first image, the identifying being a function of the affinity scores. | 1. A method for person re-identification, the method comprising: mapping color values separately for different regions from first and second images to first and second probability distributions over a plurality of colors, the plurality of colors in a first color space different than a second color space of the color values; calculating separately, with a processor, for the different regions a similarity score between the first and second probability distributions; determining an affinity score as a function of the similarity scores from the different regions, and different weights applied to different similarity scores, the weight being a rank-boosted machine-learnt value; and identifying a person in the second image as a person in the first image, the identifying being a function of the affinity scores. 6. The method of claim 1 wherein calculating comprises calculating Bhattacharyya coefficients. | 0.832143 |
8,493,229 | 1 | 2 | 1. A product container, the container comprising: a body having an opening associated with an interior portion; a product disposed within the interior portion; an enclosure member positioned proximate to the opening and movable between a first position in which the product is retained in the interior portion and a second position in which the product can exit the interior portion via the opening; a sensor operably coupled to at least one of the body and the enclosure member; and an audible warning system carried by the container and operably coupled to the sensor, wherein the audible warning system is configured to audibly output a spoken warning regarding the product in response to receiving an indication from the sensor associated with movement of the enclosure member from the first position toward the second position. | 1. A product container, the container comprising: a body having an opening associated with an interior portion; a product disposed within the interior portion; an enclosure member positioned proximate to the opening and movable between a first position in which the product is retained in the interior portion and a second position in which the product can exit the interior portion via the opening; a sensor operably coupled to at least one of the body and the enclosure member; and an audible warning system carried by the container and operably coupled to the sensor, wherein the audible warning system is configured to audibly output a spoken warning regarding the product in response to receiving an indication from the sensor associated with movement of the enclosure member from the first position toward the second position. 2. The container of claim 1 wherein the audible warning system includes: a controller operably coupled to the sensor; a data storage medium operably coupled to the controller, the data storage medium containing the spoken warning; a power source operably coupled to the controller; and a speaker operably coupled to the controller, wherein the controller causes the speaker to audibly output the spoken warning in response to receiving the indication from the sensor. | 0.5 |
9,672,206 | 49 | 50 | 49. The method according to claim 48 , where the at least two texts are ranked for similarity by sorting by their respective combined string and semantic similarity scores. | 49. The method according to claim 48 , where the at least two texts are ranked for similarity by sorting by their respective combined string and semantic similarity scores. 50. The method according to claim 49 , where a score of canonical forms is determined by a k nearest neighbor score. | 0.5 |
7,925,506 | 1 | 2 | 1. A speech recognition system for providing a textual output from an audible signal representative of spoken words, said system comprising: a storage unit, said storage unit storing a plurality of sentence types on a storage medium, each of said sentence type including a pre-arranged ordered list of concepts, each concept in said pre-arranged ordered list of concepts being expandable to a plurality of words conceptually related to the each expanded concept; a natural language processor operatively connected to said storage unit, said natural language processor being configured to parse a partially recognized sentence having an ordered list of recognized words and unrecognized sound groupings into a first ordered list of concepts and placeholders, said concepts in said first ordered lists corresponding to said recognized words and said placeholders corresponding to said unrecognized sound groupings, and said natural language processor being further configured to identify a sentence type from said plurality of sentence types utilizing said first ordered list of concepts and placeholders, said identified sentence type having an associated ordered list of concepts, the order of concepts in said associated ordered list of concepts being determined by the spoken words, each concept in said associated ordered list of concepts being expandable to a plurality of words conceptually related to the each expanded concept, said partially recognized sentence corresponding to the audible signal; a grammar rule generator for expanding each of said concepts at a location corresponding to one of said unrecognized sound groupings into a respective plurality of related words; a speech recognition engine for converting the audible signal to the textual output, said speech recognition engine being operatively connected to said respective plurality of related words for resolving the one of said unrecognized sound grouping. | 1. A speech recognition system for providing a textual output from an audible signal representative of spoken words, said system comprising: a storage unit, said storage unit storing a plurality of sentence types on a storage medium, each of said sentence type including a pre-arranged ordered list of concepts, each concept in said pre-arranged ordered list of concepts being expandable to a plurality of words conceptually related to the each expanded concept; a natural language processor operatively connected to said storage unit, said natural language processor being configured to parse a partially recognized sentence having an ordered list of recognized words and unrecognized sound groupings into a first ordered list of concepts and placeholders, said concepts in said first ordered lists corresponding to said recognized words and said placeholders corresponding to said unrecognized sound groupings, and said natural language processor being further configured to identify a sentence type from said plurality of sentence types utilizing said first ordered list of concepts and placeholders, said identified sentence type having an associated ordered list of concepts, the order of concepts in said associated ordered list of concepts being determined by the spoken words, each concept in said associated ordered list of concepts being expandable to a plurality of words conceptually related to the each expanded concept, said partially recognized sentence corresponding to the audible signal; a grammar rule generator for expanding each of said concepts at a location corresponding to one of said unrecognized sound groupings into a respective plurality of related words; a speech recognition engine for converting the audible signal to the textual output, said speech recognition engine being operatively connected to said respective plurality of related words for resolving the one of said unrecognized sound grouping. 2. The speech recognition system of claim 1 , wherein the storage unit stores a collection of concepts and mappings from concepts to keywords, said storage unit being further operatively connected to the grammar rule generator. | 0.71625 |
9,684,986 | 5 | 7 | 5. The method of claim 4 , further comprising: determining, by the one or more computer processors, a second distance value between the first positional reference line and the third positional reference line; determining, by the one or more computer processors, that the second distance value is different than the first distance value; assigning, by the one or more computer processors, a second numerical identifier to the second glyph, wherein the second numerical identifier is different from the first numerical identifier; and generating, by the one or more computer processors, second glyph data associated with the second glyph, the second glyph data comprising the second distance value; wherein the font file further comprises the second glyph data. | 5. The method of claim 4 , further comprising: determining, by the one or more computer processors, a second distance value between the first positional reference line and the third positional reference line; determining, by the one or more computer processors, that the second distance value is different than the first distance value; assigning, by the one or more computer processors, a second numerical identifier to the second glyph, wherein the second numerical identifier is different from the first numerical identifier; and generating, by the one or more computer processors, second glyph data associated with the second glyph, the second glyph data comprising the second distance value; wherein the font file further comprises the second glyph data. 7. The method of claim 5 , wherein: the first positional reference line is a first vertical reference line indicative of a horizontal alignment of the first character; the second positional reference line is a second vertical reference line indicative of a horizontal alignment of a first group of characters forming the first word; the third positional reference line is a third vertical reference line indicative of a horizontal alignment of a second group of characters forming the second word; and the first distance value for the first glyph is a first horizontal adjustment for the first glyph between the first vertical reference line and the second vertical reference line. | 0.5 |
8,909,597 | 1 | 5 | 1. A method comprising: receiving, in a graphical user interface area, first inputs specifying drag-and-drop operations with respect to icons representing documents, the drag-and-drop operations indicating that the documents are to be added to a workflow represented by the graphical user interface area; depicting the documents within the graphical user interface area in a particular order, wherein the particular order reflects dependencies between the documents, the particular order indicating at least that processing of a second document of the documents is dependent upon a first document output of a first document of the documents; processing the workflow to generate a first workflow output for the workflow, wherein processing the workflow comprises at least iteratively generating outputs for each of the documents, in accordance with the particular order, the outputs including the first document output and a second document output for the second document; wherein generating the first document output comprises executing instructions within the first document configured to cause deriving a data set from a data source external to the first document; wherein generating the second document output comprises executing instructions within the second document configured to cause generating one or more graphs based on the first document output; reprocessing the workflow to generate a second workflow output for the workflow, wherein the second workflow output differs from the first workflow output as a result of a change in the first document output; wherein the method is performed by one or more computing devices. | 1. A method comprising: receiving, in a graphical user interface area, first inputs specifying drag-and-drop operations with respect to icons representing documents, the drag-and-drop operations indicating that the documents are to be added to a workflow represented by the graphical user interface area; depicting the documents within the graphical user interface area in a particular order, wherein the particular order reflects dependencies between the documents, the particular order indicating at least that processing of a second document of the documents is dependent upon a first document output of a first document of the documents; processing the workflow to generate a first workflow output for the workflow, wherein processing the workflow comprises at least iteratively generating outputs for each of the documents, in accordance with the particular order, the outputs including the first document output and a second document output for the second document; wherein generating the first document output comprises executing instructions within the first document configured to cause deriving a data set from a data source external to the first document; wherein generating the second document output comprises executing instructions within the second document configured to cause generating one or more graphs based on the first document output; reprocessing the workflow to generate a second workflow output for the workflow, wherein the second workflow output differs from the first workflow output as a result of a change in the first document output; wherein the method is performed by one or more computing devices. 5. The method of claim 1 , further comprising: in response to input in the graphical user interface at a first computer, causing a workflow data structure describing the workflow to be stored; wherein processing the workflow occurs at the first computer; subsequently accessing the workflow data structure at a second computer to reconstruct the workflow within the graphical user interface at the second computer; wherein reprocessing the workflow occurs at the second computer. | 0.5 |
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