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9,706,256 | 1 | 4 | 1. A video augmented object creating system, comprising: an augmented object creating unit adapted to; track a path of movement of an object displayed in a video across a first frame and a second frame of the video, wherein the path of movement of the object is tracked from a first position in the first frame to a second position in the second frame, and wherein the second position is distinct from the first position; receive an interaction of a user with the object displayed in the video, the interaction comprising the user selecting the object in the video, and the interaction generating an augmented object instruction from the user, the augmented object instruction comprising a designation of the object displayed in the video by the user and a request for an augmented object associated with the object; identify the selected object by machine object recognition and, in response to the selection of the object in the video, dynamically retrieve information about the object from a semantic web; create augmented object information for the selected object based on the augmented object instruction and the retrieved information from the semantic web; generate the augmented object from the augmented object information and display the retrieved information from the semantic web with the generated augmented object; and associate the generated augmented object with the tracked path of movement of the object, wherein the augmented object tracks with the object displayed in the video; and an augmented object replaying unit adapted to: execute a preview of the augmented object information for the video by relocating the augmented object information for the object along the path of movement of the object from the first position in the first frame to the second position in the second frame; and receive an editing instruction from the user in response to the executed preview, the editing instruction comprising a change in the augmented object information for the video, wherein the video and the augmented object information are registered in a platform for sharing the video, wherein the user shares the video through the platform, and wherein the augmented object information for the video is adapted to permit user interaction with the augmented object in an environment of the video, the interaction with the augmented object triggering further interaction with the augmented object in the environment of the video. | 1. A video augmented object creating system, comprising: an augmented object creating unit adapted to; track a path of movement of an object displayed in a video across a first frame and a second frame of the video, wherein the path of movement of the object is tracked from a first position in the first frame to a second position in the second frame, and wherein the second position is distinct from the first position; receive an interaction of a user with the object displayed in the video, the interaction comprising the user selecting the object in the video, and the interaction generating an augmented object instruction from the user, the augmented object instruction comprising a designation of the object displayed in the video by the user and a request for an augmented object associated with the object; identify the selected object by machine object recognition and, in response to the selection of the object in the video, dynamically retrieve information about the object from a semantic web; create augmented object information for the selected object based on the augmented object instruction and the retrieved information from the semantic web; generate the augmented object from the augmented object information and display the retrieved information from the semantic web with the generated augmented object; and associate the generated augmented object with the tracked path of movement of the object, wherein the augmented object tracks with the object displayed in the video; and an augmented object replaying unit adapted to: execute a preview of the augmented object information for the video by relocating the augmented object information for the object along the path of movement of the object from the first position in the first frame to the second position in the second frame; and receive an editing instruction from the user in response to the executed preview, the editing instruction comprising a change in the augmented object information for the video, wherein the video and the augmented object information are registered in a platform for sharing the video, wherein the user shares the video through the platform, and wherein the augmented object information for the video is adapted to permit user interaction with the augmented object in an environment of the video, the interaction with the augmented object triggering further interaction with the augmented object in the environment of the video. 4. The video augmented object creating system of claim 1 , further comprising a tool structured to create the augmented object information, and wherein the tool is adapted to include functions for selecting the video for augmented object, selecting the object in the video, inputting the augmented object information for the object including an image or text to be annotated to the object, aligning frames or shots of the video, reviewing or modifying the augmented object, and executing the preview of the augmented object. | 0.5 |
9,508,339 | 1 | 5 | 1. A server computer, comprising: a processing unit; and memory coupled to the processing unit; the server computer configured to perform operations for updating language understanding classifier models, the operations comprising: receiving from at least one computing device of a plurality of computing devices communicatively coupled to the server computer, a first user selection of at least one of the following: at least one intent of a plurality of available intents and/or at least one slot for the at least one intent, wherein: the at least one intent is associated with at least one action used to perform at least one function of a category of functions for a domain; the at least one slot indicating a value used for performing the at least one action; and the first user selection associated with a digital voice input received at the at least one computing device; and upon receiving from at least another computing device of the plurality of computing devices, a plurality of subsequent user selections that are identical to the first user selection and a plurality of subsequent digital voice inputs corresponding to the plurality of subsequent user selections, wherein the plurality of subsequent digital voice inputs are substantially similar to the digital voice input: generating a labeled data set by pairing the digital voice input with the first user selection; selecting a language understanding classifier from a plurality of available language understanding classifiers associated with one or more agent definitions, the selecting based at least on the at least one intent; and updating the selected language understanding classifier based on the generated labeled data set. | 1. A server computer, comprising: a processing unit; and memory coupled to the processing unit; the server computer configured to perform operations for updating language understanding classifier models, the operations comprising: receiving from at least one computing device of a plurality of computing devices communicatively coupled to the server computer, a first user selection of at least one of the following: at least one intent of a plurality of available intents and/or at least one slot for the at least one intent, wherein: the at least one intent is associated with at least one action used to perform at least one function of a category of functions for a domain; the at least one slot indicating a value used for performing the at least one action; and the first user selection associated with a digital voice input received at the at least one computing device; and upon receiving from at least another computing device of the plurality of computing devices, a plurality of subsequent user selections that are identical to the first user selection and a plurality of subsequent digital voice inputs corresponding to the plurality of subsequent user selections, wherein the plurality of subsequent digital voice inputs are substantially similar to the digital voice input: generating a labeled data set by pairing the digital voice input with the first user selection; selecting a language understanding classifier from a plurality of available language understanding classifiers associated with one or more agent definitions, the selecting based at least on the at least one intent; and updating the selected language understanding classifier based on the generated labeled data set. 5. The server computer according to claim 1 , the operations further comprising: determining a number of the plurality of subsequent user selections which comprise at least one intent and at least one slot that are different from the at least one intent and the at least one slot of the first user selection. | 0.575758 |
9,384,264 | 1 | 17 | 1. A computer system to extract contender values as positively associated with a pre-defined value from a compilation of one or more electronically stored documents, the system comprising: one or more computer readable storage devices configured to store one or more software modules including computer executable instructions, and the compilation, wherein the electronically stored documents comprise one or more semi-structured document(s), one or more unstructured document(s), or a combination thereof, and each of the one or more electronically stored documents comprises one or more pages; a network configured to distribute information to a user workstation; one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the one or more software modules in order to cause the computer system to access, from the one or more computer readable storage devices, the compilation; receive information regarding the pre-defined value, wherein the pre-defined value has a certain format, has a certain two-dimensional spatial relationship to words in a pre-selected page, and is associated with one or more keywords; for each page of the compilation, identify words and contender values on the page using optical character recognition (OCR) and post-OCR processing, and group the identified words and the identified contender values into anchor blocks based on their spatial positioning on the page, such that the page comprises a plurality of anchor blocks and each anchor block comprises one or more words, one contender value, or a combination thereof; on the page, for each of the contender values, numerically determine a first confidence that the contender value is associated with the pre-defined value based at least in part on a comparison of a calculated two-dimensional spatial relationship between the contender value and the anchor blocks on the page with the pre-defined two-dimensional spatial relationship between the pre-defined value and the words in the pre-selected page, numerically determine a second confidence that the contender value is associated with the pre-defined value based at least in part on a comparison of words in the anchor blocks on the page with the one or more keywords associated with the pre-defined value, and numerically determine a third confidence that the contender value is associated with the pre-defined value based at least in part on a comparison of a format of the contender value with the certain format of the pre-defined value; over all the pages of the compilation, extract positive contender values as positively associated with the pre-defined value based at least in part on the first confidence, the second confidence, and the third confidence; store the positive contender values in the one or more computer readable storage devices; and transmit the positive contender values over the network to the user workstation in response to a search for values associated with the pre-defined value at the user workstation. | 1. A computer system to extract contender values as positively associated with a pre-defined value from a compilation of one or more electronically stored documents, the system comprising: one or more computer readable storage devices configured to store one or more software modules including computer executable instructions, and the compilation, wherein the electronically stored documents comprise one or more semi-structured document(s), one or more unstructured document(s), or a combination thereof, and each of the one or more electronically stored documents comprises one or more pages; a network configured to distribute information to a user workstation; one or more hardware computer processors in communication with the one or more computer readable storage devices and configured to execute the one or more software modules in order to cause the computer system to access, from the one or more computer readable storage devices, the compilation; receive information regarding the pre-defined value, wherein the pre-defined value has a certain format, has a certain two-dimensional spatial relationship to words in a pre-selected page, and is associated with one or more keywords; for each page of the compilation, identify words and contender values on the page using optical character recognition (OCR) and post-OCR processing, and group the identified words and the identified contender values into anchor blocks based on their spatial positioning on the page, such that the page comprises a plurality of anchor blocks and each anchor block comprises one or more words, one contender value, or a combination thereof; on the page, for each of the contender values, numerically determine a first confidence that the contender value is associated with the pre-defined value based at least in part on a comparison of a calculated two-dimensional spatial relationship between the contender value and the anchor blocks on the page with the pre-defined two-dimensional spatial relationship between the pre-defined value and the words in the pre-selected page, numerically determine a second confidence that the contender value is associated with the pre-defined value based at least in part on a comparison of words in the anchor blocks on the page with the one or more keywords associated with the pre-defined value, and numerically determine a third confidence that the contender value is associated with the pre-defined value based at least in part on a comparison of a format of the contender value with the certain format of the pre-defined value; over all the pages of the compilation, extract positive contender values as positively associated with the pre-defined value based at least in part on the first confidence, the second confidence, and the third confidence; store the positive contender values in the one or more computer readable storage devices; and transmit the positive contender values over the network to the user workstation in response to a search for values associated with the pre-defined value at the user workstation. 17. The system of claim 1 , wherein, when the pre-defined value is a ZIP code, the one or more computer readable storage devices are configured to store valid ZIP codes and wherein numerically determining the third confidence that the contender value is associated with the pre-defined value is based at least in part on a comparison of the contender value to the valid ZIP codes. | 0.818356 |
9,588,741 | 9 | 10 | 9. An apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least: generate a build of an application in a C Object-Oriented Programming Language; generate a unity file including a plurality of source files comprising references to a plurality of header files, at least two of the source files comprise references to a same header file, wherein generate the unity file further comprises excluding the source files from being separately compiled one at a time; compile the unity file comprising the plurality of source files to obtain a single object file; link the single object file to generate an executable of the application; and generate another build of the application based in part on determining that one or more new source files are added to the unity file in response to receipt of an indication of a selection to generate a full unity build. | 9. An apparatus comprising at least one processor and at least one memory including computer program code, the at least one memory and the computer program code configured to, with the processor, cause the apparatus to at least: generate a build of an application in a C Object-Oriented Programming Language; generate a unity file including a plurality of source files comprising references to a plurality of header files, at least two of the source files comprise references to a same header file, wherein generate the unity file further comprises excluding the source files from being separately compiled one at a time; compile the unity file comprising the plurality of source files to obtain a single object file; link the single object file to generate an executable of the application; and generate another build of the application based in part on determining that one or more new source files are added to the unity file in response to receipt of an indication of a selection to generate a full unity build. 10. The apparatus of claim 9 , wherein the memory and computer program code are further configured to, with the processor, cause the apparatus to: compile the unity file based in part on reading and parsing the header files referenced by respective source files once, even though the at least two source files comprise references to the same header file. | 0.648111 |
8,767,825 | 19 | 20 | 19. The method of claim 16 , wherein training the rate-distortion model and the scaling model comprises: selecting a set of videos from among the plurality of different videos of the video corpus; encoding the selected set of videos in multiple video formats; obtaining a plurality of rate-distortion data from the encoded videos; and estimating the rate-distortion model based on the obtained plurality of rate-distortion data; and estimating the scaling model based on the obtained plurality of rate-distortion data. | 19. The method of claim 16 , wherein training the rate-distortion model and the scaling model comprises: selecting a set of videos from among the plurality of different videos of the video corpus; encoding the selected set of videos in multiple video formats; obtaining a plurality of rate-distortion data from the encoded videos; and estimating the rate-distortion model based on the obtained plurality of rate-distortion data; and estimating the scaling model based on the obtained plurality of rate-distortion data. 20. The method of claim 19 , wherein estimating the rate-distortion model comprises deriving a rate-distortion measurement based on the video coding complexity scores of the selected videos. | 0.5 |
8,700,385 | 1 | 3 | 1. A system that provides a task oriented data structure to correlate natural language task descriptions to at least one of a plurality of application level commands available for inclusion in the task oriented data structure, comprising: an activity tracking component that monitors performance of a first application level task and registers at least one first application level command utilized in accomplishing the first application level task, the at least one first application level command utilized in accomplishing the first application level task being one of the plurality of application level commands; an activity translation component that obtains a first natural language task description for the first application level task; a language modeling component that generates a first task oriented data structure based on the first natural language task description and the at least one first application level command utilized in accomplishing the first application level task, the first task oriented data structure facilitates execution of the at least one first application level command such that the first task oriented data structure specifies the at least one first application level command to be executed and causes the execution, at least in part, of the at least one first application level command; and a namespace execution component that receives a second natural language task description for a second application level task and causes the execution of the second application level task based at least in part on the second natural language task description and the first task oriented data structure, the first natural language task description and the second natural language task description differing at least in part such that the at least one first application level command utilized in accomplishing the first application level task differs at least in part from at least one second application level command utilized in accomplishing the second application level task. | 1. A system that provides a task oriented data structure to correlate natural language task descriptions to at least one of a plurality of application level commands available for inclusion in the task oriented data structure, comprising: an activity tracking component that monitors performance of a first application level task and registers at least one first application level command utilized in accomplishing the first application level task, the at least one first application level command utilized in accomplishing the first application level task being one of the plurality of application level commands; an activity translation component that obtains a first natural language task description for the first application level task; a language modeling component that generates a first task oriented data structure based on the first natural language task description and the at least one first application level command utilized in accomplishing the first application level task, the first task oriented data structure facilitates execution of the at least one first application level command such that the first task oriented data structure specifies the at least one first application level command to be executed and causes the execution, at least in part, of the at least one first application level command; and a namespace execution component that receives a second natural language task description for a second application level task and causes the execution of the second application level task based at least in part on the second natural language task description and the first task oriented data structure, the first natural language task description and the second natural language task description differing at least in part such that the at least one first application level command utilized in accomplishing the first application level task differs at least in part from at least one second application level command utilized in accomplishing the second application level task. 3. The system of claim 1 , comprising a template compilation component that generates a namespace template for the first application level task, the template incorporates a plurality of natural language descriptions of the first application level task, and associates the descriptions with a plurality of application level commands utilized to accomplish the first application level task. | 0.779545 |
9,749,762 | 14 | 15 | 14. The system of claim 13 , wherein the finite-state automaton is a non-deterministic finite-state automaton that can exist in multiple states at the same time; and wherein the non-deterministic finite-state automaton maintains a probability value for each of the multiple states that the finite-state automaton can exist in. | 14. The system of claim 13 , wherein the finite-state automaton is a non-deterministic finite-state automaton that can exist in multiple states at the same time; and wherein the non-deterministic finite-state automaton maintains a probability value for each of the multiple states that the finite-state automaton can exist in. 15. The system of claim 14 , wherein if a probability value for a state in the non-deterministic finite-state automaton does not meet an activation-potential-related threshold value after a state-transition operation, the probability value for the state is set to zero. | 0.5 |
8,938,408 | 12 | 13 | 12. The system of claim 11 , wherein the pairwise classification comprises: generating a learning set of classifiers based on the pairs of Web address features. | 12. The system of claim 11 , wherein the pairwise classification comprises: generating a learning set of classifiers based on the pairs of Web address features. 13. The system of claim 12 , wherein generating a learning set of classifiers comprises: assigning a label to at least each of the extracted Web address features; assigning a value of 1 to the pairs of Web address features relating to a similar or same search goal and assigning a value of 0 to all other pairs of the Web address features; and training the learning set of classifiers using at least the extracted Web address features. | 0.5 |
8,352,248 | 19 | 24 | 19. An apparatus comprising: a speech encoder, which processes an input speech signal, resulting in a compressed encoder representation of the input speech signal; a speech recognizer, which processes the input speech signal; and a difference encoder, which determines a compressed recognizer representation of a corresponding dictionary speech element that approximates the input speech signal when the speech recognizer identifies the corresponding dictionary speech element, calculates one or more differences between the compressed encoder representation and the compressed recognizer representation, and compiles compressed speech information that includes representations of the one or more differences; and a transmitter, which transmits the compressed speech information that includes representations of the one or more differences when the speech recognizer identifies the corresponding dictionary speech element and transmits the compressed encoder representation of the input speech signal when the speech recognizer does not identify a dictionary speech element that approximates the input speech signal. | 19. An apparatus comprising: a speech encoder, which processes an input speech signal, resulting in a compressed encoder representation of the input speech signal; a speech recognizer, which processes the input speech signal; and a difference encoder, which determines a compressed recognizer representation of a corresponding dictionary speech element that approximates the input speech signal when the speech recognizer identifies the corresponding dictionary speech element, calculates one or more differences between the compressed encoder representation and the compressed recognizer representation, and compiles compressed speech information that includes representations of the one or more differences; and a transmitter, which transmits the compressed speech information that includes representations of the one or more differences when the speech recognizer identifies the corresponding dictionary speech element and transmits the compressed encoder representation of the input speech signal when the speech recognizer does not identify a dictionary speech element that approximates the input speech signal. 24. The apparatus of claim 19 , further comprising an electronic information storage device for storing the compressed speech information. | 0.867816 |
8,977,645 | 12 | 18 | 12. A method, comprising: receiving a search query; providing a structured presentation for display on a display device responsive to the search query, the structured presentation visually presenting information in a systematic and structured arrangement that conforms with a structured design, the structured presentation denoting associations between an instance and values that characterize attributes an entity corresponding to of the instance using an arrangement of the values in respective cells of the structured presentation responsive to the search query; receiving a user interaction with a first cell of the structured presentation, the first cell having a first value for a particular attribute of an instance associated with the first cell; and in response to the received user interaction with the first cell: determining that the first value of the first cell provided in the structured presentations resulted from a prior search of the unstructured collection of electronic documents by a system comprising one or more computers that identified one or more particular electronic documents as including content characterizing the particular attribute of the instance, wherein the first value was determined from the content of the one or more particular electronic documents; and in response to determining that the prior search was conducted, providing information regarding the prior search including providing a search interface associated with the first value of the first cell for presentation on the display device, the search interface configured to present search result information characterizing the prior search including providing information identifying a first electronic document of the particular electronic documents from which the first value for the attribute of the instance was determined including providing for display a link to the first electronic document. | 12. A method, comprising: receiving a search query; providing a structured presentation for display on a display device responsive to the search query, the structured presentation visually presenting information in a systematic and structured arrangement that conforms with a structured design, the structured presentation denoting associations between an instance and values that characterize attributes an entity corresponding to of the instance using an arrangement of the values in respective cells of the structured presentation responsive to the search query; receiving a user interaction with a first cell of the structured presentation, the first cell having a first value for a particular attribute of an instance associated with the first cell; and in response to the received user interaction with the first cell: determining that the first value of the first cell provided in the structured presentations resulted from a prior search of the unstructured collection of electronic documents by a system comprising one or more computers that identified one or more particular electronic documents as including content characterizing the particular attribute of the instance, wherein the first value was determined from the content of the one or more particular electronic documents; and in response to determining that the prior search was conducted, providing information regarding the prior search including providing a search interface associated with the first value of the first cell for presentation on the display device, the search interface configured to present search result information characterizing the prior search including providing information identifying a first electronic document of the particular electronic documents from which the first value for the attribute of the instance was determined including providing for display a link to the first electronic document. 18. The method of claim 12 , further comprising displaying a snippet characterizing a context of the first value in a first document of the electronic document collection. | 0.788366 |
10,013,656 | 1 | 2 | 1. A method for generating one or more prediction models for a workflow composed of a plurality of activities, comprising: extracting one or more input features from input data from a plurality of previous executions of said plurality of activities and extracting one or more output features from output data from said plurality of previous executions of said plurality of activities, wherein said plurality of activities execute in one or more computing devices; automatically learning, using at least one processing device, a plurality of prediction functions from one or more input features and one or more output features of said workflow, wherein each of said prediction functions predicts at least one of said output features of at least one of said plurality of activities of said workflow based on one or more of said input features of said at least one activity of said workflow; selecting, using said at least one processing device, one of said plurality of prediction functions for each of said plurality of activities in said workflow based on a particular goal and a succession of said plurality of activities according to a definition of said workflow to generate a selected subset of prediction functions; combining, using said at least one processing device, said selected subset of said plurality of prediction functions to generate said one or more prediction models based on the succession of said plurality of activities according to the definition of said workflow, wherein each of said one or more prediction models predicts a final output feature of said workflow based on one or more of said input features extracted from one or more initial inputs of said workflow; and selecting an instantiation of said workflow for a given input and said particular goal by evaluating a plurality of said one or more prediction models. | 1. A method for generating one or more prediction models for a workflow composed of a plurality of activities, comprising: extracting one or more input features from input data from a plurality of previous executions of said plurality of activities and extracting one or more output features from output data from said plurality of previous executions of said plurality of activities, wherein said plurality of activities execute in one or more computing devices; automatically learning, using at least one processing device, a plurality of prediction functions from one or more input features and one or more output features of said workflow, wherein each of said prediction functions predicts at least one of said output features of at least one of said plurality of activities of said workflow based on one or more of said input features of said at least one activity of said workflow; selecting, using said at least one processing device, one of said plurality of prediction functions for each of said plurality of activities in said workflow based on a particular goal and a succession of said plurality of activities according to a definition of said workflow to generate a selected subset of prediction functions; combining, using said at least one processing device, said selected subset of said plurality of prediction functions to generate said one or more prediction models based on the succession of said plurality of activities according to the definition of said workflow, wherein each of said one or more prediction models predicts a final output feature of said workflow based on one or more of said input features extracted from one or more initial inputs of said workflow; and selecting an instantiation of said workflow for a given input and said particular goal by evaluating a plurality of said one or more prediction models. 2. The method of claim 1 , wherein said one or more input features and said one or more output features are extracted from one or more of input data, output data, execution data and provenance data of said workflow. | 0.693732 |
8,484,730 | 15 | 18 | 15. A non-transitory computer-readable-storage medium comprising one or more computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to: identify a user account subject to parental monitoring; identify a plurality of online resources accessed by the user account over a period of time; maintain a reputation database by collecting, aggregating, and analyzing information about each of the plurality of online resources from user devices within a community; determine a reputation for each of the plurality of online resources, wherein: the reputation indicates a level of security threat; the determination of the reputation comprises providing information identifying each online resource to an online resource reputation system that maintains reputation information for online resources and receiving, from the online resource reputation system, a reputation score for each online resource; generate an online behavior score for the user account based on the reputation score for each online resource in the plurality of online resources, the online behavior score indicating an overall level of security threat posed by online activity on the user account; report the online behavior score to a predetermined contact associated with the user account. | 15. A non-transitory computer-readable-storage medium comprising one or more computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to: identify a user account subject to parental monitoring; identify a plurality of online resources accessed by the user account over a period of time; maintain a reputation database by collecting, aggregating, and analyzing information about each of the plurality of online resources from user devices within a community; determine a reputation for each of the plurality of online resources, wherein: the reputation indicates a level of security threat; the determination of the reputation comprises providing information identifying each online resource to an online resource reputation system that maintains reputation information for online resources and receiving, from the online resource reputation system, a reputation score for each online resource; generate an online behavior score for the user account based on the reputation score for each online resource in the plurality of online resources, the online behavior score indicating an overall level of security threat posed by online activity on the user account; report the online behavior score to a predetermined contact associated with the user account. 18. The non-transitory computer-readable-storage medium according to claim 15 , further comprising computer-executable instructions that, when executed by at least one processor of a computing device, cause the computing device to automatically adjust the user account's level of online access in response to the generating of the online behavior score. | 0.685943 |
9,069,954 | 8 | 10 | 8. A threat detection system comprising: a non-transitory data storage that stores security events associated with network devices, and an actor category model including a plurality of levels arranged in a hierarchy and each level is associated with a subcategory for a category of the actor category model, wherein the actor category model comprises an attribute for users, and the actor category model comprises parent-child relationships between the plurality of levels, and child levels inherit rules from their parent levels; and at least one physical processor that correlates security events with the actor category model, wherein to correlate the security events the at least one processor: identifies a user for each security event; determines the actor category model is applicable to the user for each security event and any of the security events associated with the user by matching the attribute for users in the actor category model with a user attribute of the user in a user data model; identifies a level in the actor category model associated with the user for each security event; and determines whether a security threat exists based on the correlating, wherein to determine whether the security threat exists, the at least one processor: determines a security rule for the identified level; and applies the security rule to determine whether the security threat exists. | 8. A threat detection system comprising: a non-transitory data storage that stores security events associated with network devices, and an actor category model including a plurality of levels arranged in a hierarchy and each level is associated with a subcategory for a category of the actor category model, wherein the actor category model comprises an attribute for users, and the actor category model comprises parent-child relationships between the plurality of levels, and child levels inherit rules from their parent levels; and at least one physical processor that correlates security events with the actor category model, wherein to correlate the security events the at least one processor: identifies a user for each security event; determines the actor category model is applicable to the user for each security event and any of the security events associated with the user by matching the attribute for users in the actor category model with a user attribute of the user in a user data model; identifies a level in the actor category model associated with the user for each security event; and determines whether a security threat exists based on the correlating, wherein to determine whether the security threat exists, the at least one processor: determines a security rule for the identified level; and applies the security rule to determine whether the security threat exists. 10. The threat detection system of claim 8 , wherein to identify a user, for each security event, the physical processor determines an application associated with the security event, identifies an authenticator that provisions user accounts for the application, determines an account ID associated with the security event and determines the user based on the authenticator and the account ID. | 0.653097 |
4,171,816 | 1 | 7 | 1. A game apparatus, comprising: a plurality of strips having two faces, one of said faces being a front face having thereon a word or combination of words exemplifying a language category, the other face being a rear face having a word or words identifying the language category exemplified on said front face; a game board having a plurality of spaces oriented in a plurality of rows and a plurality of columns for receiving and accumulating said strips according to each of said language categories, certain preselected ones of said spaces on the game board having a designation therein for rewarding bonus points; an indicator means for random selection of any one of said language categories; and dice, each of which has words or syllables on its face for determining by change an amount of bonus points to be rewarded upon receiving and accumulating one of said strips upon one of said certain preselected spaces of said game board. | 1. A game apparatus, comprising: a plurality of strips having two faces, one of said faces being a front face having thereon a word or combination of words exemplifying a language category, the other face being a rear face having a word or words identifying the language category exemplified on said front face; a game board having a plurality of spaces oriented in a plurality of rows and a plurality of columns for receiving and accumulating said strips according to each of said language categories, certain preselected ones of said spaces on the game board having a designation therein for rewarding bonus points; an indicator means for random selection of any one of said language categories; and dice, each of which has words or syllables on its face for determining by change an amount of bonus points to be rewarded upon receiving and accumulating one of said strips upon one of said certain preselected spaces of said game board. 7. The apparatus of claim 1, wherein said language categories are the tenses of verbs. | 0.852234 |
8,990,126 | 8 | 13 | 8. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: collecting a plurality of task-oriented, human-human dialog interactions between users and human agents for a given domain; after collecting the plurality of task-oriented, human-human dialog interactions, extracting a respective dialog structure associated with each of the plurality of task-oriented, human-human dialog interactions, wherein extracting the respective dialog structure comprises: identifying a respective task in each of the plurality of task-oriented, human-human dialog interactions; identifying subtasks in the respective task and associating relations between the subtasks, wherein the identifying of the subtask is done using a chunk model equation PT*=argmax Σ ST P(ST|U)P(PT|ST), where PT* is the most likely plan tree, ST is each subtask in a sequence of utterances U, PT represents likelihood of each plan tree, and P represents the individual probabilities within the chunk model equation where the chunk model equation uses the respective dialog structures U and ST as a weighted lattice; and identifying a dialog act and a set of predicate-argument relations for the subtasks by annotating user utterances in the plurality of task-oriented, human-human dialog interactions with tags; generating a clause from the set of predicate-argument relations; removing speech repairs and dysfluencies from a respective user utterance in each of the plurality of task-oriented, human-human dialog interactions; storing the respective task, the subtasks, the dialog act, the set of predicate-argument relations, the clause, inter-clausal relations within the clause, and a set of dominance and precedence relations associated with the respective task as a dialog interaction set represented as a single tree. | 8. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: collecting a plurality of task-oriented, human-human dialog interactions between users and human agents for a given domain; after collecting the plurality of task-oriented, human-human dialog interactions, extracting a respective dialog structure associated with each of the plurality of task-oriented, human-human dialog interactions, wherein extracting the respective dialog structure comprises: identifying a respective task in each of the plurality of task-oriented, human-human dialog interactions; identifying subtasks in the respective task and associating relations between the subtasks, wherein the identifying of the subtask is done using a chunk model equation PT*=argmax Σ ST P(ST|U)P(PT|ST), where PT* is the most likely plan tree, ST is each subtask in a sequence of utterances U, PT represents likelihood of each plan tree, and P represents the individual probabilities within the chunk model equation where the chunk model equation uses the respective dialog structures U and ST as a weighted lattice; and identifying a dialog act and a set of predicate-argument relations for the subtasks by annotating user utterances in the plurality of task-oriented, human-human dialog interactions with tags; generating a clause from the set of predicate-argument relations; removing speech repairs and dysfluencies from a respective user utterance in each of the plurality of task-oriented, human-human dialog interactions; storing the respective task, the subtasks, the dialog act, the set of predicate-argument relations, the clause, inter-clausal relations within the clause, and a set of dominance and precedence relations associated with the respective task as a dialog interaction set represented as a single tree. 13. The computer-readable storage device of claim 8 , wherein the subtasks are segmented into beginning, middle and end utterances. | 0.794025 |
7,899,807 | 1 | 17 | 1. A computer system for fetching a web page, comprising: an index for use by a search engine, wherein the index indexes a set of previously crawled web pages; a web crawler for fetching a plurality of web pages to update said index; and a storage device that stores information about a set of queries that have been received by the search engine; wherein said storage device further stores data that indicates which queries in the set of queries are needy queries; wherein said needy queries are queries for which the index does not currently index adequate, relevant content; a crawling policy manager, operably coupled to the web crawler, for implementing a policy for estimating an impact, on said needy queries, of fetching a particular uncrawled web page by comparing terms of said needy queries with at least one of: (a) an anchortext of links, obtained from the previously crawled web pages, that point to the particular uncrawled web page, and (b) a Uniform Resource Locator (URL), obtained from the previously crawled web pages, that points to the particular uncrawled web page; a crawl ordering engine, operably coupled to the crawling policy manager, for ordering web pages to fetch by the web crawler based, at least in part, on the estimated impact, on said needy queries, of crawling the particular uncrawled page. | 1. A computer system for fetching a web page, comprising: an index for use by a search engine, wherein the index indexes a set of previously crawled web pages; a web crawler for fetching a plurality of web pages to update said index; and a storage device that stores information about a set of queries that have been received by the search engine; wherein said storage device further stores data that indicates which queries in the set of queries are needy queries; wherein said needy queries are queries for which the index does not currently index adequate, relevant content; a crawling policy manager, operably coupled to the web crawler, for implementing a policy for estimating an impact, on said needy queries, of fetching a particular uncrawled web page by comparing terms of said needy queries with at least one of: (a) an anchortext of links, obtained from the previously crawled web pages, that point to the particular uncrawled web page, and (b) a Uniform Resource Locator (URL), obtained from the previously crawled web pages, that points to the particular uncrawled web page; a crawl ordering engine, operably coupled to the crawling policy manager, for ordering web pages to fetch by the web crawler based, at least in part, on the estimated impact, on said needy queries, of crawling the particular uncrawled page. 17. The system of claim 1 , wherein the crawling policy manager compares the terms of said needy queries with at least one of: (a) the anchortext of links, obtained from the previously crawled web pages, that points to the particular uncrawled web page, and (b) the URL, obtained from the previously crawled web pages, that points to the particular uncrawled web page by comparing a word-level n-gram representing a query string in a particular needy query and a word-level n-gram representing an anchortext string. | 0.701622 |
9,852,211 | 13 | 15 | 13. A processing system comprising: at least one processor; and a machine-readable medium in communication with the at least one processor, the machine readable medium storing application logic including topic merge logic that is executable by the at least one processor, the application logic being executed by the at least one processor to cause operations to be performed, the operations comprising: receiving a request to merge a first topic with a second topic of a plurality of topics, the plurality of topics stored as separate records in a database table, each record having a first field to store a topic identifier that identifies its respective topic, a second field to store a topic identifier into which the respective topic has been merged, and a third field to store a topic name different than the topic identifier; responsive to reading the second field of the record for the second topic to determine that the second topic has been merged with a third topic of the plurality of topics, writing a topic identifier of the third topic into the second field of the record for the first topic to indicate that the first topic has been merged into the third topic; identify ones of the plurality of topics that have been merged into the third topic; for each of the third topic and the ones of the plurality of topics that have been merged into the third topic, identify at least one of a question and a user associated with the third topic and the ones of the plurality of topics; for each of the question and the user, merge the questions and the users on an associated question table and user table, respectively; and provide a list of questions and users associated with the first topic to an application logic component. | 13. A processing system comprising: at least one processor; and a machine-readable medium in communication with the at least one processor, the machine readable medium storing application logic including topic merge logic that is executable by the at least one processor, the application logic being executed by the at least one processor to cause operations to be performed, the operations comprising: receiving a request to merge a first topic with a second topic of a plurality of topics, the plurality of topics stored as separate records in a database table, each record having a first field to store a topic identifier that identifies its respective topic, a second field to store a topic identifier into which the respective topic has been merged, and a third field to store a topic name different than the topic identifier; responsive to reading the second field of the record for the second topic to determine that the second topic has been merged with a third topic of the plurality of topics, writing a topic identifier of the third topic into the second field of the record for the first topic to indicate that the first topic has been merged into the third topic; identify ones of the plurality of topics that have been merged into the third topic; for each of the third topic and the ones of the plurality of topics that have been merged into the third topic, identify at least one of a question and a user associated with the third topic and the ones of the plurality of topics; for each of the question and the user, merge the questions and the users on an associated question table and user table, respectively; and provide a list of questions and users associated with the first topic to an application logic component. 15. The processing system of claim 13 , wherein the topic merge logic is to prevent the first topic from being merged into the second topic when the second field of the record for the second topic contains a topic identifier of a third topic, indicating that the second topic has been merged into the third topic. | 0.577027 |
7,676,517 | 12 | 13 | 12. A computer-implemented method of processing a query, the method comprising: employing a processor to execute code instructions stored in a computer readable medium, the code instructions when executed by the processor implement the following acts: receiving a query character into a query input box of a client application; searching an Internet-based index service in realtime that returns search results based on the received query character; suggesting additional query characters in a realtime look-ahead manner, the additional query characters are presented to a user in association with the received query character in response to receiving the search results; facilitating the inclusion of one or more of the additional query characters and one or more of impacting, refining, and filtering additional query data resulting from the one or more additional query characters; automatically generating one or more rules to adjust the realtime look-ahead injection of the additional query characters into the query input box of the client application based on user interaction, wherein the realtime look-ahead injection of the additional query characters is more automated when the user interaction indicates the user is more skillful and less automated when the user is indicated to be more novice; and employing a probabilistic or statistical-based analysis, or a combination thereof, to prognose or infer an action that a user desires to be automatically performed. | 12. A computer-implemented method of processing a query, the method comprising: employing a processor to execute code instructions stored in a computer readable medium, the code instructions when executed by the processor implement the following acts: receiving a query character into a query input box of a client application; searching an Internet-based index service in realtime that returns search results based on the received query character; suggesting additional query characters in a realtime look-ahead manner, the additional query characters are presented to a user in association with the received query character in response to receiving the search results; facilitating the inclusion of one or more of the additional query characters and one or more of impacting, refining, and filtering additional query data resulting from the one or more additional query characters; automatically generating one or more rules to adjust the realtime look-ahead injection of the additional query characters into the query input box of the client application based on user interaction, wherein the realtime look-ahead injection of the additional query characters is more automated when the user interaction indicates the user is more skillful and less automated when the user is indicated to be more novice; and employing a probabilistic or statistical-based analysis, or a combination thereof, to prognose or infer an action that a user desires to be automatically performed. 13. The method of claim 12 , further comprising accessing a local cache of most popular queries at least one of in addition to and alternatively to the act of accessing the Internet-based search service. | 0.587398 |
7,668,887 | 14 | 17 | 14. A computer-implemented system for maintaining a list of documents of interest to a user within a corpus of documents, the system including one or more computers comprising: at least one processor; a database of the corpus of documents; and at least one storage medium operatively coupled to the processor, the storage medium containing program instructions for execution by the processor, said program instructions causing the processor to execute the steps of: associating an editable user document with said corpus of documents; generating an initial list of documents within the corpus based upon an initial content of the editable user document by cross-referencing said initial content with content of documents in the corpus, each entry in said initial list being assigned a corresponding initial ranking value based upon said cross-referencing; presenting the user with an initial list of one or more documents of interest from within the corpus on the basis of said initial ranking values; responsive to one or more updates of the editable document by the user, generating one or more further lists of documents within the corpus based upon updated content of the editable user document by cross-referencing said updated content with content of documents in the corpus, each entry in said further list being assigned a corresponding revised ranking value based upon said cross-referencing; and presenting the user with a revised list of one or more documents of interest from within the corpus on the basis of said revised ranking values. | 14. A computer-implemented system for maintaining a list of documents of interest to a user within a corpus of documents, the system including one or more computers comprising: at least one processor; a database of the corpus of documents; and at least one storage medium operatively coupled to the processor, the storage medium containing program instructions for execution by the processor, said program instructions causing the processor to execute the steps of: associating an editable user document with said corpus of documents; generating an initial list of documents within the corpus based upon an initial content of the editable user document by cross-referencing said initial content with content of documents in the corpus, each entry in said initial list being assigned a corresponding initial ranking value based upon said cross-referencing; presenting the user with an initial list of one or more documents of interest from within the corpus on the basis of said initial ranking values; responsive to one or more updates of the editable document by the user, generating one or more further lists of documents within the corpus based upon updated content of the editable user document by cross-referencing said updated content with content of documents in the corpus, each entry in said further list being assigned a corresponding revised ranking value based upon said cross-referencing; and presenting the user with a revised list of one or more documents of interest from within the corpus on the basis of said revised ranking values. 17. The system of claim 14 wherein said program instructions cause the processor, in the steps of generating an initial list of documents and generating one or more further lists of documents, to compute a ranking value for each listed document by accumulating co-occurrence values corresponding with common occurrences of stemmed words within the content of the user document and within each said document of the corpus. | 0.719707 |
8,359,309 | 1 | 6 | 1. A method implemented by data processing apparatus, the method comprising: determining, for a plurality of search results responsive to a query, a respective count of times search results in the plurality of search results that refer to documents in a base corpus have been presented, and a respective count of times search results in the plurality of search results that refer to documents in the base corpus have been selected, wherein the respective counts for presentations and selections of search results that refer to documents in the base corpus are for searches initiated by users in a plurality of different countries who employ a specific language; determining, for the plurality of search results responsive to the query, a respective count of times search results in the plurality of search results that refer to documents in a second corpus have been presented, and a respective count of times search results in the plurality of search results that refer to documents in the second corpus have been selected, wherein the respective counts for presentations and selections of search results that refer to documents in the second corpus are for searches initiated by users in the plurality of different countries who employ the specific language; calculating a click through rate of the base corpus for the query based at least in part on the respective counts for the base corpus; calculating a click through rate of the second corpus for the query based at least in part on the respective counts for the second corpus; calculating a measure of relative relevance based at least in part on a ratio of the second corpus click through rate to the base corpus click through rate; and providing the measure of relative relevance to a ranking engine for ranking of search results for a search corresponding to the query; and wherein fewer search results of the plurality refer to documents in the second corpus than to documents in the base corpus. | 1. A method implemented by data processing apparatus, the method comprising: determining, for a plurality of search results responsive to a query, a respective count of times search results in the plurality of search results that refer to documents in a base corpus have been presented, and a respective count of times search results in the plurality of search results that refer to documents in the base corpus have been selected, wherein the respective counts for presentations and selections of search results that refer to documents in the base corpus are for searches initiated by users in a plurality of different countries who employ a specific language; determining, for the plurality of search results responsive to the query, a respective count of times search results in the plurality of search results that refer to documents in a second corpus have been presented, and a respective count of times search results in the plurality of search results that refer to documents in the second corpus have been selected, wherein the respective counts for presentations and selections of search results that refer to documents in the second corpus are for searches initiated by users in the plurality of different countries who employ the specific language; calculating a click through rate of the base corpus for the query based at least in part on the respective counts for the base corpus; calculating a click through rate of the second corpus for the query based at least in part on the respective counts for the second corpus; calculating a measure of relative relevance based at least in part on a ratio of the second corpus click through rate to the base corpus click through rate; and providing the measure of relative relevance to a ranking engine for ranking of search results for a search corresponding to the query; and wherein fewer search results of the plurality refer to documents in the second corpus than to documents in the base corpus. 6. The method of claim 1 wherein the ranking engine is configured to increase a score of a search result for the query that refers to a document in the second corpus based at least in part on the measure of relative relevance. | 0.698667 |
8,943,417 | 1 | 6 | 1. A method for providing notifications to collaborators of a document, comprising: accessing a document editor program that includes collaborative authoring functionality for collaboration and communication on the document and an integrated collaborative user interface that is used to display information relating to the collaboration; displaying collaborative user interface elements within the integrated collaborative user interface, wherein displaying the collaborative user interface comprises displaying a ribbon menu pane, a document editing pane and a document assembly pane, wherein displaying the ribbon menu pane comprises displaying a document elements ribbon including a publish element, a view details element and section elements including an insert element, a delete element, and a view details element while in collaborative mode and hiding the collaborative user interface elements when not in collaborative mode; wherein displaying the document assembly pane further comprises displaying, within the document assembly pane, a document detail pane, a section detail pane, and an expanded section detail pane, wherein displaying the document detail pane comprises displaying document details metadata associated with collaboratively authoring the document, and wherein displaying the section details pane comprising displaying section details metadata associated with an author assigned to at least one section of the document; using the integrated collaborative user interface to associate collaborators with one or more sections of the document for at least one of: reviewing the one or more sections and updating the one or more sections, wherein more than one collaborator can be associated with a same section; receiving an update to the document as a result of an input made by at least one of the collaborators; sending a notification of the update to the document to at least one of: a new collaborator and an existing collaborator of the document; and refreshing the document to reflect the update. | 1. A method for providing notifications to collaborators of a document, comprising: accessing a document editor program that includes collaborative authoring functionality for collaboration and communication on the document and an integrated collaborative user interface that is used to display information relating to the collaboration; displaying collaborative user interface elements within the integrated collaborative user interface, wherein displaying the collaborative user interface comprises displaying a ribbon menu pane, a document editing pane and a document assembly pane, wherein displaying the ribbon menu pane comprises displaying a document elements ribbon including a publish element, a view details element and section elements including an insert element, a delete element, and a view details element while in collaborative mode and hiding the collaborative user interface elements when not in collaborative mode; wherein displaying the document assembly pane further comprises displaying, within the document assembly pane, a document detail pane, a section detail pane, and an expanded section detail pane, wherein displaying the document detail pane comprises displaying document details metadata associated with collaboratively authoring the document, and wherein displaying the section details pane comprising displaying section details metadata associated with an author assigned to at least one section of the document; using the integrated collaborative user interface to associate collaborators with one or more sections of the document for at least one of: reviewing the one or more sections and updating the one or more sections, wherein more than one collaborator can be associated with a same section; receiving an update to the document as a result of an input made by at least one of the collaborators; sending a notification of the update to the document to at least one of: a new collaborator and an existing collaborator of the document; and refreshing the document to reflect the update. 6. The method of claim 1 , further comprising hiding a display of the information relating to the collaboration from a display of the document. | 0.700837 |
5,412,756 | 38 | 49 | 38. A method of simulating plant operation with an artificial intelligence software shell comprising the steps of: storing, in a database, objects representing plant elements and concepts; reading input data from an input data file; determining when artificial intelligence knowledge sources should execute in accordance with a predetermined knowledge source priority scheme; and executing knowledge sources, in accordance with the determination, on specific predefined objects; wherein the step of determining includes the step of accessing a hash table being defined by a chaining algorithm, the hash table including a data point structure having entries for objects and at least one expression list. | 38. A method of simulating plant operation with an artificial intelligence software shell comprising the steps of: storing, in a database, objects representing plant elements and concepts; reading input data from an input data file; determining when artificial intelligence knowledge sources should execute in accordance with a predetermined knowledge source priority scheme; and executing knowledge sources, in accordance with the determination, on specific predefined objects; wherein the step of determining includes the step of accessing a hash table being defined by a chaining algorithm, the hash table including a data point structure having entries for objects and at least one expression list. 49. A method as claimed in claim 38 wherein the step of executing knowledge sources includes the step of interrupting execution of a lower priority knowledge source and executing a higher priority knowledge source in accordance with the knowledge source priority scheme. | 0.652956 |
9,323,838 | 1 | 3 | 1. A method comprising: extracting description information of multiple products; clustering the description information of the multiple products belonging to a particular model into a first text; processing the first text by segmenting the first text to one of remove from the first text one or more terms whose term frequencies are higher than a first set threshold, and remove from the first text one or more terms whose term frequencies are lower than a second set threshold; clustering, after processing the first text, first texts of products belonging to different models into a second text; applying a subject analysis to the second text to obtain one or more subjects; defining one or more names for the one or more subjects respectively; assigning a respective name of a respective subject correlated to description information of a respective product as an identifier of the respective product; and labeling the respective product by using the identifier, wherein the applying the subject analysis to the second text to obtain one or more subjects comprises: setting a number of subjects in one or more subject models; applying the subject analysis to the second text by using a text analysis method based on the one or more subject models; obtaining a number of subsets corresponding to the number of subjects from a set of terms in the second text, the number of subsets being equal to the number of subjects, a respective subset corresponding to a respective subject; and according to the respective subset that one or more terms in the description information of the products locate, correlating the description information of the products to the respective subject corresponding to the respective subset. | 1. A method comprising: extracting description information of multiple products; clustering the description information of the multiple products belonging to a particular model into a first text; processing the first text by segmenting the first text to one of remove from the first text one or more terms whose term frequencies are higher than a first set threshold, and remove from the first text one or more terms whose term frequencies are lower than a second set threshold; clustering, after processing the first text, first texts of products belonging to different models into a second text; applying a subject analysis to the second text to obtain one or more subjects; defining one or more names for the one or more subjects respectively; assigning a respective name of a respective subject correlated to description information of a respective product as an identifier of the respective product; and labeling the respective product by using the identifier, wherein the applying the subject analysis to the second text to obtain one or more subjects comprises: setting a number of subjects in one or more subject models; applying the subject analysis to the second text by using a text analysis method based on the one or more subject models; obtaining a number of subsets corresponding to the number of subjects from a set of terms in the second text, the number of subsets being equal to the number of subjects, a respective subset corresponding to a respective subject; and according to the respective subset that one or more terms in the description information of the products locate, correlating the description information of the products to the respective subject corresponding to the respective subset. 3. The method as recited in claim 1 , wherein the one or more subject models include a probabilistic latent semantic analysis (PLSA) or a latent Dirichlet allocation (LDA). | 0.85274 |
7,725,319 | 1 | 3 | 1. A method for processing a speech signal, comprising: using a memory, coupled to a processor, to receive an input speech signal; using the processor to construct a phoneme lattice for the input speech signal; determining vertices and arc parameters of the phoneme lattice for the input speech signal; searching the phoneme lattice to produce a likelihood score for each potential path; and determining a processing result for the input speech signal based on the likelihood score of each potential path; wherein constructing the phoneme lattice includes: segmenting an input speech signal into frames, extracting acoustic features for a frame of the input speech signal, determining K-best initial phoneme paths leading to the frame based on a first score of each potential phoneme path leading to the frame, and calculating a second score for each of the K-best phoneme paths for the frame; wherein searching the phoneme lattice comprises: receiving a phoneme lattice; traversing the phoneme lattice via potential paths; computing a score for a traversed path based on at least one of a phoneme confusion matrix and a plurality of language models; and modifying the score for the traversed path by allowing repetition of phonemes and allowing flexible endpoints for phonemes in a path such that at least one of a first arc that ends at a first frame and a second arc that starts at a third frame is extended so that the first arc and the second arc are directly connected at a second frame. | 1. A method for processing a speech signal, comprising: using a memory, coupled to a processor, to receive an input speech signal; using the processor to construct a phoneme lattice for the input speech signal; determining vertices and arc parameters of the phoneme lattice for the input speech signal; searching the phoneme lattice to produce a likelihood score for each potential path; and determining a processing result for the input speech signal based on the likelihood score of each potential path; wherein constructing the phoneme lattice includes: segmenting an input speech signal into frames, extracting acoustic features for a frame of the input speech signal, determining K-best initial phoneme paths leading to the frame based on a first score of each potential phoneme path leading to the frame, and calculating a second score for each of the K-best phoneme paths for the frame; wherein searching the phoneme lattice comprises: receiving a phoneme lattice; traversing the phoneme lattice via potential paths; computing a score for a traversed path based on at least one of a phoneme confusion matrix and a plurality of language models; and modifying the score for the traversed path by allowing repetition of phonemes and allowing flexible endpoints for phonemes in a path such that at least one of a first arc that ends at a first frame and a second arc that starts at a third frame is extended so that the first arc and the second arc are directly connected at a second frame. 3. The method of claim 1 , wherein determining vertices and arc parameters of the phoneme lattice comprises: clustering together K-best initial phoneme paths for at least one consecutive frame; and selecting M-best refined phoneme paths among the clustered phoneme paths based on second scores of these paths. | 0.5 |
10,102,190 | 1 | 2 | 1. A computer-implemented method for memory conserving versioning of an electronic document, comprising: receiving, at a server, client edits to the electronic document; analyzing, by the server, a plurality of server memory conserving versioning factors for determining whether to save the client edits as a new version of the electronic document, wherein at least one of the plurality of server memory conserving versioning factors is based on an amount of storage available to a particular client user or group of client users, and at least one of the plurality of server memory conserving versioning factors is based on a difficulty level of reproducing the client edits; generating a derived value based on the server memory conserving versioning factors; generating a versioning score at a client versioning analyzer based on the derived value and the client edits, and comparing the versioning score to a threshold versioning score; and in response to the versioning score meeting or exceeding the threshold versioning score: generating a new version identifier for the electronic document; and saving the client edits to a storage repository using the new version identifier. | 1. A computer-implemented method for memory conserving versioning of an electronic document, comprising: receiving, at a server, client edits to the electronic document; analyzing, by the server, a plurality of server memory conserving versioning factors for determining whether to save the client edits as a new version of the electronic document, wherein at least one of the plurality of server memory conserving versioning factors is based on an amount of storage available to a particular client user or group of client users, and at least one of the plurality of server memory conserving versioning factors is based on a difficulty level of reproducing the client edits; generating a derived value based on the server memory conserving versioning factors; generating a versioning score at a client versioning analyzer based on the derived value and the client edits, and comparing the versioning score to a threshold versioning score; and in response to the versioning score meeting or exceeding the threshold versioning score: generating a new version identifier for the electronic document; and saving the client edits to a storage repository using the new version identifier. 2. The computer-implemented method of claim 1 , wherein receiving client edits to the electronic document comprises receiving an update request from a client, and wherein the update request is a request for the server to update the electronic document with the client edits. | 0.703463 |
8,886,639 | 7 | 8 | 7. A computer program product tangibly embodied in a non-transitory computer-readable storage medium and comprising instructions that when executed by a processor perform a method for performing a search of services, the method comprising: receiving a search string that includes multiple words and that a user inputs for searching services in a repository; searching a multi-document index using the search string, the multi-document index identify, for each of the services, multiple documents that each reflect at least one aspect regarding the service; providing multiple results in response to the search of the multi-document index, each of the multiple results being associated with a corresponding service and the multiple documents identified in the multi-document index for the corresponding service; scoring the multiple results by providing, for each of the results: a first score that reflects an amount of the words from the search string that appear in any of the multiple documents that are associated with the result, and a second score that reflects a combination of: (i) one score that identifies an amount of the words from the search string that appear in a first one of the multiple documents that are associated with the result, and (ii) another score that identifies an amount of the words from the search string that appear in a second one of the multiple documents that are associated with the result; generating, for each of the results, a weighted score by weighting the first score and the second score for the result; ranking the results based on the weighted score that was generated for each of the results; and presenting an outcome of the search of the multi-document index to the user in response to receiving the search string, wherein the ranked results are included in the outcome of the search. | 7. A computer program product tangibly embodied in a non-transitory computer-readable storage medium and comprising instructions that when executed by a processor perform a method for performing a search of services, the method comprising: receiving a search string that includes multiple words and that a user inputs for searching services in a repository; searching a multi-document index using the search string, the multi-document index identify, for each of the services, multiple documents that each reflect at least one aspect regarding the service; providing multiple results in response to the search of the multi-document index, each of the multiple results being associated with a corresponding service and the multiple documents identified in the multi-document index for the corresponding service; scoring the multiple results by providing, for each of the results: a first score that reflects an amount of the words from the search string that appear in any of the multiple documents that are associated with the result, and a second score that reflects a combination of: (i) one score that identifies an amount of the words from the search string that appear in a first one of the multiple documents that are associated with the result, and (ii) another score that identifies an amount of the words from the search string that appear in a second one of the multiple documents that are associated with the result; generating, for each of the results, a weighted score by weighting the first score and the second score for the result; ranking the results based on the weighted score that was generated for each of the results; and presenting an outcome of the search of the multi-document index to the user in response to receiving the search string, wherein the ranked results are included in the outcome of the search. 8. The computer program product of claim 7 , wherein the multi-document index identifies, for at least some of the services: a service document that represents the service; an entity-set document that represents a data element of the service; an entity-type document that represents a data type of one or more entries being returned as a service response; a complex-type document that represents a data type of a non-simple typed property; a function document that represents at least one service operation of an entity set; a navigation property document that represents at least one association from an entity-type entity to one or more related entities of another entity type; a property document that represents a field of a data type; and a parameter document that represents a service operation parameter. | 0.5 |
7,676,521 | 12 | 13 | 12. A keyword search volume forecasting system having a processor and system memory for forecasting keyword search volume, the system comprising: keyword categorizer to determine a forecastability category of a keyword based on measured keyword search volumes, wherein the keyword categorizer categorizes keywords into directly forecastable and non-directly forecastable categories, and wherein a directly forecastable keyword is associated with at least a predefined amount of accumulated historical search volume data and a non-directly forecastable keyword is associated with less than the predefined amount of accumulated historical search volume data; a seasonality detector to detect a seasonality of keywords and keyword categories, wherein the seasonality is based on trends identified from historical search volume data associated with the the directly forecastable keywords, wherein the seasonality of each non-directly forecastable keyword is determined based on the seasonality of one or more directly forecastable keywords with which the non-directly forecastable keyword is associated; and a forecasting engine to forecast a keyword search volume corresponding to the non-directly forecastable keyword, wherein the forecasted search volume for the non-directly forecastable keyword is based at least on the seasonality and one or more of the historical search volume data of the non-directly forecastable keyword and the historical search volume data of the one or more directly forecastable keywords with which the non-directly forecastable keyword is associated. | 12. A keyword search volume forecasting system having a processor and system memory for forecasting keyword search volume, the system comprising: keyword categorizer to determine a forecastability category of a keyword based on measured keyword search volumes, wherein the keyword categorizer categorizes keywords into directly forecastable and non-directly forecastable categories, and wherein a directly forecastable keyword is associated with at least a predefined amount of accumulated historical search volume data and a non-directly forecastable keyword is associated with less than the predefined amount of accumulated historical search volume data; a seasonality detector to detect a seasonality of keywords and keyword categories, wherein the seasonality is based on trends identified from historical search volume data associated with the the directly forecastable keywords, wherein the seasonality of each non-directly forecastable keyword is determined based on the seasonality of one or more directly forecastable keywords with which the non-directly forecastable keyword is associated; and a forecasting engine to forecast a keyword search volume corresponding to the non-directly forecastable keyword, wherein the forecasted search volume for the non-directly forecastable keyword is based at least on the seasonality and one or more of the historical search volume data of the non-directly forecastable keyword and the historical search volume data of the one or more directly forecastable keywords with which the non-directly forecastable keyword is associated. 13. The forecasting system of claim 12 , wherein the seasonality detector classifies keywords as seasonal and non-seasonal. | 0.686224 |
8,145,481 | 4 | 5 | 4. The method of claim 3 , further comprising: generating a confidence score to determine whether the generated word lattices are acceptable. | 4. The method of claim 3 , further comprising: generating a confidence score to determine whether the generated word lattices are acceptable. 5. The method of claim 4 , wherein: the parameters of the background model are determined based on a first sample period; the parameters of the transducer model are determined based on a second sample period; and the confidence score is compared to a predetermined value in order to determine whether to perform the automatic speech recognition process again. | 0.5 |
9,507,947 | 1 | 4 | 1. A method of performing data loss prevention on content from a content source, the method comprising: generating, by processing circuitry, multiple variants from the content, the multiple variants including a set of variants for each parsed word of the content, each variant of the set (i) including multiple characters and (ii) differing from other variants of the set by at least one character; performing, by the processing circuitry, evaluation operations to determine whether any of the variants includes sensitive data; and in response to the evaluation operations, performing, by the processing circuitry, a control operation which (i) releases all of the parsed words of the content to a destination when none of the variants is determined to include sensitive data, and (ii) blocks at least one parsed word of the content from reaching the destination when at least one variant is determined to include sensitive data; wherein generating the multiple variants from the content includes: applying a set of predefined transformations from a transformation database to the content from the content source to form the multiple variants. | 1. A method of performing data loss prevention on content from a content source, the method comprising: generating, by processing circuitry, multiple variants from the content, the multiple variants including a set of variants for each parsed word of the content, each variant of the set (i) including multiple characters and (ii) differing from other variants of the set by at least one character; performing, by the processing circuitry, evaluation operations to determine whether any of the variants includes sensitive data; and in response to the evaluation operations, performing, by the processing circuitry, a control operation which (i) releases all of the parsed words of the content to a destination when none of the variants is determined to include sensitive data, and (ii) blocks at least one parsed word of the content from reaching the destination when at least one variant is determined to include sensitive data; wherein generating the multiple variants from the content includes: applying a set of predefined transformations from a transformation database to the content from the content source to form the multiple variants. 4. A method as in claim 1 wherein a content extraction phase involves extracting the content from the content source; and wherein applying the set of predefined transformations from the transformation database to the content from the content source includes: following the content extraction phase and during a classification phase in which the content is classified to a vocabulary, generating (i) first word variants for a first parsed word of the content and (ii) second word variants for a second parsed word of the content. | 0.5 |
9,842,390 | 11 | 12 | 11. The computer program product of claim 7 , wherein the plurality of imaging studies are echocardiogram studies and the region of interest is a Doppler spectrum. | 11. The computer program product of claim 7 , wherein the plurality of imaging studies are echocardiogram studies and the region of interest is a Doppler spectrum. 12. The computer program product of claim 11 wherein extracting one or more discriminating image features includes densely sampling both an envelope and an interior of the Doppler spectrum using one or more scale-invariant feature transform features. | 0.5 |
8,001,119 | 1 | 2 | 1. A computer-implemented method of automatically assisting an analyst in a current information analysis task, comprising the steps of: modeling an analytic context, in a user-system cooperative manner, wherein the analytic context is a structure representative of analytic actions performed by a user in conducting an information analysis task and relationships associated with the user's analytic actions, wherein analytic actions include data inquiry actions, data synthesis actions, and visual manipulation actions by the user; and utilizing at least a portion of the user-system cooperatively-modeled analytic context structure to adaptively gather information relevant to a current state of the information analysis task, wherein the step of modeling an analytic context further comprises modeling the analytic context as a graph of user analytic actions, and wherein the step of modeling the analytic context as a graph of user analytic actions comprises modeling a user analytic action for a particular investigative target as a node of the analytic action graph. | 1. A computer-implemented method of automatically assisting an analyst in a current information analysis task, comprising the steps of: modeling an analytic context, in a user-system cooperative manner, wherein the analytic context is a structure representative of analytic actions performed by a user in conducting an information analysis task and relationships associated with the user's analytic actions, wherein analytic actions include data inquiry actions, data synthesis actions, and visual manipulation actions by the user; and utilizing at least a portion of the user-system cooperatively-modeled analytic context structure to adaptively gather information relevant to a current state of the information analysis task, wherein the step of modeling an analytic context further comprises modeling the analytic context as a graph of user analytic actions, and wherein the step of modeling the analytic context as a graph of user analytic actions comprises modeling a user analytic action for a particular investigative target as a node of the analytic action graph. 2. The method of claim 1 , wherein the step of modeling a user analytic action for a particular investigative target as a node of the analytic action graph further comprises the step of persisting user queries on investigative targets, gathered information and interactions with the results related to information gathering. | 0.5 |
9,672,253 | 1 | 4 | 1. A computer implemented method, comprising: receiving a search query; identifying a plurality of documents that are responsive to the search query, the plurality of documents including a first document and a second document; determining a first data measure for the first document, wherein the first data measure is indicative of an amount of data usage required to load the first document; determining a second data measure for the second document, wherein the second data measure is indicative of an amount of data usage required to load the second document; determining that the first document is similar to the second document; in response to determining that the first document is similar to the second document, ranking the first document relative to the second document based on the first data measure and the second data measure; and providing search results for display in response to the search query, wherein providing the search results comprises providing a first search result that is based on the first document, providing a second search result that is based on the second document, and providing the first search result and the second search result based on the ranking. | 1. A computer implemented method, comprising: receiving a search query; identifying a plurality of documents that are responsive to the search query, the plurality of documents including a first document and a second document; determining a first data measure for the first document, wherein the first data measure is indicative of an amount of data usage required to load the first document; determining a second data measure for the second document, wherein the second data measure is indicative of an amount of data usage required to load the second document; determining that the first document is similar to the second document; in response to determining that the first document is similar to the second document, ranking the first document relative to the second document based on the first data measure and the second data measure; and providing search results for display in response to the search query, wherein providing the search results comprises providing a first search result that is based on the first document, providing a second search result that is based on the second document, and providing the first search result and the second search result based on the ranking. 4. The method of claim 1 , further comprising determining that the search query is non-navigational, wherein ranking the first document relative to the second document is based on determining the search query is non-navigational. | 0.828593 |
8,275,803 | 1 | 2 | 1. A computer-implemented method of generating answers to questions based on a corpus of data, said method comprising: receiving an input query; performing a query context analysis upon said input query to break down said input query into query terms, said query terms comprising searchable components; conducting a first search in said corpus of data using one of more of said searchable components to obtain documents potentially including candidate answers, wherein all documents potentially including candidate answers are stored in a data storage device; analyzing all of said documents and each document's metadata, in a candidate answer generation module, to generate a set of candidate answers; conducting a second search in said corpus of data using said candidate answers and said searchable components of said query terms to obtain one or more supporting passages, wherein said supporting passages have at least one of said candidate answers and at least one of said searchable components of said query terms; scoring said candidate answers using said supporting passages, wherein said scoring is carried out by a plurality of parallel implemented scoring modules, each scoring module producing a candidate score; selecting one or more query answers based on said candidate score; generating a query response based on said one or more query answers for delivery to a user, wherein each said plurality of parallel implemented scoring modules for scoring all candidate answers using the said supporting passages automatically conducts, in parallel, one or more analyses each producing a candidate score, wherein one candidate score comprises a term match score obtained by implementing executable instructions for counting the number of terms in said supporting passage and determining if said number matches a number of terms in a candidate answer; and, wherein a further score comprises a textual alignment score obtained by said processor implementing executable instructions for determining if placement of words in said supporting passages are in alignment with placement of words of said candidate answers; and, wherein a further score comprises a deeper analysis score obtained by said processor implementing executable instructions for determining the meaning of the supporting passages and input queries by analyzing lexical or semantic relations. | 1. A computer-implemented method of generating answers to questions based on a corpus of data, said method comprising: receiving an input query; performing a query context analysis upon said input query to break down said input query into query terms, said query terms comprising searchable components; conducting a first search in said corpus of data using one of more of said searchable components to obtain documents potentially including candidate answers, wherein all documents potentially including candidate answers are stored in a data storage device; analyzing all of said documents and each document's metadata, in a candidate answer generation module, to generate a set of candidate answers; conducting a second search in said corpus of data using said candidate answers and said searchable components of said query terms to obtain one or more supporting passages, wherein said supporting passages have at least one of said candidate answers and at least one of said searchable components of said query terms; scoring said candidate answers using said supporting passages, wherein said scoring is carried out by a plurality of parallel implemented scoring modules, each scoring module producing a candidate score; selecting one or more query answers based on said candidate score; generating a query response based on said one or more query answers for delivery to a user, wherein each said plurality of parallel implemented scoring modules for scoring all candidate answers using the said supporting passages automatically conducts, in parallel, one or more analyses each producing a candidate score, wherein one candidate score comprises a term match score obtained by implementing executable instructions for counting the number of terms in said supporting passage and determining if said number matches a number of terms in a candidate answer; and, wherein a further score comprises a textual alignment score obtained by said processor implementing executable instructions for determining if placement of words in said supporting passages are in alignment with placement of words of said candidate answers; and, wherein a further score comprises a deeper analysis score obtained by said processor implementing executable instructions for determining the meaning of the supporting passages and input queries by analyzing lexical or semantic relations. 2. The computer-implemented method as claimed in claim 1 , wherein said query context analysis includes determining, from said query, one or more predicate argument structures for each input query. | 0.780134 |
9,177,530 | 1 | 13 | 1. A method for displaying an electronic document, the method comprising: receiving an electronic document; displaying a current page of the electronic document on a screen of a handheld device operated by a user; and displaying an adjacent page of the electronic document on a display that is external to the handheld device, wherein the adjacent page is adjacent to the current page within the electronic document. | 1. A method for displaying an electronic document, the method comprising: receiving an electronic document; displaying a current page of the electronic document on a screen of a handheld device operated by a user; and displaying an adjacent page of the electronic document on a display that is external to the handheld device, wherein the adjacent page is adjacent to the current page within the electronic document. 13. The method of claim 1 , further comprising wherein the display is substantially larger than the screen. | 0.692529 |
8,363,235 | 10 | 11 | 10. A non-transitory computer-readable medium storing a program that causes a computer to execute document processing, the document processing comprising: acquiring document data containing plural pieces of page image data corresponding to respective pages of a plurality of documents, each document being formed by stacking and half-folding sheets; a first detection step of detecting, based on characteristics of the plural pieces of page image data, pieces of page image data corresponding to pages to be printed on a same side of a same sheet in the documents, from the plural pieces of page image data contained in the document data; specifying, based on positions of the detected pieces of page image data in the document data, pieces of page image data corresponding to respective pages of each document, from the plural pieces of page image data contained in the document data; outputting data, which is based on pieces of page image data corresponding to respective pages of at least one of the documents, based on a result of the specifying a second detection step of detecting page image data having an image drawn in a first area corresponding to a first end; and a third detection step of detecting page image data having an image drawn in a second area corresponding to a second end opposed to the first end, wherein the first detection step detects the pieces of page image data corresponding to the pages to be printed on the same side of the same sheet in the documents, based on a result of the second detection step and a result of the third detection step. | 10. A non-transitory computer-readable medium storing a program that causes a computer to execute document processing, the document processing comprising: acquiring document data containing plural pieces of page image data corresponding to respective pages of a plurality of documents, each document being formed by stacking and half-folding sheets; a first detection step of detecting, based on characteristics of the plural pieces of page image data, pieces of page image data corresponding to pages to be printed on a same side of a same sheet in the documents, from the plural pieces of page image data contained in the document data; specifying, based on positions of the detected pieces of page image data in the document data, pieces of page image data corresponding to respective pages of each document, from the plural pieces of page image data contained in the document data; outputting data, which is based on pieces of page image data corresponding to respective pages of at least one of the documents, based on a result of the specifying a second detection step of detecting page image data having an image drawn in a first area corresponding to a first end; and a third detection step of detecting page image data having an image drawn in a second area corresponding to a second end opposed to the first end, wherein the first detection step detects the pieces of page image data corresponding to the pages to be printed on the same side of the same sheet in the documents, based on a result of the second detection step and a result of the third detection step. 11. The non-transitory computer-readable medium according to claim 10 , wherein the document data is configured so that the plural pieces of page image data corresponding to the respective pages of the plurality of documents can be read out in a predetermined order, the document processing further comprises determining as to whether or not a rank of the page image data detected in the second detection step and a rank of the page image data detected in the third detection step have a predetermined relationship therebetween, and when it is determined that the rank of the page image data detected in the second detection step and the rank of the page image data detected in the third detection step have the predetermined relationship, the first detection step detects that the page image data detected in the second detection step and the page image data detected in the third detection step are the pieces of page image data corresponding to the pages to be printed on the same side of the same sheet in the documents. | 0.5 |
9,817,886 | 1 | 4 | 1. A method, performed by at least one computer system, of retrieving documents in response to a search query that includes a phrase and a first date, the method comprising: selecting, from a corpus of documents, a plurality of documents that are relevant to the query; determining, using a processor of the at least one computer system, for at least one of the plurality of documents, a date range for the document, the date range representing a period for which no change in the document has been detected; calculating, using a processor of the at least one computer system, a weighted relevance score for each of the plurality of documents, the weighted relevance score for a particular document being a relevance score for the particular document adjusted by a difference between the first date and the date range for the particular document when the particular document has a date range; and ranking, using a processor of the at least one computer system, the plurality of documents according to their weighted relevance scores. | 1. A method, performed by at least one computer system, of retrieving documents in response to a search query that includes a phrase and a first date, the method comprising: selecting, from a corpus of documents, a plurality of documents that are relevant to the query; determining, using a processor of the at least one computer system, for at least one of the plurality of documents, a date range for the document, the date range representing a period for which no change in the document has been detected; calculating, using a processor of the at least one computer system, a weighted relevance score for each of the plurality of documents, the weighted relevance score for a particular document being a relevance score for the particular document adjusted by a difference between the first date and the date range for the particular document when the particular document has a date range; and ranking, using a processor of the at least one computer system, the plurality of documents according to their weighted relevance scores. 4. The method of claim 1 , wherein the relevance score for a document is down-weighted in proportion to proximity of the date range for the document with respect to the first date. | 0.5 |
8,752,074 | 1 | 5 | 1. A method performed by one or more processing devices comprising: polling a server for script relating to a device; receiving the script from the server, the script being in a self-describing computer language, the script comprising simple object access protocol (SOAP) commands and executable code that is in the self-describing computer language and that defines functions to be performed on variables to be passed from the executable code to corresponding SOAP commands; interpreting a part of the script to perform a function contained in the script on a variable and to pass the variable to a SOAP command; parsing the SOAP command from the script; passing the SOAP command to a SOAP interpreter to execute the SOAP command with the variable; and repeating the interpreting, parsing and passing for a different part of the script comprising a different function, a different variable, and a different SOAP command; wherein interpreting, parsing, passing and repeating are performed without requiring further communication to the server; and wherein the function comprises an If-Then statement or an If-Then-Else statement. | 1. A method performed by one or more processing devices comprising: polling a server for script relating to a device; receiving the script from the server, the script being in a self-describing computer language, the script comprising simple object access protocol (SOAP) commands and executable code that is in the self-describing computer language and that defines functions to be performed on variables to be passed from the executable code to corresponding SOAP commands; interpreting a part of the script to perform a function contained in the script on a variable and to pass the variable to a SOAP command; parsing the SOAP command from the script; passing the SOAP command to a SOAP interpreter to execute the SOAP command with the variable; and repeating the interpreting, parsing and passing for a different part of the script comprising a different function, a different variable, and a different SOAP command; wherein interpreting, parsing, passing and repeating are performed without requiring further communication to the server; and wherein the function comprises an If-Then statement or an If-Then-Else statement. 5. The method of claim 1 , wherein the function comprises a conditional statement. | 0.78866 |
9,189,548 | 1 | 5 | 1. A method performed by a computer system, the method comprising: generating, by one or more processors associated with the computer system, links to a set of documents relevant to a search query submitted by a user device; associating, by the one or more processors, a visual cue with one of the generated links, the one of the generated links pointing to a particular document, the visual cue being associated with the one of the generated links based on detecting that a click through rate associated with the particular document is greater, by at least a threshold amount, than click through rates associated with all other documents in the set of documents, the visual cue being associated with the one of the generated links without being associated with at least another one of the generated links based on detecting that the click through rate is greater than the click through rates; and providing, by the one or more processors, the generated links and the associated visual cue to the user device. | 1. A method performed by a computer system, the method comprising: generating, by one or more processors associated with the computer system, links to a set of documents relevant to a search query submitted by a user device; associating, by the one or more processors, a visual cue with one of the generated links, the one of the generated links pointing to a particular document, the visual cue being associated with the one of the generated links based on detecting that a click through rate associated with the particular document is greater, by at least a threshold amount, than click through rates associated with all other documents in the set of documents, the visual cue being associated with the one of the generated links without being associated with at least another one of the generated links based on detecting that the click through rate is greater than the click through rates; and providing, by the one or more processors, the generated links and the associated visual cue to the user device. 5. The method of claim 1 , where the click through rate, associated with the particular document, includes an observed historical click through rate calculated as a ratio representing a total number of times that users have selected the particular document to a total number of times that users have selected another document. | 0.694757 |
9,268,455 | 8 | 9 | 8. The method as claimed in claim 1 , wherein one or more search terms, which can be logically combined, are stored in a data memory, a computing unit accesses network nodes connected to source databases via a network, and data of the source databases are selected on the basis of the search terms, in a data memory, at least one weighting parameter is stored and allocated to a search term or a logical combination of search terms, wherein by a filter module of the computing unit, a multiplicity of source databases of the network nodes are accessed and a weighting list with found data records is generated for each weighting parameter in conjunction with the associated search terms, at least one or more of a source database type or a time information of the occurrence of the documents in this source database or location information of the source database is stored and allocated to each of the data records found, and wherein, by a parameterizing module, one or more variable mood variables are generated at least partially dynamically on the basis of at least one or more of the weighting list, the associated source database types or the time information or location information for the respective weighting parameter, which variable mood variables correspond to temporal mood fluctuations of users of the network, the generated search terms or node elements comprising at least the mood variables. | 8. The method as claimed in claim 1 , wherein one or more search terms, which can be logically combined, are stored in a data memory, a computing unit accesses network nodes connected to source databases via a network, and data of the source databases are selected on the basis of the search terms, in a data memory, at least one weighting parameter is stored and allocated to a search term or a logical combination of search terms, wherein by a filter module of the computing unit, a multiplicity of source databases of the network nodes are accessed and a weighting list with found data records is generated for each weighting parameter in conjunction with the associated search terms, at least one or more of a source database type or a time information of the occurrence of the documents in this source database or location information of the source database is stored and allocated to each of the data records found, and wherein, by a parameterizing module, one or more variable mood variables are generated at least partially dynamically on the basis of at least one or more of the weighting list, the associated source database types or the time information or location information for the respective weighting parameter, which variable mood variables correspond to temporal mood fluctuations of users of the network, the generated search terms or node elements comprising at least the mood variables. 9. The method as claimed in claim 8 , wherein the weighting list with the data records found or references to data records found is stored accessible to a user in a content module of the computing unit. | 0.568376 |
7,856,472 | 70 | 205 | 70. A computer program product embodied on a non-transitory computer readable medium, comprising: computer code for displaying at least one window in connection with a website; computer code for displaying, utilizing the at least one window, a stock-related field; computer code for receiving a plurality of characters of text from a user as the user is typing the text utilizing the stock-related field; computer code for dynamically determining, after the user types each character in the received text, whether the characters typed so far match one or more text strings in one of a plurality of n-tuples including at least two text strings, each of the plurality of n-tuples including first text representing a stock ticker symbol and second text representing a company name corresponding to the stock ticker symbol; computer code for indicating to the user that a match has been found, utilizing the at least one window, if it is determined that the characters typed so far match the one or more text strings in the one of the plurality of n-tuples; computer code for displaying, utilizing the at least one window, a plurality of message summaries; wherein the plurality of message summaries comprise first information derived from a first message of a plurality of first messages and second information derived from a second message of a plurality of second messages associated with at least one online forum; computer code for displaying, utilizing the at least one window, a first set of representations; computer code for receiving first input from the user indicating a selection of one of the first set of representations; computer code for displaying a second set of representations representing a set of hyperlinks, utilizing the at least one window, in response to receiving the first input; computer code for receiving second input from the user indicating a selection of one of the second set of representations; and computer code for navigating to a destination specified by the selected one of the second set of representations, in response to receiving the second input. | 70. A computer program product embodied on a non-transitory computer readable medium, comprising: computer code for displaying at least one window in connection with a website; computer code for displaying, utilizing the at least one window, a stock-related field; computer code for receiving a plurality of characters of text from a user as the user is typing the text utilizing the stock-related field; computer code for dynamically determining, after the user types each character in the received text, whether the characters typed so far match one or more text strings in one of a plurality of n-tuples including at least two text strings, each of the plurality of n-tuples including first text representing a stock ticker symbol and second text representing a company name corresponding to the stock ticker symbol; computer code for indicating to the user that a match has been found, utilizing the at least one window, if it is determined that the characters typed so far match the one or more text strings in the one of the plurality of n-tuples; computer code for displaying, utilizing the at least one window, a plurality of message summaries; wherein the plurality of message summaries comprise first information derived from a first message of a plurality of first messages and second information derived from a second message of a plurality of second messages associated with at least one online forum; computer code for displaying, utilizing the at least one window, a first set of representations; computer code for receiving first input from the user indicating a selection of one of the first set of representations; computer code for displaying a second set of representations representing a set of hyperlinks, utilizing the at least one window, in response to receiving the first input; computer code for receiving second input from the user indicating a selection of one of the second set of representations; and computer code for navigating to a destination specified by the selected one of the second set of representations, in response to receiving the second input. 205. The computer program product of claim 70 , wherein the computer program product is operable such that the second set of representations are displayed for allowing the user to scan through the hyperlinks before the navigation. | 0.708122 |
9,477,583 | 1 | 5 | 1. A computer implemented method, comprising: communicating, between a test case automation tool and a software application, to extract a list of methods to test from the software application; storing the list of methods in a first extensible markup language (XML) file; defining a first automated test case in a second XML file for testing the software application, the defining including: receiving selection input of a set of methods from the list of methods in the first XML file and indicating in the second XML file the set of methods; receiving parameter values for parameter fields for the set of methods to use in a test case execution and indicating in the second XML file the parameter fields and the selected parameter values; indicating in the second XML file a specified order of execution of the set of methods, wherein the specified order of execution of the set of methods comprises an order that is different than an order of the set of methods in the software application; indicating in the second XML file a list of files required for the set of methods; and in response to indication of the first automated test case, reading the second XML file and executing the set of methods indicated in the second XML file according to the specified order in the second XML file and with the selected parameter values in the second XML file. | 1. A computer implemented method, comprising: communicating, between a test case automation tool and a software application, to extract a list of methods to test from the software application; storing the list of methods in a first extensible markup language (XML) file; defining a first automated test case in a second XML file for testing the software application, the defining including: receiving selection input of a set of methods from the list of methods in the first XML file and indicating in the second XML file the set of methods; receiving parameter values for parameter fields for the set of methods to use in a test case execution and indicating in the second XML file the parameter fields and the selected parameter values; indicating in the second XML file a specified order of execution of the set of methods, wherein the specified order of execution of the set of methods comprises an order that is different than an order of the set of methods in the software application; indicating in the second XML file a list of files required for the set of methods; and in response to indication of the first automated test case, reading the second XML file and executing the set of methods indicated in the second XML file according to the specified order in the second XML file and with the selected parameter values in the second XML file. 5. The computer implemented method of claim 1 , further comprising: receiving input defining a plurality of automated tests cases, including the first automated test case, as an automated test set in a third XML, file; and indicating dependencies among the plurality of automated test cases as parameter values in the third XML file. | 0.579545 |
9,037,470 | 16 | 18 | 16. A non-transitory computer-readable medium, comprising instructions for: determining, by a processor, whether at least one agent has followed at least one script relating to an automatic speech recognition component's ability to analyze at least one voice interaction between the at least one agent and at least one client; and dispositioning at least one interaction, wherein the at least one agent reads the at least one script to the at least one client, based on a comparison of a duration of the at least one interaction to an expected duration parameter associated with the at least one interaction, wherein the dispositioning comprises indicating the at least one interaction as potentially fraudulent if the duration is outside of an expected duration. | 16. A non-transitory computer-readable medium, comprising instructions for: determining, by a processor, whether at least one agent has followed at least one script relating to an automatic speech recognition component's ability to analyze at least one voice interaction between the at least one agent and at least one client; and dispositioning at least one interaction, wherein the at least one agent reads the at least one script to the at least one client, based on a comparison of a duration of the at least one interaction to an expected duration parameter associated with the at least one interaction, wherein the dispositioning comprises indicating the at least one interaction as potentially fraudulent if the duration is outside of an expected duration. 18. The non-transitory computer-readable medium of claim 16 , comprising instructions for supplying audio files of at least one voice interaction in real time and/or recording the at least one voice interaction and supplying the files to the automatic speech recognition component. | 0.5 |
10,120,534 | 11 | 17 | 11. A method for automatically generating a user interface for an application program comprising: using a first computer, obtaining from one or more non-transitory computer-readable data storage media a copy of one or more sequences of instructions that are stored on the media and are arranged, when executed using a second computer among a plurality of other computers to cause the second computer to perform: using a computer, in response to detecting an event, selecting, by the application program, a primary widget from a plurality of widgets to display on the user interface; using the computer, in response to selecting the primary widget, querying a data store that is storing tags associated with widgets, using one or more particular tags that are associated with the primary widget; using the computer, based on the querying, determining one or more secondary widgets from the plurality of widgets, wherein the one or more secondary widgets are associated with at least one of the one or more particular tags of the primary widget; using the computer, for each particular secondary widget among the one or more secondary widgets, determining correlation data that measures correlation of the particular secondary widget to the primary widget; using the computer, based on the correlation data of the particular secondary widget, determining whether to display the particular secondary widget on the user interface in a particular arrangement comprising the particular secondary widget and one or more other secondary widgets from among the one or more secondary widgets. | 11. A method for automatically generating a user interface for an application program comprising: using a first computer, obtaining from one or more non-transitory computer-readable data storage media a copy of one or more sequences of instructions that are stored on the media and are arranged, when executed using a second computer among a plurality of other computers to cause the second computer to perform: using a computer, in response to detecting an event, selecting, by the application program, a primary widget from a plurality of widgets to display on the user interface; using the computer, in response to selecting the primary widget, querying a data store that is storing tags associated with widgets, using one or more particular tags that are associated with the primary widget; using the computer, based on the querying, determining one or more secondary widgets from the plurality of widgets, wherein the one or more secondary widgets are associated with at least one of the one or more particular tags of the primary widget; using the computer, for each particular secondary widget among the one or more secondary widgets, determining correlation data that measures correlation of the particular secondary widget to the primary widget; using the computer, based on the correlation data of the particular secondary widget, determining whether to display the particular secondary widget on the user interface in a particular arrangement comprising the particular secondary widget and one or more other secondary widgets from among the one or more secondary widgets. 17. The method of claim 11 , wherein the particular secondary widget presents monitoring data for a particular secondary managed system element, and wherein the correlation data for the particular secondary widget comprises indication whether the monitoring data for the particular secondary managed system element exceeded one or more threshold values for the particular secondary managed system element. | 0.5 |
8,996,993 | 1 | 13 | 1. A text analysis method comprising: using processing circuitry, generating a first representation of a text item using a first measurement basis; using the processing circuitry, generating a second representation of the text item using a second measurement basis different than the first measurement basis, wherein the second representation is different than the first representation; using the processing circuitry, analyzing the text item using the first representation and the second representation; using the processing circuitry, steering the generating of at least one of the first and second representations according to a perspective of interest of a user; using the processing circuitry, accessing least one text pattern of interest to the user; using the processing circuitry, generating one of the first measurement basis and the second measurement basis using the at least one text pattern of interest to the user; and wherein the generating the one of the first measurement basis and the second measurement basis comprises generating the one of the first measurement basis and the second measurement basis to comprise associations of a plurality of measurement features in the form of text patterns with a plurality of dimension anchors which comprise different topics of textual content. | 1. A text analysis method comprising: using processing circuitry, generating a first representation of a text item using a first measurement basis; using the processing circuitry, generating a second representation of the text item using a second measurement basis different than the first measurement basis, wherein the second representation is different than the first representation; using the processing circuitry, analyzing the text item using the first representation and the second representation; using the processing circuitry, steering the generating of at least one of the first and second representations according to a perspective of interest of a user; using the processing circuitry, accessing least one text pattern of interest to the user; using the processing circuitry, generating one of the first measurement basis and the second measurement basis using the at least one text pattern of interest to the user; and wherein the generating the one of the first measurement basis and the second measurement basis comprises generating the one of the first measurement basis and the second measurement basis to comprise associations of a plurality of measurement features in the form of text patterns with a plurality of dimension anchors which comprise different topics of textual content. 13. The method of claim 1 wherein the generating the one of the first measurement basis and the second measurement basis comprises generating the one of the first measurement basis and the second measurement basis wherein the at least one text pattern comprises one of the measurement features and one of the dimension anchors. | 0.62065 |
9,052,812 | 11 | 20 | 11. A computer-implemented method comprising: providing a graphical design environment to a user using a processor, wherein the graphical design environment includes a drag and drop interface that allows the user to add a widget to a design; displaying a note field in a note interface in the graphical design environment that accepts a text string from the user; exporting the design from the graphical design environment and storing the design as an intermittent coded representation of the design in a markup language format, wherein a set of at least two widgets that include the widget are exported with the design; rendering the design in a design player using the intermitted coded representation of the design in the markup language format; displaying a discussion interface in the design player that: (i) is displayed in the design player consistently with the design; (ii) displays the text string from the user as a note; (iii) has a scrollbar; and (iv) accepts a comment from a second user regarding the note; allowing the second user to use the scrollbar to scroll through a set of notes that are associated with different portions of the design while viewing a fixed portion of the design; in response to selection of an interface element that is in the discussion interface with the note by the second user, placing the design player into a state wherein each widget in the set of at least two widgets is exposed for selection by the second user as a selected widget, and wherein selection of the selected widget by the second user links the note with the widget; and displaying the comment in the graphical design environment after being accepted in the discussion interface; wherein the text string and comment are: (i) stored in a data store along with an indication of the selected widget; (ii) read from the data store and rendered by the design player from the markup language format; and (iii) read from the data store and displayed in the graphical design environment from a design environment format; and wherein the data store is accessible to the graphical design environment and the design player. | 11. A computer-implemented method comprising: providing a graphical design environment to a user using a processor, wherein the graphical design environment includes a drag and drop interface that allows the user to add a widget to a design; displaying a note field in a note interface in the graphical design environment that accepts a text string from the user; exporting the design from the graphical design environment and storing the design as an intermittent coded representation of the design in a markup language format, wherein a set of at least two widgets that include the widget are exported with the design; rendering the design in a design player using the intermitted coded representation of the design in the markup language format; displaying a discussion interface in the design player that: (i) is displayed in the design player consistently with the design; (ii) displays the text string from the user as a note; (iii) has a scrollbar; and (iv) accepts a comment from a second user regarding the note; allowing the second user to use the scrollbar to scroll through a set of notes that are associated with different portions of the design while viewing a fixed portion of the design; in response to selection of an interface element that is in the discussion interface with the note by the second user, placing the design player into a state wherein each widget in the set of at least two widgets is exposed for selection by the second user as a selected widget, and wherein selection of the selected widget by the second user links the note with the widget; and displaying the comment in the graphical design environment after being accepted in the discussion interface; wherein the text string and comment are: (i) stored in a data store along with an indication of the selected widget; (ii) read from the data store and rendered by the design player from the markup language format; and (iii) read from the data store and displayed in the graphical design environment from a design environment format; and wherein the data store is accessible to the graphical design environment and the design player. 20. The computer-implemented method of claim 11 , further comprising: displaying an identifier for the user with the note in the discussion interface. | 0.813896 |
8,583,420 | 10 | 17 | 10. A method for building a knowledge base containing entailment relations, comprising the steps of: a) providing at least one input pattern (p) with N pattern slots (N>1), said input pattern (p) expressing a specific semantic relation between N entities that fill the N pattern slots of the input pattern (p) as slot fillers, b) providing at least one cluster (c) of articles, said articles of said cluster (c) relating to a common main topic; c) processing, by a computer device, said articles with respect to the input pattern (p) and identifying the identities which match the semantic type of the N pattern slots; d) if said at least one input pattern matches a portion of an article (a) of said at least one cluster (c): i) storing, by the computer device, the N slot fillers (s 1 , s 2 , . . . , s N ), which match the slots of the pattern (p), and a cluster identifier I c of the cluster (c) into a first table S, wherein the N-tuple (s 1 , s 2 , . . . , s N ) and the cluster identifier I c of the associated cluster (c) form one element of said table S; ii) for each element of table S, identifying, by the computer device, appearances of the slot fillers (s 1 , s 2 , . . . , s N ) in a plurality of articles of cluster (c) and for each appearance so identified, storing the slot fillers (s 1 , s 2 , . . . , s N ) together with the sentence in which they occur into a second table C 0 ; iii) from the sentences stored in table C 0 , extracting, by the computer device, patterns which span over the corresponding N slot fillers (s 1 , s 2 , . . . , s N ), said extracted pattern expressing a semantic relation between said N slot fillers; and iv) storing, by the computer device, said extracted patterns together with said input pattern as entailment relation into said knowledge base. | 10. A method for building a knowledge base containing entailment relations, comprising the steps of: a) providing at least one input pattern (p) with N pattern slots (N>1), said input pattern (p) expressing a specific semantic relation between N entities that fill the N pattern slots of the input pattern (p) as slot fillers, b) providing at least one cluster (c) of articles, said articles of said cluster (c) relating to a common main topic; c) processing, by a computer device, said articles with respect to the input pattern (p) and identifying the identities which match the semantic type of the N pattern slots; d) if said at least one input pattern matches a portion of an article (a) of said at least one cluster (c): i) storing, by the computer device, the N slot fillers (s 1 , s 2 , . . . , s N ), which match the slots of the pattern (p), and a cluster identifier I c of the cluster (c) into a first table S, wherein the N-tuple (s 1 , s 2 , . . . , s N ) and the cluster identifier I c of the associated cluster (c) form one element of said table S; ii) for each element of table S, identifying, by the computer device, appearances of the slot fillers (s 1 , s 2 , . . . , s N ) in a plurality of articles of cluster (c) and for each appearance so identified, storing the slot fillers (s 1 , s 2 , . . . , s N ) together with the sentence in which they occur into a second table C 0 ; iii) from the sentences stored in table C 0 , extracting, by the computer device, patterns which span over the corresponding N slot fillers (s 1 , s 2 , . . . , s N ), said extracted pattern expressing a semantic relation between said N slot fillers; and iv) storing, by the computer device, said extracted patterns together with said input pattern as entailment relation into said knowledge base. 17. The method for building a knowledge base containing entailment relations according to claim 10 , wherein prior to iv), each extracted pattern is weighted with respect of the number of sentences and the number of slot filler N-tuples which support the respective extracted pattern, and wherein only those extracted patterns, for which the weight exceeds a predetermined threshold, are further considered in iv). | 0.5 |
9,911,358 | 1 | 2 | 1. A system for real-time tracking of at least one of a position, orientation, and movement of a tongue of a user during speech comprising: a tracer unit; magnetic sensors; a speech characteristic sensor; a sensor control unit; a computing platform; and a feedback system; wherein the tracer unit is adapted to be non-obstructively affixed at a location on the tongue of the user; wherein the magnetic sensors are configurable to measure a magnetic flux density at the location of the tracer unit, the magnetic sensors in non-obstructive proximity to the tracer unit and mouth of the user; wherein the speech characteristic sensor configurable to detect a speech characteristic selected from the group consisting of sound produced by the user, an air flow produced by the user, a lip movement/gesture produced by the user, a physical contact between the tongue and a palate of the user, an articulator muscle movement produced by the user, and an electrical activity of a brain of the user; wherein the sensor control unit is configurable to: receive a magnetic sensor signal from a magnetic sensors; receive a speech characteristic sensor signal from the speech characteristic sensor; synchronize the magnetic sensor signal with the speech characteristic sensor signal; and transmit the synchronized sensor signal to the computing platform; wherein the computing platform is configurable to: perform a tongue tracking signal processing algorithm, the algorithm including minimizing a cost function that correlates to the measured magnetic flux density and an estimated magnetic flux density at the location of the tracer unit, the location of the tracer unit being defined within a three-dimensional, non-discrete space; determine, based on the algorithm, one or more of a position, orientation, and movement of the tracer unit in real time within the three-dimensinal, non-discrete space; generate a combination of the one or more determined position, determined orientation, and determined movement of the tracer unit with the speech characteristic sensor signal; and transmit the combination to the feedback system; and wherein the feedback system is configurable to provide assistive speech-related feedback to the user in real time, based on the combination, wherein the assistive speech-related feedback is selected from the group consisting of a representation of temporally and spatially continuous tracking of the user's tongue movement during speech of a target phoneme within the three-dimensional non-discrete space, an interactive game to quantify and monitor the user's progress, and vibrotactile biofeedback comparing speech of the user to correct speech of a target phoneme. | 1. A system for real-time tracking of at least one of a position, orientation, and movement of a tongue of a user during speech comprising: a tracer unit; magnetic sensors; a speech characteristic sensor; a sensor control unit; a computing platform; and a feedback system; wherein the tracer unit is adapted to be non-obstructively affixed at a location on the tongue of the user; wherein the magnetic sensors are configurable to measure a magnetic flux density at the location of the tracer unit, the magnetic sensors in non-obstructive proximity to the tracer unit and mouth of the user; wherein the speech characteristic sensor configurable to detect a speech characteristic selected from the group consisting of sound produced by the user, an air flow produced by the user, a lip movement/gesture produced by the user, a physical contact between the tongue and a palate of the user, an articulator muscle movement produced by the user, and an electrical activity of a brain of the user; wherein the sensor control unit is configurable to: receive a magnetic sensor signal from a magnetic sensors; receive a speech characteristic sensor signal from the speech characteristic sensor; synchronize the magnetic sensor signal with the speech characteristic sensor signal; and transmit the synchronized sensor signal to the computing platform; wherein the computing platform is configurable to: perform a tongue tracking signal processing algorithm, the algorithm including minimizing a cost function that correlates to the measured magnetic flux density and an estimated magnetic flux density at the location of the tracer unit, the location of the tracer unit being defined within a three-dimensional, non-discrete space; determine, based on the algorithm, one or more of a position, orientation, and movement of the tracer unit in real time within the three-dimensinal, non-discrete space; generate a combination of the one or more determined position, determined orientation, and determined movement of the tracer unit with the speech characteristic sensor signal; and transmit the combination to the feedback system; and wherein the feedback system is configurable to provide assistive speech-related feedback to the user in real time, based on the combination, wherein the assistive speech-related feedback is selected from the group consisting of a representation of temporally and spatially continuous tracking of the user's tongue movement during speech of a target phoneme within the three-dimensional non-discrete space, an interactive game to quantify and monitor the user's progress, and vibrotactile biofeedback comparing speech of the user to correct speech of a target phoneme. 2. The system of claim 1 , the tracer unit comprising a magnet. | 0.910765 |
9,363,288 | 1 | 2 | 1. A method for preserving privacy of a domain name related request, comprising: receiving, at a computer, a client computer request for information related to a domain name, wherein the request comprises at least one tokenized string representing the domain name, wherein the tokenized string was tokenized by a first tokenizing authority computer different from the client computer and operatively coupled to the client computer through a network, wherein the tokenized string was tokenized by a tokenizing authority computer at least in part by application of a cryptographic function, wherein the request comprises a request to determine domain name registration availability; comparing, via the computer, the at least one tokenized string to the store of tokenized strings, wherein the tokenized terms have been tokenized by a second tokenizing authority based on a tokenizing function equivalent to a tokenizing function of the first tokenizing authority, wherein the second tokenizing authority computer is different from the client computer and from the store of tokenized strings; determining if the at least one tokenized string is contained in the store of tokenized strings; and returning an indication whether the at least one tokenized string is contained in the store of tokenized strings. | 1. A method for preserving privacy of a domain name related request, comprising: receiving, at a computer, a client computer request for information related to a domain name, wherein the request comprises at least one tokenized string representing the domain name, wherein the tokenized string was tokenized by a first tokenizing authority computer different from the client computer and operatively coupled to the client computer through a network, wherein the tokenized string was tokenized by a tokenizing authority computer at least in part by application of a cryptographic function, wherein the request comprises a request to determine domain name registration availability; comparing, via the computer, the at least one tokenized string to the store of tokenized strings, wherein the tokenized terms have been tokenized by a second tokenizing authority based on a tokenizing function equivalent to a tokenizing function of the first tokenizing authority, wherein the second tokenizing authority computer is different from the client computer and from the store of tokenized strings; determining if the at least one tokenized string is contained in the store of tokenized strings; and returning an indication whether the at least one tokenized string is contained in the store of tokenized strings. 2. The method of claim 1 , wherein the information related to a domain name comprises a fully qualified domain name. | 0.597222 |
10,025,860 | 1 | 11 | 1. A system, comprising: at least one processor; a memory coupled to the processor through a bus; and a process executed from the memory by the processor causes the at least one processor to retrieve a plurality of citations composed by a plurality of subjects citing a plurality of objects that fit one or more search criteria, determine an influence of each of the subjects and the objects using a citation graph, wherein the citation graph including includes the plurality of citations each describing an opinion of an object by a subject, the citation graph further including nodes or entities that are subjects that have an opinion or make citations and objects cited by citations relative to subjects that have opinions or make citations, determine an expertise of a subject as a measure of the subjects expertise in a topic relative to a larger population of multiple subjects and allow for determination of expertise on any query term in real-time, rank the cited objects of the plurality of citations using the influence and relative expertise of the subjects, and select objects as a search result for a user based on the matching of the objects with the search criteria as well as the relative expertise of the citing subjects. | 1. A system, comprising: at least one processor; a memory coupled to the processor through a bus; and a process executed from the memory by the processor causes the at least one processor to retrieve a plurality of citations composed by a plurality of subjects citing a plurality of objects that fit one or more search criteria, determine an influence of each of the subjects and the objects using a citation graph, wherein the citation graph including includes the plurality of citations each describing an opinion of an object by a subject, the citation graph further including nodes or entities that are subjects that have an opinion or make citations and objects cited by citations relative to subjects that have opinions or make citations, determine an expertise of a subject as a measure of the subjects expertise in a topic relative to a larger population of multiple subjects and allow for determination of expertise on any query term in real-time, rank the cited objects of the plurality of citations using the influence and relative expertise of the subjects, and select objects as a search result for a user based on the matching of the objects with the search criteria as well as the relative expertise of the citing subjects. 11. The system of claim 1 , wherein the process further causes the processor to rank the objects in the search result based on one or more of a ranking function of the citations for the objects matching the search criteria, the influence of the subjects of each matching citation, and the relative expertise on of each of the citing subjects. | 0.657315 |
8,645,137 | 30 | 31 | 30. The system of claim 28 , wherein the processor is further configured to decompose the at least one phoneme-independent spectral feature vector of the input speech signal into at least one content input sequence, and to authenticate the input speech signal if the at least one content input sequence is similar to the at least one content reference sequence. | 30. The system of claim 28 , wherein the processor is further configured to decompose the at least one phoneme-independent spectral feature vector of the input speech signal into at least one content input sequence, and to authenticate the input speech signal if the at least one content input sequence is similar to the at least one content reference sequence. 31. The system of claim 30 , wherein the processor is further configured to determine similarity based on a distance calculated between the at least one content input sequence and the at least one content reference sequence. | 0.5 |
7,813,912 | 11 | 12 | 11. The method of claim 8 , wherein translating instructions of the assembly language representation further comprises creating HDL models of hardware components for the hardware system according to instructions of the assembly language. | 11. The method of claim 8 , wherein translating instructions of the assembly language representation further comprises creating HDL models of hardware components for the hardware system according to instructions of the assembly language. 12. The method of claim 11 , wherein translating instructions of the assembly language representation further comprises creating HDL models of first-in-first-outs that link the HDL models of hardware components for the hardware system according to operands of the instructions of the assembly language representation. | 0.5 |
8,402,005 | 3 | 5 | 3. A method for creating, in response to a single action, a self-extracting file from an associated input file, wherein the associated input file is automatically launched upon execution of the self-extracting file, and wherein a user is not required to separately choose a data compression method, create a compressed archive using the chosen compression method, select an input file to be launched upon decompression of the compressed archive, and create a self-extracting file from the compressed archive, the method comprising: receiving an input file to be used in creating a self-extracting file, wherein the file is one of a plurality of file types; and in response to only a single action, creating a self-extracting file from the input file, wherein the input file is configured to be automatically launched upon execution of the self-extracting file. | 3. A method for creating, in response to a single action, a self-extracting file from an associated input file, wherein the associated input file is automatically launched upon execution of the self-extracting file, and wherein a user is not required to separately choose a data compression method, create a compressed archive using the chosen compression method, select an input file to be launched upon decompression of the compressed archive, and create a self-extracting file from the compressed archive, the method comprising: receiving an input file to be used in creating a self-extracting file, wherein the file is one of a plurality of file types; and in response to only a single action, creating a self-extracting file from the input file, wherein the input file is configured to be automatically launched upon execution of the self-extracting file. 5. The method of claim 3 , wherein the single action is a double-click with a computer pointing device. | 0.718579 |
8,701,008 | 26 | 27 | 26. The method of claim 25 , further comprising: receiving playback instructions; and based on the playback instructions, displaying the synchronized edited multimedia content and multimedia editing objects. | 26. The method of claim 25 , further comprising: receiving playback instructions; and based on the playback instructions, displaying the synchronized edited multimedia content and multimedia editing objects. 27. The method of claim 26 , wherein receiving playback instructions comprises receiving a thumbnail graphic selection. | 0.5 |
10,133,621 | 1 | 3 | 1. A system comprising: one or more processors of a machine; and a memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: accessing, from a machine-readable storage device, a data object representing an investigative issue; causing presentation, on a display of a device, of a user interface configured to receive user search queries and to present search results for each received search query; causing presentation of a set of search results within the user interface in response to receiving a search query; receiving a user selection of one or more filters; filtering the search results in accordance with the one or more filters; receiving a user selection of text included in a particular search result of the set of search results; generating a token that includes the text; identifying additional instances of the token in a remainder of the set of search results; upon receiving a request to present one of the remainder of the set of search results, visually distinguishing the additional instances of the token in the one of the remainder of the set of search results; tracking user activity that includes one or more user actions performed as part of an investigation of the investigatory issue, the one or more user actions including user interactions with the user interface; creating a record of the user activity involving the investigatory issue, the record including the one or more user actions; and linking the record of the user activity with the data object representing the investigative issue, the linking of the record of user activity with the data object including modifying the data object to include a reference to the record of user activity. | 1. A system comprising: one or more processors of a machine; and a memory storing instructions that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: accessing, from a machine-readable storage device, a data object representing an investigative issue; causing presentation, on a display of a device, of a user interface configured to receive user search queries and to present search results for each received search query; causing presentation of a set of search results within the user interface in response to receiving a search query; receiving a user selection of one or more filters; filtering the search results in accordance with the one or more filters; receiving a user selection of text included in a particular search result of the set of search results; generating a token that includes the text; identifying additional instances of the token in a remainder of the set of search results; upon receiving a request to present one of the remainder of the set of search results, visually distinguishing the additional instances of the token in the one of the remainder of the set of search results; tracking user activity that includes one or more user actions performed as part of an investigation of the investigatory issue, the one or more user actions including user interactions with the user interface; creating a record of the user activity involving the investigatory issue, the record including the one or more user actions; and linking the record of the user activity with the data object representing the investigative issue, the linking of the record of user activity with the data object including modifying the data object to include a reference to the record of user activity. 3. The system of claim 1 , wherein the operations further comprise causing presentation of a graphical representation of the user activity within a portion of the user interface, the graphical representation of the user activity including a textual list of the one or more user actions. | 0.637056 |
8,428,944 | 3 | 4 | 3. A method according to claim 2 wherein the compensated speech recognition takes the acoustic difference into account by assuming the second user utterance has an amplified or diminished acoustic difference. | 3. A method according to claim 2 wherein the compensated speech recognition takes the acoustic difference into account by assuming the second user utterance has an amplified or diminished acoustic difference. 4. A method according to claim 3 wherein a browser records the first and second user utterances and sends utterance data, prompt count and a previous utterance reference to an automatic speech recognition engine (ASR) of the speech recognition system and the ASR performs compensated speech recognition when the prompt count indicates that the second user utterance is a repeat utterance. | 0.5 |
8,515,939 | 4 | 6 | 4. The method of claim 1 , wherein the input rule can be a text-based input rule or an element-based input rule. | 4. The method of claim 1 , wherein the input rule can be a text-based input rule or an element-based input rule. 6. The method of claim 4 , wherein the element-based input rule can be an elementary or advanced element-based input rule; wherein the elementary element-based input rule can include one or more of: a combination rule, a comparison rule, a steno rule, a mixture rule, an ownership rule, an execution rule, an XML path-language assessment rule, and a miscellaneous rule; and wherein the advanced element-based input rule can include one or more of: a syntax sequence rule, a head-tail sequence rule, and a sub-map object rule. | 0.537852 |
9,031,894 | 4 | 5 | 4. The method of claim 1 , wherein the first tuple of structured data files comprises a first data file of content values and a second data file of style characteristic related to the content values. | 4. The method of claim 1 , wherein the first tuple of structured data files comprises a first data file of content values and a second data file of style characteristic related to the content values. 5. The method of claim 4 comprising: generating a second tuple of data files for a second structured image based on the expression, wherein the second tuple of data files comprises a third data file of content values and a fourth data file of style characteristics related to the content values; rendering a third structured image from the first data file based on the first structured image and the fourth data file based on the second structured image. | 0.5 |
9,864,781 | 19 | 20 | 19. A computer-implemented method of accessing a digital item stored on at least one of a Network Attached Storage (NAS) device and a Direct Attached Storage (DAS) device, the computer-implemented method comprising: receiving computer-perceptible search inputs from a single user in a computing device comprising memory, storage, and a display, at least one of the computer-perceptible search inputs comprising search terms that are unrelated to a name, original metadata, or content of the stored digital item; determining a similarity of the received computer-perceptible search inputs with one or more previously-stored indicia of computer-perceptible search inputs to the at least one of the NAS and DAS devices from the single user, and that previously led the single user to access the stored digital item based upon: the received computer-perceptible search inputs; prior computer-perceptible search inputs of search terms by the single user; prior accesses of the at least one digital item stored in at least one of the NAS and the DAS devices based upon the prior computer-perceptible search inputs of the search terms; and prior associations of the search terms of the prior computer-perceptible search inputs with prior search results comprising the at least one stored digital item; accessing, over a computer network, the at least one of the NAS and the DAS devices; retrieving the stored digital item responsive to the determined similarity exceeding a predetermined threshold; and presenting the stored digital item to the single user on the display of the computing device. | 19. A computer-implemented method of accessing a digital item stored on at least one of a Network Attached Storage (NAS) device and a Direct Attached Storage (DAS) device, the computer-implemented method comprising: receiving computer-perceptible search inputs from a single user in a computing device comprising memory, storage, and a display, at least one of the computer-perceptible search inputs comprising search terms that are unrelated to a name, original metadata, or content of the stored digital item; determining a similarity of the received computer-perceptible search inputs with one or more previously-stored indicia of computer-perceptible search inputs to the at least one of the NAS and DAS devices from the single user, and that previously led the single user to access the stored digital item based upon: the received computer-perceptible search inputs; prior computer-perceptible search inputs of search terms by the single user; prior accesses of the at least one digital item stored in at least one of the NAS and the DAS devices based upon the prior computer-perceptible search inputs of the search terms; and prior associations of the search terms of the prior computer-perceptible search inputs with prior search results comprising the at least one stored digital item; accessing, over a computer network, the at least one of the NAS and the DAS devices; retrieving the stored digital item responsive to the determined similarity exceeding a predetermined threshold; and presenting the stored digital item to the single user on the display of the computing device. 20. The computer-implemented method of claim 19 , further comprising storing indicia of the received computer-perceptible search inputs. | 0.5 |
10,134,165 | 10 | 14 | 10. In a digital medium environment for distractor removal from an image, a system comprising: a distractor processing system, implemented by one or more computing devices, to remove distractors from the image, the distractor processing system including: a segmentation module implemented at least partially in hardware to form a plurality of segments from the image; a segment prediction module implemented at least partially in hardware to perform operations comprising: calculating a score for each of the plurality of segments that is indicative of a relative likelihood that a respective said segment is considered a distractor within the image, the calculation performed using at least one distractor model trained using machine learning; classifying the plurality of segments as comprising salient objects that are less likely to be considered important to a user and salient objects that are more likely to be considered important to the user based on the calculated scores for the respective segments; outputting the classifications for the plurality of segments; and a distractor removal module implemented at least partially in hardware to modify at least one segment of the plurality of segments based on the classification of the at least one segment. | 10. In a digital medium environment for distractor removal from an image, a system comprising: a distractor processing system, implemented by one or more computing devices, to remove distractors from the image, the distractor processing system including: a segmentation module implemented at least partially in hardware to form a plurality of segments from the image; a segment prediction module implemented at least partially in hardware to perform operations comprising: calculating a score for each of the plurality of segments that is indicative of a relative likelihood that a respective said segment is considered a distractor within the image, the calculation performed using at least one distractor model trained using machine learning; classifying the plurality of segments as comprising salient objects that are less likely to be considered important to a user and salient objects that are more likely to be considered important to the user based on the calculated scores for the respective segments; outputting the classifications for the plurality of segments; and a distractor removal module implemented at least partially in hardware to modify at least one segment of the plurality of segments based on the classification of the at least one segment. 14. A system as described in claim 10 , wherein the system further comprises a distractor model creation module implemented at least partially in hardware to generate the at least one distractor model. | 0.594758 |
8,340,425 | 20 | 23 | 20. An apparatus comprising: a character recognition module including a zoning engine that zones an image of a paginated document to identify text zones and an optical character recognition (OCR) engine that performs character recognition on the text zones to generate textual content corresponding to the paginated document; and a re-zoning engine that identifies new text zones not identified by the zoning engine based on the generated textual content and the image of the paginated document and invokes the OCR engine to perform character recognition at least on the identified new text zones to generate updated textual content corresponding to the paginated document; wherein the character recognition module and the re-zoning engine are embodied by a digital processing device. | 20. An apparatus comprising: a character recognition module including a zoning engine that zones an image of a paginated document to identify text zones and an optical character recognition (OCR) engine that performs character recognition on the text zones to generate textual content corresponding to the paginated document; and a re-zoning engine that identifies new text zones not identified by the zoning engine based on the generated textual content and the image of the paginated document and invokes the OCR engine to perform character recognition at least on the identified new text zones to generate updated textual content corresponding to the paginated document; wherein the character recognition module and the re-zoning engine are embodied by a digital processing device. 23. The apparatus as set forth in claim 20 , wherein the re-zoning engine (i) identifies an incremental sequence in the textual content generated by the first-pass character recognition and (ii) identifies a new sequence element text zone not identified by the zoning engine that has a location corresponding to a missing element of the incremental sequence. | 0.736377 |
9,183,250 | 9 | 10 | 9. The method as recited in claim 1 , further comprising providing the plurality of different categories corresponding to the search results selected most often associated with the search term to the user. | 9. The method as recited in claim 1 , further comprising providing the plurality of different categories corresponding to the search results selected most often associated with the search term to the user. 10. The method as recited in claim 9 , wherein providing the plurality of different categories corresponding to the search results selected most often associated with the search term to the user comprises providing a plurality of meanings that correspond to the search term. | 0.5 |
8,909,655 | 11 | 17 | 11. A system comprising: at least one data processing apparatus programmed to perform operations comprising: determining historical click-through rates over a plurality of time periods for a first search result responsive to a query and for a second search result responsive to the query wherein the first and second search results refer to different respective web pages; calculating click-fractions for one or more of the plurality of time periods based on the determined historical click-through rates of the first and second search results; determining that a particular click-fraction of the calculated click-fractions in a first time period of the plurality of time periods exceeds a minimum change threshold; obtaining search results responsive to the query during a second time period that chronologically follows the plurality of time periods; adjusting a ranking of the first search result in the obtained search results during the second time period. | 11. A system comprising: at least one data processing apparatus programmed to perform operations comprising: determining historical click-through rates over a plurality of time periods for a first search result responsive to a query and for a second search result responsive to the query wherein the first and second search results refer to different respective web pages; calculating click-fractions for one or more of the plurality of time periods based on the determined historical click-through rates of the first and second search results; determining that a particular click-fraction of the calculated click-fractions in a first time period of the plurality of time periods exceeds a minimum change threshold; obtaining search results responsive to the query during a second time period that chronologically follows the plurality of time periods; adjusting a ranking of the first search result in the obtained search results during the second time period. 17. The system of claim 11 wherein the first time period and the second time period are corresponding periods based on a lunar calendar or a Gregorian calendar. | 0.746032 |
8,506,305 | 1 | 7 | 1. A non-transitory machine-readable medium storing instructions for presenting a question item of an electronic learning curriculum, said instructions, when executed by a processor of a computing device, causing said computing device to: (a) retrieve from a data store a question item comprising: textual, visual or auditory subject matter; a query or instruction pertaining to said subject matter; and a representation of a response mechanism for receiving a user response to said query or instruction; (b) present said subject matter, said query or instruction and said response mechanism in a presentation sequence, wherein a presentation duration of each of said subject matter, said query or instruction and said response mechanism in said presentation sequence is controlled by, and is measured on the basis of, user input for advancing through the presentation sequence; (c) based on said user input, determine: a presentation duration of said subject matter by measuring a duration of display of the subject matter; a presentation duration of said query or instruction by measuring a duration of display of the query or instruction; and a presentation duration of said response mechanism by measuring a duration of display of the response mechanism; (d) store indicators of each of said three presentation durations; (e) receive a user response to said query or instruction via said response mechanism; (f) ascertain a response accuracy based on said response and at least one predetermined correct response; (g) determine a completion time for said question item based on one or more of said presentation duration of said subject matter, said presentation duration of said query or instruction and said presentation duration of said response mechanism; and (h) store said response accuracy and said completion time for said current trial, wherein said instructions cause said computing device to present said question item S times by performing (b)-(h) for each of S trials, S being an integer greater than one, and to: (i) calculate an average response accuracy for said question item based on the stored response accuracies of said S trials; (j) calculate an average completion time for said question item based on the stored completion times of only the ones of said S trials in which a correct user response was given; (k) calculate a relative average completion time for said question item based on said average completion time and either one or both of a predetermined minimum completion time for said question item and a predetermined maximum completion time for said question item; and (I) calculate a user competency measure for said question item based on said average response accuracy and said relative average completion time. | 1. A non-transitory machine-readable medium storing instructions for presenting a question item of an electronic learning curriculum, said instructions, when executed by a processor of a computing device, causing said computing device to: (a) retrieve from a data store a question item comprising: textual, visual or auditory subject matter; a query or instruction pertaining to said subject matter; and a representation of a response mechanism for receiving a user response to said query or instruction; (b) present said subject matter, said query or instruction and said response mechanism in a presentation sequence, wherein a presentation duration of each of said subject matter, said query or instruction and said response mechanism in said presentation sequence is controlled by, and is measured on the basis of, user input for advancing through the presentation sequence; (c) based on said user input, determine: a presentation duration of said subject matter by measuring a duration of display of the subject matter; a presentation duration of said query or instruction by measuring a duration of display of the query or instruction; and a presentation duration of said response mechanism by measuring a duration of display of the response mechanism; (d) store indicators of each of said three presentation durations; (e) receive a user response to said query or instruction via said response mechanism; (f) ascertain a response accuracy based on said response and at least one predetermined correct response; (g) determine a completion time for said question item based on one or more of said presentation duration of said subject matter, said presentation duration of said query or instruction and said presentation duration of said response mechanism; and (h) store said response accuracy and said completion time for said current trial, wherein said instructions cause said computing device to present said question item S times by performing (b)-(h) for each of S trials, S being an integer greater than one, and to: (i) calculate an average response accuracy for said question item based on the stored response accuracies of said S trials; (j) calculate an average completion time for said question item based on the stored completion times of only the ones of said S trials in which a correct user response was given; (k) calculate a relative average completion time for said question item based on said average completion time and either one or both of a predetermined minimum completion time for said question item and a predetermined maximum completion time for said question item; and (I) calculate a user competency measure for said question item based on said average response accuracy and said relative average completion time. 7. The machine-readable medium of claim 1 wherein said calculating said relative average completion time comprises computing a difference between one and a quotient, said quotient computed by dividing said average completion time by said predetermined maximum completion time, and exponentiating said difference. | 0.707317 |
4,817,156 | 11 | 12 | 11. A method as in claim 10 wherein step (g) includes the steps of: (m) dividing into two portions the labels generated by an acoustic processor in response to the subsequent speaker uttering part of a sample text; (n) entering the first portion of labels and updated re-parameterized probabilities into a forward-backward algorithm processor and computing counts C.sub.1 and a probability P.sub.1 ; (o) entering the second portion of labels and updated re-parameterized probabilities into a forward-backward algorithm processor and computing counts C.sub.2 and a probability P.sub.2 ; and (p) computing the smoothed label output probabilities according to the expression: ##EQU20## wherein .lambda..sub.m is a selectable weighting factor and wherein A.sub.ij represents a transition from a state i to a state j in a phone machine. | 11. A method as in claim 10 wherein step (g) includes the steps of: (m) dividing into two portions the labels generated by an acoustic processor in response to the subsequent speaker uttering part of a sample text; (n) entering the first portion of labels and updated re-parameterized probabilities into a forward-backward algorithm processor and computing counts C.sub.1 and a probability P.sub.1 ; (o) entering the second portion of labels and updated re-parameterized probabilities into a forward-backward algorithm processor and computing counts C.sub.2 and a probability P.sub.2 ; and (p) computing the smoothed label output probabilities according to the expression: ##EQU20## wherein .lambda..sub.m is a selectable weighting factor and wherein A.sub.ij represents a transition from a state i to a state j in a phone machine. 12. A method as in claim 11 comprising the further step of: (q) selecting .lambda..sub.m according to the expression: ##EQU21## where P.sub.o represents an initial probability and wherein S.sub.m represents an mth class of M classes of transitions. | 0.5 |
9,031,293 | 1 | 14 | 1. A method for determining an emotional state of a user, comprising: extracting features including one or more acoustic features, visual features, linguistic features, physical feature s from signals obtained by one or more sensors with a processor; analyzing the features including the acoustic features, visual features, linguistic features, and physical features with one or more machine learning algorithms implemented on a processor; wherein analyzing the acoustic features, visual features, linguistic features, and physical features includes use of separate machine learning algorithms for the acoustic, visual, linguistic, and physical features; wherein a first machine learning algorithm provides feedback to a second machine learning algorithm in a serial fashion; and extracting an emotional state of the user from analysis of the features including analysis of the acoustic features, visual features, linguistic features, and physical features with the one or more machine learning algorithms. | 1. A method for determining an emotional state of a user, comprising: extracting features including one or more acoustic features, visual features, linguistic features, physical feature s from signals obtained by one or more sensors with a processor; analyzing the features including the acoustic features, visual features, linguistic features, and physical features with one or more machine learning algorithms implemented on a processor; wherein analyzing the acoustic features, visual features, linguistic features, and physical features includes use of separate machine learning algorithms for the acoustic, visual, linguistic, and physical features; wherein a first machine learning algorithm provides feedback to a second machine learning algorithm in a serial fashion; and extracting an emotional state of the user from analysis of the features including analysis of the acoustic features, visual features, linguistic features, and physical features with the one or more machine learning algorithms. 14. The method of claim 1 , wherein the physical features include heart rate, blood pressure, respiration rate, skin moisture, grip an object, depth and pace of breath, serotonin level, epinephrine level, skin moisture level, skin temperature, pressure in hands/fingers/wrist, level of saliva, level of hormones in enzymes in saliva, level of enzymes in saliva, or skin conductance. | 0.582969 |
5,412,804 | 4 | 8 | 4. The method as claimed in claim 2, further comprising the step of parsing said inner and outer query to form a linked data structure including a first node representing said inner query and a second node representing said outer query. | 4. The method as claimed in claim 2, further comprising the step of parsing said inner and outer query to form a linked data structure including a first node representing said inner query and a second node representing said outer query. 8. The method as claimed in claim 4, wherein said linked data structure is hierarchical and includes a multiplicity of nodes descendant from a root node, and said steps of converting are performed upon parent-child pairs of nodes when the child nodes are leaf nodes in said linked data structure. | 0.5 |
8,010,518 | 10 | 11 | 10. The system of claim 9 , wherein the schema for the first data object defines the allowable content or structure of the first data object and the schema for the second data object defines the allowable content or structure of the second data object. | 10. The system of claim 9 , wherein the schema for the first data object defines the allowable content or structure of the first data object and the schema for the second data object defines the allowable content or structure of the second data object. 11. The system of claim 10 , wherein the first and second data objects are XML documents and wherein the schema for the first and second data objects are XML schemas. | 0.5 |
8,862,459 | 1 | 8 | 1. A computer-implemented method for generating an output banner associated with a Chinese language input couplet comprising first and second sentences, the method comprising: identifying a set of related words, each related word being identified based on a number of times that the related word and a word in the input couplet occur at a same position in a couplet corpus, each of the words in the set of related words and the input couplet being in a Chinese language; calculating an association strength between each of the related words in the set of related words and the input couplet; utilizing a computer processor that is a component of a computer to combine related words in the set of related words in a plurality of different combinations to create a set of banner candidates, the related words in the set of related words being combined based on their association strengths; selecting the output banner from the set of banner candidates; and providing an output indicative of the output banner. | 1. A computer-implemented method for generating an output banner associated with a Chinese language input couplet comprising first and second sentences, the method comprising: identifying a set of related words, each related word being identified based on a number of times that the related word and a word in the input couplet occur at a same position in a couplet corpus, each of the words in the set of related words and the input couplet being in a Chinese language; calculating an association strength between each of the related words in the set of related words and the input couplet; utilizing a computer processor that is a component of a computer to combine related words in the set of related words in a plurality of different combinations to create a set of banner candidates, the related words in the set of related words being combined based on their association strengths; selecting the output banner from the set of banner candidates; and providing an output indicative of the output banner. 8. The method of claim 1 , wherein the input couplet comprises first and second scroll sentences. | 0.78821 |
9,626,658 | 5 | 7 | 5. The method of claim 2 , further comprising: parsing the second task that is received subsequent to the first task and identifying the one or more keywords in the second task; and in response to identifying the third one or more keywords, associating the second task with the first task. | 5. The method of claim 2 , further comprising: parsing the second task that is received subsequent to the first task and identifying the one or more keywords in the second task; and in response to identifying the third one or more keywords, associating the second task with the first task. 7. The method of claim 5 , wherein associating the second task with the first task includes determining that the second task is a subtask of the first task based on the one or more keywords in the second task. | 0.507075 |
7,603,353 | 1 | 6 | 1. A computer-implemented method for processing multilingual documents in a document database database using a computer-implemented system comprising a processor and a display operatively coupled to the processor, the method comprising: operating the processor to perform the following generating an initial ranking of retrieved multi-lingual documents using an information retrieval system and based upon a user search query provided by a user; displaying for the user the initial ranking of the retrieved multi-lingual documents; permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved multi-lingual documents; generating respective relevancies of the user-selected vocabulary words in the retrieved multi-lingual documents; generating a re-ranking of the retrieved multi-lingual documents based on the generated respective relevancies of the vocabulary words; and operating the display to display for the user the re-ranking of the multi-lingual documents, and for each multi-lingual document being displayed, also to display its initial ranking. | 1. A computer-implemented method for processing multilingual documents in a document database database using a computer-implemented system comprising a processor and a display operatively coupled to the processor, the method comprising: operating the processor to perform the following generating an initial ranking of retrieved multi-lingual documents using an information retrieval system and based upon a user search query provided by a user; displaying for the user the initial ranking of the retrieved multi-lingual documents; permitting user selection of a plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved multi-lingual documents; generating respective relevancies of the user-selected vocabulary words in the retrieved multi-lingual documents; generating a re-ranking of the retrieved multi-lingual documents based on the generated respective relevancies of the vocabulary words; and operating the display to display for the user the re-ranking of the multi-lingual documents, and for each multi-lingual document being displayed, also to display its initial ranking. 6. A computer-implemented method according to claim 1 further comprising generating the plurality of vocabulary words based upon occurrences thereof in at least some of the retrieved multi-lingual documents before generating the initial ranking of the retrieved documents. | 0.632432 |
9,424,344 | 1 | 4 | 1. An apparatus for performing a natural language search, the apparatus comprising: a processor configured to search an index, said index contains information which references a domain model, using key words from a user's natural language question and the context of the user's question, and to save a plurality of documents obtained in response to the search of the index; the processor further configured to map each of the documents as a node into an object graph, wherein each node is associated with a parent node, except when the node is a root node; the processor further configured to identify the root node of each document; the processor further configured to identify the path of each node from the node to the node's root node, wherein said path comprises a plurality of nodes that connect the node to the root node; the processor further configured to identify a plurality of matching paths, each of said matching paths, wherein each matching path provides an answer to the user's natural language question, each of said plurality of paths that comprises a discrete path of nodes; the processor further configured to filter out paths depending on a set of the user's pre-determined criterion; the processor further configured to rank the remaining paths; and a display configured to display, in response to the filtering and ranking, a selected answer to the user. | 1. An apparatus for performing a natural language search, the apparatus comprising: a processor configured to search an index, said index contains information which references a domain model, using key words from a user's natural language question and the context of the user's question, and to save a plurality of documents obtained in response to the search of the index; the processor further configured to map each of the documents as a node into an object graph, wherein each node is associated with a parent node, except when the node is a root node; the processor further configured to identify the root node of each document; the processor further configured to identify the path of each node from the node to the node's root node, wherein said path comprises a plurality of nodes that connect the node to the root node; the processor further configured to identify a plurality of matching paths, each of said matching paths, wherein each matching path provides an answer to the user's natural language question, each of said plurality of paths that comprises a discrete path of nodes; the processor further configured to filter out paths depending on a set of the user's pre-determined criterion; the processor further configured to rank the remaining paths; and a display configured to display, in response to the filtering and ranking, a selected answer to the user. 4. The apparatus of claim 1 , wherein the each node in the graph has an id number; and each document in the index has an identification number, and the identification numbers of the documents in the graph and in the search index are identical. | 0.5 |
7,669,119 | 12 | 15 | 12. A computer-implemented method, comprising: extracting a first set of data values from a structural graph representation of a first markup language document that includes a datapoint, wherein at least some of the data values correspond to different nodes of said structural graph representation than other data values; extracting a second set of data values from a structural graph representation of a second markup language document that includes the datapoint, wherein at least some of the data values of the second set correspond to different nodes of the structural graph representation of the second markup language document than data values of the second set; and programmatically determining, by execution of program code by a computer, whether a sufficient degree of correlation exists between the first and second sets of data values to use the first and second sets in combination to generate a combined extraction rule for extracting the datapoint from markup language documents; wherein the method comprises generating a first extraction rule based on the first set of data values, generating a second extraction rule based on the second set of data values, and merging the first and second extraction rules to create the combined extraction rule in response to determining that a sufficient degree of correlation exists between the first and second sets of data values, said first and second extraction rules each capable of being applied independently of the other to extract the datapoint. | 12. A computer-implemented method, comprising: extracting a first set of data values from a structural graph representation of a first markup language document that includes a datapoint, wherein at least some of the data values correspond to different nodes of said structural graph representation than other data values; extracting a second set of data values from a structural graph representation of a second markup language document that includes the datapoint, wherein at least some of the data values of the second set correspond to different nodes of the structural graph representation of the second markup language document than data values of the second set; and programmatically determining, by execution of program code by a computer, whether a sufficient degree of correlation exists between the first and second sets of data values to use the first and second sets in combination to generate a combined extraction rule for extracting the datapoint from markup language documents; wherein the method comprises generating a first extraction rule based on the first set of data values, generating a second extraction rule based on the second set of data values, and merging the first and second extraction rules to create the combined extraction rule in response to determining that a sufficient degree of correlation exists between the first and second sets of data values, said first and second extraction rules each capable of being applied independently of the other to extract the datapoint. 15. The method of claim 12 , further comprising, in response to determining that a sufficient degree of correlation exists, merging the first and second sets of data values such that data values not common to the first and second sets are omitted from the combined extraction rule. | 0.589181 |
8,166,017 | 1 | 12 | 1. A computer program product, tangibly embodied on a machine readable medium, the computer program product comprising instructions that, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: identifying a user; and synchronizing a first set of bookmarks stored for the identified user in a server-side bookmark database, with a second set of bookmarks stored in a client-side browser bookmark list, wherein one or more bookmarks in the first set of bookmarks or the second set of bookmarks are associated with ratings of resources, the resources being identified by the one or more bookmarks, and wherein synchronizing the first set of bookmarks and the second set of bookmarks comprises preserving the ratings associated with the one or more bookmarks. | 1. A computer program product, tangibly embodied on a machine readable medium, the computer program product comprising instructions that, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: identifying a user; and synchronizing a first set of bookmarks stored for the identified user in a server-side bookmark database, with a second set of bookmarks stored in a client-side browser bookmark list, wherein one or more bookmarks in the first set of bookmarks or the second set of bookmarks are associated with ratings of resources, the resources being identified by the one or more bookmarks, and wherein synchronizing the first set of bookmarks and the second set of bookmarks comprises preserving the ratings associated with the one or more bookmarks. 12. The computer program product of claim 1 , further comprising instructions that, when executed, cause the data processing apparatus to perform operations comprising: identifying, from amongst several sets of bookmarks stored for the user in the server-side bookmark database, the first set of bookmarks to synchronize with the second set of bookmarks. | 0.623404 |
8,880,520 | 6 | 11 | 6. A system comprising: at least one computing device comprising a memory to store instructions and further comprising one or more processors to execute the instructions to: receive a search query from a search user; classify the search query into at least one query-class from a plurality of query-classes; perform a search using the search query over a plurality of non-trust data sources to obtain a plurality of non-trust search results; selectively perform another search using the search query over a plurality identified trust data sources to obtain a plurality of trust search results, wherein the identified trust data sources include explicit trusted data sources that are trusted specifically by the search user and wherein the non-trust data sources are non-trusted specifically by the search user; categorize the plurality of trust search results based on the search user's respective relationship with each identified trust data source, the search user's respective relationship being one from a group of relationships comprising an explicit trust data source relationship, an implicit trust data source relationship, and another trust data source relationship having a correspondence with a social networking source for which the search user is not a member; determine, based on the at least one query-class for the search query and the trust search results categorization, a number and a position for selectively displaying each of the plurality of trust search results in a rank order; and selectively display the plurality of trust search results distinct from a display of the plurality of non-trust search results, wherein the selectively displayed plurality of trust search results is in accordance with the determination and includes display of information indicating an identified trust data source of each of plurality of trust search results. | 6. A system comprising: at least one computing device comprising a memory to store instructions and further comprising one or more processors to execute the instructions to: receive a search query from a search user; classify the search query into at least one query-class from a plurality of query-classes; perform a search using the search query over a plurality of non-trust data sources to obtain a plurality of non-trust search results; selectively perform another search using the search query over a plurality identified trust data sources to obtain a plurality of trust search results, wherein the identified trust data sources include explicit trusted data sources that are trusted specifically by the search user and wherein the non-trust data sources are non-trusted specifically by the search user; categorize the plurality of trust search results based on the search user's respective relationship with each identified trust data source, the search user's respective relationship being one from a group of relationships comprising an explicit trust data source relationship, an implicit trust data source relationship, and another trust data source relationship having a correspondence with a social networking source for which the search user is not a member; determine, based on the at least one query-class for the search query and the trust search results categorization, a number and a position for selectively displaying each of the plurality of trust search results in a rank order; and selectively display the plurality of trust search results distinct from a display of the plurality of non-trust search results, wherein the selectively displayed plurality of trust search results is in accordance with the determination and includes display of information indicating an identified trust data source of each of plurality of trust search results. 11. The system of claim 6 , wherein the plurality of identified trust data sources comprises at least one of a plurality of social networking websites, or a plurality of messages from at least one of a friend or family member to the search user. | 0.89503 |
9,430,829 | 1 | 2 | 1. A non-transitory computer-readable storage medium storing computer-executable instructions that when executed by a computer control the computer to perform a method for detecting cellular mitosis in a region of cancerous tissue, the method comprising: acquiring an image of cancerous tissue; segmenting the image into a candidate mitosis patch; extracting a set of convolutional neural network (CNN) learned features from the candidate mitosis patch using a CNN; training a CNN classifier using the set of CNN-learned features; generating a CNN classification score by classifying the candidate mitosis patch with the CNN classifier; extracting a set of hand-crafted (HC) features from the candidate mitosis patch; training an HC classifier using the set of HC features; generating an HC classification score by classifying the candidate mitosis patch with the HC classifier; producing a final classification based, at least in part, on both the CNN classification score and the HC classification score; controlling an automated mitotic nuclei detection system to classify the candidate mitosis patch as mitotic or non-mitotic based on the final classification; generating a mitotic count by summing the number of candidate mitosis patches classified as mitotic by the automated mitotic nuclei detection system; and controlling an automated cancer grading system to grade the image using a Bloom-Richardson grade, where the Bloom-Richardson grade is based, at least in part, on the mitotic count, where producing the final classification comprises: comparing the CNN classification score to the HC classification score, and upon determining that the CNN classification score and the HC classification score are not within a threshold range: training a cascaded classifier using a stacked set of features, where the stacked set of features comprises the set of CNN-learned features and the set of HC features; generating a cascaded classification score by classifying the candidate mitosis patch with the cascaded classifier, and producing a final classification, based, at least in part, on a weighted average of the CNN classification score, the HC classification score, and the cascaded classification score, where the final classification indicates the probability that the mitosis patch is mitotic. | 1. A non-transitory computer-readable storage medium storing computer-executable instructions that when executed by a computer control the computer to perform a method for detecting cellular mitosis in a region of cancerous tissue, the method comprising: acquiring an image of cancerous tissue; segmenting the image into a candidate mitosis patch; extracting a set of convolutional neural network (CNN) learned features from the candidate mitosis patch using a CNN; training a CNN classifier using the set of CNN-learned features; generating a CNN classification score by classifying the candidate mitosis patch with the CNN classifier; extracting a set of hand-crafted (HC) features from the candidate mitosis patch; training an HC classifier using the set of HC features; generating an HC classification score by classifying the candidate mitosis patch with the HC classifier; producing a final classification based, at least in part, on both the CNN classification score and the HC classification score; controlling an automated mitotic nuclei detection system to classify the candidate mitosis patch as mitotic or non-mitotic based on the final classification; generating a mitotic count by summing the number of candidate mitosis patches classified as mitotic by the automated mitotic nuclei detection system; and controlling an automated cancer grading system to grade the image using a Bloom-Richardson grade, where the Bloom-Richardson grade is based, at least in part, on the mitotic count, where producing the final classification comprises: comparing the CNN classification score to the HC classification score, and upon determining that the CNN classification score and the HC classification score are not within a threshold range: training a cascaded classifier using a stacked set of features, where the stacked set of features comprises the set of CNN-learned features and the set of HC features; generating a cascaded classification score by classifying the candidate mitosis patch with the cascaded classifier, and producing a final classification, based, at least in part, on a weighted average of the CNN classification score, the HC classification score, and the cascaded classification score, where the final classification indicates the probability that the mitosis patch is mitotic. 2. The non-transitory computer-readable storage medium of claim 1 , where producing the final classification comprises: comparing the CNN classification score to the HC classification score, and upon determining that the CNN classification score and the HC classification score are within a threshold range: producing a final classification, based, at least in part, on the CNN classification score and the HC classification score, where the final classification indicates the probability that the mitosis patch is mitotic. | 0.5 |
10,072,941 | 9 | 10 | 9. The system of claim 7 wherein the conversational narrative comprises at least one implied navigation oriented conversational element wherein the at least one implied navigation oriented conversational element is one of omitted, ambiguous, inaccurate, incomplete, grammatically miss-specified, irrelevant, incorrect, contradictory, misleading or a combination thereof. | 9. The system of claim 7 wherein the conversational narrative comprises at least one implied navigation oriented conversational element wherein the at least one implied navigation oriented conversational element is one of omitted, ambiguous, inaccurate, incomplete, grammatically miss-specified, irrelevant, incorrect, contradictory, misleading or a combination thereof. 10. The system of claim 9 wherein the third logic is further executable by the processor to cause the processor to derive the at least one implied navigation oriented element from a context in which the conversational narrative is occurring wherein the context comprises one of a geographic location, other navigation oriented element, temporal characteristic, or combinations thereof. | 0.51995 |
9,530,070 | 1 | 2 | 1. An apparatus comprising a non-transitory computer readable storage medium storing a program having instructions which when executed by a processor will cause the processor to parse text in complex graphical images, the instructions of the program for: obtaining a series of blocks of text from a complex graphical image along with associated location coordinates, identifying a location within the complex graphical image, and bounding box data, indicating a size for each block of text within the complex graphical image, for each block of the series; generating location scores for each of the series of blocks of text using locations within the complex graphical image such that blocks closest to a lower, right-hand corner receive a location score of 1.0 and blocks closest to an upper, left hand corner receive a location score of 0.0 with interpolation used to generate location scores for those blocks located in between; generating size scores for each of the series of blocks of text using sizes of each of the series of blocks of text such that largest size blocks receive a size score of 1.0 and smallest size blocks receives a size score of 0.0 with interpolation used to generate size scores for those blocks with sizes in between; weighting each location score by multiplying by a location weighting to create a weighted location score; weighting each size score by multiplying by a size weighting to create a weighted size score; linearly summing each of the weighted location score and the weighted size score to derive an overall score for each block of text of the series; identifying a highest score text block associated with a highest overall score as the most likely to be a desired text block; and repeating each instruction above for each page of a multi-page document made up of a series of complex graphical images. | 1. An apparatus comprising a non-transitory computer readable storage medium storing a program having instructions which when executed by a processor will cause the processor to parse text in complex graphical images, the instructions of the program for: obtaining a series of blocks of text from a complex graphical image along with associated location coordinates, identifying a location within the complex graphical image, and bounding box data, indicating a size for each block of text within the complex graphical image, for each block of the series; generating location scores for each of the series of blocks of text using locations within the complex graphical image such that blocks closest to a lower, right-hand corner receive a location score of 1.0 and blocks closest to an upper, left hand corner receive a location score of 0.0 with interpolation used to generate location scores for those blocks located in between; generating size scores for each of the series of blocks of text using sizes of each of the series of blocks of text such that largest size blocks receive a size score of 1.0 and smallest size blocks receives a size score of 0.0 with interpolation used to generate size scores for those blocks with sizes in between; weighting each location score by multiplying by a location weighting to create a weighted location score; weighting each size score by multiplying by a size weighting to create a weighted size score; linearly summing each of the weighted location score and the weighted size score to derive an overall score for each block of text of the series; identifying a highest score text block associated with a highest overall score as the most likely to be a desired text block; and repeating each instruction above for each page of a multi-page document made up of a series of complex graphical images. 2. The apparatus of claim 1 wherein optical character recognition is performed on a complex graphical image in order to obtain the series of blocks of text from the complex graphical image. | 0.890625 |
7,797,674 | 23 | 25 | 23. A computing device for extending a graphical simulation language comprising: a processor for executing: a plurality of domain components, a domain component comprising a plurality of nodes; a plurality of parameterization nodes, a parameterization node being associated with one of the plurality of domain components; one or more partitioning blocks associated with a graphical simulation language for defining each of the plurality of parameterization nodes; and a plurality of parameterization functions distinct from the plurality of parameterization nodes, one of the plurality of parameterization functions being associated with one of the plurality of parameterization nodes, the one of the plurality of parameterization functions specifying parameters associated with a parameterization node that is associated with the one of the plurality of domain components, the one of the plurality of parameterization functions providing the specified parameters to the plurality of nodes associated with the one of the plurality of domain components and the one of the plurality of parameterization functions not providing the specified parameters associated with the parameterization node that is associated with the one of the plurality of domain components to a second domain component. | 23. A computing device for extending a graphical simulation language comprising: a processor for executing: a plurality of domain components, a domain component comprising a plurality of nodes; a plurality of parameterization nodes, a parameterization node being associated with one of the plurality of domain components; one or more partitioning blocks associated with a graphical simulation language for defining each of the plurality of parameterization nodes; and a plurality of parameterization functions distinct from the plurality of parameterization nodes, one of the plurality of parameterization functions being associated with one of the plurality of parameterization nodes, the one of the plurality of parameterization functions specifying parameters associated with a parameterization node that is associated with the one of the plurality of domain components, the one of the plurality of parameterization functions providing the specified parameters to the plurality of nodes associated with the one of the plurality of domain components and the one of the plurality of parameterization functions not providing the specified parameters associated with the parameterization node that is associated with the one of the plurality of domain components to a second domain component. 25. The computing device of claim 23 , wherein the parameterization node is manually configured for use in extending the graphical simulation language. | 0.635266 |
9,940,584 | 16 | 17 | 16. The apparatus of claim 15 , wherein traversing the given path in the ontology comprises: instantiating a source node of the given path with a known fact in the set of known facts; and instantiating an unknown argument of each relationship in the given path based on the at least one candidate answer. | 16. The apparatus of claim 15 , wherein traversing the given path in the ontology comprises: instantiating a source node of the given path with a known fact in the set of known facts; and instantiating an unknown argument of each relationship in the given path based on the at least one candidate answer. 17. The apparatus of claim 16 , wherein instantiating the unknown argument of each relationship in the given path comprises looking up the relationship in a database or knowledge base. | 0.5 |
8,661,041 | 2 | 8 | 2. A semantic-based searching method comprising: receiving an input search query; and generating a search result corresponding to a final search object in response to the input search query using semantic metadata and an associative search structure, wherein the semantic metadata is stored in conformity with a semantic index configuration that includes a feature metadata index including a keyword and an inverted index used to identify a specific object, a semantic entity metadata index to indicate semantic entities corresponding to the keyword, and a semantic relation metadata index to indicate a relation between the semantic entities, and the associative search structure is previously defined to obtain the final search object. | 2. A semantic-based searching method comprising: receiving an input search query; and generating a search result corresponding to a final search object in response to the input search query using semantic metadata and an associative search structure, wherein the semantic metadata is stored in conformity with a semantic index configuration that includes a feature metadata index including a keyword and an inverted index used to identify a specific object, a semantic entity metadata index to indicate semantic entities corresponding to the keyword, and a semantic relation metadata index to indicate a relation between the semantic entities, and the associative search structure is previously defined to obtain the final search object. 8. The semantic-based searching method of claim 2 , wherein the previously defined associative search structure includes a plurality of information items used to obtain the search result and a group of relations between the information items. | 0.5 |
9,495,424 | 1 | 5 | 1. A method comprising: receiving a user-defined parameter for named entity recognition, wherein the user-defined parameter comprises a beginning position and one of a length or an ending position to define a section of a written work on which the named entity recognition is to be performed, wherein an individual position or the length are measured in one of chapters, pages, paragraphs, or words; recognizing, based at least in part on the user-defined parameter, one or more textual strings within the section of the written work, wherein a textual string of the one or more textual strings is associated with a named entity of a plurality of named entities within the portion of the written work; calculating, by one or more hardware processors, a significance value based at least in part on a number of the one or more textual strings; selecting a primary textual string from the one or more textual strings; and providing an ordered list of at least a portion of the plurality of named entities, wherein a position of the primary textual string within the ordered list is based at least in part on the significance value. | 1. A method comprising: receiving a user-defined parameter for named entity recognition, wherein the user-defined parameter comprises a beginning position and one of a length or an ending position to define a section of a written work on which the named entity recognition is to be performed, wherein an individual position or the length are measured in one of chapters, pages, paragraphs, or words; recognizing, based at least in part on the user-defined parameter, one or more textual strings within the section of the written work, wherein a textual string of the one or more textual strings is associated with a named entity of a plurality of named entities within the portion of the written work; calculating, by one or more hardware processors, a significance value based at least in part on a number of the one or more textual strings; selecting a primary textual string from the one or more textual strings; and providing an ordered list of at least a portion of the plurality of named entities, wherein a position of the primary textual string within the ordered list is based at least in part on the significance value. 5. The method of claim 1 , further comprising determining a most frequently occurring textual string of the one or more textual strings, wherein the primary textual string comprises the most frequently occurring textual string. | 0.763048 |
9,443,246 | 1 | 2 | 1. A method comprising: operating a computing device by: displaying on a display of the computing device a graphical user interface, the graphical user interface comprising: a first display object configured to display available states that are capable of being categorized among categories by a user to provide a state categorization, each of the categories corresponding to a respective cost of interruption for the available states that are included in the respective category, a second display object configured to display potential profiles, including respective subsets of the available states categorized among the categories based at least in part on preferences from users other than the user in a community of users, based at least in part on an extent to which categorization of the subsets among the categories in the potential profiles is similar to categorization of one or more of the available states among the categories in the state categorization, and at least one input object configured to receive user input specifying categorization of at least one of the available states among at least one of the categories; selecting a specified category, which is chosen by the user, from the categories to be associated with a specified available state, which is chosen by the user, based at least in part on the specified category being chosen by the user; adding the specified available state to the specified category, based at least in part on the specified available state being chosen by the user, in response to selecting the specified category from the categories to be associated with the specified available state; filtering a set of profiles derived from the community of users based at least in part on the user input to automatically modify the potential profiles displayed in the second display object; and configuring an application based at least in part on a selected profile of the filtered set of profiles. | 1. A method comprising: operating a computing device by: displaying on a display of the computing device a graphical user interface, the graphical user interface comprising: a first display object configured to display available states that are capable of being categorized among categories by a user to provide a state categorization, each of the categories corresponding to a respective cost of interruption for the available states that are included in the respective category, a second display object configured to display potential profiles, including respective subsets of the available states categorized among the categories based at least in part on preferences from users other than the user in a community of users, based at least in part on an extent to which categorization of the subsets among the categories in the potential profiles is similar to categorization of one or more of the available states among the categories in the state categorization, and at least one input object configured to receive user input specifying categorization of at least one of the available states among at least one of the categories; selecting a specified category, which is chosen by the user, from the categories to be associated with a specified available state, which is chosen by the user, based at least in part on the specified category being chosen by the user; adding the specified available state to the specified category, based at least in part on the specified available state being chosen by the user, in response to selecting the specified category from the categories to be associated with the specified available state; filtering a set of profiles derived from the community of users based at least in part on the user input to automatically modify the potential profiles displayed in the second display object; and configuring an application based at least in part on a selected profile of the filtered set of profiles. 2. The method of claim 1 , wherein the second display object comprises a recommendations display of potential profiles determined via a collaborative filter. | 0.59949 |
8,166,032 | 14 | 26 | 14. The method of claim 13 , further comprises: receiving, by the computer, a second query string comprising a second contemporaneous publication representative of the particular topic, the second contemporaneous publication having a second contemporaneous publication date and comprising a second context of a second plurality of publication terms; assessing the sentimentality of the second contemporaneous publication, by the computer, by comparing a representation of the second query string for semantic similarity to the region of sentimental significance in the document sentiment vector space; and quantizing, by the computer, a second sentiment score for the sentimental significance of the second query string to the particular topic based on the semantic similarity of the representation of the second query string to the region of sentimental significance in the document sentiment vector space, wherein the second sentiment score being indicative of the sentimental significance of the second contemporaneous publication toward the particular topic. | 14. The method of claim 13 , further comprises: receiving, by the computer, a second query string comprising a second contemporaneous publication representative of the particular topic, the second contemporaneous publication having a second contemporaneous publication date and comprising a second context of a second plurality of publication terms; assessing the sentimentality of the second contemporaneous publication, by the computer, by comparing a representation of the second query string for semantic similarity to the region of sentimental significance in the document sentiment vector space; and quantizing, by the computer, a second sentiment score for the sentimental significance of the second query string to the particular topic based on the semantic similarity of the representation of the second query string to the region of sentimental significance in the document sentiment vector space, wherein the second sentiment score being indicative of the sentimental significance of the second contemporaneous publication toward the particular topic. 26. The method of claim 14 , further comprises: receiving, by the computer, a global community sentiment score for the contemporaneous publication, the global community sentiment score being indicative of the sentiment of a global community of humans toward the particular topic with respect to the contemporaneous publication; receiving, by the computer, a second global community sentiment score for the second contemporaneous publication, the second global community sentiment score being indicative of the sentiment of the global community of humans toward the particular topic with respect to the second contemporaneous publication; receiving, by the computer, a trusted group sentiment score for the contemporaneous publication, the trusted group sentiment score being indicative of the sentiment of a trusted group of humans toward the particular topic with respect to the contemporaneous publication; receiving, by the computer, a second trusted group sentiment score for the second contemporaneous publication, the second trusted group sentiment score being indicative of the sentiment of the trusted group of humans toward the particular topic with respect to the second contemporaneous publication; finding, by the computer, a cumulative sentiment score for the contemporaneous publication relative to the sentiment score, the trusted group sentiment score and the global community sentiment score; and finding, by the computer, a second cumulative sentiment score for the second contemporaneous publication relative to the second sentiment score, the second trusted group sentiment score, and the second global community sentiment score; receiving, by the computer, a sentiment time decay factor for publications, wherein the sentiment time decay factor reflects a limited timeframe of influence of the publications on the extrinsic metric relative to the publication dates for the publications; finding, by the computer, an age sentiment score for the contemporaneous publication by applying the sentiment time decay factor to the cumulative sentiment score for age relative to the contemporaneous publication date; finding, by the computer, a second age sentiment score for the second contemporaneous publication by applying the sentiment time decay factor to the second cumulative sentiment score for age relative to the second contemporaneous publication date; and sentiment ranking, by the computer, the contemporaneous publication and the second contemporaneous publication based on their respective age sentiment score and second age sentiment score. | 0.5 |
8,935,744 | 8 | 9 | 8. A system for creating a list of trustworthy DNS resolvers comprising: a processing system comprising one or more processors; a communications port for receiving communications from networked devices and for transmitting communications to the networked devices; and a memory storing instructions that, when executed by the processing system, cause the processing system to perform operations comprising: building, at a computer, a resolver profile for a resolver that is operable to send queries to a domain name server, wherein the resolver profile is based on one or more of a top-talker status of the resolver, a normalcy of distribution of domain names queried, or a continuity of distribution of query type, a RD (Recursion Desired bit status, and information related to query traffic at one or more nodes in a distributed domain name server topology; determining that the resolver is trustworthy by applying a policy to the resolver profile; and adding, by the computer, the resolver to a list of trustworthy resolvers based on the determining that the resolver is trustworthy. | 8. A system for creating a list of trustworthy DNS resolvers comprising: a processing system comprising one or more processors; a communications port for receiving communications from networked devices and for transmitting communications to the networked devices; and a memory storing instructions that, when executed by the processing system, cause the processing system to perform operations comprising: building, at a computer, a resolver profile for a resolver that is operable to send queries to a domain name server, wherein the resolver profile is based on one or more of a top-talker status of the resolver, a normalcy of distribution of domain names queried, or a continuity of distribution of query type, a RD (Recursion Desired bit status, and information related to query traffic at one or more nodes in a distributed domain name server topology; determining that the resolver is trustworthy by applying a policy to the resolver profile; and adding, by the computer, the resolver to a list of trustworthy resolvers based on the determining that the resolver is trustworthy. 9. The system of claim 8 , wherein building comprises building a resolver profile based on a continuity of an IP time-to-live variance of queries from the resolver. | 0.791349 |
8,271,509 | 5 | 18 | 5. A customer service system comprising: a communication interface comprising a financial institution's web page accessible to a customer of the financial institution, wherein the communication interface is configured to receive information about a customer-initiated search query, where the search query relates to a financial product; a memory device comprising a database comprising a list of subject matters and respective skill sets corresponding to each of two or more customer service associates of the financial institution, the database further comprising at least one rule wherein the at least one rule relates at least partially to predetermined criteria for automatically displaying on the communication interface accessible to the customer an invitation to chat with one of the two or more customer service associates of the financial institution, and wherein the predetermined criteria relates to whether the customer service associate is capable of answering questions about the financial product and whether the customer service associate is currently available to chat with the customer; and a computer processor operatively coupled to the communication interface and the memory device, wherein the computer processor is configured to automatically without a prompt from the customer to chat: analyze the search query to determine a subject matter and information associated with the customer-initiated search query; compare the subject matter associated with the customer-initiated query to the subject matter list and compare the information associated with the customer-initiated search query with the respective skill set stored for the two or more customer services associates to the at least one rule in the memory device; determine that a customer service associate is skilled in the subject matter related to the customer-initiated search query based at least partially on the comparison of the subject matter associated with the customer-initiated query to the subject matter list and information associated with the customer-initiated search query with the skill set corresponding to each of the two or more customer service associates; and determine whether or not to display on the communication interface accessible to the customer an invitation to initiate a chat between the customer service associate and the customer based at least partially on determining that the customer service associate is skilled in the subject matter related to the customer-initiated search query and that the customer service associate is currently available to chat. | 5. A customer service system comprising: a communication interface comprising a financial institution's web page accessible to a customer of the financial institution, wherein the communication interface is configured to receive information about a customer-initiated search query, where the search query relates to a financial product; a memory device comprising a database comprising a list of subject matters and respective skill sets corresponding to each of two or more customer service associates of the financial institution, the database further comprising at least one rule wherein the at least one rule relates at least partially to predetermined criteria for automatically displaying on the communication interface accessible to the customer an invitation to chat with one of the two or more customer service associates of the financial institution, and wherein the predetermined criteria relates to whether the customer service associate is capable of answering questions about the financial product and whether the customer service associate is currently available to chat with the customer; and a computer processor operatively coupled to the communication interface and the memory device, wherein the computer processor is configured to automatically without a prompt from the customer to chat: analyze the search query to determine a subject matter and information associated with the customer-initiated search query; compare the subject matter associated with the customer-initiated query to the subject matter list and compare the information associated with the customer-initiated search query with the respective skill set stored for the two or more customer services associates to the at least one rule in the memory device; determine that a customer service associate is skilled in the subject matter related to the customer-initiated search query based at least partially on the comparison of the subject matter associated with the customer-initiated query to the subject matter list and information associated with the customer-initiated search query with the skill set corresponding to each of the two or more customer service associates; and determine whether or not to display on the communication interface accessible to the customer an invitation to initiate a chat between the customer service associate and the customer based at least partially on determining that the customer service associate is skilled in the subject matter related to the customer-initiated search query and that the customer service associate is currently available to chat. 18. The system of claim 5 , wherein the computer processor is further configured to initiate a search using the information received about the customer-initiated search query. | 0.700342 |
8,791,905 | 2 | 5 | 2. The method of claim 1 , wherein the number of language objects is a number of second language objects, and the number of linguistic results is a number of second linguistic results, the method further comprising: employing a number of first language objects that each correspond to at least a portion of the ambiguous editing input to generate a number of first linguistic results; and outputting at least one of the first linguistic results. | 2. The method of claim 1 , wherein the number of language objects is a number of second language objects, and the number of linguistic results is a number of second linguistic results, the method further comprising: employing a number of first language objects that each correspond to at least a portion of the ambiguous editing input to generate a number of first linguistic results; and outputting at least one of the first linguistic results. 5. The method of claim 2 , further comprising outputting the at least one of the first linguistic results having appended thereto at least one of the linguistic elements of the at least a portion of the first output. | 0.855228 |
4,656,603 | 4 | 6 | 4. The system of claim 1 wherein said prompts initiated by said computer processor instruct a methodology designer to define points of connection to each icon. | 4. The system of claim 1 wherein said prompts initiated by said computer processor instruct a methodology designer to define points of connection to each icon. 6. The system of claim 4 wherein said prompts instruct a methodology designer to indicate for each connection point, the connector line styles which are permitted to be connected to that point. | 0.81758 |
8,892,479 | 17 | 18 | 17. A device for determining user gestures based on electromyography (EMG) signals derived from EMG sensors, comprising: a plurality of EMG sensors arbitrarily arranged on a user's forearm; a processor for interacting with one or more modules; a signal analysis module configured to obtain samples from one or more of the EMG sensors of EMG signals generated by muscle contractions of a user while the user is performing one or more predefined finger gestures; wherein the signal analysis module further monitors the predefined finger gestures using a secondary input mechanism to verify that correct predefined finger gestures were performed; a feature extraction module configured to extract feature samples from the sampled EMG signals and label the feature samples according to corresponding finger gestures that have been verified as correct by the secondary input mechanism; and a training module configured to train a machine learning model using the labeled feature samples to identify arbitrary finger gestures relative to one or more of the predefined finger gestures performed by the user. | 17. A device for determining user gestures based on electromyography (EMG) signals derived from EMG sensors, comprising: a plurality of EMG sensors arbitrarily arranged on a user's forearm; a processor for interacting with one or more modules; a signal analysis module configured to obtain samples from one or more of the EMG sensors of EMG signals generated by muscle contractions of a user while the user is performing one or more predefined finger gestures; wherein the signal analysis module further monitors the predefined finger gestures using a secondary input mechanism to verify that correct predefined finger gestures were performed; a feature extraction module configured to extract feature samples from the sampled EMG signals and label the feature samples according to corresponding finger gestures that have been verified as correct by the secondary input mechanism; and a training module configured to train a machine learning model using the labeled feature samples to identify arbitrary finger gestures relative to one or more of the predefined finger gestures performed by the user. 18. The device of claim 17 wherein one or more of the predefined finger gestures are performed while the user is maintaining one or more predefined arm positions including, one or more of arm bent, arm extended, palm up, and palm down. | 0.5 |
8,923,630 | 1 | 6 | 1. A data mining method, comprising: receiving a set of multimodal data objects comprising semantically interrelated information of a first type and a second type, each being of a different type selected from the group consisting of image information, audio information, video information, and semantic information; representing at least the first type of information of the multimodal data objects as feature vectors within a feature space comprising the first type of information and the second type of information, and the semantic interrelation between the first type of information and the second type of information; clustering the feature vectors into classified clusters according to at least one semantic clustering criterion by at least one automated processor, to thereby determine a classification of the respective feature vectors; associating data objects with respective members of the set of multimodal data objects by the at least one automated processor, based on the clustering, the associated data objects comprising information of a third type semantically interrelated to the second type of information, selected from the group consisting of images, audio, video and semantic information, wherein the type of information of the third type is distinct from the type of information of the first type; estimating a joint feature representation of the set of multimodal data objects and the associated data objects by the at least one automated processor; optimizing the joint feature representation by the at least one automated processor to provide a structured output space of interdependent objects, based on at least a prediction error criterion, by iteratively solving a dual problem by selectively partitioning data objects into a working set and a non-working set, comprising: moving the data objects in the non-working set that can be moved without changing an objective function to the working set, and moving the data objects in the working set that can be moved with a decrease in the objective function to the non-working set; receiving a query represented according to the first type of information; and identifying data objects from the set of multimodal data objects that correspond to the query by the at least one automated processor, based on at least the structured output space of interdependent multimodal objects. | 1. A data mining method, comprising: receiving a set of multimodal data objects comprising semantically interrelated information of a first type and a second type, each being of a different type selected from the group consisting of image information, audio information, video information, and semantic information; representing at least the first type of information of the multimodal data objects as feature vectors within a feature space comprising the first type of information and the second type of information, and the semantic interrelation between the first type of information and the second type of information; clustering the feature vectors into classified clusters according to at least one semantic clustering criterion by at least one automated processor, to thereby determine a classification of the respective feature vectors; associating data objects with respective members of the set of multimodal data objects by the at least one automated processor, based on the clustering, the associated data objects comprising information of a third type semantically interrelated to the second type of information, selected from the group consisting of images, audio, video and semantic information, wherein the type of information of the third type is distinct from the type of information of the first type; estimating a joint feature representation of the set of multimodal data objects and the associated data objects by the at least one automated processor; optimizing the joint feature representation by the at least one automated processor to provide a structured output space of interdependent objects, based on at least a prediction error criterion, by iteratively solving a dual problem by selectively partitioning data objects into a working set and a non-working set, comprising: moving the data objects in the non-working set that can be moved without changing an objective function to the working set, and moving the data objects in the working set that can be moved with a decrease in the objective function to the non-working set; receiving a query represented according to the first type of information; and identifying data objects from the set of multimodal data objects that correspond to the query by the at least one automated processor, based on at least the structured output space of interdependent multimodal objects. 6. The method according to claim 1 , wherein the multimodal data objects comprise semantic information, image information and audio information. | 0.92623 |
9,852,337 | 14 | 16 | 14. A non-transitory computer readable medium (CRM) storing instructions for assessing similarity of documents, the instructions comprising functionality for: extracting a reference document text from a reference document; extracting an archived document text from an archived document; quantifying the reference document, comprising: tokenizing sentences of the reference document; and vectorizing the tokenized sentences to obtain a reference document text vector for each sentence of the reference document; quantifying the archived document, comprising: tokenizing sentences of the archived document; and vectorizing the tokenized sentences to obtain an archived document text vector for each sentence of the archived document; determining a document similarity value of the quantified reference document and the quantified archived document, comprising: calculating a plurality of vector similarity values for a plurality of combinations of a reference document text vector and an archived document text vector, the calculating including multiplying each of the vector similarity values of the plurality of vector similarity values with a corresponding weight that is determined, based at least in part on a number of skipped tokens; and calculating the document similarity value, comprising a sum of the plurality of vector similarity values. | 14. A non-transitory computer readable medium (CRM) storing instructions for assessing similarity of documents, the instructions comprising functionality for: extracting a reference document text from a reference document; extracting an archived document text from an archived document; quantifying the reference document, comprising: tokenizing sentences of the reference document; and vectorizing the tokenized sentences to obtain a reference document text vector for each sentence of the reference document; quantifying the archived document, comprising: tokenizing sentences of the archived document; and vectorizing the tokenized sentences to obtain an archived document text vector for each sentence of the archived document; determining a document similarity value of the quantified reference document and the quantified archived document, comprising: calculating a plurality of vector similarity values for a plurality of combinations of a reference document text vector and an archived document text vector, the calculating including multiplying each of the vector similarity values of the plurality of vector similarity values with a corresponding weight that is determined, based at least in part on a number of skipped tokens; and calculating the document similarity value, comprising a sum of the plurality of vector similarity values. 16. The non-transitory CRM of claim 14 , wherein vectorizing tokenized sentences of the reference document and of the archived document is performed using a k-skip-n-gram vectorization, wherein skip-grams of a length n with a maximum number of skipped tokens k are generated; and wherein each skip-gram is separately vectorized. | 0.863561 |
9,135,244 | 1 | 14 | 1. A method for transforming an input data stream comprising data that is expressed in a non-linguistic format into a format that can be expressed linguistically in a textual output, the method comprising: accessing a document plan containing one or more messages, wherein messages represent a phrase or a simple sentence and are created in an instance in which the input data stream comprises data that satisfies one or more message requirements; generating a text specification containing one or more phrase specifications that correspond to the one or more messages in the document plan; applying, using a processor, a set of lexicalization rules to each of the one or more messages to populate the one or more phrase specifications, wherein the set of lexicalization rules are specified using a microplanning rule specification language that is configured to hide linguistic complexities from a user and comprise a set of message-level rules and a set of slot-level rules; and realizing the text specification to generate a textual output that linguistically describes at least a portion of the input data stream, wherein the textual output is displayable via a user interface. | 1. A method for transforming an input data stream comprising data that is expressed in a non-linguistic format into a format that can be expressed linguistically in a textual output, the method comprising: accessing a document plan containing one or more messages, wherein messages represent a phrase or a simple sentence and are created in an instance in which the input data stream comprises data that satisfies one or more message requirements; generating a text specification containing one or more phrase specifications that correspond to the one or more messages in the document plan; applying, using a processor, a set of lexicalization rules to each of the one or more messages to populate the one or more phrase specifications, wherein the set of lexicalization rules are specified using a microplanning rule specification language that is configured to hide linguistic complexities from a user and comprise a set of message-level rules and a set of slot-level rules; and realizing the text specification to generate a textual output that linguistically describes at least a portion of the input data stream, wherein the textual output is displayable via a user interface. 14. The method according to claim 1 , further comprising: aggregating at least two phrases specifications of the one or more phrase specifications based on contents of the at least two phrase specifications, properties of the text specification and the set of lexicalization rules that produced the at least two phrase specifications. | 0.562827 |
7,636,700 | 11 | 12 | 11. An object recognition system incorporating swarming domain classifiers as set forth in claim 10 , wherein the domain is a domain selected from a group consisting of an image, space, frequency, time, Doppler shift, time delay, wave length, and phase. | 11. An object recognition system incorporating swarming domain classifiers as set forth in claim 10 , wherein the domain is a domain selected from a group consisting of an image, space, frequency, time, Doppler shift, time delay, wave length, and phase. 12. An object recognition system incorporating swarming domain classifiers as set forth in claim 11 , wherein each agent includes a classifier selected from a group consisting of Haar wavelet, fuzzy symmetry, decision tree, correlators, and a back-propagation neural network classification engine. | 0.5 |
7,873,621 | 3 | 11 | 3. A computer-readable medium having instructions stored thereon, which, when executed by one or more processors, cause the processors to perform operations comprising: receiving a request for an advertisement to embed in a Web page identifying one or more search results, the search results responsive to a user-submitted search query that includes a name of an individual; identifying one or more name-based profiles associated with the name, the name-based profiles including characteristics of persons derived from the name; selecting one or more advertisements based on the characteristics of persons included in the one or more name-based profiles. | 3. A computer-readable medium having instructions stored thereon, which, when executed by one or more processors, cause the processors to perform operations comprising: receiving a request for an advertisement to embed in a Web page identifying one or more search results, the search results responsive to a user-submitted search query that includes a name of an individual; identifying one or more name-based profiles associated with the name, the name-based profiles including characteristics of persons derived from the name; selecting one or more advertisements based on the characteristics of persons included in the one or more name-based profiles. 11. The computer-readable medium of claim 3 , wherein the one or more name-based profiles include one or more etymology profiles associated with the name and the characteristics of persons in the etymology profiles are derived from an etymology of the name. | 0.718818 |
7,580,957 | 5 | 7 | 5. A structured data storage device comprising: a storage means for storing a structured data file having structured data into a first storage medium to be removably attached to the structured data storage device, and store an index file having index information for use to search the structured data into a second storage medium built in the structured data storage device; a detecting means for detecting whether or not the structured data file stored in the first storage medium has been updated by an external device; and an index information generating means for analyzing, when the detecting means detects that the stored structured data file has been updated, the updated structured data file, generate new index information relating to the structured data included in the updated structured data file, and update the index file stored in the second storage medium using the new index information, wherein the structured data has a plurality of data units identically configured with hierarchically structured elements, each data unit comprises a reference element positioned at the top of the respective data units, and one or more search elements positioned below the reference element, the index information comprises a first index component and a second index component, the first index component links together information which identifies the reference element, information which identifies the structured data file having the structured data comprising the identified reference element, information which identifies the position of the identified reference element in the structured data included in the identified structured data file, information which identifies respective search elements positioned below the identified reference element, and content information of the respective search elements, the second index component links together information which identifies respective search elements, content information of the respective search elements, and information which identifies a reference element having the respective search elements, the index information generating means detects a reference element included in the structured data in the updated structured data file, analyzes the updated structured data file by detecting a search element positioned below the detected reference element, and generates the new index information comprising a new first index component and a new second index component, the index information generating means links together, as the new first index component, information which identifies the detected reference element, information which identifies the updated structured data file having the structured data comprising the identified reference element, information which identifies the position of the identified reference element in the structured data included in the identified structured data file, information which identifies the detected search element positioned below the identified reference element, and content information of the detected search element, and the index information generating means links together, as the new second index component, information which identifies the detected search element, content information of the respective search elements, and information which identifies the detected reference element having the respective search elements. | 5. A structured data storage device comprising: a storage means for storing a structured data file having structured data into a first storage medium to be removably attached to the structured data storage device, and store an index file having index information for use to search the structured data into a second storage medium built in the structured data storage device; a detecting means for detecting whether or not the structured data file stored in the first storage medium has been updated by an external device; and an index information generating means for analyzing, when the detecting means detects that the stored structured data file has been updated, the updated structured data file, generate new index information relating to the structured data included in the updated structured data file, and update the index file stored in the second storage medium using the new index information, wherein the structured data has a plurality of data units identically configured with hierarchically structured elements, each data unit comprises a reference element positioned at the top of the respective data units, and one or more search elements positioned below the reference element, the index information comprises a first index component and a second index component, the first index component links together information which identifies the reference element, information which identifies the structured data file having the structured data comprising the identified reference element, information which identifies the position of the identified reference element in the structured data included in the identified structured data file, information which identifies respective search elements positioned below the identified reference element, and content information of the respective search elements, the second index component links together information which identifies respective search elements, content information of the respective search elements, and information which identifies a reference element having the respective search elements, the index information generating means detects a reference element included in the structured data in the updated structured data file, analyzes the updated structured data file by detecting a search element positioned below the detected reference element, and generates the new index information comprising a new first index component and a new second index component, the index information generating means links together, as the new first index component, information which identifies the detected reference element, information which identifies the updated structured data file having the structured data comprising the identified reference element, information which identifies the position of the identified reference element in the structured data included in the identified structured data file, information which identifies the detected search element positioned below the identified reference element, and content information of the detected search element, and the index information generating means links together, as the new second index component, information which identifies the detected search element, content information of the respective search elements, and information which identifies the detected reference element having the respective search elements. 7. The structured data storage device according to claim 5 , further comprising a deletion means for deleting elements of the structured data, in accordance with externally specified elements-to-be-deleted information, wherein the deletion means: specifies a search element of a candidate for deletion, and content information of the search element of the candidate for deletion, in accordance with the externally specified elements-to-be-deleted information; extracts, from the second index component, a pair of information which identifies the specified search element and content information of the specified search element; extracts, from the second index component, information which is associated with the extracted pair and identifies the reference element; extracts, from the first index component, information which identifies the structured data file, the information being associated with the information which identifies the extracted reference element, and information which identifies the position of the reference element; reads the reference element from the structured data file identified by the information which identifies the extracted structured data file and the information which identifies the position of the extracted reference element; deletes at least one of the elements positioned below the read reference element; and causes the storage means to store again the structured data file with the elements already deleted, into the first storage medium, and causes the index information generating means to analyze the structured data file with the elements already deleted to update the index information. | 0.542833 |
7,478,047 | 38 | 44 | 38. A computer readable medium encoding computer readable instructions for controlling a synthetic character that is autonomous and interacts with others in a shared environment, such character having an associated mental state that changes over time at least in part as a function of said mental state, said mental state comprising a dynamic perceptual state that depends on said shared environment, said shared environment including the entities with which the character is interacting, and an action state defining actions to be taken by the character, that cause a processor to perform steps comprising: providing speech data corresponding to at least a part of an intended communication generated by the character; creating modified speech data by modifying, by an automatically determined amount, at least one of the pitch or duration of at least a portion of the speech data, such modification based at least in part on at least a portion of said mental state; and generating speech sounds associated with the character using the modified speech data wherein the mental state is determined at least in part by interaction of the character with others in a shared environment. | 38. A computer readable medium encoding computer readable instructions for controlling a synthetic character that is autonomous and interacts with others in a shared environment, such character having an associated mental state that changes over time at least in part as a function of said mental state, said mental state comprising a dynamic perceptual state that depends on said shared environment, said shared environment including the entities with which the character is interacting, and an action state defining actions to be taken by the character, that cause a processor to perform steps comprising: providing speech data corresponding to at least a part of an intended communication generated by the character; creating modified speech data by modifying, by an automatically determined amount, at least one of the pitch or duration of at least a portion of the speech data, such modification based at least in part on at least a portion of said mental state; and generating speech sounds associated with the character using the modified speech data wherein the mental state is determined at least in part by interaction of the character with others in a shared environment. 44. The computer readable medium of claim 38 wherein said mental state further comprises a defined motivational or goal state. | 0.65 |
8,706,739 | 13 | 14 | 13. The non-transitory computer readable medium of claim 11 , the instructions when executed by the processor further comprising functionality for: selectively augmenting the target OSN user profile tokens with a semantically equivalent addition; and storing the target OSN user profile tokens with the semantically equivalent addition in a data structure that is partitioned based on the plurality of users. | 13. The non-transitory computer readable medium of claim 11 , the instructions when executed by the processor further comprising functionality for: selectively augmenting the target OSN user profile tokens with a semantically equivalent addition; and storing the target OSN user profile tokens with the semantically equivalent addition in a data structure that is partitioned based on the plurality of users. 14. The non-transitory computer readable medium of claim 13 , wherein the data structure is further partitioned based on at least one selected from a group consisting of a class, a type, and a length of the target OSN user profile tokens, wherein the class comprises a key attribute class where the target OSN user profile key token belongs, a derivable attribute class where the target OSN user profile derived token belongs, and a statistical attribute class, and wherein the type comprises an alphabetic type and a numeric type. | 0.5 |
7,870,117 | 28 | 32 | 28. A computer system for constructing a search query to execute a search of a knowledge base, the system comprising: a computer-readable storage medium storing executable software components comprising: a query parser for parsing an input query received from a user conducting the search of the knowledge base into a plurality of sub-components; a search engine for: matching at least one of the plurality of sub-components to concepts represented as nodes in a semantic concept network of the knowledge base that provides an index of a plurality of documents that are target concepts linked to one or more nodes in the network; selecting from the knowledge base a set of matching concepts that match at least part of the sub-components; mapping the matching concepts to a structured set of criteria and criteria values that specify a set of constraints on and scoring parameters for the matching concepts, the criteria and criteria values being linked to nodes of the matching concepts; executing the search of the database to retrieve a set of target concepts as search results constrained by the criteria according to a relationship between the search results and the matching concepts, the search results retrieved by matching nodes of the criteria and criteria values across the network to nodes of the target concepts using transitivity, wherein the search results are scored against each of the matched concepts and the search results are ranked based on the criteria values, the search results including one or more of the documents indexed; and a processor configured to execute the software components stored by the computer-readable storage medium. | 28. A computer system for constructing a search query to execute a search of a knowledge base, the system comprising: a computer-readable storage medium storing executable software components comprising: a query parser for parsing an input query received from a user conducting the search of the knowledge base into a plurality of sub-components; a search engine for: matching at least one of the plurality of sub-components to concepts represented as nodes in a semantic concept network of the knowledge base that provides an index of a plurality of documents that are target concepts linked to one or more nodes in the network; selecting from the knowledge base a set of matching concepts that match at least part of the sub-components; mapping the matching concepts to a structured set of criteria and criteria values that specify a set of constraints on and scoring parameters for the matching concepts, the criteria and criteria values being linked to nodes of the matching concepts; executing the search of the database to retrieve a set of target concepts as search results constrained by the criteria according to a relationship between the search results and the matching concepts, the search results retrieved by matching nodes of the criteria and criteria values across the network to nodes of the target concepts using transitivity, wherein the search results are scored against each of the matched concepts and the search results are ranked based on the criteria values, the search results including one or more of the documents indexed; and a processor configured to execute the software components stored by the computer-readable storage medium. 32. The system of claim 28 , wherein the concept network represents a directed acyclic graph. | 0.906627 |
10,007,868 | 15 | 20 | 15. In a digital medium environment to enable font replacement at a destination device for a document created at a source device, a method implemented by at least one computing device, the method comprising: receiving, by the at least one computing device, a document with an image from a remote computing device, the image including multiple glyphs rendered using a font such that the image represents a visual appearance of the font; inputting, by the at least one computing device, the image including the multiple glyphs to a font visual similarity model trained with machine learning; computing, by the at least one computing device, a font descriptor corresponding to the font responsive to the inputting, the font descriptor including font features derived from the visual appearance of the font by the font visual similarity model; comparing the font descriptor with multiple font descriptors of multiple local fonts to determine a visually similar local font; and displaying the document with the visually similar local font. | 15. In a digital medium environment to enable font replacement at a destination device for a document created at a source device, a method implemented by at least one computing device, the method comprising: receiving, by the at least one computing device, a document with an image from a remote computing device, the image including multiple glyphs rendered using a font such that the image represents a visual appearance of the font; inputting, by the at least one computing device, the image including the multiple glyphs to a font visual similarity model trained with machine learning; computing, by the at least one computing device, a font descriptor corresponding to the font responsive to the inputting, the font descriptor including font features derived from the visual appearance of the font by the font visual similarity model; comparing the font descriptor with multiple font descriptors of multiple local fonts to determine a visually similar local font; and displaying the document with the visually similar local font. 20. The method as described in claim 15 , wherein the comparing comprises: selecting at least one matching font based on the font descriptor; and transmitting to the remote computing device an offer to procure the at least one matching font. | 0.833793 |
5,437,036 | 24 | 27 | 24. A method of providing an application programming interface capable of providing text checking functionality for a plurality of programs, comprising: receiving text from a calling program in to an input buffer that is in communication with the calling program; addressing the text in the input buffer using an input buffer pointer; passing the text from the input buffer to a text checking engine using the input buffer pointer, the test checking engine being addressable by a plurality of programs; requesting the engine to perform a text checking function; using the engine to perform the requested function and produce information responsive to the requested function using a same process context used by the calling program; receiving the responsive information from the engine in a return buffer communicating with the text checking engine; and passing the responsive information from the return buffer to the calling program. | 24. A method of providing an application programming interface capable of providing text checking functionality for a plurality of programs, comprising: receiving text from a calling program in to an input buffer that is in communication with the calling program; addressing the text in the input buffer using an input buffer pointer; passing the text from the input buffer to a text checking engine using the input buffer pointer, the test checking engine being addressable by a plurality of programs; requesting the engine to perform a text checking function; using the engine to perform the requested function and produce information responsive to the requested function using a same process context used by the calling program; receiving the responsive information from the engine in a return buffer communicating with the text checking engine; and passing the responsive information from the return buffer to the calling program. 27. The method of claim 24 further including providing a main dictionary in communication with the engine, the engine employing the main dictionary to perform the requested function. | 0.612766 |
8,571,867 | 8 | 9 | 8. The system of claim 6 , wherein the biometric voice analyzer: determines one or more vocal tract cross-section areas from the feature vector; and determines one or more vocal tract lengths for the one or more vocal tract cross-section areas. | 8. The system of claim 6 , wherein the biometric voice analyzer: determines one or more vocal tract cross-section areas from the feature vector; and determines one or more vocal tract lengths for the one or more vocal tract cross-section areas. 9. The system of claim 8 , wherein the biometric voice analyzer: calculates a variation bounds for producing variation vectors for the feature vectors in the feature matrix; determines a logarithmic distance for the variation vectors; and establishes a threshold based on the logarithmic distance, wherein the threshold is used to determine whether a vocal tract configuration difference for authenticating a user is within a variation bounds. | 0.5 |
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