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6,055,515 | 22 | 26 | 22. An integrated computer browsing system, for building a multi-inheritance taxonomy of product categories, organizing such categories into hierarchies, comprising: a computer controlled user interface display, means for presenting hierarchies of data having a complex lattice data structure in a tree data structure, browsing means for navigating through said data structure by means of multi-navigation paths, means for using said multi-inheritance taxonomy, means for providing multiple parents in said taxonomy, means for storing the nodes of each of said multiple parents wherein each node is stored at a single location, each of said parents being displayed in said taxonomy a plurality of times, and means for finding information in said taxonomy without expanding said tree by displaying categories of information located beyond currently displayed information, wherein an indicator means is used for finding information in said taxonomy without expanding said tree by displaying categories of information located beyond currently displayed information. | 22. An integrated computer browsing system, for building a multi-inheritance taxonomy of product categories, organizing such categories into hierarchies, comprising: a computer controlled user interface display, means for presenting hierarchies of data having a complex lattice data structure in a tree data structure, browsing means for navigating through said data structure by means of multi-navigation paths, means for using said multi-inheritance taxonomy, means for providing multiple parents in said taxonomy, means for storing the nodes of each of said multiple parents wherein each node is stored at a single location, each of said parents being displayed in said taxonomy a plurality of times, and means for finding information in said taxonomy without expanding said tree by displaying categories of information located beyond currently displayed information, wherein an indicator means is used for finding information in said taxonomy without expanding said tree by displaying categories of information located beyond currently displayed information. 26. The system of claim 22 wherein said taxonomy of information in said system exhibits configurable node labels that show a description or other characteristics of said node by merely clicking on said node. | 0.706799 |
7,680,749 | 17 | 20 | 17. The method of claim 16 wherein learning conditional variants comprises determining if at least one of an explicit and implicit condition applies to a particular conditional variant of a model. | 17. The method of claim 16 wherein learning conditional variants comprises determining if at least one of an explicit and implicit condition applies to a particular conditional variant of a model. 20. The method of claim 17 wherein for implicit conditions, learning conditional variants further comprises: for each driving session, forming a mini-model for a target attribute by statistically merging attribute data computed for that driving session; identifying pairs of like mini-models using a similarity metric; and forming a conditional variant model based on attribute data from pairs of like mini-models. | 0.661765 |
8,589,160 | 7 | 11 | 7. A method for providing a dictation interface, comprising: actuating a target application, the target application configured to receive input from a user, the target application further configured to provide a target application interface for providing the input as text for display; actuating a dictation application, the dictation application configured to receive an audio dictation from the user, the dictation application configured to convert the audio dictation into text for display, the dictation application further providing a dictation application interface for providing the audio dictation as text for display, wherein the dictation application interface comprises a full overlay mode option, a partial overlay mode option, and a windowed mode option, wherein in response to selection of the full overlay mode option, the dictation application interface is automatically sized and positioned over the target application interface to fully cover a text area of the target application interface to appear as if the dictation application interface is part of the target application interface such that movement of the target application interface will cause the dictation application interface to move as well and, if the target application interface is moved, minimized, maximized, or resized, the dictation application interface will adjust to match the target application interface, wherein in response to selection of the partial overlay mode option, the dictation application interface is automatically sized and positioned to cover a predetermined portion of the text area to appear as if the dictation application interface is part of the target application interface, wherein in response to selection of the windowed mode option, the dictation application interface is sized and positioned to appear separate from the target application interface; receiving the audio dictation from the user; converting the audio dictation into text; providing the text in the dictation application interface; and in response to receiving a first user command to complete, automatically copying the text from the dictation application interface and inserting the text into the target application interface. | 7. A method for providing a dictation interface, comprising: actuating a target application, the target application configured to receive input from a user, the target application further configured to provide a target application interface for providing the input as text for display; actuating a dictation application, the dictation application configured to receive an audio dictation from the user, the dictation application configured to convert the audio dictation into text for display, the dictation application further providing a dictation application interface for providing the audio dictation as text for display, wherein the dictation application interface comprises a full overlay mode option, a partial overlay mode option, and a windowed mode option, wherein in response to selection of the full overlay mode option, the dictation application interface is automatically sized and positioned over the target application interface to fully cover a text area of the target application interface to appear as if the dictation application interface is part of the target application interface such that movement of the target application interface will cause the dictation application interface to move as well and, if the target application interface is moved, minimized, maximized, or resized, the dictation application interface will adjust to match the target application interface, wherein in response to selection of the partial overlay mode option, the dictation application interface is automatically sized and positioned to cover a predetermined portion of the text area to appear as if the dictation application interface is part of the target application interface, wherein in response to selection of the windowed mode option, the dictation application interface is sized and positioned to appear separate from the target application interface; receiving the audio dictation from the user; converting the audio dictation into text; providing the text in the dictation application interface; and in response to receiving a first user command to complete, automatically copying the text from the dictation application interface and inserting the text into the target application interface. 11. The method of claim 7 , further comprising providing a medical dictation interface for providing a user option to include a text version of the audio dictation into a medical record. | 0.836842 |
10,083,690 | 7 | 9 | 7. The method of claim 1 , further comprising: identifying a second substring from the textual representation that corresponds to a second attribute of the primary domain; and parsing the identified second substring to determine a second secondary domain representing a user intent for the second substring, wherein performing the task flow is further based on the second secondary domain. | 7. The method of claim 1 , further comprising: identifying a second substring from the textual representation that corresponds to a second attribute of the primary domain; and parsing the identified second substring to determine a second secondary domain representing a user intent for the second substring, wherein performing the task flow is further based on the second secondary domain. 9. The method of claim 7 , wherein identifying the second sub string from the textual representation comprises: identifying in the textual representation one or more predetermined words corresponding to the second attribute; and identifying the second substring based on the one or more predetermined words corresponding to the second attribute. | 0.565491 |
7,523,076 | 21 | 33 | 21. A computer-readable storage medium containing computer executable instructions for causing a computer to select a profile model for use in examining a structure formed on a semiconductor wafer using optical metrology, comprising instructions for: a) obtaining an initial profile model having a set of profile parameters that characterize the structure to be examined; b) training a machine learning system using the initial profile model; c) generating a simulated diffraction signal for an optimized profile model using the trained machine learning system, wherein the optimized profile model has a set of profile parameters with the same or fewer profile parameters than the initial profile model; d) modifying the optimized profile model by eliminating at least one profile parameter or fixing to a value at least one profile parameter and iterating steps c) and d) using the modified optimized profile model and the same trained machine learning system until one or more termination criteria are met. | 21. A computer-readable storage medium containing computer executable instructions for causing a computer to select a profile model for use in examining a structure formed on a semiconductor wafer using optical metrology, comprising instructions for: a) obtaining an initial profile model having a set of profile parameters that characterize the structure to be examined; b) training a machine learning system using the initial profile model; c) generating a simulated diffraction signal for an optimized profile model using the trained machine learning system, wherein the optimized profile model has a set of profile parameters with the same or fewer profile parameters than the initial profile model; d) modifying the optimized profile model by eliminating at least one profile parameter or fixing to a value at least one profile parameter and iterating steps c) and d) using the modified optimized profile model and the same trained machine learning system until one or more termination criteria are met. 33. The computer-readable storage medium of claim 21 , further comprising: if one or more termination criteria are met, selecting at least one profile parameter of the optimized profile model; and setting the at least one profile parameter to a determined value. | 0.710177 |
9,501,566 | 1 | 7 | 1. A computer-implemented method comprising: receiving, from an input device, an input phrase defining an initial scope of a concept search; identifying, by a processing device, a plurality of concept terms related to the input phrase in view of an analysis of documents in a data set; determining, by the processing device, a relevance score for each of the plurality of concept terms; determining, by the processing device, a set of concept terms from the plurality of concept terms that have a relevance score that exceeds a threshold value; displaying the set of concept terms at a first section of a graphical user interface (GUI); displaying the input phrase at a second section of the GUI; receiving, from the input device, a selection of a concept term from the set of concept terms; displaying, in the second section of the GUI, a visual representation of a relationship between the selected concept term and the input phrase in response to the selection of the concept term; identifying, by the processing device, one or more of the documents related to the selection of the concept term and the input phrase; displaying, in a third section of the GUI, a count of the one or more documents related to the selection of the concept term and the input phrase; receiving, from the input device, a selection of an additional concept term from the set of concept terms; identifying, by the processing device, one or more of the documents related to the selected concept term, the input phrase, and the additional concept term; updating the visual representation to indicate a relationship between the selected concept term, the additional concept term, and the input phrase; and displaying the one or more documents to a user. | 1. A computer-implemented method comprising: receiving, from an input device, an input phrase defining an initial scope of a concept search; identifying, by a processing device, a plurality of concept terms related to the input phrase in view of an analysis of documents in a data set; determining, by the processing device, a relevance score for each of the plurality of concept terms; determining, by the processing device, a set of concept terms from the plurality of concept terms that have a relevance score that exceeds a threshold value; displaying the set of concept terms at a first section of a graphical user interface (GUI); displaying the input phrase at a second section of the GUI; receiving, from the input device, a selection of a concept term from the set of concept terms; displaying, in the second section of the GUI, a visual representation of a relationship between the selected concept term and the input phrase in response to the selection of the concept term; identifying, by the processing device, one or more of the documents related to the selection of the concept term and the input phrase; displaying, in a third section of the GUI, a count of the one or more documents related to the selection of the concept term and the input phrase; receiving, from the input device, a selection of an additional concept term from the set of concept terms; identifying, by the processing device, one or more of the documents related to the selected concept term, the input phrase, and the additional concept term; updating the visual representation to indicate a relationship between the selected concept term, the additional concept term, and the input phrase; and displaying the one or more documents to a user. 7. The method of claim 1 , further comprising: receiving an input for search criteria, the search criteria comprising at least one of a date range, custodian, location of data, data type, language, tag in folder, or property; and executing a search of the data set to locate the one or more documents based on the search criteria, the input phrase, and the selection of the concept term. | 0.5 |
8,843,466 | 24 | 30 | 24. The computer storage medium of claim 16 , the operations further comprising: generating one or more attribute suggestions for the search query, each attribute suggestion identifying an additional attribute associated with first entity type. | 24. The computer storage medium of claim 16 , the operations further comprising: generating one or more attribute suggestions for the search query, each attribute suggestion identifying an additional attribute associated with first entity type. 30. The computer storage medium of claim 24 , the operations further comprising: in response to a user input indicating that a first attribute suggestion does not match the first search query, generating an additional search query that includes the first search query, the first attribute suggestion, and an operator that indicates that resources including the first attribute suggestion should not be included in search results generated for the additional search query. | 0.5 |
9,619,457 | 1 | 2 | 1. A computer-implemented method, comprising: obtaining, at a server having one or more processors, a training corpus including pairs of (i) documents and (ii) abstracts, each abstract representing a summary of a corresponding document; obtaining, at the server, part-of-speech (POS) tags and dependency parses for each abstract and each corresponding document; identifying, at the server, a set of entity mentions in each abstract and each corresponding document based on their respective POS tags and dependency parses; clustering, at the server, the sets of entity mentions referring to a same underlying entity to obtain clusters for each document and each corresponding abstract; aligning, at the server, specific abstract entity mentions to corresponding document entity mentions to obtain a set of aligned abstract and document entities; labeling, at the server, the set of aligned entities as salient and unaligned entities as non-salient to generate a labeled corpus; training, at the server, features of a classifier using the labeled corpus to obtain a trained classifier and generating, at the server, a model including the trained classifier, wherein the features include count features indicative of at least one of entity mentions and entity head word mentions, and wherein the training and generating further comprises bucketing, by the server, the count features by applying a function to the count features, wherein the function is:
ƒ( x )=round(log( k ( x+ 1))), where x represents a particular count feature and k controls the number of buckets; applying, at the server, the model to a collection of documents to obtain the salience estimates, the collection of documents representing a web browsing history of a user of a computing device; utilizing, at the server, the salience estimates to obtain a prediction of an advertisement that should be displayed to the user; and outputting, from the server and to the computing device via a network, the prediction, wherein receipt of the prediction causes the computing device to display the advertisement to the user. | 1. A computer-implemented method, comprising: obtaining, at a server having one or more processors, a training corpus including pairs of (i) documents and (ii) abstracts, each abstract representing a summary of a corresponding document; obtaining, at the server, part-of-speech (POS) tags and dependency parses for each abstract and each corresponding document; identifying, at the server, a set of entity mentions in each abstract and each corresponding document based on their respective POS tags and dependency parses; clustering, at the server, the sets of entity mentions referring to a same underlying entity to obtain clusters for each document and each corresponding abstract; aligning, at the server, specific abstract entity mentions to corresponding document entity mentions to obtain a set of aligned abstract and document entities; labeling, at the server, the set of aligned entities as salient and unaligned entities as non-salient to generate a labeled corpus; training, at the server, features of a classifier using the labeled corpus to obtain a trained classifier and generating, at the server, a model including the trained classifier, wherein the features include count features indicative of at least one of entity mentions and entity head word mentions, and wherein the training and generating further comprises bucketing, by the server, the count features by applying a function to the count features, wherein the function is:
ƒ( x )=round(log( k ( x+ 1))), where x represents a particular count feature and k controls the number of buckets; applying, at the server, the model to a collection of documents to obtain the salience estimates, the collection of documents representing a web browsing history of a user of a computing device; utilizing, at the server, the salience estimates to obtain a prediction of an advertisement that should be displayed to the user; and outputting, from the server and to the computing device via a network, the prediction, wherein receipt of the prediction causes the computing device to display the advertisement to the user. 2. The computer-implemented method of claim 1 , wherein the identification of specific abstract entities and specific document entities is limited to those having at least one proper name mention, and wherein aligning a specific abstract entity to a specific document entity requires that one of the abstract entity mentions shares a syntactic head token with one of the document entity mentions. | 0.5 |
7,904,876 | 33 | 35 | 33. In a network having a server executing a graphical modeling environment and a client device in communication with the server, a method comprising: obtaining, at the server, a graphical block diagram model in a graphical modeling environment, the graphical block diagram model representing a dynamic system, the graphical block diagram model including at least one block that represents a portion of the system and at least one line representing a signal provided as an input or an output of the block; converting the graphical block diagram model to an interactive graphics language format; receiving, at the client device from the server, a converted graphical block diagram model in the interactive graphics language format; displaying a view of the graphical block diagram model in the interactive graphics language format outside of the graphical modeling environment; and allowing modifying the displayed view without modifying the graphical block diagram model. | 33. In a network having a server executing a graphical modeling environment and a client device in communication with the server, a method comprising: obtaining, at the server, a graphical block diagram model in a graphical modeling environment, the graphical block diagram model representing a dynamic system, the graphical block diagram model including at least one block that represents a portion of the system and at least one line representing a signal provided as an input or an output of the block; converting the graphical block diagram model to an interactive graphics language format; receiving, at the client device from the server, a converted graphical block diagram model in the interactive graphics language format; displaying a view of the graphical block diagram model in the interactive graphics language format outside of the graphical modeling environment; and allowing modifying the displayed view without modifying the graphical block diagram model. 35. The method of claim 33 wherein the interactive graphics language format comprises Scalable Vector Graphics (SVG). | 0.553435 |
8,139,900 | 2 | 10 | 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. 10. The method of claim 2 , wherein specifying the content for display includes identifying additional images that contain the selected one or more objects. | 0.672269 |
9,613,267 | 11 | 15 | 11. An image processing system comprising: a processor configured to receive a digital version of a document, the processor configured to execute instructions to perform a method of extracting structured label and value pairwise data associated with the digital version of the document, the method comprising: a) performing a layout analysis of the digital version of the document to generate one or more layout structures associated with the document, each layout structure including a plurality of structural elements vertically or horizontally aligned where each structural element is defined as a typographical box including one or more lines of textual elements associated with the digital version of the document; b) processing the one or more lines of textual elements to identify and tag textual elements associated with label and value pairwise data; c) processing the one or more layout structures and associated tagged textual elements to generate one or more respective label:value sequences of tagged textual elements representative of a respective layout structure; and d) extracting label and value pairwise data from the one or more label:value sequences of tagged elements, wherein step c) generates the one or more respective label:value sequences of tagged textual element using a sequence-based method to hierarchically segment a sequence of elements associated with the generated one or more layout structures associated with the digital version of the document; and wherein the sequence-based method includes: generating a set of n-grams from the sequence of elements, an n-gram including an ordered sequence of n features provided by a sequence of n named elements; electing sequential n-grams from the set of n-grams, the sequential n-grams defined as similar contiguous n-grams; selecting a most frequent sequential n-gram from the elected sequential n-grams; and generating a new sequence of the elements by matching the selected most frequent sequential n-gram against the sequence of elements associated with the document, replacing matched elements of the sequence of elements with a respective node, and associating the matched elements of the sequence of elements as children of the respective node. | 11. An image processing system comprising: a processor configured to receive a digital version of a document, the processor configured to execute instructions to perform a method of extracting structured label and value pairwise data associated with the digital version of the document, the method comprising: a) performing a layout analysis of the digital version of the document to generate one or more layout structures associated with the document, each layout structure including a plurality of structural elements vertically or horizontally aligned where each structural element is defined as a typographical box including one or more lines of textual elements associated with the digital version of the document; b) processing the one or more lines of textual elements to identify and tag textual elements associated with label and value pairwise data; c) processing the one or more layout structures and associated tagged textual elements to generate one or more respective label:value sequences of tagged textual elements representative of a respective layout structure; and d) extracting label and value pairwise data from the one or more label:value sequences of tagged elements, wherein step c) generates the one or more respective label:value sequences of tagged textual element using a sequence-based method to hierarchically segment a sequence of elements associated with the generated one or more layout structures associated with the digital version of the document; and wherein the sequence-based method includes: generating a set of n-grams from the sequence of elements, an n-gram including an ordered sequence of n features provided by a sequence of n named elements; electing sequential n-grams from the set of n-grams, the sequential n-grams defined as similar contiguous n-grams; selecting a most frequent sequential n-gram from the elected sequential n-grams; and generating a new sequence of the elements by matching the selected most frequent sequential n-gram against the sequence of elements associated with the document, replacing matched elements of the sequence of elements with a respective node, and associating the matched elements of the sequence of elements as children of the respective node. 15. The image processing system according to claim 11 , wherein a predefined list of terms is used to identify and tag textual elements associated with label data. | 0.765805 |
8,031,201 | 13 | 20 | 13. A method for signifying information objects comprising the steps: obtaining a plurality of information objects; providing the plurality of information objects to an indexer for signification; providing the indexer with a deliberately ambiguated signifier prompt; wherein the deliberately ambiguated signifier prompt is a multi-dimensional signifier prompt defining a multi-dimensional continuum having a plurality of labeled points specifying attributes, wherein the indexer signifies each of the information objects by indicating a position on the deliberately ambiguated signifier prompt to represent the information object; and storing in a computer system each of the information objects with the indexer's response to the deliberately ambiguated signifier prompt. | 13. A method for signifying information objects comprising the steps: obtaining a plurality of information objects; providing the plurality of information objects to an indexer for signification; providing the indexer with a deliberately ambiguated signifier prompt; wherein the deliberately ambiguated signifier prompt is a multi-dimensional signifier prompt defining a multi-dimensional continuum having a plurality of labeled points specifying attributes, wherein the indexer signifies each of the information objects by indicating a position on the deliberately ambiguated signifier prompt to represent the information object; and storing in a computer system each of the information objects with the indexer's response to the deliberately ambiguated signifier prompt. 20. The method for signifying information objects of claim 13 , further comprising the steps of providing the indexer with a signifier prompt about the indexer, and storing the indexer's response to the signifier prompt about the indexer with each of the information objects. | 0.681713 |
9,934,430 | 1 | 3 | 1. A non-transitory computer-readable media having instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: training a multi-script handwriting recognition model based on spatially-derived features of a multi-script training corpus, the multi-script training corpus including respective handwriting samples corresponding to characters of one or more scripts; receiving a handwriting input from a user which includes characters from a plurality of scripts; and in response to receiving the handwriting input, providing real-time handwriting recognition output for the handwriting input using the multi-script handwriting recognition model that has been trained on the spatially-derived features of the multi-script training corpus, wherein the real-time handwriting recognition output includes characters from a plurality of scripts. | 1. A non-transitory computer-readable media having instructions stored thereon, the instructions, when executed by one or more processors, cause the processors to perform operations comprising: training a multi-script handwriting recognition model based on spatially-derived features of a multi-script training corpus, the multi-script training corpus including respective handwriting samples corresponding to characters of one or more scripts; receiving a handwriting input from a user which includes characters from a plurality of scripts; and in response to receiving the handwriting input, providing real-time handwriting recognition output for the handwriting input using the multi-script handwriting recognition model that has been trained on the spatially-derived features of the multi-script training corpus, wherein the real-time handwriting recognition output includes characters from a plurality of scripts. 3. The media of claim 1 , wherein the training of the multi-script handwriting recognition model is independent of temporal information associated with respective strokes in the handwriting samples. | 0.8213 |
9,104,969 | 17 | 18 | 17. A non-transitory computer-readable medium for use in a computer to utilize semantic analysis to set a processing level of a processor processing measurements of affective response; the computer comprising a processor, and the non-transitory computer-readable medium comprising: program code for receiving a first indication derived from an evaluation comprising semantic analysis of a first segment of content; wherein the first segment comprises data representing text; program code for determining that the first indication indicates that a first value related to a prediction of emotional response to the first segment does not reach a first predetermined threshold, and for configuring a processor to operate at a first processing level to process measurements of affective response of a user to the first segment; program code for receiving a second indication derived from an evaluation comprising semantic analysis of a second segment of content; wherein the second segment comprises data representing text; and program code for determining that the second indication indicates that a second value related to a prediction of emotional response to the second segment reaches a second predetermined threshold, and for configuring the processor to operate at a second processing level to process measurements of affective response of the user to the second segment; wherein, per volume unit of measurement data, the number of computation cycles utilized by the processor to process, at the first processing level, the measurements of the affective response of the user to the first segment, is at least 50% lower than the number of computation cycles utilized by the processor to process, at the second processing level, the measurements of the affective response of the user to the second segment. | 17. A non-transitory computer-readable medium for use in a computer to utilize semantic analysis to set a processing level of a processor processing measurements of affective response; the computer comprising a processor, and the non-transitory computer-readable medium comprising: program code for receiving a first indication derived from an evaluation comprising semantic analysis of a first segment of content; wherein the first segment comprises data representing text; program code for determining that the first indication indicates that a first value related to a prediction of emotional response to the first segment does not reach a first predetermined threshold, and for configuring a processor to operate at a first processing level to process measurements of affective response of a user to the first segment; program code for receiving a second indication derived from an evaluation comprising semantic analysis of a second segment of content; wherein the second segment comprises data representing text; and program code for determining that the second indication indicates that a second value related to a prediction of emotional response to the second segment reaches a second predetermined threshold, and for configuring the processor to operate at a second processing level to process measurements of affective response of the user to the second segment; wherein, per volume unit of measurement data, the number of computation cycles utilized by the processor to process, at the first processing level, the measurements of the affective response of the user to the first segment, is at least 50% lower than the number of computation cycles utilized by the processor to process, at the second processing level, the measurements of the affective response of the user to the second segment. 18. The non-transitory computer-readable medium of claim 17 , further comprising program code for receiving the second segment from an interactive computer game that provides context information about the second segment that may be utilized for computing the second indication. | 0.55178 |
7,991,786 | 1 | 3 | 1. A method for query processing by using a streaming application programming interface (API) for a mark-up language data stream of a textual document, said method comprising: producing, by said streaming API for a mark-up language data stream, an ordered index of all textual elements corresponding to their order in said mark-up language data stream, said ordered index comprising tag identifiers and end positions corresponding to each of said all textual elements; scanning, by a processor, all tag identifiers of said ordered index to determine if there exists a match between a query and any of said tag identifiers; parsing a matched textual element, if a tag identifier, corresponding to said matched textual element, matches said query; and skipping an unmatched textual element for parsing, if a tag identifier, corresponding to said unmatched textual element, does not match said query. | 1. A method for query processing by using a streaming application programming interface (API) for a mark-up language data stream of a textual document, said method comprising: producing, by said streaming API for a mark-up language data stream, an ordered index of all textual elements corresponding to their order in said mark-up language data stream, said ordered index comprising tag identifiers and end positions corresponding to each of said all textual elements; scanning, by a processor, all tag identifiers of said ordered index to determine if there exists a match between a query and any of said tag identifiers; parsing a matched textual element, if a tag identifier, corresponding to said matched textual element, matches said query; and skipping an unmatched textual element for parsing, if a tag identifier, corresponding to said unmatched textual element, does not match said query. 3. The method of claim 1 , all the limitations of which are incorporated herein by reference, further comprising storing a parsed matched textual element in a buffer. | 0.74772 |
8,000,970 | 4 | 5 | 4. The method of claim 3 , further comprising: retrieving said VXML data from said specified location; and parsing said VXML data to convert said VXML data to an intermediate format. | 4. The method of claim 3 , further comprising: retrieving said VXML data from said specified location; and parsing said VXML data to convert said VXML data to an intermediate format. 5. The method of claim 4 , further comprising: receiving said parsed VXML data; and providing said parsed VXML data to said associated service processor. | 0.5 |
8,612,847 | 11 | 12 | 11. The system of claim 7 , wherein at least one of the plurality of rendering engines is a reentrant rendering engine. | 11. The system of claim 7 , wherein at least one of the plurality of rendering engines is a reentrant rendering engine. 12. The system of claim 11 , wherein the first rendering engine identifies itself as configured to render embedded content of the second type; and wherein the first rendering engine invokes itself through the first rendering engine's common interface. | 0.5 |
9,043,746 | 1 | 3 | 1. A method comprising: representing an event processing application as an event processing network, being a graph with event processing agents as nodes; generating a finite state machine based on the event processing network, wherein the finite state machine is an over-approximation of the event processing application; expressing stateful rules and policies that are associated with the event processing application using temporal logic, to yield a temporal representation of the event processing application; combining the temporal representation and the finite state machine into a model; generating a statement associated with at least one user-selected verification-related property of the event processing application, wherein the statement is generated using the temporal representation; and applying the statement to the model, to yield an indication for: (i) a correctness of the statement or (ii) a counter example, respectively, wherein at least one of: the representing, the expressing, the combining the generating, and the applying is carried out by at least one processor, wherein the at least one verification-related property of the event processing application is a mutual exclusivity of two of the event processing agents within the graph, and wherein the statement indicates that the two or more of the event processing agents are mutual exclusive such that for any given input, one of the two event processing agents produces a different output from another one of the two event processing agents, at a same point of time, and wherein the counter example is compilable into a sequence of events that contradicts the statement. | 1. A method comprising: representing an event processing application as an event processing network, being a graph with event processing agents as nodes; generating a finite state machine based on the event processing network, wherein the finite state machine is an over-approximation of the event processing application; expressing stateful rules and policies that are associated with the event processing application using temporal logic, to yield a temporal representation of the event processing application; combining the temporal representation and the finite state machine into a model; generating a statement associated with at least one user-selected verification-related property of the event processing application, wherein the statement is generated using the temporal representation; and applying the statement to the model, to yield an indication for: (i) a correctness of the statement or (ii) a counter example, respectively, wherein at least one of: the representing, the expressing, the combining the generating, and the applying is carried out by at least one processor, wherein the at least one verification-related property of the event processing application is a mutual exclusivity of two of the event processing agents within the graph, and wherein the statement indicates that the two or more of the event processing agents are mutual exclusive such that for any given input, one of the two event processing agents produces a different output from another one of the two event processing agents, at a same point of time, and wherein the counter example is compilable into a sequence of events that contradicts the statement. 3. The method according to claim 1 , wherein the modeling is carried out using a language capable of describing a transition system and wherein the expressing is carried out using a language capable of expressing a sequential behavior of the finite state machine. | 0.743665 |
9,980,753 | 1 | 5 | 1. A bone anchor assembly for securing a longitudinal connecting member to a bone, the bone anchor assembly comprising: a receiver having a through bore around a central vertical axis, the receiver including a lower body with a bottom opening and an internal cavity communicating with an upper portion having a pair of opposed arms defining a first channel therebetween opening onto a top thereof, the first channel having opposed inner surfaces and a transverse axis perpendicular to the central vertical axis, the first channel sized and shaped for receiving a portion of the longitudinal connecting member, the arms having a discontinuous helically wound guide and advancement structure thereon, and the receiver including interior opposed recesses having downwardly-facing top surfaces located entirely below the helically wound guide and advancement structure; a bone attachment structure having a body and an upper head portion having a substantially spherical surface above a hemisphere thereof, the body extending through the receiver bottom opening and pivotal with respect to the receiver; and an insert having a body with upright arms forming a second channel therebetween, the second channel being alienable with the receiver transverse axis to receive the portion of the longitudinal connecting member, the upright arms having uppermost top surfaces, the insert body further including a central through-and-through tool receiving opening and oppositely-directed opposed radial extending portions with outer surfaces in the direction of the receiver transverse axis engageable with the receiver first channel inner surfaces to inhibit rotation between the receiver and the insert, the opposed radial extending portions having top surfaces that extend radially outward and underneath a most bottom surface of the portion of the longitudinal connecting member positioned within the receiver first channel, wherein when the uppermost top surfaces of the upright arms of the insert are snapped under and engaging the downwardly-facing top surfaces of the receiver opposed recesses, the bone attachment structure has a non-floppy relationship with respect to the receiver, and the insert is prevented from moving back up within the receiver prior to the longitudinal connecting member being positioned within the receiver and the insert first and second channels and locked by a closure structure. | 1. A bone anchor assembly for securing a longitudinal connecting member to a bone, the bone anchor assembly comprising: a receiver having a through bore around a central vertical axis, the receiver including a lower body with a bottom opening and an internal cavity communicating with an upper portion having a pair of opposed arms defining a first channel therebetween opening onto a top thereof, the first channel having opposed inner surfaces and a transverse axis perpendicular to the central vertical axis, the first channel sized and shaped for receiving a portion of the longitudinal connecting member, the arms having a discontinuous helically wound guide and advancement structure thereon, and the receiver including interior opposed recesses having downwardly-facing top surfaces located entirely below the helically wound guide and advancement structure; a bone attachment structure having a body and an upper head portion having a substantially spherical surface above a hemisphere thereof, the body extending through the receiver bottom opening and pivotal with respect to the receiver; and an insert having a body with upright arms forming a second channel therebetween, the second channel being alienable with the receiver transverse axis to receive the portion of the longitudinal connecting member, the upright arms having uppermost top surfaces, the insert body further including a central through-and-through tool receiving opening and oppositely-directed opposed radial extending portions with outer surfaces in the direction of the receiver transverse axis engageable with the receiver first channel inner surfaces to inhibit rotation between the receiver and the insert, the opposed radial extending portions having top surfaces that extend radially outward and underneath a most bottom surface of the portion of the longitudinal connecting member positioned within the receiver first channel, wherein when the uppermost top surfaces of the upright arms of the insert are snapped under and engaging the downwardly-facing top surfaces of the receiver opposed recesses, the bone attachment structure has a non-floppy relationship with respect to the receiver, and the insert is prevented from moving back up within the receiver prior to the longitudinal connecting member being positioned within the receiver and the insert first and second channels and locked by a closure structure. 5. The bone anchor assembly of claim 1 , wherein the bone attachment structure is positioned within the receiver prior to the insert uppermost top surfaces being snapped under the downwardly-facing top surfaces of the receiver opposed recesses. | 0.709524 |
8,745,148 | 11 | 18 | 11. A method of providing user communications, the method comprising: providing over a network an application software program for installation on a mobile computing device associated with a user; providing, by a computer system comprising a computing device and a network interface, a communication service to a web document of the user, wherein the communication service facilitates communications from a visitor to the user web document to the user; receiving, from a first visitor at the computer system, a communication request to communicate with the user via a communication interface displayed in association with the user web document, the communication interface including a text entry field configured to receive a text message from the first visitor for the user; causing, at least in part by the communication service, at least a first system to transmit a text message entered by the first visitor into the text entry field to the user mobile computing device, the user mobile computing device having the application software program installed thereon, without the first visitor providing, and without revealing to the first visitor, a mobile communication device phone address of the user; determining by the computer system if the user has a first account; and if the user does not have a first account, requesting that the user provide at least a first type of registration information prior to enabling the application software program to be installed on the user mobile computing device. | 11. A method of providing user communications, the method comprising: providing over a network an application software program for installation on a mobile computing device associated with a user; providing, by a computer system comprising a computing device and a network interface, a communication service to a web document of the user, wherein the communication service facilitates communications from a visitor to the user web document to the user; receiving, from a first visitor at the computer system, a communication request to communicate with the user via a communication interface displayed in association with the user web document, the communication interface including a text entry field configured to receive a text message from the first visitor for the user; causing, at least in part by the communication service, at least a first system to transmit a text message entered by the first visitor into the text entry field to the user mobile computing device, the user mobile computing device having the application software program installed thereon, without the first visitor providing, and without revealing to the first visitor, a mobile communication device phone address of the user; determining by the computer system if the user has a first account; and if the user does not have a first account, requesting that the user provide at least a first type of registration information prior to enabling the application software program to be installed on the user mobile computing device. 18. The method as defined in claim 11 , wherein the application software program is provided via a software download to the mobile communication device of the user. | 0.818182 |
9,489,386 | 1 | 3 | 1. A computer-implemented method comprising: importing a set of data into a data structure in a memory, the data structure having a plurality of rows and a plurality of columns, wherein the set of data includes a first column and a second column; importing metadata for the set of data into the memory; determining, by a rules engine, one or more operations on particular columns of the set of data according to a set of rules, wherein a rule of the set of rules includes a condition defined in terms of the metadata, the rule including comparing a metadata attribute of the first column with a metadata attribute of the second column; inputting the determined operations into a data analysis tool; performing the determined operations by the data analysis tool; presenting results of the operations on a display device as an additional column to the plurality of columns; determining, in the rules engine, a count for one or more rules in the set of rules, each count having an associated rule in the one or more rules, wherein each count is based on a number of times the rules engine has generated a column using the associated rule; ranking the one or more rules based on their associated counts; and displaying the one or more rules to a user in an order consistent with their ranking. | 1. A computer-implemented method comprising: importing a set of data into a data structure in a memory, the data structure having a plurality of rows and a plurality of columns, wherein the set of data includes a first column and a second column; importing metadata for the set of data into the memory; determining, by a rules engine, one or more operations on particular columns of the set of data according to a set of rules, wherein a rule of the set of rules includes a condition defined in terms of the metadata, the rule including comparing a metadata attribute of the first column with a metadata attribute of the second column; inputting the determined operations into a data analysis tool; performing the determined operations by the data analysis tool; presenting results of the operations on a display device as an additional column to the plurality of columns; determining, in the rules engine, a count for one or more rules in the set of rules, each count having an associated rule in the one or more rules, wherein each count is based on a number of times the rules engine has generated a column using the associated rule; ranking the one or more rules based on their associated counts; and displaying the one or more rules to a user in an order consistent with their ranking. 3. The method of claim 1 , wherein the metadata includes a dimension of the first column and a dimension of the second column, and the rule further includes comparing the respective dimensions of the first and second columns. | 0.722906 |
8,595,175 | 1 | 8 | 1. A computer system comprising: a logical processor; a memory in operable communication with the logical processor; an object-relational mapping session residing in the memory; a mapped persistence ignorant object residing in the memory and having at least one state as part of the session; a fluent interface residing in the memory; and a developer code containing an API Pattern and residing in the memory, which upon execution of the developer code manipulates the mapped persistence ignorant object using calls to the fluent interface in the API Pattern. | 1. A computer system comprising: a logical processor; a memory in operable communication with the logical processor; an object-relational mapping session residing in the memory; a mapped persistence ignorant object residing in the memory and having at least one state as part of the session; a fluent interface residing in the memory; and a developer code containing an API Pattern and residing in the memory, which upon execution of the developer code manipulates the mapped persistence ignorant object using calls to the fluent interface in the API Pattern. 8. The system of claim 1 , wherein the API Pattern is a dictionary API Pattern, namely, an API Pattern which specifies at least one of the following actions on the object: setting a current value of the object from a dictionary, setting an original value of the object from a dictionary. | 0.612162 |
7,536,634 | 21 | 22 | 21. An apparatus for use in converting data from a first form to a second form, comprising: an input port for receiving an input including a first content string to be converted; and a processor operative for analyzing said content string to determine an applied schema for converting at least a portion of said content string, wherein said schema is applied to less than the whole of a subject matter area including said content string and includes one or more conversion rules for use in converting data from said first form to said second form; said processor further being operative for using said schema to convert said content string from said first form to said second form and to provide a corresponding output. | 21. An apparatus for use in converting data from a first form to a second form, comprising: an input port for receiving an input including a first content string to be converted; and a processor operative for analyzing said content string to determine an applied schema for converting at least a portion of said content string, wherein said schema is applied to less than the whole of a subject matter area including said content string and includes one or more conversion rules for use in converting data from said first form to said second form; said processor further being operative for using said schema to convert said content string from said first form to said second form and to provide a corresponding output. 22. An apparatus as set forth in claim 21 , wherein said processor is further operative for accessing one or more stored public schema, each said public schema including conversion rules generally applicable to said subject matter area independent of any entity or group of entities associated with said input, that establishes a structure for understanding at least a portion of the subject matter area. | 0.5 |
8,793,715 | 1 | 2 | 1. A method comprising: dividing a media instance into a first component and a second component, the first component and second component concurrently presented; correlating first physiological response data from a first subject exposed to media with the first component and the second component to form first correlated data and second correlated data; processing, using a processor, the first correlated data to identify a first transition representative of a first change; processing, using the processor, the second correlated data to identify a second transition representative of a second change; parsing the first component into a first plurality of events based on the first transition; parsing the second component into a second plurality of events based on the second transition; identifying a first event of the first plurality of events as a first candidate for modification based on the first change; and identifying a second event of the second plurality of events as a second candidate for modification based on the second change. | 1. A method comprising: dividing a media instance into a first component and a second component, the first component and second component concurrently presented; correlating first physiological response data from a first subject exposed to media with the first component and the second component to form first correlated data and second correlated data; processing, using a processor, the first correlated data to identify a first transition representative of a first change; processing, using the processor, the second correlated data to identify a second transition representative of a second change; parsing the first component into a first plurality of events based on the first transition; parsing the second component into a second plurality of events based on the second transition; identifying a first event of the first plurality of events as a first candidate for modification based on the first change; and identifying a second event of the second plurality of events as a second candidate for modification based on the second change. 2. The method of claim 1 , wherein the first component and the second component comprise at least one of voiceover, music, branding, dialogue, text, or a visual component, the first component being different from the second component. | 0.880855 |
9,800,618 | 1 | 2 | 1. A system, comprising: storage including at least one privacy preference relative to at least one user identity; an editor, responsive to user selections that indicate at least one preference-related input that relates to the at least one user identity, the editor to: generate at least one privacy preference based on the user selections wherein the user identity is represented by at least one information card used in an online transaction with a relying party; and determine a privacy preference for each category; an engine, operatively connected to the storage, the engine configured to perform an evaluation using the at least one privacy preference of any category that references at least one required attribute; and a host computer to evaluate the at least one privacy preference against a privacy policy associated with the online transaction and obtained from the relying party; wherein the host computer provides the at least one information card that represents the user identity to the relying party. | 1. A system, comprising: storage including at least one privacy preference relative to at least one user identity; an editor, responsive to user selections that indicate at least one preference-related input that relates to the at least one user identity, the editor to: generate at least one privacy preference based on the user selections wherein the user identity is represented by at least one information card used in an online transaction with a relying party; and determine a privacy preference for each category; an engine, operatively connected to the storage, the engine configured to perform an evaluation using the at least one privacy preference of any category that references at least one required attribute; and a host computer to evaluate the at least one privacy preference against a privacy policy associated with the online transaction and obtained from the relying party; wherein the host computer provides the at least one information card that represents the user identity to the relying party. 2. The system of claim 1 , wherein the editor enables execution of a process to define at least one category, and populate each category with a respective group of user identity attributes. | 0.671875 |
8,615,527 | 21 | 22 | 21. A data processing system, comprising: a computer processor and memory; a data repository; an application suitable for querying the data repository; and a data repository abstraction generator configured to generate, by operation of the computer processor, a data repository abstraction component describing, and used to access, data in the data repository based on usage information collected by monitoring and parsing queries issued against the data repository by the application; wherein the data repository abstraction generator is configured to generate a plurality of logical field specifications for a limited subset of fields of the data repository accessed by the application, as indicated by the monitored queries; whereby the data repository abstraction is customized on the basis of how the application queries the data repository. | 21. A data processing system, comprising: a computer processor and memory; a data repository; an application suitable for querying the data repository; and a data repository abstraction generator configured to generate, by operation of the computer processor, a data repository abstraction component describing, and used to access, data in the data repository based on usage information collected by monitoring and parsing queries issued against the data repository by the application; wherein the data repository abstraction generator is configured to generate a plurality of logical field specifications for a limited subset of fields of the data repository accessed by the application, as indicated by the monitored queries; whereby the data repository abstraction is customized on the basis of how the application queries the data repository. 22. The data processing system of claim 21 , wherein the data repository abstraction generator is configured to determine a logical name, to include in one or more of the generated logical field specifications, based on reference to one or more corresponding fields in the data repository in the monitored queries. | 0.503165 |
7,917,502 | 1 | 10 | 1. A method for updating database statistics for use in generating query execution plans, comprising: receiving a first query for a table in a database; determining whether valid and updated statistics for compiling the first query are available from a first store comprising a first entry with statistics associated with the table in the database; if valid and updated statistics for compiling the first query are not available from the first store, obtaining updated statistics from a further store comprising statistics associated with the table in the database; and storing the obtained updated statistics associated with the table in the database in the first store as a second entry, thereby storing multiple entries for the statistics associated with the same table in the database, wherein the first store is a metadata cache and the further store is a temporary cache. | 1. A method for updating database statistics for use in generating query execution plans, comprising: receiving a first query for a table in a database; determining whether valid and updated statistics for compiling the first query are available from a first store comprising a first entry with statistics associated with the table in the database; if valid and updated statistics for compiling the first query are not available from the first store, obtaining updated statistics from a further store comprising statistics associated with the table in the database; and storing the obtained updated statistics associated with the table in the database in the first store as a second entry, thereby storing multiple entries for the statistics associated with the same table in the database, wherein the first store is a metadata cache and the further store is a temporary cache. 10. The method of claim 1 , wherein, only one of the multiple entries is valid, while all other of the multiple entries are invalid. | 0.903084 |
9,836,765 | 3 | 5 | 3. The method of claim 1 , wherein the generating the item models based on the user preference data of the plurality of users and the item information of the plurality of items comprises generating the item models using a combination of content-based features associated with the plurality of items and collaborative-based features associated with the user preference data of the plurality of users. | 3. The method of claim 1 , wherein the generating the item models based on the user preference data of the plurality of users and the item information of the plurality of items comprises generating the item models using a combination of content-based features associated with the plurality of items and collaborative-based features associated with the user preference data of the plurality of users. 5. The method of claim 3 , further comprising: extracting the collaborative-based features from the user preference data of the plurality of users and the item information of the plurality of items. | 0.705357 |
7,822,762 | 9 | 10 | 9. A computer-implemented method of performing an entity-based computer search, wherein the method is performed by a processor that executes at least the following acts: gathering data associated with an entity, the data corresponding to a goal of the entity, a mission of the entity, or a purpose of the entity, wherein the entity comprises a group of individuals, and wherein the data associated with the entity corresponds to least the group of individuals; training a search model with the data associated with the entity; receiving a search query from an individual in the entity; employing the search model to modify the search query into a modified search query as a function of the data associated with the entity, wherein the search query being modified into the modified search query is transparent to a user inputting the search query; retrieving entity-based search results in accordance with the modified search query; providing the entity-based search results to the individual in the entity; re-ranking the entity-based search results uses the trained search model prior to display to the user; organizing a subset of the entity-based search results; and performing a utility-based analysis in connection with displaying the subset of the entity-based search results to the user, wherein the utility-based analysis factors a probability of cost of displaying a result to the user versus a probability of benefit of displaying the result to the user. | 9. A computer-implemented method of performing an entity-based computer search, wherein the method is performed by a processor that executes at least the following acts: gathering data associated with an entity, the data corresponding to a goal of the entity, a mission of the entity, or a purpose of the entity, wherein the entity comprises a group of individuals, and wherein the data associated with the entity corresponds to least the group of individuals; training a search model with the data associated with the entity; receiving a search query from an individual in the entity; employing the search model to modify the search query into a modified search query as a function of the data associated with the entity, wherein the search query being modified into the modified search query is transparent to a user inputting the search query; retrieving entity-based search results in accordance with the modified search query; providing the entity-based search results to the individual in the entity; re-ranking the entity-based search results uses the trained search model prior to display to the user; organizing a subset of the entity-based search results; and performing a utility-based analysis in connection with displaying the subset of the entity-based search results to the user, wherein the utility-based analysis factors a probability of cost of displaying a result to the user versus a probability of benefit of displaying the result to the user. 10. The method of claim 9 , further comprising: establishing an entity context; and modifying the entity-based search query based on, at least in part, the entity context, wherein the entity context includes a role of a searching member of the entity, structure of the entity, a location of the searching member of the entity, product information associated with the entity, and customer relations management (CRM) data associated with the entity. | 0.5 |
8,661,093 | 1 | 9 | 1. A server system including one or more computers, comprising: a database having content criteria and supplemental multi-media content in a variety of different personalities; and one or more processors configured to: evaluate multi-media content accessible to a user's computer using the content criteria and to identify supplemental multi-media content of the database based on the evaluating; trigger from the evaluation to generate identified supplemental multi-media content to the user's computer in a personality corresponding to a current user for display; and transmit selected supplemental multi-media content in the corresponding personality to the user's computer. | 1. A server system including one or more computers, comprising: a database having content criteria and supplemental multi-media content in a variety of different personalities; and one or more processors configured to: evaluate multi-media content accessible to a user's computer using the content criteria and to identify supplemental multi-media content of the database based on the evaluating; trigger from the evaluation to generate identified supplemental multi-media content to the user's computer in a personality corresponding to a current user for display; and transmit selected supplemental multi-media content in the corresponding personality to the user's computer. 9. The server system of claim 1 , wherein the processors are further configured to analyze the content criteria of a particular user profile to develop a personality profile for a user and wherein the identified supplemental multi-media content is generated in a personality based on the developed personality profile. | 0.5 |
7,644,091 | 9 | 12 | 9. A computer-implemented system for handling Health Level Seven (HL7) electronic medical data, comprising: means for receiving HL7 electronic medical data; wherein the HL7 electronic medical data includes data segments, wherein a segment has a three character name and a pre-defined format of specific fields; an HL7 message processor configured to execute in a computer system and to create an electronic indexing medical record based upon the received HL7 electronic medical data; said HL7 message processor creating a medically-related document containing data from the received HL7 electronic medical data; wherein the indexing medical record and the medically-related document are provided to a document management system; wherein the document management system is configured to execute in the computer system and to store the medically-related document and to use the provided indexing medical record in order to index the medically-related document. | 9. A computer-implemented system for handling Health Level Seven (HL7) electronic medical data, comprising: means for receiving HL7 electronic medical data; wherein the HL7 electronic medical data includes data segments, wherein a segment has a three character name and a pre-defined format of specific fields; an HL7 message processor configured to execute in a computer system and to create an electronic indexing medical record based upon the received HL7 electronic medical data; said HL7 message processor creating a medically-related document containing data from the received HL7 electronic medical data; wherein the indexing medical record and the medically-related document are provided to a document management system; wherein the document management system is configured to execute in the computer system and to store the medically-related document and to use the provided indexing medical record in order to index the medically-related document. 12. The system of claim 9 , wherein the HL7 electronic medical data includes hospital patient demographic data. | 0.764831 |
9,569,080 | 3 | 9 | 3. The method of claim 1 , where the language control is a slider control indicating the two or more languages for presenting information on the map interface, and wherein a user can manipulate the slider control to select from the two or more languages for presenting information on the map interface. | 3. The method of claim 1 , where the language control is a slider control indicating the two or more languages for presenting information on the map interface, and wherein a user can manipulate the slider control to select from the two or more languages for presenting information on the map interface. 9. The method of claim 3 , wherein the two or more languages includes the default language and at least one local language, and wherein an amount of information that is presented on the map interface in the default language and an amount of information that is presented in the at least one local language are varied based on a selected position of the language control. | 0.5 |
8,041,694 | 26 | 35 | 26. A system comprising: one or more computers, the one or more computers implementing: a dataset tool to identify a comparison vector x having processed features and non-processed features, a first set of vectors, each vector in the first set of vectors having processed features and non-processed features corresponding to the processed features and non-processed features of the comparison vector x, and a candidate vector y from the first set of vectors; and a similarity tool to determine a similarity threshold, and a maximum similarity between the non-processed features of x and the non-processed features of y; wherein the dataset tool removes the vector y from the first set of vectors if the maximum similarity does not meet the similarity threshold. | 26. A system comprising: one or more computers, the one or more computers implementing: a dataset tool to identify a comparison vector x having processed features and non-processed features, a first set of vectors, each vector in the first set of vectors having processed features and non-processed features corresponding to the processed features and non-processed features of the comparison vector x, and a candidate vector y from the first set of vectors; and a similarity tool to determine a similarity threshold, and a maximum similarity between the non-processed features of x and the non-processed features of y; wherein the dataset tool removes the vector y from the first set of vectors if the maximum similarity does not meet the similarity threshold. 35. The system of claim 26 in which each vector in the set of vectors represents a corresponding user in a community, and each feature of each vector represents the corresponding user's click-behavior with regard to a content item. | 0.840028 |
7,667,862 | 6 | 8 | 6. A system for interactively viewing raster images using scalable vector graphics (SVG), comprising: a receiver for (i) receiving an SVG document from a server computer, the SVG document including a reference to a raster image within the SVG document, the reference indicating a rectangular portion, a display width and height, and an IP address for a server computer, (ii) receiving a modified SVG document from the server computer, modified according to a different portion, and (iii) receiving a portion of raster image data from the server computer; a transmitter for (i) requesting from the server computer a first portion of raster image data corresponding to the rectangular portion, display width and display height, the first portion of raster image data being derived from the raster image, and (ii) requesting a different portion of the raster image data; and an SVG renderer operatively coupled with said receiver and said transmitter for rendering an SVG document, comprising a raster image processor for displaying a portion of raster image data. | 6. A system for interactively viewing raster images using scalable vector graphics (SVG), comprising: a receiver for (i) receiving an SVG document from a server computer, the SVG document including a reference to a raster image within the SVG document, the reference indicating a rectangular portion, a display width and height, and an IP address for a server computer, (ii) receiving a modified SVG document from the server computer, modified according to a different portion, and (iii) receiving a portion of raster image data from the server computer; a transmitter for (i) requesting from the server computer a first portion of raster image data corresponding to the rectangular portion, display width and display height, the first portion of raster image data being derived from the raster image, and (ii) requesting a different portion of the raster image data; and an SVG renderer operatively coupled with said receiver and said transmitter for rendering an SVG document, comprising a raster image processor for displaying a portion of raster image data. 8. The system of claim 6 wherein the modified SVG document has a modified rectangular portion within the reference to the raster image. | 0.5 |
8,832,048 | 1 | 9 | 1. A method of managing information comprising: providing an organization having an information management system comprising one or more rules and policy abstractions stored at a policy server to manage information of the organization, wherein a rule comprises an expression having a policy abstraction; within the organization, providing a user logged onto a client device and a confidential document managed by the information management system; receiving at the information management system a profile of the client device, wherein the profile is based on the user and the client device; at the information management system, determining a subset of the one or more rules of the policy server relevant to the profile, wherein a rule is relevant to the profile when the client device is capable of supporting a syntax format of the rule; determining a first rule of the subset of the one or more rules in a first syntax format is not supported by the client device; converting the first rule into a second syntax format, wherein the client device supports the second syntax format but not the first syntax format; storing the subset of the one or more rules of the policy server on the client device including the first translated rule; and when the user attempts to perform an operation on the confidential document, evaluating the one or more rules at the client device, without evaluating rules stored at the policy server, to determine whether to store information regarding the attempted operation in a storage location, wherein based on a first context expression of a first rule, approving the attempted operation will occur only during a particular time period, and based on a second context expression of a second rule, approving the attempted operation will occur only when the user is in a particular location. | 1. A method of managing information comprising: providing an organization having an information management system comprising one or more rules and policy abstractions stored at a policy server to manage information of the organization, wherein a rule comprises an expression having a policy abstraction; within the organization, providing a user logged onto a client device and a confidential document managed by the information management system; receiving at the information management system a profile of the client device, wherein the profile is based on the user and the client device; at the information management system, determining a subset of the one or more rules of the policy server relevant to the profile, wherein a rule is relevant to the profile when the client device is capable of supporting a syntax format of the rule; determining a first rule of the subset of the one or more rules in a first syntax format is not supported by the client device; converting the first rule into a second syntax format, wherein the client device supports the second syntax format but not the first syntax format; storing the subset of the one or more rules of the policy server on the client device including the first translated rule; and when the user attempts to perform an operation on the confidential document, evaluating the one or more rules at the client device, without evaluating rules stored at the policy server, to determine whether to store information regarding the attempted operation in a storage location, wherein based on a first context expression of a first rule, approving the attempted operation will occur only during a particular time period, and based on a second context expression of a second rule, approving the attempted operation will occur only when the user is in a particular location. 9. The method of claim 1 wherein when the user attempts to perform an operation on the confidential document, the one or more rules further determine whether to send a notification to at least one recipient within the organization regarding the attempted operation on the confidential document. | 0.711765 |
7,523,390 | 1 | 6 | 1. A method, at least partially implemented on a computer, comprising: displaying a first free floating field, a second free floating field, and text from a document written in eXtensible Markup Language (XML); determining a type of content already in the first free floating field; displaying a first user interface if the first type of content determined to already be in the first free floating field is a formula and displaying a second user interface if the first type of content determined to already be in the free floating field is text, wherein the first user interface is distinct from the second user interface, the first user interface being associated with formula entry and the second user interface being associated with text entry; receiving first additional content entered into the first free floating field by a user; interpreting the first additional content based upon the first type of content already in the first free floating field, as determined; automatically recalculating any formulas within the document, as needed, upon receipt of the first additional content; determining that a second type of content already in the second free floating field is a different type than the first type; displaying the other of the first user interface and the second user interface not displayed in the second-mentioned act of displaying; receiving second additional content entered into the second free floating field by the user; interpreting the second additional content based on the second type of content already in the second free floating field, as determined; and automatically recalculating any formulas within the document, as needed, upon receipt of the second additional content. | 1. A method, at least partially implemented on a computer, comprising: displaying a first free floating field, a second free floating field, and text from a document written in eXtensible Markup Language (XML); determining a type of content already in the first free floating field; displaying a first user interface if the first type of content determined to already be in the first free floating field is a formula and displaying a second user interface if the first type of content determined to already be in the free floating field is text, wherein the first user interface is distinct from the second user interface, the first user interface being associated with formula entry and the second user interface being associated with text entry; receiving first additional content entered into the first free floating field by a user; interpreting the first additional content based upon the first type of content already in the first free floating field, as determined; automatically recalculating any formulas within the document, as needed, upon receipt of the first additional content; determining that a second type of content already in the second free floating field is a different type than the first type; displaying the other of the first user interface and the second user interface not displayed in the second-mentioned act of displaying; receiving second additional content entered into the second free floating field by the user; interpreting the second additional content based on the second type of content already in the second free floating field, as determined; and automatically recalculating any formulas within the document, as needed, upon receipt of the second additional content. 6. The method of claim 1 , wherein a first formula is in the first free floating field, the method further comprising: displaying a third free floating field in the document; enabling the user to enter a second formula into the third free floating field, the second formula referencing the first free floating field; and upon modification of one of the first and third free floating fields, automatically recalculating the other of the first and third free floating fields. | 0.5 |
8,433,123 | 56 | 60 | 56. A method of depositing U.S. currency bills and checks associated with a deposit transaction, comprising: receiving U.S. currency bills and checks associated with the deposit transaction in a document processing system; imaging the received U.S. currency bills and checks in the document processing system to generate first records associated with the deposit transaction, each of the first records including respective identifying information and respective image data that is reproducible as a visually readable image of at least a portion of a respective one of the U.S. currency bills or checks associated with the deposit transaction; transmitting the first records associated with the deposit transaction from the document processing system to a network; transmitting deposit information associated with the deposit transaction from the document processing system to the network, the deposit information being associated with the transmitted first records, the deposit information including a total declared deposit amount; receiving in a financial institution system the transmitted first records associated with the deposit transaction and the transmitted deposit information associated with the deposit transaction; in response to receiving the transmitted records and deposit information, determining that one of the received first records is a suspect record based on a comparison of the respective identifying information included in the one of the received first records with suspect information in a database; and provisionally crediting a customer financial account maintained within the financial institution system an amount, the amount being a percentage of the total declared deposit amount minus a value associated with the determined suspect record. | 56. A method of depositing U.S. currency bills and checks associated with a deposit transaction, comprising: receiving U.S. currency bills and checks associated with the deposit transaction in a document processing system; imaging the received U.S. currency bills and checks in the document processing system to generate first records associated with the deposit transaction, each of the first records including respective identifying information and respective image data that is reproducible as a visually readable image of at least a portion of a respective one of the U.S. currency bills or checks associated with the deposit transaction; transmitting the first records associated with the deposit transaction from the document processing system to a network; transmitting deposit information associated with the deposit transaction from the document processing system to the network, the deposit information being associated with the transmitted first records, the deposit information including a total declared deposit amount; receiving in a financial institution system the transmitted first records associated with the deposit transaction and the transmitted deposit information associated with the deposit transaction; in response to receiving the transmitted records and deposit information, determining that one of the received first records is a suspect record based on a comparison of the respective identifying information included in the one of the received first records with suspect information in a database; and provisionally crediting a customer financial account maintained within the financial institution system an amount, the amount being a percentage of the total declared deposit amount minus a value associated with the determined suspect record. 60. The method of claim 56 , wherein the first records and the deposit information are transmitted together. | 0.790698 |
8,340,974 | 11 | 12 | 11. The audio data processing system of claim 10 , further comprising a processing portion operable to retrieve the portion of the at least one of content data and advertisement data based on the determined characteristics of the first user. | 11. The audio data processing system of claim 10 , further comprising a processing portion operable to retrieve the portion of the at least one of content data and advertisement data based on the determined characteristics of the first user. 12. The audio data processing system of claim 11 , wherein the processing portion is operable to retrieve the portion of the at least one of content data and advertisement data based further on the determined interests of the first user. | 0.5 |
10,042,543 | 8 | 13 | 8. An apparatus comprising: a processor; a memory storing machine readable code executable by the processor, the machine readable code comprising: an input reception module configured to detect a gesture from a single touch input item on a touch-enabled display of an input device, the gesture input comprising a swipe gesture; a characteristic determination module configured to determine a location on the touch-enabled display where the swipe gesture begins and a direction of the swipe gesture; a subdividing module configured to dynamically subdivide a view area of the touch-enabled display into one or more segments based on the location and the direction of the swipe gesture, wherein each segment represents a particular word length, and wherein visible boundaries representing each segment are displayed on the touch-enabled display; a word presentation module configured to present a list of one or more words having word lengths determined in response to detecting the swipe gesture move into a first segment of the one or more segments; and an update module configured to dynamically update the presented list of one or more words with one or more different words having different word lengths indicated by the second segment in response to detecting the swipe gesture move into a second segment of the one or more segments and in response to a period of time elapsing after modification of the swipe gesture. | 8. An apparatus comprising: a processor; a memory storing machine readable code executable by the processor, the machine readable code comprising: an input reception module configured to detect a gesture from a single touch input item on a touch-enabled display of an input device, the gesture input comprising a swipe gesture; a characteristic determination module configured to determine a location on the touch-enabled display where the swipe gesture begins and a direction of the swipe gesture; a subdividing module configured to dynamically subdivide a view area of the touch-enabled display into one or more segments based on the location and the direction of the swipe gesture, wherein each segment represents a particular word length, and wherein visible boundaries representing each segment are displayed on the touch-enabled display; a word presentation module configured to present a list of one or more words having word lengths determined in response to detecting the swipe gesture move into a first segment of the one or more segments; and an update module configured to dynamically update the presented list of one or more words with one or more different words having different word lengths indicated by the second segment in response to detecting the swipe gesture move into a second segment of the one or more segments and in response to a period of time elapsing after modification of the swipe gesture. 13. The apparatus of claim 8 , further comprising a tracking module configured to track a usage frequency of one or more words having a particular length, the list of one or more words being sorted based on a usage frequency distribution such that more-frequently used words are listed before less-frequently used words. | 0.59596 |
8,954,317 | 1 | 2 | 1. A method of processing a text message from a mobile station at a third party provider via text messaging, the method comprising: receiving the text message from the mobile station via a receiver of a computing device, wherein the text message comprises a transaction request from a user; parsing the message, via a processor of the computing device, and performing a natural language interpretation of the message to identify at least one emotion related keyword or phrase included in the message; processing the parsed message, via the processor, to determine the user's requested objective from the transaction request; assigning an emotion status to the message, via the processor, based on the identified at least one emotion related keyword or phrase by identifying a frequency of occurrences of the at least one emotion related keyword or phrase and associating the identified at least one keyword or phrase with the emotion status if a threshold predefined set number of occurrences of the at least one emotion related keyword or phrase is identified; generating a response to the message based on the user's requested objective and the assigned emotion status, wherein the response comprises a pre-defined return text message acknowledging the user's requested objective corresponding to the transaction and an incentive based on the assigned emotional status; if a confidence of the generated response exceeds a threshold sending the response to the mobile station, via a transmitter of the computing device, and otherwise sending the response to a live agent for correction, sending the corrected response to the mobile station and storing the corrected response as the predefined return text message. | 1. A method of processing a text message from a mobile station at a third party provider via text messaging, the method comprising: receiving the text message from the mobile station via a receiver of a computing device, wherein the text message comprises a transaction request from a user; parsing the message, via a processor of the computing device, and performing a natural language interpretation of the message to identify at least one emotion related keyword or phrase included in the message; processing the parsed message, via the processor, to determine the user's requested objective from the transaction request; assigning an emotion status to the message, via the processor, based on the identified at least one emotion related keyword or phrase by identifying a frequency of occurrences of the at least one emotion related keyword or phrase and associating the identified at least one keyword or phrase with the emotion status if a threshold predefined set number of occurrences of the at least one emotion related keyword or phrase is identified; generating a response to the message based on the user's requested objective and the assigned emotion status, wherein the response comprises a pre-defined return text message acknowledging the user's requested objective corresponding to the transaction and an incentive based on the assigned emotional status; if a confidence of the generated response exceeds a threshold sending the response to the mobile station, via a transmitter of the computing device, and otherwise sending the response to a live agent for correction, sending the corrected response to the mobile station and storing the corrected response as the predefined return text message. 2. The method of claim 1 , further comprising: confirming the user's requested objective has been fulfilled in the response. | 0.680412 |
8,319,648 | 9 | 12 | 9. The method of claim 8 , wherein the obtaining the physiologic information comprises monitoring at least one of an implantable or an external physiologic sensor. | 9. The method of claim 8 , wherein the obtaining the physiologic information comprises monitoring at least one of an implantable or an external physiologic sensor. 12. The method of claim 9 , comprising: querying a user for at least some of the physiologic information, wherein the query includes at least one of whether the patient has experienced shortness of breath, abnormal fatigue, abnormal pain, abnormal swelling, a chronic cough, a decreased appetite, or a need for an extra pillow when sleeping; and receiving a user response including at least some of the physiologic information. | 0.5 |
9,471,641 | 11 | 12 | 11. The computer-readable medium of claim 10 , where the instructions further comprise: one or more instructions that, when executed by the processor, cause the processor to: receive selection of a particular ranked identifier from the one or more particular ranked identifiers, and connect a particular block, associated with the particular ranked identifier, to the block. | 11. The computer-readable medium of claim 10 , where the instructions further comprise: one or more instructions that, when executed by the processor, cause the processor to: receive selection of a particular ranked identifier from the one or more particular ranked identifiers, and connect a particular block, associated with the particular ranked identifier, to the block. 12. The computer-readable medium of claim 11 , where the instructions further comprise: one or more instructions that, when executed by the processor, cause the processor to: provide for display, via the user interface, the model with the block connected to the particular block. | 0.5 |
9,779,368 | 9 | 11 | 9. A non-transitory, computer-readable medium storing computer-readable instructions executable by a computer and operable to: receive a plurality of core data foundations representing database resources and comprising database tables and operations; define a derived data foundation comprising a first plurality of links to the plurality of core data foundations and representing a hierarchical inheritance relationship of the plurality of core data foundations; receive a plurality of core business layers representing business concepts and comprising data objects associated to the database tables and the operations; define a derived business layer comprising a second plurality of links to the plurality of core business layers; generate a universe by compiling the derived business layer on top of the derived data foundation, wherein the universe exposes only data objects that are permitted to be published and that are associated with the derived business layer or inherited by the derived business layer from the derived data foundation; and process the universe using a computer-executable model checking tool for evaluating an integrity of the universe by determining whether one or more links of the first plurality of links or the second plurality of links is broken, such that determining that the one or more links are broken triggers a notification configured to enable a repair of the one or more links. | 9. A non-transitory, computer-readable medium storing computer-readable instructions executable by a computer and operable to: receive a plurality of core data foundations representing database resources and comprising database tables and operations; define a derived data foundation comprising a first plurality of links to the plurality of core data foundations and representing a hierarchical inheritance relationship of the plurality of core data foundations; receive a plurality of core business layers representing business concepts and comprising data objects associated to the database tables and the operations; define a derived business layer comprising a second plurality of links to the plurality of core business layers; generate a universe by compiling the derived business layer on top of the derived data foundation, wherein the universe exposes only data objects that are permitted to be published and that are associated with the derived business layer or inherited by the derived business layer from the derived data foundation; and process the universe using a computer-executable model checking tool for evaluating an integrity of the universe by determining whether one or more links of the first plurality of links or the second plurality of links is broken, such that determining that the one or more links are broken triggers a notification configured to enable a repair of the one or more links. 11. The non-transitory, computer-readable medium of claim 9 , further comprising instructions operable to customize the derived data foundation by at least one of selecting only necessary core database tables, adding JOINS between tables from different core data foundations, adding contexts, adding calculated columns, or adding a list of values or parameters. | 0.5 |
7,970,773 | 1 | 2 | 1. A computer system for determining a set of variation-phrases from a collection of documents, the system comprising: a processor; and a memory storing instructions, wherein the said instructions are executable by the processor to: access a document corpus comprising a plurality of documents; for each document in the document corpus: identify a set of similar documents from the document corpus having at least some tokens in common; align the text of the documents of the identified set of similar documents to compare and identify potential variation-phrase pairs, each identified potential variation-phrase pair comprising two phrases from said identified set that are non-synonymous descriptions of a common item type offered for sale; wherein aligning the text of the documents of the identified set of similar documents to identify potential variation-phrase pairs comprises: aligning the text of a first document from said set of similar documents with the text of a second document from said set of similar documents; and identifying non-matching tokens that resulted from aligning the first and second documents from said set of similar documents as potential variation-phrase pairs; and add the identified potential variation-phrase pairs to a variation-phrase set, at least some of the phrases in the variation-phrase set being non-synonymous with the other phrases in that set; filter the potential variation-phrase pairs to remove from the variation-phrase set potential variation-phrase pairs that do not satisfy one or more predetermined criteria; and store the resulting variation-phrase set in a data store. | 1. A computer system for determining a set of variation-phrases from a collection of documents, the system comprising: a processor; and a memory storing instructions, wherein the said instructions are executable by the processor to: access a document corpus comprising a plurality of documents; for each document in the document corpus: identify a set of similar documents from the document corpus having at least some tokens in common; align the text of the documents of the identified set of similar documents to compare and identify potential variation-phrase pairs, each identified potential variation-phrase pair comprising two phrases from said identified set that are non-synonymous descriptions of a common item type offered for sale; wherein aligning the text of the documents of the identified set of similar documents to identify potential variation-phrase pairs comprises: aligning the text of a first document from said set of similar documents with the text of a second document from said set of similar documents; and identifying non-matching tokens that resulted from aligning the first and second documents from said set of similar documents as potential variation-phrase pairs; and add the identified potential variation-phrase pairs to a variation-phrase set, at least some of the phrases in the variation-phrase set being non-synonymous with the other phrases in that set; filter the potential variation-phrase pairs to remove from the variation-phrase set potential variation-phrase pairs that do not satisfy one or more predetermined criteria; and store the resulting variation-phrase set in a data store. 2. The computer system of claim 1 , wherein identifying a set of similar documents form the document corpus comprises: generating a set of bigrams for a first selected document; and identifying a set of documents from the document corpus that include at least one of the bigrams of the set of bigrams. | 0.59434 |
8,886,636 | 18 | 19 | 18. The system of claim 17 , wherein the classes further comprise miscellaneous, or another category, and wherein the query characteristics comprise one or more of query frequency, query length, and query topic. | 18. The system of claim 17 , wherein the classes further comprise miscellaneous, or another category, and wherein the query characteristics comprise one or more of query frequency, query length, and query topic. 19. The system of claim 18 , wherein the query topic comprises a query class predicted by an automatic query classifier with respect to a commercial taxonomy. | 0.5 |
7,561,780 | 74 | 81 | 74. An optical disc player for reproducing text subtitle streams downloaded from an external source, the optical disc player comprising: an audio decoder configured to decode audio streams recorded on the optical disc into audio data; a video decoder configured to decode video streams recorded on the optical disc into video image data; a text subtitle decoder configured to decode a text subtitle stream recorded on the optical disc into text subtitle image data; and an image superimposition unit configured to superimpose the decoded text subtitle image data with the decoded video image data, wherein the text subtitle decoder comprises: a text subtitle processor configured to parse the text subtitle stream into composition information, rendering information, and text data for at least one region, the text data including one or more text strings for each region; a text renderer configured to render the text strings into graphic data for each region according to the rendering information; and a presentation controller configured to compose the rendered graphic data according to the composition information. | 74. An optical disc player for reproducing text subtitle streams downloaded from an external source, the optical disc player comprising: an audio decoder configured to decode audio streams recorded on the optical disc into audio data; a video decoder configured to decode video streams recorded on the optical disc into video image data; a text subtitle decoder configured to decode a text subtitle stream recorded on the optical disc into text subtitle image data; and an image superimposition unit configured to superimpose the decoded text subtitle image data with the decoded video image data, wherein the text subtitle decoder comprises: a text subtitle processor configured to parse the text subtitle stream into composition information, rendering information, and text data for at least one region, the text data including one or more text strings for each region; a text renderer configured to render the text strings into graphic data for each region according to the rendering information; and a presentation controller configured to compose the rendered graphic data according to the composition information. 81. The optical disc player of claim 74 , wherein the text subtitle processor is configured to parse the text subtitle stream into the composition information including at least a portion of region style information specifying one region style defined by a style segment. | 0.607246 |
9,967,380 | 42 | 45 | 42. A communication system comprising: a hard of hearing user's captioned device, the captioned device including a display screen and a processor, the captioned device configured to: establish communication with a hard of hearing user's wireless phone device that is independent of the hard of hearing user's captioned device; receive a hearing user's voice signal originating at a hearing user's phone device from the hard of hearing user's phone device; establish a first communication link with a relay; route the hearing user's voice signal via the first communication link to the relay for transcription; receive a text communication originating at the relay on a second communication link that is separate from the first communication link, the text communication corresponding to a transcription of the hearing user's voice signal; and display a text caption corresponding to the text communication on the display. | 42. A communication system comprising: a hard of hearing user's captioned device, the captioned device including a display screen and a processor, the captioned device configured to: establish communication with a hard of hearing user's wireless phone device that is independent of the hard of hearing user's captioned device; receive a hearing user's voice signal originating at a hearing user's phone device from the hard of hearing user's phone device; establish a first communication link with a relay; route the hearing user's voice signal via the first communication link to the relay for transcription; receive a text communication originating at the relay on a second communication link that is separate from the first communication link, the text communication corresponding to a transcription of the hearing user's voice signal; and display a text caption corresponding to the text communication on the display. 45. The communication system of claim 42 wherein the captioned device is configured to establish communication with the hard of hearing user's phone device in response to a user input. | 0.59292 |
8,315,879 | 8 | 9 | 8. A computer-readable non-transitory medium having a computer program product encoded thereon comprising: computer usable program code for recording an audio instruction for modifying one or more documents via a mobile device adapted to record audio instructions; computer usable program code for converting the audio instruction into a command script for changing one or more documents, the documents associated with an application type; computer usable program code for associating the command script with a document identifier, the document identifier designating one or more underlying documents, the document identifier designating one or more underlying documents regardless of whether the one or more documents is open in an application or not open in an application, the document identifier serving to identify the application type used to open the one or more designated underlying documents; computer usable program code for forwarding the document identifier and the associated command script to a target location, the target location different than the mobile device, the target location for running the application type associated with the one or more underlying documents; and computer usable program code for executing the command script on the one or more underlying documents in order to make changes on the one or more underlying documents indicated by the recorded audio instructions. | 8. A computer-readable non-transitory medium having a computer program product encoded thereon comprising: computer usable program code for recording an audio instruction for modifying one or more documents via a mobile device adapted to record audio instructions; computer usable program code for converting the audio instruction into a command script for changing one or more documents, the documents associated with an application type; computer usable program code for associating the command script with a document identifier, the document identifier designating one or more underlying documents, the document identifier designating one or more underlying documents regardless of whether the one or more documents is open in an application or not open in an application, the document identifier serving to identify the application type used to open the one or more designated underlying documents; computer usable program code for forwarding the document identifier and the associated command script to a target location, the target location different than the mobile device, the target location for running the application type associated with the one or more underlying documents; and computer usable program code for executing the command script on the one or more underlying documents in order to make changes on the one or more underlying documents indicated by the recorded audio instructions. 9. The computer-readable medium of claim 8 further comprising: computer usable program code for creating the document identifier; and computer usable program code for receiving an indication that a change should be made to a document identified by the document identifier. | 0.850877 |
7,761,394 | 5 | 6 | 5. The method of claim 1 , wherein generating the taxonomy of the augmented dataset comprises generating a hierarchical taxonomy. | 5. The method of claim 1 , wherein generating the taxonomy of the augmented dataset comprises generating a hierarchical taxonomy. 6. The method of claim 5 , wherein generating the hierarchy comprises successively merging a pair of clusters together according to a predetermined entropic similarity condition. | 0.5 |
8,429,179 | 41 | 42 | 41. The computer readable medium of claim 40 , wherein mapping the graph representation of the input to the graph representation of the ontology to create a unified graph comprises mapping the survey response to the survey. | 41. The computer readable medium of claim 40 , wherein mapping the graph representation of the input to the graph representation of the ontology to create a unified graph comprises mapping the survey response to the survey. 42. The computer readable medium of claim 41 , further comprising, providing the graph representation of the survey to a user device and receiving the survey response back from the user device. | 0.5 |
7,761,843 | 1 | 21 | 1. A tangible computer-readable medium having computer-executable instructions for implementing a method of computer programming for a target programming language, wherein the computer programming includes at least one programming command, the computer executable instructions comprising instructions for: providing a predefined command sentence, the predefined command sentence comprising at least a portion of a programming command and a structure other than a syntax of the target programming language; defining the programming command as the predefined command sentence, wherein the programming command comprises at least one word; providing an entry component corresponding to at least one word in the predefined command sentence; receiving data relating to an input value for the entry component; and converting the predefined command sentence and the input value for the entry component into a completed command sentence, wherein the programming command comprises the completed command sentence, wherein the computer executable instructions for defining the programming command comprise instructions for: inserting a word into the programming command; deleting a word from the programming command; modifying a definition of a word of the programming command; and writing a translation procedure for the programming command. | 1. A tangible computer-readable medium having computer-executable instructions for implementing a method of computer programming for a target programming language, wherein the computer programming includes at least one programming command, the computer executable instructions comprising instructions for: providing a predefined command sentence, the predefined command sentence comprising at least a portion of a programming command and a structure other than a syntax of the target programming language; defining the programming command as the predefined command sentence, wherein the programming command comprises at least one word; providing an entry component corresponding to at least one word in the predefined command sentence; receiving data relating to an input value for the entry component; and converting the predefined command sentence and the input value for the entry component into a completed command sentence, wherein the programming command comprises the completed command sentence, wherein the computer executable instructions for defining the programming command comprise instructions for: inserting a word into the programming command; deleting a word from the programming command; modifying a definition of a word of the programming command; and writing a translation procedure for the programming command. 21. The tangible computer-readable medium having computer-executable instructions of claim 1 , further comprising instructions for: analyzing the completed programming command for errors; and providing notification of an occurrence of an error. | 0.717593 |
8,850,581 | 8 | 11 | 8. A process for use by an analyst assisted by a computational machine to identify software program code as a malware detection signature generation candidate, the software program configured to run on a virtual machine, the process comprising the steps of: utilizing at least one processor and a memory to run the program code on the virtual machine, the virtual machine changing states while the program code is running; making a determination, from at least one result which corresponds to at least one state of the virtual machine while running the program code, that the program code should be investigated as a possible carrier of malware; associating an identification start state in memory with the determination; causing the computational machine to place in a set of variables of interest in a memory of the computational machine at least one variable which is visible in the identification start state, namely, a variable which is within scope and could be assigned a value; the computational machine also being caused to search previously executed states of the virtual machine (states prior to the identification start state) for any assignment of a variable that belongs to the set of variables of interest; the computational machine also being caused to put into a set of assignments of interest in the memory an assignment that was found by the searching step; when the set of assignments of interest contains a nonterminated assignment having at least one source parameter variable, the computational machine also being caused to place the source parameter variable(s) of that nonterminated assignment in the set of variables of interest and then repeat the searching and putting steps; when the set of assignments of interest does not contain a nonterminated assignment having at least one source parameter variable, the computational machine also being caused to produce an identification of a region of code as the malware detection signature generation candidate, the region of code defined by the set of assignments of interest; and receiving the malware detection signature generation candidate identification which was produced by the computational machine. | 8. A process for use by an analyst assisted by a computational machine to identify software program code as a malware detection signature generation candidate, the software program configured to run on a virtual machine, the process comprising the steps of: utilizing at least one processor and a memory to run the program code on the virtual machine, the virtual machine changing states while the program code is running; making a determination, from at least one result which corresponds to at least one state of the virtual machine while running the program code, that the program code should be investigated as a possible carrier of malware; associating an identification start state in memory with the determination; causing the computational machine to place in a set of variables of interest in a memory of the computational machine at least one variable which is visible in the identification start state, namely, a variable which is within scope and could be assigned a value; the computational machine also being caused to search previously executed states of the virtual machine (states prior to the identification start state) for any assignment of a variable that belongs to the set of variables of interest; the computational machine also being caused to put into a set of assignments of interest in the memory an assignment that was found by the searching step; when the set of assignments of interest contains a nonterminated assignment having at least one source parameter variable, the computational machine also being caused to place the source parameter variable(s) of that nonterminated assignment in the set of variables of interest and then repeat the searching and putting steps; when the set of assignments of interest does not contain a nonterminated assignment having at least one source parameter variable, the computational machine also being caused to produce an identification of a region of code as the malware detection signature generation candidate, the region of code defined by the set of assignments of interest; and receiving the malware detection signature generation candidate identification which was produced by the computational machine. 11. The process of claim 8 , wherein the region of code received during the receiving step is the set of assignments of interest together with at least code for whatever function each assignment is contained in. | 0.703652 |
8,671,095 | 22 | 38 | 22. A method of responding to a search query to a user with a computing system comprising: a) processing a query from a user concerning a first topic with the computing system; b) automatically determining a geographic region associated with said user with the computing system; c) automatically determining if said first topic query relates to one or more events occurring within said geographic region; wherein said determining is performed by analyzing published online content relating to said one or more events or updates to said event(s) with the computing system; d) automatically selecting first news content relating to said first topic with the computing system when said first topic query relates to said one or more events or updates to said event(s) occurring within said geographic region; and e) presenting search results to said user with the computing system for said query including optionally said first topic news content in response to said query directed to said first topic, wherein advertising is presented within said interface based on an expected mental state of said user predicted based on a state of an event identified in said first topic news content. | 22. A method of responding to a search query to a user with a computing system comprising: a) processing a query from a user concerning a first topic with the computing system; b) automatically determining a geographic region associated with said user with the computing system; c) automatically determining if said first topic query relates to one or more events occurring within said geographic region; wherein said determining is performed by analyzing published online content relating to said one or more events or updates to said event(s) with the computing system; d) automatically selecting first news content relating to said first topic with the computing system when said first topic query relates to said one or more events or updates to said event(s) occurring within said geographic region; and e) presenting search results to said user with the computing system for said query including optionally said first topic news content in response to said query directed to said first topic, wherein advertising is presented within said interface based on an expected mental state of said user predicted based on a state of an event identified in said first topic news content. 38. The method of claim 22 wherein an advertising auction employs pricing for advertisements presented with said search results based on a prediction of an expected time for said user to complete reviewing said search results. | 0.647975 |
9,055,074 | 21 | 28 | 21. A method for aggregating social media content items from a plurality of social media providers, the method being implemented in a computer that includes one or more processors programmed with computer program instructions that, when executed by the one or more physical processors, programs the one or more physical processors to perform the method, the method comprising: receiving, by the one or more physical processors, a request to retrieve a previously aggregated set of social media content items, the request comprising an identification of a geofeed definition that comprises a specification of one or more geographically definable locations; obtaining, by the one or more physical processors, the geofeed definition based on the received request; determining, by the one or more physical processors, the specification of the one or more geographically definable locations from the geofeed definition; generating, by the one or more physical processors, a first request that specifies the one or more geographically definable locations in a first format used by a first social media content provider; generating, by the one or more physical processors, a second request that specifies the one or more geographically definable locations in a second format used by a second social media content provider; communicating, by the one or more physical processors, the first request to the first social media content provider; communicating, by the one or more physical processors, the second request to the second social media content provider; receiving, by the one or more physical processors, a first set of social media content items from the first social media content provider, wherein the first set of social media content items includes at least a first social media content item associated with information that indicates that the first social media content item is relevant to the one or more geographically definable locations; receiving, by the one or more physical processors, a second set of social media content items from the second social media content provider, wherein the second set of social media content items includes at least a second social media item associated with information that indicates that the second social media content item is relevant to the one or more geographically definable locations; aggregating, by the one or more physical processors, the first set of social media content items with the second set of social media content items to generate an aggregated set of social media content items; and communicating, by the one or more physical processors, the aggregated set of social media content items. | 21. A method for aggregating social media content items from a plurality of social media providers, the method being implemented in a computer that includes one or more processors programmed with computer program instructions that, when executed by the one or more physical processors, programs the one or more physical processors to perform the method, the method comprising: receiving, by the one or more physical processors, a request to retrieve a previously aggregated set of social media content items, the request comprising an identification of a geofeed definition that comprises a specification of one or more geographically definable locations; obtaining, by the one or more physical processors, the geofeed definition based on the received request; determining, by the one or more physical processors, the specification of the one or more geographically definable locations from the geofeed definition; generating, by the one or more physical processors, a first request that specifies the one or more geographically definable locations in a first format used by a first social media content provider; generating, by the one or more physical processors, a second request that specifies the one or more geographically definable locations in a second format used by a second social media content provider; communicating, by the one or more physical processors, the first request to the first social media content provider; communicating, by the one or more physical processors, the second request to the second social media content provider; receiving, by the one or more physical processors, a first set of social media content items from the first social media content provider, wherein the first set of social media content items includes at least a first social media content item associated with information that indicates that the first social media content item is relevant to the one or more geographically definable locations; receiving, by the one or more physical processors, a second set of social media content items from the second social media content provider, wherein the second set of social media content items includes at least a second social media item associated with information that indicates that the second social media content item is relevant to the one or more geographically definable locations; aggregating, by the one or more physical processors, the first set of social media content items with the second set of social media content items to generate an aggregated set of social media content items; and communicating, by the one or more physical processors, the aggregated set of social media content items. 28. The method of claim 21 , the method further comprising: performing, by the one or more physical processors, a data integrity check of the first social media content item; determining, by the one or more processors, whether the first social media content item passes the data integrity check; and removing, by the one or more processors, the first social media content item responsive to a determination that the first social media content item fails the data integrity check. | 0.5 |
8,442,812 | 18 | 39 | 18. A system for creating a recognition grammar for use with an interactive user interface to human readable text data that is also machine readable, the interactive user interface being responsive to spoken input, the system comprising: means for providing access to a phrase thesaurus database comprising a plurality of classes of phrases, wherein any two phrases that are semantic equivalent of each other are assigned to a same class; means for formulating an expression representing a part of the text data for each of one or more parts of the text data, wherein each formulated expression is constructed as one or more combinations of one or more phrases in the phrase thesaurus database; and means for automatically using the phrase thesaurus database to construct one or more equivalent expressions of each formulated expression based on assigned classes of the one or more phrases of each formulated expression, wherein the recognition grammar comprises the collection of all of the expressions. | 18. A system for creating a recognition grammar for use with an interactive user interface to human readable text data that is also machine readable, the interactive user interface being responsive to spoken input, the system comprising: means for providing access to a phrase thesaurus database comprising a plurality of classes of phrases, wherein any two phrases that are semantic equivalent of each other are assigned to a same class; means for formulating an expression representing a part of the text data for each of one or more parts of the text data, wherein each formulated expression is constructed as one or more combinations of one or more phrases in the phrase thesaurus database; and means for automatically using the phrase thesaurus database to construct one or more equivalent expressions of each formulated expression based on assigned classes of the one or more phrases of each formulated expression, wherein the recognition grammar comprises the collection of all of the expressions. 39. The system as in claim 18 , further comprising means for manually editing the recognition grammar. | 0.930801 |
9,342,626 | 1 | 2 | 1. A method, comprising: identifying a current query of a user, wherein the current query is a partial query entered by the user; identifying one or more past queries of the user, the past queries issued by the user prior to the current query; identifying one or more past entity collections related to one or more of the identified past queries, the past entity collections being a first set of entity collections, wherein each of the entity collections includes a grouping of entities that are members of the entity collection and that share one or more aspects in common; identifying one or more candidate query suggestions for the current query based at least in part on one or more characters of the current query; identifying, for a given candidate query suggestion of the candidate query suggestions, one or more current entity collections related to the given candidate query suggestion, the current entity collections being a second set of the entity collections; determining, for the given candidate query suggestion, the current entity collections that match the past entity collections; and ranking the given candidate query suggestion based on a comparison of the current entity collections that match the past entity collections to the current entity collections of a group of the current entity collections, the group including one or more of the current entity collections that do not match the past entity collections. | 1. A method, comprising: identifying a current query of a user, wherein the current query is a partial query entered by the user; identifying one or more past queries of the user, the past queries issued by the user prior to the current query; identifying one or more past entity collections related to one or more of the identified past queries, the past entity collections being a first set of entity collections, wherein each of the entity collections includes a grouping of entities that are members of the entity collection and that share one or more aspects in common; identifying one or more candidate query suggestions for the current query based at least in part on one or more characters of the current query; identifying, for a given candidate query suggestion of the candidate query suggestions, one or more current entity collections related to the given candidate query suggestion, the current entity collections being a second set of the entity collections; determining, for the given candidate query suggestion, the current entity collections that match the past entity collections; and ranking the given candidate query suggestion based on a comparison of the current entity collections that match the past entity collections to the current entity collections of a group of the current entity collections, the group including one or more of the current entity collections that do not match the past entity collections. 2. The method of claim 1 , further comprising: determining, based on the ranking, whether to provide the given candidate query suggestion as a query suggestion for the current query. | 0.808421 |
7,721,200 | 1 | 10 | 1. A method of generating a customized document about a product, the method comprising: a) providing a user with a document manager input interface on a computer, the input interface including a definition manager module, an electronic library manager module, an automatic text generator module, a document editor module, an effectivity interface module, and a document builder module; b) on the computer, defining a document definition based on a plurality of predefined data elements arranged in a tree-like data structure using the definition manager module, the predefined data elements being retrieved from a parts library contained in the document builder module, wherein the document definition comprises at least one of (i) organization of sections of the customized document, (ii) maintenance codes specific to the product, and (iii) page formatting information; c) on the computer, creating the customized document from the document definition using the definition manager module; d) on the computer, storing the customized document in a relational database; e) on the computer, editing one or more of the predefined data elements using the document editor module by using content-specific selection menus to generate revised data elements that are stored in the relational database; f) on the computer, deconstructing syntax of textual data elements that are syntactically joined with linguistic rules, specifying a category in which to place a business rule, generating one or more tasks associated with the business rule, and applying the business rule to the textual data elements of the customized document using the automatic text generator module; g) on the computer, modifying given data that is standard in particular data structures, and customizing the given data for particular applications using the electronic library manager module; h) on the computer, establishing effectivity associations, using the effectivity interface module, for a given component of the product, and thereby defining a manner in which a change to the given component is propagated throughout the customized document; i) in response to the user making the change to the given component via the effectivity interface module, propagating the change throughout the customized document according to the effectivity associations established by the user; j) synthesizing text from the revised data elements according to (i) the document definition defined by the document definition module, (ii) edits made by the user via the document editor module, (iii) the business rule applied by the user via the automatic text generator module, (iv) the customized data provided by the electronic library manager module, and (v) the effectivity associations established via the effectivity interface module; and k) generating and publishing the customized document. | 1. A method of generating a customized document about a product, the method comprising: a) providing a user with a document manager input interface on a computer, the input interface including a definition manager module, an electronic library manager module, an automatic text generator module, a document editor module, an effectivity interface module, and a document builder module; b) on the computer, defining a document definition based on a plurality of predefined data elements arranged in a tree-like data structure using the definition manager module, the predefined data elements being retrieved from a parts library contained in the document builder module, wherein the document definition comprises at least one of (i) organization of sections of the customized document, (ii) maintenance codes specific to the product, and (iii) page formatting information; c) on the computer, creating the customized document from the document definition using the definition manager module; d) on the computer, storing the customized document in a relational database; e) on the computer, editing one or more of the predefined data elements using the document editor module by using content-specific selection menus to generate revised data elements that are stored in the relational database; f) on the computer, deconstructing syntax of textual data elements that are syntactically joined with linguistic rules, specifying a category in which to place a business rule, generating one or more tasks associated with the business rule, and applying the business rule to the textual data elements of the customized document using the automatic text generator module; g) on the computer, modifying given data that is standard in particular data structures, and customizing the given data for particular applications using the electronic library manager module; h) on the computer, establishing effectivity associations, using the effectivity interface module, for a given component of the product, and thereby defining a manner in which a change to the given component is propagated throughout the customized document; i) in response to the user making the change to the given component via the effectivity interface module, propagating the change throughout the customized document according to the effectivity associations established by the user; j) synthesizing text from the revised data elements according to (i) the document definition defined by the document definition module, (ii) edits made by the user via the document editor module, (iii) the business rule applied by the user via the automatic text generator module, (iv) the customized data provided by the electronic library manager module, and (v) the effectivity associations established via the effectivity interface module; and k) generating and publishing the customized document. 10. The method of claim 1 , further comprising: providing automatic revision markings on the customized document by comparing the customized document during editing to a previously archived document on the fly. | 0.738806 |
7,496,500 | 9 | 10 | 9. The system of claim 1 , the reformulation of the data includes producing a logical form of the data and generating an action description from the logical form based on the intent. | 9. The system of claim 1 , the reformulation of the data includes producing a logical form of the data and generating an action description from the logical form based on the intent. 10. The system of claim 9 , logical form comprises at least one non-deictic element that replaced a deictic element in the data. | 0.5 |
8,799,254 | 1 | 6 | 1. A method comprising: receiving, at a portable apparatus, text input as search text from a user of said portable apparatus; searching for content items of at least one content type matching said search text, resulting in a list containing zero or more matching content items; directing presentment of said list of matching content items on a display of said portable apparatus, when said list of matching content items contains at least a threshold number of content items; directing presentment of at least one option to search at least one of at least two databases available over a network using said search text on said display, when said list of matching content items comprises less than said threshold number of content items; and based on selection of the at least one option, searching the at least one of the at least two databases associated with the at least one option using search information in addition to said search text, wherein the search information is related to a type of data stored in the at least one of the at least two databases associated with the at least one option; wherein said receiving text input, searching for content items, directing presentment of said list and directing presentment of at least one option to search a database are repeated until either an item of said list of matching content items is selected or an option of said at least one option is selected. | 1. A method comprising: receiving, at a portable apparatus, text input as search text from a user of said portable apparatus; searching for content items of at least one content type matching said search text, resulting in a list containing zero or more matching content items; directing presentment of said list of matching content items on a display of said portable apparatus, when said list of matching content items contains at least a threshold number of content items; directing presentment of at least one option to search at least one of at least two databases available over a network using said search text on said display, when said list of matching content items comprises less than said threshold number of content items; and based on selection of the at least one option, searching the at least one of the at least two databases associated with the at least one option using search information in addition to said search text, wherein the search information is related to a type of data stored in the at least one of the at least two databases associated with the at least one option; wherein said receiving text input, searching for content items, directing presentment of said list and directing presentment of at least one option to search a database are repeated until either an item of said list of matching content items is selected or an option of said at least one option is selected. 6. The method of claim 1 , further comprising: providing, in response to user selection of one of said at least one option, location information of said portable apparatus as search criteria to a database associated with said selected option. | 0.69598 |
8,805,818 | 9 | 12 | 9. A method as in claim 8 wherein the at least one relational subject sequence is distributed as whole records to the multiple processing units. | 9. A method as in claim 8 wherein the at least one relational subject sequence is distributed as whole records to the multiple processing units. 12. A method as in claim 9 wherein each processing unit contains a complete copy of a subject sequence, and each processing unit receives a unique query sequence. | 0.625 |
9,256,968 | 1 | 3 | 1. A method for converting a sketch shape into a semantic element, the method comprising the steps of: receiving a request to convert a first sketch shape into a first semantic element, wherein the first sketch shape and a second semantic element are part of a first nested shape combination, wherein the first sketch shape includes a visual depiction corresponding to a first class of semantic descriptions, wherein the first semantic element is a visual depiction further including a first semantic description of the first class of semantic descriptions; determining that a first semantic relationship between the first semantic element and the second semantic element exists; and based on determining the first semantic relationship converting the first sketch shape to the first semantic element, such that the determined first semantic relationship is depicted between the second semantic element and first semantic element; wherein at least one of the steps is carried out using a computing device. | 1. A method for converting a sketch shape into a semantic element, the method comprising the steps of: receiving a request to convert a first sketch shape into a first semantic element, wherein the first sketch shape and a second semantic element are part of a first nested shape combination, wherein the first sketch shape includes a visual depiction corresponding to a first class of semantic descriptions, wherein the first semantic element is a visual depiction further including a first semantic description of the first class of semantic descriptions; determining that a first semantic relationship between the first semantic element and the second semantic element exists; and based on determining the first semantic relationship converting the first sketch shape to the first semantic element, such that the determined first semantic relationship is depicted between the second semantic element and first semantic element; wherein at least one of the steps is carried out using a computing device. 3. The method of claim 1 , wherein the step of determining that the first semantic relationship between the first semantic element and the second semantic element exist further comprises: determining that the first semantic relationship between the second semantic element and the first semantic element can be depicted upon receipt of prerequisite information; requesting the prerequisite information; and receiving the prerequisite information. | 0.680057 |
7,756,915 | 15 | 16 | 15. The digital music library builder of claim 1 wherein the meta-data generator tracks a number of repetitions of a song that is received repeatedly by the receiver. | 15. The digital music library builder of claim 1 wherein the meta-data generator tracks a number of repetitions of a song that is received repeatedly by the receiver. 16. The digital music library builder of claim 15 further comprising a digital rights manager for restricting access to the song, based on the tracked number of repetitions of the song. | 0.5 |
9,418,137 | 12 | 15 | 12. A non-transitory computer-readable medium comprising computer program instructions stored thereon, wherein the computer program instructions are executable by at least one computer processor to perform a method, the method comprising: (1) storing data representing a plurality of classes and a plurality of instances in a bijective-set memory; (2) storing data representing class membership relationships between the plurality of classes and the plurality of instances in the bijective-set memory; (3) receiving data representing a query, wherein the query does not specify any table; (4) identifying an operation specified by the query; (5) identifying an operand specified by the query; (6) executing the query, comprising: (6) (a) identifying a table to be searched, based on the query; and (6) (b) performing the operation on the operand, including searching the identified table, to produce an output; wherein (1) comprises storing the data representing the plurality of classes and the plurality of instances in a single table in the bijective-set memory, and wherein (2) comprises storing the data representing the class membership relationships between the plurality of classes and the plurality of instances in the single table in the bijective-set memory. | 12. A non-transitory computer-readable medium comprising computer program instructions stored thereon, wherein the computer program instructions are executable by at least one computer processor to perform a method, the method comprising: (1) storing data representing a plurality of classes and a plurality of instances in a bijective-set memory; (2) storing data representing class membership relationships between the plurality of classes and the plurality of instances in the bijective-set memory; (3) receiving data representing a query, wherein the query does not specify any table; (4) identifying an operation specified by the query; (5) identifying an operand specified by the query; (6) executing the query, comprising: (6) (a) identifying a table to be searched, based on the query; and (6) (b) performing the operation on the operand, including searching the identified table, to produce an output; wherein (1) comprises storing the data representing the plurality of classes and the plurality of instances in a single table in the bijective-set memory, and wherein (2) comprises storing the data representing the class membership relationships between the plurality of classes and the plurality of instances in the single table in the bijective-set memory. 15. The non-transitory computer-readable medium of claim 12 , wherein the query is not written in a structured language. | 0.61039 |
8,319,648 | 8 | 15 | 8. The method of claim 7 , wherein the deriving the disease status includes deriving a heart failure decompensation status. | 8. The method of claim 7 , wherein the deriving the disease status includes deriving a heart failure decompensation status. 15. The method of claim 8 , comprising providing an alert to a user when the heart failure decompensation status indicates an onset of acute heart failure decompensation. | 0.628821 |
8,739,022 | 7 | 13 | 7. A method of parsing a plurality of portions of a hierarchically organized data document in parallel, comprising: providing a hierarchical skeleton of the data document, the hierarchical skeleton representing a hierarchical arrangement of data document elements, wherein at least one node of the hierarchical skeleton has a plurality of subtrees; providing a plurality of processors, each processor executing in parallel; automatically allocating to the plurality of processors respective tasks, each task representing a parsing operation on an element of the data document selected in dependence on the hierarchical skeleton; generating a set of tasks by iteratively removing a remaining branch of the hierarchical skeleton which represents a largest task, and elevating the root of the subtree represented by the largest task to a next higher level, wherein a sufficient number of tasks is generated to permit efficient balancing, wherein an assignment of tasks to respective processors is balanced; and automatically generating a data structure or procedural function calls representing the parsed data structure elements. | 7. A method of parsing a plurality of portions of a hierarchically organized data document in parallel, comprising: providing a hierarchical skeleton of the data document, the hierarchical skeleton representing a hierarchical arrangement of data document elements, wherein at least one node of the hierarchical skeleton has a plurality of subtrees; providing a plurality of processors, each processor executing in parallel; automatically allocating to the plurality of processors respective tasks, each task representing a parsing operation on an element of the data document selected in dependence on the hierarchical skeleton; generating a set of tasks by iteratively removing a remaining branch of the hierarchical skeleton which represents a largest task, and elevating the root of the subtree represented by the largest task to a next higher level, wherein a sufficient number of tasks is generated to permit efficient balancing, wherein an assignment of tasks to respective processors is balanced; and automatically generating a data structure or procedural function calls representing the parsed data structure elements. 13. The method according to claim 7 , wherein each element is defined to have no interdependence with another element which precludes separate processing thereof. | 0.736156 |
9,311,111 | 28 | 32 | 28. A method comprising: providing, in a language processing environment, a handle base class; receiving a first class definition, the first class definition defining a handle subclass, where the handle subclass has a class hierarchy that includes the handle base class; constructing, by a processor, one or more handle objects from the handle subclass; using the one or more handle objects, where the one or more handle objects are used exclusively through references to the one or more handle objects; receiving a second class definition, the second class definition defining a non-handle base class; receiving a third class definition, the third class definition defining a non-handle subclass, where the non-handle subclass has a class hierarchy that includes the non-handle base class and does not include the handle base class; constructing, by the processor, non-handle objects from the non-handle subclass; using the non-handle objects, where the non-handle objects are used exclusively by value; storing the one or more handle objects and the non-handle objects in a memory coupled to the processor; providing, in the language processing environment, a first syntax for constructing both the non-handle objects and the one or more handle objects; and providing, in the language processing environment, a second syntax for using both the non-handle objects and the one or more handle objects. | 28. A method comprising: providing, in a language processing environment, a handle base class; receiving a first class definition, the first class definition defining a handle subclass, where the handle subclass has a class hierarchy that includes the handle base class; constructing, by a processor, one or more handle objects from the handle subclass; using the one or more handle objects, where the one or more handle objects are used exclusively through references to the one or more handle objects; receiving a second class definition, the second class definition defining a non-handle base class; receiving a third class definition, the third class definition defining a non-handle subclass, where the non-handle subclass has a class hierarchy that includes the non-handle base class and does not include the handle base class; constructing, by the processor, non-handle objects from the non-handle subclass; using the non-handle objects, where the non-handle objects are used exclusively by value; storing the one or more handle objects and the non-handle objects in a memory coupled to the processor; providing, in the language processing environment, a first syntax for constructing both the non-handle objects and the one or more handle objects; and providing, in the language processing environment, a second syntax for using both the non-handle objects and the one or more handle objects. 32. The method of claim 28 wherein the third class definition includes: a term, where the term is classdef; a name for the non-handle subclass; a less-then sign, and a name of the non-handle base class. | 0.579167 |
4,829,423 | 51 | 52 | 51. An interface system for providing constrained outputs to a computing system in accordance with inputs received from a user in a language, the inputs having a predefined correspondence to the outputs, comprising: an output for indicating to the user a set of permissible items; designating means for allowing the user to designate a particular item from among those indicated by said output; a recognizer, coupled to said output and to said designating means, for cumulatively parsing inputs as sequences of items successively entered, and for repeatedly generating all permissible items which could immediately follow a currently received sequence of items in accordance with the language. | 51. An interface system for providing constrained outputs to a computing system in accordance with inputs received from a user in a language, the inputs having a predefined correspondence to the outputs, comprising: an output for indicating to the user a set of permissible items; designating means for allowing the user to designate a particular item from among those indicated by said output; a recognizer, coupled to said output and to said designating means, for cumulatively parsing inputs as sequences of items successively entered, and for repeatedly generating all permissible items which could immediately follow a currently received sequence of items in accordance with the language. 52. The system of claim 51, further comprising a translator coupled to said recognizer for translating a completed input into an output according to the predefined correspondence. | 0.5 |
10,026,506 | 5 | 6 | 5. The system of claim 2 , further comprising: a plurality of the mobile devices associated with a plurality of the vehicles, respectively, wherein the controller is further configured to: determine a number of the plurality of vehicles within the predetermined distance of the pick-up request; and determine a charge for the pick-up request as the output value based upon the determined number of the plurality of vehicles. | 5. The system of claim 2 , further comprising: a plurality of the mobile devices associated with a plurality of the vehicles, respectively, wherein the controller is further configured to: determine a number of the plurality of vehicles within the predetermined distance of the pick-up request; and determine a charge for the pick-up request as the output value based upon the determined number of the plurality of vehicles. 6. The system of claim 5 , wherein the charge determined for the pick-up request further includes a minimum charge acceptable to each of the number of the plurality of vehicles and a maximum charge acceptable for the client device. | 0.5 |
8,824,783 | 3 | 8 | 3. Method according to claim 1 , said method comprises using training data used for training the learning system for re-training, also, wherein contribution of the selection and the training data for re-training is controlled by a first weight factor assigned to the selection and at least a different second weight factor assigned to the training data. | 3. Method according to claim 1 , said method comprises using training data used for training the learning system for re-training, also, wherein contribution of the selection and the training data for re-training is controlled by a first weight factor assigned to the selection and at least a different second weight factor assigned to the training data. 8. Method according to claim 3 , wherein at least one of the first and the at least a different second weight factor is received through said user interface. | 0.753918 |
9,465,795 | 1 | 7 | 1. A method, comprising: receiving enterprise network traffic associated with a particular user; identifying irrelevant documents in the received network traffic using a document filter; developing a personal vocabulary for the particular user based on the enterprise network traffic, wherein the irrelevant documents are not evaluated to develop the personal vocabulary, wherein the personal vocabulary is developed independent of additional users; determining an expertise associated with the particular user based, at least in part, on the personal vocabulary and activity of the additional users; determining a category associated with the particular user, wherein the category is at least partially based on applications used by the particular user; determining areas of interest for the particular user based on the personal vocabulary, the category, and inter-category terms, wherein the inter-category terms are used to link similar categories; determining associations for the particular user in relation to the additional users; and generating a feed based on a portion of the enterprise network traffic and areas of interest for the particular user, wherein the feed is automatically delivered to a subset of the additional users. | 1. A method, comprising: receiving enterprise network traffic associated with a particular user; identifying irrelevant documents in the received network traffic using a document filter; developing a personal vocabulary for the particular user based on the enterprise network traffic, wherein the irrelevant documents are not evaluated to develop the personal vocabulary, wherein the personal vocabulary is developed independent of additional users; determining an expertise associated with the particular user based, at least in part, on the personal vocabulary and activity of the additional users; determining a category associated with the particular user, wherein the category is at least partially based on applications used by the particular user; determining areas of interest for the particular user based on the personal vocabulary, the category, and inter-category terms, wherein the inter-category terms are used to link similar categories; determining associations for the particular user in relation to the additional users; and generating a feed based on a portion of the enterprise network traffic and areas of interest for the particular user, wherein the feed is automatically delivered to a subset of the additional users. 7. The method of claim 1 , wherein the personal vocabulary is updated in order to develop an additional feed to be delivered to at least some of the additional users. | 0.600962 |
8,370,139 | 1 | 6 | 1. A feature-vector compensating apparatus for compensating a feature vector of speech used in speech processing under a background noise environment, comprising: a first storing unit that stores therein a compensation vector for compensating the feature vector of the speech for each of a plurality of noise environments; a second storing unit that stores therein a noise-environment hidden Markov model that maintains each of the noise environments as a state and is obtained by modeling parameters of a Gaussian mixture model that is a probability model of the feature vector in each of the noise environments and a state transition probability between states; a feature extracting unit that extracts the feature vector of the speech in each of a plurality of frames of input speech; an estimating unit that estimates a noise-environment series based on the noise-environment hidden Markov model, a feature-vector series including a plurality of extracted feature vectors for the frames and a degree of similarity that indicates a certainty that a respective feature vector is generated under the noise environment in each current frame and at least one of an immediately previous frame and an immediately subsequent frame of the current frame, the noise-environment series being a series of noise environments which generates each of the plurality of extracted feature vectors in the feature-vector series; a calculating unit that obtains a compensation vector corresponding to each noise environment in the estimated noise-environment series based on the compensation vectors present in the first storing unit, wherein the calculating unit obtains a first compensation vector from the compensation vector present in the first storing unit, and calculates a second compensation vector by performing a weighting addition of the obtained first compensation vector with an occupation probability of each state obtained from the noise-environment hidden Markov model as a weighting coefficient; and a compensating unit that compensates the extracted feature vectors of the speech based on the obtained second compensation vectors. | 1. A feature-vector compensating apparatus for compensating a feature vector of speech used in speech processing under a background noise environment, comprising: a first storing unit that stores therein a compensation vector for compensating the feature vector of the speech for each of a plurality of noise environments; a second storing unit that stores therein a noise-environment hidden Markov model that maintains each of the noise environments as a state and is obtained by modeling parameters of a Gaussian mixture model that is a probability model of the feature vector in each of the noise environments and a state transition probability between states; a feature extracting unit that extracts the feature vector of the speech in each of a plurality of frames of input speech; an estimating unit that estimates a noise-environment series based on the noise-environment hidden Markov model, a feature-vector series including a plurality of extracted feature vectors for the frames and a degree of similarity that indicates a certainty that a respective feature vector is generated under the noise environment in each current frame and at least one of an immediately previous frame and an immediately subsequent frame of the current frame, the noise-environment series being a series of noise environments which generates each of the plurality of extracted feature vectors in the feature-vector series; a calculating unit that obtains a compensation vector corresponding to each noise environment in the estimated noise-environment series based on the compensation vectors present in the first storing unit, wherein the calculating unit obtains a first compensation vector from the compensation vector present in the first storing unit, and calculates a second compensation vector by performing a weighting addition of the obtained first compensation vector with an occupation probability of each state obtained from the noise-environment hidden Markov model as a weighting coefficient; and a compensating unit that compensates the extracted feature vectors of the speech based on the obtained second compensation vectors. 6. The apparatus according to claim 1 , wherein the extracting unit extracts a Mel frequency cepstrum coefficient of the input speech as the feature vector. | 0.793651 |
10,091,147 | 2 | 3 | 2. The method of claim 1 , wherein determining that the term is a vague term comprises: identifying multiple entities that are associated with the vague term in a database. | 2. The method of claim 1 , wherein determining that the term is a vague term comprises: identifying multiple entities that are associated with the vague term in a database. 3. The method of claim 2 , wherein using the user-restricted content associated with the first additional user to determine the additional information that is related to the vague term comprises: selecting a subset of the multiple entities based on the user-restricted content; and determining the additional information based on the selected subset. | 0.5 |
7,618,313 | 3 | 4 | 3. A word game device as recited in claim 2 wherein said plurality of playing positions is mapped on the surface of a three-dimensional housing. | 3. A word game device as recited in claim 2 wherein said plurality of playing positions is mapped on the surface of a three-dimensional housing. 4. A word game device as recited in claim 3 , wherein said three-dimensional housing is in the form of a cube. | 0.5 |
6,064,952 | 13 | 15 | 13. An information abstracting apparatus comprising: input means for accepting an input of character string data divided into prescribed units each subdivided into prescribed paragraphs, with each individual character represented by a character code; keyword extracting means for extracting a keyword for each paragraph in each of said prescribed units from said character string data input from said input means; keyword associating means for generating a keyword association by associating one keyword with another among keywords obtained from the same paragraph; similarity calculating means for calculating similarity between keywords thus extracted, on the basis of a plurality of factors including said keyword association; weighting means for weighting said extracted keyword by taking into account a state of occurrence, in the other prescribed units, of keywords that are identical or similar to said extracted keyword, and for weighting said generated keyword association by taking into account a state of occurrence, in the other prescribed paragraphs, of keyword associations that are identical to said generated keyword association; selecting means for selecting keywords and keyword associations from said extracted keywords and said generated keyword associations on the basis of the weighted results; and outputting said selected keywords and keyword associations as an information abstract relating to said character string data. | 13. An information abstracting apparatus comprising: input means for accepting an input of character string data divided into prescribed units each subdivided into prescribed paragraphs, with each individual character represented by a character code; keyword extracting means for extracting a keyword for each paragraph in each of said prescribed units from said character string data input from said input means; keyword associating means for generating a keyword association by associating one keyword with another among keywords obtained from the same paragraph; similarity calculating means for calculating similarity between keywords thus extracted, on the basis of a plurality of factors including said keyword association; weighting means for weighting said extracted keyword by taking into account a state of occurrence, in the other prescribed units, of keywords that are identical or similar to said extracted keyword, and for weighting said generated keyword association by taking into account a state of occurrence, in the other prescribed paragraphs, of keyword associations that are identical to said generated keyword association; selecting means for selecting keywords and keyword associations from said extracted keywords and said generated keyword associations on the basis of the weighted results; and outputting said selected keywords and keyword associations as an information abstract relating to said character string data. 15. An information abstracting apparatus according to claim 13, wherein said keyword is weighted by using at least one of the number of units from which keywords whose similarity with the keyword to be weighted is greater than a predetermined reference were extracted, the frequency of occurrence in each prescribed unit of keywords whose similarity with said keyword is greater than said predetermined reference, and the number of characters of said keyword. | 0.5 |
8,825,645 | 9 | 15 | 9. A system comprising: one or more processors to: identify a plurality of documents, a first document, of the identified plurality of documents, being linked to by a second document, of the identified plurality of documents, the second document and a third document, of the identified plurality of documents, being in a set of affiliated documents; calculate a first value for each document in the set of affiliated documents, calculating the first value for each document in the set of affiliated documents being based on: a ranking score of the document, and a number of outbound links from the document; determine that the first value calculated for the third document is a maximum of the first values calculated for each document in the set of affiliated documents; assign a ranking score to the first document based the first value calculated for the third document; and store the ranking score. | 9. A system comprising: one or more processors to: identify a plurality of documents, a first document, of the identified plurality of documents, being linked to by a second document, of the identified plurality of documents, the second document and a third document, of the identified plurality of documents, being in a set of affiliated documents; calculate a first value for each document in the set of affiliated documents, calculating the first value for each document in the set of affiliated documents being based on: a ranking score of the document, and a number of outbound links from the document; determine that the first value calculated for the third document is a maximum of the first values calculated for each document in the set of affiliated documents; assign a ranking score to the first document based the first value calculated for the third document; and store the ranking score. 15. The system of claim 9 , where affiliation among a plurality of documents in the affiliated set of documents is defined by a binary model of affiliation. | 0.865749 |
9,367,606 | 26 | 30 | 26. The method of claim 1 , wherein the relevance model comprises a plurality of features including at least one document-specific feature and at least one query-specific feature. | 26. The method of claim 1 , wherein the relevance model comprises a plurality of features including at least one document-specific feature and at least one query-specific feature. 30. The method of claim 26 , further comprising modifying the relevance model, wherein modifying the relevance model comprises modifying a parameter for at least one feature in the relevance model using at least one user input event. | 0.783859 |
6,138,270 | 42 | 45 | 42. A computer-implemented method for detecting differences between first and second graphical programs, wherein the method executes on a computer including a display, the method comprising: creating the first graphical program, wherein the first graphical program comprises first graphical code; creating the second graphical program, wherein the second graphical program comprises second graphical code; determining differences between said first graphical program and said second graphical program; and displaying an indication of said differences on the display; wherein said differences are used to evaluate at least one of the first graphical program and the second graphical program. | 42. A computer-implemented method for detecting differences between first and second graphical programs, wherein the method executes on a computer including a display, the method comprising: creating the first graphical program, wherein the first graphical program comprises first graphical code; creating the second graphical program, wherein the second graphical program comprises second graphical code; determining differences between said first graphical program and said second graphical program; and displaying an indication of said differences on the display; wherein said differences are used to evaluate at least one of the first graphical program and the second graphical program. 45. The method of claim 42, wherein said graphical code includes interconnected function block icons. | 0.872152 |
9,465,862 | 15 | 19 | 15. A computer program product embodied on a non-transitory computer readable storage medium, the computer program product including instructions for causing a computer to execute a method for integrating query categories, comprising: executing a reductionist module on the search query to extract a core term from the search query, the core term used to search a hash table that maps core terms to corresponding categories; deriving a first result comprising at least one of the categories from the search of the hash table; executing an enrichment module on the search query to yield a second result, the enrichment module including searching an index of terms that are mapped to documents and corresponding categories in the index, the second result indicative of one of the corresponding categories in the index based on a probability score; upon determining the core term is present in the hash table, calculating a weighted average for corresponding values of the first result and the second result based on training data acquired from the execution of the reductionist module and the execution of the enrichment module, the calculated weighted average stored in a memory device; and upon determining the core term from the search query is not listed in the hash table, and upon determining the probability score of the one of the corresponding categories in the index for the second result meets a minimum defined confidence value, inserting and storing the core term and the one of the corresponding categories in the hash table and mapping the core term to the one of the corresponding categories in the hash table. | 15. A computer program product embodied on a non-transitory computer readable storage medium, the computer program product including instructions for causing a computer to execute a method for integrating query categories, comprising: executing a reductionist module on the search query to extract a core term from the search query, the core term used to search a hash table that maps core terms to corresponding categories; deriving a first result comprising at least one of the categories from the search of the hash table; executing an enrichment module on the search query to yield a second result, the enrichment module including searching an index of terms that are mapped to documents and corresponding categories in the index, the second result indicative of one of the corresponding categories in the index based on a probability score; upon determining the core term is present in the hash table, calculating a weighted average for corresponding values of the first result and the second result based on training data acquired from the execution of the reductionist module and the execution of the enrichment module, the calculated weighted average stored in a memory device; and upon determining the core term from the search query is not listed in the hash table, and upon determining the probability score of the one of the corresponding categories in the index for the second result meets a minimum defined confidence value, inserting and storing the core term and the one of the corresponding categories in the hash table and mapping the core term to the one of the corresponding categories in the hash table. 19. The computer program product of claim 15 , wherein the weighted average is applied equally to the first result and the second result based on training data derived from the execution of the reductionist module and the execution of the enrichment module. | 0.578689 |
8,892,443 | 1 | 4 | 1. A method comprising: receiving a spoken user search query at a portable device; determining a present location based on the portable device; incorporating a granularity description of the present location into a local language model used to process the spoken user search query, the granularity description using weights for topologically concentric locations to determine probabilities; and outputting results associated with the spoken user search query based on the present location and a term in the spoken user search query. | 1. A method comprising: receiving a spoken user search query at a portable device; determining a present location based on the portable device; incorporating a granularity description of the present location into a local language model used to process the spoken user search query, the granularity description using weights for topologically concentric locations to determine probabilities; and outputting results associated with the spoken user search query based on the present location and a term in the spoken user search query. 4. The method of claim 1 wherein the model is a query model described by a probability distribution function of the form p(x|l). | 0.884685 |
9,418,057 | 1 | 6 | 1. A method executed by at least one processor comprising the steps of: receiving, at a system, a profile submitted by a user, the system configured to compare a set of profiles to one another; determining a geographical location from which the profile was submitted; determining that the geographical location from which the profile was submitted is a geographical location associated with fraudulent profile submissions; determining a text score for the profile by comparing a first set of phrases included in the profile to a second set of phrases, the second set of phrases comprising phrases from stored text, the stored text comprising stored text known to be genuine and stored text known to be fraudulent; determining that the profile is fraudulent using the text score and the geographical location from which the profile was submitted; and in response to determining that the profile is fraudulent, preventing the system from comparing the profile to the set of profiles. | 1. A method executed by at least one processor comprising the steps of: receiving, at a system, a profile submitted by a user, the system configured to compare a set of profiles to one another; determining a geographical location from which the profile was submitted; determining that the geographical location from which the profile was submitted is a geographical location associated with fraudulent profile submissions; determining a text score for the profile by comparing a first set of phrases included in the profile to a second set of phrases, the second set of phrases comprising phrases from stored text, the stored text comprising stored text known to be genuine and stored text known to be fraudulent; determining that the profile is fraudulent using the text score and the geographical location from which the profile was submitted; and in response to determining that the profile is fraudulent, preventing the system from comparing the profile to the set of profiles. 6. The method of claim 1 , wherein comparing the first set of phrases included in the profile to a second set of phrases comprises generating a tree structure corresponding to the first set of phrases. | 0.767898 |
6,119,101 | 28 | 30 | 28. A method for quantifying demand by a provider for a product, comprising in combination the steps of: selecting a demand agent manager to supervise the subsequent steps; composing a demand query; creating a demand agent; delivering the demand agent to a market; accepting the demand agent by the market; and searching demand. | 28. A method for quantifying demand by a provider for a product, comprising in combination the steps of: selecting a demand agent manager to supervise the subsequent steps; composing a demand query; creating a demand agent; delivering the demand agent to a market; accepting the demand agent by the market; and searching demand. 30. A method for quantifying demand according to claim 28, wherein the step of creating a demand agent comprises, in combination, the steps of: creating a decision agent with a unique identifier; storing a reference to a personal agent of the provider, a reference to the market that is to be searched, the search expiry time, the delivery media, time, and period, and the query; and logging the creation of the new decision agent with the decision agent's log function. | 0.754697 |
8,793,277 | 1 | 8 | 1. A forensic system configured to acquire digital information recorded on a plurality of computers or a server to analyze the acquired digital information, the forensic system comprising: a digital information acquiring unit configured to acquire digital information containing digital document information composed of a plurality of document files, and to acquire user information about users using the plurality of computers or the server; a recording unit configured to record therein the digital information acquired by the digital information acquiring unit; a display unit configured to display the recorded digital information; a user-specifying information setting unit configured to set user-specifying information showing which one of users contained in the user-specifying information each of the plurality of document files is related with, to set ranking information showing a first relative degree of relationship a first user from among the users has with litigation, and showing a second relative degree of relationship a second user from among the users has with the litigation, and configured to cause the recording unit to record the set user-specifying information, via the display unit; a user selecting unit configured to select at least one user via the display unit; a control unit, comprising: a searching unit configured to search a document file where the user-specifying information corresponding to the selected user was set, and to provide a book-mark function allowing book-mark search for material set with a hierarchy structure book-mark; a highlight display function configured to highlight, on the display unit, a searched word or phrase; a managing unit including an access right control function configured to set one or more rights for each of a plurality of accounts associated with a browser, wherein the one or more rights set by the managing unit includes a manager right associated with the browser; a statistical data producing unit configured to produce statistical data represented by data size for each data format of the acquired digital document information or statistical data represented by data size for each data format of the digital document information; a digital document extracting unit configured to select a kind of file to be searched; a data converting unit configured to preserve a selected file as a separate file; an additional information setting unit configured to set additional information showing whether or not the searched document file is related with the litigation, wherein the additional information includes at least one of a first tag indicating that the searched document file is related with the litigation, a second tag indicating that the searched document file is potentially related with the litigation, and a third tag indicating that the searched document file is not related with the litigation; and an output unit configured to output the document file which is related with the litigation, based on the first relative degree of relationship the first user from among the users has with the litigation, the second relative degree of relationship the second user from among the users has with the litigation, and the at least one of the first tag indicating that the searched document file is related with the litigation, the second tag indicating that the searched document file is potentially related with the litigation, and the third tag indicating that the searched document file is not related with the litigation. | 1. A forensic system configured to acquire digital information recorded on a plurality of computers or a server to analyze the acquired digital information, the forensic system comprising: a digital information acquiring unit configured to acquire digital information containing digital document information composed of a plurality of document files, and to acquire user information about users using the plurality of computers or the server; a recording unit configured to record therein the digital information acquired by the digital information acquiring unit; a display unit configured to display the recorded digital information; a user-specifying information setting unit configured to set user-specifying information showing which one of users contained in the user-specifying information each of the plurality of document files is related with, to set ranking information showing a first relative degree of relationship a first user from among the users has with litigation, and showing a second relative degree of relationship a second user from among the users has with the litigation, and configured to cause the recording unit to record the set user-specifying information, via the display unit; a user selecting unit configured to select at least one user via the display unit; a control unit, comprising: a searching unit configured to search a document file where the user-specifying information corresponding to the selected user was set, and to provide a book-mark function allowing book-mark search for material set with a hierarchy structure book-mark; a highlight display function configured to highlight, on the display unit, a searched word or phrase; a managing unit including an access right control function configured to set one or more rights for each of a plurality of accounts associated with a browser, wherein the one or more rights set by the managing unit includes a manager right associated with the browser; a statistical data producing unit configured to produce statistical data represented by data size for each data format of the acquired digital document information or statistical data represented by data size for each data format of the digital document information; a digital document extracting unit configured to select a kind of file to be searched; a data converting unit configured to preserve a selected file as a separate file; an additional information setting unit configured to set additional information showing whether or not the searched document file is related with the litigation, wherein the additional information includes at least one of a first tag indicating that the searched document file is related with the litigation, a second tag indicating that the searched document file is potentially related with the litigation, and a third tag indicating that the searched document file is not related with the litigation; and an output unit configured to output the document file which is related with the litigation, based on the first relative degree of relationship the first user from among the users has with the litigation, the second relative degree of relationship the second user from among the users has with the litigation, and the at least one of the first tag indicating that the searched document file is related with the litigation, the second tag indicating that the searched document file is potentially related with the litigation, and the third tag indicating that the searched document file is not related with the litigation. 8. The forensic system according to claim 1 , further comprising: a clock unit which, when newly acquiring digital information, is configured to clock a date and time of the acquisition of the digital information, the digital information further including folder information saving the digital document information, wherein the digital information acquiring unit is configured to acquire the digital document information and the folder information which were produced after the time and date previously clocked by the clock unit, and is configured to acquire user information related with the acquired digital document information. | 0.5 |
10,007,883 | 10 | 11 | 10. A non-transitory computer-readable storage medium encoded with computer-executable instructions to select a preferred data set, which in response to execution by a computing device, cause the computing device to perform or control performance of operations that comprise: process a first relation to retain a set of tuples in the first relation, wherein the set of tuples includes at least one of a fully dominated tuple, a locally dominated tuple, and a non-locally dominated tuple in the first relation, wherein the retained set of tuples comprises a first set of tuples that corresponds to the fully dominated tuple in the first relation, and wherein the first relation includes a first join attribute and a plurality of first existence probability attributes; process a second relation to retain another set of tuples in the second relation, wherein the another set of tuples includes at least one of a fully dominated tuple, a locally dominated tuple, and a non-locally dominated tuple in the second relation, wherein the retained another set of tuples comprises a second set of tuples that corresponds to the locally dominated tuple in the second relation, wherein the second relation includes a second join attribute compatible with the first join attribute and a plurality of second existence probability attributes, and wherein the first join attribute is compatible with the second joined attribute based at least on a logical relationship between the first join attribute and the second join attribute; generate a joined relation based on the first relation and the second relation, wherein the joined relation comprises a first joined tuple which is joined based on a tuple from the first set of tuples and a tuple from the second set of tuples, and wherein the joined relation further comprises a skyline probability attribute based, at least in part, on a product of a value of the plurality of first existence probability attributes and a value of plurality of the second existence probability attributes; and select the preferred data set from the joined relation based on a comparison of a first value of the skyline probability attribute and a skyline probability threshold; compare a first joined tuple with one or more target tuples in the joined relation to determine whether the first joined tuple is fully dominated by the one or more target tuples, wherein the one or more target tuples comprise tuples formed by joining the tuple from the second set of tuples with the set of tuples in the first relation; and select the first joined tuple based on a determination that the first joined tuple is not dominated by the one or more target tuples, wherein the comparison of the first joined tuple with the one or more target tuples in the joined relation eliminates unnecessary comparisons with tuples formed by joining one or more tuples from the set of tuples in the first relation with one or more tuples from the another set of tuples in the second relation. | 10. A non-transitory computer-readable storage medium encoded with computer-executable instructions to select a preferred data set, which in response to execution by a computing device, cause the computing device to perform or control performance of operations that comprise: process a first relation to retain a set of tuples in the first relation, wherein the set of tuples includes at least one of a fully dominated tuple, a locally dominated tuple, and a non-locally dominated tuple in the first relation, wherein the retained set of tuples comprises a first set of tuples that corresponds to the fully dominated tuple in the first relation, and wherein the first relation includes a first join attribute and a plurality of first existence probability attributes; process a second relation to retain another set of tuples in the second relation, wherein the another set of tuples includes at least one of a fully dominated tuple, a locally dominated tuple, and a non-locally dominated tuple in the second relation, wherein the retained another set of tuples comprises a second set of tuples that corresponds to the locally dominated tuple in the second relation, wherein the second relation includes a second join attribute compatible with the first join attribute and a plurality of second existence probability attributes, and wherein the first join attribute is compatible with the second joined attribute based at least on a logical relationship between the first join attribute and the second join attribute; generate a joined relation based on the first relation and the second relation, wherein the joined relation comprises a first joined tuple which is joined based on a tuple from the first set of tuples and a tuple from the second set of tuples, and wherein the joined relation further comprises a skyline probability attribute based, at least in part, on a product of a value of the plurality of first existence probability attributes and a value of plurality of the second existence probability attributes; and select the preferred data set from the joined relation based on a comparison of a first value of the skyline probability attribute and a skyline probability threshold; compare a first joined tuple with one or more target tuples in the joined relation to determine whether the first joined tuple is fully dominated by the one or more target tuples, wherein the one or more target tuples comprise tuples formed by joining the tuple from the second set of tuples with the set of tuples in the first relation; and select the first joined tuple based on a determination that the first joined tuple is not dominated by the one or more target tuples, wherein the comparison of the first joined tuple with the one or more target tuples in the joined relation eliminates unnecessary comparisons with tuples formed by joining one or more tuples from the set of tuples in the first relation with one or more tuples from the another set of tuples in the second relation. 11. The computer-readable storage medium of claim 10 , wherein the operations further comprise: process the first relation to retain a third set of tuples in the first relation which are non-fully dominated tuples, wherein the non-fully dominated tuples of the third set include at least one of the locally dominated tuple and the non-locally dominated tuple of the first relation. | 0.501309 |
8,332,231 | 1 | 12 | 1. A computer-implemented method for operating an interactive response system comprising: receiving data representing a multi-utterance transaction with a person, the data having multiple elements, a subset of the elements including sensitive customer data; portioning the multi-utterance transaction into discrete, logical utterance units; automatically presenting the utterance units in perceptible form through a routing device and an analyst interface to each of a number of intent analysts, the utterance units being distributed so that no intent analyst is ever exposed to more than one of said subset of the elements including sensitive customer data; accepting intent input from each intent analyst through the respective analyst user interface, where the intent input characterizes the intent analyst's interpretation of the person's intent expressed in the utterance unit; and using a processor, automatically communicating a message to the person, in perceptible form and in substantially real time relative to the receiving step, the message being automatically selected from among a predetermined set of possible messages as a function of the intent input accepted from the intent analysts. | 1. A computer-implemented method for operating an interactive response system comprising: receiving data representing a multi-utterance transaction with a person, the data having multiple elements, a subset of the elements including sensitive customer data; portioning the multi-utterance transaction into discrete, logical utterance units; automatically presenting the utterance units in perceptible form through a routing device and an analyst interface to each of a number of intent analysts, the utterance units being distributed so that no intent analyst is ever exposed to more than one of said subset of the elements including sensitive customer data; accepting intent input from each intent analyst through the respective analyst user interface, where the intent input characterizes the intent analyst's interpretation of the person's intent expressed in the utterance unit; and using a processor, automatically communicating a message to the person, in perceptible form and in substantially real time relative to the receiving step, the message being automatically selected from among a predetermined set of possible messages as a function of the intent input accepted from the intent analysts. 12. The method of claim 1 , wherein the presentation to the intent analysts occurs in at least two geographically diverse locations. | 0.80758 |
8,452,099 | 9 | 11 | 9. The method of claim 1 , further comprising: receiving, by the processor, an image of unknown text having a given text type; inputting the image of the unknown text, by the processor, into each OCR engine; receiving output text corresponding to the image of the unknown text, by the processor, from each OCR engine; where the output text received from each OCR engine is not identical, selecting the output text to use as at least provisionally correct for the unknown text, by the processor, based on the confidence values of the OCR engines for the given text type of the unknown text. | 9. The method of claim 1 , further comprising: receiving, by the processor, an image of unknown text having a given text type; inputting the image of the unknown text, by the processor, into each OCR engine; receiving output text corresponding to the image of the unknown text, by the processor, from each OCR engine; where the output text received from each OCR engine is not identical, selecting the output text to use as at least provisionally correct for the unknown text, by the processor, based on the confidence values of the OCR engines for the given text type of the unknown text. 11. The method of claim 9 , wherein selecting the output text to use comprises: for each OCR engine, setting a weight for the output text received from the OCR engine as equal to the confidence value of the OCR engine for the given text type of the unknown text; where the output text received from two or more OCR engines of the plurality of OCR engines is identical, summing the weights for the two or more OCR engines as the weight for the output text received from the two or more OCR engines; and, selecting the output text having a highest weight. | 0.5 |
9,852,182 | 1 | 2 | 1. A database controller for a database of information encoded as a set of data items distributed among a plurality of storage units distinguishable from one another by respective identifying information and each data item comprising a value of each of two or more data elements, the set of data items having a prescribed order of the two or more data elements of which the first one or two data elements are assigned as a prefix portion, the database controller comprising computing hardware including a processor and a memory coupled to the processor and storing processing instructions which when executed by the processor cause the processor to execute a process, the process comprising: receiving a range query specifying a value of the or each of one or more data elements as a search prefix portion which each data item returned as a range query result must include in its prefix portion; storing an ordered list comprising, for each of the data items from the set of data items individually, the identifying information of a storage unit upon which the data item is stored, the order of the identifying information being determined by an ordering metric applied to prefix portions of the respective data items; maintaining a frequency record, recording values of the data elements assigned as prefix portions of the set of data items and the number of data items having each prefix portion, the frequency record being maintained in an order determined by applying the ordering metric to the prefix portion of the data items; calculating, based on the frequency record, one or more list positions in the ordered list at which the identifying information of the plurality of storage units upon which data items including the search prefix portion in their prefix portion are stored, comprising calculating a start point of the one or more list positions by summing the numbers of data items having prefix portions preceding the search prefix portion in the order determined by the ordering metric, and calculating the end point of the one or more list positions by adding the number of data items having prefix portions including the search prefix portion to the start point; and requesting the data items including the search prefix portion in their prefix portion from the plurality of storage units identified in the calculated one or more list positions, wherein the ordered list is periodically updated based on information received from the plurality of storage units, and, after each update, each occupied list position in the ordered list is succeeded by a predetermined number of vacant list positions; and the process further comprises, when a new data item is added to the set of data items or a duplicate set, adding the identifying information of a storage unit upon which the new data item is stored to a vacant list position in the respective ordered list, the vacant list position being determined by applying the ordering metric to the prefix portion of the new data item in relation to the prefix portions of the respective occupied list positions by referring to the frequency record, such that the immediately preceding occupied list position stores the identifying information of a data item having a prefix preceding or equal to the prefix of the new data item according to the ordering metric, and the immediately following occupied list position stores the identifying information of a data item having a prefix following or equal to the prefix of the new data item according to the ordering metric. | 1. A database controller for a database of information encoded as a set of data items distributed among a plurality of storage units distinguishable from one another by respective identifying information and each data item comprising a value of each of two or more data elements, the set of data items having a prescribed order of the two or more data elements of which the first one or two data elements are assigned as a prefix portion, the database controller comprising computing hardware including a processor and a memory coupled to the processor and storing processing instructions which when executed by the processor cause the processor to execute a process, the process comprising: receiving a range query specifying a value of the or each of one or more data elements as a search prefix portion which each data item returned as a range query result must include in its prefix portion; storing an ordered list comprising, for each of the data items from the set of data items individually, the identifying information of a storage unit upon which the data item is stored, the order of the identifying information being determined by an ordering metric applied to prefix portions of the respective data items; maintaining a frequency record, recording values of the data elements assigned as prefix portions of the set of data items and the number of data items having each prefix portion, the frequency record being maintained in an order determined by applying the ordering metric to the prefix portion of the data items; calculating, based on the frequency record, one or more list positions in the ordered list at which the identifying information of the plurality of storage units upon which data items including the search prefix portion in their prefix portion are stored, comprising calculating a start point of the one or more list positions by summing the numbers of data items having prefix portions preceding the search prefix portion in the order determined by the ordering metric, and calculating the end point of the one or more list positions by adding the number of data items having prefix portions including the search prefix portion to the start point; and requesting the data items including the search prefix portion in their prefix portion from the plurality of storage units identified in the calculated one or more list positions, wherein the ordered list is periodically updated based on information received from the plurality of storage units, and, after each update, each occupied list position in the ordered list is succeeded by a predetermined number of vacant list positions; and the process further comprises, when a new data item is added to the set of data items or a duplicate set, adding the identifying information of a storage unit upon which the new data item is stored to a vacant list position in the respective ordered list, the vacant list position being determined by applying the ordering metric to the prefix portion of the new data item in relation to the prefix portions of the respective occupied list positions by referring to the frequency record, such that the immediately preceding occupied list position stores the identifying information of a data item having a prefix preceding or equal to the prefix of the new data item according to the ordering metric, and the immediately following occupied list position stores the identifying information of a data item having a prefix following or equal to the prefix of the new data item according to the ordering metric. 2. A database controller according to claim 1 , wherein the set of data items is duplicated one or more times, with each duplicate set storing the same database of information as the set of data items and having a different fixed order and different one or two data elements assigned as a prefix portion from that of the set of data items; the process further comprising: storing an ordered list for each duplicate set, the ordered list comprising, for each of the data items from the duplicate set of data items individually, the identifying information of the storage unit upon which the duplicate data item is stored, the order of the identifying information being determined by an ordering metric applied to the prefix portions of the respective duplicate data items; and maintaining a frequency record for each duplicate set, recording the prefix portions of the duplicate set and the number of duplicate data items having each prefix. | 0.589878 |
8,862,543 | 13 | 17 | 13. The article of manufacture of claim 12 , wherein the relevancy parameters are selected from a group consisting: a hit-score, a version number, a latest version number, a maximum possible quality rating, a weight for a version number, a weight for version label, a weight for proximity based upon a security principle, a weight for quality rating, a weight for hit-score, and one or more artifact containers containing the retrieved artifacts. | 13. The article of manufacture of claim 12 , wherein the relevancy parameters are selected from a group consisting: a hit-score, a version number, a latest version number, a maximum possible quality rating, a weight for a version number, a weight for version label, a weight for proximity based upon a security principle, a weight for quality rating, a weight for hit-score, and one or more artifact containers containing the retrieved artifacts. 17. The article of manufacture of claim 13 , wherein a fourth computed score associated with the relevancy parameters is calculated by computing a ratio of the quality rating and the maximum possible quality rating for each artifact associated with the identifier retrieved from the primary repository; computing a product of the ratio and the weight for the quality rating for each artifact; and computing a sum of the product and the third computed score. | 0.5 |
8,316,001 | 7 | 8 | 7. A method according to claim 2 , wherein the specified criteria include a histogram analysis of frequency of occurrence of an attribute of patents identified in the search results web page. | 7. A method according to claim 2 , wherein the specified criteria include a histogram analysis of frequency of occurrence of an attribute of patents identified in the search results web page. 8. A method according to claim 7 , wherein the histogram analysis is selectable from among attributes including assignees, current assignees, and inventors of the patents. | 0.5 |
9,436,915 | 1 | 12 | 1. A diagnosis support apparatus comprising: an inference unit configured to, based on a plurality of pieces of medical information, calculate an inference probability with respect to plural candidates of diagnosis name concerning medical diagnosis; a calculation unit configured to calculate, for a plurality of partial sets, each including, as an element, at least one piece of medical information retrieved from the plurality of pieces of medical information, a degree of effect on a respective inference probability of at least one of the plural candidates of diagnosis name, the calculation unit being configured to calculate the degree of effect individually for the at least one of the plural candidates of diagnosis name; and a display control unit configured to cause a display unit to display, as an inference result, the at least one of the plural candidates of diagnosis name, wherein the at least one of the plural candidates is specified based on the inference probability calculated by the inference unit, and to cause the display unit to display medical information included in a partial set of information retrieved from the plurality of pieces of medical information, wherein the partial set including the displayed medical information is retrieved from the plurality of pieces of medical information, based on the degree of effect calculated by the calculation unit based on the inference result. | 1. A diagnosis support apparatus comprising: an inference unit configured to, based on a plurality of pieces of medical information, calculate an inference probability with respect to plural candidates of diagnosis name concerning medical diagnosis; a calculation unit configured to calculate, for a plurality of partial sets, each including, as an element, at least one piece of medical information retrieved from the plurality of pieces of medical information, a degree of effect on a respective inference probability of at least one of the plural candidates of diagnosis name, the calculation unit being configured to calculate the degree of effect individually for the at least one of the plural candidates of diagnosis name; and a display control unit configured to cause a display unit to display, as an inference result, the at least one of the plural candidates of diagnosis name, wherein the at least one of the plural candidates is specified based on the inference probability calculated by the inference unit, and to cause the display unit to display medical information included in a partial set of information retrieved from the plurality of pieces of medical information, wherein the partial set including the displayed medical information is retrieved from the plurality of pieces of medical information, based on the degree of effect calculated by the calculation unit based on the inference result. 12. The diagnosis support apparatus according to claim 1 , wherein the inference unit obtains at least one of the plural candidates of diagnosis name as an inference result based on inference probabilities calculated for the plural candidates of diagnosis name respectively. | 0.804565 |
8,892,479 | 12 | 13 | 12. One or more computer readable memories storing information to enable a computing device to perform a process comprising: using a plurality of electromyography (EMG) sensors arbitrarily arranged on a user's forearm to obtain samples of EMG signals generated by muscle contractions of a user while the user is performing one or more predefined finger gestures; monitoring the predefined finger gestures using a secondary input mechanism to verify that correct gestures were performed; extracting feature samples from the sampled EMG signals and labeling feature samples according to the corresponding finger gestures that have been verified as correct by the secondary input mechanism; training a machine learning model with the labeled feature samples; and using the trained machine learning model to evaluate EMG signal samples obtained during arbitrary finger gestures to identify those arbitrary finger gestures relative to one or more of the predefined finger gestures performed by the user. | 12. One or more computer readable memories storing information to enable a computing device to perform a process comprising: using a plurality of electromyography (EMG) sensors arbitrarily arranged on a user's forearm to obtain samples of EMG signals generated by muscle contractions of a user while the user is performing one or more predefined finger gestures; monitoring the predefined finger gestures using a secondary input mechanism to verify that correct gestures were performed; extracting feature samples from the sampled EMG signals and labeling feature samples according to the corresponding finger gestures that have been verified as correct by the secondary input mechanism; training a machine learning model with the labeled feature samples; and using the trained machine learning model to evaluate EMG signal samples obtained during arbitrary finger gestures to identify those arbitrary finger gestures relative to one or more of the predefined finger gestures performed by the user. 13. The computer readable memories of claim 12 wherein the trained machine learning model: evaluates a sequence of two or more successive EMG signal samples to identify arbitrary finger gestures corresponding to each sample; aggregates each sequential identified arbitrary finger gesture; and evaluates the aggregate identifications to identify a single arbitrary finger gesture corresponding to the sequence of two or more successive EMG signal samples. | 0.5 |
8,909,513 | 9 | 14 | 9. A system comprising: one or more computers programmed to perform operations comprising: selecting one or more segments from a text field, wherein each of the segments is in proximity to a current position of an input cursor in the text field; analyzing the segments to determine a respective context for each of the segments, wherein the context is at least one of a respective target subtext or a respective target meaning of the segment; for one or more of the segments, identifying a respective candidate emoticon for the segment based on an association between the candidate emoticon and the context of the segment, the association exceeding a threshold value and being based on, at least, statistical usage of the candidate emoticon for the context by one or more users, wherein a strength of the association varies according to the statistical usage; providing one or more of the candidate emoticons for user selection, the candidate emoticons for user selection being based on at least one of a user preference, user-related information, and recipient-related information; receiving user selection of one or more of the provided emoticons and inserting the selected emoticons into the text field at the current position of the input cursor; and updating the statistical usage of at least one of the provided emoticons based on the user selection. | 9. A system comprising: one or more computers programmed to perform operations comprising: selecting one or more segments from a text field, wherein each of the segments is in proximity to a current position of an input cursor in the text field; analyzing the segments to determine a respective context for each of the segments, wherein the context is at least one of a respective target subtext or a respective target meaning of the segment; for one or more of the segments, identifying a respective candidate emoticon for the segment based on an association between the candidate emoticon and the context of the segment, the association exceeding a threshold value and being based on, at least, statistical usage of the candidate emoticon for the context by one or more users, wherein a strength of the association varies according to the statistical usage; providing one or more of the candidate emoticons for user selection, the candidate emoticons for user selection being based on at least one of a user preference, user-related information, and recipient-related information; receiving user selection of one or more of the provided emoticons and inserting the selected emoticons into the text field at the current position of the input cursor; and updating the statistical usage of at least one of the provided emoticons based on the user selection. 14. The system of claim 9 wherein a particular segment comprises at least one of a word, a sentence fragment, a sentence, a phrase, and a passage that precedes or follows the current position of the input cursor. | 0.665615 |
7,788,274 | 25 | 29 | 25. A non-transitory computer-readable storage medium on which is encoded executable program code for category-based search, the program code comprising: program code for identifying an event comprising a user interaction with an article stored on a storage device of a client device responsive to monitoring user interactions with the client device; program code for identifying an event schema describing a format of the identified event responsive at least in part to an article type of the article, the schema comprising fields based on the article type and fields that describe interactions with the article; program code for identifying a plurality of attributes associated with the identified event that correspond to the fields based on the article type and fields that describe interactions with the article, the plurality of attributes identified responsive to the article and the monitored user interactions; program code for determining at least a first category associated with the article based at least in part on the attributes; program code for storing at least a first association data record, the association data record comprising a category-article pair identifier associating the first category and an article identifier identifying the article; program code for receiving an implicit search query; program code for causing the implicit search query to be executed on a data store comprising the first association data record; and program code for receiving the first association data record from the data store. | 25. A non-transitory computer-readable storage medium on which is encoded executable program code for category-based search, the program code comprising: program code for identifying an event comprising a user interaction with an article stored on a storage device of a client device responsive to monitoring user interactions with the client device; program code for identifying an event schema describing a format of the identified event responsive at least in part to an article type of the article, the schema comprising fields based on the article type and fields that describe interactions with the article; program code for identifying a plurality of attributes associated with the identified event that correspond to the fields based on the article type and fields that describe interactions with the article, the plurality of attributes identified responsive to the article and the monitored user interactions; program code for determining at least a first category associated with the article based at least in part on the attributes; program code for storing at least a first association data record, the association data record comprising a category-article pair identifier associating the first category and an article identifier identifying the article; program code for receiving an implicit search query; program code for causing the implicit search query to be executed on a data store comprising the first association data record; and program code for receiving the first association data record from the data store. 29. The computer-readable storage medium of claim 25 , wherein program code for determining at least a first category associated with the article further comprises program code for creating the category. | 0.77191 |
8,421,823 | 13 | 18 | 13. Method comprising: capturing an image of a viewer of a first audio video display using a camera associated with the first audio video display; presenting on the display an emotion presentation user interface (UI), the UI including a first selector element selectable to cause an actual image of a viewer of the display as captured by a camera to be overlaid onto video, the UI including a second selector element selectable by a user to cause an emoticon to be overlaid onto video, the emoticon being established by the processor responsive to selection of the second selector element to match closely as possible the actual image of the viewer as captured by the camera and processed by the processor executing a recognition engine; and responsive to user selection of the first or second selector element, presenting the actual image of the viewer or the emoticon, respectively. | 13. Method comprising: capturing an image of a viewer of a first audio video display using a camera associated with the first audio video display; presenting on the display an emotion presentation user interface (UI), the UI including a first selector element selectable to cause an actual image of a viewer of the display as captured by a camera to be overlaid onto video, the UI including a second selector element selectable by a user to cause an emoticon to be overlaid onto video, the emoticon being established by the processor responsive to selection of the second selector element to match closely as possible the actual image of the viewer as captured by the camera and processed by the processor executing a recognition engine; and responsive to user selection of the first or second selector element, presenting the actual image of the viewer or the emoticon, respectively. 18. The method of claim 13 , comprising presenting audio captured by a microphone associated with the first audio video display along with the emoticon. | 0.512821 |
9,976,859 | 1 | 2 | 1. A method comprising: receiving, by use of a communication device, a request for navigation data from a mobile device, the request having a type; determining, by a processor coupled with the communication device, the type of the request, wherein the type of request is (a) a display request, (b) a route request, (c) a name request, or (d) some combination thereof; generating, by the processor responsive to receipt of the request, a query; generating, by the processor responsive to receipt of the query, a virtual table, the virtual table generated based on (a) one or more parameters determined based on the determined type of the request from the mobile device and (b) a navigation database, coupled with the processor, in which a set of navigation data is stored, the generated virtual table comprising at least a subset of the set of navigation data stored in the navigation database and independent from schema of the navigation database, the subset being determined by the determined type of the request, the generated virtual table and the navigation database being accessible via a same query format; querying, by the processor using the query format, the virtual table based on the request for navigation data to obtain the requested navigation data therefrom; constructing, by the processor, a map tile command based on the obtained navigation data; and sending, by the communication device, the map tile command to the mobile device. | 1. A method comprising: receiving, by use of a communication device, a request for navigation data from a mobile device, the request having a type; determining, by a processor coupled with the communication device, the type of the request, wherein the type of request is (a) a display request, (b) a route request, (c) a name request, or (d) some combination thereof; generating, by the processor responsive to receipt of the request, a query; generating, by the processor responsive to receipt of the query, a virtual table, the virtual table generated based on (a) one or more parameters determined based on the determined type of the request from the mobile device and (b) a navigation database, coupled with the processor, in which a set of navigation data is stored, the generated virtual table comprising at least a subset of the set of navigation data stored in the navigation database and independent from schema of the navigation database, the subset being determined by the determined type of the request, the generated virtual table and the navigation database being accessible via a same query format; querying, by the processor using the query format, the virtual table based on the request for navigation data to obtain the requested navigation data therefrom; constructing, by the processor, a map tile command based on the obtained navigation data; and sending, by the communication device, the map tile command to the mobile device. 2. The method of claim 1 , wherein the display request further includes a tile render request, a region render request, a tile vector request, or some combination thereof. | 0.590909 |
9,905,220 | 1 | 8 | 1. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: accessing, by the one or more computers, a neural network that has been trained, using speech in each of multiple languages, to be able to provide prosody information for each of the multiple languages; providing, by the one or more computers, input to the neural network that includes (i) a representation of a text in a first language and (ii) a language identifier for the first language; generating, by the one or more computers, audio data for a synthesized utterance of the text in the first language based on prosody information for the text that is output by the neural network in response to receiving the representation of the text and the language identifier for the first language; and providing, by the one or more computers, the audio data for the synthesized utterance of the text in the first language. | 1. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: accessing, by the one or more computers, a neural network that has been trained, using speech in each of multiple languages, to be able to provide prosody information for each of the multiple languages; providing, by the one or more computers, input to the neural network that includes (i) a representation of a text in a first language and (ii) a language identifier for the first language; generating, by the one or more computers, audio data for a synthesized utterance of the text in the first language based on prosody information for the text that is output by the neural network in response to receiving the representation of the text and the language identifier for the first language; and providing, by the one or more computers, the audio data for the synthesized utterance of the text in the first language. 8. The system of claim 1 , wherein generating, by the one or more computers, audio data for the synthesized utterance of the text in the first language comprises generating the audio data using the prosody information for the text that is output by the neural network and audio coefficients representing synthesized speech characteristics. | 0.807167 |
7,721,259 | 14 | 16 | 14. A method for generation of customized metadata variants of a software application, the method comprising: generating, with a processor associated with a computing device, custom rule metadata configured to be overlaid on base rule metadata and to characterize a variant of the software application; analyzing, with the processor associated with a computing device, the custom rule metadata and the base rule metadata with regard to constraint metadata; and associating, with a processor associated with a computing device, the custom rule metadata with one or more execution context parameters, the execution context parameters being configured for selecting the custom rule metadata from among a plurality of custom rule metadata at runtime of the software application. | 14. A method for generation of customized metadata variants of a software application, the method comprising: generating, with a processor associated with a computing device, custom rule metadata configured to be overlaid on base rule metadata and to characterize a variant of the software application; analyzing, with the processor associated with a computing device, the custom rule metadata and the base rule metadata with regard to constraint metadata; and associating, with a processor associated with a computing device, the custom rule metadata with one or more execution context parameters, the execution context parameters being configured for selecting the custom rule metadata from among a plurality of custom rule metadata at runtime of the software application. 16. The method of claim 14 , further including analyzing the custom rule metadata and base rule metadata with regard to relationship metadata. | 0.605556 |
8,107,727 | 12 | 13 | 12. The method according to claim 8 , wherein the second extracting includes extracting second positional information that indicates a position of the second character information; and the storing includes storing the second positional information in association with the second character information. | 12. The method according to claim 8 , wherein the second extracting includes extracting second positional information that indicates a position of the second character information; and the storing includes storing the second positional information in association with the second character information. 13. The method according to claim 12 , wherein the outputting includes outputting the second character information by arranging the second character information at the second positional information. | 0.5 |
8,676,565 | 19 | 23 | 19. A method implemented by one or more computer processors, the method comprising: receiving an input that specifies a particular semantic graph of user utterances that is based on a linguistic analysis; processing a corpus that is a historical log of user utterances, the processing performed using the specified semantic graph of user utterances and one or more other semantic graphs of user utterances that are part of semantic clusters that are formed for like topics; and outputting a result of the processing in a user interface. | 19. A method implemented by one or more computer processors, the method comprising: receiving an input that specifies a particular semantic graph of user utterances that is based on a linguistic analysis; processing a corpus that is a historical log of user utterances, the processing performed using the specified semantic graph of user utterances and one or more other semantic graphs of user utterances that are part of semantic clusters that are formed for like topics; and outputting a result of the processing in a user interface. 23. A method as described in claim 19 , wherein the user interface is configured to allow an agent to respond to the input. | 0.797697 |
8,230,016 | 4 | 5 | 4. The method of claim 1 , further comprising: storing the at least one component reference table for the application; and mapping the at least one component associated with each of the identifiers included in the at least one component reference table to the application. | 4. The method of claim 1 , further comprising: storing the at least one component reference table for the application; and mapping the at least one component associated with each of the identifiers included in the at least one component reference table to the application. 5. The method of claim 4 , wherein the indication that the user selected the user recommendation control is an indication that the user recommended the application, and further comprising: generating a user interface screen based on the mapped components included in the at least one component reference table stored for the application, the user interface screen identifying the components of the application; and responsive to receiving the indication that the user recommended the application, using the user interface screen to query the user to select at least one of the components applicable to the recommendation. | 0.5 |
9,021,372 | 1 | 2 | 1. A method comprising: at a computer system having one or more processors and memory storing one or more programs: sending messages in a first set of conversation messages for display; selecting, without user involvement, a second set of conversation messages by: parsing a hierarchy of sets of conversation messages including the first set of conversation messages and the second set of conversation messages, or determining that the second set of conversation messages is similar to the first set of conversation messages; wherein a combined number of messages in the first and second sets of conversation messages total at least a predetermined number of messages; and sending messages in the second set of conversation messages for concurrent display with the messages in the first set of conversation messages. | 1. A method comprising: at a computer system having one or more processors and memory storing one or more programs: sending messages in a first set of conversation messages for display; selecting, without user involvement, a second set of conversation messages by: parsing a hierarchy of sets of conversation messages including the first set of conversation messages and the second set of conversation messages, or determining that the second set of conversation messages is similar to the first set of conversation messages; wherein a combined number of messages in the first and second sets of conversation messages total at least a predetermined number of messages; and sending messages in the second set of conversation messages for concurrent display with the messages in the first set of conversation messages. 2. The method of claim 1 , wherein the first set of conversation messages and the second set of conversation messages originate from chat rooms. | 0.794872 |
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