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8,358,703 | 4 | 6 | 4. The method of claim 1 wherein decoding of the first coded portion produces a first image result, and decoding of the modified first arithmetically coded portion produces a modified first image result that is different from the first image result. | 4. The method of claim 1 wherein decoding of the first coded portion produces a first image result, and decoding of the modified first arithmetically coded portion produces a modified first image result that is different from the first image result. 6. The method of claim 4 wherein the first result is part of a first image and the modified first result is part of a modified first image, and the method further comprises: providing the modified first arithmetically coded portion for use in applying one or more watermarking bits to the first image; and providing location information that identifies location of the modified first result for use in recovering the one or more watermarking bits from the modified first image. | 0.820136 |
7,895,137 | 11 | 17 | 11. A computer program product for transforming data into computer executable rules for mining and constructing situation categories that are applied to information technology resource messages or events comprising: a computer usable medium having computer usable program code embodied therewith, the computer usable program code comprising: computer usable program code configured to receive computer readable data by a computer processing device from at least one of: a raw log and a catalog, where the received data is at least one of: initial seed data and knowledge data, to derive the computer executable rules for mining and constructing situation categories; computer usable program code configured to transform the received data into a predetermined standard format if the received data is not already in the predetermined standard format; computer usable program code configured to parse the predetermined standard formatted data; computer usable program code configured to perform an outer, iterative loop until at least one predetermined stopping criterion is met, comprising: computer usable program code configured to utilize a keyword rule classifier by the computer processing device to automatically pre-classify at least a portion of the parsed data; computer usable program code configured to perform an inner iterative loop within the outer iterative loop, comprising: computer usable program code configured to select a subset of the parsed data for expert review; computer usable program code configured to use at least one of keyword rules, features, and classifications to find, within data available to the computer processing device, a corresponding previously labeled subset of data that has similar semantics to semantics of the selected subset of data; computer usable program code configured to label the selected subset of data with the label associated with the corresponding previously labeled subset of data; and computer usable program code configured to repeat the inner iterative loop if another subset of data is to be processed; computer usable program code configured to store each labeled subset of data on a data storage device; computer usable program code configured to generate new computer executable rules for mining and constructing situation categories from the stored labeled subsets of data; computer usable program code configured to transform keyword list classifiers using the stored labeled subsets of data; and computer usable program code configured to repeat the outer iterative loop if the predetermined stopping criterion is not met. | 11. A computer program product for transforming data into computer executable rules for mining and constructing situation categories that are applied to information technology resource messages or events comprising: a computer usable medium having computer usable program code embodied therewith, the computer usable program code comprising: computer usable program code configured to receive computer readable data by a computer processing device from at least one of: a raw log and a catalog, where the received data is at least one of: initial seed data and knowledge data, to derive the computer executable rules for mining and constructing situation categories; computer usable program code configured to transform the received data into a predetermined standard format if the received data is not already in the predetermined standard format; computer usable program code configured to parse the predetermined standard formatted data; computer usable program code configured to perform an outer, iterative loop until at least one predetermined stopping criterion is met, comprising: computer usable program code configured to utilize a keyword rule classifier by the computer processing device to automatically pre-classify at least a portion of the parsed data; computer usable program code configured to perform an inner iterative loop within the outer iterative loop, comprising: computer usable program code configured to select a subset of the parsed data for expert review; computer usable program code configured to use at least one of keyword rules, features, and classifications to find, within data available to the computer processing device, a corresponding previously labeled subset of data that has similar semantics to semantics of the selected subset of data; computer usable program code configured to label the selected subset of data with the label associated with the corresponding previously labeled subset of data; and computer usable program code configured to repeat the inner iterative loop if another subset of data is to be processed; computer usable program code configured to store each labeled subset of data on a data storage device; computer usable program code configured to generate new computer executable rules for mining and constructing situation categories from the stored labeled subsets of data; computer usable program code configured to transform keyword list classifiers using the stored labeled subsets of data; and computer usable program code configured to repeat the outer iterative loop if the predetermined stopping criterion is not met. 17. The computer program product of claim 11 , wherein computer usable program code configured to use at least one of keyword rules, features, and classifications to find, within data available to the computer processing device, a corresponding previously labeled subset of data comprises computer usable program code configured to determine if all selected features of previously labeled subsets of data correspond to a feature set of the selected subset of data and determine if no negated features of the previously labeled subset of data appear in the feature set of the selected subset of data. | 0.82162 |
9,087,106 | 15 | 18 | 15. A system, comprising: a plurality of network devices that are configured to perform actions, including: for each user of a plurality of users: accessing a user profile index to determine at least one reading interest of the user; gathering publishing data of the plurality of users from publicly available content generated by the plurality of users; indexing publishing interests of the plurality of users based on gathered publishing data of the plurality of users, such that the publishing interests include topics generated from key words in the publishing behavior information and latent semantic topics inferred from the publishing behavior information; performing based on the indexing, relevance matching to determine matching users from the plurality of users such that each matching user has at least one publishing interest that is relevant to at least one reading interest of the user; ranking the matching users; based on the ranking, determining one or more top ranked matching users; and providing suggestions for a social recommendation for each of the one or more top ranked matching users to be made to the user, each of the suggestions for the top ranked matching users comprises respective representative publishing content pieces of each of the top ranked matching users. | 15. A system, comprising: a plurality of network devices that are configured to perform actions, including: for each user of a plurality of users: accessing a user profile index to determine at least one reading interest of the user; gathering publishing data of the plurality of users from publicly available content generated by the plurality of users; indexing publishing interests of the plurality of users based on gathered publishing data of the plurality of users, such that the publishing interests include topics generated from key words in the publishing behavior information and latent semantic topics inferred from the publishing behavior information; performing based on the indexing, relevance matching to determine matching users from the plurality of users such that each matching user has at least one publishing interest that is relevant to at least one reading interest of the user; ranking the matching users; based on the ranking, determining one or more top ranked matching users; and providing suggestions for a social recommendation for each of the one or more top ranked matching users to be made to the user, each of the suggestions for the top ranked matching users comprises respective representative publishing content pieces of each of the top ranked matching users. 18. The system of claim 15 , wherein the plurality of network devices are configured to perform further actions, including: generating the user profile index by indexing a plurality of users profiles based on gathered consumption behavior from the plurality of users such that the user profile index includes reading interests of the users; indexing publishing interests of the plurality of users based on gathered publishing data from the plurality of users. | 0.688179 |
9,104,755 | 14 | 15 | 14. The ontology enhancement system according to claim 10 , wherein the enhancement module determines whether the enhanced ontology should be modified or further enhanced; when the enhanced ontology is determined to be modified, the enhancement module modifies the enhanced ontology; when the enhanced ontology is determined to be further enhanced, the enhancement module further enhances the enhanced ontology. | 14. The ontology enhancement system according to claim 10 , wherein the enhancement module determines whether the enhanced ontology should be modified or further enhanced; when the enhanced ontology is determined to be modified, the enhancement module modifies the enhanced ontology; when the enhanced ontology is determined to be further enhanced, the enhancement module further enhances the enhanced ontology. 15. The ontology enhancement system according to claim 14 , wherein an user interface is provided to at least an user to determine whether the enhanced ontology should be modified or further enhanced. | 0.972467 |
8,484,210 | 9 | 14 | 9. A system for representing markup language document data in a searchable format, composing: one or more processors; a module configured to parse, using the one or more processors, a markup language document into a data stream, wherein the data stream includes: a plurality of fields in a predefined format having a symbol table for at least one of the fields, wherein offset values for fields of the data stream are calculated automatically and without requiring storage in the data stream, and optimized field sizes based on a maximum value of data within each field; and a module configured to store, using the one or more processors, the data stream in data storage. | 9. A system for representing markup language document data in a searchable format, composing: one or more processors; a module configured to parse, using the one or more processors, a markup language document into a data stream, wherein the data stream includes: a plurality of fields in a predefined format having a symbol table for at least one of the fields, wherein offset values for fields of the data stream are calculated automatically and without requiring storage in the data stream, and optimized field sizes based on a maximum value of data within each field; and a module configured to store, using the one or more processors, the data stream in data storage. 14. The system of claim 9 , wherein the symbol table comprises an array of element names for each unique node element of the markup language document. | 0.776786 |
8,065,303 | 12 | 14 | 12. A method of searching a database for different types of digital assets, the method comprising: storing data in a memory that is read by a computer, the data comprising a server application program and only one single document type definition (DTD) for use in storing, retrieving, searching, or tracking at least three different types of digital assets stored in a single database, each digital asset of the digital assets including content and metadata, the metadata including rights management information, the server application program including modules for a parser, a query language utility, and a style sheet processor; receiving a demand containing user entered search parameters for information pertaining to the at least three different types of digital assets; accessing the DTD by executing the server application program, the DTD defining declared elements for the at least three different types of digital assets and defining elements and attributes for rights management of the at least three different types of digital assets, the at least three different types of digital assets including photographs, video recordings, and at least one of audio recordings, movies, promotional announcements, voiceovers, graphics, artwork, or text documents, wherein the rights management elements and attributes comprise metadata for at least one of: a contract identifier, an availability start date, an availability end date, an allowed number of plays per agreement, a copyright holder identifier, or a worldwide rights identifier, wherein the DTD defines metadata for photographs and metadata attributes for the photograph metadata, the photograph-metadata attributes comprising at least one of: a definition for black/white, a definition for color, a definition for caption, or a definition for legal restrictions, wherein the DTD defines metadata for video recordings and metadata attributes for the video recordings metadata, the video-recordings-metadata attributes comprising at least one of: a definition for title, a definition for version, a definition for author, a definition for caption, or a definition for ownership rights; converting the demand into a query to be transmitted to the database by using the query language utility; searching the at least three different types of the digital assets in accordance with the converted demand and the accessed DTD; and converting search results returned from the database into a style sheet for input to a client application by using the style sheet processor. | 12. A method of searching a database for different types of digital assets, the method comprising: storing data in a memory that is read by a computer, the data comprising a server application program and only one single document type definition (DTD) for use in storing, retrieving, searching, or tracking at least three different types of digital assets stored in a single database, each digital asset of the digital assets including content and metadata, the metadata including rights management information, the server application program including modules for a parser, a query language utility, and a style sheet processor; receiving a demand containing user entered search parameters for information pertaining to the at least three different types of digital assets; accessing the DTD by executing the server application program, the DTD defining declared elements for the at least three different types of digital assets and defining elements and attributes for rights management of the at least three different types of digital assets, the at least three different types of digital assets including photographs, video recordings, and at least one of audio recordings, movies, promotional announcements, voiceovers, graphics, artwork, or text documents, wherein the rights management elements and attributes comprise metadata for at least one of: a contract identifier, an availability start date, an availability end date, an allowed number of plays per agreement, a copyright holder identifier, or a worldwide rights identifier, wherein the DTD defines metadata for photographs and metadata attributes for the photograph metadata, the photograph-metadata attributes comprising at least one of: a definition for black/white, a definition for color, a definition for caption, or a definition for legal restrictions, wherein the DTD defines metadata for video recordings and metadata attributes for the video recordings metadata, the video-recordings-metadata attributes comprising at least one of: a definition for title, a definition for version, a definition for author, a definition for caption, or a definition for ownership rights; converting the demand into a query to be transmitted to the database by using the query language utility; searching the at least three different types of the digital assets in accordance with the converted demand and the accessed DTD; and converting search results returned from the database into a style sheet for input to a client application by using the style sheet processor. 14. A computer system for performing the method of claim 12 , the system comprising: a server comprising the single database; a first computer readable storage medium comprising the DTD; and a second computer readable storage medium comprising the server application program. | 0.739089 |
8,887,121 | 1 | 10 | 1. A non-transitory computer-accessible memory medium that stores program instructions executable by a computer system to perform: providing a graphical program development environment comprising a graphical specification and constraint language that allows specification of a model of computation and explicit declaration of constraints; and creating a graphical program in the graphical specification and constraint language in response to user input, wherein the graphical program comprises: a specified model of computation; a plurality of interconnected functional blocks that visually indicate functionality of the graphical program in accordance with the specified model of computation; and graphically indicated specifications or constraints for at least one of the functional blocks in the graphical program; wherein the specifications or constraints comprise: input count (IC), comprising a number of tokens consumed at an input terminal of the at least one functional block by one firing of the at least one functional block; output count (OC), comprising a number of tokens produced at an output terminal of the at least one functional block by one firing of the at least one functional block; execution time (ET), comprising a number of cycles needed by the at least one functional block to complete firing; initiation interval (II), comprising a minimum number of cycles between firings of the at least one functional block; input pattern (IP), comprising a sequence of Boolean values of length at most II, wherein the sequence of Boolean values aligns with the beginning of firing of the at least one functional block, wherein each true value in the sequence denotes consumption of a token at an input terminal of the at least one functional block; and output pattern (OP), comprising a sequence of Boolean values of length at most II, wherein the sequence of Boolean values aligns with the end of firing of the at least one functional block, wherein each true value in the sequence denotes production of a token at an output terminal of the at least one functional block; and automatically generating a program based on the graphical program, wherein the program implements the functionality of the graphical program in accordance with the specified model of computation, and further implements the specifications or constraints; wherein the program is useable to configure a programmable hardware element to perform the functionality subject to the specifications or constraints. | 1. A non-transitory computer-accessible memory medium that stores program instructions executable by a computer system to perform: providing a graphical program development environment comprising a graphical specification and constraint language that allows specification of a model of computation and explicit declaration of constraints; and creating a graphical program in the graphical specification and constraint language in response to user input, wherein the graphical program comprises: a specified model of computation; a plurality of interconnected functional blocks that visually indicate functionality of the graphical program in accordance with the specified model of computation; and graphically indicated specifications or constraints for at least one of the functional blocks in the graphical program; wherein the specifications or constraints comprise: input count (IC), comprising a number of tokens consumed at an input terminal of the at least one functional block by one firing of the at least one functional block; output count (OC), comprising a number of tokens produced at an output terminal of the at least one functional block by one firing of the at least one functional block; execution time (ET), comprising a number of cycles needed by the at least one functional block to complete firing; initiation interval (II), comprising a minimum number of cycles between firings of the at least one functional block; input pattern (IP), comprising a sequence of Boolean values of length at most II, wherein the sequence of Boolean values aligns with the beginning of firing of the at least one functional block, wherein each true value in the sequence denotes consumption of a token at an input terminal of the at least one functional block; and output pattern (OP), comprising a sequence of Boolean values of length at most II, wherein the sequence of Boolean values aligns with the end of firing of the at least one functional block, wherein each true value in the sequence denotes production of a token at an output terminal of the at least one functional block; and automatically generating a program based on the graphical program, wherein the program implements the functionality of the graphical program in accordance with the specified model of computation, and further implements the specifications or constraints; wherein the program is useable to configure a programmable hardware element to perform the functionality subject to the specifications or constraints. 10. The non-transitory computer-accessible memory medium of claim 1 , wherein the number of tokens consumed and produced are resolved at the time the functional blocks are connected; and wherein the number of tokens consumed and produced are specified as a different functional block in the graphical program. | 0.67542 |
8,380,721 | 10 | 12 | 10. A computer implemented method for operating context-sensitive databases, the method comprising: receiving a user selection of one of a plurality of contexts; determining one or more predefined concepts associated with the one of the plurality of contexts from a representation of a structured web community stored in a database, the structured web community comprising a plurality of contexts, each context comprising a set of content, the set of content included in each context determined using a community finding method based on structural closeness and semantic closeness of the content in the context, each context including an array of predefined concepts generated based on terms extracted from the set content in the context and statistical frequency of occurrence of terms within the set of content in the context, each predefined concept characterized by a pattern of terms derived from the set of content in the context, wherein a plurality of the plurality of contexts are associated together to form a hierarchy of overlapping contexts; associating an advertisement with the one of the plurality of contexts based on the at least one predefined concept; and presenting the advertisement in response to the user selection of the one of the plurality of contexts; wherein determining the set of content in each context using a community finding method based on structural closeness and semantic closeness of the content comprises: selecting a node in a network as a source node; computing a set of local communities for the source node; identifying a set of nodes in the set of local communities having a weight greater than a threshold; generating a strong local community for the source node including only the set of nodes that have a weight greater than the threshold; storing the strong local community as one of a plurality of communities of the network; removing the set of nodes in the strong local community and edges connected to the set of nodes from the network to generate a reduced network; selecting a node in the reduced network as a second source node; generating a second strong local community for the second source node, the second strong local community comprising a second set of nodes; storing the second strong local community as one of the plurality of communities of the network; removing the second set of nodes in the second strong local community from the network to generate a second reduced network; repeating the selecting, generating, storing and removing until a reduced network is generated that comprises only nodes with a degree less than a threshold value; and labeling the set of stored strong local communities as one of a disjoint community structure of the network or an overlapping community structure of the network. | 10. A computer implemented method for operating context-sensitive databases, the method comprising: receiving a user selection of one of a plurality of contexts; determining one or more predefined concepts associated with the one of the plurality of contexts from a representation of a structured web community stored in a database, the structured web community comprising a plurality of contexts, each context comprising a set of content, the set of content included in each context determined using a community finding method based on structural closeness and semantic closeness of the content in the context, each context including an array of predefined concepts generated based on terms extracted from the set content in the context and statistical frequency of occurrence of terms within the set of content in the context, each predefined concept characterized by a pattern of terms derived from the set of content in the context, wherein a plurality of the plurality of contexts are associated together to form a hierarchy of overlapping contexts; associating an advertisement with the one of the plurality of contexts based on the at least one predefined concept; and presenting the advertisement in response to the user selection of the one of the plurality of contexts; wherein determining the set of content in each context using a community finding method based on structural closeness and semantic closeness of the content comprises: selecting a node in a network as a source node; computing a set of local communities for the source node; identifying a set of nodes in the set of local communities having a weight greater than a threshold; generating a strong local community for the source node including only the set of nodes that have a weight greater than the threshold; storing the strong local community as one of a plurality of communities of the network; removing the set of nodes in the strong local community and edges connected to the set of nodes from the network to generate a reduced network; selecting a node in the reduced network as a second source node; generating a second strong local community for the second source node, the second strong local community comprising a second set of nodes; storing the second strong local community as one of the plurality of communities of the network; removing the second set of nodes in the second strong local community from the network to generate a second reduced network; repeating the selecting, generating, storing and removing until a reduced network is generated that comprises only nodes with a degree less than a threshold value; and labeling the set of stored strong local communities as one of a disjoint community structure of the network or an overlapping community structure of the network. 12. The method of claim 10 , wherein the presenting comprises: matching a document retrieved by the user with one of the certain contexts; and providing the advertisement in a context-sensitive Ad Billboard. | 0.904432 |
6,016,380 | 20 | 25 | 20. A computer system for generating a representation of a video program as sequence of edit events to be used by a digital video editor for editing the video program, the computer system comprising: input means for receiving a video edit decision list in a first syntax for a first machine, wherein the video edit decision list comprises a formatted list of computer instructions for an edit controller for assembling the video program, wherein each instruction defines source material and a destination of an edit event; a format template library providing a plurality of format specifiers wherein each format specifier specifies a syntax of an edit decision list for a different machine, including a first format specifier for the first syntax, selecting means, connected to the input means and the format template library, for selecting the first format specifier in the format template library, and generating means for generating, according to the edit decision list and the first format specifier, the representation of the sequence of edit events corresponding to instructions in the video edit decision list. | 20. A computer system for generating a representation of a video program as sequence of edit events to be used by a digital video editor for editing the video program, the computer system comprising: input means for receiving a video edit decision list in a first syntax for a first machine, wherein the video edit decision list comprises a formatted list of computer instructions for an edit controller for assembling the video program, wherein each instruction defines source material and a destination of an edit event; a format template library providing a plurality of format specifiers wherein each format specifier specifies a syntax of an edit decision list for a different machine, including a first format specifier for the first syntax, selecting means, connected to the input means and the format template library, for selecting the first format specifier in the format template library, and generating means for generating, according to the edit decision list and the first format specifier, the representation of the sequence of edit events corresponding to instructions in the video edit decision list. 25. The system of claim 20, further comprising output means for making the sequence of edit events available to a digital video editor. | 0.884021 |
7,606,718 | 19 | 26 | 19. A system for processing an interaction with a person, comprising a processor, one or more analyst user interface devices in communication with the processor, and a memory in communication with the processor, the memory storing programming instructions executable by the processor to: receive data representing an utterance from the person; automatically present the utterance in perceptible form to two or more intent analysts at substantially the same time, each through a respective one of the analyst user interface devices; accept intent input from each of the two or more intent analysts through the respective analyst user interface device, where the intent input characterizes the intent analyst's interpretation of the person's intent expressed in the utterance, but does not directly indicate to the system any information that is to be communicated to the person; when the two or more intent analysts provide intent input that characterizes different intents: automatically present the utterance in perceptible form to at least one additional intent analyst through at least one additional analyst user interface device; and accept further intent input from the at least one additional intent analyst through the at least one additional analyst user interface device, where the further intent input characterizes the at least one additional intent analyst's interpretation of the person's intent expressed in the utterance, and where the further intent input does not directly indicate to the system any information that is to be communicated to the person; and automatically communicate a message to the person, in perceptible form and in substantially real time relative to the receiving function, the message being selected as a function of the intent input and the further intent input. | 19. A system for processing an interaction with a person, comprising a processor, one or more analyst user interface devices in communication with the processor, and a memory in communication with the processor, the memory storing programming instructions executable by the processor to: receive data representing an utterance from the person; automatically present the utterance in perceptible form to two or more intent analysts at substantially the same time, each through a respective one of the analyst user interface devices; accept intent input from each of the two or more intent analysts through the respective analyst user interface device, where the intent input characterizes the intent analyst's interpretation of the person's intent expressed in the utterance, but does not directly indicate to the system any information that is to be communicated to the person; when the two or more intent analysts provide intent input that characterizes different intents: automatically present the utterance in perceptible form to at least one additional intent analyst through at least one additional analyst user interface device; and accept further intent input from the at least one additional intent analyst through the at least one additional analyst user interface device, where the further intent input characterizes the at least one additional intent analyst's interpretation of the person's intent expressed in the utterance, and where the further intent input does not directly indicate to the system any information that is to be communicated to the person; and automatically communicate a message to the person, in perceptible form and in substantially real time relative to the receiving function, the message being selected as a function of the intent input and the further intent input. 26. The system of claim 19 , wherein the number is automatically increased when the load factor is lower than a predetermined threshold. | 0.794562 |
8,086,038 | 6 | 7 | 6. A computer-implemented method for generating and storing invisible junctions, the method comprising: receiving, with a processor, an electronic document; applying, with the processor, a distance transformation to the electronic document to generate a distance transform; detecting, with the processor, a skeleton in the distance transform; determining, with the processor, junction points in the skeleton as the invisible junctions, the junction points having a distance transformation value based on the distance transform; determining, with the processor, a junction size for at least one junction point, the junction size based at least in part on the distance transformation value; extracting, with the processor, an invisible junction feature descriptor from the electronic document for each invisible junction, the invisible junction feature descriptor including the including the junction size; creating, with the processor, a feature index from the invisible junction feature descriptors; and storing the feature index. | 6. A computer-implemented method for generating and storing invisible junctions, the method comprising: receiving, with a processor, an electronic document; applying, with the processor, a distance transformation to the electronic document to generate a distance transform; detecting, with the processor, a skeleton in the distance transform; determining, with the processor, junction points in the skeleton as the invisible junctions, the junction points having a distance transformation value based on the distance transform; determining, with the processor, a junction size for at least one junction point, the junction size based at least in part on the distance transformation value; extracting, with the processor, an invisible junction feature descriptor from the electronic document for each invisible junction, the invisible junction feature descriptor including the including the junction size; creating, with the processor, a feature index from the invisible junction feature descriptors; and storing the feature index. 7. The method of claim 6 , wherein storing the feature index comprises storing the feature index in a database. | 0.950885 |
8,769,454 | 1 | 8 | 1. A method for register-transfer level (RTL) design checking for exploring simulation mismatches, synthesis mismatches, or ambiguous language semantics associated with generating a derived design from RTL design code, the method comprising: providing the RTL design code, to at least one processor, to generate an internal representation for verification of an electronic circuit design; comparing, by a design match engine, the RTL design code with design violation patterns contained in a design violation pattern database, wherein the design violation patterns identify violations relating to the simulation mismatches, synthesis mismatches, or ambiguous language semantics associated with generating the derived design that are otherwise undetected during equivalence checking between the derived design and the RTL design code; assigning a rule object to a design pattern in the RTL design code, by the at least one processor, when the design match engine determines that the design pattern in the RTL design code matches one of the design violation patterns in the design violation pattern database; and generating, with the at least one processor, a violation report comprising the rule objects and their corresponding design violation patterns. | 1. A method for register-transfer level (RTL) design checking for exploring simulation mismatches, synthesis mismatches, or ambiguous language semantics associated with generating a derived design from RTL design code, the method comprising: providing the RTL design code, to at least one processor, to generate an internal representation for verification of an electronic circuit design; comparing, by a design match engine, the RTL design code with design violation patterns contained in a design violation pattern database, wherein the design violation patterns identify violations relating to the simulation mismatches, synthesis mismatches, or ambiguous language semantics associated with generating the derived design that are otherwise undetected during equivalence checking between the derived design and the RTL design code; assigning a rule object to a design pattern in the RTL design code, by the at least one processor, when the design match engine determines that the design pattern in the RTL design code matches one of the design violation patterns in the design violation pattern database; and generating, with the at least one processor, a violation report comprising the rule objects and their corresponding design violation patterns. 8. The method of claim 1 , wherein the method further comprises, selecting hi-lighted RTL design code corresponding to one of the rule objects, and graphically displaying on a display the corresponding rule object in the violation report. | 0.817204 |
8,645,370 | 1 | 5 | 1. A computing device for determining relevance of a document to a text string, the document containing text and images, the text and the text string having terms, the document having a layout when the document is rendered, comprising: a memory storing computer-executable instructions implementing a component that, for each of a plurality of images contained in the document, identifies text associated with the image by extracting from the document that portion of the text that is determined to be adjacent to the image based on analysis of the layout of the document when the document is rendered; a component that, for each of the plurality of images, calculates a text score indicating relevance of the identified text associated with the image to the text string based on comparison of terms of the identified text to terms of the text string; and a component that determines relevance of the document to the text string based on the calculated the text score indicating relevance of the identified text associated with each of the plurality of the images to the text string and factoring in an image importance score for each of the plurality of images that indicates importance of the image to the document; and a processor for executing the instructions stored in the memory. | 1. A computing device for determining relevance of a document to a text string, the document containing text and images, the text and the text string having terms, the document having a layout when the document is rendered, comprising: a memory storing computer-executable instructions implementing a component that, for each of a plurality of images contained in the document, identifies text associated with the image by extracting from the document that portion of the text that is determined to be adjacent to the image based on analysis of the layout of the document when the document is rendered; a component that, for each of the plurality of images, calculates a text score indicating relevance of the identified text associated with the image to the text string based on comparison of terms of the identified text to terms of the text string; and a component that determines relevance of the document to the text string based on the calculated the text score indicating relevance of the identified text associated with each of the plurality of the images to the text string and factoring in an image importance score for each of the plurality of images that indicates importance of the image to the document; and a processor for executing the instructions stored in the memory. 5. The computing device of claim 1 wherein the component that determines relevance of the document to the text string is further based on relevance of text content of the document to the text string. | 0.512255 |
7,725,869 | 4 | 6 | 4. A method of modeling multiple instances of an electronic circuit, comprising: defining, using a computer, a program using an imperative programming language; wherein said program includes multiple calls to a function, said function having a persistent variable associated with an internal state of said electronic circuit; and wherein said function is configured to initialize said persistent variable based on at least one call path to said function in said program and to maintain a first lookup table and a second lookup table; wherein said first lookup table includes values of said persistent variable respectively associated with keys, each of said keys being defined by a call path to said function in said program and a name of said persistent variable; wherein said second lookup table includes a last call path value associated with a key, said last call path variable being indicative of a last call path to said function in said program, said key being defined by said name of said persistent variable and a name of said function; and wherein said function is further configured to, for each of said multiple calls: access said second lookup table to obtain said last call path value; store a current value of said persistent variable in said first lookup table using a current key defined by said last call path value and said name of said persistent variable; and update said last call path value in said second lookup table to refer to a current call path to said function in said program. | 4. A method of modeling multiple instances of an electronic circuit, comprising: defining, using a computer, a program using an imperative programming language; wherein said program includes multiple calls to a function, said function having a persistent variable associated with an internal state of said electronic circuit; and wherein said function is configured to initialize said persistent variable based on at least one call path to said function in said program and to maintain a first lookup table and a second lookup table; wherein said first lookup table includes values of said persistent variable respectively associated with keys, each of said keys being defined by a call path to said function in said program and a name of said persistent variable; wherein said second lookup table includes a last call path value associated with a key, said last call path variable being indicative of a last call path to said function in said program, said key being defined by said name of said persistent variable and a name of said function; and wherein said function is further configured to, for each of said multiple calls: access said second lookup table to obtain said last call path value; store a current value of said persistent variable in said first lookup table using a current key defined by said last call path value and said name of said persistent variable; and update said last call path value in said second lookup table to refer to a current call path to said function in said program. 6. The method of claim 4 , wherein said function is further configured to, for each of said multiple calls: form a new key from said current call path and said name of said persistent variable; and access said first lookup table using said new key to obtain a new value for said persistent variable. | 0.725688 |
9,424,597 | 5 | 13 | 5. A method comprising: receiving, at an ecommerce service, text from a first user, the text in a first language and pertaining to a first listing on the ecommerce service; retrieving contextual information about the first listing; translating the text to a second language; locating, in a database, a plurality of text objects, in the second language, similar to the translated text, each text object comprising textual information pertaining to at least one listing; ranking the plurality of text objects similar to the translated text based on a comparison of the contextual information about the first listing and contextual information stored in the database for the listings corresponding to the plurality of text objects similar to the translated text; translating at least one of the ranked plurality of text objects to the first language; presenting a subset of the ranked plurality of text objects to the first user; receiving feedback from the first user; selecting one of the subset of the ranked plurality of text objects based on the feedback; and using the selected text object in the ecommerce service. | 5. A method comprising: receiving, at an ecommerce service, text from a first user, the text in a first language and pertaining to a first listing on the ecommerce service; retrieving contextual information about the first listing; translating the text to a second language; locating, in a database, a plurality of text objects, in the second language, similar to the translated text, each text object comprising textual information pertaining to at least one listing; ranking the plurality of text objects similar to the translated text based on a comparison of the contextual information about the first listing and contextual information stored in the database for the listings corresponding to the plurality of text objects similar to the translated text; translating at least one of the ranked plurality of text objects to the first language; presenting a subset of the ranked plurality of text objects to the first user; receiving feedback from the first user; selecting one of the subset of the ranked plurality of text objects based on the feedback; and using the selected text object in the ecommerce service. 13. The method of claim 5 , wherein the translating the text to a second language and the translating at least one of the ranked plurality of text objects to the first language both utilize a single translation module. | 0.738609 |
7,574,659 | 18 | 19 | 18. A search engine method, comprising: storing records relating to a content of a plurality of information resources at a first database; storing records relating to commercial messages at a second database; persistently storing an identifier; receiving a search query and automatically defining in dependence thereon a query of the first database to retrieve hyperlinked identifiers of records of the first database corresponding to the search query, and a selection of records from the second database to define hyperlinked identifiers of records of the second database relating to commercial messages associated with at least one of the search query and the persistent identifier; automatically organizing the identifiers of records from the first database together with the identifiers of records from the second database in a common output, in further dependence on the stored identifier; wherein the step of automatically organizing comprises: defining a hierarchy from the hyperlinked identifiers of records of said first database corresponding to said search query according to content of or linkage among the hyperlinked identifiers of records of said first database and inserting the hyperlinked identifiers of records of said second database relating to commercial messages associated with at least one of said search query and said persistent identifier into the hierarchy according to content of or linkage between the hyperlinked identifiers of records of said second database and the hyperlinked identifiers of records of said first database; and automatically recording accounting information for at least one of a presentation and a selection of an identifier of a record from the second database with respect to an account maintained by an entity relating to a corresponding commercial message. | 18. A search engine method, comprising: storing records relating to a content of a plurality of information resources at a first database; storing records relating to commercial messages at a second database; persistently storing an identifier; receiving a search query and automatically defining in dependence thereon a query of the first database to retrieve hyperlinked identifiers of records of the first database corresponding to the search query, and a selection of records from the second database to define hyperlinked identifiers of records of the second database relating to commercial messages associated with at least one of the search query and the persistent identifier; automatically organizing the identifiers of records from the first database together with the identifiers of records from the second database in a common output, in further dependence on the stored identifier; wherein the step of automatically organizing comprises: defining a hierarchy from the hyperlinked identifiers of records of said first database corresponding to said search query according to content of or linkage among the hyperlinked identifiers of records of said first database and inserting the hyperlinked identifiers of records of said second database relating to commercial messages associated with at least one of said search query and said persistent identifier into the hierarchy according to content of or linkage between the hyperlinked identifiers of records of said second database and the hyperlinked identifiers of records of said first database; and automatically recording accounting information for at least one of a presentation and a selection of an identifier of a record from the second database with respect to an account maintained by an entity relating to a corresponding commercial message. 19. The method according to claim 18 , wherein the common output comprises an hierarchal organizational structure in graphic format, and wherein the hierarchal organizational structure is automatically generated based on a content of or linkage between records. | 0.885022 |
9,781,178 | 1 | 4 | 1. A method comprising: generating a template for a publication, the template including a plurality of content frames, a portion of the plurality of content frames being prepopulated with content, the remainder of the plurality of content frames providing an empty placeholder for populating content; receiving a content item from a first user of a group of users designated as contributors to the publication; receiving, from a second user of the group of users designated as contributors to the publication, rating information comprising a first rating for the content item and a second rating for a placement of the content item within a particular content frame from among the remainder of the plurality of content frames; and generating the publication using the template and the received content item, the generating of the publication including determining placement of the content item in one of the remainder of the plurality of content frames based on the first and second ratings received from the second user. | 1. A method comprising: generating a template for a publication, the template including a plurality of content frames, a portion of the plurality of content frames being prepopulated with content, the remainder of the plurality of content frames providing an empty placeholder for populating content; receiving a content item from a first user of a group of users designated as contributors to the publication; receiving, from a second user of the group of users designated as contributors to the publication, rating information comprising a first rating for the content item and a second rating for a placement of the content item within a particular content frame from among the remainder of the plurality of content frames; and generating the publication using the template and the received content item, the generating of the publication including determining placement of the content item in one of the remainder of the plurality of content frames based on the first and second ratings received from the second user. 4. The method of claim 1 , wherein the group of users designated as contributors to the publication is defined by contribution privilege information associated with the template, the contribution privilege information specifying a manner in which each member of the group of users may contribute to each element of the publication. | 0.732201 |
9,998,342 | 1 | 11 | 1. A method for generating a graph segment providing a gist or summary of an online social network conversation, the method comprising: generating, by a processor, a graph of the online social network conversation, wherein the graph of the online social network conversation comprises a plurality of nodes and each node connecting at least one other node by an edge, each node representing a message of the online social network conversation and each edge corresponding to an action by a participant in the online social network conversation; determining, by the processor, an edge weight for each edge; analyzing, by the processor, the graph of the online social network conversation, by the processor, using at least the edge weight of at least some of the edges; and generating, by the processor, a graph segment comprising a reduced number of nodes of the graph of the online social network conversation based on analyzing the graph of the online social network conversation and the graph segment providing a gist or summary comprising an abbreviated view of the online social network conversation based on the analysis, each node of the reduced number of nodes corresponding to its own respective node of the graph of the online social network conversation. | 1. A method for generating a graph segment providing a gist or summary of an online social network conversation, the method comprising: generating, by a processor, a graph of the online social network conversation, wherein the graph of the online social network conversation comprises a plurality of nodes and each node connecting at least one other node by an edge, each node representing a message of the online social network conversation and each edge corresponding to an action by a participant in the online social network conversation; determining, by the processor, an edge weight for each edge; analyzing, by the processor, the graph of the online social network conversation, by the processor, using at least the edge weight of at least some of the edges; and generating, by the processor, a graph segment comprising a reduced number of nodes of the graph of the online social network conversation based on analyzing the graph of the online social network conversation and the graph segment providing a gist or summary comprising an abbreviated view of the online social network conversation based on the analysis, each node of the reduced number of nodes corresponding to its own respective node of the graph of the online social network conversation. 11. The method of claim 1 , wherein analyzing the graph of the online social network conversation comprises determining a longest path or thread of the online social network conversation. | 0.897814 |
9,280,610 | 17 | 19 | 17. A system, comprising: one or more processors; and memory storing instructions, the instructions, when executed by the one or more processors, cause the processors to perform operations comprising: receiving a user request from a mobile client device, the user request including at least a speech input and seeks an informational answer or performance of a task; detecting a failure to provide a satisfactory response to the user request; in response to detecting the failure, crowd-sourcing information relevant to the user request by querying one or more crowd sourcing information sources; receiving one or more answers from the crowd sourcing information sources; and generating a response to the user request based on at least one of the one or more answers received from the one or more crowd sourcing information sources. | 17. A system, comprising: one or more processors; and memory storing instructions, the instructions, when executed by the one or more processors, cause the processors to perform operations comprising: receiving a user request from a mobile client device, the user request including at least a speech input and seeks an informational answer or performance of a task; detecting a failure to provide a satisfactory response to the user request; in response to detecting the failure, crowd-sourcing information relevant to the user request by querying one or more crowd sourcing information sources; receiving one or more answers from the crowd sourcing information sources; and generating a response to the user request based on at least one of the one or more answers received from the one or more crowd sourcing information sources. 19. The system of claim 17 , wherein the crowd-sourcing further comprises identifying, from a set of crowd sourcing information sources, the one or more crowd sourcing information sources to be queried. | 0.812268 |
8,112,708 | 5 | 7 | 5. A method of populating a predictive text dictionary according to claim 1 , further comprising: discarding at least one of the words in said predictive text dictionary of said handheld electronic device. | 5. A method of populating a predictive text dictionary according to claim 1 , further comprising: discarding at least one of the words in said predictive text dictionary of said handheld electronic device. 7. A method of populating a predictive text dictionary according to claim 5 , further comprising: determining said at least one of said words in said predictive text dictionary based on an expiry date associated with the words. | 0.871606 |
9,715,491 | 1 | 4 | 1. A method, comprising: receiving a signal associated with a portion of a document; determining a meaning of the portion by interpreting a concept represented by text within the portion; selecting a document template based on the portion, the document template being associated with at least one document type; preparing the portion of the document for comparison with the document template by aligning a section of the portion of the document with the document template; analyzing the meaning with respect to a condition associated with the at least one document type based on a policy preference associated with the document template, the policy preference including an indication of the condition and an indication of a recommendation associated with the condition; and sending the indication of the recommendation to an entity in response to the meaning satisfying the condition. | 1. A method, comprising: receiving a signal associated with a portion of a document; determining a meaning of the portion by interpreting a concept represented by text within the portion; selecting a document template based on the portion, the document template being associated with at least one document type; preparing the portion of the document for comparison with the document template by aligning a section of the portion of the document with the document template; analyzing the meaning with respect to a condition associated with the at least one document type based on a policy preference associated with the document template, the policy preference including an indication of the condition and an indication of a recommendation associated with the condition; and sending the indication of the recommendation to an entity in response to the meaning satisfying the condition. 4. The method of claim 1 , wherein the receiving includes receiving in response to a request to access content associated with the document. | 0.913259 |
9,020,932 | 11 | 14 | 11. The system of claim 10 , wherein the processing unit, when executing the program instructions stored on the computer-readable storage medium via the computer readable memory, further identifies the generic occupational identity search data that is associated with occupational identity indicia that is common to the user and at least one other user having the common occupational identity indicia by: recognizing a type of network access used by the user to submit the text string query; determining a predominant occupational identity associated with the recognized type of network access; and retrieving search history common to pluralities of users that share the determined predominant occupational identity as the generic occupational identity search data. | 11. The system of claim 10 , wherein the processing unit, when executing the program instructions stored on the computer-readable storage medium via the computer readable memory, further identifies the generic occupational identity search data that is associated with occupational identity indicia that is common to the user and at least one other user having the common occupational identity indicia by: recognizing a type of network access used by the user to submit the text string query; determining a predominant occupational identity associated with the recognized type of network access; and retrieving search history common to pluralities of users that share the determined predominant occupational identity as the generic occupational identity search data. 14. The system of claim 11 , wherein the processing unit, when executing the program instructions stored on the computer-readable storage medium via the computer readable memory, displays the primary set of search results, the secondary set of search results and the set of peripheral knowledge articles to the user in the different, respective tabbed sheets that are nested on top of one another in a web-based interface dashboard, by: displaying a list of the primary set of results to the user in a primary tabbed sheet of the nested tabbed sheets; listing the secondary set of search results in a secondary tabbed sheet of the nested tabbed sheets, wherein the list of the secondary set of search results is nested behind the primary tabbed sheet and not visible to the user unless selected by the user; and listing the set of peripheral search results in a peripheral tabbed sheet of the nested tabbed sheets, wherein the list of the set of peripheral search results is nested behind the primary and secondary tabbed sheets and not visible to the user unless selected by the user; and wherein selection of one of the secondary tabbed sheet and the peripheral tabbed sheet by the user via a graphical user interface cursor routine causes the processing unit to display the list of results of the selected one of the secondary tabbed sheet and the peripheral tabbed sheet in a tabbed sheet display above each of other unselected ones of the primary tabbed sheet, the secondary tabbed sheet and the peripheral tabbed sheet. | 0.748433 |
8,054,317 | 3 | 4 | 3. The method of claim 1 , wherein the distance of each color theme of the collection of color themes from the identified color theme is based at least in part on determination of color-to-color distances of each color of the identified color theme to a color of the color theme of the collection, wherein each color-to-color distance uses a different color of the color theme of the collection. | 3. The method of claim 1 , wherein the distance of each color theme of the collection of color themes from the identified color theme is based at least in part on determination of color-to-color distances of each color of the identified color theme to a color of the color theme of the collection, wherein each color-to-color distance uses a different color of the color theme of the collection. 4. The method of claim 3 , wherein determination of color-to-color distances comprises: a first determination of a first closest color of the color theme of the collection to a first color of the identified color theme, the first determination comprising comparing the first color of the identified color theme with each color of the color theme of the collection; and a second determination of a second closest color of the color theme of the collection to a second color of the identified color theme, the second determination comprising comparing the second color of the identified color theme with each color of the color theme of the collection except the first closest color. | 0.694345 |
9,501,467 | 1 | 2 | 1. A computer-implemented method comprising: accessing a preexisting entity list; analyzing by a computer a first document to detect an entity, the entity comprising a person, place, or organization, the first document being associated with a current legal event; resolving the entity with the preexisting entity list and: upon determining by the computer the entity is not present in the preexisting entity list, adding the entity to the preexisting entity list and generating a first set of relationship data associated with the relationship between the first document, the current legal event, and the entity, the first set of relationship data further comprising a set of information associated with the relationship between the entity and the current legal event; or upon determining by the computer the entity is present in the preexisting entity list, generating a first set of relationship data associated with a relationship between the first document and the entity, the first set of relationship data further comprising a set of information associated with the relationship between the entity and the current legal event; repeating the resolving step for each distinct entity detected in the first document; generating a second set of relationship data representing the relationship between the entity and a professional support resource comprising tools for creating and editing a work product document, the work product document comprising a reference to at least one of the resolved entities; storing the first and second sets of relationship data in a memory associated with the computer; displaying a user interface to allow a user to select from a set of professional support resources; associating the reference to the at least one resolved entity with a smart tag; and editing the work product document in response to a signal representing a user input associated with the professional support resource and related to the smart tag. | 1. A computer-implemented method comprising: accessing a preexisting entity list; analyzing by a computer a first document to detect an entity, the entity comprising a person, place, or organization, the first document being associated with a current legal event; resolving the entity with the preexisting entity list and: upon determining by the computer the entity is not present in the preexisting entity list, adding the entity to the preexisting entity list and generating a first set of relationship data associated with the relationship between the first document, the current legal event, and the entity, the first set of relationship data further comprising a set of information associated with the relationship between the entity and the current legal event; or upon determining by the computer the entity is present in the preexisting entity list, generating a first set of relationship data associated with a relationship between the first document and the entity, the first set of relationship data further comprising a set of information associated with the relationship between the entity and the current legal event; repeating the resolving step for each distinct entity detected in the first document; generating a second set of relationship data representing the relationship between the entity and a professional support resource comprising tools for creating and editing a work product document, the work product document comprising a reference to at least one of the resolved entities; storing the first and second sets of relationship data in a memory associated with the computer; displaying a user interface to allow a user to select from a set of professional support resources; associating the reference to the at least one resolved entity with a smart tag; and editing the work product document in response to a signal representing a user input associated with the professional support resource and related to the smart tag. 2. The method of claim 1 , wherein the detected entity is selected from the group consisting of: attorney names, judge names, courts, names of parties to a lawsuit, expert names, witness names, and law firm names. | 0.884239 |
8,046,221 | 16 | 17 | 16. A spoken dialog system that applies a multi-state barge-in acoustic model, the system comprising: a module configured to present prompt to a user; a module configured to receive an audio speech input from the user during a presentation prompt; a module configured to accumulate the audio speech input from the user; a module configured to apply a non-speech component having at least two one-state Hidden Markov Models (HMMs) and two three-state left-to-right HMMs; and a module configured to apply a non-speech component having at least two one-state Hidden Markov Models (HMMs) to the audio speech input from the user; a module configured to apply a speech component having at least five three-state HMMs to the audio speech input from the user, wherein each of the five three-state HMMs represents a different phonetic category; a module configured to determine whether the audio speech input is a barge-in-speech input from the user; and a module configured, if the audio speech input is determined to be the barge-in-speech input from the user, to terminate the presentation of the prompt. | 16. A spoken dialog system that applies a multi-state barge-in acoustic model, the system comprising: a module configured to present prompt to a user; a module configured to receive an audio speech input from the user during a presentation prompt; a module configured to accumulate the audio speech input from the user; a module configured to apply a non-speech component having at least two one-state Hidden Markov Models (HMMs) and two three-state left-to-right HMMs; and a module configured to apply a non-speech component having at least two one-state Hidden Markov Models (HMMs) to the audio speech input from the user; a module configured to apply a speech component having at least five three-state HMMs to the audio speech input from the user, wherein each of the five three-state HMMs represents a different phonetic category; a module configured to determine whether the audio speech input is a barge-in-speech input from the user; and a module configured, if the audio speech input is determined to be the barge-in-speech input from the user, to terminate the presentation of the prompt. 17. The system of claim 16 , wherein each of the phonetic categories comprises vowels and glides, unvoiced fricatives, voiced fricatives, other consonants and nasals. | 0.621005 |
7,984,074 | 6 | 7 | 6. The computer program product of claim 1 wherein the data structure is responsive to an agent component corresponding to the defined new entity category, such that the agent components corresponding an existing entity category are predefined. | 6. The computer program product of claim 1 wherein the data structure is responsive to an agent component corresponding to the defined new entity category, such that the agent components corresponding an existing entity category are predefined. 7. The computer program product of claim 6 wherein the object to be deployed is a connectivity device in a storage area network, the connectivity device operable to provide connectivity between a set of storage arrays and an infrastructure server for accessing data in the storage array. | 0.920278 |
9,547,628 | 8 | 9 | 8. An apparatus for automatically improving legibility based on preferred font characteristics comprising: a computer having one or more processors; a non-transitory storage medium comprising instructions, that when executed by the one or more processors, cause the apparatus to: determine a plurality of preferences regarding a plurality of font size characteristics of sample text, wherein the plurality of preferences comprises a preferred height, a preferred weight, and a preferred condensation; adjust an initial zoom level of text of an electronic document to a first zoom level based on the preferred height; adjust the first zoom level of the text to a second zoom level based on the preferred weight; adjust the second zoom level to a final zoom level based on the preferred condensation; and display the text of the electronic document at the final zoom level based on the plurality of preferences. | 8. An apparatus for automatically improving legibility based on preferred font characteristics comprising: a computer having one or more processors; a non-transitory storage medium comprising instructions, that when executed by the one or more processors, cause the apparatus to: determine a plurality of preferences regarding a plurality of font size characteristics of sample text, wherein the plurality of preferences comprises a preferred height, a preferred weight, and a preferred condensation; adjust an initial zoom level of text of an electronic document to a first zoom level based on the preferred height; adjust the first zoom level of the text to a second zoom level based on the preferred weight; adjust the second zoom level to a final zoom level based on the preferred condensation; and display the text of the electronic document at the final zoom level based on the plurality of preferences. 9. The apparatus of claim 8 , wherein the preferred height, the preferred weight, and the preferred condensation are measured in pixels. | 0.891892 |
9,135,915 | 1 | 3 | 1. A method, comprising: receiving audio data representative of audio detected by a microphone, wherein the microphone is positioned on a head-mountable device (HMD); determining whether the received audio data comprises audio speech data in an audio-channel speech band or audio non-speech data outside the audio-channel speech band; receiving vibration data representative of vibrations detected by a sensor other than the microphone, wherein the sensor is positioned on the HMD; determining a degree of spectral coherency, with respect to a threshold, between the audio data and the vibration data; determining whether or not the audio data is causally related to the vibration data based on the determined degree of spectral coherency; and if the received audio data both: (a) comprises audio speech data in an audio-channel speech band and (b) is determined to be causally related to the vibration data based on the degree of spectral coherency, then generating an indication that the audio data contains HMD-wearer speech and conditioning at least one of the audio data and the vibration data as speech data, wherein the conditioning comprises amplifying at least one of the audio data and the vibration data; if the received audio data both: (a) comprises audio non-speech data outside the audio-channel speech band and (b) is determined to be causally related to the vibration data based on the degree of spectral coherency, then conditioning at least one of the audio data and the vibration data as coherent non-speech data, wherein the conditioning comprises removing or replacing non-speech data from at least one of the audio data and the vibration data; and otherwise, determining that the received audio data and the vibration data are non-coherent and conditioning at least one of the audio data and the vibration data as non-speech data, wherein the conditioning comprises removing or replacing non-speech data from at least one of the audio data and the vibration data. | 1. A method, comprising: receiving audio data representative of audio detected by a microphone, wherein the microphone is positioned on a head-mountable device (HMD); determining whether the received audio data comprises audio speech data in an audio-channel speech band or audio non-speech data outside the audio-channel speech band; receiving vibration data representative of vibrations detected by a sensor other than the microphone, wherein the sensor is positioned on the HMD; determining a degree of spectral coherency, with respect to a threshold, between the audio data and the vibration data; determining whether or not the audio data is causally related to the vibration data based on the determined degree of spectral coherency; and if the received audio data both: (a) comprises audio speech data in an audio-channel speech band and (b) is determined to be causally related to the vibration data based on the degree of spectral coherency, then generating an indication that the audio data contains HMD-wearer speech and conditioning at least one of the audio data and the vibration data as speech data, wherein the conditioning comprises amplifying at least one of the audio data and the vibration data; if the received audio data both: (a) comprises audio non-speech data outside the audio-channel speech band and (b) is determined to be causally related to the vibration data based on the degree of spectral coherency, then conditioning at least one of the audio data and the vibration data as coherent non-speech data, wherein the conditioning comprises removing or replacing non-speech data from at least one of the audio data and the vibration data; and otherwise, determining that the received audio data and the vibration data are non-coherent and conditioning at least one of the audio data and the vibration data as non-speech data, wherein the conditioning comprises removing or replacing non-speech data from at least one of the audio data and the vibration data. 3. The method of claim 1 , further comprising: in response to determining that the audio speech data is causally related to the vibration speech data, providing at least the audio speech data to a speech recognizer. | 0.770299 |
8,682,932 | 16 | 25 | 16. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing-devices, cause performance of: generating an index mapping data objects to terms associated with the data objects; generating a graph describing hierarchical relationships between each of the data objects; receiving a search request comprising a plurality of search terms; based on the index, calculating multiple candidate sets of data objects by, for each particular term in the plurality of search terms, identifying a particular candidate set of data objects that are mapped to the particular term; calculating priority scores for at least the data objects in the candidate sets based at least in part on one or more of: a link analysis of the graph; or metadata describing structural constraints upon the data objects; based on the graph, identifying one or more search result subgraphs, wherein each particular subgraph of the one or more search result subgraphs is a hierarchy of data objects that comprises, for each particular term, at least one data object mapped to the particular term in the index; wherein identifying the one or more search result subgraphs comprises investigating the hierarchical relationships described by the graph, in an order that is based on the priority scores, to locate at least one ancestor object that, for each particular candidate set, is the same as, or an ancestor of, at least one member object of that particular candidate set; providing information indicating the one or more search result subgraphs in response to the search request. | 16. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing-devices, cause performance of: generating an index mapping data objects to terms associated with the data objects; generating a graph describing hierarchical relationships between each of the data objects; receiving a search request comprising a plurality of search terms; based on the index, calculating multiple candidate sets of data objects by, for each particular term in the plurality of search terms, identifying a particular candidate set of data objects that are mapped to the particular term; calculating priority scores for at least the data objects in the candidate sets based at least in part on one or more of: a link analysis of the graph; or metadata describing structural constraints upon the data objects; based on the graph, identifying one or more search result subgraphs, wherein each particular subgraph of the one or more search result subgraphs is a hierarchy of data objects that comprises, for each particular term, at least one data object mapped to the particular term in the index; wherein identifying the one or more search result subgraphs comprises investigating the hierarchical relationships described by the graph, in an order that is based on the priority scores, to locate at least one ancestor object that, for each particular candidate set, is the same as, or an ancestor of, at least one member object of that particular candidate set; providing information indicating the one or more search result subgraphs in response to the search request. 25. The one or more non-transitory computer-readable media of claim 16 , wherein the priority scores are based on the metadata, the method further comprising: generating a metadata graph describing relationships between each metadata item of the metadata; performing the link analysis of the metadata graph to calculate relationship scores for the metadata items; calculating the priority score for each particular data object based in part on the relationship score of a particular metadata item corresponding to the particular data object. | 0.539182 |
9,779,133 | 1 | 2 | 1. A computer-implemented method for testing Structured Query Language (SQL) queries in a software application during application development, the method comprising: executing, in a debug mode, a database-accessing software application including a main program written in a non-SQL programming language and, embedded in the main program, an SQL query, the debug mode specifying a breakpoint in the main program that is associated with the SQL query, the SQL query comprising at least one unresolved parameter having a value that is unresolved in the SQL query itself and is determinable during execution of the main program; copying the SQL query associated with the breakpoint, in response to user selection of the SQL query in a program editor upon reaching the breakpoint, from the program editor into an SQL console; and by the SQL console, resolving the at least one unresolved parameter based on the execution of the main program; by the SQL console, parsing the SQL query to extract a source part and a result part from the SQL query, and automatically determining a data type definition and data declaration based on the extracted source part and result part and identifying one or more tables accessible by the SQL query based on the source part; determining that a user has authority to access the one or more tables and, following the determination, causing execution of the SQL query, separately from the execution of the main program, by generating and causing execution of a dynamic subroutine with the determined data type definition and data declaration to thereby retrieve data from a database in accordance with the SQL query; and displaying the retrieved data to the user. | 1. A computer-implemented method for testing Structured Query Language (SQL) queries in a software application during application development, the method comprising: executing, in a debug mode, a database-accessing software application including a main program written in a non-SQL programming language and, embedded in the main program, an SQL query, the debug mode specifying a breakpoint in the main program that is associated with the SQL query, the SQL query comprising at least one unresolved parameter having a value that is unresolved in the SQL query itself and is determinable during execution of the main program; copying the SQL query associated with the breakpoint, in response to user selection of the SQL query in a program editor upon reaching the breakpoint, from the program editor into an SQL console; and by the SQL console, resolving the at least one unresolved parameter based on the execution of the main program; by the SQL console, parsing the SQL query to extract a source part and a result part from the SQL query, and automatically determining a data type definition and data declaration based on the extracted source part and result part and identifying one or more tables accessible by the SQL query based on the source part; determining that a user has authority to access the one or more tables and, following the determination, causing execution of the SQL query, separately from the execution of the main program, by generating and causing execution of a dynamic subroutine with the determined data type definition and data declaration to thereby retrieve data from a database in accordance with the SQL query; and displaying the retrieved data to the user. 2. The method of claim 1 , wherein the SQL query comprises at least one of a select statement, a create statement, a delete statement, or an update statement. | 0.880845 |
7,853,587 | 10 | 13 | 10. The system of claim 1 , wherein the at least one filter includes one or more of a query filter, a punctuation filter, a title filter, and a similarity filter. | 10. The system of claim 1 , wherein the at least one filter includes one or more of a query filter, a punctuation filter, a title filter, and a similarity filter. 13. The system of claim 10 , wherein the similarity filter is configured to generate an index associated with snippets in the search result summary and examine a current snippet to determine if the current snippet should be discarded based in part on an examination of the index. | 0.913729 |
8,316,394 | 39 | 40 | 39. The method of claim 1 , further comprising selecting, in response to determining that the filtered plurality of video assets is empty, supplementary information for display in the first cell. | 39. The method of claim 1 , further comprising selecting, in response to determining that the filtered plurality of video assets is empty, supplementary information for display in the first cell. 40. The method of claim 39 , wherein the supplementary information includes a message about the current or future availability of an additional plurality of video assets. | 0.929694 |
10,135,887 | 13 | 15 | 13. A system comprising: a memory storage; and one or more processing units coupled to the memory storage, wherein the one or more processing units are operable to: receive a piece of source video content; receive a selection to share annotations with a group of users who have access to the source video content; receive an indication to record a first annotation comprising a video annotation having an audio track at a location in the source video content, wherein the location comprises an annotation linkage location; create metadata associating the first annotation to the location in the source video content; receive a new annotation associated with the first annotation and the location in the source video content; create metadata associating the new annotation with the first annotation and the location in the source video content; convert the audio track of the video annotation to text to enable display of the text of the converted audio track and preclude simultaneous audio track playback; notify one or more users of the group of users that the annotations are shared and that the first annotation and the new annotation are associated with the source video content; control interaction with the annotations according to varying levels of control that include controlling which of the one or more users can access the annotations and which of the one or more users can create associated annotations; request a list of annotation linkage locations for annotations associated with the source video content prior to playback of the source video content including annotation linkage locations associated with the new annotation and the first annotation; enable a display of the first annotation and the new annotation synchronously with playback of the source video content with the simultaneous audio track playback according to an optimal viewing format; enable a display the first annotation and the new annotation synchronously with playback of the source video content absent the simultaneous audio track playback according to a different optimal viewing format; and store the first annotation, the new annotation, and the associated metadata, wherein the associated metadata includes annotation metadata comprising a list of points in the source video content and a link to one or more annotations associated with each point including a timestamp, a frame marker, a chapter marker, or another annotation. | 13. A system comprising: a memory storage; and one or more processing units coupled to the memory storage, wherein the one or more processing units are operable to: receive a piece of source video content; receive a selection to share annotations with a group of users who have access to the source video content; receive an indication to record a first annotation comprising a video annotation having an audio track at a location in the source video content, wherein the location comprises an annotation linkage location; create metadata associating the first annotation to the location in the source video content; receive a new annotation associated with the first annotation and the location in the source video content; create metadata associating the new annotation with the first annotation and the location in the source video content; convert the audio track of the video annotation to text to enable display of the text of the converted audio track and preclude simultaneous audio track playback; notify one or more users of the group of users that the annotations are shared and that the first annotation and the new annotation are associated with the source video content; control interaction with the annotations according to varying levels of control that include controlling which of the one or more users can access the annotations and which of the one or more users can create associated annotations; request a list of annotation linkage locations for annotations associated with the source video content prior to playback of the source video content including annotation linkage locations associated with the new annotation and the first annotation; enable a display of the first annotation and the new annotation synchronously with playback of the source video content with the simultaneous audio track playback according to an optimal viewing format; enable a display the first annotation and the new annotation synchronously with playback of the source video content absent the simultaneous audio track playback according to a different optimal viewing format; and store the first annotation, the new annotation, and the associated metadata, wherein the associated metadata includes annotation metadata comprising a list of points in the source video content and a link to one or more annotations associated with each point including a timestamp, a frame marker, a chapter marker, or another annotation. 15. The system of claim 13 , wherein the one or more processing units are further operable to: receive an indication of a selection to view the source video content and the associated first annotation; and provide the first annotation and associated metadata for display or play of the first annotation, wherein the first annotation is synchronized with the source video content. | 0.768054 |
6,088,042 | 1 | 7 | 1. A method for animating a character figure in a video image memory responsive to stored motion data, said character figure being represented in said memory as having a first plurality of joints and a plurality of links coupled between respective pairs of said first plurality of joints, said plurality of links representing respective limbs of said character figure, said method further responsive to an input goal to animate said character subject to at least one constraint, said method comprising: storing a representation of each of said first plurality of joints in said memory; storing a representation of each of said plurality of links in said memory; storing a representation of the respective positions of said first plurality of joints and said plurality of links in said memory; computing, responsive to said stored motion data, a first set of motions derived from said stored motion data for each of said first plurality of joints respectively; computing, responsive to said input goal, a second set of motions subject to said constraint for each of said first plurality of joints respectively; combining said first set of motions with said second set of motions to form a combined set motions; modifying said stored representation of the positions of said first plurality of joints and said plurality of links in said memory using said combined set of motions; and rendering said stored representation of said links as the limbs of said character figure in said video image memory. | 1. A method for animating a character figure in a video image memory responsive to stored motion data, said character figure being represented in said memory as having a first plurality of joints and a plurality of links coupled between respective pairs of said first plurality of joints, said plurality of links representing respective limbs of said character figure, said method further responsive to an input goal to animate said character subject to at least one constraint, said method comprising: storing a representation of each of said first plurality of joints in said memory; storing a representation of each of said plurality of links in said memory; storing a representation of the respective positions of said first plurality of joints and said plurality of links in said memory; computing, responsive to said stored motion data, a first set of motions derived from said stored motion data for each of said first plurality of joints respectively; computing, responsive to said input goal, a second set of motions subject to said constraint for each of said first plurality of joints respectively; combining said first set of motions with said second set of motions to form a combined set motions; modifying said stored representation of the positions of said first plurality of joints and said plurality of links in said memory using said combined set of motions; and rendering said stored representation of said links as the limbs of said character figure in said video image memory. 7. A method in accordance with claim 1, wherein said constraint is obstacle avoidance. | 0.953564 |
9,990,360 | 12 | 14 | 12. A non-transitory computer readable storage medium that is configured to transform an input data stream comprising spatio-temporal data that is expressed at least in part in a non-linguistic format into a format that can be expressed at least in part via a linguistic representation in a textual output, the non-transitory computer readable storage medium comprising instructions, that, when executed by a processor, configure the processor to: receive a set of eventualities, the set of eventualities describing at least one of a domain event and a domain state, the at least one of the domain event and the domain state derived from a set of spatio-temporal data and the set of eventualities associated with a particular region and a particular time period; organize the set of eventualities according to a domain model; wherein organizing the set of eventualities comprises determining an importance score for one or more of the set of eventualities using the domain model that comprises a set of importance rules for one or more of the set of eventualities, wherein the importance rules provide an importance score based on an externally specified importance value for an eventuality type, a number of spatial points in the eventuality, and a time period of the eventuality; organizing the set of eventualities based on the importance scores; and at least one of filtering out one or more eventualities, partitioning one or more of the set of eventualities into a portion of the particular region, and ordering the set of eventualities into a particular order; generate a document plan, wherein the document plan is generated based on the organized set of eventualities; instantiate the document plan with one or more messages that describe each eventuality of the organized set of eventualities; and generate a linguistic representation of the one or more messages using the document plan, wherein the linguistic representation of the one or more messages is displayable via a user interface. | 12. A non-transitory computer readable storage medium that is configured to transform an input data stream comprising spatio-temporal data that is expressed at least in part in a non-linguistic format into a format that can be expressed at least in part via a linguistic representation in a textual output, the non-transitory computer readable storage medium comprising instructions, that, when executed by a processor, configure the processor to: receive a set of eventualities, the set of eventualities describing at least one of a domain event and a domain state, the at least one of the domain event and the domain state derived from a set of spatio-temporal data and the set of eventualities associated with a particular region and a particular time period; organize the set of eventualities according to a domain model; wherein organizing the set of eventualities comprises determining an importance score for one or more of the set of eventualities using the domain model that comprises a set of importance rules for one or more of the set of eventualities, wherein the importance rules provide an importance score based on an externally specified importance value for an eventuality type, a number of spatial points in the eventuality, and a time period of the eventuality; organizing the set of eventualities based on the importance scores; and at least one of filtering out one or more eventualities, partitioning one or more of the set of eventualities into a portion of the particular region, and ordering the set of eventualities into a particular order; generate a document plan, wherein the document plan is generated based on the organized set of eventualities; instantiate the document plan with one or more messages that describe each eventuality of the organized set of eventualities; and generate a linguistic representation of the one or more messages using the document plan, wherein the linguistic representation of the one or more messages is displayable via a user interface. 14. The non-transitory computer readable storage medium of claim 12 , wherein the non-transitory computer readable storage medium further comprises instructions to configure the processor to organize the set of eventualities based on the importance by placing a most important eventuality first in the document plan. | 0.716846 |
8,583,415 | 18 | 19 | 18. The system of claim 15 , wherein the query normalized string is based on a query native string and the one or more search content normalized strings are based on one or more search content native strings. | 18. The system of claim 15 , wherein the query normalized string is based on a query native string and the one or more search content normalized strings are based on one or more search content native strings. 19. The system of claim 18 , wherein the query native string and the search content native strings are based on an Indian writing system. | 0.969269 |
8,725,517 | 15 | 17 | 15. A computer-readable storage device having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising: selecting a recursive transition network flow controller from a database, to yield a selected top level flow controller; selecting an available reusable subdialog for an application part below the selected top level flow controller; developing a subdialog for each application part not associated with the available reusable subdialog, to yield developed subdialogs; and deploying a spoken dialog service using the selected top level flow controller, the available reusable subdialog, and the developed subdialogs. | 15. A computer-readable storage device having instructions stored which, when executed by a computing device, result in the computing device performing operations comprising: selecting a recursive transition network flow controller from a database, to yield a selected top level flow controller; selecting an available reusable subdialog for an application part below the selected top level flow controller; developing a subdialog for each application part not associated with the available reusable subdialog, to yield developed subdialogs; and deploying a spoken dialog service using the selected top level flow controller, the available reusable subdialog, and the developed subdialogs. 17. The computer-readable storage device of claim 15 , wherein application dependencies are declared outside of the available reusable subdialog. | 0.711155 |
8,484,552 | 1 | 2 | 1. A method in a computing system for generating an extensible stylesheet, the method comprising: receiving a target file in a markup language, the target file including a plurality of dynamic objects; receiving a structure tree, each node of the structure tree corresponding to one of the dynamic objects in the target file; creating a data structure by associating each of the dynamic objects in the target file with at least one element in at least one source file by a meta-tag; and generating, from the data structure, the extensible stylesheet in reference to the target file, wherein the stylesheet, when applied to the target file, controls visual aspects of how the target file is displayed; wherein said associating each of the dynamic objects in the target file with at least one element in at least one source file by a meta-tag comprises: copying each of the dynamic objects into a corresponding one of the elements in the at least one source file, or creating or updating an identifier to link each of the dynamic objects with the corresponding one of the elements in the at least one source file; and traversing the structure tree to obtain related information for one or more of the meta-tags, wherein the related information includes an association between the at least one dynamic object and the corresponding element in the at least one source file. | 1. A method in a computing system for generating an extensible stylesheet, the method comprising: receiving a target file in a markup language, the target file including a plurality of dynamic objects; receiving a structure tree, each node of the structure tree corresponding to one of the dynamic objects in the target file; creating a data structure by associating each of the dynamic objects in the target file with at least one element in at least one source file by a meta-tag; and generating, from the data structure, the extensible stylesheet in reference to the target file, wherein the stylesheet, when applied to the target file, controls visual aspects of how the target file is displayed; wherein said associating each of the dynamic objects in the target file with at least one element in at least one source file by a meta-tag comprises: copying each of the dynamic objects into a corresponding one of the elements in the at least one source file, or creating or updating an identifier to link each of the dynamic objects with the corresponding one of the elements in the at least one source file; and traversing the structure tree to obtain related information for one or more of the meta-tags, wherein the related information includes an association between the at least one dynamic object and the corresponding element in the at least one source file. 2. The method of claim 1 , wherein said receiving a target file in a markup language comprises causing display of the target file in an authoring tool that is capable of displaying the target file in a desired manner. | 0.885428 |
7,761,584 | 14 | 16 | 14. The system of claim 12 , wherein the second protocol is an interface. | 14. The system of claim 12 , wherein the second protocol is an interface. 16. The system of claim 14 , wherein the second protocol is a common language runtime interface. | 0.970838 |
5,384,703 | 1 | 13 | 1. An automated, computer implemented method of electronically processing a document stored in a memory of a computer, said document containing text represented by characters, said method comprising the steps of: a) using the computer, automatically determining a frequency of occurrence of expressions in the document not contained in a stop list and having at least a first predetermined level of complexity, said stop list stored in the memory of said computer; b) using the computer, automatically forming a seed list comprised of a second predetermined number of the most frequently occurring expressions determined in step (a), said seed list stored in said memory of said computer; c) using said computer, automatically forming a summary of the document comprised of regions in the document containing at least two members of said seed list, said summary stored in said memory of said computer; and d) using said computer, automatically repeating steps (a)-(c) on said summary until a length of said summary is no greater than a predetermined length, each time steps (a)-(c) are repeated, adding the members of said seed list to said stop list and reducing said first predetermined level of complexity. | 1. An automated, computer implemented method of electronically processing a document stored in a memory of a computer, said document containing text represented by characters, said method comprising the steps of: a) using the computer, automatically determining a frequency of occurrence of expressions in the document not contained in a stop list and having at least a first predetermined level of complexity, said stop list stored in the memory of said computer; b) using the computer, automatically forming a seed list comprised of a second predetermined number of the most frequently occurring expressions determined in step (a), said seed list stored in said memory of said computer; c) using said computer, automatically forming a summary of the document comprised of regions in the document containing at least two members of said seed list, said summary stored in said memory of said computer; and d) using said computer, automatically repeating steps (a)-(c) on said summary until a length of said summary is no greater than a predetermined length, each time steps (a)-(c) are repeated, adding the members of said seed list to said stop list and reducing said first predetermined level of complexity. 13. The method of claim 1, further comprising including in a final summary of said document, any regions located in a first paragraph of said document, and contained in a summary of the document a first time step (c) is performed by said computer. | 0.874619 |
7,703,003 | 10 | 11 | 10. The system as recited in claim 1 , wherein the instructions when executed further cause the one or more processors to implement: a service object generator configured to generate a new service object in response to input received from a user and store the new service object in the database, wherein the input specifies one or more activities for a service to be represented by the service object. | 10. The system as recited in claim 1 , wherein the instructions when executed further cause the one or more processors to implement: a service object generator configured to generate a new service object in response to input received from a user and store the new service object in the database, wherein the input specifies one or more activities for a service to be represented by the service object. 11. The system as recited in claim 10 , wherein the service object generator is further configured to: in response to additional user input, retrieve an existing service object from the service store; modify the existing service object; and store the modified service object in the database. | 0.939801 |
6,035,061 | 36 | 37 | 36. 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 table region, including a black pixel connected region having a predetermined size, and extracting a particular character string region from a plurality of character string regions in the table region as a title region, wherein said title extracting means is adapted for outputting the character string regions in order of positions closest to an upper left edge of the table region. | 36. 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 table region, including a black pixel connected region having a predetermined size, and extracting a particular character string region from a plurality of character string regions in the table region as a title region, wherein said title extracting means is adapted for outputting the character string regions in order of positions closest to an upper left edge of the table region. 37. The title extracting apparatus as set forth in claim 36, wherein said character string region generating means is adapted for generating one or a plurality of character string rectangles, including character regions, as character string regions, and wherein said title extracting means is adapted for assigning a priority order to a plurality of character string rectangles in the table region corresponding to coordinate values of particular vertexes of the character string rectangles. | 0.766635 |
8,996,500 | 1 | 7 | 1. A computer-implemented method for optimizing query performance in a relational database management system, comprising: receiving, by a processor, a query at the relational database management system; determining, by the processor, whether the query is expected to be a long-running query; in response to determining that the query is expected to be a long-running query, starting, by the processor, a full table scan to fetch records needed to satisfy the query from the relational database management system; in parallel with conducting the full table scan, building, by the processor, a performance object capable of satisfying the query in the relational database management system; in response to completing the construction of the performance object prior to completing the full table scan, stopping the full table scan and using the newly built performance object instead to satisfy the query; and storing the performance object in storage or memory for a predetermined time period. | 1. A computer-implemented method for optimizing query performance in a relational database management system, comprising: receiving, by a processor, a query at the relational database management system; determining, by the processor, whether the query is expected to be a long-running query; in response to determining that the query is expected to be a long-running query, starting, by the processor, a full table scan to fetch records needed to satisfy the query from the relational database management system; in parallel with conducting the full table scan, building, by the processor, a performance object capable of satisfying the query in the relational database management system; in response to completing the construction of the performance object prior to completing the full table scan, stopping the full table scan and using the newly built performance object instead to satisfy the query; and storing the performance object in storage or memory for a predetermined time period. 7. The method of claim 1 , wherein determining whether the query is expected to be long-running includes: estimating a time required to satisfy the query; and comparing the estimated time required to satisfy the query to a threshold value representing a time for a query considered to be a long-running query. | 0.633886 |
9,405,855 | 11 | 14 | 11. The system of claim 9 , wherein to generate the discovered component the one or more processors are further configured to: generate a maximum common sub-graph between the query graph and the data graph, wherein the maximum common sub-graph includes a maximum number of vertices that are common to the first and second plurality of vertices and wherein the maximum common sub-graph is the discovered component of the query graph. | 11. The system of claim 9 , wherein to generate the discovered component the one or more processors are further configured to: generate a maximum common sub-graph between the query graph and the data graph, wherein the maximum common sub-graph includes a maximum number of vertices that are common to the first and second plurality of vertices and wherein the maximum common sub-graph is the discovered component of the query graph. 14. The system of claim 11 , wherein to generate the maximum common sub-graph the one or more processors are further configured to: generate a list of maximum common sub-graphs, wherein the list includes a first maximum common sub-graph generated using the first vertex of the second plurality of vertices in the query graph and a second maximum common sub-graph generated using a third vertex of the second plurality of vertices in; and select the maximum common sub-graph from the list. | 0.809375 |
9,805,268 | 1 | 13 | 1. A system for extracting video highlights from a video stream comprising: storage, containing said video stream in digital form; and a processor, in communication with said storage, said processor executing software for performing the following functions: i. reading an initial plurality of frames from said video stream and constructing a new dictionary based on said initial plurality of frames, said dictionary containing data summarizing the content of said initial plurality of frames; ii. breaking the remainder of said video stream into a plurality of segments of approximately equal length; iii. reading the next segment from said video stream; iv. detecting interest points in said segment and defining a local spatio-temporal cuboid for each of said detected interest points; v. calculating, for each of said spatio-temporal cuboids, a plurality of feature vectors and concatenating said plurality of feature vectors into a feature representation for each of said spatio-temporal cuboids; vi. determining if a group of feature representations representing all of said spatio-temporal cuboids in said segment can be sparsely reconstructed for a cost not exceeding a predetermined threshold, using existing entries in said dictionary, and, if not, adding said group of feature representations to said dictionary and adding said segment to said video highlights; vii. repeating steps iii.-vi. until all segments in said video stream have been processed. | 1. A system for extracting video highlights from a video stream comprising: storage, containing said video stream in digital form; and a processor, in communication with said storage, said processor executing software for performing the following functions: i. reading an initial plurality of frames from said video stream and constructing a new dictionary based on said initial plurality of frames, said dictionary containing data summarizing the content of said initial plurality of frames; ii. breaking the remainder of said video stream into a plurality of segments of approximately equal length; iii. reading the next segment from said video stream; iv. detecting interest points in said segment and defining a local spatio-temporal cuboid for each of said detected interest points; v. calculating, for each of said spatio-temporal cuboids, a plurality of feature vectors and concatenating said plurality of feature vectors into a feature representation for each of said spatio-temporal cuboids; vi. determining if a group of feature representations representing all of said spatio-temporal cuboids in said segment can be sparsely reconstructed for a cost not exceeding a predetermined threshold, using existing entries in said dictionary, and, if not, adding said group of feature representations to said dictionary and adding said segment to said video highlights; vii. repeating steps iii.-vi. until all segments in said video stream have been processed. 13. The system of claim 1 wherein said function of updating said dictionary minimizes the difference between a vector representing an event and a vector reconstructed using the dictionary, minimizes the number of dictionary items and requires that all feature vectors in nearby video segments use similar dictionary items. | 0.501548 |
9,998,919 | 18 | 21 | 18. A system comprising: a text messaging hub comprising a processor and a memory that stores instructions that when executed cause the processor to: receive a sign-up request, the sign-up request including a user number for a user, the user number for the user including a phone number for the user; responsive to receiving the sign-up request; assign a first user-specific system number to which a mobile device is to direct future text messages, the mobile device being associated with the phone number for the user, wherein assigning the first user-specific system number comprises storing the first user-specific system number and the phone number for the user to a set of authorized user number and specific number pairs, the first user-specific system number being different from the phone number for the user; and send an initiation message to the mobile device associated with the phone number for the user, the initiation messaging including the first user-specific system number; receive a text message from a device, the text message being directed to a specific number associated with the text messaging hub, wherein the specific number is one of the plurality of possible numbers associated with the text messaging hub, the text message including the phone number for the user; determine whether the text message is authentic based on whether the phone number for the user is associated with the specific number based on the set of authorized user number and specific number pairs, wherein the phone number for the user is not associated with the specific number when the specific number to which the message is directed is not the first user-specific system number, determine that the text message is not authentic in response to determining the phone number for the user is not associated with the specific number; and responsive to determining that the text message is not authentic: assign a second user-specific system number to which the mobile device is to direct future text messages; and send, to the mobile device at the phone number for the user, a notification text message that includes the second user-specific system number. | 18. A system comprising: a text messaging hub comprising a processor and a memory that stores instructions that when executed cause the processor to: receive a sign-up request, the sign-up request including a user number for a user, the user number for the user including a phone number for the user; responsive to receiving the sign-up request; assign a first user-specific system number to which a mobile device is to direct future text messages, the mobile device being associated with the phone number for the user, wherein assigning the first user-specific system number comprises storing the first user-specific system number and the phone number for the user to a set of authorized user number and specific number pairs, the first user-specific system number being different from the phone number for the user; and send an initiation message to the mobile device associated with the phone number for the user, the initiation messaging including the first user-specific system number; receive a text message from a device, the text message being directed to a specific number associated with the text messaging hub, wherein the specific number is one of the plurality of possible numbers associated with the text messaging hub, the text message including the phone number for the user; determine whether the text message is authentic based on whether the phone number for the user is associated with the specific number based on the set of authorized user number and specific number pairs, wherein the phone number for the user is not associated with the specific number when the specific number to which the message is directed is not the first user-specific system number, determine that the text message is not authentic in response to determining the phone number for the user is not associated with the specific number; and responsive to determining that the text message is not authentic: assign a second user-specific system number to which the mobile device is to direct future text messages; and send, to the mobile device at the phone number for the user, a notification text message that includes the second user-specific system number. 21. The system of claim 18 , wherein the instructions further cause the processor to: forward the text message to a text messaging application when the text message is determined to be authentic. | 0.78139 |
4,605,080 | 1 | 4 | 1. Weighing apparatus comprising: first means for sensing the weight of an article and generating an analog signal indicative of the weight sensed, second means for receiving, processing and analyzing said analog signal and generating first digital signals indicative of the weight sensed by said first means, third means including electrically operated indicating means for indicating a variable associated with the article sensed by said first means, a microphone, first electronic computing means connected to receive speech signals output by said microphone, process and analyze same and generate first control signals, second electronic computing means operable to receive said first digital signals and said first control signals and to perfrom a computing function with respect to the information defined by said signals and to generate second control signals defining information relating to computations involving said first digital weight defining signals and said first control signals generated by said first electronic computing means, and means for applying said second control signals to selectively control the operation of said electrically operated indicating means to cause said indicating means to indicate the information defined by said second control signals. | 1. Weighing apparatus comprising: first means for sensing the weight of an article and generating an analog signal indicative of the weight sensed, second means for receiving, processing and analyzing said analog signal and generating first digital signals indicative of the weight sensed by said first means, third means including electrically operated indicating means for indicating a variable associated with the article sensed by said first means, a microphone, first electronic computing means connected to receive speech signals output by said microphone, process and analyze same and generate first control signals, second electronic computing means operable to receive said first digital signals and said first control signals and to perfrom a computing function with respect to the information defined by said signals and to generate second control signals defining information relating to computations involving said first digital weight defining signals and said first control signals generated by said first electronic computing means, and means for applying said second control signals to selectively control the operation of said electrically operated indicating means to cause said indicating means to indicate the information defined by said second control signals. 4. Weighing apparatus in accordance with claim 1 wherein said electrically operated indicating means is a printing means operable to print the information defined by said second control signals directly on a surface of the article weighed. | 0.732662 |
7,735,621 | 69 | 70 | 69. A currency bill processing device comprising: (a) a plurality of currency bill output receptacles; and (b) an operator interface configured to permit the operator of the device to change the designation of at least one of the output receptacles between being a fixed output receptacle and being a dynamic output receptacle, wherein a fixed output receptacle is an output receptacle assigned to a particular currency bill parameter such that during normal operation only bills having the particular parameter may be transported to the fixed output receptacle and wherein a dynamic output receptacle is an output receptacle subject to dynamic assignment of a bill parameter during normal operation of the device; and (c) and evaluating unit configured to determined to denomination of currency bills delivered to the output receptacles. | 69. A currency bill processing device comprising: (a) a plurality of currency bill output receptacles; and (b) an operator interface configured to permit the operator of the device to change the designation of at least one of the output receptacles between being a fixed output receptacle and being a dynamic output receptacle, wherein a fixed output receptacle is an output receptacle assigned to a particular currency bill parameter such that during normal operation only bills having the particular parameter may be transported to the fixed output receptacle and wherein a dynamic output receptacle is an output receptacle subject to dynamic assignment of a bill parameter during normal operation of the device; and (c) and evaluating unit configured to determined to denomination of currency bills delivered to the output receptacles. 70. The device of claim 69 wherein the operator interface is further configured to permit the operator to designate an output receptacle as unavailable. | 0.904881 |
9,082,129 | 11 | 19 | 11. A non-transitory computer-readable storage medium storing executable computer program instructions, the instructions executable to perform steps comprising: providing, to a client device associated with a first user of a plurality of users of a social networking system, a user interface for display to the first user; receiving from the first user, via the client device, a check-in at a location associated with a page in the social networking system, wherein the page is a social networking system page about at least one of a product, a business, a location, and a topic of interest, and wherein the page is a node in a social graph of the social networking system; responsive to receiving the check-in, providing a user interface element for receiving a tip associated with the page; receiving, via the client device, a tip from the first user that is associated with the page; identifying a plurality of tips, including the received tip, that are associated with the page, the plurality of tips shared by one or more of the plurality of users of the social networking system; receiving, via a second client device, a request from a second user of the plurality of users to display one or more of the plurality of tips associated with the page, wherein each tip is associated with privacy criteria that identify users having permission to view that tip; determining that the second user meets privacy criteria associated with a set of candidate tips of the plurality of tips; selecting, by a computer processor, one or more tips, including the received tip, from the set of candidate tips to display to the second user based in part on the second user meeting the privacy criteria associated with the received tip and a relevancy score associated with the received tip, the relevancy score providing a likelihood the second user will view the received tip and is based in part on a number of interactions between the second user and the first user within the social networking system; and responsive to the selecting, providing the page to the second client device, the page displaying the selected one or more tips. | 11. A non-transitory computer-readable storage medium storing executable computer program instructions, the instructions executable to perform steps comprising: providing, to a client device associated with a first user of a plurality of users of a social networking system, a user interface for display to the first user; receiving from the first user, via the client device, a check-in at a location associated with a page in the social networking system, wherein the page is a social networking system page about at least one of a product, a business, a location, and a topic of interest, and wherein the page is a node in a social graph of the social networking system; responsive to receiving the check-in, providing a user interface element for receiving a tip associated with the page; receiving, via the client device, a tip from the first user that is associated with the page; identifying a plurality of tips, including the received tip, that are associated with the page, the plurality of tips shared by one or more of the plurality of users of the social networking system; receiving, via a second client device, a request from a second user of the plurality of users to display one or more of the plurality of tips associated with the page, wherein each tip is associated with privacy criteria that identify users having permission to view that tip; determining that the second user meets privacy criteria associated with a set of candidate tips of the plurality of tips; selecting, by a computer processor, one or more tips, including the received tip, from the set of candidate tips to display to the second user based in part on the second user meeting the privacy criteria associated with the received tip and a relevancy score associated with the received tip, the relevancy score providing a likelihood the second user will view the received tip and is based in part on a number of interactions between the second user and the first user within the social networking system; and responsive to the selecting, providing the page to the second client device, the page displaying the selected one or more tips. 19. The computer-readable medium of claim 11 , wherein the relevancy score includes at least one of: an elapsed time since received tip was shared, an endorsement from a local business, and an amount of feedback associated with the received tip. | 0.640762 |
8,140,338 | 8 | 10 | 8. A system for history tracking corrections in an electronic document, wherein said electronic document is a speech-based document comprising one or more sections of text recognized or transcribed from sections of speech, wherein said sections of speech are dictated by a user and processed by a speech recognizer in a speech recognition system into corresponding sections of text of said speech-based document, said system comprising: at least one processor programmed to: associate at least one speech attribute with a section of text in said speech-based document, said at least one speech attribute comprising information related to said section of text; detect a first action being performed within said section of text; update information of said at least one speech attribute related to the first action detected on said section of text for updating said speech-based document, whereby said updated information of said at least one speech attribute is used for history tracking corrections of said speech-based document in use of said system; detect a second action being performed within said section of text; and add information for the at least one speech attribute related to the second action detected on said section of text for updating said speech-based document to the information of said at least one speech attribute related to the first action. | 8. A system for history tracking corrections in an electronic document, wherein said electronic document is a speech-based document comprising one or more sections of text recognized or transcribed from sections of speech, wherein said sections of speech are dictated by a user and processed by a speech recognizer in a speech recognition system into corresponding sections of text of said speech-based document, said system comprising: at least one processor programmed to: associate at least one speech attribute with a section of text in said speech-based document, said at least one speech attribute comprising information related to said section of text; detect a first action being performed within said section of text; update information of said at least one speech attribute related to the first action detected on said section of text for updating said speech-based document, whereby said updated information of said at least one speech attribute is used for history tracking corrections of said speech-based document in use of said system; detect a second action being performed within said section of text; and add information for the at least one speech attribute related to the second action detected on said section of text for updating said speech-based document to the information of said at least one speech attribute related to the first action. 10. A system according to claim 8 , wherein a structure of said speech-based document is defined dynamically from a set of document building elements. | 0.774775 |
8,326,624 | 1 | 2 | 1. A computer implemented method in a data processing system for determining and communicating biometrics of a recorded speaker in a voice transcription process, the computer implemented method comprising: receiving, by the data processing system, a request from a user for a transcription of a voice file stored in a memory of the data processing system; obtaining, by the data processing system, a profile associated with the requesting user, wherein the profile comprises biometric parameters and preferences defined by the user; analyzing, by the data processing system, the requested voice file for biometric elements according to the parameters specified in the user's profile; responsive to the data processing system detecting, in the voice file, biometric elements conforming to the parameters specified in the user's profile, modifying, by the data processing system, a transcription output of the voice file according to the preferences specified in the user's profile for the detected biometric elements to form a modified transcription output file; responsive to the data processing system determining that no preferences are specified in the user's profile, modifying, by the data processing system, the transcription output of the voice file according to default settings for the detected biometric elements to form the modified transcription output file; and providing, by the data processing system, the modified transcription output file to the requesting user. | 1. A computer implemented method in a data processing system for determining and communicating biometrics of a recorded speaker in a voice transcription process, the computer implemented method comprising: receiving, by the data processing system, a request from a user for a transcription of a voice file stored in a memory of the data processing system; obtaining, by the data processing system, a profile associated with the requesting user, wherein the profile comprises biometric parameters and preferences defined by the user; analyzing, by the data processing system, the requested voice file for biometric elements according to the parameters specified in the user's profile; responsive to the data processing system detecting, in the voice file, biometric elements conforming to the parameters specified in the user's profile, modifying, by the data processing system, a transcription output of the voice file according to the preferences specified in the user's profile for the detected biometric elements to form a modified transcription output file; responsive to the data processing system determining that no preferences are specified in the user's profile, modifying, by the data processing system, the transcription output of the voice file according to default settings for the detected biometric elements to form the modified transcription output file; and providing, by the data processing system, the modified transcription output file to the requesting user. 2. The computer implemented method of claim 1 , further comprising: receiving, by the data processing system, user selections in a profile for biometric parameters to be used by the data processing system when transcribing a voice file for the user; receiving, by the data processing system, user selections in the profile for preferences that specify how detected biometric elements are to be displayed in the modified transcription output file; and storing, by the data processing system, the profile in the memory of the data processing system. | 0.571317 |
9,519,714 | 7 | 12 | 7. A computerized method that provides list previews among search results, the method comprising: receiving a user query comprising a query list intent, wherein the query list intent indicates an intent to view one or more webpages that include at least one list, wherein the at least one list is a portion of at least one of the one or more webpages and includes a list, a collection of items, a set of items, or a table; identifying a first list contained within a first webpage of the one or more webpages corresponding with a first search result of a plurality of search results relevant to the user query, wherein the first list is identified as exceeding a predetermined level of relevance; selecting a set of items from the first list contained within the first webpage; and providing, for presentation within a search results page, (1) the plurality of search results, (2) the first search result associated with the first webpage and including the first list exceeding the predetermined level of relevance, (3) a list preview including the set of items from the first list, and (4) at least one list attribute associated with the first list, the at least one list attribute indicating at least one of a number of items within the first list of the first webpage, a relevancy score associated with the first list, or a quality score associated with the first list. | 7. A computerized method that provides list previews among search results, the method comprising: receiving a user query comprising a query list intent, wherein the query list intent indicates an intent to view one or more webpages that include at least one list, wherein the at least one list is a portion of at least one of the one or more webpages and includes a list, a collection of items, a set of items, or a table; identifying a first list contained within a first webpage of the one or more webpages corresponding with a first search result of a plurality of search results relevant to the user query, wherein the first list is identified as exceeding a predetermined level of relevance; selecting a set of items from the first list contained within the first webpage; and providing, for presentation within a search results page, (1) the plurality of search results, (2) the first search result associated with the first webpage and including the first list exceeding the predetermined level of relevance, (3) a list preview including the set of items from the first list, and (4) at least one list attribute associated with the first list, the at least one list attribute indicating at least one of a number of items within the first list of the first webpage, a relevancy score associated with the first list, or a quality score associated with the first list. 12. The computerized method of claim 7 , wherein the set of items is provided within the list preview and is integrated with the first search result or near the first search result. | 0.9155 |
9,471,635 | 1 | 2 | 1. A system for optimizing a query, comprising: a memory, and at least one processor operatively coupled to the memory; a construction module executed via the at least one processor and capable of building a data structure for a query, the data structure including a plurality of components, wherein each of the plurality of components corresponds to at least one graph pattern; a flow module executed via the at least one processor and capable of determining a plurality of flows of query variables between the plurality of components; a cost determination and ranking module executed via the at least one processor and capable of determining a combination of the plurality of flows between the plurality of components that results in a minimum cost to execute the query; a constraint module executed via the at least one processor and capable of generating one or more constraints for ruling out invalid flows of the plurality of flows; and an integral linear programming (ILP) solver, wherein the cost determination and ranking module uses the ILP solver to solve a linear optimization problem of determining the combination of the plurality of flows between the plurality of components that results in the minimum cost under the one or more constraints generated by the constraint module; wherein the one or more constraints comprise a component constraint enforcing semantics of an external view of one or more of the components, a graph constraint enforcing semantics of the plurality of flows of query variables, and a predecessor constraint enforcing semantics of one or more potential predecessors. | 1. A system for optimizing a query, comprising: a memory, and at least one processor operatively coupled to the memory; a construction module executed via the at least one processor and capable of building a data structure for a query, the data structure including a plurality of components, wherein each of the plurality of components corresponds to at least one graph pattern; a flow module executed via the at least one processor and capable of determining a plurality of flows of query variables between the plurality of components; a cost determination and ranking module executed via the at least one processor and capable of determining a combination of the plurality of flows between the plurality of components that results in a minimum cost to execute the query; a constraint module executed via the at least one processor and capable of generating one or more constraints for ruling out invalid flows of the plurality of flows; and an integral linear programming (ILP) solver, wherein the cost determination and ranking module uses the ILP solver to solve a linear optimization problem of determining the combination of the plurality of flows between the plurality of components that results in the minimum cost under the one or more constraints generated by the constraint module; wherein the one or more constraints comprise a component constraint enforcing semantics of an external view of one or more of the components, a graph constraint enforcing semantics of the plurality of flows of query variables, and a predecessor constraint enforcing semantics of one or more potential predecessors. 2. The system according to claim 1 , wherein the constraint module is further capable of ruling out one or more flows that would violate semantics of one or more control statements in the query. | 0.632576 |
9,104,391 | 1 | 10 | 1. A system for use in adaptively updating template candidate order sets, comprising: a repository of information comprising a plurality of candidate order sets individually including a plurality of candidate items for order and associated corresponding related order parameters, an individual item for order being associated with a plurality of related order parameters; a data entry monitor for monitoring user selection of candidate items from a candidate order set acquired from said repository and recording candidate item usage data identifying items selected by a user for order from individual particular candidate order sets for a plurality of different candidate order sets; and a data processor device for determining from the recorded candidate item usage data parameters comprising at least one of, (a) data indicative of the number or proportion of candidate items of a particular candidate order set that were selected by a user during order entry and (b) data indicative of the number or proportion of candidate items of a particular candidate order set that were not selected by a user during order entry, said data processor device automatically identifies, based on the determined parameters, a candidate order set from the plurality of candidate order sets to be updated. | 1. A system for use in adaptively updating template candidate order sets, comprising: a repository of information comprising a plurality of candidate order sets individually including a plurality of candidate items for order and associated corresponding related order parameters, an individual item for order being associated with a plurality of related order parameters; a data entry monitor for monitoring user selection of candidate items from a candidate order set acquired from said repository and recording candidate item usage data identifying items selected by a user for order from individual particular candidate order sets for a plurality of different candidate order sets; and a data processor device for determining from the recorded candidate item usage data parameters comprising at least one of, (a) data indicative of the number or proportion of candidate items of a particular candidate order set that were selected by a user during order entry and (b) data indicative of the number or proportion of candidate items of a particular candidate order set that were not selected by a user during order entry, said data processor device automatically identifies, based on the determined parameters, a candidate order set from the plurality of candidate order sets to be updated. 10. A system according to claim 1 , including an update processor for automatically updating a particular candidate order set by at least one of, (a) removing a candidate item, (b) adding a candidate item and (c) modifying a candidate item. | 0.622642 |
7,539,675 | 1 | 2 | 1. A server/client system for searching for digitized non-text entities in a data collection comprising: an indexing input device for collecting basic information pertaining to at least one distinctive feature and at least one locator for each digitized non-text entity in a set of non-text entities from the data collection, the indexing input device including an index generator for receiving the basic information and producing in response thereto at least one rank parameter for each digitized non-text entity, an index database for storing index information relating to the digitized non-text entities in the set, a search engine for receiving search directives and in response thereto performing searches in the index database, and a user client interface for receiving a search request from at least one user client terminal, forwarding the search request as a search directive to the search engine, receiving a hit list of digitized non-text entities and returning a result of a corresponding search in the index database to the at least one user client terminal, wherein the index database is organized such that the index information for a particular digitized non-text entity comprises the at least one rank parameter, which is indicative of a degree of relevance for at least one distinctive feature associated with said digitized non-text entity, wherein the at least one rank parameter is based on a first rank component that is generated by ranking each distinctive feature associated with each digitized non-text entity based on a relative number of occurrences of the distinctive feature in association with multiple copies of the digitized non-text entity in the data collection, and wherein the at least one rank parameter is further based on a second rank component that is generated by ranking each individual distinctive feature related to the digitized non-text entity based on a position of the distinctive feature in a descriptive field associated with the digitized non-text entity, wherein the rank parameter is a combination of the first rank component with the second rank component. | 1. A server/client system for searching for digitized non-text entities in a data collection comprising: an indexing input device for collecting basic information pertaining to at least one distinctive feature and at least one locator for each digitized non-text entity in a set of non-text entities from the data collection, the indexing input device including an index generator for receiving the basic information and producing in response thereto at least one rank parameter for each digitized non-text entity, an index database for storing index information relating to the digitized non-text entities in the set, a search engine for receiving search directives and in response thereto performing searches in the index database, and a user client interface for receiving a search request from at least one user client terminal, forwarding the search request as a search directive to the search engine, receiving a hit list of digitized non-text entities and returning a result of a corresponding search in the index database to the at least one user client terminal, wherein the index database is organized such that the index information for a particular digitized non-text entity comprises the at least one rank parameter, which is indicative of a degree of relevance for at least one distinctive feature associated with said digitized non-text entity, wherein the at least one rank parameter is based on a first rank component that is generated by ranking each distinctive feature associated with each digitized non-text entity based on a relative number of occurrences of the distinctive feature in association with multiple copies of the digitized non-text entity in the data collection, and wherein the at least one rank parameter is further based on a second rank component that is generated by ranking each individual distinctive feature related to the digitized non-text entity based on a position of the distinctive feature in a descriptive field associated with the digitized non-text entity, wherein the rank parameter is a combination of the first rank component with the second rank component. 2. A server/client system according to claim 1 , wherein the second rank component indicates a ranking of at least one individual distinctive feature related to the digitized non-text entity on basis of both the position of the least one individual distinctive feature in the descriptive field as well as a relevancy parameter reflecting the distinctive feature's significance in relation to other distinctive features in a particular position in the descriptive field. | 0.501064 |
8,433,698 | 16 | 23 | 16. A non-transitory computer-readable storage medium storing modules that, when executed by a processor, cause a computer to perform a method of searching for media objects associated with a search term, the method comprising: retrieving, based upon a received first search term, at least one web page including the first search term; analyzing a plurality of positional relationships between the first search term and additional terms within an individual one of the at least one web page; scoring each of the plurality of positional relationships; determining, based on the scoring, at least one additional search term, and retrieving, based on the at least one additional search term, at least one media object. | 16. A non-transitory computer-readable storage medium storing modules that, when executed by a processor, cause a computer to perform a method of searching for media objects associated with a search term, the method comprising: retrieving, based upon a received first search term, at least one web page including the first search term; analyzing a plurality of positional relationships between the first search term and additional terms within an individual one of the at least one web page; scoring each of the plurality of positional relationships; determining, based on the scoring, at least one additional search term, and retrieving, based on the at least one additional search term, at least one media object. 23. The non-transitory computer-readable storage medium of claim 16 , wherein the retrieving the at least one web page retrieving comprises accessing an internet search engine. | 0.707641 |
8,032,823 | 1 | 2 | 1. A system for processing a user request, the system comprising: an intermediary agent configured for receiving input data from a user, the input data including at least natural language associated with a user request, wherein the intermediary agent includes an electronic computer processor and at least one electronic non-transitory computer-readable medium, an analysis module operatively associated with the intermediary agent, wherein the analysis module is configured for analyzing the user input data; the intermediary agent being further configured for: selecting at least one form based on analyzing the user input data; and, executing at least one update based on at least the selected form; and, a learning system operatively associated with the intermediary agent, the learning system configured for: electronically receiving information regarding processing of the request; and adding an example to the learning system, wherein the example is derived from performance of the intermediary agent with regard to processing the request. | 1. A system for processing a user request, the system comprising: an intermediary agent configured for receiving input data from a user, the input data including at least natural language associated with a user request, wherein the intermediary agent includes an electronic computer processor and at least one electronic non-transitory computer-readable medium, an analysis module operatively associated with the intermediary agent, wherein the analysis module is configured for analyzing the user input data; the intermediary agent being further configured for: selecting at least one form based on analyzing the user input data; and, executing at least one update based on at least the selected form; and, a learning system operatively associated with the intermediary agent, the learning system configured for: electronically receiving information regarding processing of the request; and adding an example to the learning system, wherein the example is derived from performance of the intermediary agent with regard to processing the request. 2. The system of claim 1 , further comprising the intermediary agent being configured for filling the selected form with data responsive to the user request. | 0.789544 |
10,157,426 | 1 | 13 | 1. A computer-implemented method performed by a computing device comprising a data store including computer-executable instructions of a computerized tax return preparation application and a processor executing the computer-executable instructions of the computerized tax return preparation application, the computer-implemented method comprising: the computing device, by executing a rule-based logic agent, reading first runtime data of an electronic tax return from a shared data store, selecting candidate topics or questions from a data structure comprising a plurality of rows defining respective rules and a plurality of columns defining respective questions, generating a plurality of non-binding suggestions of candidate topics or questions to be presented to the user based at least in part upon the first runtime data and the data structure, and generating prioritization data associated with the plurality of non-binding suggestions; the computing device, by executing a user interface controller in communication with the rule-based logic agent, receiving the plurality of non-binding suggestions from the rule-based logic agent; the computing device, by executing a pagination engine associated with the user interface controller, receiving prioritization data generated by the rule-based logic agent and associated with the plurality of non-binding suggestions, and generating an output based at least in part upon the prioritization data; the computing device, by executing the user interface controller, generating an interview screen that is presented to the user through a display of the computing device, the interview screen comprising a first paginated screen including topics or questions of at least one selected non-binding suggestion generated by the rule-based logic agent and structured based at least in part upon the pagination engine outputs; the computing device, by executing the user interface controller, receiving user input through the first paginated screen, the user input corresponding to selection of a topic or question of the first paginated screen, and writing the response to the shared data store shared with the rule-based logic agent to update the first runtime data and generate second runtime data; and the computing device, by executing a calculation engine, reading the second runtime data from the shared data store, determining a calculation result based on performing a calculation using the second runtime data, and writing the calculation result to the shared data store to update the second runtime data and generate third runtime data. | 1. A computer-implemented method performed by a computing device comprising a data store including computer-executable instructions of a computerized tax return preparation application and a processor executing the computer-executable instructions of the computerized tax return preparation application, the computer-implemented method comprising: the computing device, by executing a rule-based logic agent, reading first runtime data of an electronic tax return from a shared data store, selecting candidate topics or questions from a data structure comprising a plurality of rows defining respective rules and a plurality of columns defining respective questions, generating a plurality of non-binding suggestions of candidate topics or questions to be presented to the user based at least in part upon the first runtime data and the data structure, and generating prioritization data associated with the plurality of non-binding suggestions; the computing device, by executing a user interface controller in communication with the rule-based logic agent, receiving the plurality of non-binding suggestions from the rule-based logic agent; the computing device, by executing a pagination engine associated with the user interface controller, receiving prioritization data generated by the rule-based logic agent and associated with the plurality of non-binding suggestions, and generating an output based at least in part upon the prioritization data; the computing device, by executing the user interface controller, generating an interview screen that is presented to the user through a display of the computing device, the interview screen comprising a first paginated screen including topics or questions of at least one selected non-binding suggestion generated by the rule-based logic agent and structured based at least in part upon the pagination engine outputs; the computing device, by executing the user interface controller, receiving user input through the first paginated screen, the user input corresponding to selection of a topic or question of the first paginated screen, and writing the response to the shared data store shared with the rule-based logic agent to update the first runtime data and generate second runtime data; and the computing device, by executing a calculation engine, reading the second runtime data from the shared data store, determining a calculation result based on performing a calculation using the second runtime data, and writing the calculation result to the shared data store to update the second runtime data and generate third runtime data. 13. The method of claim 1 , a non-binding suggestion comprising a candidate question or topic that was identified by the rule-based logic agent based upon an inference about the user by the rule-based logic agent in view of the current runtime data and data from a source external of the electronic tax return is ranked higher than other non-binding suggestions that do not include a candidate question identified based at least in part upon an inference about the user. | 0.862734 |
8,630,483 | 1 | 7 | 1. A method for identifying a complex-object in a query image, the method comprising: performing computer-enabled steps of: processing at least one pixel patch from the query image with a cascade of classifiers, each classifier of the cascade configured to identify at least one discriminative feature characteristic of a part of the complex-object, wherein each successive classifier of the cascade identifies a number of discriminative features greater than a number of discriminative features identified by prior classifiers of the cascade; and selecting an additional pixel patch from the query image for processing after a last classifier of the cascade has identified the distinguishing feature, wherein the selecting is based on a known positional relationship between the part and an additional part of the complex-object. | 1. A method for identifying a complex-object in a query image, the method comprising: performing computer-enabled steps of: processing at least one pixel patch from the query image with a cascade of classifiers, each classifier of the cascade configured to identify at least one discriminative feature characteristic of a part of the complex-object, wherein each successive classifier of the cascade identifies a number of discriminative features greater than a number of discriminative features identified by prior classifiers of the cascade; and selecting an additional pixel patch from the query image for processing after a last classifier of the cascade has identified the distinguishing feature, wherein the selecting is based on a known positional relationship between the part and an additional part of the complex-object. 7. The method of claim 1 , further comprising designating a searched pixel patch to be disregarded when selecting future pixel patches, the searched pixel patch determined to be devoid of the discriminative features characterizing a part of the complex-object. | 0.792 |
9,621,602 | 13 | 15 | 13. The method of claim 12 , wherein identifying the physical movement profiles as corresponding to a physical social action comprises matching each of the profiles to at least one baseline profile of a physical social interaction. | 13. The method of claim 12 , wherein identifying the physical movement profiles as corresponding to a physical social action comprises matching each of the profiles to at least one baseline profile of a physical social interaction. 15. The method of claim 13 , wherein the baseline profile corresponds to a plurality of profiles identified as corresponding to a physical social interaction by a plurality of users of the social networking system. | 0.946607 |
7,584,419 | 1 | 2 | 1. A method for representing non-structured features in a ML document, comprising: determining a start feature tag location for a non-structured feature; wherein the non-structured feature spans a range that begins at a location that is after a start tag of an outer element and before an end tag of the outer element; determining an end feature tag location for the non-structured feature; wherein the non-structured feature spans the range that ends at a location that is after the end tag of the outer element; placing a start feature tag at the start feature tag location; wherein the start feature tag does not include other elements and the start feature tag includes a start identifier attribute; and placing an end feature tag at the end feature tag location, wherein the end feature tag does not include other elements and the end feature tag includes an end identifier attribute; and wherein the start feature tag and the end feature tag are separated by the range while maintaining a well formed ML document; determining a reference value, the reference value indicating an association between the start feature tag and the end feature tag; setting the start identifier attribute to the reference value; and setting the end identifier attribute to the reference value. | 1. A method for representing non-structured features in a ML document, comprising: determining a start feature tag location for a non-structured feature; wherein the non-structured feature spans a range that begins at a location that is after a start tag of an outer element and before an end tag of the outer element; determining an end feature tag location for the non-structured feature; wherein the non-structured feature spans the range that ends at a location that is after the end tag of the outer element; placing a start feature tag at the start feature tag location; wherein the start feature tag does not include other elements and the start feature tag includes a start identifier attribute; and placing an end feature tag at the end feature tag location, wherein the end feature tag does not include other elements and the end feature tag includes an end identifier attribute; and wherein the start feature tag and the end feature tag are separated by the range while maintaining a well formed ML document; determining a reference value, the reference value indicating an association between the start feature tag and the end feature tag; setting the start identifier attribute to the reference value; and setting the end identifier attribute to the reference value. 2. The method of claim 1 , wherein the ML document is an XML document. | 0.892638 |
9,020,840 | 1 | 10 | 1. A method for custom-fitting a service solution to consumer requirements, comprising: acquiring a request for the service solution from a consumer via a conversational interface executed on a processor; issuing a query to a service knowledge base to obtain a set of service knowledge representation items from the service knowledge base; obtaining the set of service knowledge representation items from the service knowledge base; analyzing each service knowledge representation item to determine whether a custom-fit service solution can be developed; determining that a custom-fit service solution can be developed; computing, by the conversational interface executed on the processor, the query to be issued to the service knowledge base based on the request for the service solution, and forwarding the query to a service specification mining module, wherein the service specification mining module synthesizes the custom-fit service solution and transmits the custom-fit service solution to the conversational interface; assetizing the custom-fit service solution, wherein the custom-fit service solution is added to the service knowledge base; and determining that the request cannot be fulfilled automatically by concluding that each parameter of every service knowledge representation item of the set of the service knowledge representation items is an unpluggable parameter. | 1. A method for custom-fitting a service solution to consumer requirements, comprising: acquiring a request for the service solution from a consumer via a conversational interface executed on a processor; issuing a query to a service knowledge base to obtain a set of service knowledge representation items from the service knowledge base; obtaining the set of service knowledge representation items from the service knowledge base; analyzing each service knowledge representation item to determine whether a custom-fit service solution can be developed; determining that a custom-fit service solution can be developed; computing, by the conversational interface executed on the processor, the query to be issued to the service knowledge base based on the request for the service solution, and forwarding the query to a service specification mining module, wherein the service specification mining module synthesizes the custom-fit service solution and transmits the custom-fit service solution to the conversational interface; assetizing the custom-fit service solution, wherein the custom-fit service solution is added to the service knowledge base; and determining that the request cannot be fulfilled automatically by concluding that each parameter of every service knowledge representation item of the set of the service knowledge representation items is an unpluggable parameter. 10. The method of claim 1 , wherein a service knowledge representation item is machine-processable content obtained from a service characterization. | 0.762058 |
8,655,901 | 1 | 7 | 1. A method comprising: receiving a first query pattern, the query pattern identifying a particular rule to interpret a particular type of query, the query pattern being in a first language; identifying, with a system comprising one or more computing devices, a collection of queries in the first language matching the query pattern by determining which queries in a query log match the query pattern; segmenting a given query among the collection into one or more tokens in the first language, wherein each token includes one or more terms from the given query; annotating each query of the collection of queries with one or more labels identifying the parts of each query, wherein annotating each query of the collection of queries with one or more labels comprises: associating each of the one or more tokens with corresponding components of the first query pattern; and annotating the one or more tokens with labels for the corresponding components of the first query pattern; translating the collection of annotated queries in the first language into a translated collection of queries in a second language; and extracting a translated query pattern from the translated collection of queries, wherein for the given one of the plurality of queries, extracting a translated query pattern from the translated collection of queries comprises: determining, from an order in which the one or more tokens into which the given query was segmented in the first language are translated into the second language, an order in which labels for the components of the first query pattern correspond to translated terms of the given query; and extracting the translated query pattern from the order in which labels for the components of the first query pattern correspond to the translated terms of the given query pattern. | 1. A method comprising: receiving a first query pattern, the query pattern identifying a particular rule to interpret a particular type of query, the query pattern being in a first language; identifying, with a system comprising one or more computing devices, a collection of queries in the first language matching the query pattern by determining which queries in a query log match the query pattern; segmenting a given query among the collection into one or more tokens in the first language, wherein each token includes one or more terms from the given query; annotating each query of the collection of queries with one or more labels identifying the parts of each query, wherein annotating each query of the collection of queries with one or more labels comprises: associating each of the one or more tokens with corresponding components of the first query pattern; and annotating the one or more tokens with labels for the corresponding components of the first query pattern; translating the collection of annotated queries in the first language into a translated collection of queries in a second language; and extracting a translated query pattern from the translated collection of queries, wherein for the given one of the plurality of queries, extracting a translated query pattern from the translated collection of queries comprises: determining, from an order in which the one or more tokens into which the given query was segmented in the first language are translated into the second language, an order in which labels for the components of the first query pattern correspond to translated terms of the given query; and extracting the translated query pattern from the order in which labels for the components of the first query pattern correspond to the translated terms of the given query pattern. 7. The method of claim 1 , where extracting a translated query pattern further comprises cross-validating the translated query pattern with a query log with respect to a specified occurrence threshold. | 0.649826 |
7,882,100 | 16 | 20 | 16. The system of claim 15 , wherein the transform module identifies a portion of the left deep nested loop join tree requiring transformation into a bushy tree shape for generating a semantically correct query execution plan. | 16. The system of claim 15 , wherein the transform module identifies a portion of the left deep nested loop join tree requiring transformation into a bushy tree shape for generating a semantically correct query execution plan. 20. The system of claim 16 , wherein said portion of the left deep nested loop join tree requiring transformation includes an outer join. | 0.923378 |
9,953,085 | 7 | 8 | 7. A system for matching a content item in a data file to a search entity comprising one or more processors and a memory configured to: maintain a plurality of entity-action pairs and bidding parameters specific to each entity-action pair of the plurality of entity-action pairs; receive a first search query from a client device, the first search query including a query term indicative of a first search entity; identify, from the plurality of entity-action pairs, a first entity-action pair comprising the first search entity and a first online action and a second entity-action pair comprising the first search entity and a second online action that is different from the first online action responsive to the query term indicative of the first search entity in the received first search query; identify a second search entity not included in the first search query and identified using the first search entity and a knowledge graph of search entities; conduct a first content auction for the first entity-action pair based on bidding parameters specific to the first entity-action pair and a second content auction for the second entity-action pair based on bidding parameters specific to the second entity-action pair and responsive to identifying the first entity-action pair and the second entity-action pair; determine a first set of third-party content items associated with the first entity-action pair for participating in the first content auction, each third-party content item of the first set of third-party content items including executable instructions for causing an application of the client device to automatically perform the first online action upon actuating that third-party content item by the client device; determine a second set of third-party content items associated with the first entity-action pair for participating in the second content auction, each third-party content item of the second set of third-party content items including executable instructions for causing the application of the client device to automatically perform the second online action upon actuating that third-party content item by the client device; select, responsive to the first content auction, a first content item of a first third-party content provider based on a first bidding parameter of the first third-party content provider specific to the first entity-action pair and select, responsive to the second content auction, a second content item of a second third-party content provider based on a second bidding parameter of the second third-party content provider specific to the second entity-action pair, the first and second content items for presenting with search results corresponding to the first search query on the client device; and select a link associated with the second search entity for presenting with the search results corresponding to the first search query on the client device, wherein actuation of the link by the client device causes the first search query to be replaced with a second search query associated with the second search entity and new content items to be selected instead of the first and second content items. | 7. A system for matching a content item in a data file to a search entity comprising one or more processors and a memory configured to: maintain a plurality of entity-action pairs and bidding parameters specific to each entity-action pair of the plurality of entity-action pairs; receive a first search query from a client device, the first search query including a query term indicative of a first search entity; identify, from the plurality of entity-action pairs, a first entity-action pair comprising the first search entity and a first online action and a second entity-action pair comprising the first search entity and a second online action that is different from the first online action responsive to the query term indicative of the first search entity in the received first search query; identify a second search entity not included in the first search query and identified using the first search entity and a knowledge graph of search entities; conduct a first content auction for the first entity-action pair based on bidding parameters specific to the first entity-action pair and a second content auction for the second entity-action pair based on bidding parameters specific to the second entity-action pair and responsive to identifying the first entity-action pair and the second entity-action pair; determine a first set of third-party content items associated with the first entity-action pair for participating in the first content auction, each third-party content item of the first set of third-party content items including executable instructions for causing an application of the client device to automatically perform the first online action upon actuating that third-party content item by the client device; determine a second set of third-party content items associated with the first entity-action pair for participating in the second content auction, each third-party content item of the second set of third-party content items including executable instructions for causing the application of the client device to automatically perform the second online action upon actuating that third-party content item by the client device; select, responsive to the first content auction, a first content item of a first third-party content provider based on a first bidding parameter of the first third-party content provider specific to the first entity-action pair and select, responsive to the second content auction, a second content item of a second third-party content provider based on a second bidding parameter of the second third-party content provider specific to the second entity-action pair, the first and second content items for presenting with search results corresponding to the first search query on the client device; and select a link associated with the second search entity for presenting with the search results corresponding to the first search query on the client device, wherein actuation of the link by the client device causes the first search query to be replaced with a second search query associated with the second search entity and new content items to be selected instead of the first and second content items. 8. The system of claim 7 , wherein the one or more processors and the memory are configured to: receive a data file from a computing device of a first third-party content provider comprising one or more content items including the first content item, each of the one or more content items comprising identification data, a respective content item type, and a respective online action, each of the one or more content items associated with a product or service of the first third-party content provider; identify the first search entity based on identification data and a content item type for the first content item in the data file, the first search entity corresponding to a named physical entity; generate, based on the data file, the first entity-action pair comprising the first search entity and the first online action, the first online action associated with the first content item in the data file; and associate the first entity-action pair with the first bidding parameter specific to the first entity-action pair. | 0.632616 |
8,091,017 | 14 | 15 | 14. The apparatus of claim 1 wherein the program instructions are further configured to: receive and validate a user-supplied symbolic link anchor definition including a symbolic link name; insert a symbolic link anchor at a user-specified location in the one or more components; and add said symbolic link anchor definition to a list of all symbolic link anchor definitions. | 14. The apparatus of claim 1 wherein the program instructions are further configured to: receive and validate a user-supplied symbolic link anchor definition including a symbolic link name; insert a symbolic link anchor at a user-specified location in the one or more components; and add said symbolic link anchor definition to a list of all symbolic link anchor definitions. 15. The apparatus of claim 14 wherein the program instructions are further configured to: receive and validate a symbolic link name including comparing the symbolic link name to the symbolic link anchor definitions in the list of all symbolic link anchor definitions; and insert a symbolic hypertext link at a user-specified location in the one or more components wherein the hypertext link points to the symbolic link anchor location associated with the validated symbolic link name. | 0.872093 |
8,370,826 | 1 | 5 | 1. A method for automatically managing mashup widget versions comprising: identifying a request for a mashup widget having a plurality of versions from an identifiable source; querying a data store to determine if a previous request for said mashup widget was made by the identifiable source; during the querying after determining a version was used to handle a previous request, determining a last used date that the version was last used by the identifiable source; when said previous request is not found when querying the data store: (a) determining one of the mashup versions to be utilized based upon a programmatic rule; (b) querying a user profile to determine requestor specific settings affecting the programmatic rule; and (c) applying these requestor specific settings when executing the programmatic rule; when said previous request exists: (a) automatically determining a version of said mashup widget used to handle said previous request, wherein said determined version is one of the plurality of versions; (b) comparing the determined data against a last update date associated with a most current one of the plurality of versions; (c) when the last update date is more recent than the last used date, prompting whether to use the most current version or to use determined version to handle the request; and using said determined version to generate a response to said request. | 1. A method for automatically managing mashup widget versions comprising: identifying a request for a mashup widget having a plurality of versions from an identifiable source; querying a data store to determine if a previous request for said mashup widget was made by the identifiable source; during the querying after determining a version was used to handle a previous request, determining a last used date that the version was last used by the identifiable source; when said previous request is not found when querying the data store: (a) determining one of the mashup versions to be utilized based upon a programmatic rule; (b) querying a user profile to determine requestor specific settings affecting the programmatic rule; and (c) applying these requestor specific settings when executing the programmatic rule; when said previous request exists: (a) automatically determining a version of said mashup widget used to handle said previous request, wherein said determined version is one of the plurality of versions; (b) comparing the determined data against a last update date associated with a most current one of the plurality of versions; (c) when the last update date is more recent than the last used date, prompting whether to use the most current version or to use determined version to handle the request; and using said determined version to generate a response to said request. 5. The method of claim 1 , further comprising Saving the mashup version used to generate the response to said request in the queried data store so that said saved mashup version will be used to handle future requests by the identifiable source. | 0.83558 |
7,801,942 | 13 | 14 | 13. An article comprising a non-transitory tangible machine-accessible storage medium having associated data that, when accessed, results in a machine: surfing a network to collect textual information of at least one webpage of at least one website of the network; storing the textual information in a database; parsing the textual information; queuing a request to take at least one snap-shot image responsive to the textual information of the at least one webpage; taking the at least one snap-shot image of the at least one webpage; displaying user selectable options configurable to provide first search results responsive to keywords entered by at least one user of the network, the first search results to show at least some of the textual information of the at least one webpage; and collecting demographic information of the at least one user of the network, the demographic information including age, income level, and employment history, and targeting an ad placement to the at least one user responsive to the demographic information. | 13. An article comprising a non-transitory tangible machine-accessible storage medium having associated data that, when accessed, results in a machine: surfing a network to collect textual information of at least one webpage of at least one website of the network; storing the textual information in a database; parsing the textual information; queuing a request to take at least one snap-shot image responsive to the textual information of the at least one webpage; taking the at least one snap-shot image of the at least one webpage; displaying user selectable options configurable to provide first search results responsive to keywords entered by at least one user of the network, the first search results to show at least some of the textual information of the at least one webpage; and collecting demographic information of the at least one user of the network, the demographic information including age, income level, and employment history, and targeting an ad placement to the at least one user responsive to the demographic information. 14. An article according to claim 13 , wherein the user selectable options are further configurable to provide second search results to show the at least one snap-shot image of the at least one webpage and at least some of the textual information of the at least one webpage. | 0.867021 |
9,600,806 | 21 | 22 | 21. A computer-implemented method, comprising: analyzing electronic messages of a first user with respect to one or more features associated with the electronic messages; associating descriptive tags with the electronic messages of the first user based on the analyzing; and performing tasks with respect to the electronic messages of the first user, on behalf of the first user, based on the descriptive tags associated with the respective electronic messages; wherein the analyzing includes identifying a sender of a first electronic message received by the first user and determining relevance of the first electronic message with respect to the first user as a function of at least one of, a relationship between the sender and the first user within an implied social graph of electronic message users, a quality of the relationship between the sender and the first user, a syntactic structure of the first electronic message, metadata associated with the first electronic message, a language used in the first electronic message, a character set used in the first electronic message, an action taken by the first user with respect to a second electronic message for which one or more features are similar to one or more corresponding features of the first electronic message, and an action taken by a second user with respect to an electronic message received by the second user for which one or more features are similar to one or more corresponding features of the first electronic message. | 21. A computer-implemented method, comprising: analyzing electronic messages of a first user with respect to one or more features associated with the electronic messages; associating descriptive tags with the electronic messages of the first user based on the analyzing; and performing tasks with respect to the electronic messages of the first user, on behalf of the first user, based on the descriptive tags associated with the respective electronic messages; wherein the analyzing includes identifying a sender of a first electronic message received by the first user and determining relevance of the first electronic message with respect to the first user as a function of at least one of, a relationship between the sender and the first user within an implied social graph of electronic message users, a quality of the relationship between the sender and the first user, a syntactic structure of the first electronic message, metadata associated with the first electronic message, a language used in the first electronic message, a character set used in the first electronic message, an action taken by the first user with respect to a second electronic message for which one or more features are similar to one or more corresponding features of the first electronic message, and an action taken by a second user with respect to an electronic message received by the second user for which one or more features are similar to one or more corresponding features of the first electronic message. 22. The method of claim 21 , wherein the determining relevance includes: determining the relevance based at least in part on the relationship between the sender and the recipient within the implied social graph. | 0.866286 |
8,554,601 | 1 | 4 | 1. A computer-implemented method for selecting information to provide to users based on reputations of evaluators of the information, the method comprising: receiving from a reviewer user a review related to an item available from a Web merchant, the receiving of the review being performed by one or more programmed computing systems of the Web merchant; receiving multiple evaluations of the review, each of the multiple evaluations being from one of multiple evaluator users who each has an existing reputation weight for the Web merchant that is based at least in part on previous evaluations supplied by that evaluator user for multiple other reviews for items available from the Web merchant, each received evaluation including a quantitative assessment of contents of the review for each of one or more of multiple content rating dimensions available for use in assessing the review; automatically generating an aggregate assessment of the content of the review based at least in part on combining quantitative assessments from the received evaluations for the review, the generated aggregate assessment being further based on the existing reputation weights of the evaluator users in such a manner that a first quantitative assessment from a first evaluator user with a first reputation weight has a different impact on that generated aggregate assessment than that first quantitative assessment from a distinct second evaluator user with a distinct second reputation weight, the automatic generating being performed by the one or more programmed computing systems; automatically updating the existing reputation weights for each of one or more of the evaluator users based on a relationship of the quantitative assessments from the evaluation of that evaluator user to the quantitative assessments from the evaluations of other of the evaluator users, the automatic updating being performed by the one or more programmed computing systems; and for each of multiple additional users of the Web merchant who are distinct from the multiple evaluator users and from the reviewer user, determining whether to provide the review to the additional user based at least in part on the automatically generated aggregate assessment for the content of the review. | 1. A computer-implemented method for selecting information to provide to users based on reputations of evaluators of the information, the method comprising: receiving from a reviewer user a review related to an item available from a Web merchant, the receiving of the review being performed by one or more programmed computing systems of the Web merchant; receiving multiple evaluations of the review, each of the multiple evaluations being from one of multiple evaluator users who each has an existing reputation weight for the Web merchant that is based at least in part on previous evaluations supplied by that evaluator user for multiple other reviews for items available from the Web merchant, each received evaluation including a quantitative assessment of contents of the review for each of one or more of multiple content rating dimensions available for use in assessing the review; automatically generating an aggregate assessment of the content of the review based at least in part on combining quantitative assessments from the received evaluations for the review, the generated aggregate assessment being further based on the existing reputation weights of the evaluator users in such a manner that a first quantitative assessment from a first evaluator user with a first reputation weight has a different impact on that generated aggregate assessment than that first quantitative assessment from a distinct second evaluator user with a distinct second reputation weight, the automatic generating being performed by the one or more programmed computing systems; automatically updating the existing reputation weights for each of one or more of the evaluator users based on a relationship of the quantitative assessments from the evaluation of that evaluator user to the quantitative assessments from the evaluations of other of the evaluator users, the automatic updating being performed by the one or more programmed computing systems; and for each of multiple additional users of the Web merchant who are distinct from the multiple evaluator users and from the reviewer user, determining whether to provide the review to the additional user based at least in part on the automatically generated aggregate assessment for the content of the review. 4. The method of claim 1 wherein the relationship of the quantitative assessments from the evaluation of an evaluator user to the quantitative assessments from the evaluations of other of the evaluator users that is used when automatically updating the reputation weight for that evaluator user is based on a degree of agreement between the quantitative assessments from the evaluation of the evaluator user and quantitative assessments from a consensus evaluation for the received evaluations. | 0.849114 |
10,140,976 | 6 | 7 | 6. The method for language processing of claim 1 , wherein selecting the hypothesis comprises determining a word error rate for each hypothesis that considers only errors in words of the respective hypothesis that are in the first natural language processing dictionary using the discriminative language model. | 6. The method for language processing of claim 1 , wherein selecting the hypothesis comprises determining a word error rate for each hypothesis that considers only errors in words of the respective hypothesis that are in the first natural language processing dictionary using the discriminative language model. 7. The method for language processing of claim 6 , further comprising selecting the hypothesis having the lowest word error rate. | 0.945013 |
10,147,038 | 1 | 16 | 1. A computer implemented method of integrating a trained model trained on a training data set into an application, the method comprising: instantiating, by a project engine, a mechanical turk project that includes a plurality of tasks available to project members; receiving, by the project engine, project results data from the project members; generating, by the project engine, a training data set from the project results data; training, by the project engine, a trained model from the training data set; converting, by an application generator module, the project results data in the form of the trained model into a trained application module formatted for integration into an application; and causing, by the application generator module, integration of the trained application module into the application. | 1. A computer implemented method of integrating a trained model trained on a training data set into an application, the method comprising: instantiating, by a project engine, a mechanical turk project that includes a plurality of tasks available to project members; receiving, by the project engine, project results data from the project members; generating, by the project engine, a training data set from the project results data; training, by the project engine, a trained model from the training data set; converting, by an application generator module, the project results data in the form of the trained model into a trained application module formatted for integration into an application; and causing, by the application generator module, integration of the trained application module into the application. 16. The method of claim 1 , wherein the training data set comprises a domain-specific training set. | 0.833893 |
9,984,152 | 10 | 12 | 10. An apparatus for providing a proactive validation of a transformation script, the apparatus comprising: a memory device that stores a set of instructions; one or more processors that execute the set of instructions to configure the one or more processors to: associate the transformation script with ontology parameters, wherein the ontology parameters include parameters that assign an entity as being an object or a property of an object; initiate a debugging operation of the transformation script having at least one condition, wherein the transformation script uses a builder that defines a definition of the entity as the entity being an object or a property of an object; import, from a data source, at least one data item for transformation; determine, as part of the debugging operation, whether the at least one condition that uses the at least one data item is valid if the assignment of the entity associated with the transformation script is consistent with the definition of the entity, the determination whether the at least one condition that uses the at least one data item is valid being based on the ontology parameters; and provide an indication of a result associated with the determination, wherein the result is at least one of an expressed result or an implicit result. | 10. An apparatus for providing a proactive validation of a transformation script, the apparatus comprising: a memory device that stores a set of instructions; one or more processors that execute the set of instructions to configure the one or more processors to: associate the transformation script with ontology parameters, wherein the ontology parameters include parameters that assign an entity as being an object or a property of an object; initiate a debugging operation of the transformation script having at least one condition, wherein the transformation script uses a builder that defines a definition of the entity as the entity being an object or a property of an object; import, from a data source, at least one data item for transformation; determine, as part of the debugging operation, whether the at least one condition that uses the at least one data item is valid if the assignment of the entity associated with the transformation script is consistent with the definition of the entity, the determination whether the at least one condition that uses the at least one data item is valid being based on the ontology parameters; and provide an indication of a result associated with the determination, wherein the result is at least one of an expressed result or an implicit result. 12. The apparatus of claim 10 , wherein the data source includes unstructured data or the data source includes structured data. | 0.874753 |
6,044,375 | 1 | 4 | 1. A method of automatically extracting metadata from a document, the method comprising: (a) providing: a computer readable document including blocks comprised of words, an authority list, including common uses of a set of words, and a neural network trained to extract metadata from compounds; (b) locating authority information associated with the words by comparing the words with the authority list; (c) creating compounds, a first of the compounds describing a first of the blocks and including: first-block words, descriptive information associated with one of the first-block and the first block words, and authority information associated with one first-block word; (d) processing the compounds through the neural network to generate metadata guesses; and (e) deriving the metadata from the metadata guesses. | 1. A method of automatically extracting metadata from a document, the method comprising: (a) providing: a computer readable document including blocks comprised of words, an authority list, including common uses of a set of words, and a neural network trained to extract metadata from compounds; (b) locating authority information associated with the words by comparing the words with the authority list; (c) creating compounds, a first of the compounds describing a first of the blocks and including: first-block words, descriptive information associated with one of the first-block and the first block words, and authority information associated with one first-block word; (d) processing the compounds through the neural network to generate metadata guesses; and (e) deriving the metadata from the metadata guesses. 4. A method as in claim 1, in which the descriptive information includes font information for the first-block words. | 0.851282 |
7,761,298 | 9 | 10 | 9. A non-transitory computer-readable storage medium storing instructions which, when executed by a computing device, cause the computing device to evaluate effectiveness of speech retrieval of documents, the instructions comprising: removing terms in vectors that are not recognized by a recognizer, the vectors being associated with automatic transcriptions of documents; generating weighted vectors by modifying weights of terms in the vectors; adding to the weighted vectors terms which were not recognized by the recognizer; receiving a plurality of speech queries for the documents, wherein the speech queries are based on the weighted vectors; and determining effectiveness of the received plurality of speech queries based on queries in the plurality of speech queries which result in a number of relevant documents equal to or greater than a predetermined threshold. | 9. A non-transitory computer-readable storage medium storing instructions which, when executed by a computing device, cause the computing device to evaluate effectiveness of speech retrieval of documents, the instructions comprising: removing terms in vectors that are not recognized by a recognizer, the vectors being associated with automatic transcriptions of documents; generating weighted vectors by modifying weights of terms in the vectors; adding to the weighted vectors terms which were not recognized by the recognizer; receiving a plurality of speech queries for the documents, wherein the speech queries are based on the weighted vectors; and determining effectiveness of the received plurality of speech queries based on queries in the plurality of speech queries which result in a number of relevant documents equal to or greater than a predetermined threshold. 10. The non-transitory computer-readable storage medium of claim 9 , wherein documents relates to a first document based at least on a frame of time. | 0.503333 |
8,972,872 | 4 | 5 | 4. The apparatus according to claim 3 , wherein the UI objects, the UI display screens and the UI events are determined according to queries, output of queries or both specifying the UI objects of the task. | 4. The apparatus according to claim 3 , wherein the UI objects, the UI display screens and the UI events are determined according to queries, output of queries or both specifying the UI objects of the task. 5. The apparatus according to claim 4 , wherein the metadata is based upon an ontology. | 0.986022 |
7,831,951 | 50 | 51 | 50. A method of designing an essentially digital system, the method comprising: generating a description of the functionality and timing of the digital system, wherein the description includes a system-level description comprising a plurality of tasks; and optimizing the system-level description; and designing the essentially digital system based at least upon the optimized system-level description, wherein non-deterministic behavior of the digital system is modeled by interacting the tasks, while each of the tasks describe part of the deterministic behavior of the digital system and wherein the method is executed on a processor-based system. | 50. A method of designing an essentially digital system, the method comprising: generating a description of the functionality and timing of the digital system, wherein the description includes a system-level description comprising a plurality of tasks; and optimizing the system-level description; and designing the essentially digital system based at least upon the optimized system-level description, wherein non-deterministic behavior of the digital system is modeled by interacting the tasks, while each of the tasks describe part of the deterministic behavior of the digital system and wherein the method is executed on a processor-based system. 51. The method of claim 50 , wherein the optimized system-level description comprises a task concurrency system-level description obtained by optimizing task concurrency. | 0.818763 |
7,711,571 | 15 | 23 | 15. An apparatus comprising: a language translation device that includes a database configured to accommodate translation data, the language translation device being equipped to provide a number of language translation services to a user, and the language translation device being responsive to a contextual translation data update signal that updates the database; an electronic data input and output module, configured to provide the contextual translation data update signal to the language translation device, the electronic data input and output module being responsive to a context change signal indicative that the database may need to be updated; and a context comparator configured to provide the context change signal if the translation data is insufficient to cover a present or anticipated context of the apparatus, wherein the contextual translation data update signal is input into the apparatus, and the context change signal is output from the apparatus, wherein the present or anticipated context is a setting in a country having a primary language different from a language in which the user is fluent, and wherein said updates include adding to the database a selected subset of phrases that are suitable for said setting, and removing from the database another selected subset of phrases that are irrelevant to said setting, and said setting includes a temperature. | 15. An apparatus comprising: a language translation device that includes a database configured to accommodate translation data, the language translation device being equipped to provide a number of language translation services to a user, and the language translation device being responsive to a contextual translation data update signal that updates the database; an electronic data input and output module, configured to provide the contextual translation data update signal to the language translation device, the electronic data input and output module being responsive to a context change signal indicative that the database may need to be updated; and a context comparator configured to provide the context change signal if the translation data is insufficient to cover a present or anticipated context of the apparatus, wherein the contextual translation data update signal is input into the apparatus, and the context change signal is output from the apparatus, wherein the present or anticipated context is a setting in a country having a primary language different from a language in which the user is fluent, and wherein said updates include adding to the database a selected subset of phrases that are suitable for said setting, and removing from the database another selected subset of phrases that are irrelevant to said setting, and said setting includes a temperature. 23. The apparatus of claim 15 , wherein the context change signal includes, or is accompanied by, an indication of at least one translation need or desire of the user. | 0.690741 |
7,920,968 | 1 | 10 | 1. A machine-readable medium encoded with instructions, that when executed by a processor, cause the processor to carry out a process for generating human-centric driving directions, the process comprising: generating a route in response to a user request for travel directions, the request specifying at least a target destination; identifying distinctive waypoints along the route, wherein the waypoints are physical structures along the route and are in addition to road names and road topology and each waypoint is associated with a distinctiveness score, wherein the distinctiveness score of each waypoint is based at least in part on a visual prominence of the respective waypoint and based at least in part on an advertising fee per use for incorporating the respective waypoint in travel directions; and incorporating one or more of the waypoints into travel directions responsive to the associated distinctiveness score. | 1. A machine-readable medium encoded with instructions, that when executed by a processor, cause the processor to carry out a process for generating human-centric driving directions, the process comprising: generating a route in response to a user request for travel directions, the request specifying at least a target destination; identifying distinctive waypoints along the route, wherein the waypoints are physical structures along the route and are in addition to road names and road topology and each waypoint is associated with a distinctiveness score, wherein the distinctiveness score of each waypoint is based at least in part on a visual prominence of the respective waypoint and based at least in part on an advertising fee per use for incorporating the respective waypoint in travel directions; and incorporating one or more of the waypoints into travel directions responsive to the associated distinctiveness score. 10. The machine-readable medium of claim 1 further comprising at least one of: sending the travel directions to the user for display; and sending the travel directions to the user for aural presentation. | 0.689602 |
9,311,361 | 7 | 8 | 7. A system for algorithmically determining a visual appeal of content items, said system comprising: a processor; and a computer-readable memory device having encoded thereon computer readable instructions that when executed by the processor cause the processor to: store a plurality of software implemented algorithms in the memory device, each algorithm comprising one or more rules representing expert knowledge for subject matter of online content items, the rules are capable of recognizing graphic content parameters, recognizing textual content parameters, and relating the graphic content parameters and the textual content parameters to a set of desired parameters accessible to the rules based on the expert knowledge, the parameters relating to the appearance of the graphic content and the textual content, each algorithm pertains to a different aspect of online content; receive one or more generated items of online content from a content provider computing device; determine graphic content parameters and textual content parameters of the received items of online content, by parsing the online content using the plurality of algorithms according to the different rules included in each algorithm, wherein determining the graphic content parameters and textual content parameters include determining a relative size of a font with respect to other textual content, a location of the textual content within the content item, a location of breaks used in text wrapping in the textual content, a relative alignment of the textual content, a readability of the textual content based on font colors and background colors, and an orientation of graphic objects within the content item; compare the determined parameters to the set of desired parameters, by determining whether each aspect meets a respective predefined threshold value; rank the items of online content based on the comparisons; and provide guidance for improving a quality of the items of online content by outputting the ranked items of online content to the content provider computing device. | 7. A system for algorithmically determining a visual appeal of content items, said system comprising: a processor; and a computer-readable memory device having encoded thereon computer readable instructions that when executed by the processor cause the processor to: store a plurality of software implemented algorithms in the memory device, each algorithm comprising one or more rules representing expert knowledge for subject matter of online content items, the rules are capable of recognizing graphic content parameters, recognizing textual content parameters, and relating the graphic content parameters and the textual content parameters to a set of desired parameters accessible to the rules based on the expert knowledge, the parameters relating to the appearance of the graphic content and the textual content, each algorithm pertains to a different aspect of online content; receive one or more generated items of online content from a content provider computing device; determine graphic content parameters and textual content parameters of the received items of online content, by parsing the online content using the plurality of algorithms according to the different rules included in each algorithm, wherein determining the graphic content parameters and textual content parameters include determining a relative size of a font with respect to other textual content, a location of the textual content within the content item, a location of breaks used in text wrapping in the textual content, a relative alignment of the textual content, a readability of the textual content based on font colors and background colors, and an orientation of graphic objects within the content item; compare the determined parameters to the set of desired parameters, by determining whether each aspect meets a respective predefined threshold value; rank the items of online content based on the comparisons; and provide guidance for improving a quality of the items of online content by outputting the ranked items of online content to the content provider computing device. 8. The system of claim 7 , wherein the computer readable instructions when executed by the processor cause the processor to determine parameters that relate to the semantics of objects or combinations of objects in the graphic content. | 0.849744 |
7,996,369 | 9 | 10 | 9. The improvement of claim 6 where if a gram is very frequent, keeping selected ones of the corresponding extended grams in the frequency trie comprises if n.freq>T, selecting a maximal subset of the current node n's children excluding leaf-node child L to remove, so that the summation of the frequencies of the maximal subset of the current node and the frequency of the leaf-node child, L.freq, is not greater than T, adding the summation of the frequencies of the maximal subset of the current node to the frequency of the leaf-node child, and for the remaining children the current node n, excluding leaf-node L, recursively pruning the subtrie. | 9. The improvement of claim 6 where if a gram is very frequent, keeping selected ones of the corresponding extended grams in the frequency trie comprises if n.freq>T, selecting a maximal subset of the current node n's children excluding leaf-node child L to remove, so that the summation of the frequencies of the maximal subset of the current node and the frequency of the leaf-node child, L.freq, is not greater than T, adding the summation of the frequencies of the maximal subset of the current node to the frequency of the leaf-node child, and for the remaining children the current node n, excluding leaf-node L, recursively pruning the subtrie. 10. The improvement of claim 9 where selecting a maximal subset of the current node n's children excluding leaf-node child L comprises choosing children with the smallest frequencies to remove, choosing children with the largest frequencies to remove, or randomly selecting children to remove so that the frequency of the leaf-node child, L.freq, is not greater than T after addition of the frequencies of the selected children which have been removed into the leaf-node child L's frequency. | 0.836115 |
7,676,369 | 1 | 4 | 1. A conversation control apparatus, comprising: (a) a conversation database having stored therein: a plurality of topic specifying information items; a plurality of topic titles including sub-pluralities respectively correlated to correspond to respective ones of said topic specifying information items; a plurality of reply sentences including sub-pluralities each respectively correlated to correspond to a respective one of said topic titles; and a plurality of event information flags each corresponding to an emotion and including sub-pluralities each correlated to correspond to a respective one of said reply sentences; (b) a voice input unit configured to receive speech input of a user; (c) a sensor unit configured to acquire facial image data of the user; (d) an emotion estimation module configured to estimate a current emotion of the user, based upon a characteristic quantity of an expression computed from the facial image data of the user acquired by the sensor unit, and to generate event information indicative of a result of the estimate; (e) a past conversation information storage unit storing a plurality of past conversation information items determined based upon a past speech by the user and a past reply sentence in response to the past speech, the past reply sentence having been output by the conversation control apparatus; (f) an output unit configured to output sentences; and (g) a conversation control unit, the conversation control unit being configured to execute the following operations: (i) accept the speech input received by the voice input unit from the user as current conversation information and store the current conversation information for future use as the past conversation information of the user in the past conversation information storage unit; (ii) acquire the facial image data of the user, who uttered the speech input, and generate by the emotion estimation module, the event information used for estimating the current emotion of the user, based upon the acquired facial image data of the user; (iii) extract a relevant conversation information item, from among the plurality of the past conversation information items stored in the past conversation information storage unit, based upon the current conversation information of the user accepted in operation (i); (iv) extract a relevant topic specifying information item, from among the plurality of the topic specifying information items stored in the conversation database unit, based upon the relevant conversation information item extracted in the operation (iii); (v) extract a relevant topic title, from among the plurality of the topic titles determined as relevant based on corresponding to the relevant topic specifying information item extracted in the operation (iv) which was extracted based on the current conversation information of the user input in the operation (i), and also to select one of the sub-plurality of reply sentences by determining correlation thereof to the relevant topic title; (vi) extract a relevant event information flag, from among the sub-plurality of the event information flags correlated to the selected one of the sub-plurality of reply sentences correlated to the relevant topic tide extracted in the operation (v), based upon the event information indicative of the current emotion of the user and generated in the operation (ii) by the emotion estimation module; (vii) extract a relevant reply sentence from the sub-plurality of reply sentences correlated to the relevant topic title extracted in the operation (v), by determining the relevant reply sentence corresponds to the relevant event information flag extracted in the operation (vi), such that said relevant reply sentence is extracted based upon all of the following: the current conversation information of the user accepted in operation (i) being used to extract the relevant conversation information item which in turn is used to extract the relevant topic specifying information item which is then used to extract the relevant topic title which is then used to select the sub-plurality of reply sentences; the past speech by the user and the past reply sentence issued in response to the past speech being used to provide the past conversation information from which the relevant conversation information item is extracted; and outside information in the form of the facial image data of the user based upon which the event information is generated and used to extract the relevant reply sentence from the selected sub-plurality of reply sentences by confirming the event information flag of the reply sentence relates to the event information; and (viii) output the relevant reply sentence, extracted in the operation (vii), to the user. | 1. A conversation control apparatus, comprising: (a) a conversation database having stored therein: a plurality of topic specifying information items; a plurality of topic titles including sub-pluralities respectively correlated to correspond to respective ones of said topic specifying information items; a plurality of reply sentences including sub-pluralities each respectively correlated to correspond to a respective one of said topic titles; and a plurality of event information flags each corresponding to an emotion and including sub-pluralities each correlated to correspond to a respective one of said reply sentences; (b) a voice input unit configured to receive speech input of a user; (c) a sensor unit configured to acquire facial image data of the user; (d) an emotion estimation module configured to estimate a current emotion of the user, based upon a characteristic quantity of an expression computed from the facial image data of the user acquired by the sensor unit, and to generate event information indicative of a result of the estimate; (e) a past conversation information storage unit storing a plurality of past conversation information items determined based upon a past speech by the user and a past reply sentence in response to the past speech, the past reply sentence having been output by the conversation control apparatus; (f) an output unit configured to output sentences; and (g) a conversation control unit, the conversation control unit being configured to execute the following operations: (i) accept the speech input received by the voice input unit from the user as current conversation information and store the current conversation information for future use as the past conversation information of the user in the past conversation information storage unit; (ii) acquire the facial image data of the user, who uttered the speech input, and generate by the emotion estimation module, the event information used for estimating the current emotion of the user, based upon the acquired facial image data of the user; (iii) extract a relevant conversation information item, from among the plurality of the past conversation information items stored in the past conversation information storage unit, based upon the current conversation information of the user accepted in operation (i); (iv) extract a relevant topic specifying information item, from among the plurality of the topic specifying information items stored in the conversation database unit, based upon the relevant conversation information item extracted in the operation (iii); (v) extract a relevant topic title, from among the plurality of the topic titles determined as relevant based on corresponding to the relevant topic specifying information item extracted in the operation (iv) which was extracted based on the current conversation information of the user input in the operation (i), and also to select one of the sub-plurality of reply sentences by determining correlation thereof to the relevant topic title; (vi) extract a relevant event information flag, from among the sub-plurality of the event information flags correlated to the selected one of the sub-plurality of reply sentences correlated to the relevant topic tide extracted in the operation (v), based upon the event information indicative of the current emotion of the user and generated in the operation (ii) by the emotion estimation module; (vii) extract a relevant reply sentence from the sub-plurality of reply sentences correlated to the relevant topic title extracted in the operation (v), by determining the relevant reply sentence corresponds to the relevant event information flag extracted in the operation (vi), such that said relevant reply sentence is extracted based upon all of the following: the current conversation information of the user accepted in operation (i) being used to extract the relevant conversation information item which in turn is used to extract the relevant topic specifying information item which is then used to extract the relevant topic title which is then used to select the sub-plurality of reply sentences; the past speech by the user and the past reply sentence issued in response to the past speech being used to provide the past conversation information from which the relevant conversation information item is extracted; and outside information in the form of the facial image data of the user based upon which the event information is generated and used to extract the relevant reply sentence from the selected sub-plurality of reply sentences by confirming the event information flag of the reply sentence relates to the event information; and (viii) output the relevant reply sentence, extracted in the operation (vii), to the user. 4. The method according to claim 1 , further comprising: storing emotional condition information of a predetermined character; receive the event information indicative of the current emotion of the user generated in operation (ii); and updating the emotional condition information of the predetermined character so that the current emotion of the user is reflected in the predetermined character, based upon the event information received and indicative of the current emotion of the user; and displaying the predetermined character on a display unit, said displaying including displaying a motion and an expression of the predetermined character as a function of the emotional condition information last updated. | 0.635107 |
7,546,527 | 1 | 6 | 1. A method for extracting data from a document formatted using a first markup language and presenting the extracted data using a second, different markup language, the method comprising: providing a content converter system operating as an interface between a client and a server, the content converter system including one or more templates for extracting data from documents, a template table associating each template with a network location identifier of a particular document and a particular target markup language, and a markup language application for reformatting the extracted data using a different markup language; receiving a content request from the client by the content converter system, said content request specifying a network location from which a specified document including formatted content in the first markup language can be retrieved, said content request further indicating the second target markup language; responsive to the content request, identifying a template which corresponds to said specified document and said target markup language using the template table, said template providing at least one content marker, wherein the at least one content marker indicates a data offset for identifying within the specified document one or more data fields containing information corresponding to at least one among a type of data and a particular action, wherein the template further specifies at least one among markup language tags, code, and additional text to associate with the information contained in a particular data field when presented in said target markup language, and wherein said template can be customized by a user to extract in one or more different combinations from the specified document information based upon the at least one content marker; retrieving said specified document from said specified network location; applying said template to said specified document and extracting data from said formatted content based upon the template, by: identifying a presentation order of the at least one content marker in said template; and extracting the information in said data fields from said specified document in accordance with the presentation order; and formatting said information by the markup language application of the content converter system for presentation in said presentation order based upon said associated markup language tags, code, and additional text specified in the template, wherein said formatting produces a second document formatted for presentation according to the second target markup language. | 1. A method for extracting data from a document formatted using a first markup language and presenting the extracted data using a second, different markup language, the method comprising: providing a content converter system operating as an interface between a client and a server, the content converter system including one or more templates for extracting data from documents, a template table associating each template with a network location identifier of a particular document and a particular target markup language, and a markup language application for reformatting the extracted data using a different markup language; receiving a content request from the client by the content converter system, said content request specifying a network location from which a specified document including formatted content in the first markup language can be retrieved, said content request further indicating the second target markup language; responsive to the content request, identifying a template which corresponds to said specified document and said target markup language using the template table, said template providing at least one content marker, wherein the at least one content marker indicates a data offset for identifying within the specified document one or more data fields containing information corresponding to at least one among a type of data and a particular action, wherein the template further specifies at least one among markup language tags, code, and additional text to associate with the information contained in a particular data field when presented in said target markup language, and wherein said template can be customized by a user to extract in one or more different combinations from the specified document information based upon the at least one content marker; retrieving said specified document from said specified network location; applying said template to said specified document and extracting data from said formatted content based upon the template, by: identifying a presentation order of the at least one content marker in said template; and extracting the information in said data fields from said specified document in accordance with the presentation order; and formatting said information by the markup language application of the content converter system for presentation in said presentation order based upon said associated markup language tags, code, and additional text specified in the template, wherein said formatting produces a second document formatted for presentation according to the second target markup language. 6. The method of claim 1 , wherein said step of extracting information comprises reading data in said formatted content from an offset within said specified document, said offset identified by a content marker within said template. | 0.65727 |
7,788,292 | 1 | 5 | 1. A system implemented on a machine that effectuates and facilitates normalization of document representation for use with a Naïve Bayes model, comprising: a component that receives a document from an interface, the component determines a norm associated with the document by aggregating absolute term weight values associated with the document and ascertains a term weight for a feature associated with the document, the component divides the term weight for the feature associated with the document with the norm associated with the document to produce a normalized document representation. | 1. A system implemented on a machine that effectuates and facilitates normalization of document representation for use with a Naïve Bayes model, comprising: a component that receives a document from an interface, the component determines a norm associated with the document by aggregating absolute term weight values associated with the document and ascertains a term weight for a feature associated with the document, the component divides the term weight for the feature associated with the document with the norm associated with the document to produce a normalized document representation. 5. The system of claim 1 , the term weight for the feature derived from a previous iteration of the Naïve Bayes model. | 0.837017 |
8,020,187 | 1 | 6 | 1. A method for associating an electronic document work with an action, the document work comprising text, the method comprising: a) electronically extracting within a client device features from the electronic document work; b) transmitting the extracted features from the client device to one or more servers; c) receiving at the client device from the one or more servers an identification of the electronic document work based on the extracted features, wherein the identification is based on a sub-linear search to identify at least a neighbor; d) electronically determining an action” based on the identification of the electronic document work; and e) electronically performing the action on the client device. | 1. A method for associating an electronic document work with an action, the document work comprising text, the method comprising: a) electronically extracting within a client device features from the electronic document work; b) transmitting the extracted features from the client device to one or more servers; c) receiving at the client device from the one or more servers an identification of the electronic document work based on the extracted features, wherein the identification is based on a sub-linear search to identify at least a neighbor; d) electronically determining an action” based on the identification of the electronic document work; and e) electronically performing the action on the client device. 6. The method of claim 1 , wherein the step of electronically extracting the features is performed by at least one of a microprocessor of the client device and a digital signal processor of the client device. | 0.607547 |
8,990,074 | 1 | 6 | 1. A method of noise-robust speech classification, comprising: inputting classification parameters to a speech classifier from external components; generating, in the speech classifier, internal classification parameters from at least one of the input classification parameters; setting a Normalized Auto-correlation Coefficient Function threshold, wherein setting the Normalized Auto-correlation Coefficient Function threshold comprises: increasing a first voicing threshold for classifying a current frame as unvoiced when a signal-to-noise ratio (SNR) fails to exceed a first SNR threshold, wherein the first voicing threshold is not adjusted if the SNR is above the first SNR threshold, and increasing an energy threshold for classifying the current frame as unvoiced when the noise estimate exceeds a noise estimate threshold, wherein the energy threshold is not adjusted if the noise estimate is below the noise estimate threshold; and determining a speech mode classification based on a the first voicing threshold and the energy threshold. | 1. A method of noise-robust speech classification, comprising: inputting classification parameters to a speech classifier from external components; generating, in the speech classifier, internal classification parameters from at least one of the input classification parameters; setting a Normalized Auto-correlation Coefficient Function threshold, wherein setting the Normalized Auto-correlation Coefficient Function threshold comprises: increasing a first voicing threshold for classifying a current frame as unvoiced when a signal-to-noise ratio (SNR) fails to exceed a first SNR threshold, wherein the first voicing threshold is not adjusted if the SNR is above the first SNR threshold, and increasing an energy threshold for classifying the current frame as unvoiced when the noise estimate exceeds a noise estimate threshold, wherein the energy threshold is not adjusted if the noise estimate is below the noise estimate threshold; and determining a speech mode classification based on a the first voicing threshold and the energy threshold. 6. The method of claim 1 , wherein the input parameters comprise Normalized Auto-correlation Coefficient Function information. | 0.906942 |
9,870,572 | 1 | 3 | 1. A method of selecting an advertisement associated with a geographic location, comprising: receiving, using one or more processors, a request from a remote computer, the request identifying the geographic location from location signals associated with the remote computer, the location signals determined at the remote computer using an antenna for receiving location signals and associated software for determining the position of the remote computer based on the received location signals; determining, using the one or more processors, a listing associated with the geographic location and the request; determining, using the one or more processors, a number of previous users that selected the listing associated with the geographic location in response to the previous users providing a first search term; when the number of previous users exceeds a predetermined threshold, selecting, using the one or more processors, the first search term as one or more search terms associated with the geographic location; when the number of previous users does not exceed the predetermined threshold, determining, using the one or more processors, a number of listing categories associated with the geographic location; when the number of listing categories falls below a given threshold, selecting, using the one or more processors, the listing categories as the one or more search terms associated with the geographic location; when the number of listing categories does not fall below the given threshold, determining, using the one or more processors and without user input, a point of interest that is associated with the geographic location and selecting a title of the point of interest as the one or more search terms associated with the geographic location; determining, using the one or more processors, an advertisement based at least in part on the one or more search terms associated with the geographic location; and transmitting, using the one or more processors, the advertisement to an electronic display of the remote computer for display to the user in response to the request. | 1. A method of selecting an advertisement associated with a geographic location, comprising: receiving, using one or more processors, a request from a remote computer, the request identifying the geographic location from location signals associated with the remote computer, the location signals determined at the remote computer using an antenna for receiving location signals and associated software for determining the position of the remote computer based on the received location signals; determining, using the one or more processors, a listing associated with the geographic location and the request; determining, using the one or more processors, a number of previous users that selected the listing associated with the geographic location in response to the previous users providing a first search term; when the number of previous users exceeds a predetermined threshold, selecting, using the one or more processors, the first search term as one or more search terms associated with the geographic location; when the number of previous users does not exceed the predetermined threshold, determining, using the one or more processors, a number of listing categories associated with the geographic location; when the number of listing categories falls below a given threshold, selecting, using the one or more processors, the listing categories as the one or more search terms associated with the geographic location; when the number of listing categories does not fall below the given threshold, determining, using the one or more processors and without user input, a point of interest that is associated with the geographic location and selecting a title of the point of interest as the one or more search terms associated with the geographic location; determining, using the one or more processors, an advertisement based at least in part on the one or more search terms associated with the geographic location; and transmitting, using the one or more processors, the advertisement to an electronic display of the remote computer for display to the user in response to the request. 3. The method of claim 1 , wherein the advertisement is at least one business listing associated with the point of interest. | 0.930804 |
9,204,107 | 2 | 9 | 2. The apparatus of claim 1 , wherein the content analysis engine comprises: a gross change detector to analyze the video input and to determine if a gross change event has occurred. | 2. The apparatus of claim 1 , wherein the content analysis engine comprises: a gross change detector to analyze the video input and to determine if a gross change event has occurred. 9. The apparatus of claim 2 , wherein if a gross change event has occurred, the content analysis engine: enters a warm-up state, does not produce gross change primitives while in the warm-up state, and after the warm-up state is finished, begins to perform analysis of the video input to produce one or more gross change primitives after the warm-up state is finished. | 0.88656 |
9,911,413 | 2 | 4 | 2. A method for configuring a natural language (NL) understanding system, the NL understanding system including at least a linguistic classifier, the linguistic classifier being configurable with configuration data to distinguish a plurality of linguistic categories based on a linguistic input, the method comprising: configuring the linguistic classifier with first configuration data; processing a second plurality of user inputs to the system, wherein the processing includes, for each of the second plurality of user inputs, using the linguistic classifier configured with the first configuration data to determine a recognized linguistic category corresponding to said input, and causing determination of a corresponding response to the input based on the recognized linguistic category; storing second collected data, the second collected data comprising, for each of the second plurality of user inputs, a representation of the user input and the corresponding responses; receiving annotations for the second collected data, an annotation for each item of the second collected data indicating whether the corresponding response is consistent with the user input; determining second configuration data for the first linguistic classifier, the second configuration data being determined to distinguish the plurality of linguistic categories by computing the second configuration data to match the second annotated data; and configuring the linguistic classifier with the second configuration data. | 2. A method for configuring a natural language (NL) understanding system, the NL understanding system including at least a linguistic classifier, the linguistic classifier being configurable with configuration data to distinguish a plurality of linguistic categories based on a linguistic input, the method comprising: configuring the linguistic classifier with first configuration data; processing a second plurality of user inputs to the system, wherein the processing includes, for each of the second plurality of user inputs, using the linguistic classifier configured with the first configuration data to determine a recognized linguistic category corresponding to said input, and causing determination of a corresponding response to the input based on the recognized linguistic category; storing second collected data, the second collected data comprising, for each of the second plurality of user inputs, a representation of the user input and the corresponding responses; receiving annotations for the second collected data, an annotation for each item of the second collected data indicating whether the corresponding response is consistent with the user input; determining second configuration data for the first linguistic classifier, the second configuration data being determined to distinguish the plurality of linguistic categories by computing the second configuration data to match the second annotated data; and configuring the linguistic classifier with the second configuration data. 4. The method of claim 2 wherein the linguistic classifier comprises a slot recognizer, and the linguistic categories comprise slots. | 0.873092 |
9,507,435 | 17 | 18 | 17. The one or more computer-storage media devices of claim 16 , wherein replacing the display of the digital ink with the text comprises: monitoring for an occurrence of at least one predetermined event; and upon detecting the occurrence of a predetermined event, displaying the text in place of the digital ink. | 17. The one or more computer-storage media devices of claim 16 , wherein replacing the display of the digital ink with the text comprises: monitoring for an occurrence of at least one predetermined event; and upon detecting the occurrence of a predetermined event, displaying the text in place of the digital ink. 18. The one or more computer-storage media devices of claim 17 , wherein monitoring for the occurrence of at least one predetermined event comprises: monitoring for movement of the handheld writing device a predetermined distance from the location of the digital ink; monitoring for stabilization of recognition results for the handwriting input for a predetermined period of time; and monitoring for further handwriting input within a second predetermined period of time. | 0.869829 |
9,418,111 | 1 | 8 | 1. A method comprising: receiving, by one or more computers, input specifying, explicitly or implicitly, (i) an aggregation function agg having an input type and an output type, a relation s that has a domain and a range, wherein s represents one or more entities to be aggregated over, and a relation t that is a relation from the range of s to the input type of the aggregation function agg, and (ii) a recursive relation definition, wherein an aggregation construct agg* is within a recursive term of the recursive relation definition; and evaluating, by the one or more computers, the recursive relation definition, including evaluating the aggregation construct agg* to calculate a relation between the domain of s and the output type of the aggregation function agg according to
agg*( s,t )={( m ,agg( n ))|∃ d :( m,d )ε s,nεΠ{|t ( y )| yεs ( m )|}}. | 1. A method comprising: receiving, by one or more computers, input specifying, explicitly or implicitly, (i) an aggregation function agg having an input type and an output type, a relation s that has a domain and a range, wherein s represents one or more entities to be aggregated over, and a relation t that is a relation from the range of s to the input type of the aggregation function agg, and (ii) a recursive relation definition, wherein an aggregation construct agg* is within a recursive term of the recursive relation definition; and evaluating, by the one or more computers, the recursive relation definition, including evaluating the aggregation construct agg* to calculate a relation between the domain of s and the output type of the aggregation function agg according to
agg*( s,t )={( m ,agg( n ))|∃ d :( m,d )ε s,nεΠ{|t ( y )| yεs ( m )|}}. 8. The method of claim 1 , wherein receiving input comprises: receiving programming language input comprising language elements specifying, explicitly or implicitly, the aggregation construct agg* for the aggregation function agg. | 0.826546 |
8,740,620 | 13 | 14 | 13. The computer-based system of claim 1 , wherein said target language or said specified language is one or more of: English, Spanish, Italian, Portuguese, French, Dutch, Polish, German, Russian, Ukrainian, Mandarin, Wu, Cantonese, Hindi, Punjabi, Bengali, Marathi, Urdu, Arabic, Turkish, Tamil, Farsi, Japanese, Korean, Vietnamese, Thai, Burmese, Malay, Telugu, Javanese, and Tagalog. | 13. The computer-based system of claim 1 , wherein said target language or said specified language is one or more of: English, Spanish, Italian, Portuguese, French, Dutch, Polish, German, Russian, Ukrainian, Mandarin, Wu, Cantonese, Hindi, Punjabi, Bengali, Marathi, Urdu, Arabic, Turkish, Tamil, Farsi, Japanese, Korean, Vietnamese, Thai, Burmese, Malay, Telugu, Javanese, and Tagalog. 14. The computer-based system of claim 13 , wherein said target language is English. | 0.97503 |
9,665,559 | 10 | 11 | 10. The method of claim 1 wherein said plurality of electronic text document files are processed as a batch of files. | 10. The method of claim 1 wherein said plurality of electronic text document files are processed as a batch of files. 11. The method of claim 10 wherein a text report file is generated for said batch of files, identifying a list of any potentially inappropriate words found in each of said electronic text document files. | 0.959286 |
8,060,574 | 15 | 18 | 15. The central server of claim 14 wherein the metadata for the digital content comprises the default target quality level for the digital content, and in order to effect review of the digital content, the control system is further configured to: a) select a group of reviewers from the others of the plurality of authors for a review at a first quality level that is less than the default target quality level based on the reviewer credentials; b) effect transfer of the digital content to user devices associated with the group of reviewers; c) receive feedback from the group of reviewers; d) determine whether the digital content is to be reviewed at a next quality level based on the feedback and the default target quality level; and e) if the digital content is to be reviewed at the next quality level, repeat a)-e) for the next quality level. | 15. The central server of claim 14 wherein the metadata for the digital content comprises the default target quality level for the digital content, and in order to effect review of the digital content, the control system is further configured to: a) select a group of reviewers from the others of the plurality of authors for a review at a first quality level that is less than the default target quality level based on the reviewer credentials; b) effect transfer of the digital content to user devices associated with the group of reviewers; c) receive feedback from the group of reviewers; d) determine whether the digital content is to be reviewed at a next quality level based on the feedback and the default target quality level; and e) if the digital content is to be reviewed at the next quality level, repeat a)-e) for the next quality level. 18. The central server of claim 15 wherein the control system is further configured to provide the feedback to the one of the plurality of authors based on the feedback from each of the groups of reviewers if the digital content is not to be reviewed at the next quality level. | 0.887123 |
8,538,752 | 18 | 19 | 18. An apparatus for predicting a word accuracy, comprising: a processor; and a computer-readable medium in communication with the processor, storing a plurality of instructions which, when executed by the processor, cause the processor to perform operations, the operations comprising: obtaining an utterance in speech data, wherein the utterance comprises an actual word string; processing the utterance for generating an interpretation of the actual word string; processing the utterance to identify an utterance frame; and calculating a prediction of a word accuracy associated with the interpretation based on a stationary signal-to-noise ratio and a non-stationary signal-to-noise ratio, wherein the stationary signal-to-noise ratio and the non-stationary signal-to-noise ratio are determined according to a frame energy associated with the utterance frame, and wherein the calculating the prediction of the word accuracy associated with the interpretation comprises: computing the stationary signal-to-noise ratio for the utterance; computing the non-stationary signal-to-noise ratio for the utterance; and computing the prediction of the word accuracy associated with the interpretation using the stationary signal-to-noise ratio and the non-stationary signal-to-noise ratio. | 18. An apparatus for predicting a word accuracy, comprising: a processor; and a computer-readable medium in communication with the processor, storing a plurality of instructions which, when executed by the processor, cause the processor to perform operations, the operations comprising: obtaining an utterance in speech data, wherein the utterance comprises an actual word string; processing the utterance for generating an interpretation of the actual word string; processing the utterance to identify an utterance frame; and calculating a prediction of a word accuracy associated with the interpretation based on a stationary signal-to-noise ratio and a non-stationary signal-to-noise ratio, wherein the stationary signal-to-noise ratio and the non-stationary signal-to-noise ratio are determined according to a frame energy associated with the utterance frame, and wherein the calculating the prediction of the word accuracy associated with the interpretation comprises: computing the stationary signal-to-noise ratio for the utterance; computing the non-stationary signal-to-noise ratio for the utterance; and computing the prediction of the word accuracy associated with the interpretation using the stationary signal-to-noise ratio and the non-stationary signal-to-noise ratio. 19. The apparatus of claim 18 , wherein the obtaining the utterance in speech data, the processing the utterance to generate the interpretation of the actual word string, the processing the utterance to identify the utterance frame, and the calculating the prediction of the word accuracy are repeated for an additional utterance. | 0.683301 |
8,156,079 | 1 | 6 | 1. A method of tracking a plurality of objects being stored, comprising: applying a search optimization algorithm to the name of each of the plurality of objects being stored to generate a name value for each of the plurality of objects comprising at least a portion of each name for each of the plurality of objects; concatenating the name values of each of the plurality of objects into a hint, wherein the hint comprises a single value formed by appending the name values of each of the plurality of objects end to end; associating the plurality of objects with a saveset; associating the hint with the saveset; storing the hint in an index, wherein the index comprises a savepoint configured to store information about a longest pathname containing the plurality of objects; wherein concatenating at least a portion of a name of each object into the hint includes selecting a portion of the name of each object; and wherein the name of each object comprises characters, and selecting a portion of the name of each object includes selecting the first n characters of the name of each object. | 1. A method of tracking a plurality of objects being stored, comprising: applying a search optimization algorithm to the name of each of the plurality of objects being stored to generate a name value for each of the plurality of objects comprising at least a portion of each name for each of the plurality of objects; concatenating the name values of each of the plurality of objects into a hint, wherein the hint comprises a single value formed by appending the name values of each of the plurality of objects end to end; associating the plurality of objects with a saveset; associating the hint with the saveset; storing the hint in an index, wherein the index comprises a savepoint configured to store information about a longest pathname containing the plurality of objects; wherein concatenating at least a portion of a name of each object into the hint includes selecting a portion of the name of each object; and wherein the name of each object comprises characters, and selecting a portion of the name of each object includes selecting the first n characters of the name of each object. 6. The method as recited in claim 1 , wherein concatenating at least a portion of a name of each object into the hint includes concatenating the name of each object into the hint. | 0.57783 |
9,069,755 | 11 | 18 | 11. One or more computer-readable storage devices having computer-executable instructions, which when executed perform steps, comprising, performing machine translation or speech recognition on natural language input by estimating a probability for a token in a natural language sequence of n tokens based upon a number of times the token was observed in training data following a natural language sequence of n−1 tokens using actual counts, including, when the number of times is greater than zero, computing the probability based upon count data, a discount parameter and interpolation weights in which the interpolation weights are not determined from the discount parameter and are computed based upon a smaller context than the natural language sequence of n−1 tokens, correcting the estimated probability for the token representing at least one output candidate for the natural language input by mathematically combining the discount probability with the interpolation probability to provide the estimated probability, and when the number of times is zero, computing the probability based upon a backoff weight. | 11. One or more computer-readable storage devices having computer-executable instructions, which when executed perform steps, comprising, performing machine translation or speech recognition on natural language input by estimating a probability for a token in a natural language sequence of n tokens based upon a number of times the token was observed in training data following a natural language sequence of n−1 tokens using actual counts, including, when the number of times is greater than zero, computing the probability based upon count data, a discount parameter and interpolation weights in which the interpolation weights are not determined from the discount parameter and are computed based upon a smaller context than the natural language sequence of n−1 tokens, correcting the estimated probability for the token representing at least one output candidate for the natural language input by mathematically combining the discount probability with the interpolation probability to provide the estimated probability, and when the number of times is zero, computing the probability based upon a backoff weight. 18. The one or more computer-readable storage devices of claim 11 having further computer-executable instruction comprising setting the discount parameter by using a first discount value if the sequence is of length one, using a second discount value if the sequence is of length two, and using a third discount value if the sequence is greater than length two. | 0.622385 |
8,103,099 | 3 | 4 | 3. A method for providing characters and character groups from a roundel image comprising the steps of: vertically-aligning a region of electronically represented text in the roundel image; determining a point at which the roundel image starts; electronically analyzing the region to produce characters and character confidences; dividing the roundel image into sections according to the point; selecting the characters associated with highest character confidence values of the character confidences; computing character group confidences by summing the highest character confidence values for each of the selected characters that form the character groups; selecting the character groups with highest character group confidence values of the character group confidences as the selected character groups; marking each of the selected character groups as flipped; creating flipped marked character groups if the selected character group meets pre-determined criteria; marking each of the selected character groups in one of the sections as unflipped if none of the selected character groups in the one section is flipped, or if the one section includes predetermined text that is unflipped; if there are the flipped marked character groups, creating an image by rearranging the underlying representation of the flipped marked character groups; electronically analyzing the image to produce new characters each associated with new character confidences; selecting final characters according to the associated new character confidences; and providing the final characters to an electronic sink. | 3. A method for providing characters and character groups from a roundel image comprising the steps of: vertically-aligning a region of electronically represented text in the roundel image; determining a point at which the roundel image starts; electronically analyzing the region to produce characters and character confidences; dividing the roundel image into sections according to the point; selecting the characters associated with highest character confidence values of the character confidences; computing character group confidences by summing the highest character confidence values for each of the selected characters that form the character groups; selecting the character groups with highest character group confidence values of the character group confidences as the selected character groups; marking each of the selected character groups as flipped; creating flipped marked character groups if the selected character group meets pre-determined criteria; marking each of the selected character groups in one of the sections as unflipped if none of the selected character groups in the one section is flipped, or if the one section includes predetermined text that is unflipped; if there are the flipped marked character groups, creating an image by rearranging the underlying representation of the flipped marked character groups; electronically analyzing the image to produce new characters each associated with new character confidences; selecting final characters according to the associated new character confidences; and providing the final characters to an electronic sink. 4. The method as in claim 3 further comprising the steps of: determining unflipped characters and unflipped character confidences for each character in the vertically-aligned electronically represented text; flipping the characters; determining flipped characters and flipped character confidences for the flipped characters; selecting a set of character confidences from the unflipped confidences and the flipped confidences according to predetermined criteria; summing the set of character confidences for each of the characters to compile a set of unflipped character group confidences; and summing the set of flipped character confidences for each of the flipped characters to compile a set of flipped character group confidences. | 0.567727 |
7,904,411 | 1 | 11 | 1. A method to determine and display indicia of a relationship definition between data items that have been integrated into a database from a plurality of data sources associated with a domain type, comprising: providing, in the database, a plurality of entity tables relevant to the domain type, wherein a system server stores data items extracted from the plurality of data sources in respective fields of the plurality of entity tables, including storing a first data item extracted from a first data source in a first field and storing a second data item extracted from the first data source in a second field, wherein the plurality of data sources includes both structured and unstructured data sources, and wherein the system server is configured to: populate a first row of a direct relationship table having a plurality of rows with a first direct relationship definition indicating that the first and second fields store respective data items that have been extracted from the first data source, search the direct relationship table for a second row having a second direct relationship definition indicating that a third field stores a third data item that has been extracted from a second data source from which the first data item has also been extracted, wherein the second data source is different than the first data source, determine a transitive relationship definition, based on the first direct and second direct relationship definitions from the direct relationship table, indicating that the second field is related to the third field, wherein the transitive relationship definition is based on at least two separate relationships between data fields, and store the third relationship definition in a transitive relationship table; displaying the second data item on a graphical user interface on a display; and receiving an activation by a user of the second data item and responsively displaying, on the graphical user interface, indicia representing the third relationship definition. | 1. A method to determine and display indicia of a relationship definition between data items that have been integrated into a database from a plurality of data sources associated with a domain type, comprising: providing, in the database, a plurality of entity tables relevant to the domain type, wherein a system server stores data items extracted from the plurality of data sources in respective fields of the plurality of entity tables, including storing a first data item extracted from a first data source in a first field and storing a second data item extracted from the first data source in a second field, wherein the plurality of data sources includes both structured and unstructured data sources, and wherein the system server is configured to: populate a first row of a direct relationship table having a plurality of rows with a first direct relationship definition indicating that the first and second fields store respective data items that have been extracted from the first data source, search the direct relationship table for a second row having a second direct relationship definition indicating that a third field stores a third data item that has been extracted from a second data source from which the first data item has also been extracted, wherein the second data source is different than the first data source, determine a transitive relationship definition, based on the first direct and second direct relationship definitions from the direct relationship table, indicating that the second field is related to the third field, wherein the transitive relationship definition is based on at least two separate relationships between data fields, and store the third relationship definition in a transitive relationship table; displaying the second data item on a graphical user interface on a display; and receiving an activation by a user of the second data item and responsively displaying, on the graphical user interface, indicia representing the third relationship definition. 11. The method of claim 1 further comprising: storing in the database an entity table that contains attributes about an unstructured data source, including a title of the unstructured data source; and establishing in the database a field-to-text link between a data item integrated from a structured data source and the entity table if the integrated data item is mentioned in the unstructured data source. | 0.792008 |
10,052,147 | 19 | 20 | 19. A non-transitory computer readable storage device storing a program of instructions executable by a machine to perform a method for touch-free operation of an ablator workstation by an associated user, comprising: detecting location and motion movements of a body part of the associated user, receiving detected location and motion movements of the body part, deducing a gesture based on the received motion movement of the body part, validating the gesture based on a physical characteristic of the gesture, determining whether the validated gesture is defined with an ablator task, causing the ablator workstation to perform the ablator task, comparing a difference between an initial movement location and a subsequent movement location, authorizing the gesture as being from the associated user when the difference is within a predicted location, and associating the ablator workstation to the user, thereby giving control of the ablator workstation to the associated user, wherein the ablator workstation is disassociated from the associated user after a period of motionlessness. | 19. A non-transitory computer readable storage device storing a program of instructions executable by a machine to perform a method for touch-free operation of an ablator workstation by an associated user, comprising: detecting location and motion movements of a body part of the associated user, receiving detected location and motion movements of the body part, deducing a gesture based on the received motion movement of the body part, validating the gesture based on a physical characteristic of the gesture, determining whether the validated gesture is defined with an ablator task, causing the ablator workstation to perform the ablator task, comparing a difference between an initial movement location and a subsequent movement location, authorizing the gesture as being from the associated user when the difference is within a predicted location, and associating the ablator workstation to the user, thereby giving control of the ablator workstation to the associated user, wherein the ablator workstation is disassociated from the associated user after a period of motionlessness. 20. The non-transitory computer readable storage device of claim 19 , wherein a different ablator task is caused to be performed when voice input is received in conjunction with the gesture. | 0.715569 |
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