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8,787,494 | 3 | 7 | 3. The method of claim 2 , wherein the set of polynomial basis functions includes a set of orthogonal basis functions. | 3. The method of claim 2 , wherein the set of polynomial basis functions includes a set of orthogonal basis functions. 7. The method of claim 3 , wherein the second predistorter model is a set of power basis functions, and wherein the conversion function is a matrix. | 0.5 |
9,141,200 | 1 | 5 | 1. An electronic device, comprising: a display; a touch-sensitive keyboard; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying a text entry area on the display; detecting a first input on the touch-sensitive keyboard, the touch-sensitive keyboard including one or more character keys; in accordance with a determination that the first input corresponds to activation of a character key on the touch-sensitive keyboard, entering a first character corresponding to the character key into the text entry area; in accordance with a determination that the first input corresponds to a first portion of a character drawn on the touch-sensitive keyboard and in accordance with detecting that the first input starts in a predefined region of the touch-sensitive keyboard that is a smaller subset of area than the entire keyboard area and that includes one or more character keys: determining one or more candidate characters for the drawn first portion of the character; and displaying a candidate character selection interface on the display, including displaying at least one of the candidate characters in the candidate character selection interface; while displaying the candidate character selection interface on the display, detecting a second input that selects a respective candidate character within the candidate character selection interface; and in response to detecting the second input, entering the selected respective candidate character into the text entry area. | 1. An electronic device, comprising: a display; a touch-sensitive keyboard; one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: displaying a text entry area on the display; detecting a first input on the touch-sensitive keyboard, the touch-sensitive keyboard including one or more character keys; in accordance with a determination that the first input corresponds to activation of a character key on the touch-sensitive keyboard, entering a first character corresponding to the character key into the text entry area; in accordance with a determination that the first input corresponds to a first portion of a character drawn on the touch-sensitive keyboard and in accordance with detecting that the first input starts in a predefined region of the touch-sensitive keyboard that is a smaller subset of area than the entire keyboard area and that includes one or more character keys: determining one or more candidate characters for the drawn first portion of the character; and displaying a candidate character selection interface on the display, including displaying at least one of the candidate characters in the candidate character selection interface; while displaying the candidate character selection interface on the display, detecting a second input that selects a respective candidate character within the candidate character selection interface; and in response to detecting the second input, entering the selected respective candidate character into the text entry area. 5. The device of claim 1 , including instructions for: detecting activation of a plurality of character keys on the touch-sensitive keyboard, the plurality of activated character keys corresponding to a romanization of one or more characters; identifying two or more candidate characters corresponding to the romanization; displaying at least one of the identified candidate characters corresponding to the romanization; detecting a third input that corresponds to a character drawn on the touch-sensitive keyboard of a first candidate character corresponding to the romanization; in response to detecting the third input, entering the first candidate character corresponding to the romanization into the text entry area. | 0.626812 |
9,075,861 | 1 | 18 | 1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: providing a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving input entered by a user for identifying desired content items; in response to the input entered by the user, presenting a subset of content items; receiving selection actions of selected content items of the subset from the user; learning preferred descriptive terms of the user by analyzing descriptive terms associated with the selected content items and by analyzing the date, day, and time of the selection actions and the descriptive terms associated with the selected content items to learn a periodicity of user selections of similar content items, wherein similarity of the similar content items is determined by comparing the descriptive terms associated with the selected content items with a previously selected content item, and wherein the periodicity indicates an amount of time between the selection actions of the similar content items relative to a reference point; associating the periodicity with the preferred descriptive terms associated with the similar content items; associating the preferred descriptive terms with the user; determining a measurement collection having measurements associated with the preferred descriptive terms, wherein the measurements represent relative preferences of the user for the preferred descriptive terms, wherein the measurement collection includes groups of the preferred descriptive terms, wherein the relative preferences of the user for the preferred descriptive terms in a particular group are treated as equal and the groups differentiate the relative preferences of the user for the preferred descriptive terms between the groups, and wherein a preferred descriptive term is included in the particular group at least in part based on at least one of (i) smoothing relatively smaller probability weights associated with less commonly expressed preferences of the relative preferences and (ii) aging preferences of the relative preferences of relative preferences captured in a relatively more distant past, and based further on bounding a range of values of the particular group using a relevance scale factor; and in response to receiving subsequent input entered by the user, selecting and ordering a collection of content items by promoting rankings of content items of the collection of content items associated with the preferred descriptive terms of the user according to differentiation provided by the measurement collection and further based on promoting rankings of those content items of the collection of content items associated with the preferred descriptive terms further associated with periodicities similar to the date, day, and time of the subsequent input; wherein at least one of the input and the subsequent input are entered by the user on an input constrained device. | 1. A user-interface method of selecting and presenting a collection of content items in which the presentation is ordered at least in part based on learned user preferences, the method comprising: providing a set of content items, each content item having at least one associated descriptive term to describe the content item; receiving input entered by a user for identifying desired content items; in response to the input entered by the user, presenting a subset of content items; receiving selection actions of selected content items of the subset from the user; learning preferred descriptive terms of the user by analyzing descriptive terms associated with the selected content items and by analyzing the date, day, and time of the selection actions and the descriptive terms associated with the selected content items to learn a periodicity of user selections of similar content items, wherein similarity of the similar content items is determined by comparing the descriptive terms associated with the selected content items with a previously selected content item, and wherein the periodicity indicates an amount of time between the selection actions of the similar content items relative to a reference point; associating the periodicity with the preferred descriptive terms associated with the similar content items; associating the preferred descriptive terms with the user; determining a measurement collection having measurements associated with the preferred descriptive terms, wherein the measurements represent relative preferences of the user for the preferred descriptive terms, wherein the measurement collection includes groups of the preferred descriptive terms, wherein the relative preferences of the user for the preferred descriptive terms in a particular group are treated as equal and the groups differentiate the relative preferences of the user for the preferred descriptive terms between the groups, and wherein a preferred descriptive term is included in the particular group at least in part based on at least one of (i) smoothing relatively smaller probability weights associated with less commonly expressed preferences of the relative preferences and (ii) aging preferences of the relative preferences of relative preferences captured in a relatively more distant past, and based further on bounding a range of values of the particular group using a relevance scale factor; and in response to receiving subsequent input entered by the user, selecting and ordering a collection of content items by promoting rankings of content items of the collection of content items associated with the preferred descriptive terms of the user according to differentiation provided by the measurement collection and further based on promoting rankings of those content items of the collection of content items associated with the preferred descriptive terms further associated with periodicities similar to the date, day, and time of the subsequent input; wherein at least one of the input and the subsequent input are entered by the user on an input constrained device. 18. The method of claim 1 , wherein at least one of receiving input, presenting the subset of content items, receiving the selection actions, analyzing the preferred descriptive terms, determining the measurement collection, and selecting and ordering the collection of content items is performed on a server system remote from the user. | 0.773522 |
9,076,039 | 10 | 12 | 10. A non-transitory computer readable storage medium having program instructions stored thereon that, when executed by a processor, cause the processor to: receive a first spectral signature corresponding to a region of interest (ROI) in the hyperspectral image; create a model search space including two or more models, wherein each of the two or more models corresponds to a subset of spectral signatures in a library; create, for each of the two or more models, a model spectral signature based on the corresponding subset of spectral signatures, wherein each of the model spectral signatures approximates the first spectral signature; calculate a cumulative probability of the first spectral signature indicating presence of a material within the ROI, wherein the cumulative probability is based on a sum of similarity probabilities of models that contain the material as an element; and determine the presence of the material in the ROI based on the cumulative probability. | 10. A non-transitory computer readable storage medium having program instructions stored thereon that, when executed by a processor, cause the processor to: receive a first spectral signature corresponding to a region of interest (ROI) in the hyperspectral image; create a model search space including two or more models, wherein each of the two or more models corresponds to a subset of spectral signatures in a library; create, for each of the two or more models, a model spectral signature based on the corresponding subset of spectral signatures, wherein each of the model spectral signatures approximates the first spectral signature; calculate a cumulative probability of the first spectral signature indicating presence of a material within the ROI, wherein the cumulative probability is based on a sum of similarity probabilities of models that contain the material as an element; and determine the presence of the material in the ROI based on the cumulative probability. 12. The computer readable storage medium of claim 10 , wherein the program instructions further comprise computer readable code that causes the processor to determine a background expected value of the model search space. | 0.693906 |
9,953,651 | 1 | 2 | 1. A speed podcasting method comprising: receiving a podcast of particular subject matter by a processor of a computer from over a computer communications network; speech recognizing an audio portion of the received podcast by the processor of the computer into a transcript of both essential and non-essential words, the essential words comprising nouns and verbs directed to the particular subject matter, the non-essential words comprising articles, adverbs and adjectives not essential to the particular subject matter; parsing, by the processor of the computer, the words of the transcript, filtering the transcript to exclude non-essential words leaving only essential words comprising nouns and verbs, and comparing the parsed words remaining in the filtered transcript with a set of essential words in a data store so as to identify each of the essential word speech recognized and present in the transcript; processing each word parsed in the transcript and matched to an essential word in the data store to index a corresponding audio segment of the audio portion of the podcast; selecting a playback speed for speed podcasting the received podcast; determining a rating corresponding to the selected playback speed; and, playing back each indexed audio segment corresponding to an essential word in the speech recognized transcript matched to a word in the data store and having a rating higher than the determined rating, while excluding from playback all audio segments not indexed to an essential word in the speech recognized transcript and all audio segments indexed to an essential word having a rating lower than the determined rating. | 1. A speed podcasting method comprising: receiving a podcast of particular subject matter by a processor of a computer from over a computer communications network; speech recognizing an audio portion of the received podcast by the processor of the computer into a transcript of both essential and non-essential words, the essential words comprising nouns and verbs directed to the particular subject matter, the non-essential words comprising articles, adverbs and adjectives not essential to the particular subject matter; parsing, by the processor of the computer, the words of the transcript, filtering the transcript to exclude non-essential words leaving only essential words comprising nouns and verbs, and comparing the parsed words remaining in the filtered transcript with a set of essential words in a data store so as to identify each of the essential word speech recognized and present in the transcript; processing each word parsed in the transcript and matched to an essential word in the data store to index a corresponding audio segment of the audio portion of the podcast; selecting a playback speed for speed podcasting the received podcast; determining a rating corresponding to the selected playback speed; and, playing back each indexed audio segment corresponding to an essential word in the speech recognized transcript matched to a word in the data store and having a rating higher than the determined rating, while excluding from playback all audio segments not indexed to an essential word in the speech recognized transcript and all audio segments indexed to an essential word having a rating lower than the determined rating. 2. The method of claim 1 , further comprising: consulting, by the processor of the computer, a thesaurus to retrieve words synonymous with the matched word in the data store of essential words; and, adding, by the processor of the computer, the synonymous words to the data store of essential words. | 0.5 |
8,332,231 | 18 | 30 | 18. A system for processing an interaction with a person, comprising a processor, two or more analyst user interface devices in communication with the processor, and a memory in communication with the processor, the memory storing programming instructions executable by the processor to: receive data representing a multi-utterance transaction with the person, the data having multiple elements, a subset of the elements including sensitive customer data; portion the multi-utterance transaction into discrete, logical utterance units; automatically present the utterance units in perceptible form through the analyst interface devices to 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; accept intent input from each intent analyst through the respective analyst user interface device, where the intent input characterizes the intent analyst's interpretation of the person's intent expressed in the utterance, and where the intent input is prevented from providing information to be communicated to the person; and automatically communicate a message to the person, in perceptible form and in substantially real time relative to the receiving function, the message being automatically selected from among a predetermined set of possible messages as a function of the intent input accepted from the two or more intent analysts. | 18. A system for processing an interaction with a person, comprising a processor, two or more analyst user interface devices in communication with the processor, and a memory in communication with the processor, the memory storing programming instructions executable by the processor to: receive data representing a multi-utterance transaction with the person, the data having multiple elements, a subset of the elements including sensitive customer data; portion the multi-utterance transaction into discrete, logical utterance units; automatically present the utterance units in perceptible form through the analyst interface devices to 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; accept intent input from each intent analyst through the respective analyst user interface device, where the intent input characterizes the intent analyst's interpretation of the person's intent expressed in the utterance, and where the intent input is prevented from providing information to be communicated to the person; and automatically communicate a message to the person, in perceptible form and in substantially real time relative to the receiving function, the message being automatically selected from among a predetermined set of possible messages as a function of the intent input accepted from the two or more intent analysts. 30. The system of claim 18 , wherein the programming instructions are further executable by the processor to objectively rate the speed and accuracy of the intent input from at least one of the intent analysts. | 0.740099 |
9,292,884 | 1 | 8 | 1. A method comprising, by one or more processors associated with one or more computing devices: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the plurality of nodes corresponding to a plurality of users associated with an online social network, respectively; identifying a plurality of non-overlapping clusters in the social graph using graph clustering, each cluster comprising a discrete set of nodes from the plurality of nodes; providing a treatment to at least a first set of users and a second set of users, the first and second sets of users corresponding to a first set of clusters and a second set of clusters of the plurality of clusters, respectively, the first set of clusters being discrete from the second set of clusters; and determining, for each of at least the first and second sets of users, a treatment effect of the treatment on the users of the set of users based on a network exposure to the treatment for each user, wherein, for each respective cluster, the network exposure of the nodes in the cluster is absolute k-neighborhood exposure, absolute k-core exposure, fractional q-neighborhood exposure, or fractional q-core exposure. | 1. A method comprising, by one or more processors associated with one or more computing devices: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the plurality of nodes corresponding to a plurality of users associated with an online social network, respectively; identifying a plurality of non-overlapping clusters in the social graph using graph clustering, each cluster comprising a discrete set of nodes from the plurality of nodes; providing a treatment to at least a first set of users and a second set of users, the first and second sets of users corresponding to a first set of clusters and a second set of clusters of the plurality of clusters, respectively, the first set of clusters being discrete from the second set of clusters; and determining, for each of at least the first and second sets of users, a treatment effect of the treatment on the users of the set of users based on a network exposure to the treatment for each user, wherein, for each respective cluster, the network exposure of the nodes in the cluster is absolute k-neighborhood exposure, absolute k-core exposure, fractional q-neighborhood exposure, or fractional q-core exposure. 8. The method of claim 1 , wherein a node in a particular cluster is network exposed if a threshold fractions of nodes within one degree of separation of the node are in the same treatment condition. | 0.908799 |
9,436,438 | 2 | 7 | 2. The non-transitory computer-accessible memory medium of claim 1 , wherein the program instructions are further executable to perform: analyzing the graphical program, including analyzing the specifications or constraints, thereby producing analysis results; wherein said automatically generating the output program is performed based on the analysis results. | 2. The non-transitory computer-accessible memory medium of claim 1 , wherein the program instructions are further executable to perform: analyzing the graphical program, including analyzing the specifications or constraints, thereby producing analysis results; wherein said automatically generating the output program is performed based on the analysis results. 7. The non-transitory computer-accessible memory medium of claim 2 , wherein the number of tokens consumed and produced are respectively restricted to be 0 or 1 at each phase. | 0.787105 |
9,130,651 | 1 | 2 | 1. An energy harvesting communication device configured with on chip signal booster apparatus; comprising: at least a communication apparatus; at least an antenna apparatus in association with an input and/or output device; at least a processor in communication with at least one of: said at least a communication apparatus; said at least an antenna apparatus; a charge platform in association with at least charging circuit; at least an interactive media in association with at least an interactive interface; an output device; and at least a sensor apparatus embedded in silicon substrate and etched and/or fused in nano-fiber and/or microfiber material, said at least a sensor apparatus in association with said at least a communication apparatus to provide at least one of an effective energy harvesting medium, communication clarity, communication medium, detection selectivity medium, and detection platform. | 1. An energy harvesting communication device configured with on chip signal booster apparatus; comprising: at least a communication apparatus; at least an antenna apparatus in association with an input and/or output device; at least a processor in communication with at least one of: said at least a communication apparatus; said at least an antenna apparatus; a charge platform in association with at least charging circuit; at least an interactive media in association with at least an interactive interface; an output device; and at least a sensor apparatus embedded in silicon substrate and etched and/or fused in nano-fiber and/or microfiber material, said at least a sensor apparatus in association with said at least a communication apparatus to provide at least one of an effective energy harvesting medium, communication clarity, communication medium, detection selectivity medium, and detection platform. 2. The energy harvesting communication device of claim 1 , wherein said input and/or output device further comprises a computer apparatus configured with at least a display apparatus in association with at least one of: at least a keyboard; at least a graphic user interface. | 0.92284 |
7,689,527 | 17 | 19 | 17. The computer-readable medium of claim 11 , wherein for each sequence of the plurality of attribute determination sequences in the training set, identifying the subset of attribute determinations in the attribute determination sequence that is likely to be a false positive comprises a machine learning mechanism receiving, for each input text in a training set of input texts: first data that indicates attribute determinations made by an attribute extractor based on attribute value dictionaries; and second data that indicates accurate attribute determinations or false positive attribute determinations. | 17. The computer-readable medium of claim 11 , wherein for each sequence of the plurality of attribute determination sequences in the training set, identifying the subset of attribute determinations in the attribute determination sequence that is likely to be a false positive comprises a machine learning mechanism receiving, for each input text in a training set of input texts: first data that indicates attribute determinations made by an attribute extractor based on attribute value dictionaries; and second data that indicates accurate attribute determinations or false positive attribute determinations. 19. The computer-readable medium of claim 17 , wherein the machine learning mechanism uses a conditional random field model. | 0.671958 |
8,370,328 | 22 | 35 | 22. An apparatus for creating an electronic database of disambiguated entity mentions from a corpus of electronic documents, comprising: a microprocessor; a data harvesting module comprising program instructions that, when executed by microprocessor, will cause the microprocessor to automatically extract entity mentions from the corpus of electronic documents and parse the entity mentions to produce one or more mention objects; a mention group creation module comprising program instructions that, when executed by microprocessor, will cause the microprocessor to automatically create one or more mention groups by automatically grouping mention objects together according to a distinguishing attribute common to a given class of mention objects; a collection of comparison modules having program instructions that, when executed by microprocessor, will cause the microprocessor to automatically (i) compare every mention object in a selected mention group with every other mention object in the selected mention group to produce a collection of comparison algorithm scores for every pair of mention objects in the selected mention group, and (ii) generate an overall confidence score for every pair of mention objects in the selected mention group based on the collection of comparison algorithm scores for said every pair; and an entity object creation module having program instructions that, when executed by microprocessor, will cause the microprocessor to automatically create in the electronic database one or more new entity objects for the selected mention group by automatically (i) grouping together mention objects with other mention objects, based on the confidence scores of each pair of mention objects and a specified confidence threshold, wherein pairs of mention objects having a confidence score greater than or equal to the specified threshold are assigned to the same new entity object, and (ii) merging previously-created entity objects with other previously-created entity objects, based on the confidence scores of each pair of entity objects, and a specified confidence threshold, wherein pairs of entity objects having a confidence score greater than or equal to the specified threshold are assigned to the same new entity object. | 22. An apparatus for creating an electronic database of disambiguated entity mentions from a corpus of electronic documents, comprising: a microprocessor; a data harvesting module comprising program instructions that, when executed by microprocessor, will cause the microprocessor to automatically extract entity mentions from the corpus of electronic documents and parse the entity mentions to produce one or more mention objects; a mention group creation module comprising program instructions that, when executed by microprocessor, will cause the microprocessor to automatically create one or more mention groups by automatically grouping mention objects together according to a distinguishing attribute common to a given class of mention objects; a collection of comparison modules having program instructions that, when executed by microprocessor, will cause the microprocessor to automatically (i) compare every mention object in a selected mention group with every other mention object in the selected mention group to produce a collection of comparison algorithm scores for every pair of mention objects in the selected mention group, and (ii) generate an overall confidence score for every pair of mention objects in the selected mention group based on the collection of comparison algorithm scores for said every pair; and an entity object creation module having program instructions that, when executed by microprocessor, will cause the microprocessor to automatically create in the electronic database one or more new entity objects for the selected mention group by automatically (i) grouping together mention objects with other mention objects, based on the confidence scores of each pair of mention objects and a specified confidence threshold, wherein pairs of mention objects having a confidence score greater than or equal to the specified threshold are assigned to the same new entity object, and (ii) merging previously-created entity objects with other previously-created entity objects, based on the confidence scores of each pair of entity objects, and a specified confidence threshold, wherein pairs of entity objects having a confidence score greater than or equal to the specified threshold are assigned to the same new entity object. 35. The apparatus of claim 22 , wherein: the entity mentions of the electronic documents in the corpus are not arranged according to a predefined document structure; and the data harvesting module comprises a natural language processor that, when executed by the microprocessor, causes the microprocessor to extract and parse the entity mentions in accordance with a set of natural language rules. | 0.687402 |
8,910,034 | 2 | 12 | 2. The method as claimed in claim 1 , wherein the fragment object includes a third set of data corresponding to a transformation of the document fragment of the source document, further comprising: (f) transforming the decrypted document fragment of the source document based on the third set of data; and (g) incorporating the transformed decrypted document fragment into the referencing document. | 2. The method as claimed in claim 1 , wherein the fragment object includes a third set of data corresponding to a transformation of the document fragment of the source document, further comprising: (f) transforming the decrypted document fragment of the source document based on the third set of data; and (g) incorporating the transformed decrypted document fragment into the referencing document. 12. The method as claimed in claim 2 , wherein the first set of data includes an address corresponding to a location of the encrypted document fragment of the source document. | 0.799771 |
9,304,736 | 5 | 12 | 5. A device comprising: a housing; one or more microphones arranged in the housing to receive verbal input; one or more speakers arranged in the housing; a processor to perform one or more functions; memory accessible by the processor; a control element; and a module stored in the memory and executable by the processor to facilitate non-verbal input of a code through actuation of the control element; and a light indicator arranged to emit light externally of the housing according to multiple appearance states, wherein a first appearance state of the multiple appearance states corresponds to a first value of the code received by actuation of the control element, and a second appearance state of the multiple appearance states corresponds to a second value of the code received by actuation of the control element. | 5. A device comprising: a housing; one or more microphones arranged in the housing to receive verbal input; one or more speakers arranged in the housing; a processor to perform one or more functions; memory accessible by the processor; a control element; and a module stored in the memory and executable by the processor to facilitate non-verbal input of a code through actuation of the control element; and a light indicator arranged to emit light externally of the housing according to multiple appearance states, wherein a first appearance state of the multiple appearance states corresponds to a first value of the code received by actuation of the control element, and a second appearance state of the multiple appearance states corresponds to a second value of the code received by actuation of the control element. 12. The device of claim 5 , further comprising a wireless interface to communicate with a wireless network. | 0.792636 |
8,346,765 | 1 | 6 | 1. A method for generating ranked search results, comprising: receiving a plurality of matching information items that match a search request; ranking at least some of the plurality of matching information items using a linear ranking model that linearly combines a first plurality of feature values to obtain a first set of ranked results, wherein the linear ranking model combines the first plurality of feature values in a linear fashion using weight coefficients corresponding to the first plurality of feature values; ranking at least some of the first set of ranked results using a nonlinear ranking model that nonlinearly combines a second plurality of feature values to obtain a second set of ranked results, wherein the nonlinear ranking model combines the second plurality of feature values in a nonlinear fashion using weight coefficients corresponding to the second plurality of feature values; and providing a search response based on the second set of ranked results. | 1. A method for generating ranked search results, comprising: receiving a plurality of matching information items that match a search request; ranking at least some of the plurality of matching information items using a linear ranking model that linearly combines a first plurality of feature values to obtain a first set of ranked results, wherein the linear ranking model combines the first plurality of feature values in a linear fashion using weight coefficients corresponding to the first plurality of feature values; ranking at least some of the first set of ranked results using a nonlinear ranking model that nonlinearly combines a second plurality of feature values to obtain a second set of ranked results, wherein the nonlinear ranking model combines the second plurality of feature values in a nonlinear fashion using weight coefficients corresponding to the second plurality of feature values; and providing a search response based on the second set of ranked results. 6. The method of claim 1 , wherein at least some of the first plurality of feature values used by the linear ranking model are the same as at least some of the second plurality of feature values used by the nonlinear ranking model. | 0.739278 |
8,769,454 | 1 | 8 | 1. A method for register-transfer level (RTL) design checking for exploring simulation mismatches, synthesis mismatches, or ambiguous language semantics associated with generating a derived design from RTL design code, the method comprising: providing the RTL design code, to at least one processor, to generate an internal representation for verification of an electronic circuit design; comparing, by a design match engine, the RTL design code with design violation patterns contained in a design violation pattern database, wherein the design violation patterns identify violations relating to the simulation mismatches, synthesis mismatches, or ambiguous language semantics associated with generating the derived design that are otherwise undetected during equivalence checking between the derived design and the RTL design code; assigning a rule object to a design pattern in the RTL design code, by the at least one processor, when the design match engine determines that the design pattern in the RTL design code matches one of the design violation patterns in the design violation pattern database; and generating, with the at least one processor, a violation report comprising the rule objects and their corresponding design violation patterns. | 1. A method for register-transfer level (RTL) design checking for exploring simulation mismatches, synthesis mismatches, or ambiguous language semantics associated with generating a derived design from RTL design code, the method comprising: providing the RTL design code, to at least one processor, to generate an internal representation for verification of an electronic circuit design; comparing, by a design match engine, the RTL design code with design violation patterns contained in a design violation pattern database, wherein the design violation patterns identify violations relating to the simulation mismatches, synthesis mismatches, or ambiguous language semantics associated with generating the derived design that are otherwise undetected during equivalence checking between the derived design and the RTL design code; assigning a rule object to a design pattern in the RTL design code, by the at least one processor, when the design match engine determines that the design pattern in the RTL design code matches one of the design violation patterns in the design violation pattern database; and generating, with the at least one processor, a violation report comprising the rule objects and their corresponding design violation patterns. 8. The method of claim 1 , wherein the method further comprises, selecting hi-lighted RTL design code corresponding to one of the rule objects, and graphically displaying on a display the corresponding rule object in the violation report. | 0.78442 |
8,612,466 | 8 | 11 | 8. A non-transitory device readable recording medium storing a device readable program and that, when executed by a computer, makes the computer execute: generating, based on user information represented as a group hierarchy having a user identifier and one or more groups joined by one or more operators, an inclusion relationship expression including an operator that designates an inclusion relationship for access authority; combining the inclusion relationship expression with a received search expression to generate a combined search expression; for searching at a private level, using the combined search expression to generate a first search expression using the received search expression and specifying the user identifier without specifying the one or more groups; and for searching at a shared level, using the combined search expression to generate a second search expression using the received search expression and specifying the one or more groups without specifying the user identifier. | 8. A non-transitory device readable recording medium storing a device readable program and that, when executed by a computer, makes the computer execute: generating, based on user information represented as a group hierarchy having a user identifier and one or more groups joined by one or more operators, an inclusion relationship expression including an operator that designates an inclusion relationship for access authority; combining the inclusion relationship expression with a received search expression to generate a combined search expression; for searching at a private level, using the combined search expression to generate a first search expression using the received search expression and specifying the user identifier without specifying the one or more groups; and for searching at a shared level, using the combined search expression to generate a second search expression using the received search expression and specifying the one or more groups without specifying the user identifier. 11. The non-transitory device readable recording medium storing the device readable program according to claim 8 , that, when executed by a computer, when combining, makes the computer execute: registering the search result generated from executing the first search expression at the private level as a cache item using a hash value generated from the first search expression. | 0.633528 |
8,584,012 | 18 | 19 | 18. A non-transitory computer-readable medium tangibly embodying program code executable by a computer system, the program code comprising: program code for, starting from a first end of a path, iteratively placing along the path each of a first subset of a plurality of glyphs in a first visual order based on determining that each of the first subset of glyphs has a first directional value indicating a first level of bidirectional embedding of the glyph, wherein the first visual order is the order in which the first subset of glyphs are displayed for reading; program code for determining that one of a second subset of the plurality of glyphs has a second directional value indicating a second level of bidirectional embedding of the glyph; program code for, starting from a second end of the path that is opposite to the first end of the path, iteratively placing along the path each of the second subset of glyphs in a second visual order, wherein the second visual order is the order in which the second subset of glyphs are displayed for reading; and program code for redetermining placement points for the second subset of glyphs by, starting from a start point on the path adjacent to the first subset of glyphs as placed on the path, iteratively placing the second subset of glyphs along the path such that the second visual order of the second subset of glyphs is maintained. | 18. A non-transitory computer-readable medium tangibly embodying program code executable by a computer system, the program code comprising: program code for, starting from a first end of a path, iteratively placing along the path each of a first subset of a plurality of glyphs in a first visual order based on determining that each of the first subset of glyphs has a first directional value indicating a first level of bidirectional embedding of the glyph, wherein the first visual order is the order in which the first subset of glyphs are displayed for reading; program code for determining that one of a second subset of the plurality of glyphs has a second directional value indicating a second level of bidirectional embedding of the glyph; program code for, starting from a second end of the path that is opposite to the first end of the path, iteratively placing along the path each of the second subset of glyphs in a second visual order, wherein the second visual order is the order in which the second subset of glyphs are displayed for reading; and program code for redetermining placement points for the second subset of glyphs by, starting from a start point on the path adjacent to the first subset of glyphs as placed on the path, iteratively placing the second subset of glyphs along the path such that the second visual order of the second subset of glyphs is maintained. 19. The non-transitory computer-readable medium of claim 18 , wherein the program code for iteratively placing each glyph comprises: program code for identifying a first point on the path, program code for determining a path segment to be occupied by the glyph and extending from the first point of the path to a second point on the path, program code for associating the glyph with a point on the path segment, and program code for truncating the path by removing the path segment occupied by the glyph. | 0.5 |
8,166,022 | 17 | 18 | 17. A system comprising: a processor coupled to a memory; a database; a query receiver to receive a query for which a query execution plan (QEP) is to be computed, wherein a set comprising all possible QEPs for the query describes a search space, wherein each QEP of the set of possible QEPs references a plurality of quantifiers; a QEP parallel optimizer comprising: a subproblem generator to divide the search space into a plurality of subproblems for which constituent QEPs referencing a smaller number of quantifiers are to be created; generating a skip vector array (SVA) that indicates disjoint quantifier sets between two subproblems; a partitioner to partition the plurality of subproblems into a plurality of partitions, wherein each of the subproblems within a partition references the same number of quantifiers; a process allocator to allocate each of the plurality of partitions to a thread of a plurality of threads within a multiple thread architecture, wherein a partition containing subproblems referencing fewer quantifiers is executed before a partition containing subproblems referencing more quantifiers; receiving from each of the plurality of threads a constituent QEP for each subproblem; and combining two constituents QEPs at the QEP optimizer server to determine a QEP referencing the combined set of quantifiers for the two constituent QEPs. | 17. A system comprising: a processor coupled to a memory; a database; a query receiver to receive a query for which a query execution plan (QEP) is to be computed, wherein a set comprising all possible QEPs for the query describes a search space, wherein each QEP of the set of possible QEPs references a plurality of quantifiers; a QEP parallel optimizer comprising: a subproblem generator to divide the search space into a plurality of subproblems for which constituent QEPs referencing a smaller number of quantifiers are to be created; generating a skip vector array (SVA) that indicates disjoint quantifier sets between two subproblems; a partitioner to partition the plurality of subproblems into a plurality of partitions, wherein each of the subproblems within a partition references the same number of quantifiers; a process allocator to allocate each of the plurality of partitions to a thread of a plurality of threads within a multiple thread architecture, wherein a partition containing subproblems referencing fewer quantifiers is executed before a partition containing subproblems referencing more quantifiers; receiving from each of the plurality of threads a constituent QEP for each subproblem; and combining two constituents QEPs at the QEP optimizer server to determine a QEP referencing the combined set of quantifiers for the two constituent QEPs. 18. The system of claim 17 , wherein the partitioner excludes subproblems that are indicated as not disjoint by the SVA from the plurality of partitions. | 0.5 |
9,786,271 | 10 | 11 | 10. A computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, wherein the one or more computer readable storage media are not transitory signals per se, the program instructions comprising: program instructions to identify a set of vocal variables for a user, by a voice recognition system, based, at least in part, on a user interaction with the voice recognition system, wherein the user interaction includes the user selecting a first language and a second language, and adjusting a level of accent, wherein the level of accent indicates an amount by which the second language affects the user's speaking of the first language; program instructions to generate a voice model of speech patterns that represent the user's speaking of the first language using the identified set of vocal variables, wherein the voice model is adapted to improve recognition of the user's voice by the voice recognition system; program instructions to match the generated voice model to a catalog of speech patterns, and identify a voice model code that represents speech patterns in the catalog that match the generated voice model; program instructions to provide the identified voice model code to the user; program instructions to receive voice input from the user; and program instructions to utilize the generated voice model to improve recognition of the received voice input, based on the user providing the identified voice model code. | 10. A computer program product comprising: one or more computer readable storage media and program instructions stored on the one or more computer readable storage media, wherein the one or more computer readable storage media are not transitory signals per se, the program instructions comprising: program instructions to identify a set of vocal variables for a user, by a voice recognition system, based, at least in part, on a user interaction with the voice recognition system, wherein the user interaction includes the user selecting a first language and a second language, and adjusting a level of accent, wherein the level of accent indicates an amount by which the second language affects the user's speaking of the first language; program instructions to generate a voice model of speech patterns that represent the user's speaking of the first language using the identified set of vocal variables, wherein the voice model is adapted to improve recognition of the user's voice by the voice recognition system; program instructions to match the generated voice model to a catalog of speech patterns, and identify a voice model code that represents speech patterns in the catalog that match the generated voice model; program instructions to provide the identified voice model code to the user; program instructions to receive voice input from the user; and program instructions to utilize the generated voice model to improve recognition of the received voice input, based on the user providing the identified voice model code. 11. The computer program product of claim 10 , further comprising: program instructions to receive voice input and a corresponding voice model code from a second user; and program instructions to utilize a voice model corresponding to the received voice model code in the catalog to improve recognition of the received voice input. | 0.639434 |
9,436,763 | 11 | 15 | 11. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: access, by a web crawler executing on one or more computing systems associated with a social-networking system, a structured document of a network application, the structured document comprising structural information and content comprising one or more embedded scripts and one or more resources or identifiers for the resources; execute, by the web crawler executing on the one or more computing systems, at least some of the content of the structured document; process, by the computing systems, the structured document to generate a model representation of the structured document; track, by the computing systems, one or more interactions resulting from the web crawler's execution of at least some of the content, the interactions comprising one or more outgoing requests sent by one or more of the computing systems or incoming responses received by one or more of the computing systems from one or more third-party servers; create, by the computing systems, a behavior model of the network application based on one or more of the interactions resulting from the web crawler's execution of at least some of the content, the behavior model comprising a first log of outgoing HTTP requests generated by the network application when the content is executed; create, by the computing systems, a second log that comprises an identification of one or more network resources ascertained by filtering the first log; compare, by the computing systems, one or more of the network resources identified in the second log to a list comprising an identification of one or more rogue network resources; by the computing systems, determine, based on the comparison, whether the network application meets one or more requirements of the social-networking system, wherein the one or more requirements comprise avoiding interaction with any of the rogue network resources. | 11. One or more computer-readable non-transitory storage media embodying software that is operable when executed to: access, by a web crawler executing on one or more computing systems associated with a social-networking system, a structured document of a network application, the structured document comprising structural information and content comprising one or more embedded scripts and one or more resources or identifiers for the resources; execute, by the web crawler executing on the one or more computing systems, at least some of the content of the structured document; process, by the computing systems, the structured document to generate a model representation of the structured document; track, by the computing systems, one or more interactions resulting from the web crawler's execution of at least some of the content, the interactions comprising one or more outgoing requests sent by one or more of the computing systems or incoming responses received by one or more of the computing systems from one or more third-party servers; create, by the computing systems, a behavior model of the network application based on one or more of the interactions resulting from the web crawler's execution of at least some of the content, the behavior model comprising a first log of outgoing HTTP requests generated by the network application when the content is executed; create, by the computing systems, a second log that comprises an identification of one or more network resources ascertained by filtering the first log; compare, by the computing systems, one or more of the network resources identified in the second log to a list comprising an identification of one or more rogue network resources; by the computing systems, determine, based on the comparison, whether the network application meets one or more requirements of the social-networking system, wherein the one or more requirements comprise avoiding interaction with any of the rogue network resources. 15. The media of claim 11 , wherein: the software is further operable when executed to process a request to access the network application; and accessing the web crawler is operable to access and render the network application. | 0.713384 |
8,949,865 | 5 | 6 | 5. A method for tracking interactions between a user and an application comprising: retrieving a translation engine; detecting a passive user-generated action occurs and an active user-generated action occurs; generating a first pre-translated event for the passive user generated action using a translation engine application programming interface (API) associated with the translation engine; generating a second pre-translated event for the active user generated action using the translation engine API associated with the translation engine; translating the first pre-translated event and the second pre-translated event to obtain a first translated events, wherein the first translated events are in a format associated with a first tracking system; translating the first pre-translated event and the second pre-translated event to obtain a second translated events, wherein the second translated events are in a format associated with a second tracking system; preparing the first translated events for transmission; preparing the second translated events for transmission; sending the first translated events to the first tracking system; and sending the second translated events to the second tracking system. | 5. A method for tracking interactions between a user and an application comprising: retrieving a translation engine; detecting a passive user-generated action occurs and an active user-generated action occurs; generating a first pre-translated event for the passive user generated action using a translation engine application programming interface (API) associated with the translation engine; generating a second pre-translated event for the active user generated action using the translation engine API associated with the translation engine; translating the first pre-translated event and the second pre-translated event to obtain a first translated events, wherein the first translated events are in a format associated with a first tracking system; translating the first pre-translated event and the second pre-translated event to obtain a second translated events, wherein the second translated events are in a format associated with a second tracking system; preparing the first translated events for transmission; preparing the second translated events for transmission; sending the first translated events to the first tracking system; and sending the second translated events to the second tracking system. 6. The method of claim 5 , wherein preparing the first translated events for transmission to the first tracking system comprises storing the first translated events in an event cache, and wherein sending the first translated events to the first tracking system comprises retrieving the first translated events from the event cache. | 0.561008 |
7,734,627 | 10 | 15 | 10. A similarity detection device comprising: a cluster creation hardware-implemented component that generates clusters of pairs of ordered terms by randomly sampling documents, where a particular pair of ordered terms includes a first term that occurs before a second term in a particular document, and where at least some of the pairs of ordered terms include terms that occur non-consecutively in the particular document, and where the random sampling is biased such that terms closer to one another, as measured based on a number of terms separating two terms, have a greater chance of being included, in a particular cluster, as one of the pairs of ordered terms; an inverted index hardware-implemented component that relates an order of occurrence of pairs of ordered terms to clusters that contain the pairs of ordered terms; an enumeration hardware-implemented component that generates pairs of ordered terms for a first document that is to be compared to the inverted index; a pair lookup hardware-implemented component that looks up the generated pairs of ordered terms in the inverted index to obtain clusters that contain the generated pairs of ordered terms; and a cluster selection hardware-implemented component that selects clusters obtained by the pair lookup component that are similar to the first document. | 10. A similarity detection device comprising: a cluster creation hardware-implemented component that generates clusters of pairs of ordered terms by randomly sampling documents, where a particular pair of ordered terms includes a first term that occurs before a second term in a particular document, and where at least some of the pairs of ordered terms include terms that occur non-consecutively in the particular document, and where the random sampling is biased such that terms closer to one another, as measured based on a number of terms separating two terms, have a greater chance of being included, in a particular cluster, as one of the pairs of ordered terms; an inverted index hardware-implemented component that relates an order of occurrence of pairs of ordered terms to clusters that contain the pairs of ordered terms; an enumeration hardware-implemented component that generates pairs of ordered terms for a first document that is to be compared to the inverted index; a pair lookup hardware-implemented component that looks up the generated pairs of ordered terms in the inverted index to obtain clusters that contain the generated pairs of ordered terms; and a cluster selection hardware-implemented component that selects clusters obtained by the pair lookup component that are similar to the first document. 15. The similarity detection device of claim 10 , where the sampling pairs of terms includes biasing the sampling to give preference to terms that occur in a pre-determined section of the documents. | 0.592593 |
9,501,745 | 1 | 2 | 1. A method for presenting an automated suggestion at a wearable device, the method comprising, with the wearable device: by one or more sensors coupled to the wearable device, receiving one or more real-time inputs indicative of an implicit cue regarding a user-specific physical activity in relation to a surrounding physical environment; by an automated inference engine coupled to the wearable device, accessing the real-time inputs and one more items of previously stored user-specific information; by the automated inference engine, based on a combination of the one or more real-time inputs and the stored user-specific information, generating a plurality of different user-specific contexts, each user-specific context corresponding to an inferred purpose for the user-specific physical activity; by the automated inference engine, algorithmically selecting at least one of the plurality of different user-specific contexts; generating an automated suggestion based on the selected user-specific context; and presenting the automated suggestion by an output device of the wearable device. | 1. A method for presenting an automated suggestion at a wearable device, the method comprising, with the wearable device: by one or more sensors coupled to the wearable device, receiving one or more real-time inputs indicative of an implicit cue regarding a user-specific physical activity in relation to a surrounding physical environment; by an automated inference engine coupled to the wearable device, accessing the real-time inputs and one more items of previously stored user-specific information; by the automated inference engine, based on a combination of the one or more real-time inputs and the stored user-specific information, generating a plurality of different user-specific contexts, each user-specific context corresponding to an inferred purpose for the user-specific physical activity; by the automated inference engine, algorithmically selecting at least one of the plurality of different user-specific contexts; generating an automated suggestion based on the selected user-specific context; and presenting the automated suggestion by an output device of the wearable device. 2. The method of claim 1 , comprising automatically generating the plurality of different user-specific contexts, wherein one or more of the different user-specific contexts relates to an often-repeated situation and one or more of the different user-specific contexts relates to a not-often-repeated situation. | 0.5 |
7,644,057 | 7 | 8 | 7. The computerized text classifier system of claim 1 , wherein the pre-processor selects a script from a plurality of scripts and executes the selected script to identify concepts. | 7. The computerized text classifier system of claim 1 , wherein the pre-processor selects a script from a plurality of scripts and executes the selected script to identify concepts. 8. The computerized text classifier system of claim 7 , wherein at least two of the plurality of scripts correspond to different languages. | 0.715164 |
7,734,287 | 27 | 28 | 27. The method of claim 16 , wherein said instructions conveyed to the onboard vehicle control network allow the onboard vehicle control network to be diagnosed through the graphical display on the portable handheld wireless diagnostic unit. | 27. The method of claim 16 , wherein said instructions conveyed to the onboard vehicle control network allow the onboard vehicle control network to be diagnosed through the graphical display on the portable handheld wireless diagnostic unit. 28. The method of claim 27 , wherein the instructions force individual system components of the onboard vehicle control network into desired output states. | 0.585561 |
7,610,194 | 15 | 21 | 15. An apparatus for reordering items in a database to be retrieved for display to a user, comprising: a module for accepting user input from a keyboard, said user input comprising at least one keypress; a linguistic database (LDB) containing a plurality of words ordered according to a predefined linguistic frequency of use model; a module for displaying to said user a list of any words in said LDB and any user-defined words in a user database (UDB) that match at least one letter corresponding to said at least one keypress, said words retrieved from any of said LDB and from said UDB; said UDB for storing any user-defined words entered by said user, a frequency count associated with each user-defined word, and a frequency count associated with each word stored in said LOB that was assigned a frequency count by an assigning module; a module for retrieving from any of said LOB and from said UDB a list of any words that match at least one letter corresponding to said at least one keypress of said user's input, said words dynamically reordered for display of said retrieved words as a function of said predefined linguistics frequency of use model and each frequency count associated with any of said retrieved words; and said assigning module for assigning a frequency count to every selected word in a non first order position in a list of said retrieved words and assigning a frequency count to a first order word if a word in a non first order position is selected, said frequency count being different for said first order word than said frequency count for said selected non first order word, said assigning module updating a frequency count each time a non first order word is selected from said retrieved list. | 15. An apparatus for reordering items in a database to be retrieved for display to a user, comprising: a module for accepting user input from a keyboard, said user input comprising at least one keypress; a linguistic database (LDB) containing a plurality of words ordered according to a predefined linguistic frequency of use model; a module for displaying to said user a list of any words in said LDB and any user-defined words in a user database (UDB) that match at least one letter corresponding to said at least one keypress, said words retrieved from any of said LDB and from said UDB; said UDB for storing any user-defined words entered by said user, a frequency count associated with each user-defined word, and a frequency count associated with each word stored in said LOB that was assigned a frequency count by an assigning module; a module for retrieving from any of said LOB and from said UDB a list of any words that match at least one letter corresponding to said at least one keypress of said user's input, said words dynamically reordered for display of said retrieved words as a function of said predefined linguistics frequency of use model and each frequency count associated with any of said retrieved words; and said assigning module for assigning a frequency count to every selected word in a non first order position in a list of said retrieved words and assigning a frequency count to a first order word if a word in a non first order position is selected, said frequency count being different for said first order word than said frequency count for said selected non first order word, said assigning module updating a frequency count each time a non first order word is selected from said retrieved list. 21. The apparatus of claim 15 , further comprising: a module for periodically checking for free space in said UDB and, if said free space is less than a predetermined amount, then removing from said UDB said frequency counts and corresponding object numbers or corresponding user-defined words for words that have frequency counts below a predetermined threshold. | 0.5 |
9,538,252 | 1 | 3 | 1. A method for rendering text onto moving image content, the method comprising: storing, in a provider computer system including at least one electronic processor and at least one data storage device, a master version of moving image content; generating, by a time-stamp module in the provider computer system, a time-stamped transcription of the master version of the moving image content, wherein generating the time-stamped transcription comprises: (i) generating a transcription of the master version of the moving image content comprising multiple segments, (ii) associating a starting time-stamp and an ending time-stamp with each segment of the multiple segments of the transcription, and (iii) storing, in the provider computer system, the generated transcription together with the associated starting and ending time-stamps for the each segment of the multiple segments as a copy of the master version of the moving image content being reclassified as transcribed and time-stamped; providing access to the copy of the time-stamped transcription of the master version of the moving image content by multiple client devices associated with multiple translators, wherein each client device includes at least one electronic processor and at least one data storage device; receiving, in the provider computer system, a request to translate dialog associated with the moving image content; transmitting an interface to at least one of the multiple client devices, wherein the interface is programmed with instructions for: (i) requesting the copy of the time-stamped transcription of the master version of the moving image content, and (ii) receiving input text from a translator of the multiple translators, wherein the input text corresponds to a translation into a selected language of at least one associated starting and ending time-stamped segment of the multiple segments of the copy of the time-stamped transcription of the moving image content; and receiving, in the provider computer system, a translation of the at least one segment of the multiple segments of the copy of the time-stamped transcription of the moving image content; and storing, in the provider computer system, the translation of the copy of the time-stamped transcription of the moving image content, wherein the stored translation is time-stamped to correspond with the time-stamped transcription and original dialog of the master version of the moving image content. | 1. A method for rendering text onto moving image content, the method comprising: storing, in a provider computer system including at least one electronic processor and at least one data storage device, a master version of moving image content; generating, by a time-stamp module in the provider computer system, a time-stamped transcription of the master version of the moving image content, wherein generating the time-stamped transcription comprises: (i) generating a transcription of the master version of the moving image content comprising multiple segments, (ii) associating a starting time-stamp and an ending time-stamp with each segment of the multiple segments of the transcription, and (iii) storing, in the provider computer system, the generated transcription together with the associated starting and ending time-stamps for the each segment of the multiple segments as a copy of the master version of the moving image content being reclassified as transcribed and time-stamped; providing access to the copy of the time-stamped transcription of the master version of the moving image content by multiple client devices associated with multiple translators, wherein each client device includes at least one electronic processor and at least one data storage device; receiving, in the provider computer system, a request to translate dialog associated with the moving image content; transmitting an interface to at least one of the multiple client devices, wherein the interface is programmed with instructions for: (i) requesting the copy of the time-stamped transcription of the master version of the moving image content, and (ii) receiving input text from a translator of the multiple translators, wherein the input text corresponds to a translation into a selected language of at least one associated starting and ending time-stamped segment of the multiple segments of the copy of the time-stamped transcription of the moving image content; and receiving, in the provider computer system, a translation of the at least one segment of the multiple segments of the copy of the time-stamped transcription of the moving image content; and storing, in the provider computer system, the translation of the copy of the time-stamped transcription of the moving image content, wherein the stored translation is time-stamped to correspond with the time-stamped transcription and original dialog of the master version of the moving image content. 3. The method of claim 1 , further comprising: receiving a request in the provider computer system to view the moving image content with text rendered thereon; and in response to receiving the request: transmitting the translation of the copy of the time-stamped transcription of the moving image content, and transmitting the moving image content. | 0.597222 |
8,984,398 | 1 | 7 | 1. A method comprising: extracting, by a computing platform comprising one or more processors, a group of two or more sentences of an electronic document; segmenting individual sentences of said of said two or more sentences into a first phrase and at least a second phrase, said first phrase comprising at least one word not contained within said at least a second phrase; determining two or more paths between phrases of said individual sentences, individual paths of said two or more paths comprising no more than one phrase from individual ones of said individual sentences; at least partially in response to receiving a search query, determining respective scores for said individual paths based at least in part on a utility metric and a ranking of said two or more sentences with respect to said search query; generating an abstract of said electronic document, said abstract comprising individual ones of said phrases associated with a first path of said two or more paths, said first path being associated with a highest of said respective scores, wherein a first phrase of said phrases associated with said first path is different from a second phrase of said phrases associated with said first path; and transmitting one or more search results comprising at least said abstract to a user at least partially in response to receiving said search query from said user. | 1. A method comprising: extracting, by a computing platform comprising one or more processors, a group of two or more sentences of an electronic document; segmenting individual sentences of said of said two or more sentences into a first phrase and at least a second phrase, said first phrase comprising at least one word not contained within said at least a second phrase; determining two or more paths between phrases of said individual sentences, individual paths of said two or more paths comprising no more than one phrase from individual ones of said individual sentences; at least partially in response to receiving a search query, determining respective scores for said individual paths based at least in part on a utility metric and a ranking of said two or more sentences with respect to said search query; generating an abstract of said electronic document, said abstract comprising individual ones of said phrases associated with a first path of said two or more paths, said first path being associated with a highest of said respective scores, wherein a first phrase of said phrases associated with said first path is different from a second phrase of said phrases associated with said first path; and transmitting one or more search results comprising at least said abstract to a user at least partially in response to receiving said search query from said user. 7. The method of claim 1 , further comprising: extracting said set of two or more sentences from said electronic document; determining a relevance of said two or more sentences associated with respect to said electronic document; and ranking said two or more sentences into said ranked order based at least in part on said determined relevance. | 0.751804 |
7,565,012 | 1 | 4 | 1. A method of generating an electronic document, the method comprising: photographing a document having a plurality of pages to generate moving picture data; detecting data of one page of the document by performing motion estimation on the moving picture data, performing document recognition on the data of the one page of the document, and storing the data of the one page of the document as first text data; detecting whether data of a next page is input by performing motion estimation on the moving picture data, and if the data of the next page is detected, performing document recognition on the data of the next page and storing the data of the next page as second text data; and storing the first text data and the second text data as one electronic document. | 1. A method of generating an electronic document, the method comprising: photographing a document having a plurality of pages to generate moving picture data; detecting data of one page of the document by performing motion estimation on the moving picture data, performing document recognition on the data of the one page of the document, and storing the data of the one page of the document as first text data; detecting whether data of a next page is input by performing motion estimation on the moving picture data, and if the data of the next page is detected, performing document recognition on the data of the next page and storing the data of the next page as second text data; and storing the first text data and the second text data as one electronic document. 4. The method of claim 1 , wherein the detecting the data of the one page comprises: performing motion estimation on the moving picture data; if the document is double-sided, detecting an edge between two pages within one frame, dividing the frame into the two pages, and storing data on the two pages as image data; and performing document recognition on the image data and storing a recognition result as text data. | 0.620909 |
9,442,982 | 8 | 13 | 8. One or more computer-readable storage devices comprising computer-readable instructions stored thereon that, responsive to execution by a processor, perform a method comprising: ascertaining a number of words in a user-entered query; responsive to ascertaining that the user-entered query is not more than one word and begins with at least one protocol prefix, returning relevant results using a confident method, the confident method configured to strip the user-entered query of the protocol prefix in order to perform a prefix string match against a destination's stripped uniform resource locator (URL), the confident method configured to calculate the relevant results using RSS feeds and feed items metadata, the RSS feeds and feed items metadata in the confident method comprising at least two of a stripped URL, feed title, feed name, item title, item content, and item author; and responsive to ascertaining that the user-entered query is at least two words or that the user-entered query is one word and does not begin with the protocol prefix, returning relevant results using a search method that is different than the confident method, the search method configured to perform no changes to the user-entered query, use word breaking on words of the user-entered query, and calculate the relevant results using RSS feeds and feed items metadata, the RSS feeds and feed items metadata in the search method comprising at least two of a host, path and query, feed title, feed name, item title, item content, and item author. | 8. One or more computer-readable storage devices comprising computer-readable instructions stored thereon that, responsive to execution by a processor, perform a method comprising: ascertaining a number of words in a user-entered query; responsive to ascertaining that the user-entered query is not more than one word and begins with at least one protocol prefix, returning relevant results using a confident method, the confident method configured to strip the user-entered query of the protocol prefix in order to perform a prefix string match against a destination's stripped uniform resource locator (URL), the confident method configured to calculate the relevant results using RSS feeds and feed items metadata, the RSS feeds and feed items metadata in the confident method comprising at least two of a stripped URL, feed title, feed name, item title, item content, and item author; and responsive to ascertaining that the user-entered query is at least two words or that the user-entered query is one word and does not begin with the protocol prefix, returning relevant results using a search method that is different than the confident method, the search method configured to perform no changes to the user-entered query, use word breaking on words of the user-entered query, and calculate the relevant results using RSS feeds and feed items metadata, the RSS feeds and feed items metadata in the search method comprising at least two of a host, path and query, feed title, feed name, item title, item content, and item author. 13. The one or more computer-readable storage devices of claim 8 , wherein a top-level domain included in the user-entered query is not considered a word when ascertaining the number of words in. | 0.568584 |
8,019,590 | 1 | 8 | 1. Non-transitory computer storage having stored thereon executable code that directs a computing system to detect and correct a writing problem in text by a process that comprises: searching a sentence of the text for at least one sign that indicates the possible occurrence or absence of a writing problem, the at least one sign comprising the word “what” and one or more of a verb unit and a “to be” verb; in response to determining that the word “what” is present, determining if one or more of a verb unit and a “to be” verb is present in the sentence; and selecting a proposed edit to suggest to a user, the proposed edit comprising deleting at least the word “what”. | 1. Non-transitory computer storage having stored thereon executable code that directs a computing system to detect and correct a writing problem in text by a process that comprises: searching a sentence of the text for at least one sign that indicates the possible occurrence or absence of a writing problem, the at least one sign comprising the word “what” and one or more of a verb unit and a “to be” verb; in response to determining that the word “what” is present, determining if one or more of a verb unit and a “to be” verb is present in the sentence; and selecting a proposed edit to suggest to a user, the proposed edit comprising deleting at least the word “what”. 8. The non-transitory computer storage of claim 1 , wherein the process comprises responding to a determination that the sentence includes the word “what” followed by a verb unit that is not followed by a “to be” verb by treating a phrase containing “what” and the verb unit as a false positive. | 0.702621 |
7,552,055 | 5 | 6 | 5. The computer readable storage medium of claim 4 wherein said control is adapted to combine the processing of responses in the extra answer property with the processing of responses in the extra answer property of said another control identified in the imported answer property or the imported extra answer property. | 5. The computer readable storage medium of claim 4 wherein said control is adapted to combine the processing of responses in the extra answer property with the processing of responses in the extra answer property of said another control identified in the imported answer property or the imported extra answer property. 6. The computer readable storage medium of claim 5 wherein being adapted to associate the grammar for the processing of responses in the answer property of said another control identified in the imported answer property or the imported extra answer property includes using a unique identifier for each of the answers. | 0.5 |
8,751,241 | 1 | 5 | 1. A method of obtaining information from speech at a vehicle, comprising: (a) receiving at a telematics unit in a vehicle a first speech input spoken by an occupant of the vehicle; (b) determining if telephone-related information has been requested based on the inclusion of numerical utterances in the first speech input; (c) determining if navigation information has been requested based on the inclusion of numerical utterances followed by non-numerical utterances in the first speech input; (d) enabling a navigation system of the vehicle based on the determination in step (c); (e) contacting directory assistance in response to the determination in step (b); (i) receiving at the telematics unit telephone-related information in the form of a second speech input sent to the vehicle from a remote facility via a wireless carrier system; (ii) obtaining data from the telephone-related information by performing speech recognition on the second speech input; (iii) querying the vehicle occupant based on the obtained data; and (iv) sending the obtained data to a vehicle device based on the query. | 1. A method of obtaining information from speech at a vehicle, comprising: (a) receiving at a telematics unit in a vehicle a first speech input spoken by an occupant of the vehicle; (b) determining if telephone-related information has been requested based on the inclusion of numerical utterances in the first speech input; (c) determining if navigation information has been requested based on the inclusion of numerical utterances followed by non-numerical utterances in the first speech input; (d) enabling a navigation system of the vehicle based on the determination in step (c); (e) contacting directory assistance in response to the determination in step (b); (i) receiving at the telematics unit telephone-related information in the form of a second speech input sent to the vehicle from a remote facility via a wireless carrier system; (ii) obtaining data from the telephone-related information by performing speech recognition on the second speech input; (iii) querying the vehicle occupant based on the obtained data; and (iv) sending the obtained data to a vehicle device based on the query. 5. The method of claim 1 , wherein step (e) further comprises recognizing the data from the second speech input using a selected domain specific actuator. | 0.5 |
7,499,910 | 3 | 4 | 3. The computer-readable program code embedded in the memory of claim 1 , wherein the list of candidate queries is determined by matching items in the select list of the new query with items in the select list of each of the plurality of cached queries. | 3. The computer-readable program code embedded in the memory of claim 1 , wherein the list of candidate queries is determined by matching items in the select list of the new query with items in the select list of each of the plurality of cached queries. 4. The computer-readable program code embedded in the memory of claim 3 , wherein the matching items in the select list is performed using a select list index. | 0.5 |
9,836,547 | 1 | 4 | 1. A method for capturing and managing knowledge from social networking interactions comprising: presenting a marking element in a social networking interaction, wherein: said marking element is a visual interface element that allows a user to mark a message of the social networking interaction with at least one of a question specifier and an answer specifier; said question specifier indicates that the user found a message to include a question; and said answer specifier indicates that the user found a message to include an answer; creating a knowledge element in response to a user specifying a message of the social networking interaction to be a question and specifying another message of the social networking interaction to be an answer; presenting a knowledge element indicator to accompany a corresponding message in said social networking interaction, which knowledge element indicator indicates whether said corresponding message corresponds to at least one of the group consisting of a question and an answer; and recommending said knowledge element for use in response to a user comprising a message relevant to said knowledge element in said social networking interaction before said user shares said message within said social networking interaction. | 1. A method for capturing and managing knowledge from social networking interactions comprising: presenting a marking element in a social networking interaction, wherein: said marking element is a visual interface element that allows a user to mark a message of the social networking interaction with at least one of a question specifier and an answer specifier; said question specifier indicates that the user found a message to include a question; and said answer specifier indicates that the user found a message to include an answer; creating a knowledge element in response to a user specifying a message of the social networking interaction to be a question and specifying another message of the social networking interaction to be an answer; presenting a knowledge element indicator to accompany a corresponding message in said social networking interaction, which knowledge element indicator indicates whether said corresponding message corresponds to at least one of the group consisting of a question and an answer; and recommending said knowledge element for use in response to a user comprising a message relevant to said knowledge element in said social networking interaction before said user shares said message within said social networking interaction. 4. The method of claim 1 , further comprising presenting an evaluation element for evaluating said knowledge element in said social networking interaction. | 0.621951 |
8,065,313 | 19 | 21 | 19. A computer system that automatically annotates an image, comprising: a processor; a memory; an obtaining mechanism configured to obtain images contained in two or more representative frames from a video that comprises a plurality of frames; wherein the computer system is configured to process each of the images obtained from the representative frames using the following mechanisms: an extraction mechanism configured to iteratively extract image features from a image on different spatial scales, wherein the image features comprise visual characteristics associated with different sizes within the image; a matching mechanism configured to match the extracted image features to known image features; an identification mechanism configured to: identify other images with similar image features using one or more combinations of the matched image features; and obtain text associated with the other images, wherein obtaining the text associated with the other images comprises obtaining text that surrounds each image in a web page in which the image is located; identify one or more intersecting keywords in the text associated with the other images; and an annotation mechanism configured to annotate the image with the intersecting keywords; an analysis mechanism configured to analyze the keywords for the images to determine a common set of keywords, wherein the annotation mechanism is configured to annotate the video using the common set of keywords. | 19. A computer system that automatically annotates an image, comprising: a processor; a memory; an obtaining mechanism configured to obtain images contained in two or more representative frames from a video that comprises a plurality of frames; wherein the computer system is configured to process each of the images obtained from the representative frames using the following mechanisms: an extraction mechanism configured to iteratively extract image features from a image on different spatial scales, wherein the image features comprise visual characteristics associated with different sizes within the image; a matching mechanism configured to match the extracted image features to known image features; an identification mechanism configured to: identify other images with similar image features using one or more combinations of the matched image features; and obtain text associated with the other images, wherein obtaining the text associated with the other images comprises obtaining text that surrounds each image in a web page in which the image is located; identify one or more intersecting keywords in the text associated with the other images; and an annotation mechanism configured to annotate the image with the intersecting keywords; an analysis mechanism configured to analyze the keywords for the images to determine a common set of keywords, wherein the annotation mechanism is configured to annotate the video using the common set of keywords. 21. The computer system of claim 19 , wherein the matching mechanism is configured to combine the matched image features to form one or more image-feature combinations for the image. | 0.528497 |
8,495,001 | 1 | 8 | 1. A method of operating a computer to perform a computer-implemented process for synthesizing concept definitions and relationships comprising: obtaining an active concept definition; extracting a plurality of real concept definitions comprising attributes from a domain and analyzing them for coherence within their attributes; matching the said active concept definition to the extracted real concept definitions; and deriving a plurality of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form relationships between themselves; wherein the existing real concept definitions are used as a measure of a coherence of various attribute sets. | 1. A method of operating a computer to perform a computer-implemented process for synthesizing concept definitions and relationships comprising: obtaining an active concept definition; extracting a plurality of real concept definitions comprising attributes from a domain and analyzing them for coherence within their attributes; matching the said active concept definition to the extracted real concept definitions; and deriving a plurality of virtual concept definitions from the real concept definitions by semantic processing, such that the derived virtual concept definitions form relationships between themselves; wherein the existing real concept definitions are used as a measure of a coherence of various attribute sets. 8. The method of claim 1 , wherein the derived virtual concept definitions are in a poly-hierarchal relationship with the real concept definitions. | 0.5 |
7,894,670 | 9 | 10 | 9. The method of claim 8 wherein the selecting is based at least in part upon attributes of the rendered document. | 9. The method of claim 8 wherein the selecting is based at least in part upon attributes of the rendered document. 10. The method of claim 9 wherein the selecting is based at least in part upon the identity of the rendered document. | 0.590909 |
5,384,702 | 14 | 15 | 14. The method of claim 1, wherein a grammar marker of said plurality of grammar marker includes an adverb marker. | 14. The method of claim 1, wherein a grammar marker of said plurality of grammar marker includes an adverb marker. 15. The method of claim 14, wherein said first database includes adverb conversion rules. | 0.5 |
8,046,221 | 11 | 12 | 11. The method of claim 8 , wherein the multi-state barge-in acoustic model is trained using a maximum likelihood (ML) training to detect speech during non-speech segments and to detect failure of speech when present. | 11. The method of claim 8 , wherein the multi-state barge-in acoustic model is trained using a maximum likelihood (ML) training to detect speech during non-speech segments and to detect failure of speech when present. 12. The method of claim 11 , wherein the multi-stage barge-in acoustic model is further trained using maximum mutual information (MMI) criterion discriminative training. | 0.5 |
9,384,244 | 18 | 21 | 18. A computer program product for search with autosuggest, the computer program product being embodied in a tangible non-transitory computer readable storage medium and comprising computer instructions for: determining a plurality of potential query suggestions for a partially entered query string; and automatically suggesting a plurality of queries based on a query count for each of the queries, comprising: determining a weight for each of the plurality of potential search query suggestions, comprising: determining a first weight of a first potential search query suggestion based on a first query count; determining a first position weight based on a position of a first matching word in the first potential search query suggestion; adjusting the first weight of the first potential search query suggestion based on the first position weight to obtain a first adjusted weight for the first potential search query suggestion, comprising: determining whether a portion of the query string matches a field in a document associated with the first potential search query suggestion; and in the event that the portion of the query string matches the field in the document: adjusting the first adjusted weight by a first value in the event that the field corresponds to a first type; and adjusting the first adjusted weight by a second value in the event that the field corresponds to a second type, the first value being different from the second value. | 18. A computer program product for search with autosuggest, the computer program product being embodied in a tangible non-transitory computer readable storage medium and comprising computer instructions for: determining a plurality of potential query suggestions for a partially entered query string; and automatically suggesting a plurality of queries based on a query count for each of the queries, comprising: determining a weight for each of the plurality of potential search query suggestions, comprising: determining a first weight of a first potential search query suggestion based on a first query count; determining a first position weight based on a position of a first matching word in the first potential search query suggestion; adjusting the first weight of the first potential search query suggestion based on the first position weight to obtain a first adjusted weight for the first potential search query suggestion, comprising: determining whether a portion of the query string matches a field in a document associated with the first potential search query suggestion; and in the event that the portion of the query string matches the field in the document: adjusting the first adjusted weight by a first value in the event that the field corresponds to a first type; and adjusting the first adjusted weight by a second value in the event that the field corresponds to a second type, the first value being different from the second value. 21. The computer program product recited in claim 18 , wherein the query count corresponds to a popularity of the query, and wherein the plurality of queries are listed based on a popularity of each of the plurality of queries. | 0.5 |
8,909,669 | 3 | 5 | 3. A method of document retrieval in a network environment where documents are stored with corresponding privacy codes comprising: receiving a query by at least one query server having access to a first index of documents available for searching on document servers in said network and privacy codes associated with corresponding documents in said index; said query being associated with an access level identifier of a requester, said access level identifier indicating particular privacy codes of documents authorized for viewing by said requester, wherein said access codes are privately controllable by at least one document custodian; generating by said query server in response to said query, a first list of said documents corresponding to said particular privacy codes indicated by said requester's access level identifier; generating a second index of words in each document in said first list by said query server; and generating by said query in response to said query, a second list of said documents corresponding to said at least one keyword and being included in said first list. | 3. A method of document retrieval in a network environment where documents are stored with corresponding privacy codes comprising: receiving a query by at least one query server having access to a first index of documents available for searching on document servers in said network and privacy codes associated with corresponding documents in said index; said query being associated with an access level identifier of a requester, said access level identifier indicating particular privacy codes of documents authorized for viewing by said requester, wherein said access codes are privately controllable by at least one document custodian; generating by said query server in response to said query, a first list of said documents corresponding to said particular privacy codes indicated by said requester's access level identifier; generating a second index of words in each document in said first list by said query server; and generating by said query in response to said query, a second list of said documents corresponding to said at least one keyword and being included in said first list. 5. The method of claim 3 , comprising: providing a secure interface for setting privacy codes by authorized document custodians of each document. | 0.791667 |
6,073,144 | 6 | 8 | 6. A computer program product for use in conjunction with a computer system, the computer system including a user interface to display a document and issue commands to edit the document, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising: a data structure representing the document as a hierarchical document, the hierarchical document comprising starttags and endtags and leaf contents between ones of the starttags and endtags, the data structure including starttag, endtag and leaf items representing corresponding ones of the starttags, endtags, and leaf contents; each of the starttag and endtag items representing the starttags and endtags having a corresponding index associated therewith, the data structure further including an index offset for each of the starttag and endtag items, each index offset indicating an offset to a corresponding complementary starttag or endtag item in the hierarchical document; and a document editor, executable by the computer system, for editing the hierarchical document in response to the issued commands, the document editor including instructions for traversing the data structure, both forward and backward, using the index offsets to skip over ones of the items in the data structure without having to inspect the contents of the skipped items. | 6. A computer program product for use in conjunction with a computer system, the computer system including a user interface to display a document and issue commands to edit the document, the computer program product comprising a computer readable storage medium and a computer program mechanism embedded therein, the computer program mechanism comprising: a data structure representing the document as a hierarchical document, the hierarchical document comprising starttags and endtags and leaf contents between ones of the starttags and endtags, the data structure including starttag, endtag and leaf items representing corresponding ones of the starttags, endtags, and leaf contents; each of the starttag and endtag items representing the starttags and endtags having a corresponding index associated therewith, the data structure further including an index offset for each of the starttag and endtag items, each index offset indicating an offset to a corresponding complementary starttag or endtag item in the hierarchical document; and a document editor, executable by the computer system, for editing the hierarchical document in response to the issued commands, the document editor including instructions for traversing the data structure, both forward and backward, using the index offsets to skip over ones of the items in the data structure without having to inspect the contents of the skipped items. 8. The computer program product of claim 6, wherein the computer system further includes a communication link to communicate with at least one client computer; and a server process, executable by the computer system, for transmitting the document and the document editor to the client computer. | 0.543478 |
4,818,131 | 14 | 15 | 14. A typewriter having a function of correcting a misspelled word, comprising: a keyboard having a multiplicity of character keys, a correction key for placing the typewriter in a correction mode for correcting a misspelled wrong word, and a change key for starting correction of said wrong word; an input data memory for storing input data constituting words entered through said keyboard; a printing mechanism operable for printing characters corresponding to said input data entered through said keyboard; an erasing mechanism operable for erasing said characters printed by said printing mechanism; and a control device connected to said keyboard, said input data memory, and said printing and erasing mechanisms, for controlling said input data memory, and said printing and erasing mechanisms, according to said input data entered through said keyboard; said control device including (a) a dictionary memory for storing data of a multiplicity of words, (b) spell-checking means operable upon operation of said correction key, for comparing each of the words of said input data with said multiplicity of words stored in said dictionary memory, to check said input data for any misspelled wrong words, (c) a correct-word memory for storing characters of a correct word to be substituted for a wrong word detected by said spell-checking means, (d) automatic word-correction control means operable upon operation of said change key, for activating said erasing and printing mechanisms to erase said detected wrong word and print in its place said correct word, according to data representative of said detected wrong word and said correct word stored in said correct-word memory, (e) judging means operable, after said correct word is stored in said correct-word memory, for determining whether there exists a sufficient space for printing said correct word in place of said detected wrong word, and (f) alarm means which is activated if said judging means determines that said sufficient space does not exist. | 14. A typewriter having a function of correcting a misspelled word, comprising: a keyboard having a multiplicity of character keys, a correction key for placing the typewriter in a correction mode for correcting a misspelled wrong word, and a change key for starting correction of said wrong word; an input data memory for storing input data constituting words entered through said keyboard; a printing mechanism operable for printing characters corresponding to said input data entered through said keyboard; an erasing mechanism operable for erasing said characters printed by said printing mechanism; and a control device connected to said keyboard, said input data memory, and said printing and erasing mechanisms, for controlling said input data memory, and said printing and erasing mechanisms, according to said input data entered through said keyboard; said control device including (a) a dictionary memory for storing data of a multiplicity of words, (b) spell-checking means operable upon operation of said correction key, for comparing each of the words of said input data with said multiplicity of words stored in said dictionary memory, to check said input data for any misspelled wrong words, (c) a correct-word memory for storing characters of a correct word to be substituted for a wrong word detected by said spell-checking means, (d) automatic word-correction control means operable upon operation of said change key, for activating said erasing and printing mechanisms to erase said detected wrong word and print in its place said correct word, according to data representative of said detected wrong word and said correct word stored in said correct-word memory, (e) judging means operable, after said correct word is stored in said correct-word memory, for determining whether there exists a sufficient space for printing said correct word in place of said detected wrong word, and (f) alarm means which is activated if said judging means determines that said sufficient space does not exist. 15. A typewriter according to claim 14, wherein said judging means determines whether the number of said characters of said correct word exceeds the number of characters of said detected wrong word, and said alarm means is activated if said number of characters of said correct word exceeds said number of characters of said detected wrong word. | 0.5 |
7,603,344 | 1 | 2 | 1. A computer-readable storage medium upon which is embodied and stored a sequence of programmed instructions that, when executed by a processor, cause the processor to perform functions comprising: extracting information from input data; detecting suspect data contained in said extracted data using a forensic search tool of a computing platform associated with a first agency, said detecting performed by matching said extracted data with one or more pre-defined data patterns specified by said forensic search tool, wherein said suspect data comprises data identified by said forensic search tool as being associated with inappropriate or illegal activities; including the suspect data and a non-readable and non-modifiable representation of sensitive data in the forensic search tool; outputting a report identifying said suspect data; and outputting said forensic search tool by said computing platform associated with said first agency to at least one computing platform associated with a second agency, wherein the instructions associated with said digital forensic search tool further comprise a header; a search markup language portion; a data features portion containing features of data, wherein the digital forensic search tool enables said computing platform associated with said first agency to share the suspect data with said at least one computing platform associated with a second agency in a manner that enables utilization of the suspect data by the second agency while not revealing the actual content of the sensitive data to the second agency; and wherein instructions implementing said digital forensic search tool are provided in accordance with a search markup language. | 1. A computer-readable storage medium upon which is embodied and stored a sequence of programmed instructions that, when executed by a processor, cause the processor to perform functions comprising: extracting information from input data; detecting suspect data contained in said extracted data using a forensic search tool of a computing platform associated with a first agency, said detecting performed by matching said extracted data with one or more pre-defined data patterns specified by said forensic search tool, wherein said suspect data comprises data identified by said forensic search tool as being associated with inappropriate or illegal activities; including the suspect data and a non-readable and non-modifiable representation of sensitive data in the forensic search tool; outputting a report identifying said suspect data; and outputting said forensic search tool by said computing platform associated with said first agency to at least one computing platform associated with a second agency, wherein the instructions associated with said digital forensic search tool further comprise a header; a search markup language portion; a data features portion containing features of data, wherein the digital forensic search tool enables said computing platform associated with said first agency to share the suspect data with said at least one computing platform associated with a second agency in a manner that enables utilization of the suspect data by the second agency while not revealing the actual content of the sensitive data to the second agency; and wherein instructions implementing said digital forensic search tool are provided in accordance with a search markup language. 2. The computer-readable storage medium as recited in claim 1 , further comprising a data verification portion containing a plurality of actual data representations for identifying potential suspect data. | 0.576763 |
9,904,671 | 1 | 2 | 1. A method of computer analysis of at least one computer communication of a person in an organization including people affiliated with the organization comprising: receiving with a computer the at least one computer communication relating to the organization comprised of a group of words to or from the person transmitted in the organization; deconstructing the at least one computer communication of the person with a language parser programmed in at least one computer; processing the deconstructing at least one computer communication with at least one computer to provide an analysis of the group of words with at least one psychological profiling algorithm including quantifying at least negatives, use of the word me, and direct references to determine a psychological state of the person relative to a reference of the person changing over time and based on an analysis of previous computer communications transmitted within the organization of a plurality of people affiliated with the organization with at least one psychological profiling algorithm with previous computer communications collected by at least one computer over time from the organization; and responsive to the analysis, generating with a computer an electronic communication transmitted by the organization, comparing the psychological state represented by the group of words of the person to the reference and determining with at least one computer whether the psychological state of the person poses a risk to the organization; and wherein the reference is one of an average, a mean, a calculation or a value representing a psychological state of people represented by previous computer communications or previous computer communications of the person. | 1. A method of computer analysis of at least one computer communication of a person in an organization including people affiliated with the organization comprising: receiving with a computer the at least one computer communication relating to the organization comprised of a group of words to or from the person transmitted in the organization; deconstructing the at least one computer communication of the person with a language parser programmed in at least one computer; processing the deconstructing at least one computer communication with at least one computer to provide an analysis of the group of words with at least one psychological profiling algorithm including quantifying at least negatives, use of the word me, and direct references to determine a psychological state of the person relative to a reference of the person changing over time and based on an analysis of previous computer communications transmitted within the organization of a plurality of people affiliated with the organization with at least one psychological profiling algorithm with previous computer communications collected by at least one computer over time from the organization; and responsive to the analysis, generating with a computer an electronic communication transmitted by the organization, comparing the psychological state represented by the group of words of the person to the reference and determining with at least one computer whether the psychological state of the person poses a risk to the organization; and wherein the reference is one of an average, a mean, a calculation or a value representing a psychological state of people represented by previous computer communications or previous computer communications of the person. 2. A method in accordance with claim 1 , wherein: the electronic communication indicates that the person should be studied. | 0.848894 |
8,510,347 | 19 | 21 | 19. A computer program product for use with a stored program computer, the computer program product comprising a non-transitory computer usable medium having a computer readable program code embodied therein for generating one or more software artifacts, the one or more software artifacts being generated for one or more requirements associated with an enterprise process, the computer readable program code comprising instructions for: a. capturing the one or more requirements; b. enabling a user to define a plurality of sets of meta-models, each of the sets of meta-models corresponding to at least one requirement and defined based on a predefined ontology, the predefined ontology comprising rules for defining and inter-relating meta models, and wherein at least one meta-model of a set of meta-models of the plurality of sets of meta-models being defined based on at least one other meta-model of the same set of meta-models, wherein each of the plurality of sets of meta-models comprises (i) one or more intent meta-models, each intent meta-model describing the corresponding requirement, wherein each intent meta-model is defined by a user, (ii) one or more inference meta-models for each intent meta-model, each inference meta-model describing business and technical requirements required for generating at least one software artifact of the one or more software artifacts, the business and technical requirements being determined based on the at least one requirement, each inference meta-model being defined by the user, (iii) a composer meta-model corresponding to the one or more inference meta-models, the composer meta-model defining the relation between the intent meta-model and the corresponding one or more inference meta-models, each composer meta-model being defined by the user, and (iv) a set of abstract meta-models, each abstract meta-model of the set of abstract meta-models being inherited from a predefined set of abstract meta-models while defining at least one of the one or more intent meta-models, at least one of the one or more inference meta-models and at least one composer meta-model c. enabling the user to build the meta-model schema by connecting at least one set of meta-models from among the plurality of sets of meta-models to at least one other set of meta-models from among the plurality of sets of meta-models, the connection being based on relations between the corresponding requirements; and d. calculating a completeness of the meta-model schema, the completeness of the meta-model schema being a function of: (i) a number of intent meta-models defined for the one or more requirements, (ii) a number of inference meta-models defined for each intent meta-model, (iii) a number of composer meta-models defined corresponding to the inference meta-models, and (iv) a number of meta-models of the one or more sets of meta-models that have a reference to at least one other meta-model of the set of meta-models, each reference being defined by the user, wherein the completeness of the meta-model schema is additionally a function of a number of quantifiable requirements among the one or more requirements, and wherein the completeness of the meta-model schema is calculated according to the following formula: SC=(Na/Nb)*(Nc/Nd)*((Ne+Nf−Ng)/(Ne+Nf)), wherein SC is the completeness of the meta-model schema, Na is a number of intent meta-models, Nb is the number of quantifiable requirements, Nc is a number of intent meta-models from which inference meta-models have been defined, Nd is a total number of intent meta-models, Ne is a number of inference meta-models, Nf is a number of composer meta-models, and Ng is a number of meta-models without a reference to other meta-models. | 19. A computer program product for use with a stored program computer, the computer program product comprising a non-transitory computer usable medium having a computer readable program code embodied therein for generating one or more software artifacts, the one or more software artifacts being generated for one or more requirements associated with an enterprise process, the computer readable program code comprising instructions for: a. capturing the one or more requirements; b. enabling a user to define a plurality of sets of meta-models, each of the sets of meta-models corresponding to at least one requirement and defined based on a predefined ontology, the predefined ontology comprising rules for defining and inter-relating meta models, and wherein at least one meta-model of a set of meta-models of the plurality of sets of meta-models being defined based on at least one other meta-model of the same set of meta-models, wherein each of the plurality of sets of meta-models comprises (i) one or more intent meta-models, each intent meta-model describing the corresponding requirement, wherein each intent meta-model is defined by a user, (ii) one or more inference meta-models for each intent meta-model, each inference meta-model describing business and technical requirements required for generating at least one software artifact of the one or more software artifacts, the business and technical requirements being determined based on the at least one requirement, each inference meta-model being defined by the user, (iii) a composer meta-model corresponding to the one or more inference meta-models, the composer meta-model defining the relation between the intent meta-model and the corresponding one or more inference meta-models, each composer meta-model being defined by the user, and (iv) a set of abstract meta-models, each abstract meta-model of the set of abstract meta-models being inherited from a predefined set of abstract meta-models while defining at least one of the one or more intent meta-models, at least one of the one or more inference meta-models and at least one composer meta-model c. enabling the user to build the meta-model schema by connecting at least one set of meta-models from among the plurality of sets of meta-models to at least one other set of meta-models from among the plurality of sets of meta-models, the connection being based on relations between the corresponding requirements; and d. calculating a completeness of the meta-model schema, the completeness of the meta-model schema being a function of: (i) a number of intent meta-models defined for the one or more requirements, (ii) a number of inference meta-models defined for each intent meta-model, (iii) a number of composer meta-models defined corresponding to the inference meta-models, and (iv) a number of meta-models of the one or more sets of meta-models that have a reference to at least one other meta-model of the set of meta-models, each reference being defined by the user, wherein the completeness of the meta-model schema is additionally a function of a number of quantifiable requirements among the one or more requirements, and wherein the completeness of the meta-model schema is calculated according to the following formula: SC=(Na/Nb)*(Nc/Nd)*((Ne+Nf−Ng)/(Ne+Nf)), wherein SC is the completeness of the meta-model schema, Na is a number of intent meta-models, Nb is the number of quantifiable requirements, Nc is a number of intent meta-models from which inference meta-models have been defined, Nd is a total number of intent meta-models, Ne is a number of inference meta-models, Nf is a number of composer meta-models, and Ng is a number of meta-models without a reference to other meta-models. 21. The computer program product of claim 19 , wherein the at least one meta-model of the set of meta-models being defined based on the at least one other meta-model by the user. | 0.707237 |
7,577,562 | 15 | 16 | 15. The system of claim 9 and further comprising: a decoder configured to access the well formed treelet translation pairs to translate a textual input. | 15. The system of claim 9 and further comprising: a decoder configured to access the well formed treelet translation pairs to translate a textual input. 16. The system of claim 15 wherein the decoder is configured to generate and output N-best translations of the textual input. | 0.5 |
9,460,193 | 15 | 16 | 15. A method for search ranking, the method comprising: determining, by a processor, a set of contexts based on profile of rankable information and an access history of users that have accessed at least some of the rankable information; comparing an association of a user conducting a search, based on a user profile for the user conducting the search, with at least one of the contexts to thereby rank search results based on the comparison; generating personalized clusters based on the contexts; and re-ranking the search results based on manipulation of at least one of the personalized clusters, wherein the manipulation of the at least one of the personalized clusters is based on a determination of movement of a marker that is displayed independently of the at least one of the personalized clusters towards or away from the at least one of the personalized clusters, and wherein the manipulation of the at least one of the personalized clusters is further based on a determination of selection of the at least one of the personalized clusters after selection of a different personalized cluster from the personalized clusters. | 15. A method for search ranking, the method comprising: determining, by a processor, a set of contexts based on profile of rankable information and an access history of users that have accessed at least some of the rankable information; comparing an association of a user conducting a search, based on a user profile for the user conducting the search, with at least one of the contexts to thereby rank search results based on the comparison; generating personalized clusters based on the contexts; and re-ranking the search results based on manipulation of at least one of the personalized clusters, wherein the manipulation of the at least one of the personalized clusters is based on a determination of movement of a marker that is displayed independently of the at least one of the personalized clusters towards or away from the at least one of the personalized clusters, and wherein the manipulation of the at least one of the personalized clusters is further based on a determination of selection of the at least one of the personalized clusters after selection of a different personalized cluster from the personalized clusters. 16. The method according to claim 15 , further comprising determining an association score for the user based on comparison of the user profile for the user conducting the search with the contexts of each of the users, a further association score for search result information based on comparison of the search result information with the contexts, and an overall association score based on the association scores to rank the search results. | 0.520652 |
8,725,707 | 10 | 11 | 10. A non-transitory computer readable storage medium having instructions for causing a computer to execute a method, comprising: executing a continuous data stream process with three functions that include an extract, transform, load (ETL) process, an aggregation process, and reporting process; specifying the continuous data stream process with Structured Query Language (SQL) queries; executing the SQL queries at a database management system (DBMS) level, wherein the SQL queries include User Defined Functions (UDFs) that perform relational transformations like a relational operator since the UDFs include input values as relations and output values as relations; and identifying stations with triggering conditions and outgoing pipes, the outgoing pipes defined with a relation schema for type-preservation and with a stream key for identifying stream elements, wherein relations returned from the UDF are replicated to multiple pipes for multiple destination stations. | 10. A non-transitory computer readable storage medium having instructions for causing a computer to execute a method, comprising: executing a continuous data stream process with three functions that include an extract, transform, load (ETL) process, an aggregation process, and reporting process; specifying the continuous data stream process with Structured Query Language (SQL) queries; executing the SQL queries at a database management system (DBMS) level, wherein the SQL queries include User Defined Functions (UDFs) that perform relational transformations like a relational operator since the UDFs include input values as relations and output values as relations; and identifying stations with triggering conditions and outgoing pipes, the outgoing pipes defined with a relation schema for type-preservation and with a stream key for identifying stream elements, wherein relations returned from the UDF are replicated to multiple pipes for multiple destination stations. 11. The non-transitory computer readable storage medium of claim 10 , wherein the ETL process, the aggregation process, and the reporting process execute in different cycles with the ETL process executing more frequently than the reporting process. | 0.594771 |
7,979,454 | 12 | 13 | 12. The information processing apparatus according to claim 11 , further comprising: a thesaurus dictionary used to detect a word related to the search keyword, wherein the collected written texts are subjected to the morphological analysis to find the reputation expression, and the collected written texts are subjected to the syntactic analysis to detect the word that is syntactically related to the found reputation expression, and if the detected word is the word related to the search keyword as detected by said thesaurus dictionary, the evaluation value of the found reputation expression is added as the evaluation result of the content. | 12. The information processing apparatus according to claim 11 , further comprising: a thesaurus dictionary used to detect a word related to the search keyword, wherein the collected written texts are subjected to the morphological analysis to find the reputation expression, and the collected written texts are subjected to the syntactic analysis to detect the word that is syntactically related to the found reputation expression, and if the detected word is the word related to the search keyword as detected by said thesaurus dictionary, the evaluation value of the found reputation expression is added as the evaluation result of the content. 13. The information processing apparatus according to claim 12 , wherein the evaluation value of the found reputation expression is multiplied by a different weighting factor depending on whether the detected word is the search keyword or whether the detected word is the word related to the search keyword as detected by said thesaurus dictionary, and the evaluation value of the found reputation expression multiplied by the weighting factor is added as the evaluation result of the content. | 0.5 |
7,509,303 | 21 | 28 | 21. A computer-implemented process that generates a display of information, said process comprising the steps of: receiving a query input from a user, said query comprising one or more terms representing one or more subjects of interest to the user, each of said one or more subjects having a search attribute corresponding to a first database; collecting data from a data source, said data having an attribute corresponding to a second database; associating said search attribute with said attribute of said data from said data source, wherein said attribute is not said search attribute; and generating a display of information comprising a result from executing the query input based on said association, wherein the result comprises results from (a) querying the first database using said search attribute and a term from said one or more terms for said search attribute, and (b) querying the second database using said attribute and said term from said one or more terms for said search attribute. | 21. A computer-implemented process that generates a display of information, said process comprising the steps of: receiving a query input from a user, said query comprising one or more terms representing one or more subjects of interest to the user, each of said one or more subjects having a search attribute corresponding to a first database; collecting data from a data source, said data having an attribute corresponding to a second database; associating said search attribute with said attribute of said data from said data source, wherein said attribute is not said search attribute; and generating a display of information comprising a result from executing the query input based on said association, wherein the result comprises results from (a) querying the first database using said search attribute and a term from said one or more terms for said search attribute, and (b) querying the second database using said attribute and said term from said one or more terms for said search attribute. 28. The computer-implemented process of claim 21 , wherein said receiving comprises displaying a window in a screen, said window comprising a field in which said user can input said one or more terms of said query input. | 0.558233 |
7,788,176 | 10 | 11 | 10. The method of claim 2 , further comprising: responsive to a determination that the user is playing the selected SMS game against a data processing system, performing a computer specified action associated with the selected SMS game; and sending a seventh text message to the user indicating the computer specified action taken by the data processing system. | 10. The method of claim 2 , further comprising: responsive to a determination that the user is playing the selected SMS game against a data processing system, performing a computer specified action associated with the selected SMS game; and sending a seventh text message to the user indicating the computer specified action taken by the data processing system. 11. The method of claim 10 , further comprising storing a current state of the selected SMS game in memory. | 0.5 |
4,654,798 | 1 | 3 | 1. A sentence forming apparatus comprising: first storage means for storing in a correlated manner with each other a plurality of indexes in a first language, a plurality of words in the first language semantically in coordination respectively with said indexes and grammatical information relating to said respective words, the grammatical information being semantically restricted; selection menu forming means for forming a selection menu in the first language by utilizing the contents of said first storage means; input means for inputting selective information required for forming a sentence in response to said selection menu; second storage means for storing said inputted selective information; third storage means for storing syntax information relating to grammatical syntax of the first language and word information relating to words in the first language; first sentence assembly means for assembling a sentence in the first language utilizing said selective information and said syntax information and said word information in the first language; fourth storage means for storing syntax information relating to grammatical syntax of at least one second language and word information relating to words in the at least one second language; second sentence assembly means for assembling a sentence in the at least one second language semantically equivalent to said sentence in the first language utilizing said selective information and said syntax information and said word information in the at least one second language; and output means for outputting said selection menu, said sentence assembled by said first sentence assembly means and said sentence assembled by said second assembly means. | 1. A sentence forming apparatus comprising: first storage means for storing in a correlated manner with each other a plurality of indexes in a first language, a plurality of words in the first language semantically in coordination respectively with said indexes and grammatical information relating to said respective words, the grammatical information being semantically restricted; selection menu forming means for forming a selection menu in the first language by utilizing the contents of said first storage means; input means for inputting selective information required for forming a sentence in response to said selection menu; second storage means for storing said inputted selective information; third storage means for storing syntax information relating to grammatical syntax of the first language and word information relating to words in the first language; first sentence assembly means for assembling a sentence in the first language utilizing said selective information and said syntax information and said word information in the first language; fourth storage means for storing syntax information relating to grammatical syntax of at least one second language and word information relating to words in the at least one second language; second sentence assembly means for assembling a sentence in the at least one second language semantically equivalent to said sentence in the first language utilizing said selective information and said syntax information and said word information in the at least one second language; and output means for outputting said selection menu, said sentence assembled by said first sentence assembly means and said sentence assembled by said second assembly means. 3. A sentence forming apparatus in accordance with claim 1, wherein said output means include: first output means for outputting said selection menu; second output means for outputting said sentence assembled by said first sentence assembly means; and third output means for outputting said sentence assembled by said second sentence assembly means. | 0.5 |
6,161,092 | 37 | 45 | 37. An apparatus for reporting traffic information using pre-recorded audio, comprising: a display; an input device; a storage unit; and a processor in communication with said storage unit, said input device and said display, said storage unit storing code for programming said processor to perform a method comprising the steps of: receiving data for a set of traffic incidents, said data including parameters for said traffic incidents, one or more of said parameters include codes representing a value for said parameter, identifying groups of files that store speech for describing said incidents, each group of files is associated with at least one of said incidents, said groups of files vary in number of files per group depending on how many parameters are associated with a particular incident and how many audio files are needed to describe parameters associated with said particular incident, said step of identifying groups comprises the steps of: for each incident of at least a subset of said traffic incidents, accessing parameters for said incident, and for each parameter of at least a subset of said accessed parameters, identifying one or more files that store speech using a set of information correlating codes for said parameter to references to audio files, and automatically presenting said stored speech from each group of files. | 37. An apparatus for reporting traffic information using pre-recorded audio, comprising: a display; an input device; a storage unit; and a processor in communication with said storage unit, said input device and said display, said storage unit storing code for programming said processor to perform a method comprising the steps of: receiving data for a set of traffic incidents, said data including parameters for said traffic incidents, one or more of said parameters include codes representing a value for said parameter, identifying groups of files that store speech for describing said incidents, each group of files is associated with at least one of said incidents, said groups of files vary in number of files per group depending on how many parameters are associated with a particular incident and how many audio files are needed to describe parameters associated with said particular incident, said step of identifying groups comprises the steps of: for each incident of at least a subset of said traffic incidents, accessing parameters for said incident, and for each parameter of at least a subset of said accessed parameters, identifying one or more files that store speech using a set of information correlating codes for said parameter to references to audio files, and automatically presenting said stored speech from each group of files. 45. A method according to claim 37, wherein: said step of automatically presenting includes presenting an audio/visual program that includes said stored speech, said audio/visual program does not require user interaction during presentation. | 0.5 |
8,195,772 | 22 | 23 | 22. A method according to claim 21 , wherein said context is an expression defining elements in said electronic visual content to be part of the context. | 22. A method according to claim 21 , wherein said context is an expression defining elements in said electronic visual content to be part of the context. 23. A method according to claim 22 , wherein said expression is a hierarchical expression. | 0.563107 |
9,665,571 | 14 | 25 | 14. A computer-implemented system comprising: one or more computers programmed to perform operations comprising: selecting a word or phrase of a message that was not correctly translated from a first language to a second language; selecting a plurality of users from whom to solicit user feedback for the translation, wherein each selected user has not submitted feedback more times than a quota for a time period; sending a query requesting user assistance in translating the selected word or phrase to one or more of the plurality of users; receiving at least one response to the query from one or more of the users to whom the query was sent; determining that the at least one response is approved; determining a credit based on a complexity of the selected word or phrase or an importance of the selected word or phrase; crediting with the determined credit a respective account of one or more of the users who provided the at least one approved response; updating at least one of a transformation module and a translation module according to the at least one approved response; and using at least one computer processor and at least one of the updated transformation module and the updated translation module to translate a second message comprising the selected word or phrase. | 14. A computer-implemented system comprising: one or more computers programmed to perform operations comprising: selecting a word or phrase of a message that was not correctly translated from a first language to a second language; selecting a plurality of users from whom to solicit user feedback for the translation, wherein each selected user has not submitted feedback more times than a quota for a time period; sending a query requesting user assistance in translating the selected word or phrase to one or more of the plurality of users; receiving at least one response to the query from one or more of the users to whom the query was sent; determining that the at least one response is approved; determining a credit based on a complexity of the selected word or phrase or an importance of the selected word or phrase; crediting with the determined credit a respective account of one or more of the users who provided the at least one approved response; updating at least one of a transformation module and a translation module according to the at least one approved response; and using at least one computer processor and at least one of the updated transformation module and the updated translation module to translate a second message comprising the selected word or phrase. 25. The system of claim 14 , wherein the operations further comprise: evaluating a competency of one of the plurality of users based on an accuracy of the at least one response. | 0.8584 |
8,176,091 | 16 | 17 | 16. A system for detecting a local phenomenon, the system comprises a hardware interface for receiving queries information from a system, and a hardware processor, configured to: (a) create a first local popularity chart, wherein the creating of the first local popularity chart comprises enumerating, for each geographic area of a group of sampled geographic areas, identical query strings of queries that are included in a group of queries; (b) create a first global popularity chart, wherein the creating of the first global popularity chart comprises enumerating identical query strings of the queries that are included in the group of and are associated with any one of the geographical areas of the group of sampled geographic areas; and (c) select at least one query string in response to a scoring of the query string at the first local popularity chart that indicates that the at least one query string is locally popular and to a scoring of the query string at the first global popularity chart that indicates that the at least one query string is not globally popular. | 16. A system for detecting a local phenomenon, the system comprises a hardware interface for receiving queries information from a system, and a hardware processor, configured to: (a) create a first local popularity chart, wherein the creating of the first local popularity chart comprises enumerating, for each geographic area of a group of sampled geographic areas, identical query strings of queries that are included in a group of queries; (b) create a first global popularity chart, wherein the creating of the first global popularity chart comprises enumerating identical query strings of the queries that are included in the group of and are associated with any one of the geographical areas of the group of sampled geographic areas; and (c) select at least one query string in response to a scoring of the query string at the first local popularity chart that indicates that the at least one query string is locally popular and to a scoring of the query string at the first global popularity chart that indicates that the at least one query string is not globally popular. 17. The system according to claim 16 , wherein the local phenomenon pertains to an artist, and wherein the processor is further configured to select at least one query string that is associated with the artist. | 0.5 |
8,787,819 | 1 | 9 | 1. A method for creating a discussion platform, comprising: receiving, by a processor executing instructions stored on memory, a selection of a topic-based lesson from a plurality of topic-based lessons; providing, by the processor executing instructions stored on memory, an interface for the selected topic-based lesson, the interface generated from a first template of a plurality of templates, the first template providing a type of discussion and lesson media content; receiving a submission associated with the topic-based lesson and in the form of the type of discussion, the submission received from a user through the interface, the user submission received as input in a structured format including quantitative collaborative input elements, and the user submission extensible to other individuals and embedded in an interactive environment, and wherein the selected topic-based lesson, the first template, and the user submission form a self-contained learning unit, the self-contained learning unit embeddable in a digital environment; and updating a forum interface based on the user submission. | 1. A method for creating a discussion platform, comprising: receiving, by a processor executing instructions stored on memory, a selection of a topic-based lesson from a plurality of topic-based lessons; providing, by the processor executing instructions stored on memory, an interface for the selected topic-based lesson, the interface generated from a first template of a plurality of templates, the first template providing a type of discussion and lesson media content; receiving a submission associated with the topic-based lesson and in the form of the type of discussion, the submission received from a user through the interface, the user submission received as input in a structured format including quantitative collaborative input elements, and the user submission extensible to other individuals and embedded in an interactive environment, and wherein the selected topic-based lesson, the first template, and the user submission form a self-contained learning unit, the self-contained learning unit embeddable in a digital environment; and updating a forum interface based on the user submission. 9. The method of claim 1 , wherein the submission is a private communication to a forum administrator. | 0.755981 |
9,317,557 | 1 | 3 | 1. A computer system comprising the following: one or more processors; one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by the one or more processors, cause the computing system to execute a method for processing a query using schema graph traversal, the method comprising the following: an act of receiving a query at the computer system from a query sender, the query specifying one or more relational tables and their relationships that are to be retrieved from a relational database; an act of creating a schema graph comprising one or more graph nodes representing relational tables and one or more edges that identify relationships between the relational tables, the graph nodes including relational data that was loaded from a first storage area, the schema graph itself being stored in a second storage area, wherein the creating the schema graph includes at least the following: accessing a plurality of relational tables; generating a plurality of graph nodes, with a separate graph node for each of the plurality of relational tables represented by the schema graph; generating a plurality of edges between different graph nodes that define the relationships between the relational tables, at least a first edge of the plurality of edges and a second edge of the plurality of edges define different relationship attributes, such that nodes connected by the first edge have at least one of a different type or a different quantity of relationships than different nodes that are connected by the second edge; and visually representing the schema graph with the plurality of nodes and the plurality of edges, wherein the first and second edges are represented as separate lines with different display attributes, the different display attributes corresponding to different relationship attributes between different nodes; an act of traversing the schema graph, beginning at a set of graph nodes and continuing along the edges to one or more other graph nodes until the query has been satisfied; and an act of reporting the results of the graph traversal. | 1. A computer system comprising the following: one or more processors; one or more computer-readable storage media having stored thereon computer-executable instructions that, when executed by the one or more processors, cause the computing system to execute a method for processing a query using schema graph traversal, the method comprising the following: an act of receiving a query at the computer system from a query sender, the query specifying one or more relational tables and their relationships that are to be retrieved from a relational database; an act of creating a schema graph comprising one or more graph nodes representing relational tables and one or more edges that identify relationships between the relational tables, the graph nodes including relational data that was loaded from a first storage area, the schema graph itself being stored in a second storage area, wherein the creating the schema graph includes at least the following: accessing a plurality of relational tables; generating a plurality of graph nodes, with a separate graph node for each of the plurality of relational tables represented by the schema graph; generating a plurality of edges between different graph nodes that define the relationships between the relational tables, at least a first edge of the plurality of edges and a second edge of the plurality of edges define different relationship attributes, such that nodes connected by the first edge have at least one of a different type or a different quantity of relationships than different nodes that are connected by the second edge; and visually representing the schema graph with the plurality of nodes and the plurality of edges, wherein the first and second edges are represented as separate lines with different display attributes, the different display attributes corresponding to different relationship attributes between different nodes; an act of traversing the schema graph, beginning at a set of graph nodes and continuing along the edges to one or more other graph nodes until the query has been satisfied; and an act of reporting the results of the graph traversal. 3. The computer system of claim 1 , wherein the schema graph illustrates primary key and foreign key relationships between graph nodes. | 0.713983 |
8,793,583 | 1 | 11 | 1. A method for annotation of video content in a device communicatively coupled to a network, the method comprising: receiving, in the device, a captured speech segment comprising speech from a user of a second device, wherein the captured speech segment annotates a portion of the video content streamed to the second device for being played to the user contemporaneously with the speech from the user; converting the captured speech segment to a text-segment; associating the text-segment with the portion of the video content contemporaneously played to the user; and storing in a selectively retrievable manner the text-segment so that the text-segment is associated with the portion of the video content. | 1. A method for annotation of video content in a device communicatively coupled to a network, the method comprising: receiving, in the device, a captured speech segment comprising speech from a user of a second device, wherein the captured speech segment annotates a portion of the video content streamed to the second device for being played to the user contemporaneously with the speech from the user; converting the captured speech segment to a text-segment; associating the text-segment with the portion of the video content contemporaneously played to the user; and storing in a selectively retrievable manner the text-segment so that the text-segment is associated with the portion of the video content. 11. The method of claim 1 wherein storing the text-segment further comprises: storing the text-segment in a database of a storage device communicatively coupled to the network. | 0.705686 |
8,719,519 | 33 | 36 | 33. A non-transitory machine-readable medium having stored thereon data, which if performed by at least one machine, causes the at least one machine to fabricate at least one integrated circuit to perform a method comprising: reading a portion of a data word by a computer processor, wherein the data word includes a plurality of syllables and the reading of the portion of the data word includes: reading a first syllable of the plurality of syllables from a first memory; and reading a second syllable of the plurality of syllables from a second memory, wherein bits of the second syllable are less critical than bits of the first syllable, and the second memory is distinct from the first memory based on at least a physical attribute. | 33. A non-transitory machine-readable medium having stored thereon data, which if performed by at least one machine, causes the at least one machine to fabricate at least one integrated circuit to perform a method comprising: reading a portion of a data word by a computer processor, wherein the data word includes a plurality of syllables and the reading of the portion of the data word includes: reading a first syllable of the plurality of syllables from a first memory; and reading a second syllable of the plurality of syllables from a second memory, wherein bits of the second syllable are less critical than bits of the first syllable, and the second memory is distinct from the first memory based on at least a physical attribute. 36. The machine-readable medium of claim 33 , wherein a first connection between the computer processor and the first memory includes stronger data bus repeaters than a second connection between the computer processor and the second memory. | 0.53668 |
9,760,547 | 1 | 14 | 1. A method of collaboratively modifying electronic online documents by client devices in a networked environment for display on graphical user interfaces, comprising: receiving, by a server having one or more processors in a content editing environment, from a first client device via a communication interface of the server, a search query including one or more keywords for content from the content editing environment, the content editing environment including a plurality of modes specifying content editing and viewing permissions; assigning, by the server, a first user identifier associated with the first client device to a search mode of the content editing environment; identifying, by the server, a plurality of content items based on the one or more keywords of the search query matching a corpus for each of the plurality of content items of the content editing environment; retrieving, by the server, a first plurality of recorded interests for the first user identifier, the first plurality of recorded interests comprising: one or more search queries received from the first client device including the search query, an indication of content items accessed by the first client device, an interaction with content items by the first client device, and one or more edited content items generated by the first client device; and identifying, by the server, a recorded interest common between the first plurality of recorded interests of the first user identifier and a second plurality of recorded interests of each of a plurality of second user identifiers; selecting, by the server, from the plurality of content items, one or more edited content items based on the recorded interest common between the first user identifier and each of the plurality of second user identifiers, each of the one or more edited content items associated with one or more identifiers of the plurality of second user identifiers; including, by the server, one or more hyperlinks for each of the one or more edited content items in an online document for display on an Internet user interface on the first client device; transmitting, by the server, the online document to the first client device; receiving, by the server, a first interaction indicator with a hyperlink of the one or more hyperlinks on the online document from the first client device, the first interaction indicator identifying a change on the Internet user interface from an address of the online document to an address of a selected content item corresponding to the hyperlink; assigning, by the server, responsive to receiving the first interaction indicator with the online document, the first user identifier to a view mode of the content editing environment, the view mode permitting the first client device to view a public-facing version of the selected content item; receiving, by the server, a second interaction indicator with an interface element for modifying the public-facing version of the selected content item; assigning, by the server, responsive to receiving the second interaction indicator, the first user identifier to an edit mode of the content editing environment, the edit mode permitting the first client device to modify the public-facing version of the selected content item; identifying, by the server, a region of overlap among a first edited text, a second edited text, and original text of the public-facing version of the selected content item, the first edited text and the second edited text each including modifications made via transclusion to the original text from the first user identifier or the plurality of second user identifiers; reducing, by the server, the region of overlap based on conflicting text among the first edited text, the second edited text, and the original text; determining, by the server, conflicting differences based on the region of overlap among the first edited text, the second edited text, and the original text; and transmitting, by the server, the conflicting differences to the first client device for display by the first client device of the conflicting differences on the selected content item. | 1. A method of collaboratively modifying electronic online documents by client devices in a networked environment for display on graphical user interfaces, comprising: receiving, by a server having one or more processors in a content editing environment, from a first client device via a communication interface of the server, a search query including one or more keywords for content from the content editing environment, the content editing environment including a plurality of modes specifying content editing and viewing permissions; assigning, by the server, a first user identifier associated with the first client device to a search mode of the content editing environment; identifying, by the server, a plurality of content items based on the one or more keywords of the search query matching a corpus for each of the plurality of content items of the content editing environment; retrieving, by the server, a first plurality of recorded interests for the first user identifier, the first plurality of recorded interests comprising: one or more search queries received from the first client device including the search query, an indication of content items accessed by the first client device, an interaction with content items by the first client device, and one or more edited content items generated by the first client device; and identifying, by the server, a recorded interest common between the first plurality of recorded interests of the first user identifier and a second plurality of recorded interests of each of a plurality of second user identifiers; selecting, by the server, from the plurality of content items, one or more edited content items based on the recorded interest common between the first user identifier and each of the plurality of second user identifiers, each of the one or more edited content items associated with one or more identifiers of the plurality of second user identifiers; including, by the server, one or more hyperlinks for each of the one or more edited content items in an online document for display on an Internet user interface on the first client device; transmitting, by the server, the online document to the first client device; receiving, by the server, a first interaction indicator with a hyperlink of the one or more hyperlinks on the online document from the first client device, the first interaction indicator identifying a change on the Internet user interface from an address of the online document to an address of a selected content item corresponding to the hyperlink; assigning, by the server, responsive to receiving the first interaction indicator with the online document, the first user identifier to a view mode of the content editing environment, the view mode permitting the first client device to view a public-facing version of the selected content item; receiving, by the server, a second interaction indicator with an interface element for modifying the public-facing version of the selected content item; assigning, by the server, responsive to receiving the second interaction indicator, the first user identifier to an edit mode of the content editing environment, the edit mode permitting the first client device to modify the public-facing version of the selected content item; identifying, by the server, a region of overlap among a first edited text, a second edited text, and original text of the public-facing version of the selected content item, the first edited text and the second edited text each including modifications made via transclusion to the original text from the first user identifier or the plurality of second user identifiers; reducing, by the server, the region of overlap based on conflicting text among the first edited text, the second edited text, and the original text; determining, by the server, conflicting differences based on the region of overlap among the first edited text, the second edited text, and the original text; and transmitting, by the server, the conflicting differences to the first client device for display by the first client device of the conflicting differences on the selected content item. 14. The method of claim 1 , comprising: assigning, by the server, the first user identifier to the search mode of the content editing environment, the search mode permitting the first client device to view search results generated based on the search query. | 0.791734 |
9,836,598 | 1 | 13 | 1. A method comprising: identifying, from a set of entities to be monitored, a subset of the set of entities for additional monitoring; performing the additional monitoring by: accessing a scoring rule that includes a search query, a triggering condition and a risk modifier, the scoring rule having been defined by information input via a user interface, the risk modifier indicative of an amount by which to adjust a risk score of a particular entity when the triggering condition is satisfied; after said accessing the scoring rule, executing the search query against a plurality of events associated with activity of the subset of the set of entities, wherein the search query produces a search result pertaining to activity of the particular entity, wherein each event of the plurality of events is associated with a timestamp and includes machine data; determining whether the search result meets the triggering condition; and responsive to determining that the search result meets the triggering condition, updating the risk score for the particular entity based on the risk modifier in the scoring rule, the risk score indicating a security threat associated with activity of the particular entity; and causing at least one of: display of an indication of the updated risk score, transmission of an indication of the updated risk score, or remedial action based on the updated risk score. | 1. A method comprising: identifying, from a set of entities to be monitored, a subset of the set of entities for additional monitoring; performing the additional monitoring by: accessing a scoring rule that includes a search query, a triggering condition and a risk modifier, the scoring rule having been defined by information input via a user interface, the risk modifier indicative of an amount by which to adjust a risk score of a particular entity when the triggering condition is satisfied; after said accessing the scoring rule, executing the search query against a plurality of events associated with activity of the subset of the set of entities, wherein the search query produces a search result pertaining to activity of the particular entity, wherein each event of the plurality of events is associated with a timestamp and includes machine data; determining whether the search result meets the triggering condition; and responsive to determining that the search result meets the triggering condition, updating the risk score for the particular entity based on the risk modifier in the scoring rule, the risk score indicating a security threat associated with activity of the particular entity; and causing at least one of: display of an indication of the updated risk score, transmission of an indication of the updated risk score, or remedial action based on the updated risk score. 13. The method of claim 1 , further comprising determining a statistical baseline, wherein determining the statistical baseline comprises: accessing the plurality of events indicating the activity of the set of entities; and determining a variance for the activity of the set of entities based on the plurality of events, wherein the triggering condition is satisfied when the search result indicates that the activity of the particular entity exceeds the statistical baseline by a predetermined portion of the variance. | 0.5 |
8,078,978 | 17 | 27 | 17. A method for predicting text while a message is being composed, comprising: generating a data structure associating, for each one of a plurality of a user's contacts, usage data about a history of usage of words in messages sent to and received from the user contact; updating the data structure as additional messages with each user contact are sent and received, and additional usage data is obtained therefrom; receiving an incoming message from one of the plurality of the user's contacts; and predicting text while the user is composing a reply to the incoming message, comprising: parsing the incoming message to identify questions, phone numbers and special phrases therein; presenting possible responses that the user may choose from, based on the questions, phone numbers and special phrases identified by said parsing; receiving as input from the user a character string; and generating as output an ordered list of predicted words, based on usage data in the data structure associated with the user contact from whom the incoming message was received. | 17. A method for predicting text while a message is being composed, comprising: generating a data structure associating, for each one of a plurality of a user's contacts, usage data about a history of usage of words in messages sent to and received from the user contact; updating the data structure as additional messages with each user contact are sent and received, and additional usage data is obtained therefrom; receiving an incoming message from one of the plurality of the user's contacts; and predicting text while the user is composing a reply to the incoming message, comprising: parsing the incoming message to identify questions, phone numbers and special phrases therein; presenting possible responses that the user may choose from, based on the questions, phone numbers and special phrases identified by said parsing; receiving as input from the user a character string; and generating as output an ordered list of predicted words, based on usage data in the data structure associated with the user contact from whom the incoming message was received. 27. The method of claim 17 wherein said parsing identifies a question that begins with “When”, and wherein said presenting presents a list of response words the user may choose from, the response words including “at”. | 0.676119 |
8,924,398 | 1 | 9 | 1. An automatic database command method, comprising: obtaining a plurality of relevant database log entries, the relevant database log entries being directed to database catalog entities; determining a first portion of the plurality of relevant database log entries are part of a common unit of recovery, the first portion including a plurality of database log entries; assigning the first portion of database log entries to a particular Data Definition Language (DDL) command object based on analysis of attributes of a first entry in the first portion of the database log entries, the particular DDL command object including a timestamp, an action, a target, and data from each of the first portion of database log entries; determining a DDL command object break when an action or target of a next database log entry in the first portion is inconsistent with the particular DDL command object; storing the particular DDL command object in a memory in response to determining the DDL command object break; receiving an indication of an operation type subsequent to the storing, the operation type being an UNDO or a MIGRATE operation type; ordering the entries in the particular DDL command object in an order based on the type of operation, the targets, and the actions; and generating at least one database command based on the operation type, the action, target, and data in each of the ordered entries in the particular DDL command object. | 1. An automatic database command method, comprising: obtaining a plurality of relevant database log entries, the relevant database log entries being directed to database catalog entities; determining a first portion of the plurality of relevant database log entries are part of a common unit of recovery, the first portion including a plurality of database log entries; assigning the first portion of database log entries to a particular Data Definition Language (DDL) command object based on analysis of attributes of a first entry in the first portion of the database log entries, the particular DDL command object including a timestamp, an action, a target, and data from each of the first portion of database log entries; determining a DDL command object break when an action or target of a next database log entry in the first portion is inconsistent with the particular DDL command object; storing the particular DDL command object in a memory in response to determining the DDL command object break; receiving an indication of an operation type subsequent to the storing, the operation type being an UNDO or a MIGRATE operation type; ordering the entries in the particular DDL command object in an order based on the type of operation, the targets, and the actions; and generating at least one database command based on the operation type, the action, target, and data in each of the ordered entries in the particular DDL command object. 9. The method of claim 1 , wherein determining the first portion of the plurality of relevant database log entries are part of the common unit of recovery comprises: determining a first database log entry from the plurality of relevant database log entries is identified as a first database log entry in the common unit of recovery; and determining one or more additional database log entries from the plurality of relevant database log entries identifies the common unit of recovery. | 0.521739 |
7,570,379 | 20 | 24 | 20. A program product according to claim 19 wherein after said step of submitting, said method further comprises a step of verifying, at said print service provider location, that said production ready document will be produced at said print service provider location as designed at the designer location and, if not, correcting said production ready document to ensure production substantially as designed. | 20. A program product according to claim 19 wherein after said step of submitting, said method further comprises a step of verifying, at said print service provider location, that said production ready document will be produced at said print service provider location as designed at the designer location and, if not, correcting said production ready document to ensure production substantially as designed. 24. A program product according to claim 20 wherein said selected document profile is generated and stored at the print service provider location and selected at the designer location over said electronic network. | 0.654221 |
9,798,748 | 35 | 37 | 35. A system comprising: one or more processors; an input handler executed by at least one of the processors and configured to receive a keyword by which to search a content index of a database for a corresponding data source from a plurality of data sources associated with the database, the data sources including metadata, fields and data populating the database; a search engine executed by at least one of the processors and configured to search the content index for the keyword, and to provide metadata from the content index corresponding to the keyword; the input handler being configured to receive a selection from the metadata; a query engine executed by at least one of the processors and configured to provide, responsive to the selection of the metadata, a first graphical icon in a graphical user interface, the first graphical icon representing the selected metadata, and to provide in the graphical user interface a second graphical icon representing a corresponding data source, wherein the input handler is configured to determine that the first graphical icon is graphically associated within the graphical user interface with the second graphical icon; and a translation engine configured to provide, responsive to the graphical association of the first and second graphical icons, a list of natural language queries to perform between the selected metadata and the data source, the natural language queries including intuitive descriptions of the natural language queries based on the selected metadata and an experience level of the user, the intuitive descriptions being different for users with different levels of experience, wherein the query engine is configured to query the database using query parameters based on the data source and a natural language query selected from the list of natural language queries. | 35. A system comprising: one or more processors; an input handler executed by at least one of the processors and configured to receive a keyword by which to search a content index of a database for a corresponding data source from a plurality of data sources associated with the database, the data sources including metadata, fields and data populating the database; a search engine executed by at least one of the processors and configured to search the content index for the keyword, and to provide metadata from the content index corresponding to the keyword; the input handler being configured to receive a selection from the metadata; a query engine executed by at least one of the processors and configured to provide, responsive to the selection of the metadata, a first graphical icon in a graphical user interface, the first graphical icon representing the selected metadata, and to provide in the graphical user interface a second graphical icon representing a corresponding data source, wherein the input handler is configured to determine that the first graphical icon is graphically associated within the graphical user interface with the second graphical icon; and a translation engine configured to provide, responsive to the graphical association of the first and second graphical icons, a list of natural language queries to perform between the selected metadata and the data source, the natural language queries including intuitive descriptions of the natural language queries based on the selected metadata and an experience level of the user, the intuitive descriptions being different for users with different levels of experience, wherein the query engine is configured to query the database using query parameters based on the data source and a natural language query selected from the list of natural language queries. 37. The system of claim 35 wherein the search engine is configured to provide a list of data sources based on level of relevance between each data source and the keyword. | 0.730159 |
9,704,575 | 1 | 2 | 1. A device comprising: content-addressable memory cells arranged in rows, two of the rows are timing reference rows and the remainder of the rows are data rows maintaining words of data, the data rows comprise individual matchlines, a first reference row of the reference rows comprises a precharge reference matchline, a second reference row of the reference rows comprises an evaluation reference matchline, the precharge reference matchline is hardwired to match all bits and timing for the individual matchlines to precharge is based on a time to precharge the precharge reference matchline, and the evaluation reference matchline is hardwired to a one-bit-miss word that has only one bit not producing a match and timing for the individual matchlines to evaluate a search word is based on a time for the evaluation reference matchline to evaluate the search word. | 1. A device comprising: content-addressable memory cells arranged in rows, two of the rows are timing reference rows and the remainder of the rows are data rows maintaining words of data, the data rows comprise individual matchlines, a first reference row of the reference rows comprises a precharge reference matchline, a second reference row of the reference rows comprises an evaluation reference matchline, the precharge reference matchline is hardwired to match all bits and timing for the individual matchlines to precharge is based on a time to precharge the precharge reference matchline, and the evaluation reference matchline is hardwired to a one-bit-miss word that has only one bit not producing a match and timing for the individual matchlines to evaluate a search word is based on a time for the evaluation reference matchline to evaluate the search word. 2. The device according to claim 1 , further comprising a controller connected to the individual matchlines, the precharge reference matchline, and the evaluation reference matchline, the controller determines when a precharging operation of the individual matchlines is completed based upon a precharging operation being completed within the precharge reference matchline, and the controller determines when an evaluation operation of the individual matchlines is completed based upon an evaluation operation being completed within the evaluation reference matchline. | 0.5 |
7,689,554 | 25 | 29 | 25. A system for identifying one or more queries related to a given query, the system comprising: a data store comprising a storage medium for storing a searchable query set; a search engine comprising one or more processing elements for receiving a query written according to one or more writing systems of a language with multiple writing systems, and identifying a candidate set of one or more queries in the data store, the candidate set of queries written according to one or more writing systems of the language with multiple writing systems; a conversion component comprising one or more processing elements for converting the received query and the one or more queries in the candidate set into one or more written formats; a similarity component comprising one or more processing elements for calculating a number of common characters in a given candidate query before disagreement with the query received, the similarity component further calculating a number of total common characters between the given candidate query and the query received and calculating a quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs; and a similarity score component comprising one or more processing elements for calculating a similarity score on the basis of the number of common characters before disagreement, the total number of characters for the one or more queries in the candidate set and the quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs indicating the similarity of the one or more queries with respect to the received query. | 25. A system for identifying one or more queries related to a given query, the system comprising: a data store comprising a storage medium for storing a searchable query set; a search engine comprising one or more processing elements for receiving a query written according to one or more writing systems of a language with multiple writing systems, and identifying a candidate set of one or more queries in the data store, the candidate set of queries written according to one or more writing systems of the language with multiple writing systems; a conversion component comprising one or more processing elements for converting the received query and the one or more queries in the candidate set into one or more written formats; a similarity component comprising one or more processing elements for calculating a number of common characters in a given candidate query before disagreement with the query received, the similarity component further calculating a number of total common characters between the given candidate query and the query received and calculating a quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs; and a similarity score component comprising one or more processing elements for calculating a similarity score on the basis of the number of common characters before disagreement, the total number of characters for the one or more queries in the candidate set and the quotient of the frequency with which a selected query from the candidate set follows the received query in one or more query logs and the frequency of the received query in the one or more query logs indicating the similarity of the one or more queries with respect to the received query. 29. The system of claim 25 wherein the conversion component converts a query into one or more written formats in accordance with one or more writing systems. | 0.857532 |
8,868,539 | 12 | 17 | 12. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing devices, cause performance of: generating one or more query logs that record information about previously received search queries, including, for the previously received search queries, indications of in which specific contexts, of a plurality of search contexts, the previously received search queries have been made over at least a period of time; receiving a search query; determining at least one suggested query, of the previously received search queries, based on the search query; determining, for each specific search context of a plurality of search contexts: a log-based relevance score of the search query to the specific search context, the log-based relevance score being calculated, at least in part, using a count of how many times the search query was made in the specific search context over the period of time, and further using a count of how many times the suggested query was made in the specific search context over the period of time, as recorded in the one or more query logs; wherein each search context of the plurality of search contexts is a different set of searchable information; responsive to receiving the search query, sending an indication, for each specific search context of the plurality of search contexts, of a relative size of the log-based relevance score determined for the specific search context compared to relative sizes of each other log-based relevance score determined for each other search context of the plurality of search contexts. | 12. One or more non-transitory computer-readable media storing instructions that, when executed by one or more computing devices, cause performance of: generating one or more query logs that record information about previously received search queries, including, for the previously received search queries, indications of in which specific contexts, of a plurality of search contexts, the previously received search queries have been made over at least a period of time; receiving a search query; determining at least one suggested query, of the previously received search queries, based on the search query; determining, for each specific search context of a plurality of search contexts: a log-based relevance score of the search query to the specific search context, the log-based relevance score being calculated, at least in part, using a count of how many times the search query was made in the specific search context over the period of time, and further using a count of how many times the suggested query was made in the specific search context over the period of time, as recorded in the one or more query logs; wherein each search context of the plurality of search contexts is a different set of searchable information; responsive to receiving the search query, sending an indication, for each specific search context of the plurality of search contexts, of a relative size of the log-based relevance score determined for the specific search context compared to relative sizes of each other log-based relevance score determined for each other search context of the plurality of search contexts. 17. The one or more non-transitory computer-readable media of claim 12 , wherein the indication comprises, for each specific search context of the plurality of search contexts, an indicator of the log-based relevance score determined for the specific search context, and a shortcut link for accessing a content location associated with the specific search context. | 0.803243 |
9,823,806 | 15 | 17 | 15. A computer program product comprising a non-transitory computer-readable storage medium containing computer program code for performing the steps: providing for display a plurality of options for selecting a sponsored story specification for generating a sponsored story in an online social networking system, the sponsored story comprising promoting a story selected from an organic activity stream of stories in the online social networking system; providing for display one or more entities in the online social networking system for use in generating the sponsored story specification related to one of the entities; receiving a first user input selecting a target entity from the one or more entities as a first criterion for the sponsored story specification; providing for display one or more interactions for use in generating the sponsored story specification, each interaction comprising information about a user action with the selected entity taken in the online social networking system; receiving a second user input selecting a target interaction comprising a user action with the selected entity taken in the online social networking system as a second criterion for the sponsored story; generating, by a computer processor, a new sponsored story specification, the sponsored story specification specifying the first and second criteria for identifying, from the organic activity stream of stories in the online social networking system, one or more stories describing the selected interaction taken on the selected target entity in the online social networking system; and receiving input activating the new sponsored story specification. | 15. A computer program product comprising a non-transitory computer-readable storage medium containing computer program code for performing the steps: providing for display a plurality of options for selecting a sponsored story specification for generating a sponsored story in an online social networking system, the sponsored story comprising promoting a story selected from an organic activity stream of stories in the online social networking system; providing for display one or more entities in the online social networking system for use in generating the sponsored story specification related to one of the entities; receiving a first user input selecting a target entity from the one or more entities as a first criterion for the sponsored story specification; providing for display one or more interactions for use in generating the sponsored story specification, each interaction comprising information about a user action with the selected entity taken in the online social networking system; receiving a second user input selecting a target interaction comprising a user action with the selected entity taken in the online social networking system as a second criterion for the sponsored story; generating, by a computer processor, a new sponsored story specification, the sponsored story specification specifying the first and second criteria for identifying, from the organic activity stream of stories in the online social networking system, one or more stories describing the selected interaction taken on the selected target entity in the online social networking system; and receiving input activating the new sponsored story specification. 17. The computer program product of claim 15 , wherein the entity comprises a business, an individual, a television show, an application, or a physical location. | 0.569519 |
8,977,641 | 10 | 21 | 10. A system comprising: a data processing apparatus; and a computer storage medium encoded with a computer program, the program comprising instructions that when executed by the data processing apparatus cause the data processing apparatus to perform operations comprising: receiving a first search query from a user; determining a topic associated with the first search query; determining a second search query as a suggested query to guide the user into interaction with other users who have submitted similar search queries, the second search query being associated with the topic and being different from the first search query; sending the second search query to the user, the second search query being associated with the topic and being different from the first search query; receiving a selection of the second search query from the user; determining a second query traffic volume, the second query traffic volume indicating a number of times the second search query has been received from other users within a time window; determining that the second query traffic volume is greater than a predetermined threshold traffic volume, the threshold traffic volume being indicative of a level of interest in the topic; and in response to determining that the second query traffic volume is greater than the threshold traffic volume, sending an invitation to the user, the invitation for inviting participation in an online social group comprised of others other users who have sent the second query to the server system within the time window. | 10. A system comprising: a data processing apparatus; and a computer storage medium encoded with a computer program, the program comprising instructions that when executed by the data processing apparatus cause the data processing apparatus to perform operations comprising: receiving a first search query from a user; determining a topic associated with the first search query; determining a second search query as a suggested query to guide the user into interaction with other users who have submitted similar search queries, the second search query being associated with the topic and being different from the first search query; sending the second search query to the user, the second search query being associated with the topic and being different from the first search query; receiving a selection of the second search query from the user; determining a second query traffic volume, the second query traffic volume indicating a number of times the second search query has been received from other users within a time window; determining that the second query traffic volume is greater than a predetermined threshold traffic volume, the threshold traffic volume being indicative of a level of interest in the topic; and in response to determining that the second query traffic volume is greater than the threshold traffic volume, sending an invitation to the user, the invitation for inviting participation in an online social group comprised of others other users who have sent the second query to the server system within the time window. 21. The system of claim 10 , wherein determining the topic comprises performing a search of a search index using the first search query to identify the topic; and wherein the operations further comprise correlating the topic to the second search query, the second search query relating to the topic but being different from the first search query. | 0.5 |
8,375,046 | 15 | 21 | 15. A system, comprising a plurality of devices coupled via a network, wherein each device is configured to: receive an abstract query from a requesting entity, wherein the abstract query comprises one or more logical fields defined in a first data abstraction model comprising a plurality of first logical field definitions mapping to physical fields of a first database; wherein the one or more logical fields in the abstract query each have a respective concept code relating corresponding logical field definitions of a plurality of data abstraction models including the first data abstraction model, a second data abstraction model and a third data abstraction model, the second data abstraction model being resident on the device at which the abstract query is received and comprising a plurality of second logical field definitions mapping to physical fields of a second database; modify the abstract query to include one or more of the second logical field definitions from the second data abstraction model based on the respective concept codes; issue the modified abstract query against the second database to retrieve a first set of results for the modified abstract query; send the abstract query to at least one other device of the plurality of devices, the at least one other device comprising the third data abstraction model comprising a plurality of third logical field definitions mapping to physical fields of a third database, wherein the first, second and third data abstraction models, and their respective logical field definitions, are distinct from one another, and wherein the at least one other device is configured to modify the abstract query to include one or more of the third logical field definitions from the third data abstraction model based on the respective concept codes; receive a second set of results for the abstract query from the at least one other device; and provide the first and second set of results to the requesting entity. | 15. A system, comprising a plurality of devices coupled via a network, wherein each device is configured to: receive an abstract query from a requesting entity, wherein the abstract query comprises one or more logical fields defined in a first data abstraction model comprising a plurality of first logical field definitions mapping to physical fields of a first database; wherein the one or more logical fields in the abstract query each have a respective concept code relating corresponding logical field definitions of a plurality of data abstraction models including the first data abstraction model, a second data abstraction model and a third data abstraction model, the second data abstraction model being resident on the device at which the abstract query is received and comprising a plurality of second logical field definitions mapping to physical fields of a second database; modify the abstract query to include one or more of the second logical field definitions from the second data abstraction model based on the respective concept codes; issue the modified abstract query against the second database to retrieve a first set of results for the modified abstract query; send the abstract query to at least one other device of the plurality of devices, the at least one other device comprising the third data abstraction model comprising a plurality of third logical field definitions mapping to physical fields of a third database, wherein the first, second and third data abstraction models, and their respective logical field definitions, are distinct from one another, and wherein the at least one other device is configured to modify the abstract query to include one or more of the third logical field definitions from the third data abstraction model based on the respective concept codes; receive a second set of results for the abstract query from the at least one other device; and provide the first and second set of results to the requesting entity. 21. The system of claim 15 , wherein the plurality of devices are servers. | 0.888218 |
7,647,309 | 34 | 41 | 34. A computer-implemented method for determining a browse relevance score for an item classified in multiple categories, the method comprising: a computing device comprising a memory, the memory storing instructions that, when executed, cause the computing device to: identify each category with which the item is classified; and for each identified category: determine a category fit score for the item; determine a browse score for the item based on the historical activities of users within a browse node that corresponds to the category; determine a prediction boost score that provides an additional score if the item is part of a market trend or the item is based on a popular theme; determine a popularity score for the item based on the popularity of the item and based at least in part upon the prediction boost score; and determine a browse relevance score for each item with respect to the category by summing at least the category fit score, the browse score, and the popularity score, and multiplying a result of the summing for each item by a price range score for the item, wherein the browse relevance score for each identified category is used to select an arrangement of the item in a display generated for any of the identified categories. | 34. A computer-implemented method for determining a browse relevance score for an item classified in multiple categories, the method comprising: a computing device comprising a memory, the memory storing instructions that, when executed, cause the computing device to: identify each category with which the item is classified; and for each identified category: determine a category fit score for the item; determine a browse score for the item based on the historical activities of users within a browse node that corresponds to the category; determine a prediction boost score that provides an additional score if the item is part of a market trend or the item is based on a popular theme; determine a popularity score for the item based on the popularity of the item and based at least in part upon the prediction boost score; and determine a browse relevance score for each item with respect to the category by summing at least the category fit score, the browse score, and the popularity score, and multiplying a result of the summing for each item by a price range score for the item, wherein the browse relevance score for each identified category is used to select an arrangement of the item in a display generated for any of the identified categories. 41. The computer-implemented method of claim 34 , wherein the browse relevance score is a percentage. | 0.725543 |
7,865,452 | 1 | 10 | 1. A computer-implemented method comprising steps of: receiving one or more answer submissions at an online answer submission system that accepts, from multiple users, answers to questions submitted to the online answer submission system by users other than those that submitted the one or more answer submissions; processing a set of previously scored training submissions, thereby training a machine learning mechanism to score, automatically, a plurality of submissions that are submitted by users of a system; scoring a particular submission of said plurality of submissions automatically using the machine learning mechanism, thereby producing a score; and performing, relative to the particular submission, an action that is determined based on said score; wherein said previously scored training submissions are also answers to questions submitted to the online answer submission system; wherein said steps are performed by one or more computing devices. | 1. A computer-implemented method comprising steps of: receiving one or more answer submissions at an online answer submission system that accepts, from multiple users, answers to questions submitted to the online answer submission system by users other than those that submitted the one or more answer submissions; processing a set of previously scored training submissions, thereby training a machine learning mechanism to score, automatically, a plurality of submissions that are submitted by users of a system; scoring a particular submission of said plurality of submissions automatically using the machine learning mechanism, thereby producing a score; and performing, relative to the particular submission, an action that is determined based on said score; wherein said previously scored training submissions are also answers to questions submitted to the online answer submission system; wherein said steps are performed by one or more computing devices. 10. The method of claim 1 , wherein training the machine learning mechanism comprises training the machine learning mechanism based on at least one of: (a) character distribution entropy in a submission of the plurality of submissions, (b) word distribution entropy in a submission of the plurality of submissions, (c) word length distribution entropy in a submission of the plurality of submissions, (d) a length of a submission of the plurality of submissions, (e) lexical distance between submission text that contains misspellings and corresponding reference text that does not contain misspellings, and (f) a number of words in a submission of the plurality of submissions that are absent from a dictionary of known words for a specific language. | 0.5 |
10,156,455 | 9 | 10 | 9. The method of claim 1 , wherein providing the allowed type of audio prompt further comprises: providing a verbal prompt when verbal prompts are allowed and a service is currently playing audio on the device; pausing the audio currently played on the device; playing the verbal prompt; and resuming playing the audio by the service after the verbal prompt is played. | 9. The method of claim 1 , wherein providing the allowed type of audio prompt further comprises: providing a verbal prompt when verbal prompts are allowed and a service is currently playing audio on the device; pausing the audio currently played on the device; playing the verbal prompt; and resuming playing the audio by the service after the verbal prompt is played. 10. The method of claim 9 , wherein the service is playing an audio book. | 0.5 |
9,424,823 | 1 | 10 | 1. A method, implemented by a music symbol recognition apparatus for recognising music symbols based on handwritten music notations, said method comprising: detecting handwritten music notations; pre-segmenting said handwritten music notations into a plurality of elementary ink segments; grouping the elementary ink segments into graphical objects based on spatial relationships between elementary ink segments, wherein each elementary ink segment belongs to one or more of said graphical objects; determining for each graphical object at least one music symbol candidate, in association with an assigned symbol cost, the symbol cost representing the probability of said graphical object belonging to a predetermined class of said music symbol candidate, said determining being based on graphical features extracted from said graphical object; and parsing the music symbol candidates, wherein said parsing comprises: forming one or more graphs by applying at least one of a predetermined set of grammar rules to said music symbol candidates, wherein each graph comprises at least one non-terminal node corresponding to a grammar rule applied to a set of at least one descendant node, and wherein each descendant node is either a terminal node corresponding to a music symbol candidate or a non-terminal-node corresponding to a grammar rule applied to at least one other descendant node; associating each grammar rule applied to at least two descendant nodes with a spatial cost representative of the pertinence of said applied grammar rule based on the spatial relationships between the graphical objects of said at least two descendant nodes; and selecting at least one said graph as the most representative graph of the handwritten music notations based on the symbol costs associated with each music symbol candidate and the spatial costs associated with each applied grammar rule. | 1. A method, implemented by a music symbol recognition apparatus for recognising music symbols based on handwritten music notations, said method comprising: detecting handwritten music notations; pre-segmenting said handwritten music notations into a plurality of elementary ink segments; grouping the elementary ink segments into graphical objects based on spatial relationships between elementary ink segments, wherein each elementary ink segment belongs to one or more of said graphical objects; determining for each graphical object at least one music symbol candidate, in association with an assigned symbol cost, the symbol cost representing the probability of said graphical object belonging to a predetermined class of said music symbol candidate, said determining being based on graphical features extracted from said graphical object; and parsing the music symbol candidates, wherein said parsing comprises: forming one or more graphs by applying at least one of a predetermined set of grammar rules to said music symbol candidates, wherein each graph comprises at least one non-terminal node corresponding to a grammar rule applied to a set of at least one descendant node, and wherein each descendant node is either a terminal node corresponding to a music symbol candidate or a non-terminal-node corresponding to a grammar rule applied to at least one other descendant node; associating each grammar rule applied to at least two descendant nodes with a spatial cost representative of the pertinence of said applied grammar rule based on the spatial relationships between the graphical objects of said at least two descendant nodes; and selecting at least one said graph as the most representative graph of the handwritten music notations based on the symbol costs associated with each music symbol candidate and the spatial costs associated with each applied grammar rule. 10. The method according to claim 1 , wherein said determining for each graphical object at least one music symbol candidate is performed by a neural network. | 0.811005 |
9,430,471 | 1 | 6 | 1. A computer-implemented method executed by one or more computing devices for generating a value index corresponding to a user, the method comprising: generating, by at least one of the one or more computing devices, a set of demographic nouns corresponding to a user based on one or more of: registration information provided by the user or data derived from an analysis of a connection of the user; generating, by at least one of the one or more computing devices, one or more sets of taxonomic nouns corresponding to the user, wherein the one or more sets of taxonomic nouns comprise one or more of: a set of first taxonomic nouns based upon classification information generated by an author of at least one document in a set of documents; a set of second taxonomic nouns based upon one or more user-generated tags characterizing at least a portion of at least one document in the set of documents; a set of third taxonomic nouns based upon one or more search terms utilized by the user to access at least one document in the set of documents; or a set of fourth taxonomic nouns based upon the attributes related to a method of access of at least one document in the set of documents; generating, by at least one of the one or more computing devices, a set of fifth taxonomic nouns corresponding to the user by processing at least one document in the set of documents based upon one or more pattern rules and a dictionary of known terms, wherein the one or more pattern rules specify a method of extracting terms from the at least one document; aggregating, by at least one of the one or more computing devices, at least one of the one or more sets of taxonomic nouns with the set of fifth taxonomic nouns into a composite set of taxonomic nouns corresponding to the user; and generating, by at least one of the one or more computing devices, a value index corresponding to the user based at least in part on a comparison between: a quantity of nouns in the set of demographic nouns corresponding to the user and the composite set of taxonomic nouns corresponding to the user, and one or more quantities of nouns in one or more sets of demographic nouns corresponding to one or more other users and one or more composite sets of taxonomic nouns corresponding to the one or more other users. | 1. A computer-implemented method executed by one or more computing devices for generating a value index corresponding to a user, the method comprising: generating, by at least one of the one or more computing devices, a set of demographic nouns corresponding to a user based on one or more of: registration information provided by the user or data derived from an analysis of a connection of the user; generating, by at least one of the one or more computing devices, one or more sets of taxonomic nouns corresponding to the user, wherein the one or more sets of taxonomic nouns comprise one or more of: a set of first taxonomic nouns based upon classification information generated by an author of at least one document in a set of documents; a set of second taxonomic nouns based upon one or more user-generated tags characterizing at least a portion of at least one document in the set of documents; a set of third taxonomic nouns based upon one or more search terms utilized by the user to access at least one document in the set of documents; or a set of fourth taxonomic nouns based upon the attributes related to a method of access of at least one document in the set of documents; generating, by at least one of the one or more computing devices, a set of fifth taxonomic nouns corresponding to the user by processing at least one document in the set of documents based upon one or more pattern rules and a dictionary of known terms, wherein the one or more pattern rules specify a method of extracting terms from the at least one document; aggregating, by at least one of the one or more computing devices, at least one of the one or more sets of taxonomic nouns with the set of fifth taxonomic nouns into a composite set of taxonomic nouns corresponding to the user; and generating, by at least one of the one or more computing devices, a value index corresponding to the user based at least in part on a comparison between: a quantity of nouns in the set of demographic nouns corresponding to the user and the composite set of taxonomic nouns corresponding to the user, and one or more quantities of nouns in one or more sets of demographic nouns corresponding to one or more other users and one or more composite sets of taxonomic nouns corresponding to the one or more other users. 6. The method of claim 1 , wherein the value index corresponding to the user is generated based at least in part on a comparison between: a quantity of unique nouns in the set of demographic nouns corresponding to the user and the composite set of taxonomic nouns corresponding to the user, and one or more quantities of unique nouns in the one or more sets of demographic nouns corresponding to the one or more other users and the one or more composite sets of taxonomic nouns corresponding to the one or more other users. | 0.616006 |
8,510,249 | 2 | 3 | 2. The information analysis apparatus according to claim 1 , further comprising: a unit-of-analysis generation unit that generates a plurality of the units of analysis from the text information, wherein the density estimation unit estimates the density for each unit of analysis generated by the unit-of-analysis generation unit. | 2. The information analysis apparatus according to claim 1 , further comprising: a unit-of-analysis generation unit that generates a plurality of the units of analysis from the text information, wherein the density estimation unit estimates the density for each unit of analysis generated by the unit-of-analysis generation unit. 3. The information analysis apparatus according to claim 2 , wherein the unit-of-analysis generation unit generates the plurality of units of analysis, such that a sentence included in each unit of analysis coincides with a sentence included in another unit of analysis. | 0.910773 |
8,578,328 | 13 | 14 | 13. The method according to claim 1 , further comprising the steps of: displaying a link icon (a first link icon) for the first component on or near the first component; and displaying a link icon (a second link icon) for each of the second component on or near the second component when the second component has one or more second tags matching any one, some or all of the selected first tags. | 13. The method according to claim 1 , further comprising the steps of: displaying a link icon (a first link icon) for the first component on or near the first component; and displaying a link icon (a second link icon) for each of the second component on or near the second component when the second component has one or more second tags matching any one, some or all of the selected first tags. 14. The method according to claim 13 , wherein the step of displaying the second link icon on or near the second component further includes a step of displaying the second link icon on or near a display of a property assigned a second tag matching the selected first tag. | 0.532759 |
9,753,974 | 11 | 20 | 11. A network device comprising: a transceiver that is operative to communicate over a network; a memory that is operative to store at least instructions; and a processor device that is operative to execute instructions that enable actions, including: providing a datastore comprising a plurality of time-stamped, searchable events, each event having a portion of raw data and a timestamp extracted from the portion of raw data, the portion of raw data produced by at least one hardware system; providing a data structure that contains a plurality of field names, each field name among the plurality of field names associated with a set of pointers to time-stamped, searchable events having a value for a field referred to by the field name; receiving an incoming search query that references one or more field names among the plurality of field names contained in the data structure and a time range criteria; and in response to the incoming search query, servicing the incoming search query by: (i) executing the incoming search query across the data structure, wherein one or more values from the data structure are used to create a search result; and (ii) supplementing the search result by executing a search comprising the time range criteria of the incoming search query across the time-stamped searchable events, independent of the data structure. | 11. A network device comprising: a transceiver that is operative to communicate over a network; a memory that is operative to store at least instructions; and a processor device that is operative to execute instructions that enable actions, including: providing a datastore comprising a plurality of time-stamped, searchable events, each event having a portion of raw data and a timestamp extracted from the portion of raw data, the portion of raw data produced by at least one hardware system; providing a data structure that contains a plurality of field names, each field name among the plurality of field names associated with a set of pointers to time-stamped, searchable events having a value for a field referred to by the field name; receiving an incoming search query that references one or more field names among the plurality of field names contained in the data structure and a time range criteria; and in response to the incoming search query, servicing the incoming search query by: (i) executing the incoming search query across the data structure, wherein one or more values from the data structure are used to create a search result; and (ii) supplementing the search result by executing a search comprising the time range criteria of the incoming search query across the time-stamped searchable events, independent of the data structure. 20. The network device of claim 11 , further comprising: while creating the data structure, searching the time-stamped searchable events for a value for a field using the extraction rule. | 0.740997 |
8,004,539 | 3 | 34 | 3. The method of claim 2 , wherein the determining to display the transformation object comprises: determining a type of the graphical editing operation; and determining that the transformation object is associated with the type of the graphical editing operation. | 3. The method of claim 2 , wherein the determining to display the transformation object comprises: determining a type of the graphical editing operation; and determining that the transformation object is associated with the type of the graphical editing operation. 34. The article of claim 3 , wherein the converted transformation object comprises the second parameter comprising the value associated with the transformation. | 0.5 |
7,835,999 | 14 | 16 | 14. At a computer system including a multi-touch input display surface, a method for recognizing input gesture data entered at the multi-touch input display surface as a specified symbol, the method comprising: an act of accessing input gesture data representing detected contact on the multi-touch input display surface over a period of time, the input gesture data including at least: first direction movement data, the first direction movement data being a first calculated graph including a directional axis corresponding to a first axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the first calculated graph indicating the position of detected contact on the multi-touch input display surface relative to the first axis over the time period; and second direction movement data, the second direction movement data being a second calculated graph including a directional axis corresponding to a second axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the second calculated graph indicating the position of detected contact on the multi-touch input display surface relative to a second different axis over the time period; an act of taking a plurality of samples of each of the first direction movement data and the second direction movement data at a plurality of designated intervals between the beginning of the time period and the end of the time period; an act of submitting the plurality of samples, including submitting real values, each real value corresponding to a time value from the period of time contact was detected on the multi-touch input display surface and including a directional axis value, to a corresponding plurality of input nodes of a neural network, the neural network having previously trained link weights from the input nodes to a plurality of hidden nodes and the neural network having previously trained link weights from the plurality of hidden nodes to a plurality of output nodes, each output node assigned to a specified symbol such that an output node being activated to a specified threshold value is indicative of the neural network recognizing input gesture data as the specified symbol; an act of the neural network processing the plurality of samples based on the previously trained link weights to activate values at each of the plurality of output nodes; an act of determining that the activated value at the specified output node assigned to the specified symbol is at least the specified threshold value; and an act of indicating that the specified symbol has been recognized from the input gesture data. | 14. At a computer system including a multi-touch input display surface, a method for recognizing input gesture data entered at the multi-touch input display surface as a specified symbol, the method comprising: an act of accessing input gesture data representing detected contact on the multi-touch input display surface over a period of time, the input gesture data including at least: first direction movement data, the first direction movement data being a first calculated graph including a directional axis corresponding to a first axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the first calculated graph indicating the position of detected contact on the multi-touch input display surface relative to the first axis over the time period; and second direction movement data, the second direction movement data being a second calculated graph including a directional axis corresponding to a second axis and a time axis corresponding to the period of time contact was detected on the multi-touch input display surface, the second calculated graph indicating the position of detected contact on the multi-touch input display surface relative to a second different axis over the time period; an act of taking a plurality of samples of each of the first direction movement data and the second direction movement data at a plurality of designated intervals between the beginning of the time period and the end of the time period; an act of submitting the plurality of samples, including submitting real values, each real value corresponding to a time value from the period of time contact was detected on the multi-touch input display surface and including a directional axis value, to a corresponding plurality of input nodes of a neural network, the neural network having previously trained link weights from the input nodes to a plurality of hidden nodes and the neural network having previously trained link weights from the plurality of hidden nodes to a plurality of output nodes, each output node assigned to a specified symbol such that an output node being activated to a specified threshold value is indicative of the neural network recognizing input gesture data as the specified symbol; an act of the neural network processing the plurality of samples based on the previously trained link weights to activate values at each of the plurality of output nodes; an act of determining that the activated value at the specified output node assigned to the specified symbol is at least the specified threshold value; and an act of indicating that the specified symbol has been recognized from the input gesture data. 16. The method as recited in claim 14 , wherein the act of submitting the plurality of samples to a corresponding plurality of input nodes of a neural network comprises an act of submitting the plurality of samples to a neural network that was trained to recognize characters of a specified alphabet. | 0.5 |
8,219,561 | 1 | 2 | 1. A computer-implemented method associated with a programming language in an application server that includes access to different database server implementations, wherein the programming language accesses content of database tables via work areas derived from the database tables, comprising: defining mapping of a database table, having columns to store content, each column is associated with a column type, to a work area such that, at a database server, each column in the database table is mapped to a corresponding component of the work area, the corresponding component having a default component type based on the column type of the associated column in the database table; determining that a particular column in the database table is to store large object data content; in response to the determination, automatically defining a new mapping to a work area such that the particular column maps to a corresponding component having a component type other than the default component type, wherein, as a result of said new mapping, the programming language accesses a sub-portion of the large object data content by changing the content of the large object data content via a locator and the programming language writes a sub-portion of the large object data content via the work area with at least one of an INSERT statement, an UPDATE statement, or a MODIFY statement associated with at least one of: (i) CL_ABAP_DB_C_LOCATOR and CL_ABAP_DB_X_LOCATOR for a locator, or (ii) CL_ABAP_DB_C_WRITER, CL_ABAP_DB_X_WRITER for a stream writer; determining a change to a structure of the database table; and responsive to the change to the structure of the database table, automatically adjusting the mapping of the database table to the work area such that the column to store large object data content is still mapped to a component having a component type other than the default component type. | 1. A computer-implemented method associated with a programming language in an application server that includes access to different database server implementations, wherein the programming language accesses content of database tables via work areas derived from the database tables, comprising: defining mapping of a database table, having columns to store content, each column is associated with a column type, to a work area such that, at a database server, each column in the database table is mapped to a corresponding component of the work area, the corresponding component having a default component type based on the column type of the associated column in the database table; determining that a particular column in the database table is to store large object data content; in response to the determination, automatically defining a new mapping to a work area such that the particular column maps to a corresponding component having a component type other than the default component type, wherein, as a result of said new mapping, the programming language accesses a sub-portion of the large object data content by changing the content of the large object data content via a locator and the programming language writes a sub-portion of the large object data content via the work area with at least one of an INSERT statement, an UPDATE statement, or a MODIFY statement associated with at least one of: (i) CL_ABAP_DB_C_LOCATOR and CL_ABAP_DB_X_LOCATOR for a locator, or (ii) CL_ABAP_DB_C_WRITER, CL_ABAP_DB_X_WRITER for a stream writer; determining a change to a structure of the database table; and responsive to the change to the structure of the database table, automatically adjusting the mapping of the database table to the work area such that the column to store large object data content is still mapped to a component having a component type other than the default component type. 2. The method of claim 1 , wherein the application server is associated with the programming language ABAP. | 0.582031 |
5,493,502 | 3 | 13 | 3. A method of operating a numerical control unit that is responsive to an instructed feedrate for controlling a machine tool to move along linear axes in a spatial coordinate system and rotate about one or more of said linear axes, said numerical control unit being operative to automatically control machining of a workpiece, said method comprising the steps of: determining whether a machining mode is a linear interpolation mode; determining whether a move command is for rotating said machine tool about a selected one of said linear axes if said machining mode is a linear interpolation model said selected one of said linear axes thereby becoming an axis of rotation; determining a radial distance between a tool starting position and the center of the axis of rotation if said move command is for rotating said machine tool about said axis of rotation; correcting said instructed feedrate according to said radial distance to provide a corrected feedrate equal to the relative speed of the tool and workpiece; and machining the workpiece by rotating said machine tool about said axis of rotation at said corrected feedrate. | 3. A method of operating a numerical control unit that is responsive to an instructed feedrate for controlling a machine tool to move along linear axes in a spatial coordinate system and rotate about one or more of said linear axes, said numerical control unit being operative to automatically control machining of a workpiece, said method comprising the steps of: determining whether a machining mode is a linear interpolation mode; determining whether a move command is for rotating said machine tool about a selected one of said linear axes if said machining mode is a linear interpolation model said selected one of said linear axes thereby becoming an axis of rotation; determining a radial distance between a tool starting position and the center of the axis of rotation if said move command is for rotating said machine tool about said axis of rotation; correcting said instructed feedrate according to said radial distance to provide a corrected feedrate equal to the relative speed of the tool and workpiece; and machining the workpiece by rotating said machine tool about said axis of rotation at said corrected feedrate. 13. A method as claimed in claim 3, wherein said corrected feedrate is represented by Fo and defined by the following equation: ##EQU17## wherein: F is the instructed feedrate; and r is the radial distance. | 0.52968 |
8,814,643 | 1 | 8 | 1. A challenge search query game system, comprising: a search server computing device configured to: receive a challenge query from a game program in response to an in-game action by a game player; retrieve a challenge in response to the challenge query, the challenge including one or more clues and a solution; send the challenge to the game program for display in the game, causing the game program to store the challenge and present a first clue from the one or more clues to the game player; receive a search query from the game program in response to providing the first clue to the game player, the search query based on one or more keywords input by the game player; provide search results based on the search query to the game program; determine if the one or more keywords match the solution to the challenge; and if the one or more keywords match the solution to the challenge: provide search results, sponsored links, and a solution notification embedded in the search results to the game program; send a message to the game program to perform a predefined action in response to the game player selecting the solution notification; and in response to the game player selecting a sponsored link, generate and share revenue with a game publisher of the game. | 1. A challenge search query game system, comprising: a search server computing device configured to: receive a challenge query from a game program in response to an in-game action by a game player; retrieve a challenge in response to the challenge query, the challenge including one or more clues and a solution; send the challenge to the game program for display in the game, causing the game program to store the challenge and present a first clue from the one or more clues to the game player; receive a search query from the game program in response to providing the first clue to the game player, the search query based on one or more keywords input by the game player; provide search results based on the search query to the game program; determine if the one or more keywords match the solution to the challenge; and if the one or more keywords match the solution to the challenge: provide search results, sponsored links, and a solution notification embedded in the search results to the game program; send a message to the game program to perform a predefined action in response to the game player selecting the solution notification; and in response to the game player selecting a sponsored link, generate and share revenue with a game publisher of the game. 8. The system of claim 1 , wherein the challenge is based on at least one database search on the search server computing device, the database including search trend data, wherein the search trend data is computed by the search server computing device substantially in real time. | 0.541254 |
7,756,935 | 2 | 3 | 2. The method of claim 1 , further comprising porting at least one of the attachments to a document management system. | 2. The method of claim 1 , further comprising porting at least one of the attachments to a document management system. 3. The method of claim 2 , wherein the porting comprises automatically porting. | 0.753125 |
8,209,268 | 9 | 10 | 9. The computer program product of claim 8 further comprising instructions for incrementing at least one of: a first pair counter configured to increment if the first unidentical substring pair is in the training data; a first substring counter configured to increment if the first unidentical substring is in the training data; a second substring counter configured to increment if the second unidentical substring is in the training data; a second pair counter configured to increment if the second unidentical substring pair is in the training data; a third substring counter configured to increment if the third unidentical substring is in the training data; and a fourth substring counter configured to increment if the fourth unidentical substring is in the training data. | 9. The computer program product of claim 8 further comprising instructions for incrementing at least one of: a first pair counter configured to increment if the first unidentical substring pair is in the training data; a first substring counter configured to increment if the first unidentical substring is in the training data; a second substring counter configured to increment if the second unidentical substring is in the training data; a second pair counter configured to increment if the second unidentical substring pair is in the training data; a third substring counter configured to increment if the third unidentical substring is in the training data; and a fourth substring counter configured to increment if the fourth unidentical substring is in the training data. 10. The computer program product of claim 9 further comprising instructions for: generating a matching score for each variant string pair in the training data, based upon, at least in part, at least one of the first pair counter, the first substring counter, the second substring counter, the second pair counter, the third substring counter, and the fourth substring counter. | 0.5 |
9,444,793 | 34 | 35 | 34. The system of claim 32 , wherein said controller is further configured to: receive processed text from the server; and apply a reverse processing on said processed text to obtain original input text. | 34. The system of claim 32 , wherein said controller is further configured to: receive processed text from the server; and apply a reverse processing on said processed text to obtain original input text. 35. The system of claim 34 , wherein said controller is further configured to send said original input text to said client device. | 0.5 |
8,272,009 | 30 | 32 | 30. A system that delivers content to users of a broadcast network, said broadcast network primarily involving synchronized distribution of content to multiple users, said system comprising: a first platform for providing an interface for receiving textual constraints from asset providers, such that each asset is associated with at least one textual constraint received via the interface and is further associated with at least one targeting constraint selected from the group consisting of temporal constraints, demographic constraints, or network constraints; and a processor operative to: compare said textual constraints of said assets with textual information associated with the programming to determine a goodness of fit value for each of the subset of assets; and identify a subset of the assets for presentation in conjunction with the programming according to the respective goodness of fit values; and deliver said subset of assets along with their respective textual constraints to a downstream second platform in association with an asset delivery spot in such a way that one of the subset of assets is selected by the second platform according to the respective textual constraints for presentation to at least one user of the broadcast network during the asset delivery spot. | 30. A system that delivers content to users of a broadcast network, said broadcast network primarily involving synchronized distribution of content to multiple users, said system comprising: a first platform for providing an interface for receiving textual constraints from asset providers, such that each asset is associated with at least one textual constraint received via the interface and is further associated with at least one targeting constraint selected from the group consisting of temporal constraints, demographic constraints, or network constraints; and a processor operative to: compare said textual constraints of said assets with textual information associated with the programming to determine a goodness of fit value for each of the subset of assets; and identify a subset of the assets for presentation in conjunction with the programming according to the respective goodness of fit values; and deliver said subset of assets along with their respective textual constraints to a downstream second platform in association with an asset delivery spot in such a way that one of the subset of assets is selected by the second platform according to the respective textual constraints for presentation to at least one user of the broadcast network during the asset delivery spot. 32. The system of claim 30 , wherein said interface is a graphical user interface. | 0.831276 |
9,460,414 | 14 | 15 | 14. A computer-implemented system for providing annotated electronic documents, the annotations which are to be applied to the documents being stored in a first data storage, the documents being stored in a second data storage, the first data storage and the second data storage being at least one of physically separate and logically separate, said system comprising: (A) at least one merge component, configured, to, responsive to a request from the user to retrieve the at least one document: retrieve the at least one document from a second data storage as document data, retrieve at least one annotation to be applied to said at least one document from a first data storage as annotation data, said document data including at least one element corresponding to a location of the at least one annotation within said document, wherein the annotation data is image data or text, wherein each annotation can be different from every other annotation; and combine the document data and the annotation data to form a unitary single logical document displaying the annotation embedded seamlessly in the document data at the location; (B) at least one split component complementary to the merge component, the split component is configured to, responsive to a request from the user to store the document: extract the annotation data and the document data from the single logical document, update the at least one annotation in the first data storage from the extracted annotation data, and to update the at least one document in the second data storage from the extracted document data; and (C) at least one version component, configured to at least one of manage a history of changes and to maintain a separate version for the document data and the annotation data to be applied thereto, wherein the annotation data indicates a predetermined section within the document as stored in the second data storage into which the annotation is to be embedded as indicated by an XML data schema. | 14. A computer-implemented system for providing annotated electronic documents, the annotations which are to be applied to the documents being stored in a first data storage, the documents being stored in a second data storage, the first data storage and the second data storage being at least one of physically separate and logically separate, said system comprising: (A) at least one merge component, configured, to, responsive to a request from the user to retrieve the at least one document: retrieve the at least one document from a second data storage as document data, retrieve at least one annotation to be applied to said at least one document from a first data storage as annotation data, said document data including at least one element corresponding to a location of the at least one annotation within said document, wherein the annotation data is image data or text, wherein each annotation can be different from every other annotation; and combine the document data and the annotation data to form a unitary single logical document displaying the annotation embedded seamlessly in the document data at the location; (B) at least one split component complementary to the merge component, the split component is configured to, responsive to a request from the user to store the document: extract the annotation data and the document data from the single logical document, update the at least one annotation in the first data storage from the extracted annotation data, and to update the at least one document in the second data storage from the extracted document data; and (C) at least one version component, configured to at least one of manage a history of changes and to maintain a separate version for the document data and the annotation data to be applied thereto, wherein the annotation data indicates a predetermined section within the document as stored in the second data storage into which the annotation is to be embedded as indicated by an XML data schema. 15. The system of claim 14 , wherein at least one of the logical single document, and the document data is at least one of: XML format, binary format, image data, video data, and audio data. | 0.887707 |
8,201,096 | 11 | 12 | 11. The system of claim 7 , wherein the list view area and preview area are separate and distinct areas, and wherein when a preview view entry is interactive, the preview view entry includes one or more interactive controls. | 11. The system of claim 7 , wherein the list view area and preview area are separate and distinct areas, and wherein when a preview view entry is interactive, the preview view entry includes one or more interactive controls. 12. The system of claim 11 , wherein file types include text files, PDF files, picture files, web page files, document files, spreadsheet files, sound files, music files, and movie files. | 0.5 |
8,250,145 | 1 | 5 | 1. A method for obtaining social information, the method comprising: requesting a web page from a web server, wherein the web page is within a domain of a third-party website that is different from a domain of a social networking system; receiving at a user device a markup language document for the requested web page, the markup language document including an instruction to create a frame within the web page that includes information obtained from the social networking system, wherein the frame comprises an iframe that contains a web page in the domain of the social networking system; requesting information from the social networking system based on an instruction in the markup language document, wherein requesting information from the social networking system comprises providing to the social networking system one or more parameters for selecting the requested information, wherein the requested information received from the social networking system is selected based on the parameters; providing to the social networking system an identification of a user associated with the user device; receiving the requested information from the social networking system, wherein the information received was determined by the social networking system based on social information associated with the user; rendering the web page including the information contained within the frame; and displaying the rendered web page. | 1. A method for obtaining social information, the method comprising: requesting a web page from a web server, wherein the web page is within a domain of a third-party website that is different from a domain of a social networking system; receiving at a user device a markup language document for the requested web page, the markup language document including an instruction to create a frame within the web page that includes information obtained from the social networking system, wherein the frame comprises an iframe that contains a web page in the domain of the social networking system; requesting information from the social networking system based on an instruction in the markup language document, wherein requesting information from the social networking system comprises providing to the social networking system one or more parameters for selecting the requested information, wherein the requested information received from the social networking system is selected based on the parameters; providing to the social networking system an identification of a user associated with the user device; receiving the requested information from the social networking system, wherein the information received was determined by the social networking system based on social information associated with the user; rendering the web page including the information contained within the frame; and displaying the rendered web page. 5. The method of claim 1 , wherein providing the identification of the user to the social networking system comprises allowing the social networking system to access a cookie stored on the user device. | 0.70354 |
8,166,465 | 1 | 15 | 1. A method for assembling a stream processing application, comprising: inputting a plurality of data source descriptions, wherein each of the data source descriptions includes a graph pattern that semantically describes an output of a data source; inputting a plurality of component descriptions, wherein each of the component descriptions includes a graph pattern that semantically describes an input of a component and a graph pattern that semantically describes an output of the component; inputting a stream processing request, wherein the stream processing request includes a goal that is represented by a graph pattern that semantically describes a desired stream processing outcome; assembling, using a processor of a computer, a stream processing graph in response to the stream processing request, wherein the stream processing graph is assembled by using machine code executable by the computer to process the plurality of data source descriptions and the plurality of component descriptions to obtain at least one of the data sources or at least one of the components that satisfies the desired processing outcome; and outputting the stream processing graph. | 1. A method for assembling a stream processing application, comprising: inputting a plurality of data source descriptions, wherein each of the data source descriptions includes a graph pattern that semantically describes an output of a data source; inputting a plurality of component descriptions, wherein each of the component descriptions includes a graph pattern that semantically describes an input of a component and a graph pattern that semantically describes an output of the component; inputting a stream processing request, wherein the stream processing request includes a goal that is represented by a graph pattern that semantically describes a desired stream processing outcome; assembling, using a processor of a computer, a stream processing graph in response to the stream processing request, wherein the stream processing graph is assembled by using machine code executable by the computer to process the plurality of data source descriptions and the plurality of component descriptions to obtain at least one of the data sources or at least one of the components that satisfies the desired processing outcome; and outputting the stream processing graph. 15. The method of claim 1 , wherein assembling the stream processing graph comprises: determining if an output of a first component matches an input of a second component; connecting the first component to the second component if the output of the first component matches the input of the second component; and determining a new output of the second component when the first and second components are connected to each other. | 0.5 |
8,874,427 | 23 | 33 | 23. A program product stored on a non-transitory computer readable medium for determining an in context exact (ICE) match from context matching levels of a plurality of translation memory source texts stored in a translation memory to a lookup segment to be translated, the computer readable medium comprising program code for performing the following steps: assigning a usage context hash code to the lookup segment and an asset hash code to the lookup segment; determining any exact matches for the lookup segment and the plurality of translation memory source texts; calculating for each exact match a context matching level based on: a match between the usage context hash code for the lookup segment and a usage context hash code assigned to a segment of a translation memory source text, and a match between the asset hash code for the lookup segment and an asset context hash code assigned to the segment of the translation memory source text; and determining, for each exact match if the segment of the translation memory source text providing the exact match is an ICE match for the lookup segment based on the calculated context matching level. | 23. A program product stored on a non-transitory computer readable medium for determining an in context exact (ICE) match from context matching levels of a plurality of translation memory source texts stored in a translation memory to a lookup segment to be translated, the computer readable medium comprising program code for performing the following steps: assigning a usage context hash code to the lookup segment and an asset hash code to the lookup segment; determining any exact matches for the lookup segment and the plurality of translation memory source texts; calculating for each exact match a context matching level based on: a match between the usage context hash code for the lookup segment and a usage context hash code assigned to a segment of a translation memory source text, and a match between the asset hash code for the lookup segment and an asset context hash code assigned to the segment of the translation memory source text; and determining, for each exact match if the segment of the translation memory source text providing the exact match is an ICE match for the lookup segment based on the calculated context matching level. 33. The program product of claim 23 , further comprising the step of allowing retrieval of at least one translation memory source text based on the matching of an assigned context hash code. | 0.634615 |
8,244,719 | 13 | 14 | 13. A computer apparatus as claimed in claim 9 wherein the tag previewer retrieves from the data store social tagging information about one or more variants of the candidate tag, the social tagging data in the data store being normalized and indexed by respective stem of tags. | 13. A computer apparatus as claimed in claim 9 wherein the tag previewer retrieves from the data store social tagging information about one or more variants of the candidate tag, the social tagging data in the data store being normalized and indexed by respective stem of tags. 14. A computer apparatus as claimed in claim 13 wherein the variants effectively consider any combination of: plural forms and singular forms of the candidate tag, alternative spellings of the candidate tag, and different grammatical variations of the candidate tag. | 0.5 |
8,670,968 | 13 | 14 | 13. The system of claim 8 , wherein the ranking the plurality of help postings and determining the probability uses the same ranking algorithm, wherein the ranking algorithm assigns a score to each of the plurality of help postings and test posting, and wherein the score is based on a popularity value and a seed value. | 13. The system of claim 8 , wherein the ranking the plurality of help postings and determining the probability uses the same ranking algorithm, wherein the ranking algorithm assigns a score to each of the plurality of help postings and test posting, and wherein the score is based on a popularity value and a seed value. 14. The system of claim 13 , wherein the popularity value is reduced over time using a deflation parameter value specifying a rate of reduction over time, and wherein the revised parameter values comprise the deflation parameter value. | 0.5 |
7,869,981 | 1 | 4 | 1. A configuration method for a room, the method comprising: selecting from a client device a pre-configured consumer application from a plurality of pre-configured consumer applications accessible from the client device, the consumer applications respectively reflecting different decorating styles that may be selected for the room, with each pre-configured consumer application having an associated plurality of room components; storing in a memory module data defining a plurality of attributes for each of the plurality of components associated with the room for the selected pre-configured consumer application, wherein the data are organized in a frame/slot hierarchy, wherein the plurality of components are each represented as a first and second set of frames and the plurality of attributes are each represented as slots of the first and second set of frames, respectively; selecting a user-specified attribute for at least one of the plurality of the room components, wherein selection of invalid attributes is prevented, comprising: performing in a processor-based system an attribute-based inference operation that identifies within the frame/slot hierarchy available attributes and invalid attributes for the at least one of the plurality of room components, wherein the available attributes are identified based on the selected pre-configured consumer application and the at least one of the plurality of room components; providing the available attributes for selection; and selecting the user-specified attribute from the available attributes provided; and generating an image comprising the at least one of the plurality of room components with the user-specified attribute within the room. | 1. A configuration method for a room, the method comprising: selecting from a client device a pre-configured consumer application from a plurality of pre-configured consumer applications accessible from the client device, the consumer applications respectively reflecting different decorating styles that may be selected for the room, with each pre-configured consumer application having an associated plurality of room components; storing in a memory module data defining a plurality of attributes for each of the plurality of components associated with the room for the selected pre-configured consumer application, wherein the data are organized in a frame/slot hierarchy, wherein the plurality of components are each represented as a first and second set of frames and the plurality of attributes are each represented as slots of the first and second set of frames, respectively; selecting a user-specified attribute for at least one of the plurality of the room components, wherein selection of invalid attributes is prevented, comprising: performing in a processor-based system an attribute-based inference operation that identifies within the frame/slot hierarchy available attributes and invalid attributes for the at least one of the plurality of room components, wherein the available attributes are identified based on the selected pre-configured consumer application and the at least one of the plurality of room components; providing the available attributes for selection; and selecting the user-specified attribute from the available attributes provided; and generating an image comprising the at least one of the plurality of room components with the user-specified attribute within the room. 4. The method of claim 1 further comprising: selecting a second user-specified attribute for the at least one of the plurality of the room components, wherein selection of invalid attributes is prevented, comprising: performing in a processor-based system an inference operation that identifies a second set of available attributes within the frame/slot hierarchy for the at least one of the plurality of the room components, wherein the second set of available attributes are identified based on at least the user-specified attribute; providing the second set of available attributes for selection; and selecting the second user-specified attribute from the second set of available attributes provided; and generating an image comprising the at least one of the plurality of room components with the user-specified attribute and the second user-specified attribute. | 0.5 |
7,809,704 | 1 | 6 | 1. A method of generating a model having a plurality of clusters for describing data each of which describes a plurality of data points of observed data in a data corpus, comprising: performing a probabilistic analysis on a portion of the observed data to obtain probabilistically analyzed data including using the probabilistically analyzed data to identify a search space as a subset of the observed data by identifying observed data not sufficiently well described by previously generated clusters; within the step of performing the probabilistic analysis, performing a spectral analysis on data in the search space to obtain spectrally analyzed data; and generating a new cluster that includes a subset of the data in the search space based on the probabilistically analyzed data and the spectrally analyzed data and adding the cluster to the model. | 1. A method of generating a model having a plurality of clusters for describing data each of which describes a plurality of data points of observed data in a data corpus, comprising: performing a probabilistic analysis on a portion of the observed data to obtain probabilistically analyzed data including using the probabilistically analyzed data to identify a search space as a subset of the observed data by identifying observed data not sufficiently well described by previously generated clusters; within the step of performing the probabilistic analysis, performing a spectral analysis on data in the search space to obtain spectrally analyzed data; and generating a new cluster that includes a subset of the data in the search space based on the probabilistically analyzed data and the spectrally analyzed data and adding the cluster to the model. 6. The method of claim 1 wherein performing a probabilistic analysis comprises: performing an estimation maximization (EM) algorithm having an E-step and an M-step and wherein performing a spectral analysis is performed in the M-step of the EM algorithm. | 0.505837 |
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