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7,979,280 | 1 | 3 | 1. A method for converting an input linguistic description into a speech waveform comprising: deriving at least one target unit sequence corresponding to the input linguistic description; assigning in a waveform unit database one or more waveform units to each target unit of the at least one target unit sequence; selecting for the at least one target unit sequence a plurality of alternative waveform unit sequences approximating the at least one target unit sequence, using the one or more waveform units assigned to each target unit of the at least one target unit sequence; concatenating the alternative waveform unit sequences to form alternative speech waveforms; and presenting the alternative speech waveforms to an operating person and enabling the choice of one of the presented alternative speech waveforms. | 1. A method for converting an input linguistic description into a speech waveform comprising: deriving at least one target unit sequence corresponding to the input linguistic description; assigning in a waveform unit database one or more waveform units to each target unit of the at least one target unit sequence; selecting for the at least one target unit sequence a plurality of alternative waveform unit sequences approximating the at least one target unit sequence, using the one or more waveform units assigned to each target unit of the at least one target unit sequence; concatenating the alternative waveform unit sequences to form alternative speech waveforms; and presenting the alternative speech waveforms to an operating person and enabling the choice of one of the presented alternative speech waveforms. 3. Method as claimed in claim 1 , wherein at least one unit of at least one target unit sequence has a target pitch that is higher or lower by a predetermined minimal amount than the pitch of the corresponding unit of a previously selected waveform unit sequence. | 0.678484 |
9,672,010 | 4 | 9 | 4. A universal modeling language (UML) analysis system, comprising: at least one processor; a memory coupled to the at least one processor, wherein the memory stores program instructions, wherein the program instructions are executable by the at least one processor to: import at least one tool-specific UML model from at least one UML tool, capture a snapshot of the at least one tool-specific UML model, wherein the snapshot comprises text data and at least one diagram, translate the at least one tool-specific UML model into at least one transformed UML model having a universal UML format; at least one transforming mechanism configured to translate the at least one tool-specific UML model into the universal UML format, wherein the transforming mechanism is configured to extract base data and one or more associated extended elements from the tool-specific UML model; and a monitor coupled to the at least one processor, wherein the at least one processor is configured to display a model navigation interface on the monitor, and display particular model elements based on commands input through the model navigation interface. | 4. A universal modeling language (UML) analysis system, comprising: at least one processor; a memory coupled to the at least one processor, wherein the memory stores program instructions, wherein the program instructions are executable by the at least one processor to: import at least one tool-specific UML model from at least one UML tool, capture a snapshot of the at least one tool-specific UML model, wherein the snapshot comprises text data and at least one diagram, translate the at least one tool-specific UML model into at least one transformed UML model having a universal UML format; at least one transforming mechanism configured to translate the at least one tool-specific UML model into the universal UML format, wherein the transforming mechanism is configured to extract base data and one or more associated extended elements from the tool-specific UML model; and a monitor coupled to the at least one processor, wherein the at least one processor is configured to display a model navigation interface on the monitor, and display particular model elements based on commands input through the model navigation interface. 9. The UML analysis system of claim 4 , wherein the program instructions are executable by the at least one processor to import a plurality of tool-specific UML models from a plurality of UML tools, wherein the plurality of tool-specific UML models are in different tool-specific formats, and wherein the program instructions are executable by the at least one processor to translate the plurality of tool-specific UML models into a plurality of transformed UML models, wherein each of the plurality of transformed UML models is in the universal UML format. | 0.5 |
7,565,632 | 1 | 2 | 1. A behavioral synthesis system for generating a circuit description at low abstractness from a behavioral-level description, said system comprising: language analyzing means for analyzing a behavioral-level description entered thereinto for conversion into an internal representation for behavioral synthesis, and for generating an internal representation indicative of a correspondence relationship between a pointer variable and a specific circuit entity when the pointer variable is converted into a specific circuit entity, based on a pointer type specification within the behavioral-level description; pointer-terminal converting means for converting a pointer variable in the internal representation generated by said language analyzing means into a set of a terminal and a condition section, based on a conversion rule; and behavioral synthesizing means for performing behavioral synthesis processing for the internal representation from which the pointer variable has been removed by said pointer-terminal converting means to generate and supply a circuit description at low abstractness; wherein the behavioral synthesis system includes providing a design flow which allows a caller function to be completely independent of the implementation of a callee function upon synthesis of the caller function. | 1. A behavioral synthesis system for generating a circuit description at low abstractness from a behavioral-level description, said system comprising: language analyzing means for analyzing a behavioral-level description entered thereinto for conversion into an internal representation for behavioral synthesis, and for generating an internal representation indicative of a correspondence relationship between a pointer variable and a specific circuit entity when the pointer variable is converted into a specific circuit entity, based on a pointer type specification within the behavioral-level description; pointer-terminal converting means for converting a pointer variable in the internal representation generated by said language analyzing means into a set of a terminal and a condition section, based on a conversion rule; and behavioral synthesizing means for performing behavioral synthesis processing for the internal representation from which the pointer variable has been removed by said pointer-terminal converting means to generate and supply a circuit description at low abstractness; wherein the behavioral synthesis system includes providing a design flow which allows a caller function to be completely independent of the implementation of a callee function upon synthesis of the caller function. 2. The behavioral synthesis system according to claim 1 , further comprising pointer type specification analyzing means for analyzing a pointer type specification which is a designation of a pointer variable to a specific circuit entity in the entered behavioral-level description for conversation into an internal representation for behavioral synthesis. | 0.587209 |
7,860,705 | 1 | 12 | 1. A method of context adaptation of a speech-to-speech translation system comprising the steps of: extracting a plurality of sets of paralinguistic attribute values from a plurality of input signals, wherein each set of the plurality of sets of paralinguistic attribute values is extracted from a corresponding input signal of the plurality of input signals via a corresponding classifier of a plurality of classifiers; generating a final set of paralinguistic attribute values for the plurality of input signals from the plurality of sets of paralinguistic attribute values; and modifying performance of at least one of a speech recognition module, a translation module and a text-to-speech module of the speech-to-speech translation system in accordance with the final set of paralinguistic attribute values for the plurality of input signals; wherein the set of paralinguistic attribute values that each classifier extracts is represented by a vector signal output by the classifier, the vector signal comprising two or more values corresponding to two or more paralinguistic attributes of interest such that the step of generating the final set of paralinguistic attribute values comprises combining each of the vector signals from each of the classifiers by combining values of common paralinguistic attributes of interest across the vector signals to yield a separate decision value for each of the two or more paralinguistic attributes of interest, the final set of paralinguistic attribute values comprising a plurality of decision values corresponding to respective ones of the two or more paralinguistic attributes of interest; further wherein the extracting, generating and modifying steps are implemented via instruction code that is executed by at least one processor device. | 1. A method of context adaptation of a speech-to-speech translation system comprising the steps of: extracting a plurality of sets of paralinguistic attribute values from a plurality of input signals, wherein each set of the plurality of sets of paralinguistic attribute values is extracted from a corresponding input signal of the plurality of input signals via a corresponding classifier of a plurality of classifiers; generating a final set of paralinguistic attribute values for the plurality of input signals from the plurality of sets of paralinguistic attribute values; and modifying performance of at least one of a speech recognition module, a translation module and a text-to-speech module of the speech-to-speech translation system in accordance with the final set of paralinguistic attribute values for the plurality of input signals; wherein the set of paralinguistic attribute values that each classifier extracts is represented by a vector signal output by the classifier, the vector signal comprising two or more values corresponding to two or more paralinguistic attributes of interest such that the step of generating the final set of paralinguistic attribute values comprises combining each of the vector signals from each of the classifiers by combining values of common paralinguistic attributes of interest across the vector signals to yield a separate decision value for each of the two or more paralinguistic attributes of interest, the final set of paralinguistic attribute values comprising a plurality of decision values corresponding to respective ones of the two or more paralinguistic attributes of interest; further wherein the extracting, generating and modifying steps are implemented via instruction code that is executed by at least one processor device. 12. The method of claim 1 , wherein the step of modifying performance comprises the step of obtaining an appropriate pronunciation in the text-to-speech module based on the final set of paralinguistic attribute values. | 0.787524 |
7,516,198 | 13 | 18 | 13. A method in a network node, the method comprising: receiving by the network node, for transfer between an application server configured for outputting a flow of data packets associated with an application service and a destination device configured for receiving the flow of data packets, a message having XML tags specifying prescribed user-selected quality of service attributes for the application service, the network node distinct from the destination device and the application server; parsing by the network node the XML tags for determining the prescribed user-selected quality of service attributes; selecting network parameters by the network node, based on the network node interpreting the XML tags and the prescribed user-selected quality of service attributes, enabling the flow of data packets to be transferred for the application service according to the user-selected quality of service attributes; and identifying and transferring by the network node the flow of data packets between the application server and toward the destination device according to an open network protocol and the selected network parameters. | 13. A method in a network node, the method comprising: receiving by the network node, for transfer between an application server configured for outputting a flow of data packets associated with an application service and a destination device configured for receiving the flow of data packets, a message having XML tags specifying prescribed user-selected quality of service attributes for the application service, the network node distinct from the destination device and the application server; parsing by the network node the XML tags for determining the prescribed user-selected quality of service attributes; selecting network parameters by the network node, based on the network node interpreting the XML tags and the prescribed user-selected quality of service attributes, enabling the flow of data packets to be transferred for the application service according to the user-selected quality of service attributes; and identifying and transferring by the network node the flow of data packets between the application server and toward the destination device according to an open network protocol and the selected network parameters. 18. The method of claim 13 , further comprising the network node caching the selected network parameters and identifiers for identification of subsequent packets received for the identified flow of data packets and outputting according to the selected network parameters. | 0.759752 |
7,546,334 | 12 | 13 | 12. A method of filtering and securing data as claimed in claim 11 wherein retrieving includes retrieving taxonomic words, characters or data objects from said compilation of additional data related to said security sensitive words, characters or data objects and is based upon categorization and classification as reflected in said compilation of additional data and as related to said security sensitive words, characters or data objects. | 12. A method of filtering and securing data as claimed in claim 11 wherein retrieving includes retrieving taxonomic words, characters or data objects from said compilation of additional data related to said security sensitive words, characters or data objects and is based upon categorization and classification as reflected in said compilation of additional data and as related to said security sensitive words, characters or data objects. 13. A method of filtering and securing data as claimed in claim 12 wherein storing the extracted data separately from said remainder data is based upon multiple security levels. | 0.5 |
10,049,127 | 25 | 27 | 25. An apparatus, comprising: one or more store elements; means for instantiating one or more concurrently accessible objects in the store elements; and means for performing source-level transaction-based accesses of the concurrently accessible objects in accordance with one or more methods defined in an object-oriented programming language; wherein performing a source-level transaction-based access of a given concurrently accessible object comprises an atomic transaction invoking the one or more methods to implement: determining based on at least one header word whether the object is being accessed; and in response to determining that the object is not being accessed: modifying a working copy of the object; perform one or more access operations targeting one or more other objects; and committing the atomic transaction, wherein said committing is performed subsequent to said modifying the working copy of the object and subsequent to the performing the one or more access operations, wherein the working copy becomes the current shared object. | 25. An apparatus, comprising: one or more store elements; means for instantiating one or more concurrently accessible objects in the store elements; and means for performing source-level transaction-based accesses of the concurrently accessible objects in accordance with one or more methods defined in an object-oriented programming language; wherein performing a source-level transaction-based access of a given concurrently accessible object comprises an atomic transaction invoking the one or more methods to implement: determining based on at least one header word whether the object is being accessed; and in response to determining that the object is not being accessed: modifying a working copy of the object; perform one or more access operations targeting one or more other objects; and committing the atomic transaction, wherein said committing is performed subsequent to said modifying the working copy of the object and subsequent to the performing the one or more access operations, wherein the working copy becomes the current shared object. 27. The apparatus of claim 25 , further comprising means for accessing the one or more objects without blocking. | 0.662651 |
7,962,461 | 1 | 17 | 1. A computer-implemented method comprising: at a server having one or more processors and memory storing one or more programs for execution by the one or more processors, collecting information containing product reviews for a plurality of products, wherein a respective product review provides a critical, subjective evaluation of a corresponding product by a human in electronic form; automatically extracting product reviews from the collected information; for at least some of the extracted product reviews, identifying a particular product that is associated with the extracted product review; and for each particular product in at least a subset of the plurality of products, generating aggregated review information for the particular product based on extracted product reviews that are associated with the particular product; storing the extracted product reviews and the aggregated review information; receiving a request from a client for an aggregated review of a product, the aggregated review of the product including portions of extracted product reviews of the product; and sending the aggregated review of the product in response to the request, wherein the aggregated review of the product includes a list of server-suggested search terms that are automatically selected from extracted product reviews of the product in accordance with their respective weighted occurrences in the extracted product reviews of the product. | 1. A computer-implemented method comprising: at a server having one or more processors and memory storing one or more programs for execution by the one or more processors, collecting information containing product reviews for a plurality of products, wherein a respective product review provides a critical, subjective evaluation of a corresponding product by a human in electronic form; automatically extracting product reviews from the collected information; for at least some of the extracted product reviews, identifying a particular product that is associated with the extracted product review; and for each particular product in at least a subset of the plurality of products, generating aggregated review information for the particular product based on extracted product reviews that are associated with the particular product; storing the extracted product reviews and the aggregated review information; receiving a request from a client for an aggregated review of a product, the aggregated review of the product including portions of extracted product reviews of the product; and sending the aggregated review of the product in response to the request, wherein the aggregated review of the product includes a list of server-suggested search terms that are automatically selected from extracted product reviews of the product in accordance with their respective weighted occurrences in the extracted product reviews of the product. 17. The computer-implemented method of claim 1 , wherein the aggregated review of the product includes frequently appearing phrases in the extracted product reviews associated with the particular product. | 0.635714 |
8,781,102 | 17 | 24 | 17. A method for analyzing an electronic communication between a customer and a contact center, the method comprising: receiving a single electronic communication from a communicant; generating a text file from the electronic communication; analyzing the text file of the electronic communication by mining the text file generated from the electronic communication and applying a predetermined linguistic-based psychological behavioral model to the text file generated from the electronic communication; and generating behavioral assessment data including a personality type corresponding to the analyzed text file of the electronic communication. | 17. A method for analyzing an electronic communication between a customer and a contact center, the method comprising: receiving a single electronic communication from a communicant; generating a text file from the electronic communication; analyzing the text file of the electronic communication by mining the text file generated from the electronic communication and applying a predetermined linguistic-based psychological behavioral model to the text file generated from the electronic communication; and generating behavioral assessment data including a personality type corresponding to the analyzed text file of the electronic communication. 24. The method of claim 17 , which further comprises adapting the predetermined linguistic-based psychological behavioral model to assess distress levels in a communication, the method further comprising generating distress assessment data corresponding to the analyzed text file. | 0.829476 |
9,633,275 | 1 | 9 | 1. A computer-implemented method for extracting pixel-level micro-features from image data captured by a video camera, the method comprising: receiving the image data; identifying a set of pixels in the image data associated with a foreground patch that depicts a foreground object; evaluating appearance values of the pixels included in the set of pixels to compute a plurality of micro-feature values representing the foreground object, each based on at least one pixel-level characteristic of the foreground patch, wherein the micro-feature values are computed independent of training data that defines a plurality of object types; generating a micro-feature vector that includes the plurality of micro-feature values; classifying the foreground object as depicting an object type as based on the micro-feature vector, wherein the object type is determined by mapping the micro-feature vector to a cluster in a self-organizing map (SOM) adaptive resonance theory (ART) network generated from a plurality of micro-feature vectors; and updating one or more cluster properties associated with the cluster based on the plurality of micro-feature values in the generated micro-feature vector. | 1. A computer-implemented method for extracting pixel-level micro-features from image data captured by a video camera, the method comprising: receiving the image data; identifying a set of pixels in the image data associated with a foreground patch that depicts a foreground object; evaluating appearance values of the pixels included in the set of pixels to compute a plurality of micro-feature values representing the foreground object, each based on at least one pixel-level characteristic of the foreground patch, wherein the micro-feature values are computed independent of training data that defines a plurality of object types; generating a micro-feature vector that includes the plurality of micro-feature values; classifying the foreground object as depicting an object type as based on the micro-feature vector, wherein the object type is determined by mapping the micro-feature vector to a cluster in a self-organizing map (SOM) adaptive resonance theory (ART) network generated from a plurality of micro-feature vectors; and updating one or more cluster properties associated with the cluster based on the plurality of micro-feature values in the generated micro-feature vector. 9. The computer-implemented method of claim 1 , wherein one of the computed micro-feature values is a legged-ness value based on a sum of angles between neighboring segments of a start skeleton of the foreground patch and the pixel-level characteristic is the star skeleton of the foreground patch. | 0.514658 |
8,219,516 | 13 | 14 | 13. The method of claim 12 , wherein the outputting the representation of the recommendation to change the first query comprises transmitting data configured to display the representation of the recommendation in at least one of a written form and a graphic form, and wherein the transmitting the second query comprises receiving an input at the database interface processing device that interacts with the at least one of the written form and the graphic form. | 13. The method of claim 12 , wherein the outputting the representation of the recommendation to change the first query comprises transmitting data configured to display the representation of the recommendation in at least one of a written form and a graphic form, and wherein the transmitting the second query comprises receiving an input at the database interface processing device that interacts with the at least one of the written form and the graphic form. 14. The method of claim 13 , wherein the representation of the recommendation to change the first query comprises at least one of a written hyperlink and a graphic hyperlink. | 0.5 |
6,151,609 | 7 | 11 | 7. A remote system administration method, comprising the steps of: communicating an editor input form from a server through a network to a client in response to receiving a request from the client, the client using a forms-enabled and script-enabled web browser; receiving a server path input at the server from the web browser; communicating a file selection form from the server to the web browser, the file selection form including filenames identifying files included in a server path defined by the server path input; receiving a file selection from the web browser at the server, the file selection identifying one of the files; and communicating a copy of one of the files from the server to the web browser for editing; receiving by the server an updated file for storage, the updated file produced by editing the copy of the one of the files using the web browser without the use of a plug-in to the web browser. | 7. A remote system administration method, comprising the steps of: communicating an editor input form from a server through a network to a client in response to receiving a request from the client, the client using a forms-enabled and script-enabled web browser; receiving a server path input at the server from the web browser; communicating a file selection form from the server to the web browser, the file selection form including filenames identifying files included in a server path defined by the server path input; receiving a file selection from the web browser at the server, the file selection identifying one of the files; and communicating a copy of one of the files from the server to the web browser for editing; receiving by the server an updated file for storage, the updated file produced by editing the copy of the one of the files using the web browser without the use of a plug-in to the web browser. 11. The method of claim 7, further comprising communicating a text message to the client indicating that the one of the files is not viewable by the web browser. | 0.741987 |
9,563,635 | 13 | 14 | 13. A computer system for eliminating redundant information in a log file having unknown grammar, the computer system comprising: one or more computer processors; one or more computer-readable storage media; program instructions stored on the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to identify an alphanumeric string in a log file, the alphanumeric string comprising a plurality of alphanumeric substrings separated by non-alphanumeric characters, the plurality of alphanumeric substrings including at least two distinct alphanumeric substrings; program instructions to replace each alphanumeric substring of the plurality of alphanumeric substrings with a first alphanumeric character to generate a first resulting string that includes the non-alphanumeric characters and multiple occurrences of the first alphanumeric character; program instructions to replace each pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string with a second alphanumeric character to generate a second resulting string, wherein the program instructions to replace each pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string with a second alphanumeric character to generate a second resulting string comprise: program instructions to, responsive to determining that there are multiple distinct pairs of characters of the first resulting string that are identical to another pair of characters of the first resulting string and that the multiple distinct pairs of characters occur an equal number of times in the first resulting string, select a pair of the multiple distinct pairs of characters based on a pre-defined hierarchy of characters included in the multiple distinct pairs of characters, and program instructions to replace the selected pair of characters with a second alphanumeric character to generate a second resulting string; and program instructions to replace consecutive occurrences of the second alphanumeric character, in the second resulting string, with one occurrence of the second alphanumeric character to generate a compressed string. | 13. A computer system for eliminating redundant information in a log file having unknown grammar, the computer system comprising: one or more computer processors; one or more computer-readable storage media; program instructions stored on the computer-readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to identify an alphanumeric string in a log file, the alphanumeric string comprising a plurality of alphanumeric substrings separated by non-alphanumeric characters, the plurality of alphanumeric substrings including at least two distinct alphanumeric substrings; program instructions to replace each alphanumeric substring of the plurality of alphanumeric substrings with a first alphanumeric character to generate a first resulting string that includes the non-alphanumeric characters and multiple occurrences of the first alphanumeric character; program instructions to replace each pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string with a second alphanumeric character to generate a second resulting string, wherein the program instructions to replace each pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string with a second alphanumeric character to generate a second resulting string comprise: program instructions to, responsive to determining that there are multiple distinct pairs of characters of the first resulting string that are identical to another pair of characters of the first resulting string and that the multiple distinct pairs of characters occur an equal number of times in the first resulting string, select a pair of the multiple distinct pairs of characters based on a pre-defined hierarchy of characters included in the multiple distinct pairs of characters, and program instructions to replace the selected pair of characters with a second alphanumeric character to generate a second resulting string; and program instructions to replace consecutive occurrences of the second alphanumeric character, in the second resulting string, with one occurrence of the second alphanumeric character to generate a compressed string. 14. The computer system of claim 13 , wherein the replacement of each pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string is responsive to determining that a number of occurrences of a pair of characters of the first resulting string that is identical to another pair of characters of the first resulting string is equal to or greater than a minimum cutoff value. | 0.5 |
9,754,210 | 11 | 13 | 11. One or more computer-storage media storing computer-useable instructions that, when executed by a computing device, perform a method for determining user interests, comprising: identifying a digital content in user activity data that describes an interaction between a user and said digital content; identifying a first entity and a second entity that are matched to the digital content by mapping data, said first entity and said second entity being a topic of said digital content, wherein said first entity and said second entity are included within a knowledge base comprising a plurality of entities, said knowledge base comprising an ontology comprising a knowledge graph that indicates relationships between said plurality of entities; generating first interest-level data that represents a first level of interest between said user and said first entity and said second entity; identifying a candidate entity based on said candidate entity having a relationship to both the first entity and the second entity within the knowledge base; generating second interest-level data that represents a second level of interest between said user and said candidate entity based on an analysis of said relationship; linking a user ID associated with the user to the candidate entity, thereby indicating the user is interested in the candidate entity; receiving a search query from the user; and generating a search result comprising digital contents, in response to the received search query, wherein the digital contents are ranked using the generated first interest-level data and the generated second interest-level data. | 11. One or more computer-storage media storing computer-useable instructions that, when executed by a computing device, perform a method for determining user interests, comprising: identifying a digital content in user activity data that describes an interaction between a user and said digital content; identifying a first entity and a second entity that are matched to the digital content by mapping data, said first entity and said second entity being a topic of said digital content, wherein said first entity and said second entity are included within a knowledge base comprising a plurality of entities, said knowledge base comprising an ontology comprising a knowledge graph that indicates relationships between said plurality of entities; generating first interest-level data that represents a first level of interest between said user and said first entity and said second entity; identifying a candidate entity based on said candidate entity having a relationship to both the first entity and the second entity within the knowledge base; generating second interest-level data that represents a second level of interest between said user and said candidate entity based on an analysis of said relationship; linking a user ID associated with the user to the candidate entity, thereby indicating the user is interested in the candidate entity; receiving a search query from the user; and generating a search result comprising digital contents, in response to the received search query, wherein the digital contents are ranked using the generated first interest-level data and the generated second interest-level data. 13. The one or more computer-storage media of claim 11 , wherein said first entity and said second entity and said candidate entity are each instance entities of said ontology. | 0.678832 |
8,396,733 | 8 | 11 | 8. A method, comprising: receiving, by a location decisioning system at a first computing device, a process criteria for a work function associated with an organization; receiving, by the location decisioning system, a provider attribute including a desired quality of a provider performing the work function; receiving, by the location decisioning system, a plurality of additional factors associated with the work function, the plurality of additional factors including whether information associated with the work function is non-public or privileged, whether intellectual property is involved with the work function, whether knowledge retention is desired for the work function, and whether management oversight is desired for the work function; determining, by the location decisioning system, whether the work function is eligible to be performed by an internal work group of the organization and a supplier external to the organization; and responsive to determining that the work function is eligible to be performed by an internal work group of the organization and a supplier external to the organization, determining, by the location decisioning system, a recommended location in which to perform the work function associated with the organization based on the received process criteria for the work function, the received provider attribute, including the desired quality of the provider performing the work function, the received plurality of additional factors associated with the work function, and the determination that the work function is eligible to be performed by an internal work group of the organization and a supplier external to the organization, wherein the recommended location in which to perform the work function associated with the organization is determined based at least in part on the plurality of additional factors, including whether information associated with the work function is non-public or privileged, whether intellectual property is involved with the work function, whether knowledge retention is desired for the work function, and whether management oversight is desired for the work function. | 8. A method, comprising: receiving, by a location decisioning system at a first computing device, a process criteria for a work function associated with an organization; receiving, by the location decisioning system, a provider attribute including a desired quality of a provider performing the work function; receiving, by the location decisioning system, a plurality of additional factors associated with the work function, the plurality of additional factors including whether information associated with the work function is non-public or privileged, whether intellectual property is involved with the work function, whether knowledge retention is desired for the work function, and whether management oversight is desired for the work function; determining, by the location decisioning system, whether the work function is eligible to be performed by an internal work group of the organization and a supplier external to the organization; and responsive to determining that the work function is eligible to be performed by an internal work group of the organization and a supplier external to the organization, determining, by the location decisioning system, a recommended location in which to perform the work function associated with the organization based on the received process criteria for the work function, the received provider attribute, including the desired quality of the provider performing the work function, the received plurality of additional factors associated with the work function, and the determination that the work function is eligible to be performed by an internal work group of the organization and a supplier external to the organization, wherein the recommended location in which to perform the work function associated with the organization is determined based at least in part on the plurality of additional factors, including whether information associated with the work function is non-public or privileged, whether intellectual property is involved with the work function, whether knowledge retention is desired for the work function, and whether management oversight is desired for the work function. 11. The method of claim 8 , wherein determining the recommended location includes determining a plurality of recommended locations. | 0.872568 |
9,009,220 | 1 | 20 | 1. An apparatus comprising: a data storage system associated with a provider entity and storing data on behalf of a client entity, the data being accessible from the data storage system by the client entity; a data interface enabling access by the provider entity to the data of the data storage system; and an analysis engine comprising a processor and memory maintained by the provider entity to, at discrete intervals determined by the analysis engine: access the data using the data interface, identify, among the data, electronic communications at least some of which each include data identifying a sender or a receiver, the sender or receiver being an individual associated with the client entity, analyze the data, including: identifying one or more words or phrases that occur in one or more of the electronic communications and meet a threshold frequency of occurrence, and comparing the identified words or phrases to one or more words or phrases occurring in electronic communications analyzed by the analysis engine at multiple previous discrete intervals, and at times determined based on the results of the analysis and the user's preferences for receiving information, generate results of the analysis to the client entity, the results indicating a characteristic of at least one of the individuals associated with the client entity, the characteristic being related to at least one of the identified words or phrases. | 1. An apparatus comprising: a data storage system associated with a provider entity and storing data on behalf of a client entity, the data being accessible from the data storage system by the client entity; a data interface enabling access by the provider entity to the data of the data storage system; and an analysis engine comprising a processor and memory maintained by the provider entity to, at discrete intervals determined by the analysis engine: access the data using the data interface, identify, among the data, electronic communications at least some of which each include data identifying a sender or a receiver, the sender or receiver being an individual associated with the client entity, analyze the data, including: identifying one or more words or phrases that occur in one or more of the electronic communications and meet a threshold frequency of occurrence, and comparing the identified words or phrases to one or more words or phrases occurring in electronic communications analyzed by the analysis engine at multiple previous discrete intervals, and at times determined based on the results of the analysis and the user's preferences for receiving information, generate results of the analysis to the client entity, the results indicating a characteristic of at least one of the individuals associated with the client entity, the characteristic being related to at least one of the identified words or phrases. 20. The apparatus of claim 1 , comprising: a software interface maintained by a provider entity and providing access to the provider entity to data stored by a data storage system on behalf of a client entity, wherein the extent of the access is tailored to applications that access and analyze the data at times determined by the provider entity. | 0.525956 |
8,390,839 | 3 | 5 | 3. The image formation system according to claim 2 , wherein said apparatus selection unit selects said image formation apparatus to process the selected document by dragging the document icon corresponding to said selected document onto an apparatus icon corresponding to said selected image formation apparatus by said input unit, said notification unit provides said second notification to the user, when the document icon corresponding to said selected document is dragged on the apparatus icon corresponding to said image formation apparatus by said input unit, the performance information of said image formation apparatus corresponding to said dragged apparatus icon for the type of the selected document. | 3. The image formation system according to claim 2 , wherein said apparatus selection unit selects said image formation apparatus to process the selected document by dragging the document icon corresponding to said selected document onto an apparatus icon corresponding to said selected image formation apparatus by said input unit, said notification unit provides said second notification to the user, when the document icon corresponding to said selected document is dragged on the apparatus icon corresponding to said image formation apparatus by said input unit, the performance information of said image formation apparatus corresponding to said dragged apparatus icon for the type of the selected document. 5. The image formation system according to claim 3 , wherein said notification unit provides said second notification by sound corresponding to the performance information of said image formation apparatus corresponding to said dragged apparatus icon for the type of selected document. | 0.561538 |
8,121,962 | 6 | 7 | 6. The computer-implemented method of claim 1 , further comprising: for each transaction, generating at least one score related to the transaction based on one or more mathematical models; and combining the at least one score with information from historical profiles for the entities involved in the transaction to produce a more accurate score. | 6. The computer-implemented method of claim 1 , further comprising: for each transaction, generating at least one score related to the transaction based on one or more mathematical models; and combining the at least one score with information from historical profiles for the entities involved in the transaction to produce a more accurate score. 7. The computer-implemented method of claim 6 , wherein the historical profiles are used only if the at least one score is within a predetermined range of values that indicate a high probability of the targeted outcome. | 0.5 |
7,630,974 | 47 | 51 | 47. A method of managing attributes in an identity profile, the method comprising: maintaining, at a data store, an access management system configured to receive a request to view and modify at least one of a plurality of identity profiles, wherein the request is associated with a preferred language; determining, at the access management system, whether the preferred language of the request matches an installed language at the access management system; in response to the preferred language not matching the installed language, performing an approximate language match based at least in part on a language code associated with the preferred language; maintaining, at the data store for the access management system, a plurality of multi-valued attributes in an individual data entry, wherein the individual data entry comprises a single data structure that includes the plurality of multi-valued attributes, wherein each multi-valued attribute includes a plurality of language components and value components, each of said value components specifies a value for said attribute that is associated with a corresponding language component, wherein said entry contains all available language components and value components for said multi-valued attribute; receiving a request associated with a first multi-valued attribute at a server, said request is associated with the preferred language; retrieving from the single data structure said first multi-valued attribute; and generating an output in response to said request, said output includes at least one first value for said first attribute that corresponds to said preferred language. | 47. A method of managing attributes in an identity profile, the method comprising: maintaining, at a data store, an access management system configured to receive a request to view and modify at least one of a plurality of identity profiles, wherein the request is associated with a preferred language; determining, at the access management system, whether the preferred language of the request matches an installed language at the access management system; in response to the preferred language not matching the installed language, performing an approximate language match based at least in part on a language code associated with the preferred language; maintaining, at the data store for the access management system, a plurality of multi-valued attributes in an individual data entry, wherein the individual data entry comprises a single data structure that includes the plurality of multi-valued attributes, wherein each multi-valued attribute includes a plurality of language components and value components, each of said value components specifies a value for said attribute that is associated with a corresponding language component, wherein said entry contains all available language components and value components for said multi-valued attribute; receiving a request associated with a first multi-valued attribute at a server, said request is associated with the preferred language; retrieving from the single data structure said first multi-valued attribute; and generating an output in response to said request, said output includes at least one first value for said first attribute that corresponds to said preferred language. 51. The method of claim 47 , wherein the access management system comprises an Access System that provides access management services for a network. | 0.513158 |
8,051,065 | 1 | 2 | 1. A method for generating search results comprising web documents with associated expert information, the method comprising: receiving one or more search queries; selecting one of the one or more search queries; determining one or more categories of web documents responsive to the selected search query; crawling a web graph of linked web documents to identify one or more web documents tagged as within the one or more categories responsive to the selected search query; generating a result set of the one or more web documents identified as within the one or more categories responsive to the selected search query; ranking the result set of the one or more web documents identified as within the one or more categories responsive to the selected search query based upon the quality of the secondary characteristics of the one or more documents of the result set, the secondary characteristics of the one or more documents of the result set comprising the level of experts linked to the one or more documents of the result set; and generating a list of ranked search results responsive to the selected search query. | 1. A method for generating search results comprising web documents with associated expert information, the method comprising: receiving one or more search queries; selecting one of the one or more search queries; determining one or more categories of web documents responsive to the selected search query; crawling a web graph of linked web documents to identify one or more web documents tagged as within the one or more categories responsive to the selected search query; generating a result set of the one or more web documents identified as within the one or more categories responsive to the selected search query; ranking the result set of the one or more web documents identified as within the one or more categories responsive to the selected search query based upon the quality of the secondary characteristics of the one or more documents of the result set, the secondary characteristics of the one or more documents of the result set comprising the level of experts linked to the one or more documents of the result set; and generating a list of ranked search results responsive to the selected search query. 2. The method of claim 1 wherein ranking the result set of the one or more web documents identified as within the one or more categories responsive to the selected search query comprises ranking the result set based upon the number of web documents linked to the one or more documents of the result set. | 0.5 |
9,633,173 | 1 | 8 | 1. A method implemented on a processor, the method comprising: receiving, on a computer host, an electronic document representing a pharmaceutical prescription; identifying constituent regions that include at least a first portion and a second portion within the electronic document; identifying first spatial frequencies for the first portion within the electronic document; identifying second spatial frequencies for the second portion within the electronic document; identifying a header based upon the first spatial frequencies, wherein identifying the first and second spatial frequencies includes performing a fast Fourier Transform on a portion of a document and translating spatial information into frequency information such that (i) the header identifying the prescriber is identified from the first spatial frequencies; and (ii) the second spatial frequencies are analyzed using the profile of the identified prescriber; using the header to identify a prescriber; retrieving a profile specific for the prescriber; analyzing the second spatial frequencies using the profile specific for the prescriber such that the second spatial frequencies are compared to spatial frequency domain information from the profile specific for the prescriber, the prescriber-specific profile constructed from the prescriber's past records and including isolated handwriting of the prescriber in a spatial frequency domain; and creating, based upon results from analyzing the second spatial frequencies using the profile for the prescriber, a transaction record on the computer host for a medical transaction associated with the pharmaceutical prescription. | 1. A method implemented on a processor, the method comprising: receiving, on a computer host, an electronic document representing a pharmaceutical prescription; identifying constituent regions that include at least a first portion and a second portion within the electronic document; identifying first spatial frequencies for the first portion within the electronic document; identifying second spatial frequencies for the second portion within the electronic document; identifying a header based upon the first spatial frequencies, wherein identifying the first and second spatial frequencies includes performing a fast Fourier Transform on a portion of a document and translating spatial information into frequency information such that (i) the header identifying the prescriber is identified from the first spatial frequencies; and (ii) the second spatial frequencies are analyzed using the profile of the identified prescriber; using the header to identify a prescriber; retrieving a profile specific for the prescriber; analyzing the second spatial frequencies using the profile specific for the prescriber such that the second spatial frequencies are compared to spatial frequency domain information from the profile specific for the prescriber, the prescriber-specific profile constructed from the prescriber's past records and including isolated handwriting of the prescriber in a spatial frequency domain; and creating, based upon results from analyzing the second spatial frequencies using the profile for the prescriber, a transaction record on the computer host for a medical transaction associated with the pharmaceutical prescription. 8. The method of claim 1 , wherein retrieving the profile for the prescriber includes retrieving a computer data structure that describes different spatial frequency representations for a term appearing in a dictionary. | 0.674107 |
9,069,861 | 2 | 4 | 2. A query generation system comprising: an element rank and inference engine in communication with a computing system and a user interface, the element rank and inference engine operable to: receive a plurality of terms from the user interface; derive, using latent semantic analysis, one or more inferred terms from the plurality of received terms, the one or more inferred terms comprising terms not in the plurality of received terms; modify the plurality of terms according to a specified criteria; display the modified plurality of terms and the one or more inferred terms on the user interface, the plurality of terms and the one or more inferred terms having a visual characteristic that varies according to their specified criteria; generate a query in accordance with the modified plurality of terms and the one or more inferred terms; and transmit the query to a web search engine. | 2. A query generation system comprising: an element rank and inference engine in communication with a computing system and a user interface, the element rank and inference engine operable to: receive a plurality of terms from the user interface; derive, using latent semantic analysis, one or more inferred terms from the plurality of received terms, the one or more inferred terms comprising terms not in the plurality of received terms; modify the plurality of terms according to a specified criteria; display the modified plurality of terms and the one or more inferred terms on the user interface, the plurality of terms and the one or more inferred terms having a visual characteristic that varies according to their specified criteria; generate a query in accordance with the modified plurality of terms and the one or more inferred terms; and transmit the query to a web search engine. 4. The query generation system of claim 2 , wherein modifying the plurality of terms further comprises filtering one or more of the plurality of terms and displaying the remaining plurality of terms according to the specified criteria. | 0.603041 |
8,832,080 | 17 | 18 | 17. The non-transitory computer-readable storage medium of claim 14 , further comprising instructions executable to generate an event-people graph based on the dynamic relation tree, and display the event-people graph to a user. | 17. The non-transitory computer-readable storage medium of claim 14 , further comprising instructions executable to generate an event-people graph based on the dynamic relation tree, and display the event-people graph to a user. 18. The non-transitory computer-readable storage medium of claim 17 , wherein the instructions executable to generate the event-people graph comprises instructions executable to cluster images at fixed times to identify people who appear together in certain events, and estimate the nature and closeness of the relation circles based on the characteristics of the events. | 0.5 |
8,620,918 | 19 | 24 | 19. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a plurality of electronic documents associated with a domain at a server, wherein each of the plurality of electronic documents includes meta-data and textual content; for each electronic document in at least a subset of the plurality of electronic documents: identifying one or more text strings in the textual content that are to be processed differently than an identical or similar text string in other electronic documents based on the meta-data associated with the electronic document; and associating, with the electronic document, data indicating that each of the identified text strings is to be processed differently than an identical or similar text string in other electronic documents; and performing an analysis of the electronic documents to identify one or more subsets of the electronic documents that include related subject matter, wherein a first degree of relatedness of subject matter is associated with identical or similar text strings that do not have associated data indicating that each of the identical or similar text strings is to be processed differently; and wherein a second degree of relatedness of subject matter, different than the first degree of relatedness, is associated with identical or similar text strings, in which one of the text strings has associated data indicating that the text string is to be processed differently and the other text string does not have data indicating that the text string is to be processed differently. | 19. A non-transitory computer storage medium encoded with a computer program, the program comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: receiving a plurality of electronic documents associated with a domain at a server, wherein each of the plurality of electronic documents includes meta-data and textual content; for each electronic document in at least a subset of the plurality of electronic documents: identifying one or more text strings in the textual content that are to be processed differently than an identical or similar text string in other electronic documents based on the meta-data associated with the electronic document; and associating, with the electronic document, data indicating that each of the identified text strings is to be processed differently than an identical or similar text string in other electronic documents; and performing an analysis of the electronic documents to identify one or more subsets of the electronic documents that include related subject matter, wherein a first degree of relatedness of subject matter is associated with identical or similar text strings that do not have associated data indicating that each of the identical or similar text strings is to be processed differently; and wherein a second degree of relatedness of subject matter, different than the first degree of relatedness, is associated with identical or similar text strings, in which one of the text strings has associated data indicating that the text string is to be processed differently and the other text string does not have data indicating that the text string is to be processed differently. 24. The computer storage medium of claim 19 , wherein the analysis includes using a particular text string as a potential feature for use in clustering documents if the particular text string has not been identified to be processed differently. | 0.513944 |
8,145,618 | 1 | 5 | 1. A system for scoring documents, comprising: one or more computers; and a storage medium coupled to the one or more computers and having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a search criteria; identifying one or more documents responsive to a search criteria; determining a text match score for each document based on degree of match between the responsive document and the search criteria; determining a document-categories score for each of a plurality of categories based on a degree of match between each document and each of the categories; determining a search criteria-categories score for each of the one or more categories based on a degree of match between the search criteria and each of the one or more categories, wherein the search criteria-categories score for a particular category indicates the degree of match between the search criteria and the category; determining a category match score for each document by combining the document-categories score of each of the one or more categories and the respective search criteria-categories score; determining an overall score for each document based on the text match score of each document and the respective category match score; and determining, based on the overall score for each document, a ranked order for the one or more documents. | 1. A system for scoring documents, comprising: one or more computers; and a storage medium coupled to the one or more computers and having instructions stored thereon which, when executed by the one or more computers, cause the one or more computers to perform operations comprising: receiving a search criteria; identifying one or more documents responsive to a search criteria; determining a text match score for each document based on degree of match between the responsive document and the search criteria; determining a document-categories score for each of a plurality of categories based on a degree of match between each document and each of the categories; determining a search criteria-categories score for each of the one or more categories based on a degree of match between the search criteria and each of the one or more categories, wherein the search criteria-categories score for a particular category indicates the degree of match between the search criteria and the category; determining a category match score for each document by combining the document-categories score of each of the one or more categories and the respective search criteria-categories score; determining an overall score for each document based on the text match score of each document and the respective category match score; and determining, based on the overall score for each document, a ranked order for the one or more documents. 5. The system of claim 1 , wherein the operations further comprise: mapping one or more of the documents to one or more of the plurality of categories; and associating one or more association strengths to matches between each document and the one or more categories. | 0.626404 |
9,517,418 | 1 | 2 | 1. A method for conversation management in a virtual world data processing system, the method comprising: recording a sequence of statements from different avatars in a virtual world; locating a position of each of the avatars in the virtual world; computing a temporal proximity of each of the recorded statements to others of the recorded statements; grouping selected ones of the recorded statements in the virtual world if corresponding ones of the avatars are geographically proximate to one another in the virtual world and if the selected ones of the statements have occurred within a threshold temporal proximity of one another; and, persisting the grouped statements in the virtual world as a conversation. | 1. A method for conversation management in a virtual world data processing system, the method comprising: recording a sequence of statements from different avatars in a virtual world; locating a position of each of the avatars in the virtual world; computing a temporal proximity of each of the recorded statements to others of the recorded statements; grouping selected ones of the recorded statements in the virtual world if corresponding ones of the avatars are geographically proximate to one another in the virtual world and if the selected ones of the statements have occurred within a threshold temporal proximity of one another; and, persisting the grouped statements in the virtual world as a conversation. 2. The method of claim 1 , wherein grouping the statements in the virtual world if the avatars are geographically proximate to one another in the virtual world and if the statements have occurred within a threshold temporal proximity of one another, comprises, grouping the statements in the virtual world if the avatars are geographically proximate to one another in the virtual world and if the statements have occurred within a threshold temporal proximity of one another and if a most recent one of the statements had been posted within a threshold period of elapsed time. | 0.5 |
8,416,926 | 9 | 10 | 9. The method of claim 1 , further comprising: requesting a party associated with the endpoint to provide a caller-identifying audio representation of the party's name; and providing the caller-identifying audio representation of the party's name to the particular user before connecting the endpoint and the particular user in a real-time communication session. | 9. The method of claim 1 , further comprising: requesting a party associated with the endpoint to provide a caller-identifying audio representation of the party's name; and providing the caller-identifying audio representation of the party's name to the particular user before connecting the endpoint and the particular user in a real-time communication session. 10. The method of claim 9 , further comprising storing the caller-identifying audio representation of the party's name. | 0.5 |
9,323,743 | 1 | 11 | 1. A method for generating a situational analysis text by transforming data that is expressed in a non-linguistic format into a format that can be expressed linguistically in a situational analysis text, the method comprising: assigning, at least one data channel on which an alert condition was identified, as a primary data channel; determining whether one or more data channels that are identified as related to the primary data channel are to be assigned as one or more related data channels, wherein the one or more related data channels are a subset of one or more monitored data channels; generating, using a natural language generation system that is configured to execute on a processor, a graph based at least on the data in the primary data channel, wherein at least a portion of data in the primary data channel comprises numerical data; and generating, using the natural language generation system that is configured to execute on the processor, the situational analysis text for display with the graph, the situational analysis text generated based at least on the data in the primary data channel, wherein the situational analysis text is configured to linguistically express contextual information related to the alert condition and the graph is configured to display numerical data in the primary data as a function of time, wherein at least a portion of the graph and at least a portion of the situational analysis text are generated in response to the identification of the alert condition. | 1. A method for generating a situational analysis text by transforming data that is expressed in a non-linguistic format into a format that can be expressed linguistically in a situational analysis text, the method comprising: assigning, at least one data channel on which an alert condition was identified, as a primary data channel; determining whether one or more data channels that are identified as related to the primary data channel are to be assigned as one or more related data channels, wherein the one or more related data channels are a subset of one or more monitored data channels; generating, using a natural language generation system that is configured to execute on a processor, a graph based at least on the data in the primary data channel, wherein at least a portion of data in the primary data channel comprises numerical data; and generating, using the natural language generation system that is configured to execute on the processor, the situational analysis text for display with the graph, the situational analysis text generated based at least on the data in the primary data channel, wherein the situational analysis text is configured to linguistically express contextual information related to the alert condition and the graph is configured to display numerical data in the primary data as a function of time, wherein at least a portion of the graph and at least a portion of the situational analysis text are generated in response to the identification of the alert condition. 11. The method according to claim 1 , wherein the graph further comprises one or more textual annotations. | 0.897881 |
9,230,356 | 27 | 28 | 27. The system of claim 26 , wherein the instructions further cause: animating the graphical element on the display of the first device. | 27. The system of claim 26 , wherein the instructions further cause: animating the graphical element on the display of the first device. 28. The system of claim 27 , wherein the instructions further cause: determining a style of animation to present based on a type of the second modification; and presenting the animation having the determined style. | 0.5 |
9,069,567 | 9 | 11 | 9. A computer program product, encoded on a non-transitory computer-readable medium, operable to cause one or more processors to perform operations for accessing a native application programming interface (API) of a computing device, the operations comprising: providing on the computing device, and from a first application written in a device-independent programming language, one or more control objects that include state information that defines a context for accessing the native API and include at least one control script; compiling the control script on the computing device into a second application that is native to the operating system of the computing device; executing the second application on the computing device, wherein the executed second application accesses the native API of the computing device to generate an output through a hardware interface of the computing device based on the context; and accessing the native API by the second application, based on information about the state information in the control objects from the first application that is provided as a result of user input received by the first application, to generate one or more additional outputs through the hardware interface of the computing device. | 9. A computer program product, encoded on a non-transitory computer-readable medium, operable to cause one or more processors to perform operations for accessing a native application programming interface (API) of a computing device, the operations comprising: providing on the computing device, and from a first application written in a device-independent programming language, one or more control objects that include state information that defines a context for accessing the native API and include at least one control script; compiling the control script on the computing device into a second application that is native to the operating system of the computing device; executing the second application on the computing device, wherein the executed second application accesses the native API of the computing device to generate an output through a hardware interface of the computing device based on the context; and accessing the native API by the second application, based on information about the state information in the control objects from the first application that is provided as a result of user input received by the first application, to generate one or more additional outputs through the hardware interface of the computing device. 11. The computer program product of claim 9 , wherein the second application is compiled as a process that is separate from the first application. | 0.819307 |
7,602,309 | 13 | 16 | 13. The electronic device of claim 11 , further comprising: a pointing device operable to define the at least one alphanumeric character and/or a symbol on the display. | 13. The electronic device of claim 11 , further comprising: a pointing device operable to define the at least one alphanumeric character and/or a symbol on the display. 16. The electronic device of claim 13 , wherein the processor is configured to determine the desired memory storage location responsive to the written user input comprising grouping the data and writing the at least one alphanumeric character and/or symbol in the grouping using the pointing device. | 0.54 |
7,721,203 | 16 | 17 | 16. A method of establishing a sequence validation context of a sequence of characters forming at least a portion of a complex character, the method comprising: determining, by a computer, whether a sequence checking feature operatively associated with a state transition table, containing allowable sequences of characters based on the rules of a selected language, is enabled, the sequence checking feature being set to operate by a registry entry setting set in a computer's registry, the registry entry setting being set in the computer's registry for each language requiring the sequence; upon determining that the sequence checking feature is enabled: determining, by the computer, whether the sequence of characters belongs to a set of characters comprising a selected language by beginning with a last character of the sequence of characters and determining whether the last character is valid as a complete sequence of characters comprising the complex character according to rules for forming the complex character, said determining whether the last character is valid as the complete sequence of characters comprises determining that the state transition table includes a state transition from the first state to the second state, the state transition from the first state to the second state indicating that a sequential order or reception of the first character relative to reception of the second character is consistent with at least one valid sequence of characters; when the last character of the sequence of characters is not valid as a complete sequence of characters comprising the complex character, determining, by the computer, whether a combination of the last character and a character input immediately to the left of the last character is valid as the complete sequence of characters comprising the complex character; when the combination is not valid as the complete sequence of characters comprising the complex character, then creating, by the computer, subsequent combinations of characters by adding one character at a time to the left of the last subsequent combination and determining whether each new combination after each added character is valid as the complete sequence of characters comprising the complex character until the at least one valid sequence of characters is found for forming the complex character according to the rules for forming the complex character; and when the at least one valid sequence of characters is found for forming the complex character according to the rules for forming the complex character, returning, on the computer, a context for the combination as the context for the complex character. | 16. A method of establishing a sequence validation context of a sequence of characters forming at least a portion of a complex character, the method comprising: determining, by a computer, whether a sequence checking feature operatively associated with a state transition table, containing allowable sequences of characters based on the rules of a selected language, is enabled, the sequence checking feature being set to operate by a registry entry setting set in a computer's registry, the registry entry setting being set in the computer's registry for each language requiring the sequence; upon determining that the sequence checking feature is enabled: determining, by the computer, whether the sequence of characters belongs to a set of characters comprising a selected language by beginning with a last character of the sequence of characters and determining whether the last character is valid as a complete sequence of characters comprising the complex character according to rules for forming the complex character, said determining whether the last character is valid as the complete sequence of characters comprises determining that the state transition table includes a state transition from the first state to the second state, the state transition from the first state to the second state indicating that a sequential order or reception of the first character relative to reception of the second character is consistent with at least one valid sequence of characters; when the last character of the sequence of characters is not valid as a complete sequence of characters comprising the complex character, determining, by the computer, whether a combination of the last character and a character input immediately to the left of the last character is valid as the complete sequence of characters comprising the complex character; when the combination is not valid as the complete sequence of characters comprising the complex character, then creating, by the computer, subsequent combinations of characters by adding one character at a time to the left of the last subsequent combination and determining whether each new combination after each added character is valid as the complete sequence of characters comprising the complex character until the at least one valid sequence of characters is found for forming the complex character according to the rules for forming the complex character; and when the at least one valid sequence of characters is found for forming the complex character according to the rules for forming the complex character, returning, on the computer, a context for the combination as the context for the complex character. 17. The method of claim 16 , the method further comprising: determining a maximum number of characters that comprise the at least one valid sequence of characters according to the rules for forming the complex character; and wherein adding one character at a time to the left of the last subsequent combination comprises: determining whether each new combination after each added character is valid as the complete sequence of characters comprising the complex character occurs until the maximum number of characters that comprises the at least one valid sequence have been combined; and determining whether each new combination after each added character is valid as the complete sequence of characters comprising the complex character occurs until the at least one valid sequence of characters is found for forming the complex character according to the rules for forming the complex character. | 0.5 |
9,619,024 | 13 | 18 | 13. A virtual inputting method, comprising: collecting bioelectrical signals and acceleration signals reflecting a user's gesture; performing preprocessing for the collected bioelectrical signals and the collected acceleration signals; performing segmentation processing for the preprocessed bioelectrical signals and the preprocessed acceleration signals so as to obtain a plurality of gesture segments; extracting feature values from the bioelectrical signals and the acceleration signals for respective gesture segments; combining the extracted feature values to form a combined feature vector; performing gesture recognition based on the combined feature vector; and obtaining characters corresponding to the recognized gesture according to a predetermined mapping relationship between characters and gestures, wherein the segmentation processing comprises: determining starting points and ending points for the preprocessed bioelectrical signals and the preprocessed acceleration signals respectively; and averaging the starting points so as to obtain a starting point of a gesture segment, and averaging the ending points so as to obtain an ending point of the gesture segment. | 13. A virtual inputting method, comprising: collecting bioelectrical signals and acceleration signals reflecting a user's gesture; performing preprocessing for the collected bioelectrical signals and the collected acceleration signals; performing segmentation processing for the preprocessed bioelectrical signals and the preprocessed acceleration signals so as to obtain a plurality of gesture segments; extracting feature values from the bioelectrical signals and the acceleration signals for respective gesture segments; combining the extracted feature values to form a combined feature vector; performing gesture recognition based on the combined feature vector; and obtaining characters corresponding to the recognized gesture according to a predetermined mapping relationship between characters and gestures, wherein the segmentation processing comprises: determining starting points and ending points for the preprocessed bioelectrical signals and the preprocessed acceleration signals respectively; and averaging the starting points so as to obtain a starting point of a gesture segment, and averaging the ending points so as to obtain an ending point of the gesture segment. 18. The method of claim 13 , wherein the mapping relationship between characters and recognized gesture result is a mapping relationship between characters and different parts of four fingers except thumb. | 0.5 |
9,324,324 | 1 | 3 | 1. A computer system, comprising: one or more hardware processors; and one or more non-transitory computer-readable media having stored thereon computer-executable instructions that are structured such that, when the computer-executable instructions are executed by the one or more hardware processors, the computer system generates text captions from speech data, including at least the following: receiving, from a first communications device, the speech data based on a remote party's voice: generating, at the one or more hardware processors, first text captions from the speech data using a speech recognition algorithm; determining, at the one or more hardware processors, whether the generated first text captions meet a first predetermined quality threshold; and when the first text captions meet the first predetermined quality threshold, sending the first text captions to a second communications device for display at a display device; or when the first text captions do not meet the first predetermined quality threshold, performing at least the following: generating, at the one or more hardware processors, second text captions from the speech data based on user input to the speech recognition algorithm from a human user; and sending the second text captions to the second communications device for display at the display device when the second text captions meet a second predetermined quality threshold. | 1. A computer system, comprising: one or more hardware processors; and one or more non-transitory computer-readable media having stored thereon computer-executable instructions that are structured such that, when the computer-executable instructions are executed by the one or more hardware processors, the computer system generates text captions from speech data, including at least the following: receiving, from a first communications device, the speech data based on a remote party's voice: generating, at the one or more hardware processors, first text captions from the speech data using a speech recognition algorithm; determining, at the one or more hardware processors, whether the generated first text captions meet a first predetermined quality threshold; and when the first text captions meet the first predetermined quality threshold, sending the first text captions to a second communications device for display at a display device; or when the first text captions do not meet the first predetermined quality threshold, performing at least the following: generating, at the one or more hardware processors, second text captions from the speech data based on user input to the speech recognition algorithm from a human user; and sending the second text captions to the second communications device for display at the display device when the second text captions meet a second predetermined quality threshold. 3. The computer system as recited in claim 1 , wherein the speech data based on the remote party's voice comprises intermediary speech data elements that were generated at the remote communications device based on a high-fidelity audio recording of the remote party's voice. | 0.740038 |
7,555,477 | 22 | 23 | 22. A computer program product for generating conceptual search results including targeted advertisement, comprising: a memory storing computer-executable code; and a processor in communication with the memory and operable to execute the computer-executable code to cause performance of: determining a first concept in response to a query term, determining a second concept in response to the query term, wherein the first concept and the second concept are not related to each other, determining a first advertisement relating to the first concept, determining a second advertisement relating to the second concept, wherein the first advertisement and the second advertisement are not related to each other, determining a first content type in which to represent the first concept, and determining a second content type in which to represent the second concept. | 22. A computer program product for generating conceptual search results including targeted advertisement, comprising: a memory storing computer-executable code; and a processor in communication with the memory and operable to execute the computer-executable code to cause performance of: determining a first concept in response to a query term, determining a second concept in response to the query term, wherein the first concept and the second concept are not related to each other, determining a first advertisement relating to the first concept, determining a second advertisement relating to the second concept, wherein the first advertisement and the second advertisement are not related to each other, determining a first content type in which to represent the first concept, and determining a second content type in which to represent the second concept. 23. The computer program product of claim 22 , wherein the first advertisement includes a link to a web site. | 0.700549 |
8,200,713 | 8 | 11 | 8. A computing device, comprising at least one processor, configured to implement an application development tool for facilitating development of an application having access to a database data-source, the database data-source comprising schema metadata, the application development tool providing the computing device with: means for identifying at least one subroutine including hidden information, the hidden information comprising a metadata structure unpublished in the data-source database; means for generating a definition document for the subroutine using information available from its available schema metadata; means for executing the subroutine via the database data-source; means for analysing a result set metadata of the executed subroutine to reveal the metadata structure of the hidden information; and means for enhancing the definition document with the revealed metadata structure of the hidden information, the enhanced definition document for use in developing the application. | 8. A computing device, comprising at least one processor, configured to implement an application development tool for facilitating development of an application having access to a database data-source, the database data-source comprising schema metadata, the application development tool providing the computing device with: means for identifying at least one subroutine including hidden information, the hidden information comprising a metadata structure unpublished in the data-source database; means for generating a definition document for the subroutine using information available from its available schema metadata; means for executing the subroutine via the database data-source; means for analysing a result set metadata of the executed subroutine to reveal the metadata structure of the hidden information; and means for enhancing the definition document with the revealed metadata structure of the hidden information, the enhanced definition document for use in developing the application. 11. The application development tool of claim 8 , wherein a plurality of subroutines are identified as candidates and the candidates are displayed to the user in a tree-view. | 0.5 |
9,058,174 | 22 | 23 | 22. The system of claim 21 , wherein the widget publication object further includes: (iii) a widget consumption object specifying resources consumed by the respective web widget; (iv) a widget production object specifying resources produced by the respective web widget. | 22. The system of claim 21 , wherein the widget publication object further includes: (iii) a widget consumption object specifying resources consumed by the respective web widget; (iv) a widget production object specifying resources produced by the respective web widget. 23. The system of claim 22 , wherein the widget publication object further includes: (v) one or more semantic tags pertaining to the respective web widget; (vi) the indication, wherein the indication comprises a cycle flag specifying whether cycles have been resolved for the respective web widget, wherein each cycle is a directed cycle. | 0.5 |
9,934,785 | 10 | 19 | 10. A system for processing audio signals, comprising: at least one processor configured to: retrieve at least one content object generated by an audio signal processing system, the at least one content object including (1) one or more text objects corresponding to one or more words and (2) one or more text object data elements representing (i) a type representing the one or more text objects as at least one of a sentence, a verb, a noun phrase a determiner, and an adjective (ii) an emphasis level value representing a level of emphasis of the one or more words, correspondingly and (iii) an electronically generated confidence level value representing a confidence level that the audio signal processing system has properly identified the one or more words from an audio signal; retrieve content metadata, generated by the audio signal processing system, the content metadata corresponding to the one or more words and including (i) one or more content metadata objects and (ii) a content metadata object confidence level value representing the confidence level that the audio signal processing system has properly identified the one or more content metadata objects, wherein the one or more content metadata objects include at least one of an emotion object, a gender object, an age object and an accent object; retrieve environmental metadata, generated by the audio signal processing system, the environmental metadata corresponding to the background noise and including (i) one or more environmental metadata objects and (ii) an environmental metadata object confidence level value representing the audio signal processing system has properly identified the one or more environmental metadata objects from the audio signal; retrieve, from a profile database, a user profile containing historical listening practices of a user; determine, based on the user profile, the at least one content object, the content metadata and the environmental metadata, at least one of (i) media content and (ii) a recommended next media track; and cause at least one of the media content and the recommended next media track to be output on an electronic device, wherein the outputting comprises playing the media content or displaying the recommended next media track, correspondingly, wherein when the recommended next media track is selected, media content corresponding to the recommended next media track is played. | 10. A system for processing audio signals, comprising: at least one processor configured to: retrieve at least one content object generated by an audio signal processing system, the at least one content object including (1) one or more text objects corresponding to one or more words and (2) one or more text object data elements representing (i) a type representing the one or more text objects as at least one of a sentence, a verb, a noun phrase a determiner, and an adjective (ii) an emphasis level value representing a level of emphasis of the one or more words, correspondingly and (iii) an electronically generated confidence level value representing a confidence level that the audio signal processing system has properly identified the one or more words from an audio signal; retrieve content metadata, generated by the audio signal processing system, the content metadata corresponding to the one or more words and including (i) one or more content metadata objects and (ii) a content metadata object confidence level value representing the confidence level that the audio signal processing system has properly identified the one or more content metadata objects, wherein the one or more content metadata objects include at least one of an emotion object, a gender object, an age object and an accent object; retrieve environmental metadata, generated by the audio signal processing system, the environmental metadata corresponding to the background noise and including (i) one or more environmental metadata objects and (ii) an environmental metadata object confidence level value representing the audio signal processing system has properly identified the one or more environmental metadata objects from the audio signal; retrieve, from a profile database, a user profile containing historical listening practices of a user; determine, based on the user profile, the at least one content object, the content metadata and the environmental metadata, at least one of (i) media content and (ii) a recommended next media track; and cause at least one of the media content and the recommended next media track to be output on an electronic device, wherein the outputting comprises playing the media content or displaying the recommended next media track, correspondingly, wherein when the recommended next media track is selected, media content corresponding to the recommended next media track is played. 19. The system according to claim 10 , wherein the at least one processor is further configured to: retrieve, from the profile database, at least one other user profile containing historical listening practices of at least one other user, and the determining is based also on the historical listening practice of the at least one other user. | 0.684259 |
8,200,704 | 10 | 15 | 10. A system, comprising: one or more computers programmed to perform operations comprising: identifying, in a computer, a plurality of structured documents having a same structured data format; parsing each structured document in the plurality of structured documents and extracting a plurality of data sets from each structured document; obtaining distinct metadata from a plurality of sources for each structured document in the plurality of structured documents, wherein the distinct metadata for each structured document comprises a rank of the structured document, a popularity of the structured document, or a number of downloads of the structured document, and wherein one or more sources in the plurality of sources comprises a different source than the structured document itself; merging the distinct metadata from the plurality of sources, including removing duplicate metadata; associating the distinct metadata for each respective structured document with each data set extracted from the respective structured document; adding a plurality of record items to a searchable database, wherein each record item corresponds to one of the extracted data sets, and wherein each record item is associated with the distinct metadata associated with the corresponding data set; receiving a search query; using the distinct metadata associated with each of one or more of the record items to calculate a query-independent score for at least one record item in the searchable database and using the query-independent score to identify the at least one record item as a response to the search query; and returning the identified at least one record item in response to the search query. | 10. A system, comprising: one or more computers programmed to perform operations comprising: identifying, in a computer, a plurality of structured documents having a same structured data format; parsing each structured document in the plurality of structured documents and extracting a plurality of data sets from each structured document; obtaining distinct metadata from a plurality of sources for each structured document in the plurality of structured documents, wherein the distinct metadata for each structured document comprises a rank of the structured document, a popularity of the structured document, or a number of downloads of the structured document, and wherein one or more sources in the plurality of sources comprises a different source than the structured document itself; merging the distinct metadata from the plurality of sources, including removing duplicate metadata; associating the distinct metadata for each respective structured document with each data set extracted from the respective structured document; adding a plurality of record items to a searchable database, wherein each record item corresponds to one of the extracted data sets, and wherein each record item is associated with the distinct metadata associated with the corresponding data set; receiving a search query; using the distinct metadata associated with each of one or more of the record items to calculate a query-independent score for at least one record item in the searchable database and using the query-independent score to identify the at least one record item as a response to the search query; and returning the identified at least one record item in response to the search query. 15. The system of claim 10 , wherein the distinct metadata for each structured document comprises a popularity of the structured document. | 0.848018 |
8,903,801 | 1 | 13 | 1. A computer-implemented method comprising steps of: from a workload set, identifying a plurality of database query language statements for automatic tuning, wherein the workload set comprises database query language statements and current performance data for the database query language statements; executing each database query language statement from said plurality of query language statements against a database; collecting new performance data from said executing each database query language statement, said collecting comprising measuring resource usage by said executing each database query language statement; detecting that conditions in said database that affect executing said plurality of database query language statements changed based at least in part on comparison of the new performance data with the current performance data; in response to the detecting, tuning a subset of database query language statements from said plurality of database query language statements, said subset of database query language statements comprising a database query language statement from said plurality of database query language statements, wherein the new performance data is different from the current performance data for the database query language statement; wherein the tuning the subset of database query language statements comprises generating a plurality of tuning recommendations for execution of the subset of database query language statements; testing the plurality of tuning recommendations against said database, wherein the testing the plurality of tuning recommendations comprises, for each tuning recommendation of said plurality of tuning recommendations: executing a respective database query language statement from said subset of database query language statements with said each tuning recommendation enabled; measuring resource usage by said executing the respective database query language statement with said each tuning recommendation enabled, wherein the resource usage comprises processor time or buffer gets; and measuring benefits based on performance improvement of said executing the respective database query language statement with said each tuning recommendation enabled; based on the testing, determining a subset of said plurality of tuning recommendations resulted in performance improvement that meets a specific set of criteria; implementing the subset of said plurality of tuning recommendations; and wherein the steps are automatically performed by one or more computing devices. | 1. A computer-implemented method comprising steps of: from a workload set, identifying a plurality of database query language statements for automatic tuning, wherein the workload set comprises database query language statements and current performance data for the database query language statements; executing each database query language statement from said plurality of query language statements against a database; collecting new performance data from said executing each database query language statement, said collecting comprising measuring resource usage by said executing each database query language statement; detecting that conditions in said database that affect executing said plurality of database query language statements changed based at least in part on comparison of the new performance data with the current performance data; in response to the detecting, tuning a subset of database query language statements from said plurality of database query language statements, said subset of database query language statements comprising a database query language statement from said plurality of database query language statements, wherein the new performance data is different from the current performance data for the database query language statement; wherein the tuning the subset of database query language statements comprises generating a plurality of tuning recommendations for execution of the subset of database query language statements; testing the plurality of tuning recommendations against said database, wherein the testing the plurality of tuning recommendations comprises, for each tuning recommendation of said plurality of tuning recommendations: executing a respective database query language statement from said subset of database query language statements with said each tuning recommendation enabled; measuring resource usage by said executing the respective database query language statement with said each tuning recommendation enabled, wherein the resource usage comprises processor time or buffer gets; and measuring benefits based on performance improvement of said executing the respective database query language statement with said each tuning recommendation enabled; based on the testing, determining a subset of said plurality of tuning recommendations resulted in performance improvement that meets a specific set of criteria; implementing the subset of said plurality of tuning recommendations; and wherein the steps are automatically performed by one or more computing devices. 13. The computer-implemented method of claim 1 , wherein the resource usage comprises both processor time and buffer gets. | 0.892035 |
8,788,536 | 10 | 13 | 10. A system comprising: a processor; and a memory, wherein the memory stores program instructions executable by the processor to: obtain a copy of an electronic communication, wherein the electronic communication comprises a reference to a document, and contents of the document are not included in the copy of the electronic communication as an attachment, obtain a copy of the document, in response to the reference, wherein the document exists at a location identified by the reference, archive the copy of the electronic communication and the copy of the document in archive media, store relationship information to identify a relationship between the electronic communication and the document, and add information associated with the document to a set of archival metadata to indicate that the copy of the document has been archived, wherein the information associated with the document comprises location information which identifies the location of the copy of the electronic communication and the copy of the document in the archive media. | 10. A system comprising: a processor; and a memory, wherein the memory stores program instructions executable by the processor to: obtain a copy of an electronic communication, wherein the electronic communication comprises a reference to a document, and contents of the document are not included in the copy of the electronic communication as an attachment, obtain a copy of the document, in response to the reference, wherein the document exists at a location identified by the reference, archive the copy of the electronic communication and the copy of the document in archive media, store relationship information to identify a relationship between the electronic communication and the document, and add information associated with the document to a set of archival metadata to indicate that the copy of the document has been archived, wherein the information associated with the document comprises location information which identifies the location of the copy of the electronic communication and the copy of the document in the archive media. 13. The system of claim 10 , wherein the program instructions are further executable by the processor to: update a search index for the archive media based upon at least one of the contents or characteristics of the document. | 0.821994 |
10,043,516 | 26 | 28 | 26. The non-transitory computer readable storage medium of claim 24 , wherein providing the audio output comprises providing a speech output indicative of a list of items, and wherein the portion of the audio output is indicative of an item of the list of items. | 26. The non-transitory computer readable storage medium of claim 24 , wherein providing the audio output comprises providing a speech output indicative of a list of items, and wherein the portion of the audio output is indicative of an item of the list of items. 28. The non-transitory computer readable storage medium of claim 26 , wherein the item is a location, and wherein performing the task comprises providing, via the speaker, information associated with the location. | 0.5 |
8,219,511 | 13 | 18 | 13. One or more computer-readable media storing computer-executable instructions that, when executed on one or more processors, cause the one or more processors to perform acts comprising: selecting a set of elements having a sample selection bias from a group of elements for labeling by one or more human users, the selecting based at least in part on a sample selection bias of the set of elements; receiving a label for each element of the set of elements from the one or more human users; and training a model for predicting labels for each element of the group of elements, the training based at least in part on the labels for the set of elements received from the one or more human users. | 13. One or more computer-readable media storing computer-executable instructions that, when executed on one or more processors, cause the one or more processors to perform acts comprising: selecting a set of elements having a sample selection bias from a group of elements for labeling by one or more human users, the selecting based at least in part on a sample selection bias of the set of elements; receiving a label for each element of the set of elements from the one or more human users; and training a model for predicting labels for each element of the group of elements, the training based at least in part on the labels for the set of elements received from the one or more human users. 18. One or more computer-readable media as recited in claim 13 , wherein the selecting of the set of elements is also based at least in part on an uncertainty of each element of the set of elements. | 0.910163 |
8,429,156 | 1 | 4 | 1. A system comprising: a tag relevance manager embodied via executable instructions stored on a computer-readable storage medium, the tag relevance manager including: a tag collector that obtains a plurality of tags associated with a plurality of geographic locations, each tag indicating one or more attributes associated with an entity associated with one of the geographic locations; a geographic scope component that obtains a first geographic scope indicating a first hierarchical geographic analysis level associated with the plurality of geographic locations; a first frequency component that obtains a first relative frequency of occurrence of a first one of the tags based on a first bounded geographic area that includes a first one of the geographic locations that is associated with the first one of the tags; a second frequency component that obtains a second relative frequency of occurrence of the first one of the tags based on a second bounded geographic area that is larger than the first bounded geographic area, the second bounded geographic area surrounding the first one of the geographic locations that is associated with the first one of the tags, the first bounded geographic area including at least a first portion of the plurality of geographic locations, and the second bounded geographic area including at least a second portion of the plurality of geographic locations; and a tag ranking component that determines, via a device processor, a first locale ranking value associated with the first tag indicating a relevance of the first tag based on the first geographic scope, the first and second relative frequencies of occurrence, and a locale associated with the first bounded geographic area. | 1. A system comprising: a tag relevance manager embodied via executable instructions stored on a computer-readable storage medium, the tag relevance manager including: a tag collector that obtains a plurality of tags associated with a plurality of geographic locations, each tag indicating one or more attributes associated with an entity associated with one of the geographic locations; a geographic scope component that obtains a first geographic scope indicating a first hierarchical geographic analysis level associated with the plurality of geographic locations; a first frequency component that obtains a first relative frequency of occurrence of a first one of the tags based on a first bounded geographic area that includes a first one of the geographic locations that is associated with the first one of the tags; a second frequency component that obtains a second relative frequency of occurrence of the first one of the tags based on a second bounded geographic area that is larger than the first bounded geographic area, the second bounded geographic area surrounding the first one of the geographic locations that is associated with the first one of the tags, the first bounded geographic area including at least a first portion of the plurality of geographic locations, and the second bounded geographic area including at least a second portion of the plurality of geographic locations; and a tag ranking component that determines, via a device processor, a first locale ranking value associated with the first tag indicating a relevance of the first tag based on the first geographic scope, the first and second relative frequencies of occurrence, and a locale associated with the first bounded geographic area. 4. The system of claim 1 , further comprising: a rank storage component that initiates storage of the first locale ranking value with an indicator of the first tag in a database that includes a plurality of other locale ranking values and indicators of associated tags, stored based on relevance, based on the first geographic scope. | 0.754062 |
6,026,432 | 6 | 9 | 6. The method of claim 1, wherein all reference links provided by said target page will be identified except those references including said string of words so that all references including said string will be excluded. | 6. The method of claim 1, wherein all reference links provided by said target page will be identified except those references including said string of words so that all references including said string will be excluded. 9. The method of claim 6, further comprising the step of printing said search result. | 0.595238 |
8,682,677 | 8 | 11 | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: identifying features from a set of user interactions; identifying a policy for using the features in developing a dialog manager; performing, based on the policy, a linear evaluation on the features, to yield a set of features; repeating a cubic policy process on the set of features until the set of features results in a reduced set of features having a quantity below a threshold, the cubic policy process comprising a least-squares policy iteration algorithm; and generating the dialog manager using a modified set of user interactions, the modified set of user interactions being selected based on the reduced set of features. | 8. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: identifying features from a set of user interactions; identifying a policy for using the features in developing a dialog manager; performing, based on the policy, a linear evaluation on the features, to yield a set of features; repeating a cubic policy process on the set of features until the set of features results in a reduced set of features having a quantity below a threshold, the cubic policy process comprising a least-squares policy iteration algorithm; and generating the dialog manager using a modified set of user interactions, the modified set of user interactions being selected based on the reduced set of features. 11. The system of claim 8 , the computer-readable storage medium having additional instruction stored which result in the operations further comprising ignoring, during generation of the dialog manager, features which are not in the reduced set of features. | 0.5 |
8,825,669 | 7 | 10 | 7. A mobile application search method in a mobile application search system that receives a user query from a user and provides a mobile application search result related to the input user query, the method comprising: at the mobile application search system, receiving the user query from the user; and at the mobile application search system, searching for a mobile application related to the user query using an activity knowledge database in which a list of elements involved in achieving a plurality of goals that people desire in daily life is stored and providing the search result; at the mobile application search system, receiving the user query of a text form from the user; at the mobile application search system, converting the user query of the text form into a query language query; at the mobile application search system, calculating semantic relevance between two concepts using the activity knowledge database so as to calculate a search score between text data of the mobile application and the query language query; at the mobile application search system, calculating a translation probability between the concepts based on the semantic relevance between the concepts; at the mobile application search system, calculating a semantic-based search score between words included in text data of the mobile application on a knowledge-based search model generated using the translation probability between the concepts; at the mobile application search system, calculating a semantic-based search score of the mobile application using the semantic-based search score between the words; at the mobile application search system, calculating a final search score of the mobile application by combining the calculated semantic-based search score of the mobile application with a keyword-based search score; and at the mobile application search system, outputting a high rank search result which is a search result of the mobile application corresponding to a high rank according to a predetermined criterion among the search scores of the mobile application. | 7. A mobile application search method in a mobile application search system that receives a user query from a user and provides a mobile application search result related to the input user query, the method comprising: at the mobile application search system, receiving the user query from the user; and at the mobile application search system, searching for a mobile application related to the user query using an activity knowledge database in which a list of elements involved in achieving a plurality of goals that people desire in daily life is stored and providing the search result; at the mobile application search system, receiving the user query of a text form from the user; at the mobile application search system, converting the user query of the text form into a query language query; at the mobile application search system, calculating semantic relevance between two concepts using the activity knowledge database so as to calculate a search score between text data of the mobile application and the query language query; at the mobile application search system, calculating a translation probability between the concepts based on the semantic relevance between the concepts; at the mobile application search system, calculating a semantic-based search score between words included in text data of the mobile application on a knowledge-based search model generated using the translation probability between the concepts; at the mobile application search system, calculating a semantic-based search score of the mobile application using the semantic-based search score between the words; at the mobile application search system, calculating a final search score of the mobile application by combining the calculated semantic-based search score of the mobile application with a keyword-based search score; and at the mobile application search system, outputting a high rank search result which is a search result of the mobile application corresponding to a high rank according to a predetermined criterion among the search scores of the mobile application. 10. The mobile application search method of claim 7 , wherein the calculating of the final search score of the mobile application includes calculating the search score of the mobile application using the semantic-based search score between the words, a language model, and a weight given to the activity knowledge database. | 0.577225 |
9,761,278 | 17 | 18 | 17. The method of claim 11 , further comprising: receiving a selection of one of the post-capture users from the set of post-capture users to create the edited version of the digital media content. | 17. The method of claim 11 , further comprising: receiving a selection of one of the post-capture users from the set of post-capture users to create the edited version of the digital media content. 18. The method of claim 17 , further comprising: obtaining, via a second client computing platform associated with the selected post-capture user, a portion of the edited version of the digital media content, the portion of the edited version of the digital media content having an edited time duration; effectuate transmission of the portion of the edited version of the digital media content to the second client computing platform for presentation; and receiving, from the second client computing platform, a selection of one or more edited moments of interest within the portion of the edited version of the digital media content, individual edited moments of interest corresponding to individual points in time within the edited time duration of the portion of the edited version of the digital media content. | 0.5 |
9,858,524 | 1 | 2 | 1. A method performed by one or more computers, the method comprising: obtaining an input image; processing the input image using a deep convolutional neural network to generate an alternative representation for the input image, wherein: (i) the deep convolutional neural network includes a plurality of core neural network layers that are each defined by a respective set of parameters having current values that were determined by training a second neural network having the plurality of core neural network layers on a plurality of training images, and (ii) the second neural network was trained in part by processing, with an output layer of the second neural network and for each training image, an output of a last core neural network layer of the plurality of core neural network layers to generate, for each of a plurality of object categories, a respective score that represents a predicted likelihood that the training image contains an image of an object from the object category; and processing the alternative representation for the input image using a third neural network to generate a sequence of a plurality of words in a target natural language that describes the input image. | 1. A method performed by one or more computers, the method comprising: obtaining an input image; processing the input image using a deep convolutional neural network to generate an alternative representation for the input image, wherein: (i) the deep convolutional neural network includes a plurality of core neural network layers that are each defined by a respective set of parameters having current values that were determined by training a second neural network having the plurality of core neural network layers on a plurality of training images, and (ii) the second neural network was trained in part by processing, with an output layer of the second neural network and for each training image, an output of a last core neural network layer of the plurality of core neural network layers to generate, for each of a plurality of object categories, a respective score that represents a predicted likelihood that the training image contains an image of an object from the object category; and processing the alternative representation for the input image using a third neural network to generate a sequence of a plurality of words in a target natural language that describes the input image. 2. The method of claim 1 , wherein processing the input image using the deep convolutional neural network comprises processing the input image through each of the core neural network layers, and wherein the alternative representation for the input image is an output generated by a last core neural network layer of the plurality of core neural network layers of the deep convolutional neural network. | 0.5 |
9,678,948 | 1 | 7 | 1. A method for determining a sentiment of an electronic message, comprising: providing, using a processor of a computer, sentiment dictionaries and false-positive dictionaries with associated sentiment indicators, wherein a sentiment dictionary and a false-positive dictionary are provided for each type of sentiment, wherein the sentiment dictionary includes sub-constructs that are correctly classified as the associated sentiment indicator, and wherein the false-positive dictionary includes sub-constructs that are incorrectly classified as the associated sentiment indicator; parsing the electronic message to identify one or more sub-constructs; finding a first sub-construct of the one or more sub-constructs in a false-positive dictionary from the false-positive dictionaries that indicates that the first sub-construct is incorrectly classified as the associated sentiment indicator of the false-positive dictionary; for each of the one or more sub-constructs, other than the first sub-construct, that are not found in the false-positive dictionaries, finding that sub-construct in a sentiment dictionary from the sentiment dictionaries; assigning a score for the associated sentiment indicator; and applying a rule that includes the sub-construct and another sub-construct from the one or more sub-constructs to adjust the score; obtaining a final score for each type of sentiment indicator in the electronic message by summing scores for sub-constructs having been assigned the score for that type of sentiment indicator without counting the first sub-construct that has been found in the false-positive dictionary; and based on the final score for each type of sentiment indicator, identifying the sentiment of the electronic message. | 1. A method for determining a sentiment of an electronic message, comprising: providing, using a processor of a computer, sentiment dictionaries and false-positive dictionaries with associated sentiment indicators, wherein a sentiment dictionary and a false-positive dictionary are provided for each type of sentiment, wherein the sentiment dictionary includes sub-constructs that are correctly classified as the associated sentiment indicator, and wherein the false-positive dictionary includes sub-constructs that are incorrectly classified as the associated sentiment indicator; parsing the electronic message to identify one or more sub-constructs; finding a first sub-construct of the one or more sub-constructs in a false-positive dictionary from the false-positive dictionaries that indicates that the first sub-construct is incorrectly classified as the associated sentiment indicator of the false-positive dictionary; for each of the one or more sub-constructs, other than the first sub-construct, that are not found in the false-positive dictionaries, finding that sub-construct in a sentiment dictionary from the sentiment dictionaries; assigning a score for the associated sentiment indicator; and applying a rule that includes the sub-construct and another sub-construct from the one or more sub-constructs to adjust the score; obtaining a final score for each type of sentiment indicator in the electronic message by summing scores for sub-constructs having been assigned the score for that type of sentiment indicator without counting the first sub-construct that has been found in the false-positive dictionary; and based on the final score for each type of sentiment indicator, identifying the sentiment of the electronic message. 7. The method of claim 1 , further comprising: storing the sentiment dictionaries and the false-positive dictionaries. | 0.646707 |
7,478,192 | 29 | 33 | 29. An associative memory method according to claim 27 : wherein observing comprises: observing into the network of entity associative memory networks, the associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity, based on the plurality of input documents; observing into the network of document associative memory networks, the associations among observed entities in a respective observer input document; observing into the network of feedback associative memory networks, the associations among a plurality of observed entities for a respective observer positive and/or negative evaluation for a respective task of a respective user; and observing into the network of community associative memory networks, the associations among a respective observer entity, a plurality of observed entities that are observed by the respective observer entity and a plurality of observed tasks of a plurality of users in which the observer entity was queried; and wherein imagining comprises imagining associations of entities, documents, users and/or tasks from the network of entity associative memory networks, the network of document associative memory networks, the network of feedback associative memory networks and the network of community associative memory networks, in response to user queries. | 29. An associative memory method according to claim 27 : wherein observing comprises: observing into the network of entity associative memory networks, the associations among a respective observer entity and a plurality of observed entities that are observed by the respective observer entity, based on the plurality of input documents; observing into the network of document associative memory networks, the associations among observed entities in a respective observer input document; observing into the network of feedback associative memory networks, the associations among a plurality of observed entities for a respective observer positive and/or negative evaluation for a respective task of a respective user; and observing into the network of community associative memory networks, the associations among a respective observer entity, a plurality of observed entities that are observed by the respective observer entity and a plurality of observed tasks of a plurality of users in which the observer entity was queried; and wherein imagining comprises imagining associations of entities, documents, users and/or tasks from the network of entity associative memory networks, the network of document associative memory networks, the network of feedback associative memory networks and the network of community associative memory networks, in response to user queries. 33. An associative memory method according to claim 29 wherein imagining associations of entities, documents, users and/or tasks comprises: querying the network of entity associative memory networks and the network of feedback associative memory networks to imagine associations of entities and user-task positive and/or negative evaluations in response to user queries; querying the network of document associative memory networks and the network of feedback associative memory networks to imagine associations of documents and user-task positive and/or negative evaluations in response to user queries; and querying the network of community associative memory networks to imagine associations of other user-tasks in response to user queries. | 0.5 |
8,620,918 | 1 | 6 | 1. A computer-implemented method comprising: receiving a plurality of electronic documents associated with a domain at a server, wherein each of the plurality of electronic documents includes meta-data and textual content; for each electronic document in at least a subset of the plurality of electronic documents: identifying one or more text strings in the textual content that are to be processed differently than an identical or similar text string in other electronic documents based on the meta-data associated with the electronic document; and associating, with the electronic document, data indicating that each of the identified text strings is to be processed differently than an identical or similar text string in other electronic documents; and performing an analysis of the electronic documents to identify one or more subsets of the electronic documents that include related subject matter, wherein a first degree of relatedness of subject matter is associated with identical or similar text strings that do not have associated data indicating that each of the identical or similar text strings is to be processed differently; and wherein a second degree of relatedness of subject matter, different than the first degree of relatedness, is associated with identical or similar text strings, in which one of the text strings has associated data indicating that the text string is to be processed differently and the other text string does not have data indicating that the text string is to be processed differently. | 1. A computer-implemented method comprising: receiving a plurality of electronic documents associated with a domain at a server, wherein each of the plurality of electronic documents includes meta-data and textual content; for each electronic document in at least a subset of the plurality of electronic documents: identifying one or more text strings in the textual content that are to be processed differently than an identical or similar text string in other electronic documents based on the meta-data associated with the electronic document; and associating, with the electronic document, data indicating that each of the identified text strings is to be processed differently than an identical or similar text string in other electronic documents; and performing an analysis of the electronic documents to identify one or more subsets of the electronic documents that include related subject matter, wherein a first degree of relatedness of subject matter is associated with identical or similar text strings that do not have associated data indicating that each of the identical or similar text strings is to be processed differently; and wherein a second degree of relatedness of subject matter, different than the first degree of relatedness, is associated with identical or similar text strings, in which one of the text strings has associated data indicating that the text string is to be processed differently and the other text string does not have data indicating that the text string is to be processed differently. 6. The computer-implemented method of claim 1 , wherein the analysis includes using a particular text string as a potential feature for use in clustering documents if the particular text string has not been identified to be processed differently. | 0.513834 |
9,405,965 | 2 | 3 | 2. The method of claim 1 , wherein creating the second vector includes: calculating a distance of the first vector from each of the first plurality of vectors, and selecting from the calculated distances, for entry into the second vector, the predetermined number of calculated distances that are smallest. | 2. The method of claim 1 , wherein creating the second vector includes: calculating a distance of the first vector from each of the first plurality of vectors, and selecting from the calculated distances, for entry into the second vector, the predetermined number of calculated distances that are smallest. 3. The method of claim 2 , wherein each of the first plurality of vectors defines a center of a cluster, each cluster comprising a third plurality of vectors computed based on a portion of a different image of a face. | 0.5 |
8,346,534 | 94 | 102 | 94. A system for automatically generating one or more keywords from an electronic document, the system comprising: a network; one or more client computers communicably connected to the network; one or more server computers communicably connected to the network; one or more document storage repositories communicably connected to the network, to one or more of the client computers, or to one or more of the server computers; and a processor within at least one of the client computers or server computers, wherein the processor (a) identifies candidate entries for the keywords by extracting all n-grams up to a specified length that do not cross sentence boundaries, reducing a size of a data set consisting of the extracted n-grams by applying one or more filters and balancing a distribution of positive and negative examples whenever the data set is derived from a training data set, (b) constructs a feature vector for each candidate entry, wherein the feature vector comprises at least one feature selected from the group consisting of one or more discourse comprehension features, one or more part-of-speech pattern features, and one or more encyclopedic annotation features, (c) assigns a numeric score to each candidate entry based on the feature vector for that candidate entry, and (d) selects a specified number of entries to be retained as the keywords. | 94. A system for automatically generating one or more keywords from an electronic document, the system comprising: a network; one or more client computers communicably connected to the network; one or more server computers communicably connected to the network; one or more document storage repositories communicably connected to the network, to one or more of the client computers, or to one or more of the server computers; and a processor within at least one of the client computers or server computers, wherein the processor (a) identifies candidate entries for the keywords by extracting all n-grams up to a specified length that do not cross sentence boundaries, reducing a size of a data set consisting of the extracted n-grams by applying one or more filters and balancing a distribution of positive and negative examples whenever the data set is derived from a training data set, (b) constructs a feature vector for each candidate entry, wherein the feature vector comprises at least one feature selected from the group consisting of one or more discourse comprehension features, one or more part-of-speech pattern features, and one or more encyclopedic annotation features, (c) assigns a numeric score to each candidate entry based on the feature vector for that candidate entry, and (d) selects a specified number of entries to be retained as the keywords. 102. The system as recited in claim 94 , wherein the processor balances randomly selecting ten percent or fewer of the negative examples. | 0.951384 |
8,954,840 | 10 | 11 | 10. The system of claim 9 , further comprising a configuration, the operation of the scanning module being based at least in part on the configuration. | 10. The system of claim 9 , further comprising a configuration, the operation of the scanning module being based at least in part on the configuration. 11. The system of claim 10 , wherein the configuration comprises a scanner configuration associated with the scanning module and a data mode configuration associated with the handling module. | 0.5 |
8,671,387 | 1 | 2 | 1. A method, comprising: receiving an application at a computing device, the application comprising a stack and a database, the stack comprising one or more pages for a user interface to the application; and executing the application using the computing device, wherein executing the application comprises: locating a compiled script for the application based on a global identifier assigned to the compiled script, the compiled script including a scripting-language instruction for the application, wherein the global identifier comprises an application identifier for specifically identifying the application in a plurality of applications and an object identifier for specifically identifying an object of a computational model, and wherein the computational model is either the stack or the database, injecting the compiled script into the application, executing the injected script in the application, wherein the injected script is configured to perform at least one transaction of the computational model, wherein locating the compiled script comprises: determining that a script is to be compiled; requesting that the script be compiled comprises: receiving the script at a script compiler of the computing device, the script comprising at least one scripting-language instruction for the application, wherein the at least one instruction comprises a script extension for specifying use of the computational model, wherein the script extension comprises a key character and an identifier of the computational model; locating, by the script compiler of the computing device, the script extension within the script based on the key character; determining, by the script compiler of the computing device, the identifier for the computational model specified by the script extension; and generating, by the script compiler of the computing device, the compiled script corresponding to the script, wherein the compiled script comprises scripting-language code that replaces the script extension, and wherein the scripting-language code is configured to access the computational model identified by the identifier of the computational model; and receiving the compiled script, wherein the compiled script corresponds to the script. | 1. A method, comprising: receiving an application at a computing device, the application comprising a stack and a database, the stack comprising one or more pages for a user interface to the application; and executing the application using the computing device, wherein executing the application comprises: locating a compiled script for the application based on a global identifier assigned to the compiled script, the compiled script including a scripting-language instruction for the application, wherein the global identifier comprises an application identifier for specifically identifying the application in a plurality of applications and an object identifier for specifically identifying an object of a computational model, and wherein the computational model is either the stack or the database, injecting the compiled script into the application, executing the injected script in the application, wherein the injected script is configured to perform at least one transaction of the computational model, wherein locating the compiled script comprises: determining that a script is to be compiled; requesting that the script be compiled comprises: receiving the script at a script compiler of the computing device, the script comprising at least one scripting-language instruction for the application, wherein the at least one instruction comprises a script extension for specifying use of the computational model, wherein the script extension comprises a key character and an identifier of the computational model; locating, by the script compiler of the computing device, the script extension within the script based on the key character; determining, by the script compiler of the computing device, the identifier for the computational model specified by the script extension; and generating, by the script compiler of the computing device, the compiled script corresponding to the script, wherein the compiled script comprises scripting-language code that replaces the script extension, and wherein the scripting-language code is configured to access the computational model identified by the identifier of the computational model; and receiving the compiled script, wherein the compiled script corresponds to the script. 2. The method of claim 1 , wherein executing the application further comprises removing the injected script from the application. | 0.844578 |
9,292,488 | 17 | 18 | 17. The system of claim 12 , further including transcribing the message portion. | 17. The system of claim 12 , further including transcribing the message portion. 18. The system of claim 17 , wherein the destination is an email address. | 0.733577 |
9,800,729 | 8 | 13 | 8. A system comprising: a processor; and a memory storing instructions that, when executed by the processor, cause the processor to perform operations comprising: receiving a communication from a wireless communications device associated with a calling party, the communication directed to a user, receiving call data associated with the calling party, retrieving user data associated with the user, wherein the user data comprises preference data, determining, based at least in part on the preference data and the call data, that the calling party is authorized to send a text message to the user, determining, based on the calling party being authorized to send a text message to the user, to generate a menu including a first menu option allowing the calling party to send a text message to the user, receiving account status information indicating that a text message count associated with the user is nearing a limit, in response to receiving the account status information, determining to disable an ability of the calling party to send a text message to the user, based at least on the user data associated with the user, the call data associated with the calling party, and the account status information, generating the menu for the calling party without including the first menu option allowing the calling party to send a text message to the user, and transmitting the menu to the wireless communications device associated with the calling party for display at the wireless communications device. | 8. A system comprising: a processor; and a memory storing instructions that, when executed by the processor, cause the processor to perform operations comprising: receiving a communication from a wireless communications device associated with a calling party, the communication directed to a user, receiving call data associated with the calling party, retrieving user data associated with the user, wherein the user data comprises preference data, determining, based at least in part on the preference data and the call data, that the calling party is authorized to send a text message to the user, determining, based on the calling party being authorized to send a text message to the user, to generate a menu including a first menu option allowing the calling party to send a text message to the user, receiving account status information indicating that a text message count associated with the user is nearing a limit, in response to receiving the account status information, determining to disable an ability of the calling party to send a text message to the user, based at least on the user data associated with the user, the call data associated with the calling party, and the account status information, generating the menu for the calling party without including the first menu option allowing the calling party to send a text message to the user, and transmitting the menu to the wireless communications device associated with the calling party for display at the wireless communications device. 13. The system of claim 8 , wherein the menu further comprises a second menu option allowing the calling party to provide contact information associated with the calling party to the user. | 0.878553 |
7,548,910 | 9 | 10 | 9. A query expansion method in a system having a knowledge source storing a plurality of concepts formed from a predefined vocabulary set, the knowledge source maintaining a plurality of relationship links wherein each relationship link defines a relationship between a first grouping of the concepts and a second grouping of the concepts, the method comprising: generating, under control of one or more computers indexing concepts for a plurality of documents configured to be searched based on a search request, wherein the generating of the indexing concepts includes: maintaining under control of the one or more computers, a plurality of data structures mapping each of the plurality of concepts in the knowledge source to all words appearing in the concept; receiving, under control of the one or more computers, a particular one of the free-text documents; identifying based on the plurality of data structures, one or more of the plurality of concepts in the knowledge source mapped to a set of words appearing in the particular one of the free-text documents; and returning, under control of the one or more computers, the one or more identified concepts as candidates index concepts for the particular one of the free-text documents; receiving, under control of the one or more computers, an input query having an original query concept and at least one scenario identifier; generating, under control of the one or more computers, a list of candidate query expansion concepts based on the original query concept; filtering, under control of the one or more computers, the list of candidate expansion concepts based on the scenario identifier, wherein the filtering includes removing one or more of the candidate expansion concepts from the list if the one or more candidate expansion concepts are not included in one or more first particular groupings of the concepts in the knowledge source that have a specific relationship link with a second particular grouping of the concepts containing the original query concept, the specific relationship link being identified by the at least one scenario identifier; and generating, under control of the one or more computers, an expanded input query including the original query concept and remaining ones of the candidate expansion concepts. | 9. A query expansion method in a system having a knowledge source storing a plurality of concepts formed from a predefined vocabulary set, the knowledge source maintaining a plurality of relationship links wherein each relationship link defines a relationship between a first grouping of the concepts and a second grouping of the concepts, the method comprising: generating, under control of one or more computers indexing concepts for a plurality of documents configured to be searched based on a search request, wherein the generating of the indexing concepts includes: maintaining under control of the one or more computers, a plurality of data structures mapping each of the plurality of concepts in the knowledge source to all words appearing in the concept; receiving, under control of the one or more computers, a particular one of the free-text documents; identifying based on the plurality of data structures, one or more of the plurality of concepts in the knowledge source mapped to a set of words appearing in the particular one of the free-text documents; and returning, under control of the one or more computers, the one or more identified concepts as candidates index concepts for the particular one of the free-text documents; receiving, under control of the one or more computers, an input query having an original query concept and at least one scenario identifier; generating, under control of the one or more computers, a list of candidate query expansion concepts based on the original query concept; filtering, under control of the one or more computers, the list of candidate expansion concepts based on the scenario identifier, wherein the filtering includes removing one or more of the candidate expansion concepts from the list if the one or more candidate expansion concepts are not included in one or more first particular groupings of the concepts in the knowledge source that have a specific relationship link with a second particular grouping of the concepts containing the original query concept, the specific relationship link being identified by the at least one scenario identifier; and generating, under control of the one or more computers, an expanded input query including the original query concept and remaining ones of the candidate expansion concepts. 10. The method of claim 9 , wherein the list of candidate query expansion concepts are concepts statistically related to the original query concept. | 0.836283 |
8,838,459 | 10 | 13 | 10. A teleconferencing system, comprising: a teleconference management processor for managing a teleconference session between a plurality of teleconference participants, the teleconference management processor configured to: receive a first request from one of the plurality of teleconference participants for language translation services; generate a second request for the addition of a virtual participant processor to the teleconference session in response to receiving the first request; responsive to the second request, connect the virtual participant processor to the teleconference session; and deliver translated speech data received from the virtual participant processor to the respective teleconference participants; and the virtual participant processor, the virtual participant processor being configured to: intercept speech data from each of the teleconference participants; recognize a speech language of each of the teleconference participants; translate the intercepted speech data into the recognized speech language of each of the plurality of teleconference participants; and provide the translated speech data to the teleconference management processor. | 10. A teleconferencing system, comprising: a teleconference management processor for managing a teleconference session between a plurality of teleconference participants, the teleconference management processor configured to: receive a first request from one of the plurality of teleconference participants for language translation services; generate a second request for the addition of a virtual participant processor to the teleconference session in response to receiving the first request; responsive to the second request, connect the virtual participant processor to the teleconference session; and deliver translated speech data received from the virtual participant processor to the respective teleconference participants; and the virtual participant processor, the virtual participant processor being configured to: intercept speech data from each of the teleconference participants; recognize a speech language of each of the teleconference participants; translate the intercepted speech data into the recognized speech language of each of the plurality of teleconference participants; and provide the translated speech data to the teleconference management processor. 13. The teleconferencing system of claim 10 , wherein the teleconference management processor is further configured to: send the second request to the virtual participant processor to join the teleconference session. | 0.681416 |
6,018,708 | 22 | 24 | 22. A method as defined in claim 17, wherein said standard text lexicon includes M orthographies, comprising the step of inserting into said list N orthographies present in said standard text lexicon, where M.gtoreq.N. | 22. A method as defined in claim 17, wherein said standard text lexicon includes M orthographies, comprising the step of inserting into said list N orthographies present in said standard text lexicon, where M.gtoreq.N. 24. A method as defined in claim 22, wherein said step of processing said speech recognition dictionary to derive on the basis of the spoken utterance a list of orthographies comprises the step of generating probability data indicative of a likelihood of an orthography to constitute a match to the spoken utterance, the step of scoring orthographies in said standard text lexicon including the step of utilizing said probability data. | 0.5 |
8,139,900 | 2 | 3 | 2. The method of claim 1 , wherein performing an action includes specifying a content for display in response to detecting the selection input. | 2. The method of claim 1 , wherein performing an action includes specifying a content for display in response to detecting the selection input. 3. The method of claim 2 , wherein the content includes information that is based on the metadata. | 0.794118 |
9,270,548 | 10 | 16 | 10. A data processing system comprising: a processor; and an accessible memory, wherein the data processing system is particularly configured to monitor calls from a client system to a server system for properties associated with an object, each call having a context; store call data related to the calls as a property-retrieval history, including storing the context of each call; analyze a policy associated with at least one context based on the property-retrieval history; update the policy associated with the at least one context based on the analysis; and transfer data corresponding to the at least one context based on the policy. | 10. A data processing system comprising: a processor; and an accessible memory, wherein the data processing system is particularly configured to monitor calls from a client system to a server system for properties associated with an object, each call having a context; store call data related to the calls as a property-retrieval history, including storing the context of each call; analyze a policy associated with at least one context based on the property-retrieval history; update the policy associated with the at least one context based on the analysis; and transfer data corresponding to the at least one context based on the policy. 16. The data processing system of claim 10 , wherein the call data also includes an object type and the properties associated with each call. | 0.614754 |
8,677,232 | 1 | 6 | 1. An electronic device, comprising: a display; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying at least a portion of an electronic document at a first magnification level on the display; detecting a first input indicating a first insertion point in the document, wherein the first insertion point is proximate to a first portion of text in the document; in response to detecting the first input: selecting a second magnification level different from the first magnification level, wherein the second magnification level is selected so as to display the first portion of text at a default target text display size; and displaying a portion of the document at the second magnification level; detecting a second input corresponding to a request to display a portion of the document at a third magnification level different from the second magnification level; in response to detecting the second input: displaying the portion of the document at the third magnification level; and storing a user-adjusted target text display size corresponding to a text display size of the first portion of text at the third magnification level, wherein the user-adjusted target text display size is different from the default target text display size; and after storing the user-adjusted target text display size: detecting a third input indicating a second insertion point in the document, wherein the second insertion point is proximate to a second portion of text in the document; and in response to detecting the third input, displaying the document at a respective magnification level such that the second portion of text is displayed at the user-adjusted target text display size. | 1. An electronic device, comprising: a display; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying at least a portion of an electronic document at a first magnification level on the display; detecting a first input indicating a first insertion point in the document, wherein the first insertion point is proximate to a first portion of text in the document; in response to detecting the first input: selecting a second magnification level different from the first magnification level, wherein the second magnification level is selected so as to display the first portion of text at a default target text display size; and displaying a portion of the document at the second magnification level; detecting a second input corresponding to a request to display a portion of the document at a third magnification level different from the second magnification level; in response to detecting the second input: displaying the portion of the document at the third magnification level; and storing a user-adjusted target text display size corresponding to a text display size of the first portion of text at the third magnification level, wherein the user-adjusted target text display size is different from the default target text display size; and after storing the user-adjusted target text display size: detecting a third input indicating a second insertion point in the document, wherein the second insertion point is proximate to a second portion of text in the document; and in response to detecting the third input, displaying the document at a respective magnification level such that the second portion of text is displayed at the user-adjusted target text display size. 6. The device of claim 1 , wherein the respective magnification level is different from the third magnification level if the second portion of text has a different font size from a font size of the first portion of text. | 0.634551 |
10,146,815 | 15 | 16 | 15. A system, comprising: a clustering component configured to: evaluate a query session to identify query information for queries within the query session; evaluate the queries as query pairs utilizing a goal classifier to determine common goal probabilities for the query pairs based upon the query information; group one or more query pairs associated with common goal probabilities exceeding a goal probability threshold into a plurality of goal clusters; evaluate the plurality of goal cluster as goal cluster pairs utilizing a mission classifier to determine common mission probabilities for the goal cluster pairs, wherein the plurality of goal clusters comprises at least a first goal cluster and a second goal cluster; group the first goal cluster and the second goal cluster, of a first goal cluster pair of the goal cluster pairs, into a first mission cluster based upon a first common mission probability, for the first goal cluster pair, exceeding a mission probability threshold, wherein the first mission cluster is associated with two or more query pairs; generate a query-goal-mission structure for the set of queries based upon the plurality of goal clusters and the first mission cluster; receive a search query from a remote device; evaluate the search query to identify a search query aspect; responsive to the search query aspect corresponding to an aspect of the query-goal-mission structure, use the query-goal-mission structure to identify a query recommendation; and transmit the query recommendation to the remote device. | 15. A system, comprising: a clustering component configured to: evaluate a query session to identify query information for queries within the query session; evaluate the queries as query pairs utilizing a goal classifier to determine common goal probabilities for the query pairs based upon the query information; group one or more query pairs associated with common goal probabilities exceeding a goal probability threshold into a plurality of goal clusters; evaluate the plurality of goal cluster as goal cluster pairs utilizing a mission classifier to determine common mission probabilities for the goal cluster pairs, wherein the plurality of goal clusters comprises at least a first goal cluster and a second goal cluster; group the first goal cluster and the second goal cluster, of a first goal cluster pair of the goal cluster pairs, into a first mission cluster based upon a first common mission probability, for the first goal cluster pair, exceeding a mission probability threshold, wherein the first mission cluster is associated with two or more query pairs; generate a query-goal-mission structure for the set of queries based upon the plurality of goal clusters and the first mission cluster; receive a search query from a remote device; evaluate the search query to identify a search query aspect; responsive to the search query aspect corresponding to an aspect of the query-goal-mission structure, use the query-goal-mission structure to identify a query recommendation; and transmit the query recommendation to the remote device. 16. The system of claim 15 , the query session comprising a cross device query session. | 0.874277 |
9,886,486 | 3 | 4 | 3. The method of claim 1 , wherein the data store comprises a non-relational database. | 3. The method of claim 1 , wherein the data store comprises a non-relational database. 4. The method of claim 3 , wherein the non-relational database comprises an HBase database. | 0.5 |
7,797,344 | 1 | 2 | 1. A computer-implemented method for assigning scores to a plurality of linked documents, at least some of the documents being hypermedia documents, comprising: constructing by a processor executing a program a spring network representation according to a connectivity graph of a collection of documents and links among the documents, the spring network representation including a plurality of nodes wherein each node corresponds to at least one document, the spring network representation further including an inter-nodal virtual spring connected between each pair of nodes associated with documents having a link between the documents, the inter-nodal virtual spring corresponding to the document link between the corresponding pair of documents; adding a virtual anchor spring to each node in the spring network representation, each virtual anchor spring associated with only one node and not corresponding to a link between any documents; identifying a plurality of nodes as one or more reference nodes and one or more regular nodes, each reference node preselected independently of any other node or relationship of the reference node with any other node; (a) applying a predetermined amount of virtual input displacements on the reference nodes within the spring network representation, the virtual input displacements having constant values and collectively comprising a virtual input displacement vector; (b) determining a virtual strength value for each inter-nodal virtual spring in the spring network representation, each inter-nodal spring virtual strength value derived from the virtual input displacement associated with the pair of nodes connected to a particular inter-nodal virtual spring; (c) calculating one or more virtual inter-nodal forces and a virtual anchor spring force that collectively virtually act on each node in the spring network representation, each inter-nodal force derived from the product of the virtual strength value of the inter-nodal virtual spring and virtual displacement of a particular node, each virtual anchor spring force derived from the product of an anchor spring strength and the virtual displacement of the particular node; (d) calculating a total force on each node in the spring network representation as the sum of all the virtual inter-nodal forces associated with each particular node and the virtual anchor spring force for the particular node, the total force on each node in the spring network representation collectively set as a virtual output displacement vector; (e) comparing the virtual output displacement vector and the virtual input displacement vector for the plurality of nodes; determining that the virtual output displacement vector and the virtual input displacement vector do not converge; (f) adding the virtual output displacement vector and the virtual input displacement vector for the plurality of nodes to derive a new virtual input displacement vector as the sum of the virtual output displacement vector and the virtual input displacement vector, the adding performed based on the non-convergence, a new virtual input displacement vector to be used as a new predetermined amount of virtual input displacement vector; repeating the steps (a)-(f), the repeated steps performed based on substituting the value of the pre-determined amount of virtual input displacement with values of the new virtual input displacement vector, the steps repeated until the virtual output displacement vector and the virtual input displacement vector converge; and assigning scores to documents based on values of the virtual output displacement vector of the nodes that correspond to the documents when the virtual output displacement vector and the virtual input displacement vector converge for each node within the spring network representation. | 1. A computer-implemented method for assigning scores to a plurality of linked documents, at least some of the documents being hypermedia documents, comprising: constructing by a processor executing a program a spring network representation according to a connectivity graph of a collection of documents and links among the documents, the spring network representation including a plurality of nodes wherein each node corresponds to at least one document, the spring network representation further including an inter-nodal virtual spring connected between each pair of nodes associated with documents having a link between the documents, the inter-nodal virtual spring corresponding to the document link between the corresponding pair of documents; adding a virtual anchor spring to each node in the spring network representation, each virtual anchor spring associated with only one node and not corresponding to a link between any documents; identifying a plurality of nodes as one or more reference nodes and one or more regular nodes, each reference node preselected independently of any other node or relationship of the reference node with any other node; (a) applying a predetermined amount of virtual input displacements on the reference nodes within the spring network representation, the virtual input displacements having constant values and collectively comprising a virtual input displacement vector; (b) determining a virtual strength value for each inter-nodal virtual spring in the spring network representation, each inter-nodal spring virtual strength value derived from the virtual input displacement associated with the pair of nodes connected to a particular inter-nodal virtual spring; (c) calculating one or more virtual inter-nodal forces and a virtual anchor spring force that collectively virtually act on each node in the spring network representation, each inter-nodal force derived from the product of the virtual strength value of the inter-nodal virtual spring and virtual displacement of a particular node, each virtual anchor spring force derived from the product of an anchor spring strength and the virtual displacement of the particular node; (d) calculating a total force on each node in the spring network representation as the sum of all the virtual inter-nodal forces associated with each particular node and the virtual anchor spring force for the particular node, the total force on each node in the spring network representation collectively set as a virtual output displacement vector; (e) comparing the virtual output displacement vector and the virtual input displacement vector for the plurality of nodes; determining that the virtual output displacement vector and the virtual input displacement vector do not converge; (f) adding the virtual output displacement vector and the virtual input displacement vector for the plurality of nodes to derive a new virtual input displacement vector as the sum of the virtual output displacement vector and the virtual input displacement vector, the adding performed based on the non-convergence, a new virtual input displacement vector to be used as a new predetermined amount of virtual input displacement vector; repeating the steps (a)-(f), the repeated steps performed based on substituting the value of the pre-determined amount of virtual input displacement with values of the new virtual input displacement vector, the steps repeated until the virtual output displacement vector and the virtual input displacement vector converge; and assigning scores to documents based on values of the virtual output displacement vector of the nodes that correspond to the documents when the virtual output displacement vector and the virtual input displacement vector converge for each node within the spring network representation. 2. The method of claim 1 , wherein the convergence is determined by an error function. | 0.697183 |
9,858,313 | 11 | 15 | 11. A method comprising: receiving a suggestion set at a mobile device, the suggestion set comprising a subset of two or more entities comparable to a search query and not dominated by another entity of the two or more entities based at least in part on: a plurality of attribute values of corresponding attributes and on one or more determined dominance relationships between pairs of the two or more entities based at least in part on separate consideration of query-independent and query-dependent attribute values, and one or more inference rules indicative of an existence of one or more static domination relationships between attributes of the plurality of entities; wherein the two or more entities are capable of being identified as being comparable at least partially in response to determining that comparability values between the pairs of the two or more entities have at least a threshold value of comparability, and wherein a first entity of the two or more entities is capable of being determined not to dominate a second entity of the two or more entities at least partially in response to a determination that individual first attribute values of at least two of the attributes of the first entity are not indicative of a greater scope of interest than corresponding query-dependent individual second attribute values of the at least two of the attributes of the second entity. | 11. A method comprising: receiving a suggestion set at a mobile device, the suggestion set comprising a subset of two or more entities comparable to a search query and not dominated by another entity of the two or more entities based at least in part on: a plurality of attribute values of corresponding attributes and on one or more determined dominance relationships between pairs of the two or more entities based at least in part on separate consideration of query-independent and query-dependent attribute values, and one or more inference rules indicative of an existence of one or more static domination relationships between attributes of the plurality of entities; wherein the two or more entities are capable of being identified as being comparable at least partially in response to determining that comparability values between the pairs of the two or more entities have at least a threshold value of comparability, and wherein a first entity of the two or more entities is capable of being determined not to dominate a second entity of the two or more entities at least partially in response to a determination that individual first attribute values of at least two of the attributes of the first entity are not indicative of a greater scope of interest than corresponding query-dependent individual second attribute values of the at least two of the attributes of the second entity. 15. The method of claim 11 , wherein at least one of the two or more attributes having been determined from a semi-structured or structured database. | 0.5 |
8,561,100 | 12 | 14 | 12. A system for determining access authorization, comprising: a bus; persistent storage connected to the bus; a memory connected to the bus, wherein the memory has program code stored therein; a communications unit connected to the bus; a processor unit connected to the bus, wherein the processor unit executes the program code stored in the memory to direct the system to create: an authorization control engine that evaluates a semantic ontology expression and a structural expression contained within an access control statement for determining authorization request validity using the authorization control engine for an asset, defining the access control statement for the asset, wherein the access control statement comprises a first portion comprising one or more of a structural expression, and a conditional expression wherein the structural expression defines fixed relationships of the asset and a second portion comprising one or more of a classification expression comprising ontology expressions; and an authorization checkpoint communicatively coupled to the authorization control engine that restricts access until authorization is determined. | 12. A system for determining access authorization, comprising: a bus; persistent storage connected to the bus; a memory connected to the bus, wherein the memory has program code stored therein; a communications unit connected to the bus; a processor unit connected to the bus, wherein the processor unit executes the program code stored in the memory to direct the system to create: an authorization control engine that evaluates a semantic ontology expression and a structural expression contained within an access control statement for determining authorization request validity using the authorization control engine for an asset, defining the access control statement for the asset, wherein the access control statement comprises a first portion comprising one or more of a structural expression, and a conditional expression wherein the structural expression defines fixed relationships of the asset and a second portion comprising one or more of a classification expression comprising ontology expressions; and an authorization checkpoint communicatively coupled to the authorization control engine that restricts access until authorization is determined. 14. The system of claim 12 , wherein the authorization control engine evaluates whether terms are semantically equivalent. | 0.773234 |
8,275,796 | 1 | 2 | 1. A computer-implemented method of managing a set of interrelated knowledge objects, the method comprising: creating, by a server, a knowledge object of a particular object type responsive to receiving a request from a user; wherein the particular object type is associated with a predetermined semantic structure suitable to represent the knowledge object; presenting a form specific to the particular object type having a plurality of predetermined fields in conjunction with creating the knowledge object; analyzing, by the server, the knowledge object to identify metadata associated with the knowledge object; and creating a semantic link between the knowledge object with another knowledge object of the set of interrelated knowledge objects, based on the identified metadata; tracking a set of rules including a rule to subscribe to knowledge objects in the set of interrelated knowledge objects; wherein, the set of rules further includes permission to access the set of interrelated objects, wherein, the permission to access includes authoring or editing permissions of the set of interrelated knowledge objects; wherein, the rule to subscribe specifies a source from which to subscribe to the knowledge objects; wherein, the source is a web site or a user; and wherein, the knowledge object is associated with a knowledge database; wherein, the knowledge database is an ontology or taxonomy. | 1. A computer-implemented method of managing a set of interrelated knowledge objects, the method comprising: creating, by a server, a knowledge object of a particular object type responsive to receiving a request from a user; wherein the particular object type is associated with a predetermined semantic structure suitable to represent the knowledge object; presenting a form specific to the particular object type having a plurality of predetermined fields in conjunction with creating the knowledge object; analyzing, by the server, the knowledge object to identify metadata associated with the knowledge object; and creating a semantic link between the knowledge object with another knowledge object of the set of interrelated knowledge objects, based on the identified metadata; tracking a set of rules including a rule to subscribe to knowledge objects in the set of interrelated knowledge objects; wherein, the set of rules further includes permission to access the set of interrelated objects, wherein, the permission to access includes authoring or editing permissions of the set of interrelated knowledge objects; wherein, the rule to subscribe specifies a source from which to subscribe to the knowledge objects; wherein, the source is a web site or a user; and wherein, the knowledge object is associated with a knowledge database; wherein, the knowledge database is an ontology or taxonomy. 2. The method of claim 1 , wherein, the set of rules are specifiable by an administrative user of the set of interrelated knowledge objects. | 0.5 |
9,734,233 | 12 | 13 | 12. The method of claim 1 , wherein a lock release function of limiting and releasing access to the semantic menu is added to the semantic menu displayed by operation (e). | 12. The method of claim 1 , wherein a lock release function of limiting and releasing access to the semantic menu is added to the semantic menu displayed by operation (e). 13. The method of claim 12 , wherein the lock release function is provided so as to select an entire lock for the entire semantic menus, a partial lock for partially selected menus among the semantic menus, and an individual lock for an individual semantic menu. | 0.676543 |
9,489,412 | 16 | 20 | 16. A computer system comprising: a central processing unit (CPU); a memory coupled to the CPU; and a computer-readable storage device coupled to the CPU, the storage device containing instructions that are executed by the CPU via the memory to implement a method of managing replicated data, the method comprising the steps of: the computer system receiving first metadata specifying inter-data correlation(s), which are correlation(s) between sets of replicated data in a first set of replicas; the computer system receiving second metadata specifying inter-replica correlation(s), which are correlation(s) between replicas included in a second set of replicas; the computer system receiving third metadata specifying data-replica correlation(s), which are correlation(s) between set(s) of replicated data and respective replica(s) included in a third set of replicas, the first, second and third sets of replicas being included in a plurality of replicas generated for a replicated data management system; the computer system determining a current usage of resources in the replicated data management system and a threshold usage of the resources; the computer system generating a unified replication metadata model specifying the inter-data correlation(s) based on the first metadata, the inter-replica correlation(s) based on the second metadata, and the data-replica correlation(s) based on the third metadata; based on the inter-replica correlation(s) specified by the unified replication metadata model, the computer system selecting a proper subset of replicas included in the plurality of replicas; based on the inter-replica and inter-data correlation(s) specified by the unified replication metadata model, the computer system indexing the selected proper subset of replicas to generate a unified content index, wherein the step of indexing the selected proper subset includes: if the current usage is less than the threshold usage, then the computer system determining an expected additional resource usage due to performing an indexing task online, and based on the expected additional resource usage, the computer system determining a resource affinity score for performing the indexing task online; and if the current usage is greater than or equal to the threshold usage, then the computer system determining an expected resource usage due to performing the indexing task offline and based on the expected resource usage, the computer system determining a resource affinity score for performing the indexing task offline; the computer system receiving a query to locate a data item in at least one replica included in the plurality of replicas; and based on the unified content index, the unified replication metadata model, and the received query, the computer system determining candidate replica(s) and corresponding confidence score(s), the confidence score(s) indicating respective likelihood(s) that the candidate replica(s) include the data item, and the candidate replica(s) included in the plurality of replicas. | 16. A computer system comprising: a central processing unit (CPU); a memory coupled to the CPU; and a computer-readable storage device coupled to the CPU, the storage device containing instructions that are executed by the CPU via the memory to implement a method of managing replicated data, the method comprising the steps of: the computer system receiving first metadata specifying inter-data correlation(s), which are correlation(s) between sets of replicated data in a first set of replicas; the computer system receiving second metadata specifying inter-replica correlation(s), which are correlation(s) between replicas included in a second set of replicas; the computer system receiving third metadata specifying data-replica correlation(s), which are correlation(s) between set(s) of replicated data and respective replica(s) included in a third set of replicas, the first, second and third sets of replicas being included in a plurality of replicas generated for a replicated data management system; the computer system determining a current usage of resources in the replicated data management system and a threshold usage of the resources; the computer system generating a unified replication metadata model specifying the inter-data correlation(s) based on the first metadata, the inter-replica correlation(s) based on the second metadata, and the data-replica correlation(s) based on the third metadata; based on the inter-replica correlation(s) specified by the unified replication metadata model, the computer system selecting a proper subset of replicas included in the plurality of replicas; based on the inter-replica and inter-data correlation(s) specified by the unified replication metadata model, the computer system indexing the selected proper subset of replicas to generate a unified content index, wherein the step of indexing the selected proper subset includes: if the current usage is less than the threshold usage, then the computer system determining an expected additional resource usage due to performing an indexing task online, and based on the expected additional resource usage, the computer system determining a resource affinity score for performing the indexing task online; and if the current usage is greater than or equal to the threshold usage, then the computer system determining an expected resource usage due to performing the indexing task offline and based on the expected resource usage, the computer system determining a resource affinity score for performing the indexing task offline; the computer system receiving a query to locate a data item in at least one replica included in the plurality of replicas; and based on the unified content index, the unified replication metadata model, and the received query, the computer system determining candidate replica(s) and corresponding confidence score(s), the confidence score(s) indicating respective likelihood(s) that the candidate replica(s) include the data item, and the candidate replica(s) included in the plurality of replicas. 20. The computer system of claim 16 , wherein the step of indexing the selected proper subset of replicas includes the steps of: the computer system determining index updates by determining keyword-to-replica mappings; and the computer system generating the unified content index based on the index updates. | 0.871977 |
7,987,189 | 11 | 18 | 11. In a computing system having access to multiple content entities, each content entity including searchable content, a method for performing a run-time search of the searchable content to identify a ranked list of relevant content entities, the method comprising: receiving, from a user of a client application, a query that includes one or more target search terms, the one or more target search terms being provided in a natural word format; translating the query received from the user into a database query conducive to a known architecture of a database associated with searchable content, wherein the database includes at least a double word table, the double word table including only all possible unique two word combinations of words from the searchable content; querying the database by comparing the database query to the database, thereby generating a list of content entities that are potential matches; ranking the content entities in the list in descending order, based on a calculated likelihood that a particular entity is a target of the query from the user; removing from the ranking any content entities that are duplicates; and returning, to the client application, a list of content entities with the highest ranking. | 11. In a computing system having access to multiple content entities, each content entity including searchable content, a method for performing a run-time search of the searchable content to identify a ranked list of relevant content entities, the method comprising: receiving, from a user of a client application, a query that includes one or more target search terms, the one or more target search terms being provided in a natural word format; translating the query received from the user into a database query conducive to a known architecture of a database associated with searchable content, wherein the database includes at least a double word table, the double word table including only all possible unique two word combinations of words from the searchable content; querying the database by comparing the database query to the database, thereby generating a list of content entities that are potential matches; ranking the content entities in the list in descending order, based on a calculated likelihood that a particular entity is a target of the query from the user; removing from the ranking any content entities that are duplicates; and returning, to the client application, a list of content entities with the highest ranking. 18. A method as recited in claim 11 , wherein returning, to the client application, a list of content entities with the highest ranking comprises: returning to the client a list of only those content entities with a ranking above a predetermined threshold value. | 0.5 |
7,792,789 | 1 | 3 | 1. A computer-implemented method for collaboratively searching for stored documents related to an organization, the method comprising: creating a collaborative document, wherein multiple users can add search criteria to the collaborative document; posting the collaborative document to a collaborative shared logical location accessible by multiple users; receiving at least a first search criterion from a first user computer and adding and saving the first search criterion to the collaborative document; receiving at least a second search criterion from a second user computer and adding and saving the second search criterion to the same collaborative document, wherein the first and second user computers are geographically separated; performing a search of the stored documents based on the collaborative document containing the first and second search criteria to create one or more search results that identify stored documents, wherein the search of the stored documents includes a search of an online index that stores metadata for both online and offline documents, wherein offline documents include documents stored in secondary copies, including copies stored in backups, in archive copies, or in a tape library, wherein some or all of the offline documents contain data that is no longer available on a local area network of the organization, and wherein the online index stores data at least identifying an existence and location of both the online and offline documents; and providing the one or more search results that identify stored documents, wherein the provided search results include an indication of a location of at least one offline document. | 1. A computer-implemented method for collaboratively searching for stored documents related to an organization, the method comprising: creating a collaborative document, wherein multiple users can add search criteria to the collaborative document; posting the collaborative document to a collaborative shared logical location accessible by multiple users; receiving at least a first search criterion from a first user computer and adding and saving the first search criterion to the collaborative document; receiving at least a second search criterion from a second user computer and adding and saving the second search criterion to the same collaborative document, wherein the first and second user computers are geographically separated; performing a search of the stored documents based on the collaborative document containing the first and second search criteria to create one or more search results that identify stored documents, wherein the search of the stored documents includes a search of an online index that stores metadata for both online and offline documents, wherein offline documents include documents stored in secondary copies, including copies stored in backups, in archive copies, or in a tape library, wherein some or all of the offline documents contain data that is no longer available on a local area network of the organization, and wherein the online index stores data at least identifying an existence and location of both the online and offline documents; and providing the one or more search results that identify stored documents, wherein the provided search results include an indication of a location of at least one offline document. 3. The computer-implemented method of claim 1 wherein posting the collaborative document comprises making the collaborative document available through a web portal. | 0.585859 |
9,977,656 | 17 | 19 | 17. A non-transitory computer-readable medium storing instructions for providing one or more software components for developing a software application that, when executed by a processor, cause the processor to perform operations including: receiving an input from a user via a user interface, the input including one or more requirements associated with the software application; determining, for each of a plurality of software components existing in an application development environment, a requirements matching score based on a comparison between the one or more requirements and a requirements model associated with the corresponding software component, wherein the requirements model is generated based on historic user requirements and historic usage of the software component; determining a performance score for each of the plurality of software components based on a response time associated with the corresponding software component; determining a weight corresponding to the requirements matching score and a weight corresponding to the performance score based on the requirements matching score; determining a combined score for each of the plurality of software components based on the weight corresponding to the requirements matching score and the weight corresponding to the performance score; selecting, from the plurality of software components, the one or more software components for developing the software application based on the combined score for each of the plurality of software components; and providing the one or more software components to the user via the user interface. | 17. A non-transitory computer-readable medium storing instructions for providing one or more software components for developing a software application that, when executed by a processor, cause the processor to perform operations including: receiving an input from a user via a user interface, the input including one or more requirements associated with the software application; determining, for each of a plurality of software components existing in an application development environment, a requirements matching score based on a comparison between the one or more requirements and a requirements model associated with the corresponding software component, wherein the requirements model is generated based on historic user requirements and historic usage of the software component; determining a performance score for each of the plurality of software components based on a response time associated with the corresponding software component; determining a weight corresponding to the requirements matching score and a weight corresponding to the performance score based on the requirements matching score; determining a combined score for each of the plurality of software components based on the weight corresponding to the requirements matching score and the weight corresponding to the performance score; selecting, from the plurality of software components, the one or more software components for developing the software application based on the combined score for each of the plurality of software components; and providing the one or more software components to the user via the user interface. 19. The non-transitory computer-readable medium of claim 17 , wherein the non-transitory computer-readable medium stores instructions that, when executed by the processor, cause the processor to further perform operations including: determining a functional and technical match score for each of the plurality of software components based on the input and a metadata repository, the metadata repository including metadata for each of the plurality of software components; determining a weight corresponding to functional and technical match score based on the requirements matching score; and determining a combined score for each of the plurality of software components based on the weight corresponding to the requirements matching score, the weight corresponding to the performance score, and the weight corresponding to the functional and technical match score. | 0.5 |
8,395,966 | 16 | 17 | 16. The system of claim 15 , wherein the data gathers comprise common offset gather, common receiver gathers or common midpoint gathers. | 16. The system of claim 15 , wherein the data gathers comprise common offset gather, common receiver gathers or common midpoint gathers. 17. The system of claim 16 , wherein the gathers are continuous due to at least one feature shared in common with the gathers. | 0.5 |
8,571,320 | 1 | 2 | 1. A method, comprising: initiating, by a first device, a communication event comprising speech, text, or both speech and text with a second device via a network connection; identifying, by said first device, words from said communication event using at least one of speech recognition and text recognition during the communication event, said identified words comprising words received via a user interface of said first device and words received via said network connection from said second device; identifying, by said first device, at least one picture from a library of reference pictures stored in said first device by comparing said identified words with a plurality of key picture words during the communication event, each of the at least one picture in the library of the reference pictures corresponding to at least one of the key picture words; and storing said at least one picture identified from said library in the first device such that a topic of the communication event is associated with the stored at least one picture. | 1. A method, comprising: initiating, by a first device, a communication event comprising speech, text, or both speech and text with a second device via a network connection; identifying, by said first device, words from said communication event using at least one of speech recognition and text recognition during the communication event, said identified words comprising words received via a user interface of said first device and words received via said network connection from said second device; identifying, by said first device, at least one picture from a library of reference pictures stored in said first device by comparing said identified words with a plurality of key picture words during the communication event, each of the at least one picture in the library of the reference pictures corresponding to at least one of the key picture words; and storing said at least one picture identified from said library in the first device such that a topic of the communication event is associated with the stored at least one picture. 2. The method of claim 1 , further comprising: the first device identifying and storing a background color out of a library of reference colors for the identified at least one picture by comparing said identified words with key color words, wherein each background color out of the library of the reference colors is uniquely identified by at least one of the key color words to facilitate identification of said topic of the communication event by displaying said at least one stored picture with said stored background color. | 0.5 |
7,685,514 | 48 | 49 | 48. The apparatus of claim 47 , wherein the creating means comprises means for inserting virtual font indicators before and after text within the selected portion. | 48. The apparatus of claim 47 , wherein the creating means comprises means for inserting virtual font indicators before and after text within the selected portion. 49. The apparatus of claim 48 , further comprising means for displaying the second web document, the selected portion being displayed according to the virtual font indicators. | 0.5 |
8,880,548 | 12 | 13 | 12. A hardware computer-readable storage media having instructions stored thereon that, when executed by a computing device, cause the computing device to perform acts comprising: obtaining an input search query from a user, the input search query comprising an input search term; identifying instances where other users have used the input search term as an initial search query and added additional search terms to the initial search query to obtain refined search queries, wherein the initial search query and the refined search queries were previously entered by the other users; organizing the refined search queries that were previously entered by the other users into at least multiple first refined search queries that were entered by first other users and that are associated with a first topic and multiple second refined search queries that were entered by second other users and that are associated with a second topic; estimating a first relative likelihood that an intent of the user matches the first topic; estimating a second relative likelihood that the intent of the user matches the second topic, the first relative likelihood being greater than the second relative likelihood; and causing the multiple first refined search queries that were previously entered by the first other users to be displayed on a graphical user interface (GUI) concurrently with the multiple second refined search queries that were previously entered by the second other users, the displayed GUI indicating that the first relative likelihood that the intent of the user matches the first topic is greater than the second relative likelihood that the intent of the user matches the second topic. | 12. A hardware computer-readable storage media having instructions stored thereon that, when executed by a computing device, cause the computing device to perform acts comprising: obtaining an input search query from a user, the input search query comprising an input search term; identifying instances where other users have used the input search term as an initial search query and added additional search terms to the initial search query to obtain refined search queries, wherein the initial search query and the refined search queries were previously entered by the other users; organizing the refined search queries that were previously entered by the other users into at least multiple first refined search queries that were entered by first other users and that are associated with a first topic and multiple second refined search queries that were entered by second other users and that are associated with a second topic; estimating a first relative likelihood that an intent of the user matches the first topic; estimating a second relative likelihood that the intent of the user matches the second topic, the first relative likelihood being greater than the second relative likelihood; and causing the multiple first refined search queries that were previously entered by the first other users to be displayed on a graphical user interface (GUI) concurrently with the multiple second refined search queries that were previously entered by the second other users, the displayed GUI indicating that the first relative likelihood that the intent of the user matches the first topic is greater than the second relative likelihood that the intent of the user matches the second topic. 13. The hardware computer-readable storage media of claim 12 , the acts further comprising: identifying a first seed query associated with the first topic and a second seed query associated with the second topic; comparing the refined search queries to the first seed query to identify the multiple first refined search queries associated with the first topic; and comparing the refined search queries to the second seed query to identify the multiple second refined search queries associated with the second topic. | 0.571547 |
8,851,900 | 7 | 8 | 7. The machine-readable medium of claim 3 wherein said display mode requires the response mechanism presented in (iii) to replace the other of said subject matter and said query or instruction presented in (ii). | 7. The machine-readable medium of claim 3 wherein said display mode requires the response mechanism presented in (iii) to replace the other of said subject matter and said query or instruction presented in (ii). 8. The machine-readable medium of claim 7 wherein said display mode precludes repeating (i) or (ii) after (iii) prior to entry of a user response. | 0.650718 |
4,513,435 | 2 | 4 | 2. A continuous speech recognition system as claimed in claim 1, wherein said reference pattern memorizing means comprises: means for holding, at one time, parameters characteristic of at least those two of said preselected reference words which are continuously pronounced; a reference pattern memory; and means for operatively connecting said parameter holding means and said reference pattern memory to segmenting means operable at first to segment, with each of said preselected reference wors selected, a former and a latter reference pattern segment from a parameter sequence representative of the selected reference word at the intra-word characteristic point thereof and to store said former and said latter reference pattern segments in said reference pattern memory as those two of said discrete demi-word pair reference patterns in which the preceding and the succeeding reference words are null reference words, respectively, and thereafter operable to form, for each pair of those first and second selected ones of said preselected reference words which are successively continuously pronounced, a segment concatenation of the former and the latter reference pattern segments for the first selected reference word and the former and the latter reference pattern segments for the second selected reference word, to find a pair of intra-word characteristic points in a parameter sequence representative of the first and the second selected and successively continuously pronounced reference words with reference to said segment concatenation, to segment a word pair reference pattern segment from the last-mentioned parameter sequence at said intra-word characteristic point pair, and to store said word pair reference pattern segment in said reference pattern memory as one of said discrete demi-word pair reference patterns. | 2. A continuous speech recognition system as claimed in claim 1, wherein said reference pattern memorizing means comprises: means for holding, at one time, parameters characteristic of at least those two of said preselected reference words which are continuously pronounced; a reference pattern memory; and means for operatively connecting said parameter holding means and said reference pattern memory to segmenting means operable at first to segment, with each of said preselected reference wors selected, a former and a latter reference pattern segment from a parameter sequence representative of the selected reference word at the intra-word characteristic point thereof and to store said former and said latter reference pattern segments in said reference pattern memory as those two of said discrete demi-word pair reference patterns in which the preceding and the succeeding reference words are null reference words, respectively, and thereafter operable to form, for each pair of those first and second selected ones of said preselected reference words which are successively continuously pronounced, a segment concatenation of the former and the latter reference pattern segments for the first selected reference word and the former and the latter reference pattern segments for the second selected reference word, to find a pair of intra-word characteristic points in a parameter sequence representative of the first and the second selected and successively continuously pronounced reference words with reference to said segment concatenation, to segment a word pair reference pattern segment from the last-mentioned parameter sequence at said intra-word characteristic point pair, and to store said word pair reference pattern segment in said reference pattern memory as one of said discrete demi-word pair reference patterns. 4. A continuous speech recognition system as claimed in claim 2, wherein the intra-word characteristic point is an instant at which spectra of utterance of each of said preselected reference words have a maximum variation adjacently of an instant which bisects a duration of a parameter sequence representative of said each reference word. | 0.865796 |
7,970,793 | 15 | 16 | 15. The program product of claim 14 wherein the RSS-retrievable specific event information is a set comprising an event announcement, a date, a time and a description, and an XML file format meta-data tag; and wherein the calendar format is a format specific for the user calendar. | 15. The program product of claim 14 wherein the RSS-retrievable specific event information is a set comprising an event announcement, a date, a time and a description, and an XML file format meta-data tag; and wherein the calendar format is a format specific for the user calendar. 16. The program product of claim 15 wherein the third program instructions are further to periodically check the body content of the web page for a presence of a calendar tag; and wherein the third program instructions are further to identify the RSS-retrievable specific event information in response to the presence of the calendar tag. | 0.5 |
5,559,898 | 29 | 35 | 29. The method of claim 28, wherein the vector elements in the input vector and the template vector have numerical values, and the sort is by numerical value. | 29. The method of claim 28, wherein the vector elements in the input vector and the template vector have numerical values, and the sort is by numerical value. 35. The method of claim 29, wherein the q pairs of corresponding elements are sorted by the numerical values of the elements forming the foreground. | 0.787966 |
7,616,342 | 15 | 16 | 15. The system of claim 12 wherein said processor processes each callout among said plurality of callouts separately from each object among said plurality of objects utilizing said plurality of attributes associated with an object among said plurality of objects in order to determine place and size data for each callout thereof. | 15. The system of claim 12 wherein said processor processes each callout among said plurality of callouts separately from each object among said plurality of objects utilizing said plurality of attributes associated with an object among said plurality of objects in order to determine place and size data for each callout thereof. 16. The system of claim 15 wherein at least one callout among said plurality of callouts comprises a form callout. | 0.508621 |
8,843,554 | 15 | 18 | 15. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: by a client device, identify one or more objects or references to the one or more objects embedded in a structured document displayed to a first user, wherein: the structured document is a markup-language document displayed as a webpage; and the objects originate from one or more sources external to a social-networking system; by the client computing device, access a social graph of the social-networking system to: determine if one or more second users having an association with the first user have accessed or are accessing any of the identified objects; and retrieve, from the social-networking system, one or more social-network data elements comprising social-network profile information provided by one or more of the second users to the social-networking system; and by the client computing device, modify, for at least one of the objects, the structured document displayed as a webpage to the first user to indicate that the object embedded in the structured document and originating from the sources external to the social-networking system has been accessed or is being accessed by one or more of the second users, wherein modifying the structured document comprises displaying, proximal to the object, one or more of the social-networking data elements. | 15. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: by a client device, identify one or more objects or references to the one or more objects embedded in a structured document displayed to a first user, wherein: the structured document is a markup-language document displayed as a webpage; and the objects originate from one or more sources external to a social-networking system; by the client computing device, access a social graph of the social-networking system to: determine if one or more second users having an association with the first user have accessed or are accessing any of the identified objects; and retrieve, from the social-networking system, one or more social-network data elements comprising social-network profile information provided by one or more of the second users to the social-networking system; and by the client computing device, modify, for at least one of the objects, the structured document displayed as a webpage to the first user to indicate that the object embedded in the structured document and originating from the sources external to the social-networking system has been accessed or is being accessed by one or more of the second users, wherein modifying the structured document comprises displaying, proximal to the object, one or more of the social-networking data elements. 18. The media of claim 15 , wherein the software is further operable when executed to: responsive to one or more detected interactions by the first user with one or more of the objects or references in the structured document, generate data indicating one or more edge relationships from the objects or references to the first user; and send the data indicating the edge relationship to the social-networking system. | 0.5 |
9,081,975 | 8 | 10 | 8. A computer system comprising: one or more first computing devices operatively coupled to a first database; one or more second computing devices operatively coupled to a second database; one or more first non-transitory computer-readable media storing instructions which, when executed by the one or more first computing devices, cause the one or more first computing devices to perform the steps of: obtaining a classification to be exported from the first database; wherein the classification has a set of one or more classification markings and a set of one or more origin classifications; generating a new origin classification; wherein the new origin classification includes the set of one or more classification markings; adding the new origin classification to the set of one or more origin classifications to produce a new set of a plurality of origin classifications; wherein the new set of origin classifications includes the new origin classification; exporting the classification as export data; wherein the export data includes the new set of origin classifications; and one or more second non-transitory computer-readable media storing instructions which, when executed by the one or more second computing devices, cause the one or more second computing devices to perform the steps of: obtaining the export data; wherein the export data is obtained as part of other export data that represents an update to an access control list in the first database; obtaining, from the second database, first version information representing a version of the access control list in the second database after an update to the access control list in the second database; obtaining, from the other export data, second version information representing a version of the access control list in the first database after the update to the access control list in the first database; determining that the update to the access control list in the first database happened after the update to the access control list in the second database based on a comparison between the first version information and the second version information; performing a first iteration over the new set of origin classifications; completing the first iteration; in response to completing the first iteration, performing a second iteration over one or more origin classifications in the new set of origin classifications; completing the second iteration upon identifying a first origin classification, in the new set of origin classifications, having a first set of one or more classification markings that, according to a translation map, can be translated to a second set of classification markings based on a classification scheme used by the second database; and importing a classification into the second database, the classification imported into the second database having the second set of classification markings. | 8. A computer system comprising: one or more first computing devices operatively coupled to a first database; one or more second computing devices operatively coupled to a second database; one or more first non-transitory computer-readable media storing instructions which, when executed by the one or more first computing devices, cause the one or more first computing devices to perform the steps of: obtaining a classification to be exported from the first database; wherein the classification has a set of one or more classification markings and a set of one or more origin classifications; generating a new origin classification; wherein the new origin classification includes the set of one or more classification markings; adding the new origin classification to the set of one or more origin classifications to produce a new set of a plurality of origin classifications; wherein the new set of origin classifications includes the new origin classification; exporting the classification as export data; wherein the export data includes the new set of origin classifications; and one or more second non-transitory computer-readable media storing instructions which, when executed by the one or more second computing devices, cause the one or more second computing devices to perform the steps of: obtaining the export data; wherein the export data is obtained as part of other export data that represents an update to an access control list in the first database; obtaining, from the second database, first version information representing a version of the access control list in the second database after an update to the access control list in the second database; obtaining, from the other export data, second version information representing a version of the access control list in the first database after the update to the access control list in the first database; determining that the update to the access control list in the first database happened after the update to the access control list in the second database based on a comparison between the first version information and the second version information; performing a first iteration over the new set of origin classifications; completing the first iteration; in response to completing the first iteration, performing a second iteration over one or more origin classifications in the new set of origin classifications; completing the second iteration upon identifying a first origin classification, in the new set of origin classifications, having a first set of one or more classification markings that, according to a translation map, can be translated to a second set of classification markings based on a classification scheme used by the second database; and importing a classification into the second database, the classification imported into the second database having the second set of classification markings. 10. The system of claim 8 , wherein the step of performing the first iteration includes the step of determining, for each origin classification in the set of origin classifications, whether the origin classification has a classification scheme identifier that matches a classification scheme identifier of the classification scheme used by the second database. | 0.617834 |
9,342,741 | 1 | 5 | 1. A method, comprising: capturing an image of a document using a camera of a mobile device; classifying the image as an image of a financial document, the classifying further comprising: generating a first representation of the image, the first representation being characterized by a reduced resolution; generating a first feature vector based on the first representation; comparing the first feature vector to a plurality of reference feature matrices; and classifying an object depicted in the image as a member of a particular object class based at least in part on the comparing; determine one or more object features of the object based at least in part on the particular object class; performing optical character recognition (OCR) on the image of the financial document; extracting an identifier of the financial document from the image based at least in part on the OCR; associating the image of the financial document with metadata descriptive of one or more of the financial document and financial information relating to the financial document; and storing the image of the financial document and the associated metadata to a memory of the mobile device. | 1. A method, comprising: capturing an image of a document using a camera of a mobile device; classifying the image as an image of a financial document, the classifying further comprising: generating a first representation of the image, the first representation being characterized by a reduced resolution; generating a first feature vector based on the first representation; comparing the first feature vector to a plurality of reference feature matrices; and classifying an object depicted in the image as a member of a particular object class based at least in part on the comparing; determine one or more object features of the object based at least in part on the particular object class; performing optical character recognition (OCR) on the image of the financial document; extracting an identifier of the financial document from the image based at least in part on the OCR; associating the image of the financial document with metadata descriptive of one or more of the financial document and financial information relating to the financial document; and storing the image of the financial document and the associated metadata to a memory of the mobile device. 5. The method as recited in claim 1 , further comprising at least one of: detecting one or more OCR errors based at least in part on textual information from a complementary document; detecting one or more OCR errors in the financial document using one or more predefined business rules; detecting one or more OCR errors based at least in part on textual information from the complementary document and one or more of the predefined business rules; correcting at least one detected OCR error in the financial document using one or more of the predefined business rules; correcting at least one detected OCR error in the financial document using textual information from the complementary document; correcting at least one detected OCR error in the financial document using textual information from the complementary document and one or more of the predefined business rules; normalizing data from a complementary document using at least one of the predefined business rules; normalizing data from the financial document using at least one of the predefined business rules; and normalizing data from the financial document using textual information from the complementary document and at least one of the predefined business rules. | 0.799935 |
8,218,875 | 23 | 24 | 23. The system of claim 15 , wherein the processor is further configured to: calculate a second set of characteristic parameters associated with the at least one of each sub-word and each word associated with each column, wherein the second set of characteristic parameters is one of a line height associated with at least one of each sub-word and each word, a word spacing associated with at least one of each subword and each word, and a line spacing associated with at least one of each sub-word and each word; and group at least two sub-words based on the second set of characteristic parameters to form one of at least one sub-word and at least one word. | 23. The system of claim 15 , wherein the processor is further configured to: calculate a second set of characteristic parameters associated with the at least one of each sub-word and each word associated with each column, wherein the second set of characteristic parameters is one of a line height associated with at least one of each sub-word and each word, a word spacing associated with at least one of each subword and each word, and a line spacing associated with at least one of each sub-word and each word; and group at least two sub-words based on the second set of characteristic parameters to form one of at least one sub-word and at least one word. 24. The system of claim 23 , wherein the processor is further configured to segment the at least one sub word and the at least one word into at least one horizontal line based on at least one of the line height associated with at least one of each sub-word and each word and the line spacing associated with at least one of each sub-word and each word. | 0.5 |
9,361,604 | 12 | 14 | 12. A computer-readable storage device storing instructions which, when executed by a processor, cause the processor to perform operations comprising: performing an analysis of a history of communication sessions over two communication modalities, wherein the analysis considers a semantic meaning of the communication sessions, a temporal relationship among the communication sessions, and a user activity that transitions from a first communication session to a second communication session, wherein the first communication session and the second communication session are part of the communication sessions; identifying a relationship among the communication sessions based on the analysis; prioritizing the communication sessions based on the relationship to yield prioritized communication sessions; generating a unified communication log based on the prioritized communication sessions; outputting the unified communication log to a user; processing feedback from the user to yield processed feedback, wherein the feedback from the user comprises an observation of how the user interacts with the unified communication log; and based on the processed feedback, adaptively adjusting how the communication sessions are prioritized. | 12. A computer-readable storage device storing instructions which, when executed by a processor, cause the processor to perform operations comprising: performing an analysis of a history of communication sessions over two communication modalities, wherein the analysis considers a semantic meaning of the communication sessions, a temporal relationship among the communication sessions, and a user activity that transitions from a first communication session to a second communication session, wherein the first communication session and the second communication session are part of the communication sessions; identifying a relationship among the communication sessions based on the analysis; prioritizing the communication sessions based on the relationship to yield prioritized communication sessions; generating a unified communication log based on the prioritized communication sessions; outputting the unified communication log to a user; processing feedback from the user to yield processed feedback, wherein the feedback from the user comprises an observation of how the user interacts with the unified communication log; and based on the processed feedback, adaptively adjusting how the communication sessions are prioritized. 14. The computer-readable storage device of claim 12 , wherein the unified communication log is used as part of one of a predictive contacts application, a topic analyzer, a conferencing application, and a personal communication assistant. | 0.72779 |
5,560,060 | 10 | 14 | 10. An appliance according to claim 9, wherein an operating cycle comprises at least one pre-wash fill cycle, a main wash fill cycle, a rinse fill cycle, and a final rinse fill cycle. | 10. An appliance according to claim 9, wherein an operating cycle comprises at least one pre-wash fill cycle, a main wash fill cycle, a rinse fill cycle, and a final rinse fill cycle. 14. An appliance according to claim 10, wherein said controller varies the duration of at least one of the fill cycles as a function of liquid temperature. | 0.5 |
9,336,186 | 5 | 6 | 5. The method of claim 1 , wherein determining the set of headline, sentence pairs of the set includes: determining non-conforming headline, sentence pairs from a larger set of headline, sentence pairs; and omitting the non-conforming headline, sentence pairs from the set of headline, sentence pairs. | 5. The method of claim 1 , wherein determining the set of headline, sentence pairs of the set includes: determining non-conforming headline, sentence pairs from a larger set of headline, sentence pairs; and omitting the non-conforming headline, sentence pairs from the set of headline, sentence pairs. 6. The method of claim 5 , wherein determining non-conforming headline, sentence pairs includes determining the non-conforming sentence pairs as those that satisfy one or more of the following conditions: the headline is less than a headline threshold number of terms, the sentence is less than a sentence threshold number of terms, the headline does not include a verb, and the headline includes one or more of a noun, verb, adjective, and adverb whose lemma does not appear in the sentence. | 0.5 |
8,832,104 | 2 | 7 | 2. A method for an advertiser to associate an advertisement published on a plurality of Internet websites on the world wide web as recited in claim 1 further comprising: gathering one or more feeds associated with at least one content from a plurality of content; categorizing the at least one content into at least one general web-based category, the at least one general web-based category belonging to a set of general web-based categories, wherein the at least one content is categorized based on the one or more feeds associated with the at least one content; and translating the set of general web-based categories into the set of pre-defined categories. | 2. A method for an advertiser to associate an advertisement published on a plurality of Internet websites on the world wide web as recited in claim 1 further comprising: gathering one or more feeds associated with at least one content from a plurality of content; categorizing the at least one content into at least one general web-based category, the at least one general web-based category belonging to a set of general web-based categories, wherein the at least one content is categorized based on the one or more feeds associated with the at least one content; and translating the set of general web-based categories into the set of pre-defined categories. 7. A method for an advertiser to associate an advertisement published on a plurality of Internet websites on the world wide web as recited in claim 2 wherein the one or more feeds are obtained in at least one of a RSS 2.0 format and an ATOM 1.0 format. | 0.741803 |
8,161,065 | 1 | 10 | 1. One or more computer storage media having computer-executable instructions embodied thereon, that when executed, cause a computing device to perform a method for facilitating advertisement selection using advertisable units, the method comprising: referencing an entity that is a sequence of two or more words, the entity having one or more substrings comprising a portion of the entity; comparing search data in association with the entity to corresponding search data in association with the one or more substrings of the entity, the search data comprising data that corresponds with search results presented in response to one or more user search queries; based on the comparison of the search data associated with the entity and the one or more substrings of the entity, determining that the entity comprises an advertisable unit that is a sequence of two or more words that functions as a unit for purposes of selecting an advertisement for display; and using the advertisable unit to select an advertisement to be presented to the user. | 1. One or more computer storage media having computer-executable instructions embodied thereon, that when executed, cause a computing device to perform a method for facilitating advertisement selection using advertisable units, the method comprising: referencing an entity that is a sequence of two or more words, the entity having one or more substrings comprising a portion of the entity; comparing search data in association with the entity to corresponding search data in association with the one or more substrings of the entity, the search data comprising data that corresponds with search results presented in response to one or more user search queries; based on the comparison of the search data associated with the entity and the one or more substrings of the entity, determining that the entity comprises an advertisable unit that is a sequence of two or more words that functions as a unit for purposes of selecting an advertisement for display; and using the advertisable unit to select an advertisement to be presented to the user. 10. The one or more computer storage media of claim 1 , wherein the search data in association with the entity comprises a set of search result snippets presented in response to the entity, and the search data in association with the one or more substrings of the entity comprises a set of search result snippets for each of the one or more substrings presented in response to each of the one or more substrings. | 0.612053 |
9,864,768 | 12 | 17 | 12. One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method, the method comprising: accessing social data comprising a plurality of social networking messages from one or more social networking services; collectively analyzing text of the social networking messages to identify an action discussed by users in the text of multiple social networking messages from the plurality of social networking messages; determining to index, in a search engine index, information regarding the action in response to identifying the action in the text of multiple social networking messages; analyzing the social data to identify a plurality of segments; determining the action corresponds to a first segment; identifying at least one URL for the action, each URL corresponding with a webpage at which the action may be performed; and storing, in the search engine index, information regarding the action, the first segment, and the at least one URL for providing deeplinks for search results. | 12. One or more computer storage media storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform a method, the method comprising: accessing social data comprising a plurality of social networking messages from one or more social networking services; collectively analyzing text of the social networking messages to identify an action discussed by users in the text of multiple social networking messages from the plurality of social networking messages; determining to index, in a search engine index, information regarding the action in response to identifying the action in the text of multiple social networking messages; analyzing the social data to identify a plurality of segments; determining the action corresponds to a first segment; identifying at least one URL for the action, each URL corresponding with a webpage at which the action may be performed; and storing, in the search engine index, information regarding the action, the first segment, and the at least one URL for providing deeplinks for search results. 17. The one or more computer storage media of claim 12 , wherein the method further comprises: receiving a search query from an end user at a search engine service; identifying a web page in response to the search query by querying the search engine index based on the search query; identifying deeplinks for the web page, at least one deeplink having been identified from at least a portion of the stored information from analysis of the social data; generating a search result for the web page to include the deeplinks; and providing the search result for presentation to the end user. | 0.5 |
9,649,552 | 57 | 58 | 57. The non-transitory computer readable storage medium as recited in claim 46 , wherein the interactive puzzle includes a plurality of central clue regions, wherein each central clue region is surrounded by three or more mystery number regions, wherein the same pair of mystery number values corresponding to the pair of mystery number regions interposing any pair clue region can appear more than once in the puzzle if the pairs of mystery number regions interposing three or more pair clue regions also form the three or more mystery number regions surrounding a single central clue, in which case the same mystery number value is utilized for all mystery number regions among the pairs of mystery number regions, wherein the central clue region corresponds to a central plus clue representing an arithmetic sum of mystery number values of the mystery number regions surrounding the central clue region or a central times clue representing an arithmetic product of mystery number values of the mystery number regions surrounding the central clue region, wherein the puzzle layout is also initially devoid of central times clues and central plus clues, and wherein the instructions cause the system to at least reveal at least one central plus clue or central times clue within at least one central clue region among the plurality of central clue regions. | 57. The non-transitory computer readable storage medium as recited in claim 46 , wherein the interactive puzzle includes a plurality of central clue regions, wherein each central clue region is surrounded by three or more mystery number regions, wherein the same pair of mystery number values corresponding to the pair of mystery number regions interposing any pair clue region can appear more than once in the puzzle if the pairs of mystery number regions interposing three or more pair clue regions also form the three or more mystery number regions surrounding a single central clue, in which case the same mystery number value is utilized for all mystery number regions among the pairs of mystery number regions, wherein the central clue region corresponds to a central plus clue representing an arithmetic sum of mystery number values of the mystery number regions surrounding the central clue region or a central times clue representing an arithmetic product of mystery number values of the mystery number regions surrounding the central clue region, wherein the puzzle layout is also initially devoid of central times clues and central plus clues, and wherein the instructions cause the system to at least reveal at least one central plus clue or central times clue within at least one central clue region among the plurality of central clue regions. 58. The non-transitory computer readable storage medium as recited in claim 57 , wherein the graphical user interface is operative to provide the user with one or more hints including one or more central plus clues or one or more central times clues for the plurality of central clue regions. | 0.5 |
8,825,888 | 2 | 5 | 2. The method of claim 1 , further comprising: determining a ranking of the candidate sponsored stories for the viewing user; and selecting at least one of the candidate sponsored stories based on the ranking. | 2. The method of claim 1 , further comprising: determining a ranking of the candidate sponsored stories for the viewing user; and selecting at least one of the candidate sponsored stories based on the ranking. 5. The method of claim 2 , wherein the ranking of the candidate sponsored stories for the viewing user is based at least in part on affinities associated with the viewing user. | 0.553299 |
7,680,786 | 6 | 7 | 6. A system for targeting based on user information, the system comprising: at least one processing server, comprising a processor and memory, to identify a set of keywords associated with content information requested by a user over a network, to retrieve advertising information corresponding to said set of keywords to retrieve a user profile information associated with said user, said user profile information comprising a user matrix, said user matrix comprises, for said set of keywords and said corresponding advertising information, click-through-rates associated with said user and a bid price for said advertising information; and at least one advertising server, comprising a processor and memory, coupled to said at least one processing server to filter said advertising information to select advertisements based on said bid price for said advertising information and said corresponding click-through-rate associated with said user identified in said user matrix for said set of keywords and to provide advertising information selected to be displayed for said user in connection with said content information. | 6. A system for targeting based on user information, the system comprising: at least one processing server, comprising a processor and memory, to identify a set of keywords associated with content information requested by a user over a network, to retrieve advertising information corresponding to said set of keywords to retrieve a user profile information associated with said user, said user profile information comprising a user matrix, said user matrix comprises, for said set of keywords and said corresponding advertising information, click-through-rates associated with said user and a bid price for said advertising information; and at least one advertising server, comprising a processor and memory, coupled to said at least one processing server to filter said advertising information to select advertisements based on said bid price for said advertising information and said corresponding click-through-rate associated with said user identified in said user matrix for said set of keywords and to provide advertising information selected to be displayed for said user in connection with said content information. 7. The system according to claim 6 , wherein said at least one processing server further receives a search query from said user and parses said query to retrieve said set of keywords. | 0.732456 |
8,600,797 | 1 | 3 | 1. A method comprising: receiving information about a subset of users of the social networking system, the information describing connections between users of the social networking system and actions taken by users on the social networking system; determining an income distribution model of the subset of users based on the received information; analyzing, by a computer processor, the income distribution model to normalize the received information; defining ranges of income brackets based upon the analysis of the income distribution model; determining, by a computer processor, one or more confidence metrics for the ranges of income brackets for a user of the subset of users, each confidence metric describing a likelihood that the user's income level falls within an associated income bracket; and determining a modifier for providing an advertisement to the user that is targeted to a particular income bracket based on the confidence metric associated with the particular income bracket. | 1. A method comprising: receiving information about a subset of users of the social networking system, the information describing connections between users of the social networking system and actions taken by users on the social networking system; determining an income distribution model of the subset of users based on the received information; analyzing, by a computer processor, the income distribution model to normalize the received information; defining ranges of income brackets based upon the analysis of the income distribution model; determining, by a computer processor, one or more confidence metrics for the ranges of income brackets for a user of the subset of users, each confidence metric describing a likelihood that the user's income level falls within an associated income bracket; and determining a modifier for providing an advertisement to the user that is targeted to a particular income bracket based on the confidence metric associated with the particular income bracket. 3. The method of claim 1 , wherein the received information includes an estimated range of yearly income of each user of the subset of users of the social networking system. | 0.782116 |
8,645,141 | 1 | 2 | 1. A method of performing text to speech conversion on a portable device, said method comprising: predicting, based at least in part on prior user selection of at least one second book and on a first book being newly released and prior to user selection of listening to an audio version of the first book, the first book being different from the second book, the first book for conversion to speech format, by anticipating the first book based on at least one feature of the first book, the at least one feature being new release of the first book; responsive to the predicting and prior to user selection to listen to the audio version of the first book, performing a text to speech conversion on said book to produce converted speech; storing said converted speech into a memory device of said portable device; executing a reader application wherein a user request is received for narration of said book; and during said executing, accessing said converted speech from said memory device and rendering said converted speech on said portable device responsive to said user request. | 1. A method of performing text to speech conversion on a portable device, said method comprising: predicting, based at least in part on prior user selection of at least one second book and on a first book being newly released and prior to user selection of listening to an audio version of the first book, the first book being different from the second book, the first book for conversion to speech format, by anticipating the first book based on at least one feature of the first book, the at least one feature being new release of the first book; responsive to the predicting and prior to user selection to listen to the audio version of the first book, performing a text to speech conversion on said book to produce converted speech; storing said converted speech into a memory device of said portable device; executing a reader application wherein a user request is received for narration of said book; and during said executing, accessing said converted speech from said memory device and rendering said converted speech on said portable device responsive to said user request. 2. The method of claim 1 wherein said at least one feature further comprises identifications of newly added books and wherein said first book is taken from said newly added books. | 0.5 |
10,013,161 | 20 | 29 | 20. A computer-implemented method, comprising: at a device with a display and a touch-sensitive surface: displaying text of an electronic document on the display; displaying an insertion marker at a first position in the text of the electronic document, the text around the first position having a visual appearance; detecting a first input at a location on the touch-sensitive surface, the location on the touch-sensitive surface corresponding to a location on the display where the text of the electronic document is displayed other than the first position in the text and a second position in the text, wherein the first input is an input in a first direction; and in response to detecting the first input: in accordance with a determination that the first input in the first direction at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a first set of one or more predefined conditions: translating the electronic document on the display, and maintaining the insertion marker at the first position in the text; and, in accordance with a determination that the first input in the first direction at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a second set of one or more predefined conditions that is distinct from the first set of one or more predefined conditions, the second set of one or more predefined conditions including a condition that the first input has a speed greater than a predefined threshold velocity: moving the insertion marker in the text from the first position to the second position in the text, and maintaining the visual appearance of the text around the first position in the text. | 20. A computer-implemented method, comprising: at a device with a display and a touch-sensitive surface: displaying text of an electronic document on the display; displaying an insertion marker at a first position in the text of the electronic document, the text around the first position having a visual appearance; detecting a first input at a location on the touch-sensitive surface, the location on the touch-sensitive surface corresponding to a location on the display where the text of the electronic document is displayed other than the first position in the text and a second position in the text, wherein the first input is an input in a first direction; and in response to detecting the first input: in accordance with a determination that the first input in the first direction at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a first set of one or more predefined conditions: translating the electronic document on the display, and maintaining the insertion marker at the first position in the text; and, in accordance with a determination that the first input in the first direction at the location on the touch-sensitive surface that corresponds to the location on the display satisfies a second set of one or more predefined conditions that is distinct from the first set of one or more predefined conditions, the second set of one or more predefined conditions including a condition that the first input has a speed greater than a predefined threshold velocity: moving the insertion marker in the text from the first position to the second position in the text, and maintaining the visual appearance of the text around the first position in the text. 29. The computer-implemented method of claim 20 , wherein the second position in the text is not determined in accordance with a length of the first input. | 0.844689 |
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