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8,401,771 | 1 | 14 | 1. A system comprising: an interface component that, upon execution by a computer, collects a portion of annotation data from two or more users, the portion of annotation data comprising at least one of a geographic location and a user specific description of the geographic location; an annotation aggregator that, upon execution by the computer, evaluates annotation data corresponding to the geographic location, creates a point of interest (POI) for the geographic location based upon the evaluation, and associates the geographic location with at least one of an identified location extracted from the two or more users or a universal description extracted from the two or more users; and a POI evaluator that, upon execution by the computer, identifies a popularity ranking for at least one of a created POI or an existing POI, the popularity ranking being computed from a number of times the geographic location is submitted by the two or more users. | 1. A system comprising: an interface component that, upon execution by a computer, collects a portion of annotation data from two or more users, the portion of annotation data comprising at least one of a geographic location and a user specific description of the geographic location; an annotation aggregator that, upon execution by the computer, evaluates annotation data corresponding to the geographic location, creates a point of interest (POI) for the geographic location based upon the evaluation, and associates the geographic location with at least one of an identified location extracted from the two or more users or a universal description extracted from the two or more users; and a POI evaluator that, upon execution by the computer, identifies a popularity ranking for at least one of a created POI or an existing POI, the popularity ranking being computed from a number of times the geographic location is submitted by the two or more users. 14. The system of claim 1 , further comprising a cloud that incorporates at least one of the annotation aggregator, the POI evaluator, or the interface component. | 0.703297 |
7,609,881 | 9 | 10 | 9. An image processing method comprising: using a processor to perform steps of: extracting a plurality of image areas from image data; recognizing positional information of each extracted image area; recognizing at least attributes concerning whether each extracted image area is a filled closed area, wherein the closed area has an inside of which a color has different value from an outside of the closed area, or an unfilled closed area, wherein the closed area has an inside of which a color has same value from an outside of the closed area; producing a file by synthesizing said image areas based on positional information recognized; and setting up an overlaying sequence for each image area in accordance with the recognition result of the attributes, wherein said producing step includes producing file by overlaying said image areas in accordance with the overlaying sequence, which has been set up. | 9. An image processing method comprising: using a processor to perform steps of: extracting a plurality of image areas from image data; recognizing positional information of each extracted image area; recognizing at least attributes concerning whether each extracted image area is a filled closed area, wherein the closed area has an inside of which a color has different value from an outside of the closed area, or an unfilled closed area, wherein the closed area has an inside of which a color has same value from an outside of the closed area; producing a file by synthesizing said image areas based on positional information recognized; and setting up an overlaying sequence for each image area in accordance with the recognition result of the attributes, wherein said producing step includes producing file by overlaying said image areas in accordance with the overlaying sequence, which has been set up. 10. An image processing method according to the claim 9 , wherein said setting up step includes setting up an overlaying sequence to overlay unfilled closed areas in front of filled closed area. | 0.890147 |
8,813,047 | 7 | 14 | 7. The non-transitory computer-readable medium of claim 6 , wherein the YATL statement is selected from the group consisting of: a foreach-match statement, a match-once statement, a match statement, a foreach-element statement, a debug statement, a native statement, a print statement, a log statement, an express “on” statement, an isolated statement, a continue statement, a die statement, an “on” statement, a statement insertion statement, a layout insertion statement, an if statement, a while statement, a do while statement, a for statement, a delete statement, a transform decl statement, a transform use statement, a replace with statement, a return statement, a try catch statement, an either or statement, a fail statement, an on file statement, and a pointer declare statement. | 7. The non-transitory computer-readable medium of claim 6 , wherein the YATL statement is selected from the group consisting of: a foreach-match statement, a match-once statement, a match statement, a foreach-element statement, a debug statement, a native statement, a print statement, a log statement, an express “on” statement, an isolated statement, a continue statement, a die statement, an “on” statement, a statement insertion statement, a layout insertion statement, an if statement, a while statement, a do while statement, a for statement, a delete statement, a transform decl statement, a transform use statement, a replace with statement, a return statement, a try catch statement, an either or statement, a fail statement, an on file statement, and a pointer declare statement. 14. The non-transitory computer-readable medium of claim 7 , wherein the YATL program includes an on-file statement having “on-file” followed by a string literal followed by the compound statement. | 0.771462 |
8,290,822 | 44 | 45 | 44. The computer-implemented system of claim 39 , wherein the at least one server-side processor is further programmed to: analyze at least one product configuration rule to determine whether at least one product attribute of at least one product record is used in evaluating the at least one product configuration rule; create an attribute binary decision diagram (BDD) structure representative of the at least one product attribute of the least one product record when the at least one processor determines that the at least one product attribute is used in evaluating the at least one product configuration rule; and evaluate the attribute BDD structure to further prepare the customized product record. | 44. The computer-implemented system of claim 39 , wherein the at least one server-side processor is further programmed to: analyze at least one product configuration rule to determine whether at least one product attribute of at least one product record is used in evaluating the at least one product configuration rule; create an attribute binary decision diagram (BDD) structure representative of the at least one product attribute of the least one product record when the at least one processor determines that the at least one product attribute is used in evaluating the at least one product configuration rule; and evaluate the attribute BDD structure to further prepare the customized product record. 45. The computer-implemented system of claim 44 , wherein the attribute BDD structure comprises: an offering attribute node representative of a product attribute value selectable by the user based on evaluating the at least one product configuration rule. | 0.89037 |
8,606,735 | 4 | 5 | 4. The user's intention deduction apparatus of claim 1 , wherein the second predictor is further configured to interpret the multimodal information received from the multimodal sensor in association with the predicted part of the user's intention to predict the user's intention. | 4. The user's intention deduction apparatus of claim 1 , wherein the second predictor is further configured to interpret the multimodal information received from the multimodal sensor in association with the predicted part of the user's intention to predict the user's intention. 5. The user's intention deduction apparatus of claim 4 , wherein, in response to the predicted part of the user's intention being an intention of selecting an object displayed on a display screen and voice being input from the multimodal sensor, the second predictor is further configured to interpret the voice in association with the intention of selecting the object to predict the user's intention. | 0.5 |
8,543,382 | 1 | 3 | 1. A computer-executable method of diacritizing a text, the method comprising: storing a Hidden Markov Model in computer memory for establishing a probability for associating a given diacritical mark with a given character of the text; inputting a sequence of individual characters of the text into a computer processor, the computer processor programmed for: analyzing the text to determine whether the text requires at least one diacritical mark, the text including a plurality of characters associated with an Arabic language; converting each character to an ASCII code; feeding each ASCII code in sequence to the Hidden Markov Model; applying an expectation-maximization process to each ASCII code starting at one end of the sequence; transitioning from one diacritical mark to another diacritical mark from a set of diacritical marks for each ASCII code; recording a probability for each diacritical mark when associated with each current ASCII code; changing a state of the Hidden Markov Model based on each probability over regularly spaced periods of time; wherein the Hidden Markov Model transitions from state q i at time t to a state q i at time t+1, where t=1, 2, 3, . . . M; and i, j=1, 2, . . . , N, and where M represents a number of the transitions and N represents a number of the states; wherein a transition probability a ij , representing a probability that diacritical mark q i appears directly after diacritical mark q i , equals an expected number of transitions from state q i to state q i divided by an expected number of transitions from state q i , finalizing a diacritical mark having the highest probability for the current ASCII code; processing each character in the sequence of the text, wherein the Hidden Markov Model bases the probability at least in part on the probability of a diacritical mark applied on one or more preceding characters of the sequence and on a context of the text for determining the probability of a diacritical mark on a given character; generating a sequence of the diacritical marks corresponding to the sequence of characters; matching the sequence of diacritical marks with the text to obtain the diacritized text; and displaying the diacritized text on an output device. | 1. A computer-executable method of diacritizing a text, the method comprising: storing a Hidden Markov Model in computer memory for establishing a probability for associating a given diacritical mark with a given character of the text; inputting a sequence of individual characters of the text into a computer processor, the computer processor programmed for: analyzing the text to determine whether the text requires at least one diacritical mark, the text including a plurality of characters associated with an Arabic language; converting each character to an ASCII code; feeding each ASCII code in sequence to the Hidden Markov Model; applying an expectation-maximization process to each ASCII code starting at one end of the sequence; transitioning from one diacritical mark to another diacritical mark from a set of diacritical marks for each ASCII code; recording a probability for each diacritical mark when associated with each current ASCII code; changing a state of the Hidden Markov Model based on each probability over regularly spaced periods of time; wherein the Hidden Markov Model transitions from state q i at time t to a state q i at time t+1, where t=1, 2, 3, . . . M; and i, j=1, 2, . . . , N, and where M represents a number of the transitions and N represents a number of the states; wherein a transition probability a ij , representing a probability that diacritical mark q i appears directly after diacritical mark q i , equals an expected number of transitions from state q i to state q i divided by an expected number of transitions from state q i , finalizing a diacritical mark having the highest probability for the current ASCII code; processing each character in the sequence of the text, wherein the Hidden Markov Model bases the probability at least in part on the probability of a diacritical mark applied on one or more preceding characters of the sequence and on a context of the text for determining the probability of a diacritical mark on a given character; generating a sequence of the diacritical marks corresponding to the sequence of characters; matching the sequence of diacritical marks with the text to obtain the diacritized text; and displaying the diacritized text on an output device. 3. The computer-executable method of claim 1 further comprising determining the context associated with the text based on at least one diacritical mark applied on a portion of the text. | 0.75974 |
5,530,794 | 15 | 16 | 15. The method of claim 13, further comprising the step of setting the delimiter data bits in the file control block of an accessed file when said accessed file is opened to paste text in the accessed file into the document. | 15. The method of claim 13, further comprising the step of setting the delimiter data bits in the file control block of an accessed file when said accessed file is opened to paste text in the accessed file into the document. 16. The method of claim 15, wherein said accessed file that is opened is a word processing file that includes data stored in it indicating the type of paragraph delimiter used for the text in said word processing file. | 0.572549 |
8,648,863 | 9 | 13 | 9. The method of claim 8 wherein the visual style model is also configured to determine a plurality of output values in response to a plurality of input values of the input pose for the plurality of animation parameters. | 9. The method of claim 8 wherein the visual style model is also configured to determine a plurality of output values in response to a plurality of input values of the input pose for the plurality of animation parameters. 13. The method of claim 9 wherein the visual style model is configured to determine the plurality of output values in response to the input pose and in response to a spectral matching process. | 0.722543 |
7,599,921 | 13 | 17 | 13. An information handling system comprising: one or more processors; a memory accessible by the processors; one or more nonvolatile storage devices accessible by the processors; and a set of instructions stored in the memory, wherein one or more of the processors executes the set of instructions in order to perform actions of: retrieving a candidate name from one of the nonvolatile storage areas; identifying a cultural classification that corresponds to the candidate name; retrieving one or more culture-specific regularization rules corresponding to the cultural classification from one of the nonvolatile storage areas; applying one or more of the culture-specific regularization rules to the candidate name, resulting in a regularized candidate name, wherein the applying further comprises: determining that a first regularization rule included in the one or more culture-specific regularization rules applies to the candidate name; generating a first iteration regularized candidate name by applying the first regularized rule to the candidate name; determining that a second regularization rule included in the one or more culture-specific regularization rules applies to the candidate name; and generating the regularized candidate name by applying the second regularized rule to the first iteration regularized candidate name; and storing the regularized candidate name in one of the nonvolatile storage areas; comparing, by the processor, the regularized candidate name with a regularized query name; determining, by the processor, that the comparison meets a regularization matching threshold, which indicates a potential match between the regularized candidate name and the regularized query name; and in response to determining that comparison meets the regularization matching threshold, providing the candidate name to the user. | 13. An information handling system comprising: one or more processors; a memory accessible by the processors; one or more nonvolatile storage devices accessible by the processors; and a set of instructions stored in the memory, wherein one or more of the processors executes the set of instructions in order to perform actions of: retrieving a candidate name from one of the nonvolatile storage areas; identifying a cultural classification that corresponds to the candidate name; retrieving one or more culture-specific regularization rules corresponding to the cultural classification from one of the nonvolatile storage areas; applying one or more of the culture-specific regularization rules to the candidate name, resulting in a regularized candidate name, wherein the applying further comprises: determining that a first regularization rule included in the one or more culture-specific regularization rules applies to the candidate name; generating a first iteration regularized candidate name by applying the first regularized rule to the candidate name; determining that a second regularization rule included in the one or more culture-specific regularization rules applies to the candidate name; and generating the regularized candidate name by applying the second regularized rule to the first iteration regularized candidate name; and storing the regularized candidate name in one of the nonvolatile storage areas; comparing, by the processor, the regularized candidate name with a regularized query name; determining, by the processor, that the comparison meets a regularization matching threshold, which indicates a potential match between the regularized candidate name and the regularized query name; and in response to determining that comparison meets the regularization matching threshold, providing the candidate name to the user. 17. The information handling system of claim 13 wherein the cultural classification corresponds to an originating culture of the candidate name, and wherein applying the culture-specific regularization rules does not result in the regularized candidate name corresponding to a different originating culture than the candidate name. | 0.615116 |
9,799,227 | 11 | 12 | 11. A computer program product, the computer program product being tangibly embodied on a non-transitory computer-readable storage medium and including instructions that, when executed, are configured to cause at least one processor to: collect, in conjunction with displayed learning context provided by a learning management system (LMS) and based on a protocol format used by the LMS, first learner progression data of a first learner, and second learner progression data of a second learner, the progression collector being further configured to submit each of the first learner progression data and the second learner progression data for processing by the LMS using a learner submission process and in accordance with the protocol format; aggregate the first learner progression data and the second learner progression data into team progression data represented using the protocol format used by the LMS; provide the team progression data to the LMS as virtual learner progression data including submitting a virtual learner in accordance with the learner submission process and the protocol format; receive progression results processed by the LMS for each of the first learner progression data, the second learner progression data, and the virtual learner progression data representing team progression results, receive, from a rendering engine of the LMS, rendered team progression results including first learner progression results, second learner progression results, and virtual learner progression results; render the virtual learner progression results in conjunction with an identification of the virtual learner progression results as the team progression results, within a team-enhanced LMU user interface (UI); and blend rendered results from the rendering engine of the LMS with rendered team dynamics data representing non-content contributions of the first learner and the second learner. | 11. A computer program product, the computer program product being tangibly embodied on a non-transitory computer-readable storage medium and including instructions that, when executed, are configured to cause at least one processor to: collect, in conjunction with displayed learning context provided by a learning management system (LMS) and based on a protocol format used by the LMS, first learner progression data of a first learner, and second learner progression data of a second learner, the progression collector being further configured to submit each of the first learner progression data and the second learner progression data for processing by the LMS using a learner submission process and in accordance with the protocol format; aggregate the first learner progression data and the second learner progression data into team progression data represented using the protocol format used by the LMS; provide the team progression data to the LMS as virtual learner progression data including submitting a virtual learner in accordance with the learner submission process and the protocol format; receive progression results processed by the LMS for each of the first learner progression data, the second learner progression data, and the virtual learner progression data representing team progression results, receive, from a rendering engine of the LMS, rendered team progression results including first learner progression results, second learner progression results, and virtual learner progression results; render the virtual learner progression results in conjunction with an identification of the virtual learner progression results as the team progression results, within a team-enhanced LMU user interface (UI); and blend rendered results from the rendering engine of the LMS with rendered team dynamics data representing non-content contributions of the first learner and the second learner. 12. The computer program product of claim 11 , wherein the instructions, when executed by the at least one processor are further configured to collect the first learner progression data and the second learner progression data from the team-enhanced LMS user-interface (UI). | 0.5 |
7,529,756 | 1 | 2 | 1. A graphical user interface stored on a machine-readable medium for facilitating human interaction with a database of legal documents, the interface comprising: a first interface screen including: a first data window for displaying one or more portions of a first legal document containing one or more citations to other legal documents; and a first control interface adjacent the data window, the first control interface having first user-selectable means for indicating before selection whether the first legal document includes at least one portion having compromised legal authority and for invoking after selection display of a second interface screen, wherein the second interface screen comprises: a second data window for displaying one or more citations to other legal documents that reference the first legal document or other legal documents that the first legal document is otherwise related to; and a second control interface adjacent the second data window, the second control interface having second user-selectable means for affecting the number or type of citations displayed in the second data window; and third user-selectable means for invoking display of a third interface screen, wherein the third interface screen comprises: a third data window for displaying in a first mode one or more headnotes associated with the first legal document and for displaying in a second mode one or more subject-matter classifications associated with the first legal document; and a third control interface adjacent the third data window the third control interface including: fourth user-selectable means for switching the third data window between the first and second modes; fifth user-selectable means for selecting one or more headnotes; and sixth user-selectable means for selecting one or more legal subject-matter classifications; and seventh user-selectable means for re-invoking display of the second control screen, with the second display window responsive to the fifth or sixth user-selectable means to limit display of citations based on the selected headnotes or the selected subject-matter classifications. | 1. A graphical user interface stored on a machine-readable medium for facilitating human interaction with a database of legal documents, the interface comprising: a first interface screen including: a first data window for displaying one or more portions of a first legal document containing one or more citations to other legal documents; and a first control interface adjacent the data window, the first control interface having first user-selectable means for indicating before selection whether the first legal document includes at least one portion having compromised legal authority and for invoking after selection display of a second interface screen, wherein the second interface screen comprises: a second data window for displaying one or more citations to other legal documents that reference the first legal document or other legal documents that the first legal document is otherwise related to; and a second control interface adjacent the second data window, the second control interface having second user-selectable means for affecting the number or type of citations displayed in the second data window; and third user-selectable means for invoking display of a third interface screen, wherein the third interface screen comprises: a third data window for displaying in a first mode one or more headnotes associated with the first legal document and for displaying in a second mode one or more subject-matter classifications associated with the first legal document; and a third control interface adjacent the third data window the third control interface including: fourth user-selectable means for switching the third data window between the first and second modes; fifth user-selectable means for selecting one or more headnotes; and sixth user-selectable means for selecting one or more legal subject-matter classifications; and seventh user-selectable means for re-invoking display of the second control screen, with the second display window responsive to the fifth or sixth user-selectable means to limit display of citations based on the selected headnotes or the selected subject-matter classifications. 2. The graphical user interface of claim 1 , wherein the second control interface further includes a visual indication of the number of citations in the second data window. | 0.717105 |
9,053,061 | 4 | 5 | 4. A client device, comprising: a processor executing a first operating system and a restore manager that when executed by the processor, causes the client device to: receive a user selection for restoring backed up user data to the client device comprising a user selected order for restoring files; receive backed up user data from a server based on the user selection and according to the user selected order, the backed up user data comprising a file and a first file location of the file on a source device having a second operating system; and determine a second file location for the file in the received backed up user data based on the user selection and at least one parameter associated with the client device comprising the first operating system of the client device, responsive to the first operating system being difference from the second operating system, and store the file in the second file location. | 4. A client device, comprising: a processor executing a first operating system and a restore manager that when executed by the processor, causes the client device to: receive a user selection for restoring backed up user data to the client device comprising a user selected order for restoring files; receive backed up user data from a server based on the user selection and according to the user selected order, the backed up user data comprising a file and a first file location of the file on a source device having a second operating system; and determine a second file location for the file in the received backed up user data based on the user selection and at least one parameter associated with the client device comprising the first operating system of the client device, responsive to the first operating system being difference from the second operating system, and store the file in the second file location. 5. The client device of claim 4 , wherein the user selected order includes a file to restore first. | 0.785714 |
7,644,064 | 4 | 8 | 4. A filter engine system comprising: a processor coupled to a memory, the memory configured with instructions for implementing; an optimized filter sub-engine configured to accept an input that conforms to a language and process the input against a filter table associated with the optimized filter sub-engine, wherein the optimized filter sub-engine is configured to process only a subset of terms of the language, wherein the subset of terms of the language does not include all terms of the language, and wherein the language comprises a query language based on eXtensible Markup Language (XML), wherein the query language is XPath; a general filter sub-engine configured to accept the input and process the input against a filter table associated with the general filter sub-engine, wherein the general filter sub-engine is configured to process all terms of the input language; and an analyzer configured to determine whether the input can be processed by the optimized filter sub-engine and, if so, direct the input to the optimized filter sub-engine for processing, or if not, direct the input to the general filter sub-engine for processing. | 4. A filter engine system comprising: a processor coupled to a memory, the memory configured with instructions for implementing; an optimized filter sub-engine configured to accept an input that conforms to a language and process the input against a filter table associated with the optimized filter sub-engine, wherein the optimized filter sub-engine is configured to process only a subset of terms of the language, wherein the subset of terms of the language does not include all terms of the language, and wherein the language comprises a query language based on eXtensible Markup Language (XML), wherein the query language is XPath; a general filter sub-engine configured to accept the input and process the input against a filter table associated with the general filter sub-engine, wherein the general filter sub-engine is configured to process all terms of the input language; and an analyzer configured to determine whether the input can be processed by the optimized filter sub-engine and, if so, direct the input to the optimized filter sub-engine for processing, or if not, direct the input to the general filter sub-engine for processing. 8. The filter engine system as recited in claim 4 , further comprising a sub-expression module that is configured to perform acts comprising: determine whether the input consists of different sub-expressions; in an event the input consists of different sub-expressions, directing each of the different sub-expressions contained in the input to the analyzer, wherein the analyzer is further configured to determine whether each of the different sub-expressions can be processed by the optimized filter sub-engine and to direct each of the different sub-expressions to an appropriate filter sub-engine for processing. | 0.5 |
8,335,680 | 4 | 5 | 4. An electronic apparatus-comprising: a display device; an input unit; a dictionary storage which stores dictionary information that causes an entry word in a first language to correspond to explanatory information in a second language which is a language different from the first language; a reading-kanji correspondence storage which stores reading-kanji correspondence information that causes a kanji character in the second language to correspond to a reading in the second language; a kanji correspondence storage which stores kanji correspondence information that causes a kanji character in the first language to correspond to a kanji character in the second language; a second-language reading input section which takes in a reading in the second language via the input unit; a first language kanji display section which reads a kanji character in the second language corresponding to the reading in the second language input by the second language reading input section from the reading-kanji correspondence information stored in the reading-kanji correspondence storage, then reads a kanji character in the first language corresponding to the kanji character in the second language from the kanji correspondence information stored in the kanji correspondence storage, and performs display control of the read kanji character on the display device; and a dictionary information display section which reads explanatory information that uses a character string including the kanji character in the first language subjected to display control at the first-language kanji display section as an entry word from dictionary information stored in the dictionary storage and performs display control of the explanatory information on the display device; a multiple kanji correspondence storage which stores multiple kanji correspondence information that causes a plurality of kanji characters in the first language to correspond to a plurality of kanji characters in the second language, wherein the first-language kanji display section reads a kanji character in the second language corresponding to the reading in the second language input by the second-language reading input section from the reading-kanji correspondence information stored in the reading kanji correspondence storage and determines whether the read kanji character in the second language is in the plurality of kanji characters included in the multiple kanji correspondence information stored in the multiple kanji correspondence storage, reads the plurality of kanji characters in the first language corresponding to the plurality of kanji characters in the second language from the multiple kanji correspondence information stored in the multiple kanji correspondence storage and performs display control of the read kanji characters on the display device if it has been determined that the kanji character in the second language read from the reading-kanji correspondence information is in the plurality of kanji characters included in the multiple kanji correspondence information stored in the multiple kanji correspondence storage, and reads a kanji character in the first language corresponding to the kanji character in the second language from the kanji correspondence information stored in the kanji correspondence storage and performs display control of the read kanji character on the display device, if it has been determined that the kanji character in the second language read from the reading-kanji correspondence information is not in the plurality of kanji characters included in the multiple kanji correspondence information stored in the multiple kanji correspondence storage. | 4. An electronic apparatus-comprising: a display device; an input unit; a dictionary storage which stores dictionary information that causes an entry word in a first language to correspond to explanatory information in a second language which is a language different from the first language; a reading-kanji correspondence storage which stores reading-kanji correspondence information that causes a kanji character in the second language to correspond to a reading in the second language; a kanji correspondence storage which stores kanji correspondence information that causes a kanji character in the first language to correspond to a kanji character in the second language; a second-language reading input section which takes in a reading in the second language via the input unit; a first language kanji display section which reads a kanji character in the second language corresponding to the reading in the second language input by the second language reading input section from the reading-kanji correspondence information stored in the reading-kanji correspondence storage, then reads a kanji character in the first language corresponding to the kanji character in the second language from the kanji correspondence information stored in the kanji correspondence storage, and performs display control of the read kanji character on the display device; and a dictionary information display section which reads explanatory information that uses a character string including the kanji character in the first language subjected to display control at the first-language kanji display section as an entry word from dictionary information stored in the dictionary storage and performs display control of the explanatory information on the display device; a multiple kanji correspondence storage which stores multiple kanji correspondence information that causes a plurality of kanji characters in the first language to correspond to a plurality of kanji characters in the second language, wherein the first-language kanji display section reads a kanji character in the second language corresponding to the reading in the second language input by the second-language reading input section from the reading-kanji correspondence information stored in the reading kanji correspondence storage and determines whether the read kanji character in the second language is in the plurality of kanji characters included in the multiple kanji correspondence information stored in the multiple kanji correspondence storage, reads the plurality of kanji characters in the first language corresponding to the plurality of kanji characters in the second language from the multiple kanji correspondence information stored in the multiple kanji correspondence storage and performs display control of the read kanji characters on the display device if it has been determined that the kanji character in the second language read from the reading-kanji correspondence information is in the plurality of kanji characters included in the multiple kanji correspondence information stored in the multiple kanji correspondence storage, and reads a kanji character in the first language corresponding to the kanji character in the second language from the kanji correspondence information stored in the kanji correspondence storage and performs display control of the read kanji character on the display device, if it has been determined that the kanji character in the second language read from the reading-kanji correspondence information is not in the plurality of kanji characters included in the multiple kanji correspondence information stored in the multiple kanji correspondence storage. 5. The electronic apparatus according to claim 4 , wherein each of the first language and the second language is any one of Japanese, Korean, and Chinese. | 0.5 |
8,812,602 | 1 | 16 | 1. A method of identifying conversations of a social network system having relevance to a first file, comprising: identifying a plurality of conversations within the social network system, wherein the plurality of conversations each have a relationship with the first file, wherein the social network system provides a platform for storing and sharing conversation, and each conversation includes a conversation and associated information; generating, by a system server, a list of inquiries based on the plurality of conversations, wherein the list of inquiries includes search terms used in a search that identified the first file and the plurality of conversations, thereby establishing the relationship between the first file and the plurality of conversations by text analysis or filtering; providing, by the system server, the list of inquiries to at least one sender of the first file, wherein the sender is provided with write-privilege to the first file; receiving from the at least one sender at least one response to the list of inquiries; selecting a subset of the plurality of conversations based on the at least one response; storing information related to the selected subset of the plurality of conversations for access if the first file is selected; providing, by the system server, the selected subset of the plurality of conversations to a user that selects the first file; and identifying the at least one sender to the user. | 1. A method of identifying conversations of a social network system having relevance to a first file, comprising: identifying a plurality of conversations within the social network system, wherein the plurality of conversations each have a relationship with the first file, wherein the social network system provides a platform for storing and sharing conversation, and each conversation includes a conversation and associated information; generating, by a system server, a list of inquiries based on the plurality of conversations, wherein the list of inquiries includes search terms used in a search that identified the first file and the plurality of conversations, thereby establishing the relationship between the first file and the plurality of conversations by text analysis or filtering; providing, by the system server, the list of inquiries to at least one sender of the first file, wherein the sender is provided with write-privilege to the first file; receiving from the at least one sender at least one response to the list of inquiries; selecting a subset of the plurality of conversations based on the at least one response; storing information related to the selected subset of the plurality of conversations for access if the first file is selected; providing, by the system server, the selected subset of the plurality of conversations to a user that selects the first file; and identifying the at least one sender to the user. 16. The method of claim 1 , wherein each of the plurality of conversations includes a publication date, wherein each of the publication dates is a specific date. | 0.881965 |
10,068,490 | 1 | 6 | 1. A system for improving student learning comprising: learning material having content for presentation to a student; an EEG system configured to measure a cognitive load of the student as the learning material is presented in a learning session; a device configured to measure physiological data of the student as the learning material is presented in the learning session, wherein the data includes at least three of a brain activity of the student, a measurement of the time it takes the student to read the material, a response time of the student to a request or question posed, a correctness of a response by the student, a total time the student has been engaged in learning, a position of gaze of the student and a posture of the student; a cognitive assessment algorithm configured to determine a cognitive state of the student based on the cognitive load and the physiological data; and a learning action algorithm configured to modify a continued presentation of the learning material in real time based on the cognitive state of the student. | 1. A system for improving student learning comprising: learning material having content for presentation to a student; an EEG system configured to measure a cognitive load of the student as the learning material is presented in a learning session; a device configured to measure physiological data of the student as the learning material is presented in the learning session, wherein the data includes at least three of a brain activity of the student, a measurement of the time it takes the student to read the material, a response time of the student to a request or question posed, a correctness of a response by the student, a total time the student has been engaged in learning, a position of gaze of the student and a posture of the student; a cognitive assessment algorithm configured to determine a cognitive state of the student based on the cognitive load and the physiological data; and a learning action algorithm configured to modify a continued presentation of the learning material in real time based on the cognitive state of the student. 6. The system of claim 1 , wherein the data includes each of the brain activity of the student, the correctness of the response by the student, the measurement of the time it takes the student to read the material, the response time of the student to the request or question posed, the total time the student has been engaged in learning, the position of gaze of the student and the posture of the student. | 0.60735 |
8,407,611 | 1 | 5 | 1. A method comprising: defining, in a widget editor, a placeholder widget comprising a roughly drawn sketch, the placeholder widget having a text property; defining, in a GUI editor, a prototype graphical user interface (GUI) comprising an instance of the placeholder widget; presenting the prototype GUI to a user, an appearance of the instance of the placeholder widget based on the text property of the placeholder widget; in response to a user selection of the instance of the placeholder widget, presenting a list of second widgets to the user and receiving a user selection of one of the second widgets; in response to the selection of the selected second widget, replacing the instance of the placeholder widget in the prototype GUI with an instance of the selected second widget and transferring the text property of the placeholder widget to the instance of the selected second widget; and updating the presentation of the prototype GUI using the instance of the selected second widget wherein the widget editor is separate from the GUI editor. | 1. A method comprising: defining, in a widget editor, a placeholder widget comprising a roughly drawn sketch, the placeholder widget having a text property; defining, in a GUI editor, a prototype graphical user interface (GUI) comprising an instance of the placeholder widget; presenting the prototype GUI to a user, an appearance of the instance of the placeholder widget based on the text property of the placeholder widget; in response to a user selection of the instance of the placeholder widget, presenting a list of second widgets to the user and receiving a user selection of one of the second widgets; in response to the selection of the selected second widget, replacing the instance of the placeholder widget in the prototype GUI with an instance of the selected second widget and transferring the text property of the placeholder widget to the instance of the selected second widget; and updating the presentation of the prototype GUI using the instance of the selected second widget wherein the widget editor is separate from the GUI editor. 5. The method of claim 1 , wherein the selected second widget is stored in a memory independently of the placeholder widget that is also stored in the memory. | 0.719858 |
9,372,920 | 6 | 8 | 6. The computer-implemented method of claim 2 , further comprising: identifying a matrix of image relevance vectors; and multiplying the vector of image features values by the matrix of image relevance vectors, wherein each row of the matrix of image relevance vectors corresponds to a respective query term of the set of query terms. | 6. The computer-implemented method of claim 2 , further comprising: identifying a matrix of image relevance vectors; and multiplying the vector of image features values by the matrix of image relevance vectors, wherein each row of the matrix of image relevance vectors corresponds to a respective query term of the set of query terms. 8. The computer-implemented method of claim 6 , further comprising, for each query term, obtaining the weight for the query term based on multiplying the vector of image features values by the matrix of image relevance vectors. | 0.5 |
8,140,362 | 4 | 5 | 4. The method of claim 1 , further comprising defining the first business rules in the first business rule definition file stored in a first business rule configuration file. | 4. The method of claim 1 , further comprising defining the first business rules in the first business rule definition file stored in a first business rule configuration file. 5. The method of claim 4 , further comprising identifying one of the first business rules that is associated with an input data type; and further determining the location of the first business rule definition file that is associated with the identified one of the first business rules. | 0.5 |
9,208,220 | 11 | 13 | 11. One or more computer-readable storage media having stored thereupon computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform acts comprising: parsing a text into one or more words; filtering the one or more words into one or more filtered words prior to classification of the text, the filtering comprising: determining an amount of variation of frequencies of appearance of a word of the one or more words across a plurality of categories associated with a pre-constructed spherical space model, a number of dimensions of the spherical space model being equal to a number of the plurality of categories; and filtering the word based at least in part on whether the amount of variation is less than a first variation threshold and greater than a second variation threshold, the second variation threshold being greater than zero; determining a word vector in the spherical space model for each filtered word of the one or more filtered words; determining a distance between a sum of word vectors of the one or more filtered words and a respective category vector of each category of the plurality of categories, determining the distance including accumulating normalized word frequency values of the one or more words to obtain a normalized word vector sum; and classifying the text into one or more categories based at least in part on the determined distance associated with each category, classifying the text including classifying the text into a category corresponding to a largest component of the normalized word vector sum. | 11. One or more computer-readable storage media having stored thereupon computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform acts comprising: parsing a text into one or more words; filtering the one or more words into one or more filtered words prior to classification of the text, the filtering comprising: determining an amount of variation of frequencies of appearance of a word of the one or more words across a plurality of categories associated with a pre-constructed spherical space model, a number of dimensions of the spherical space model being equal to a number of the plurality of categories; and filtering the word based at least in part on whether the amount of variation is less than a first variation threshold and greater than a second variation threshold, the second variation threshold being greater than zero; determining a word vector in the spherical space model for each filtered word of the one or more filtered words; determining a distance between a sum of word vectors of the one or more filtered words and a respective category vector of each category of the plurality of categories, determining the distance including accumulating normalized word frequency values of the one or more words to obtain a normalized word vector sum; and classifying the text into one or more categories based at least in part on the determined distance associated with each category, classifying the text including classifying the text into a category corresponding to a largest component of the normalized word vector sum. 13. The one or more computer-readable storage media as recited in claim 11 , wherein a word vector of a filtered word comprises one or more normalized word frequency values of the filtered word in respective one or more categories. | 0.676471 |
8,078,614 | 11 | 20 | 11. A method for dynamic Web page performance scoring, comprising the steps of: loading a Web page; accessing said Web page structure in connection with the real time loading, display, and operation of said Web page; collecting information relating to a plurality of Web page performance metrics in connection with the real time loading, display, and operation of said Web page; calculating a performance subscore for each of said metrics with a heuristic mechanism; and using said collected information to calculate at least one interpretable Web page performance score. | 11. A method for dynamic Web page performance scoring, comprising the steps of: loading a Web page; accessing said Web page structure in connection with the real time loading, display, and operation of said Web page; collecting information relating to a plurality of Web page performance metrics in connection with the real time loading, display, and operation of said Web page; calculating a performance subscore for each of said metrics with a heuristic mechanism; and using said collected information to calculate at least one interpretable Web page performance score. 20. The method of claim 11 , wherein said heuristic mechanism uses user data, connection data, and DOM data for generating a first-load and second-load score for a browser. | 0.687273 |
6,052,686 | 20 | 21 | 20. The method of claim 18, wherein the pruning step comprises: identifying broken paths of the composite automaton; and generating the pruned automaton by removing portions of the composite automaton that corresponds only to the broken paths. | 20. The method of claim 18, wherein the pruning step comprises: identifying broken paths of the composite automaton; and generating the pruned automaton by removing portions of the composite automaton that corresponds only to the broken paths. 21. The method of claim 20, wherein the selecting step comprises: forming a hybrid automaton based on a state of the pruned automaton and a schema of the database; simulating the hybrid automaton against the pruned automaton; and selecting the state based on a result of the simulating step. | 0.5 |
9,141,686 | 7 | 10 | 7. Non-transitory computer readable medium comprising logic, the logic, when executed by a processor, operable to: receive unstructured data from a plurality of data sources, the plurality of data sources comprising a competitor database, a vendor database, and a marketing database, wherein the unstructured data relates to a financial risk of an organization and comprises a plurality of text documents, each text document comprising a plurality of groups of words; deconstruct each group of words from the unstructured data into individual words; convert the individual words from each group of words into a plurality of structured forms, each structured form corresponding to a single group of words; determine a numerical value associated with each individual word according to: a number of times the individual word appears in the group of words and an association of the group of words with a risk experienced by an organization, wherein each structured form is a vector that includes each individual word and the numerical value associated with the individual word; compare each structured form to another structured form using a Bayesian inference; categorize the individual words in each structured form into at least one category according to the comparison and the at least one category is selected from a set of categories consisting of organization name, geographical region, organization size, number of employees, number of countries represented, public organization, private organization, regulatory body, industry, and fine amount, the categories indicating the financial risk of the organization; and quantify the individual words in each structured form according to at least the categorization of the individual words by weighting each individual word. | 7. Non-transitory computer readable medium comprising logic, the logic, when executed by a processor, operable to: receive unstructured data from a plurality of data sources, the plurality of data sources comprising a competitor database, a vendor database, and a marketing database, wherein the unstructured data relates to a financial risk of an organization and comprises a plurality of text documents, each text document comprising a plurality of groups of words; deconstruct each group of words from the unstructured data into individual words; convert the individual words from each group of words into a plurality of structured forms, each structured form corresponding to a single group of words; determine a numerical value associated with each individual word according to: a number of times the individual word appears in the group of words and an association of the group of words with a risk experienced by an organization, wherein each structured form is a vector that includes each individual word and the numerical value associated with the individual word; compare each structured form to another structured form using a Bayesian inference; categorize the individual words in each structured form into at least one category according to the comparison and the at least one category is selected from a set of categories consisting of organization name, geographical region, organization size, number of employees, number of countries represented, public organization, private organization, regulatory body, industry, and fine amount, the categories indicating the financial risk of the organization; and quantify the individual words in each structured form according to at least the categorization of the individual words by weighting each individual word. 10. The computer readable medium of claim 7 , wherein the logic is further operable to: determine whether individual words have associated quantifiable data; and link the individual words to quantifiable data. | 0.671384 |
9,734,192 | 12 | 20 | 12. A computer program product embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process, the process comprising: receiving a single database query language statement, the single database query language statement comprising both a lexical portion having one or more lexical terms and a sentiment clause portion, the sentiment clause portion comprising: a sentiment-aware operator corresponding to a particular sentiment sought after, wherein the sentiment-aware operator comprises a first parameter and a second parameter that are both contained within the sentiment-aware operator, the first parameter corresponding to one or more sentiment terms such that a sentiment analysis is performed for the one or more sentiment terms and the second parameter corresponding to a sentiment assessment indication term corresponding to the particular sentiment to be searched for relative to the one or more sentiment terms, wherein at least one of the one or more sentiment terms in the sentiment clause portion differs from the one or more lexical terms in the lexical portion; parsing, by a computer processor, the single database query language statement to identify the one or more lexical terms to be used in a retrieval of documents containing the one or more of the lexical terms; parsing the single database query language statement based at least on the sentiment-aware operator to identify the one or more sentiment terms for performing sentiment analysis and to identify the sentiment assessment indication term that pertains to the particular sentiment relative to the one or more sentiment terms; retrieving the documents that contain at least one of the one or more lexical terms; and after retrieving the documents that contain at least one of the one or more lexical terms, performing the sentiment analysis on the one or more sentiment terms found within the documents to identify the documents that pertain to the particular sentiment based at least in part on the sentiment assessment indication term. | 12. A computer program product embodied in a non-transitory computer readable medium, the computer readable medium having stored thereon a sequence of instructions which, when executed by a processor causes the processor to execute a process, the process comprising: receiving a single database query language statement, the single database query language statement comprising both a lexical portion having one or more lexical terms and a sentiment clause portion, the sentiment clause portion comprising: a sentiment-aware operator corresponding to a particular sentiment sought after, wherein the sentiment-aware operator comprises a first parameter and a second parameter that are both contained within the sentiment-aware operator, the first parameter corresponding to one or more sentiment terms such that a sentiment analysis is performed for the one or more sentiment terms and the second parameter corresponding to a sentiment assessment indication term corresponding to the particular sentiment to be searched for relative to the one or more sentiment terms, wherein at least one of the one or more sentiment terms in the sentiment clause portion differs from the one or more lexical terms in the lexical portion; parsing, by a computer processor, the single database query language statement to identify the one or more lexical terms to be used in a retrieval of documents containing the one or more of the lexical terms; parsing the single database query language statement based at least on the sentiment-aware operator to identify the one or more sentiment terms for performing sentiment analysis and to identify the sentiment assessment indication term that pertains to the particular sentiment relative to the one or more sentiment terms; retrieving the documents that contain at least one of the one or more lexical terms; and after retrieving the documents that contain at least one of the one or more lexical terms, performing the sentiment analysis on the one or more sentiment terms found within the documents to identify the documents that pertain to the particular sentiment based at least in part on the sentiment assessment indication term. 20. The computer program product of claim 12 , wherein parsing the query comprises parsing a sentiment classifier indication. | 0.799679 |
9,734,351 | 1 | 12 | 1. A process for performing computerized employment authorization queries with a federal governmental entity, the process comprising: providing a first database for storing a record for the person; providing an electronic form having at least one variable to be entered; storing the at least one variable in the record in the first database; transmitting the at least one variable to a remote federal government system having a federal government database and employment eligibility information; receiving an indication, from the remote federal government system, that the person corresponding to the at least one variable is legally eligible for employment, the indication based on: the at least one variable sent to the remote federal government system determined to be valid by the remote federal government system; and the at least one variable sent to the remote federal government system subsequently determined to indicate the person is authorized by the remote federal government for employment; providing a first authorization interface for receiving the person's electronic signature, the first authorization interface comprising: a first user interface element for obtaining the person's electronic signature; and a second user interface element for enabling the person to withdraw a certified electronic signature previously entered by the person; receiving data transmitted by a signature server, said data confirming verification by the signature server of the person's electronic signature; displaying an electronic signature authentication receipt of said verification; providing a second authorization interface for receiving a preparer's electronic signature, the second authorization interface comprising: a first preparer interface element for obtaining the preparer's electronic signature via username and password; a second preparer interface element for obtaining an electronic instant signature from the preparer; and a third preparer interface element for calling an account management interface having a first account management interface element for creating an electronic signature account, and a second account management interface element for managing the electronic signature account; providing a third authorization interface for receiving an employer's electronic signature, the third authorization interface comprising: a first employer interface element for obtaining the employer's electronic signature via username and password; a second employer interface element for obtaining an instant signature from the employer; and a third employer interface element for calling the account management interface; and determining an expiration date for legal eligibility for employment of the person based on at least some information stored in the record in the first database. | 1. A process for performing computerized employment authorization queries with a federal governmental entity, the process comprising: providing a first database for storing a record for the person; providing an electronic form having at least one variable to be entered; storing the at least one variable in the record in the first database; transmitting the at least one variable to a remote federal government system having a federal government database and employment eligibility information; receiving an indication, from the remote federal government system, that the person corresponding to the at least one variable is legally eligible for employment, the indication based on: the at least one variable sent to the remote federal government system determined to be valid by the remote federal government system; and the at least one variable sent to the remote federal government system subsequently determined to indicate the person is authorized by the remote federal government for employment; providing a first authorization interface for receiving the person's electronic signature, the first authorization interface comprising: a first user interface element for obtaining the person's electronic signature; and a second user interface element for enabling the person to withdraw a certified electronic signature previously entered by the person; receiving data transmitted by a signature server, said data confirming verification by the signature server of the person's electronic signature; displaying an electronic signature authentication receipt of said verification; providing a second authorization interface for receiving a preparer's electronic signature, the second authorization interface comprising: a first preparer interface element for obtaining the preparer's electronic signature via username and password; a second preparer interface element for obtaining an electronic instant signature from the preparer; and a third preparer interface element for calling an account management interface having a first account management interface element for creating an electronic signature account, and a second account management interface element for managing the electronic signature account; providing a third authorization interface for receiving an employer's electronic signature, the third authorization interface comprising: a first employer interface element for obtaining the employer's electronic signature via username and password; a second employer interface element for obtaining an instant signature from the employer; and a third employer interface element for calling the account management interface; and determining an expiration date for legal eligibility for employment of the person based on at least some information stored in the record in the first database. 12. The process of claim 1 further comprising providing a web-based interface, wherein the electronic form having at least one variable to be entered is accessed via the web-based interface. | 0.75 |
10,154,047 | 16 | 21 | 16. A non-transitory, computer-readable storage medium storing instructions, an execution of which in a computer system causes the computer system to perform operations comprising: receiving event data associated with network activities, wherein the event data comprises machine data; evaluating event data based on a machine learning model utilizing historical data pertaining to evaluations of past events; identifying at least one anomaly automatically determined from machine learning on the event data; identifying at least one threat automatically determined from machine learning on the event data and the identified at least one anomaly, wherein a threat is associated with each identified anomaly that, individually or in combination, triggered the determination of the threat; and upon selection by a user, via a graphical user interface, of an identified threat, generating a kill chain view associated with the threat, wherein the kill chain view includes a plurality of stages, and, for each stage, the kill chain view lists each type of identified anomaly associated with each stage of the kill chain and the number of anomalies of each type, wherein the listing of comprises a link for each anomaly type; upon selection by the user, via a graphical user interface, of the link for a selected anomaly type, generating a listing of all anomalies of the selected type, including a link for each anomaly; upon selection by the user of the link for a selected anomaly, generating a prompt to tag the anomaly for subsequent tracking; and upon receiving input from the user regarding the identified threat based upon the anomalies in the generated kill chain view, providing feedback for training the machine learning model. | 16. A non-transitory, computer-readable storage medium storing instructions, an execution of which in a computer system causes the computer system to perform operations comprising: receiving event data associated with network activities, wherein the event data comprises machine data; evaluating event data based on a machine learning model utilizing historical data pertaining to evaluations of past events; identifying at least one anomaly automatically determined from machine learning on the event data; identifying at least one threat automatically determined from machine learning on the event data and the identified at least one anomaly, wherein a threat is associated with each identified anomaly that, individually or in combination, triggered the determination of the threat; and upon selection by a user, via a graphical user interface, of an identified threat, generating a kill chain view associated with the threat, wherein the kill chain view includes a plurality of stages, and, for each stage, the kill chain view lists each type of identified anomaly associated with each stage of the kill chain and the number of anomalies of each type, wherein the listing of comprises a link for each anomaly type; upon selection by the user, via a graphical user interface, of the link for a selected anomaly type, generating a listing of all anomalies of the selected type, including a link for each anomaly; upon selection by the user of the link for a selected anomaly, generating a prompt to tag the anomaly for subsequent tracking; and upon receiving input from the user regarding the identified threat based upon the anomalies in the generated kill chain view, providing feedback for training the machine learning model. 21. The computer-readable storage medium of claim 16 , wherein each entry in the listing of the at least one anomaly type in the kill chain view comprises a link for each anomaly type, the method further comprising: upon selection by the user, via a graphical user interface, of the link, generating a listing of all anomalies of the selected type. | 0.5 |
8,781,080 | 6 | 7 | 6. The method of claim 1 , wherein generating the one or more identification tags comprises selecting one or more terms from a beginning portion of the text-based representation of the audio message, and wherein the one or more identification tags includes the selected one or more terms. | 6. The method of claim 1 , wherein generating the one or more identification tags comprises selecting one or more terms from a beginning portion of the text-based representation of the audio message, and wherein the one or more identification tags includes the selected one or more terms. 7. The method of claim 6 , wherein the selected one or more terms from the beginning portion of the text-based representation of the audio message are indicative of the subject of the audio message. | 0.5 |
7,898,546 | 13 | 16 | 13. A computer program product comprising a non-transitory computer readable medium having computer code which when implemented on a computer implements a design of a graphics processing unit, comprising: computer program code stored on said non-transitory computer readable medium for generating a front end to receive a class of commands belonging to an abstract machine representation having a set of state variables; computer program code stored on said non-transitory computer readable medium for generating validation logic to validate input commands received by said front end; and computer program code stored on said non-transitory computer readable medium for generating a reduced memory space shadow memory storing a representation of state information smaller in size than a full representation of said set of state variables, said validation logic utilizing said reduced memory space shadow memory to provide state information for validation. | 13. A computer program product comprising a non-transitory computer readable medium having computer code which when implemented on a computer implements a design of a graphics processing unit, comprising: computer program code stored on said non-transitory computer readable medium for generating a front end to receive a class of commands belonging to an abstract machine representation having a set of state variables; computer program code stored on said non-transitory computer readable medium for generating validation logic to validate input commands received by said front end; and computer program code stored on said non-transitory computer readable medium for generating a reduced memory space shadow memory storing a representation of state information smaller in size than a full representation of said set of state variables, said validation logic utilizing said reduced memory space shadow memory to provide state information for validation. 16. The non-transitory computer readable medium of claim 13 , wherein said reduced memory space shadow memory stores a translated version of at least one state variable. | 0.555263 |
10,026,394 | 18 | 20 | 18. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform acts comprising: receiving a first audio signal representing first user speech; identifying, using the first audio signal, a first task and a second task associated with a first domain; identifying, using the first audio signal, a third task associated with a second domain; sending a second audio signal representing a first question associated with the first domain and the second domain; receiving a third audio signal representing second user speech; selecting the first domain based at least in part on the third audio signal; determining, based at least in part on the first task and the second task, at least one additional piece of information to request; based at least in part on determining the at least one additional piece of information, sending a fourth audio signal representing a second question for the at least one additional piece of information; receiving a fifth audio signal representing third user speech; and selecting the first task based at least in part on the fifth audio signal. | 18. One or more non-transitory computer-readable media storing computer-executable instructions that, when executed by one or more processors, cause the one or more processors to perform acts comprising: receiving a first audio signal representing first user speech; identifying, using the first audio signal, a first task and a second task associated with a first domain; identifying, using the first audio signal, a third task associated with a second domain; sending a second audio signal representing a first question associated with the first domain and the second domain; receiving a third audio signal representing second user speech; selecting the first domain based at least in part on the third audio signal; determining, based at least in part on the first task and the second task, at least one additional piece of information to request; based at least in part on determining the at least one additional piece of information, sending a fourth audio signal representing a second question for the at least one additional piece of information; receiving a fifth audio signal representing third user speech; and selecting the first task based at least in part on the fifth audio signal. 20. One or more non-transitory computer-readable media as recited in claim 18 , wherein the second audio signal is configured to be output by a speaker of an electronic device. | 0.74269 |
8,381,148 | 1 | 9 | 1. A computer program product for determining a deadlock condition in a circuit, the computer program product comprising a non-transitory computer-readable storage medium containing computer program code for: receiving a circuit design corresponding to the circuit, the circuit design comprising multiple subsystems that includes a plurality of ports; receiving a transaction definition associated with at least one of the plurality of ports; generating a deadlock property based on the transaction definition; analyzing data flow through the circuit design based on the deadlock property; generating a helper assertion capturing how the data flows through the circuit design, based on analysis from the analyzing step; and checking for an absence of the deadlock condition within the circuit based on the helper assertion. | 1. A computer program product for determining a deadlock condition in a circuit, the computer program product comprising a non-transitory computer-readable storage medium containing computer program code for: receiving a circuit design corresponding to the circuit, the circuit design comprising multiple subsystems that includes a plurality of ports; receiving a transaction definition associated with at least one of the plurality of ports; generating a deadlock property based on the transaction definition; analyzing data flow through the circuit design based on the deadlock property; generating a helper assertion capturing how the data flows through the circuit design, based on analysis from the analyzing step; and checking for an absence of the deadlock condition within the circuit based on the helper assertion. 9. The computer program product of claim 1 , wherein analyzing data flow through the circuit design based on the deadlock property further comprises identifying one or more trackers. | 0.849088 |
7,734,459 | 7 | 8 | 7. The computer-implemented method of claim 6 wherein each of the rules of the set of rules are applied to the dependency structures in a selected order. | 7. The computer-implemented method of claim 6 wherein each of the rules of the set of rules are applied to the dependency structures in a selected order. 8. The computer-implemented method of claim 7 wherein each of the dependency structures comprise a set of unaligned nodes and wherein each of the rules are applied successively to the set of unaligned nodes until a set of aligned nodes is identified, then the nodes of the set of aligned nodes are removed from the set of unaligned nodes and each of the rules of the set of rules is again applied successively to the set of unaligned nodes. | 0.580153 |
9,621,578 | 26 | 34 | 26. A non-transitory computer-readable storage medium having computer-executable instructions which, when executed by one or more computer processors, causes the one or more computer processors to detect a network activity of interest, the computer-executable instructions comprising instructions for: (a) obtaining a plurality of network packets from a network, wherein the obtained plurality of network packets comprises network packets categorized as Transmission Control Protocol (TCP) packets and Internet Protocol (IP) packets, wherein the obtained plurality of network packets include the network activity of interest; (b) creating a combined packet from at least two network packets of the plurality of network packets, wherein creating the combined packet comprises converting, bitwise, content from a portion of a first network packet and a portion of a second network packet into a plurality of integers, wherein the first network packet represents a communication from a first node to a second node, and wherein the second network packet represents a communication from the second node to the first node; (c) obtaining a meta-expression that: comprises a plurality of integers in an order, and corresponds to presence of the network activity of interest in network traffic; determining whether the meta-expression obtained in (c) appears in the combined packet created in (b); and initiating an operation based in response to determining that the meta-expressions obtained in (c) appears in the combined packet created in (b). | 26. A non-transitory computer-readable storage medium having computer-executable instructions which, when executed by one or more computer processors, causes the one or more computer processors to detect a network activity of interest, the computer-executable instructions comprising instructions for: (a) obtaining a plurality of network packets from a network, wherein the obtained plurality of network packets comprises network packets categorized as Transmission Control Protocol (TCP) packets and Internet Protocol (IP) packets, wherein the obtained plurality of network packets include the network activity of interest; (b) creating a combined packet from at least two network packets of the plurality of network packets, wherein creating the combined packet comprises converting, bitwise, content from a portion of a first network packet and a portion of a second network packet into a plurality of integers, wherein the first network packet represents a communication from a first node to a second node, and wherein the second network packet represents a communication from the second node to the first node; (c) obtaining a meta-expression that: comprises a plurality of integers in an order, and corresponds to presence of the network activity of interest in network traffic; determining whether the meta-expression obtained in (c) appears in the combined packet created in (b); and initiating an operation based in response to determining that the meta-expressions obtained in (c) appears in the combined packet created in (b). 34. The non-transitory computer-readable medium of claim 26 , further comprising instructions for: if the plurality of integers of the obtained meta-expression appear in the combined packet in the same order, then initiating the operation. | 0.836077 |
4,679,951 | 17 | 20 | 17. An electronic system for identifying and resolving ambiguities in the selection of single character or two-character symbolic language words, comprising: a keyboard having a plurality of key indicia corresponding to selected features of graphic characters and adapted to produce an identifier representing a character to be typed; file means containing a first list of characters and a second list of permitted character pairings, said characters and pairings being listed in said file by index codes selectable by specified identifiers, whereby a selected identifier will call up the index codes and pairings of all characters having that identifier; first storage means for receiving the index codes and permitted pairings for the identifier of a first character to be typed; second storage means for receiving the index codes for the identifier of a second character in a two-character word to be typed; a matching network for matching the index codes stored in said first storage means with the index codes in said second storage means to produce a list of possible character pairs for a two-character word; selection storage means; means for connecting said selection storage means either to said first storage means to receive and store only the index codes in said first storage means for a single character or to said matching network to receive said list of possible pairs for a two-character word; a comparator connected to said selection storage means for comparing said list of permitted character pairings with said list of possible pairs; significant pair storage means to receive and store character pairs appearing in both said list of permitted pairings and said list of possible pairs; and selector means connected either to said selection storage means to resolve single character ambiguities or to said significant pair storage means to resolve two-character word ambiguities. | 17. An electronic system for identifying and resolving ambiguities in the selection of single character or two-character symbolic language words, comprising: a keyboard having a plurality of key indicia corresponding to selected features of graphic characters and adapted to produce an identifier representing a character to be typed; file means containing a first list of characters and a second list of permitted character pairings, said characters and pairings being listed in said file by index codes selectable by specified identifiers, whereby a selected identifier will call up the index codes and pairings of all characters having that identifier; first storage means for receiving the index codes and permitted pairings for the identifier of a first character to be typed; second storage means for receiving the index codes for the identifier of a second character in a two-character word to be typed; a matching network for matching the index codes stored in said first storage means with the index codes in said second storage means to produce a list of possible character pairs for a two-character word; selection storage means; means for connecting said selection storage means either to said first storage means to receive and store only the index codes in said first storage means for a single character or to said matching network to receive said list of possible pairs for a two-character word; a comparator connected to said selection storage means for comparing said list of permitted character pairings with said list of possible pairs; significant pair storage means to receive and store character pairs appearing in both said list of permitted pairings and said list of possible pairs; and selector means connected either to said selection storage means to resolve single character ambiguities or to said significant pair storage means to resolve two-character word ambiguities. 20. The apparatus of claim 17, wherein said selector means includes: means to selectively display the graphic characters corresponding to the index code pairs stored in said significant pair storage means; and text file means to receive and store the character pair representing the two-character word to be typed. | 0.5 |
9,487,167 | 25 | 27 | 25. The one or more non-transitory computer-readable media of claim 24 , wherein the identified user input comprises at least one of a user gesture. | 25. The one or more non-transitory computer-readable media of claim 24 , wherein the identified user input comprises at least one of a user gesture. 27. The one or more non-transitory computer-readable media of claim 25 , wherein the user gesture is determined based at least in part upon one of: tracking hand movement or determining contact or proximity of a hand or finger to a defined region within the vehicle. | 0.5 |
8,180,834 | 18 | 21 | 18. A computer program product comprising a non-transitory computer useable medium including control logic stored therein, the control logic enabling the filtering of messages received by a user, and the control logic, if executed, causing a processor to perform operations comprising: determining, in a message classification module, a score for a received message by analyzing a plurality of portions of a the body of the received message, wherein each portion in the plurality of portions is scored with a portion score; determining a user-defined authoritative status for the received message; determining whether an address associated with a sender of the received message matches an entry on a positive screening list; and assigning a non-spam user-defined authoritative status for the received message if the address associated with the sender matches an entry on the positive screening list; storing the received message in a quarantine folder if the address associated with the sender does not match an entry on the positive screening list; receiving a filtering status indication for the received message; assigning a non-spam user-defined authoritative status for the received message if the filtering status indication indicates user approval of the message; assigning a spam user-defined authoritative status for the received message if the filtering status indication indicates user disapproval of the message; and automatically training the classification module when the score is inconsistent with the user-defined authoritative status. | 18. A computer program product comprising a non-transitory computer useable medium including control logic stored therein, the control logic enabling the filtering of messages received by a user, and the control logic, if executed, causing a processor to perform operations comprising: determining, in a message classification module, a score for a received message by analyzing a plurality of portions of a the body of the received message, wherein each portion in the plurality of portions is scored with a portion score; determining a user-defined authoritative status for the received message; determining whether an address associated with a sender of the received message matches an entry on a positive screening list; and assigning a non-spam user-defined authoritative status for the received message if the address associated with the sender matches an entry on the positive screening list; storing the received message in a quarantine folder if the address associated with the sender does not match an entry on the positive screening list; receiving a filtering status indication for the received message; assigning a non-spam user-defined authoritative status for the received message if the filtering status indication indicates user approval of the message; assigning a spam user-defined authoritative status for the received message if the filtering status indication indicates user disapproval of the message; and automatically training the classification module when the score is inconsistent with the user-defined authoritative status. 21. The computer program product of claim 18 , wherein the operations further comprise: initiating management of a database associated with the classification module; determining the total number of messages in the database, the total number of non-spam messages in the database, and the total number of spam messages in the database; and removing the oldest messages from the database according to a ratio representative of the ratio of the total number of non-spam messages to the total number of spam messages until a maximum message count is reached. | 0.58841 |
9,952,881 | 1 | 8 | 1. A mobile device comprising a user interface, a communicator, a central processing unit (CPU), and a storage unit storing instructions executable by the CPU, the instructions configured to implement: a first application module configured to receive a first input command from a user through the user interface; a second application module configured to receive a second input command from the user through the user interface; and an assistant interface configured to translate the first input command into a first semantic atom and to transmit the first semantic atom via the communicator to an external server to perform functions at a first external service; the assistant interface further configured to translate the second input command into a second semantic atom and to transmit the second semantic atom via the communicator to the external server to perform functions at a second external service; the storage unit further storing libraries mapping received input commands to semantic atoms, each semantic atom encapsulating digital data specifying a function to be performed, the first and second semantic atoms corresponding to semantic atoms stored by the storage unit. | 1. A mobile device comprising a user interface, a communicator, a central processing unit (CPU), and a storage unit storing instructions executable by the CPU, the instructions configured to implement: a first application module configured to receive a first input command from a user through the user interface; a second application module configured to receive a second input command from the user through the user interface; and an assistant interface configured to translate the first input command into a first semantic atom and to transmit the first semantic atom via the communicator to an external server to perform functions at a first external service; the assistant interface further configured to translate the second input command into a second semantic atom and to transmit the second semantic atom via the communicator to the external server to perform functions at a second external service; the storage unit further storing libraries mapping received input commands to semantic atoms, each semantic atom encapsulating digital data specifying a function to be performed, the first and second semantic atoms corresponding to semantic atoms stored by the storage unit. 8. The mobile device of claim 1 , the first and second semantic atoms being represented in a format comprising at least one of text, YAML, and XML. | 0.724719 |
10,032,461 | 8 | 9 | 8. The apparatus of claim 1 wherein the speech samples of the set of non-reverberating speech samples are represented by parameters for a non-reverberating speech model. | 8. The apparatus of claim 1 wherein the speech samples of the set of non-reverberating speech samples are represented by parameters for a non-reverberating speech model. 9. The apparatus of claim 8 wherein the processor is configured to determine a first reference property for a first speech sample of the set of non-reverberating speech samples from a speech sample signal generated by evaluating the non-reverberating speech model using the parameters for the first speech sample, and to determine the speech similarity indication for a first microphone signal of the plurality of microphone signals in response to a comparison of the property derived from the first microphone signal and the first reference property. | 0.5 |
9,122,950 | 1 | 2 | 1. An enhanced auto-segmentation method comprising: performing, with a processor, atlas-based auto-segmentation on a plurality of points in a subject image using atlas images to generate first data representative of at least one structure in the subject image, wherein performing the atlas-based auto-segmentation includes registering the subject image with the atlas images to map points of the subject image to points of the atlas images; applying, with the processor, a plurality of points in the subject image to a trained classifier to generate second data representative of the at least one structure in the subject image; combining, with the processor, the first data with the second data to generate third data representative of the at least one structure in the subject image; and determining, based on the third data, structure classifications associated with the subject image. | 1. An enhanced auto-segmentation method comprising: performing, with a processor, atlas-based auto-segmentation on a plurality of points in a subject image using atlas images to generate first data representative of at least one structure in the subject image, wherein performing the atlas-based auto-segmentation includes registering the subject image with the atlas images to map points of the subject image to points of the atlas images; applying, with the processor, a plurality of points in the subject image to a trained classifier to generate second data representative of the at least one structure in the subject image; combining, with the processor, the first data with the second data to generate third data representative of the at least one structure in the subject image; and determining, based on the third data, structure classifications associated with the subject image. 2. The method of claim 1 , further comprising: selecting a subset of the points in the subject image; and wherein applying the plurality of points in the subject image to the trained classifier comprises limiting the points of the subject image, that are applied to the trained classifier, to the selected subset. | 0.794889 |
8,005,680 | 1 | 2 | 1. A method in a communication network for personalizing a service, comprising the steps of: generating user dependant language models by a speech recognition system, storing said user dependant language models, making said user dependant language models, and/or a user profile derived from said user dependant language models, available to a software application running in a user's device and/or available to external service providers, for personalizing an aspect of a service unrelated to speech processing, using a microphone of a user end device of said user for gathering ambient speech material outside normal use of said user end device for voice or data communications with external devices, and using said ambient speech material for adapting said user dependant language models. | 1. A method in a communication network for personalizing a service, comprising the steps of: generating user dependant language models by a speech recognition system, storing said user dependant language models, making said user dependant language models, and/or a user profile derived from said user dependant language models, available to a software application running in a user's device and/or available to external service providers, for personalizing an aspect of a service unrelated to speech processing, using a microphone of a user end device of said user for gathering ambient speech material outside normal use of said user end device for voice or data communications with external devices, and using said ambient speech material for adapting said user dependant language models. 2. The method of claim 1 , wherein at least a subset of said user dependant language models is stored locally in a user device and synchronised with user dependant language models stored in a pervasive platform. | 0.776483 |
9,081,813 | 1 | 5 | 1. A computer system implementing a method for creating a terms database and using said terms database for the composition of queries, comprising the steps of: storing terms that are included in at least one first query received in search processes; storing, for at least one of said stored terms, a relation to at least one other said stored term, the relation being generated when both said terms appeared in the same query; received terms submitted within a second query for a search process; searching said terms database for at least one of said stored term that is not included in said second query but is related to at least one term in said second query; automatically modifying said second query by adding at least one of said related terms that is not included in said second query to said second query; automatically submitting said modified query for a search process; and displaying search results of said modified query. | 1. A computer system implementing a method for creating a terms database and using said terms database for the composition of queries, comprising the steps of: storing terms that are included in at least one first query received in search processes; storing, for at least one of said stored terms, a relation to at least one other said stored term, the relation being generated when both said terms appeared in the same query; received terms submitted within a second query for a search process; searching said terms database for at least one of said stored term that is not included in said second query but is related to at least one term in said second query; automatically modifying said second query by adding at least one of said related terms that is not included in said second query to said second query; automatically submitting said modified query for a search process; and displaying search results of said modified query. 5. The computer system of claim 1 whereas said second query is modified using said related terms with their Boolean association. | 0.785953 |
8,751,485 | 4 | 5 | 4. The search result providing system of claim 1 , wherein the exposure priority determining unit is configured to determine the exposure priority based on a query count (QC) denoting a number of inputs of the original word or the one or more allomorphs in the query, and a source from which the original word or the one or more allomorphs are extracted in response to the query. | 4. The search result providing system of claim 1 , wherein the exposure priority determining unit is configured to determine the exposure priority based on a query count (QC) denoting a number of inputs of the original word or the one or more allomorphs in the query, and a source from which the original word or the one or more allomorphs are extracted in response to the query. 5. The search result providing system of claim 4 , wherein the exposure priority determining unit is configured to allocate a weight to the QC according to the source and determine the exposure priority based on the QC allocated with the weight. | 0.519608 |
7,856,475 | 9 | 12 | 9. A system for facilitating communication between a plurality of users, comprising: a hardware processor; a data repository storing a dialogue between the plurality of users using a first communication tool; and a communication engine, executing on the hardware processor, and comprising functionality to: capture a first portion of a dialogue, between the plurality of users on a first communication tool, comprising a first version of a document and a first duration; capture a second portion of the dialogue, between the plurality of users on the first communication tool, comprising a second version of the document and a second duration; determine that a number of document versions in the dialogue exceeds a document version threshold based on the first version and the second version; determine that a frequency of the dialogue exceeds a frequency threshold based on the first duration and the second duration; identify a pre-defined usage pattern that exists prior to the dialogue based on the number of document versions in the dialogue exceeding the document version threshold and the frequency of the dialogue exceeding the frequency threshold; identify a second communication tool associated with the pre-defined usage pattern, wherein the first communication tool and the second communication tool are software applications; inform the plurality of users of the second communication tool for a communication subsequent to the dialogue; switch from the first communication tool to the second communication tool after informing the plurality of users; and generate a summary of the communication subsequent to the dialogue. | 9. A system for facilitating communication between a plurality of users, comprising: a hardware processor; a data repository storing a dialogue between the plurality of users using a first communication tool; and a communication engine, executing on the hardware processor, and comprising functionality to: capture a first portion of a dialogue, between the plurality of users on a first communication tool, comprising a first version of a document and a first duration; capture a second portion of the dialogue, between the plurality of users on the first communication tool, comprising a second version of the document and a second duration; determine that a number of document versions in the dialogue exceeds a document version threshold based on the first version and the second version; determine that a frequency of the dialogue exceeds a frequency threshold based on the first duration and the second duration; identify a pre-defined usage pattern that exists prior to the dialogue based on the number of document versions in the dialogue exceeding the document version threshold and the frequency of the dialogue exceeding the frequency threshold; identify a second communication tool associated with the pre-defined usage pattern, wherein the first communication tool and the second communication tool are software applications; inform the plurality of users of the second communication tool for a communication subsequent to the dialogue; switch from the first communication tool to the second communication tool after informing the plurality of users; and generate a summary of the communication subsequent to the dialogue. 12. The system of claim 9 , wherein the pre-defined usage pattern comprises a time delay pattern between different messages in the dialogue. | 0.686099 |
8,070,163 | 1 | 3 | 1. A method comprising the steps of: obtaining a set of multilingual tiles, each tile bearing a first character of a first language and also bearing a second character of a second language, in which the second character is not a transliteration of the first character; and positioning selected tiles to form words; and wherein at least one of the following is also present: a player gains points for words made in a language that is not the player's native language; a player loses points for words made in a language that is the player's native language; extra points are awarded if tiles form multiple words in multiple languages; or extra points are awarded if tiles form related words, namely, synonyms and/or antonyms. | 1. A method comprising the steps of: obtaining a set of multilingual tiles, each tile bearing a first character of a first language and also bearing a second character of a second language, in which the second character is not a transliteration of the first character; and positioning selected tiles to form words; and wherein at least one of the following is also present: a player gains points for words made in a language that is not the player's native language; a player loses points for words made in a language that is the player's native language; extra points are awarded if tiles form multiple words in multiple languages; or extra points are awarded if tiles form related words, namely, synonyms and/or antonyms. 3. The method of claim 1 , wherein the method comprises positioning tiles in interlocking words such that every positioned tile is part of every word in every direction it touches. | 0.5 |
8,838,465 | 15 | 16 | 15. One or more non-transitory computer-readable media having collectively thereon computer-executable instructions that configure one or more computers to collectively, at least: cause simultaneous browser-based display of a plurality of browser-rendered windows, the plurality of browser-rendered windows being selected and arranged according to a user profile customizable by a user, said plurality of browser-rendered windows including: a first browser-rendered window displaying first information derived from at least one business information system module; and a second browser-rendered window displaying second information derived from said at least one business information system module; cause the browser-based display of the first information in the first browser-rendered window to be updated at first regular time intervals in accordance with a first setting in the user profile; and cause the browser-based display of the second information in the second browser-rendered window to be updated at second regular time intervals in accordance with a second setting in the user profile. | 15. One or more non-transitory computer-readable media having collectively thereon computer-executable instructions that configure one or more computers to collectively, at least: cause simultaneous browser-based display of a plurality of browser-rendered windows, the plurality of browser-rendered windows being selected and arranged according to a user profile customizable by a user, said plurality of browser-rendered windows including: a first browser-rendered window displaying first information derived from at least one business information system module; and a second browser-rendered window displaying second information derived from said at least one business information system module; cause the browser-based display of the first information in the first browser-rendered window to be updated at first regular time intervals in accordance with a first setting in the user profile; and cause the browser-based display of the second information in the second browser-rendered window to be updated at second regular time intervals in accordance with a second setting in the user profile. 16. One or more computer-readable media in accordance with claim 15 , wherein said at last one business information system module includes at least one enterprise resource planning module. | 0.78341 |
9,432,327 | 2 | 3 | 2. The method of claim 1 , wherein the first user action is the submission of a first post. | 2. The method of claim 1 , wherein the first user action is the submission of a first post. 3. The method of claim 2 , wherein the first post comprises one or more of: a status update declared by the first user on a profile page of the first user; a wall post declared on a profile page of the first user; a wall post declared on a profile page of the second user; a declared comment on a status update declared by the second user; a declared comment on a wall post declared by the second user; or an indication or declaration by the first user of a like of a user action. | 0.5 |
9,536,067 | 8 | 9 | 8. A computer-implemented method for submitting and checking a password without additional user input, the method comprising: presenting a password entry form to a user, the password entry form having a text field for entering a password; wherein the password entry form is configured to accept passwords of variable length; detecting text input from the user; in response to detecting the text input from the user, displaying text characters in the text field; in response to the user entering text characters in the text field, submitting the contents of the text field for password verification; wherein the step of submitting the contents of the text field for password verification occurs without additional user input besides the user entering text characters in the text field; wherein the step of submitting the contents of the text field for password verification is performed repeatedly in response to the user changing the contents of the text field and is performed at least once before the user has completed entry of the password in the text field; at a first time, determining that a password submitted for verification is not a correct password of the user and not providing access to a protected computer resource; at a second time, determining that a password submitted for verification is a correct password of the user, logging in the user to provide access to the protected computer resource, and notifying the user that he or she is logged in; wherein the steps of detecting text input from the user and, in response to detecting the text input from the user, displaying text characters in the text field, are capable of occurring in parallel with the step of determining that a password submitted for verification is a correct password of the user. | 8. A computer-implemented method for submitting and checking a password without additional user input, the method comprising: presenting a password entry form to a user, the password entry form having a text field for entering a password; wherein the password entry form is configured to accept passwords of variable length; detecting text input from the user; in response to detecting the text input from the user, displaying text characters in the text field; in response to the user entering text characters in the text field, submitting the contents of the text field for password verification; wherein the step of submitting the contents of the text field for password verification occurs without additional user input besides the user entering text characters in the text field; wherein the step of submitting the contents of the text field for password verification is performed repeatedly in response to the user changing the contents of the text field and is performed at least once before the user has completed entry of the password in the text field; at a first time, determining that a password submitted for verification is not a correct password of the user and not providing access to a protected computer resource; at a second time, determining that a password submitted for verification is a correct password of the user, logging in the user to provide access to the protected computer resource, and notifying the user that he or she is logged in; wherein the steps of detecting text input from the user and, in response to detecting the text input from the user, displaying text characters in the text field, are capable of occurring in parallel with the step of determining that a password submitted for verification is a correct password of the user. 9. The method of claim 8 , further comprising determining that a threshold time has elapsed from the most recent entry of a text character in the text field before performing the step of, in response to the user entering text characters in the text field, submitting the contents of the text field for password verification. | 0.566845 |
8,751,517 | 8 | 10 | 8. A computer-implemented information processing method comprising the steps of: storing in an operation-definition storage device a record including a function name, a function ontology and an operation type, with respect to each of a plurality of APs which are applications; acquiring from said operation-definition storage device an identical ontology set which is a set of records having an identical function ontology or a set of identifiers of the records belonging to said identical ontology set; the information processing program further including a function search process wherein the computer is enabled to perform steps of: replacing an operation type of a record including said identical function ontology of a designated AP with a high frequency type which is an operation type having a high appearance frequency in said identical ontology set; searching said operation-definition storage device for a record matching both an inputted AP name and an operation type of a detected operation; outputting a function name of the extracted said record and said inputted AP name to a function execution unit executing a function of an AP identified by the AP name and the function name; storing in a context-definition storage device a context name and a sensor value, relating them to each other; storing said record in said operation-definition storage device, with respect to each context of each of said plurality of APs; acquiring from said context-definition storage device a context corresponding to an inputted sensor value; searching said operation-definition storage device for a record matching said context, an inputted AP name and an inputted operation type; outputting a function name of the extracted said record and said inputted AP name to said function execution unit executing a function of an AP identified by the AP name and the function name; and acquiring from said operation-definition storage device a set of records having both an identical context and an identical function ontology, as said identical ontology set. | 8. A computer-implemented information processing method comprising the steps of: storing in an operation-definition storage device a record including a function name, a function ontology and an operation type, with respect to each of a plurality of APs which are applications; acquiring from said operation-definition storage device an identical ontology set which is a set of records having an identical function ontology or a set of identifiers of the records belonging to said identical ontology set; the information processing program further including a function search process wherein the computer is enabled to perform steps of: replacing an operation type of a record including said identical function ontology of a designated AP with a high frequency type which is an operation type having a high appearance frequency in said identical ontology set; searching said operation-definition storage device for a record matching both an inputted AP name and an operation type of a detected operation; outputting a function name of the extracted said record and said inputted AP name to a function execution unit executing a function of an AP identified by the AP name and the function name; storing in a context-definition storage device a context name and a sensor value, relating them to each other; storing said record in said operation-definition storage device, with respect to each context of each of said plurality of APs; acquiring from said context-definition storage device a context corresponding to an inputted sensor value; searching said operation-definition storage device for a record matching said context, an inputted AP name and an inputted operation type; outputting a function name of the extracted said record and said inputted AP name to said function execution unit executing a function of an AP identified by the AP name and the function name; and acquiring from said operation-definition storage device a set of records having both an identical context and an identical function ontology, as said identical ontology set. 10. The information processing method according to claim 8 , wherein said high frequency type is an operation type having the highest appearance frequency among said identical ontology set or having an appearance frequency equal to or larger than a predetermined value. | 0.697753 |
8,103,547 | 2 | 4 | 2. The media of claim 1 , further comprising associating the text with the logocon in a table of information in a storage device, wherein the storage device communicates with the computing device or the storage device communicates with another computing device that communicates with the computing device, and wherein the another computing device is another server. | 2. The media of claim 1 , further comprising associating the text with the logocon in a table of information in a storage device, wherein the storage device communicates with the computing device or the storage device communicates with another computing device that communicates with the computing device, and wherein the another computing device is another server. 4. The media of claim 2 , wherein receiving the set of information at the computing device comprises at least one of: receiving a blog at a server wherein the set of information is the blog and the computing device is the server wherein the blog is received when a user types an entry or saves the entry; receiving the email at an email server wherein the set of information is the email and the computing device is the email server; and receiving an instant message at a message server wherein the set of information is the instant message and the computing device is the message server. | 0.5 |
9,852,219 | 7 | 8 | 7. The method of claim 3 , wherein the at least one group is indicated in a sample group description box. | 7. The method of claim 3 , wherein the at least one group is indicated in a sample group description box. 8. The method of claim 7 , wherein the at least one group of one or more samples of the streamed data is indicated in a sample group description box for the timed metadata track through associating the at least one group of one or more samples of the streamed data with respective timed metadata samples in the timed metadata track. | 0.5 |
9,380,174 | 17 | 18 | 17. A non-transitory processor-readable medium storing computer code representing instructions to cause a process for automatically converting a mobile rendering job into a secure rendering job, said computer code comprising code to: establish wireless communications between a mobile telecommunications device and a multi-function device that communicate with each another via a print server; receive through said print server a rendering job from said mobile telecommunications device configured with a mobile multifunction device user interface via a secure rendering module that enables secure rendering of said rendering job at said multi-function device via said wireless communications and facilitated by said print server; associate said secure rendering module with a print path with respect to said mobile telecommunications device; automatically check a document context associated with said rendering job as well as a context of said multi-function device to determine a confidentiality of said rendering job to securely transmit said rendering job to said multi-function device based on said determined confidentiality of said rendering job; analyze a location of said multi-function device with respect to a user primary work location and a department in an asset database, a user database, and an active directory/lightweight directory access protocol connector; and analyze an activity respect to said multi-function device utilizing a job tracking record database that communicates electronically with an activity checking unit of said secure rendering module. | 17. A non-transitory processor-readable medium storing computer code representing instructions to cause a process for automatically converting a mobile rendering job into a secure rendering job, said computer code comprising code to: establish wireless communications between a mobile telecommunications device and a multi-function device that communicate with each another via a print server; receive through said print server a rendering job from said mobile telecommunications device configured with a mobile multifunction device user interface via a secure rendering module that enables secure rendering of said rendering job at said multi-function device via said wireless communications and facilitated by said print server; associate said secure rendering module with a print path with respect to said mobile telecommunications device; automatically check a document context associated with said rendering job as well as a context of said multi-function device to determine a confidentiality of said rendering job to securely transmit said rendering job to said multi-function device based on said determined confidentiality of said rendering job; analyze a location of said multi-function device with respect to a user primary work location and a department in an asset database, a user database, and an active directory/lightweight directory access protocol connector; and analyze an activity respect to said multi-function device utilizing a job tracking record database that communicates electronically with an activity checking unit of said secure rendering module. 18. The processor-readable medium of claim 17 wherein said mobile telecommunications device comprises at least one of a smartphone, tablet computing device, or a laptop computer. | 0.705298 |
9,558,101 | 10 | 12 | 10. A non-transitory computer readable storage device including instructions stored thereon, which when executed by a machine, configure the machine to: create a set of defined preprocessor directive symbols including unique preprocessor directive symbols defined in one or more build or sub-build files of a software program, creating the set of defined preprocessor directive symbols including analyzing the one or more build or sub-build files for a preprocessor directive and recording symbols immediately following the preprocessor directive as a defined preprocessor directive symbol in the set of defined preprocessor directive symbols; create a set of used preprocessor directive symbols including unique preprocessor directive symbols defined in one or more source code flies of the software program, creating the set of used preprocessor directive symbols including analyzing the one or more source code files for the preprocessor directive and recording symbols immediately following the preprocessor directive as a used preprocessor directive symbol in the set of used preprocessor directive symbols; create a set of accurately used preprocessor directive symbols that includes only preprocessor directive symbols in the set of used preprocessor directive symbols and the set of defined preprocessor directive symbols; create a set of unused preprocessor directive symbols that includes preprocessor directive symbols in the set of defined preprocessor directive symbols and not in the set of used preprocessor directive symbols by including preprocessor directive symbols in the set of defined preprocessor directive symbols and not in the set of accurately used preprocessor directive symbols in the set of unused preprocessor directive symbols; create a set of undefined preprocessor directive symbols that includes preprocessor directive symbols in the set of used preprocessor directive symbols and not in the set of defined preprocessor directive symbols by including preprocessor directive symbols in the set of used preprocessor directive symbols and not in the set of accurately used preprocessor directive symbols in the set of undefined preprocessor directive symbols; identify a preprocessor directive symbol that is in the set of unused preprocessor directive symbols; comparing the identified preprocessor directive symbol to each preprocessor directive symbol in the set of undefined preprocessor directive symbols by respectively applying a heuristic to the identified preprocessor directive symbol and each preprocessor directive symbol from the set of undefined preprocessor directive symbols; and determine a likelihood that the identified preprocessor directive symbol is presented erroneously as respective preprocessor directive symbol of the set of undefined preprocessor directive symbols based on a result of applying the heuristic. | 10. A non-transitory computer readable storage device including instructions stored thereon, which when executed by a machine, configure the machine to: create a set of defined preprocessor directive symbols including unique preprocessor directive symbols defined in one or more build or sub-build files of a software program, creating the set of defined preprocessor directive symbols including analyzing the one or more build or sub-build files for a preprocessor directive and recording symbols immediately following the preprocessor directive as a defined preprocessor directive symbol in the set of defined preprocessor directive symbols; create a set of used preprocessor directive symbols including unique preprocessor directive symbols defined in one or more source code flies of the software program, creating the set of used preprocessor directive symbols including analyzing the one or more source code files for the preprocessor directive and recording symbols immediately following the preprocessor directive as a used preprocessor directive symbol in the set of used preprocessor directive symbols; create a set of accurately used preprocessor directive symbols that includes only preprocessor directive symbols in the set of used preprocessor directive symbols and the set of defined preprocessor directive symbols; create a set of unused preprocessor directive symbols that includes preprocessor directive symbols in the set of defined preprocessor directive symbols and not in the set of used preprocessor directive symbols by including preprocessor directive symbols in the set of defined preprocessor directive symbols and not in the set of accurately used preprocessor directive symbols in the set of unused preprocessor directive symbols; create a set of undefined preprocessor directive symbols that includes preprocessor directive symbols in the set of used preprocessor directive symbols and not in the set of defined preprocessor directive symbols by including preprocessor directive symbols in the set of used preprocessor directive symbols and not in the set of accurately used preprocessor directive symbols in the set of undefined preprocessor directive symbols; identify a preprocessor directive symbol that is in the set of unused preprocessor directive symbols; comparing the identified preprocessor directive symbol to each preprocessor directive symbol in the set of undefined preprocessor directive symbols by respectively applying a heuristic to the identified preprocessor directive symbol and each preprocessor directive symbol from the set of undefined preprocessor directive symbols; and determine a likelihood that the identified preprocessor directive symbol is presented erroneously as respective preprocessor directive symbol of the set of undefined preprocessor directive symbols based on a result of applying the heuristic. 12. The storage device of claim 10 , wherein the instructions that configure the machine to apply the heuristic include instructions, which when executed by the machine, configured the machine to apply at least one of a Hamming distance technique, Levenshtein distance technique, Damerau-Levenshtein distance technique, Jaro distance technique, Jaro-Winkler distance technique, or a phonetic matching technique to the identified preprocessor directive symbol and respective preprocessor directive symbols in the set of undefined preprocessor directive symbols. | 0.5 |
7,991,768 | 10 | 16 | 10. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause: receiving a query that specifies a particular path expression; normalizing the query to generate a normalized query, wherein normalizing the query comprises generating, based on the particular path expression, a plurality of normalized path expressions generating, based on the particular path expression, from a subset of the plurality of normalized path expressions, one or more temporary path expressions; determining whether each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by a path-subsetted XML index that is associated with one or more subsetted path expressions that indicate a set of one or more nodes that are indexed by said path-subsetted XML index; and in response to determining that each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by said path-subsetted XML index, using the path-subsetted XML index to process the plurality of normalized path expressions. | 10. One or more non-transitory machine-readable media storing instructions which, when executed by one or more processors, cause: receiving a query that specifies a particular path expression; normalizing the query to generate a normalized query, wherein normalizing the query comprises generating, based on the particular path expression, a plurality of normalized path expressions generating, based on the particular path expression, from a subset of the plurality of normalized path expressions, one or more temporary path expressions; determining whether each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by a path-subsetted XML index that is associated with one or more subsetted path expressions that indicate a set of one or more nodes that are indexed by said path-subsetted XML index; and in response to determining that each of the one or more temporary path expressions is subsumed by a path of a node that is indexed by said path-subsetted XML index, using the path-subsetted XML index to process the plurality of normalized path expressions. 16. The one or more non-transitory machine-readable media of claim 10 , wherein each normalized path expression in a subset of the plurality of normalized path expressions is subsumed by a subsetted path expression of the one or more subsetted path expressions. | 0.845562 |
9,436,440 | 1 | 2 | 1. A computer program product embodied on a non-transitory computer readable medium, comprising computer code for: identifying an object-oriented information model including JAVA™ code associated with JAVA™ programming language to be converted to a document-oriented model described in Extensible Markup Language (XML); automatically identifying a plurality of objects associated with the object-oriented information model that are each associated with a plurality of instances, including identifying a plurality of objects that each include a plurality of different object definitions for that object; optimizing the object-oriented information model by, for each of the plurality of objects each associated with the plurality of instances, storing the plurality of different object definitions in a defined data container outside of the object-oriented information model and replacing each of the plurality of different object definitions with a reference to the different object definitions in the defined data container outside of the object-oriented information model; annotating the optimized object-oriented information model, in response to performing the storing and the replacing; and automatically validating the optimized object-oriented information model by verifying the reference to the plurality of different object definitions in the defined data container outside of the optimized object-oriented information model is associated with at least one object identifier. | 1. A computer program product embodied on a non-transitory computer readable medium, comprising computer code for: identifying an object-oriented information model including JAVA™ code associated with JAVA™ programming language to be converted to a document-oriented model described in Extensible Markup Language (XML); automatically identifying a plurality of objects associated with the object-oriented information model that are each associated with a plurality of instances, including identifying a plurality of objects that each include a plurality of different object definitions for that object; optimizing the object-oriented information model by, for each of the plurality of objects each associated with the plurality of instances, storing the plurality of different object definitions in a defined data container outside of the object-oriented information model and replacing each of the plurality of different object definitions with a reference to the different object definitions in the defined data container outside of the object-oriented information model; annotating the optimized object-oriented information model, in response to performing the storing and the replacing; and automatically validating the optimized object-oriented information model by verifying the reference to the plurality of different object definitions in the defined data container outside of the optimized object-oriented information model is associated with at least one object identifier. 2. The computer program product of claim 1 , wherein identifying the plurality of objects associated with the object-oriented information model that are each associated with the plurality of instances includes identifying objects in the JAVA™ code that are each referenced more than once. | 0.566265 |
9,600,474 | 1 | 2 | 1. A computer-implemented method comprising: displaying a graphical user interface for a language translation application on a user device, the graphical user interface comprising a first graphical representation identifying a source language, a second graphical representation identifying a target language, and a third graphical representation indicating the user device operating in a listening mode that is arranged adjacent to both the first graphical representation identifying the source language and the second graphical representation identifying the target language; animating, in response to a request to initiate listening for an utterance in the source language, the third graphical representation indicating the listening mode while the language translation application prepares to listen for the source language; highlighting, in response to the language translation application completing preparations to listen for the source language, the third graphical representation indicating the listening mode while also highlighting the first graphical representation identifying the source language to create a visual correspondence between the first graphical representation identifying the source language and the third graphical representation indicating the listening mode indicating that the language translation application is prepared to receive voice input in the source language; receiving an utterance spoken in the source language for translation into the target language while the third graphical representation indicating the listening mode and the first graphical representation identifying the source language are highlighted to create a visual correspondence between the first graphical representation identifying the source language and the third graphical representation indicating the listening mode; replacing, in response to the language translation application preparing an output of a translation of the utterance into the target language, the third graphical representation indicating the listening mode on the graphical user interface with a fourth graphical representation indicating a translation transcription mode on the graphical user interface; and highlighting, in response to the language translation application completing preparations to output the translation of the transcription into the target language, the fourth graphical representation indicating the translation transcription mode while also highlighting the second graphical representation identifying the target language to create a visual correspondence between the second graphical representation identifying the target language and the fourth graphical representation indicating the translation transcription mode indicating that the language translation application is outputting a translation of the utterance in the target language. | 1. A computer-implemented method comprising: displaying a graphical user interface for a language translation application on a user device, the graphical user interface comprising a first graphical representation identifying a source language, a second graphical representation identifying a target language, and a third graphical representation indicating the user device operating in a listening mode that is arranged adjacent to both the first graphical representation identifying the source language and the second graphical representation identifying the target language; animating, in response to a request to initiate listening for an utterance in the source language, the third graphical representation indicating the listening mode while the language translation application prepares to listen for the source language; highlighting, in response to the language translation application completing preparations to listen for the source language, the third graphical representation indicating the listening mode while also highlighting the first graphical representation identifying the source language to create a visual correspondence between the first graphical representation identifying the source language and the third graphical representation indicating the listening mode indicating that the language translation application is prepared to receive voice input in the source language; receiving an utterance spoken in the source language for translation into the target language while the third graphical representation indicating the listening mode and the first graphical representation identifying the source language are highlighted to create a visual correspondence between the first graphical representation identifying the source language and the third graphical representation indicating the listening mode; replacing, in response to the language translation application preparing an output of a translation of the utterance into the target language, the third graphical representation indicating the listening mode on the graphical user interface with a fourth graphical representation indicating a translation transcription mode on the graphical user interface; and highlighting, in response to the language translation application completing preparations to output the translation of the transcription into the target language, the fourth graphical representation indicating the translation transcription mode while also highlighting the second graphical representation identifying the target language to create a visual correspondence between the second graphical representation identifying the target language and the fourth graphical representation indicating the translation transcription mode indicating that the language translation application is outputting a translation of the utterance in the target language. 2. The method of claim 1 , further comprising, animating, in response to the language translation application completing preparations to listen for the source language, the third graphical representation indicating the listening mode. | 0.592334 |
8,952,763 | 9 | 12 | 9. A frequency modulator comprising: a digitally-controlled oscillator (DCO), arranged for producing a frequency deviation in response to an integer tuning word and a fractional tuning word; and a DCO interface circuit, arranged for generating said integer tuning word and said fractional tuning word to said DCO, wherein said fractional tuning word is obtained through asynchronous sampling of a fixed-point tuning word; wherein samples of said fractional tuning word are synchronous to a resonant frequency of said DCO. | 9. A frequency modulator comprising: a digitally-controlled oscillator (DCO), arranged for producing a frequency deviation in response to an integer tuning word and a fractional tuning word; and a DCO interface circuit, arranged for generating said integer tuning word and said fractional tuning word to said DCO, wherein said fractional tuning word is obtained through asynchronous sampling of a fixed-point tuning word; wherein samples of said fractional tuning word are synchronous to a resonant frequency of said DCO. 12. The frequency modulator of claim 9 , wherein ratio of a sampling rate of said integer tuning word and a sampling rate of said fractional tuning word is not an integer. | 0.693548 |
9,891,792 | 1 | 11 | 1. A method for building and utilizing interactive software system predictive models using biometric data comprising: providing an interactive software system; defining biometric data to be obtained and analyzed; providing one or more biometric data collection systems to obtain the defined biometric data; monitoring a user's interaction with the interactive software system and obtaining user interaction activity data indicating the user's interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the user at defined times as the user interacts with the interactive software system; correlating the biometric data associated with the user with the user's interaction activity data at the defined times; obtaining baseline data associated with the user, the baseline data including data indicating when the baseline data was obtained; analyzing the biometric data associated with the user and correlated to the user's interaction activity data and the baseline data associated with the user, to generate emotional pattern predictive model data representing an emotional pattern predictive model associated with the user; based, at least in part, on the emotional pattern predictive model associated with the user, modifying one or more features and/or supporting systems associated with the interactive software system to customize an interactive software system user experience to the user; and presenting the customized interactive software system user experience to the user. | 1. A method for building and utilizing interactive software system predictive models using biometric data comprising: providing an interactive software system; defining biometric data to be obtained and analyzed; providing one or more biometric data collection systems to obtain the defined biometric data; monitoring a user's interaction with the interactive software system and obtaining user interaction activity data indicating the user's interaction with the interactive software system at defined times; using the one or more biometric data collection systems to obtain biometric data associated with the user at defined times as the user interacts with the interactive software system; correlating the biometric data associated with the user with the user's interaction activity data at the defined times; obtaining baseline data associated with the user, the baseline data including data indicating when the baseline data was obtained; analyzing the biometric data associated with the user and correlated to the user's interaction activity data and the baseline data associated with the user, to generate emotional pattern predictive model data representing an emotional pattern predictive model associated with the user; based, at least in part, on the emotional pattern predictive model associated with the user, modifying one or more features and/or supporting systems associated with the interactive software system to customize an interactive software system user experience to the user; and presenting the customized interactive software system user experience to the user. 11. The method for building and utilizing interactive software system predictive models using biometric data of claim 1 , wherein the customized interactive software system user experience is presented to the user via at least one computing system selected from the group of computing systems consisting of: a server computing system; a workstation; a desktop computing system; a user wearable computing system; and a mobile computing system. | 0.856026 |
8,631,068 | 1 | 3 | 1. A method for supporting a peer-based communications service that has peer members at clients that communicate with each other over a network about topics, wherein the peer members and topics are represented by objects that have properties, comprising: maintaining information on links between the objects and the properties of the objects as links table rows, wherein each links table row contains a privacy setting, a linking association between two respective objects, and corresponding descriptive attributes, wherein each links table row's linking association includes at least two object identifiers identifying a first object at which a link begins and second object at which a link terminates, and wherein each links table row's descriptive attributes include attributes representing the relationship between the first object and the second object; searching the information using a distributed database search, wherein: the searching propagates from a client of an originating peer member to a second client of a second peer member; the originating peer member and the second peer member are within a peer network; and as the links table associated with the second peer member is searched, search results are returned to the originating peer member; and using the privacy settings to determine whether the originating peer member can display a link between objects. | 1. A method for supporting a peer-based communications service that has peer members at clients that communicate with each other over a network about topics, wherein the peer members and topics are represented by objects that have properties, comprising: maintaining information on links between the objects and the properties of the objects as links table rows, wherein each links table row contains a privacy setting, a linking association between two respective objects, and corresponding descriptive attributes, wherein each links table row's linking association includes at least two object identifiers identifying a first object at which a link begins and second object at which a link terminates, and wherein each links table row's descriptive attributes include attributes representing the relationship between the first object and the second object; searching the information using a distributed database search, wherein: the searching propagates from a client of an originating peer member to a second client of a second peer member; the originating peer member and the second peer member are within a peer network; and as the links table associated with the second peer member is searched, search results are returned to the originating peer member; and using the privacy settings to determine whether the originating peer member can display a link between objects. 3. The method defined in claim 1 wherein each links table row contains a linking association portion having at least one object identifier and a descriptive attributes portion including the privacy setting for that links table row, the method further comprising using the linking association portions and the descriptive attributes portions to determine which links between objects and which object properties can be viewed using the originating peer member's client. | 0.661103 |
8,781,829 | 1 | 5 | 1. A computer-implemented method performed by at least one computer processor, the method comprising: (A) applying automatic speech recognition to an audio signal to produce a structured document representing contents of the audio signal; (B) determining whether the structured document includes an indication of compliance for each of a plurality of best practices to produce a conclusion; (C) inserting content into the structured document, based on the conclusion, to produce a modified structured document; (D) generating a first indication that a user should provide additional input of a first type to conform the structured document to a first best practice in the plurality of best practices; and (E) generating a second indication that the user should provide additional input of a type to conform the structured document to a second best practice in the plurality of best practices. | 1. A computer-implemented method performed by at least one computer processor, the method comprising: (A) applying automatic speech recognition to an audio signal to produce a structured document representing contents of the audio signal; (B) determining whether the structured document includes an indication of compliance for each of a plurality of best practices to produce a conclusion; (C) inserting content into the structured document, based on the conclusion, to produce a modified structured document; (D) generating a first indication that a user should provide additional input of a first type to conform the structured document to a first best practice in the plurality of best practices; and (E) generating a second indication that the user should provide additional input of a type to conform the structured document to a second best practice in the plurality of best practices. 5. The method of claim 1 , wherein (C) comprises: (C)(1) obtaining the content from a data source without human input; and (C)(2) inserting the content into the structured document. | 0.712698 |
8,959,011 | 5 | 6 | 5. The method of claim 3 , wherein the step of receiving input from a user further comprises displaying, by a processor, resembling substitution alternatives for the at least one word in the document indicated as potentially erroneous. | 5. The method of claim 3 , wherein the step of receiving input from a user further comprises displaying, by a processor, resembling substitution alternatives for the at least one word in the document indicated as potentially erroneous. 6. The method of claim 5 , further comprising enabling a user to manually select a subject of the source language from a list of source language subjects in a window; and adjusting the resembling substitution alternatives selected by a user from the window with the list to terms consistent with the subject as chosen by a user. | 0.5 |
7,877,251 | 12 | 13 | 12. The computer-readable medium of claim 11 wherein the method further comprises identifying in the second region the modified translated word. | 12. The computer-readable medium of claim 11 wherein the method further comprises identifying in the second region the modified translated word. 13. The computer-readable medium of claim 12 wherein the method further comprises identifying in the first region a word corresponding to the modified translated word. | 0.5 |
9,626,406 | 1 | 2 | 1. A method comprising: receiving a first user input that specifies criteria corresponding to an information need, the criteria including at least a category corresponding to the information need; analyzing the first user input to determine whether the first user input corresponds to a first type of category or a second type of category; in response to a determination that the first user input corresponds to the first type of category, executing a query against a set of one or more databases based on the criteria corresponding to the information need; and in response to a determination that the first user input corresponds to the second type of category, requesting additional user input that specifies at least one additional criterion corresponding to the information need, wherein the at least one additional criterion further categorizes the information need; and in response to receiving the at least one additional criterion, executing a second query against a second set of one or more databases based on the criteria corresponding to the information need and the at least one additional criterion that further categorizes the information need. | 1. A method comprising: receiving a first user input that specifies criteria corresponding to an information need, the criteria including at least a category corresponding to the information need; analyzing the first user input to determine whether the first user input corresponds to a first type of category or a second type of category; in response to a determination that the first user input corresponds to the first type of category, executing a query against a set of one or more databases based on the criteria corresponding to the information need; and in response to a determination that the first user input corresponds to the second type of category, requesting additional user input that specifies at least one additional criterion corresponding to the information need, wherein the at least one additional criterion further categorizes the information need; and in response to receiving the at least one additional criterion, executing a second query against a second set of one or more databases based on the criteria corresponding to the information need and the at least one additional criterion that further categorizes the information need. 2. The method of claim 1 , wherein the recited acts are performed in the order recited. | 0.897887 |
7,770,182 | 7 | 13 | 7. A system, comprising: a processor; and one or more computer-readable storage media having computer-executable instructions stored thereon that, when executed by the processor, implement: an extensible editor that processes editing events requesting manipulation of a document, the extensible editor having an event routing controller and a default event handler; and a first extension and a second extension coupled with the extensible editor for processing the editing events, wherein the event routing controller provides an editing event received by the extensible editor to the first extension prior to providing the editing event to be processed by the default event handler, wherein the event routing controller provides the editing event to the second extension prior to providing the editing event to be processed by the default event handler when the first extension does not consume the editing event, and wherein an order in which the editing event is routed to the first extension and the second extension is based on an order in which the first extension and the second extension were registered with the extensible editor. | 7. A system, comprising: a processor; and one or more computer-readable storage media having computer-executable instructions stored thereon that, when executed by the processor, implement: an extensible editor that processes editing events requesting manipulation of a document, the extensible editor having an event routing controller and a default event handler; and a first extension and a second extension coupled with the extensible editor for processing the editing events, wherein the event routing controller provides an editing event received by the extensible editor to the first extension prior to providing the editing event to be processed by the default event handler, wherein the event routing controller provides the editing event to the second extension prior to providing the editing event to be processed by the default event handler when the first extension does not consume the editing event, and wherein an order in which the editing event is routed to the first extension and the second extension is based on an order in which the first extension and the second extension were registered with the extensible editor. 13. The system as recited in claim 7 , wherein: the extensible editor further comprises an edit designer interface that includes a post-handle event method for providing the editing event to the first extension after the default event handler has processed the event; and the event routing controller is further configured to provide the editing event to the first extension through the edit designer interface. | 0.542316 |
9,387,391 | 1 | 7 | 1. A system for scoring a comparison of ranked items associated with a topic selected by a first user, comprising: a processor; a topic module configured to cooperate with the processor to retrieve, over a communication network, one or more potential topics based on information stored in a social data repository of a first user, and receive a topic selection from the first user, the topic selection identifying a topic selected by the first user from the one or more potential topics; a GUI module configured to cooperate with the processor to present items associated with the topic to the first user to enable the first user to input a first ranking of a first set of the items according to a subjective preference of the first user and present the items to (i) a second user to enable the second user to input a second ranking of a second set of the items, and (ii) a third user to enable the third user to input a third ranking of the second set of the items; a ranking module configured to cooperate with the processor to receive (i) the first ranking of the first set of the items by the first user, (ii) the second ranking of the second set of the items by the second user, and (iii) the third ranking of the second set of the items by the third user; and a scoring module configured to cooperate with the processor to determine a first game score based on a comparison of the second ranking relative to the first ranking, and a second game score based on a comparison of the third ranking relative to the first ranking, the scoring module further configured to present an award based, at least in part, on a comparison of the first game score and the second game score. | 1. A system for scoring a comparison of ranked items associated with a topic selected by a first user, comprising: a processor; a topic module configured to cooperate with the processor to retrieve, over a communication network, one or more potential topics based on information stored in a social data repository of a first user, and receive a topic selection from the first user, the topic selection identifying a topic selected by the first user from the one or more potential topics; a GUI module configured to cooperate with the processor to present items associated with the topic to the first user to enable the first user to input a first ranking of a first set of the items according to a subjective preference of the first user and present the items to (i) a second user to enable the second user to input a second ranking of a second set of the items, and (ii) a third user to enable the third user to input a third ranking of the second set of the items; a ranking module configured to cooperate with the processor to receive (i) the first ranking of the first set of the items by the first user, (ii) the second ranking of the second set of the items by the second user, and (iii) the third ranking of the second set of the items by the third user; and a scoring module configured to cooperate with the processor to determine a first game score based on a comparison of the second ranking relative to the first ranking, and a second game score based on a comparison of the third ranking relative to the first ranking, the scoring module further configured to present an award based, at least in part, on a comparison of the first game score and the second game score. 7. The system of claim 1 , wherein the second ranking received from the second user is based on what the second user guesses other users will rank the second set of items. | 0.660714 |
9,594,833 | 7 | 11 | 7. A computer-implemented method for classifying a type of page of a set of serially organized pages, the computer-implemented method comprising: determining a classification for a page of the set of serially organized pages based at least in part on content in the page independent of content in other pages of the set of serially organized pages; identifying a location of the page within the set of serially organized pages, wherein the location of the page indicates an ordering of the page relative to other pages in the set of serially organized pages; determining a modified classification for the page, wherein the modified classification is determined at least from inputs comprising the classification for the page, as based at least in part on the content in the page, and the location of the page relative to other pages in the set of serially organized pages; and storing the modified classification in at least one data store. | 7. A computer-implemented method for classifying a type of page of a set of serially organized pages, the computer-implemented method comprising: determining a classification for a page of the set of serially organized pages based at least in part on content in the page independent of content in other pages of the set of serially organized pages; identifying a location of the page within the set of serially organized pages, wherein the location of the page indicates an ordering of the page relative to other pages in the set of serially organized pages; determining a modified classification for the page, wherein the modified classification is determined at least from inputs comprising the classification for the page, as based at least in part on the content in the page, and the location of the page relative to other pages in the set of serially organized pages; and storing the modified classification in at least one data store. 11. The computer-implemented method of claim 7 , wherein the inputs further comprise global page data of the set of serially organized pages. | 0.827628 |
7,552,121 | 8 | 9 | 8. A computer-readable storage medium containing a program which performs an operation, the operation comprising: receiving a query configured to be executed against a database containing data, wherein the query has been previously executed against the database, and wherein statistics reflecting a number of records required to execute the query were recorded during a prior execution of the query; prior to executing the query, analyzing the query to select a locking strategy to use in executing the query, the locking strategy being selected from at least two different locking strategies, wherein the locking strategy specifies which of the data to prevent other queries from accessing when the query is executed, wherein the analyzing comprises determining whether to escalate from a row level locking strategy to a page level locking strategy by evaluating: the number of records evaluated during execution of the query during the prior execution of the query, and an estimated number of records required to execute the query; upon determining at least one of the number of records and the estimated number of records exceeds a specified threshold, escalating to at least the page level locking strategy; upon determining neither the number of records nor the estimated number of records exceeds the specified threshold, selecting the row level locking strategy; and executing the query using the selected locking strategy. | 8. A computer-readable storage medium containing a program which performs an operation, the operation comprising: receiving a query configured to be executed against a database containing data, wherein the query has been previously executed against the database, and wherein statistics reflecting a number of records required to execute the query were recorded during a prior execution of the query; prior to executing the query, analyzing the query to select a locking strategy to use in executing the query, the locking strategy being selected from at least two different locking strategies, wherein the locking strategy specifies which of the data to prevent other queries from accessing when the query is executed, wherein the analyzing comprises determining whether to escalate from a row level locking strategy to a page level locking strategy by evaluating: the number of records evaluated during execution of the query during the prior execution of the query, and an estimated number of records required to execute the query; upon determining at least one of the number of records and the estimated number of records exceeds a specified threshold, escalating to at least the page level locking strategy; upon determining neither the number of records nor the estimated number of records exceeds the specified threshold, selecting the row level locking strategy; and executing the query using the selected locking strategy. 9. The computer-readable storage medium of claim 8 , wherein determining whether to escalate from a row level locking strategy to a page level locking strategy further comprises evaluating database statistics regarding a current utilization of the database. | 0.555363 |
5,574,826 | 21 | 22 | 21. A memory section for an electronic controller which performs inference operations according to rules, each rule comprising at least one preposition and at least one implication, wherein a membership function, defined for a finite number of points of a universe of discourse, appears in the preposition of at least one of the rules, the membership function having a value for each of the finite number of points, which value is indicative of a degree of membership, wherein the memory section stores for each point of the finite number of points the values of only those membership functions for the point which are not zero. | 21. A memory section for an electronic controller which performs inference operations according to rules, each rule comprising at least one preposition and at least one implication, wherein a membership function, defined for a finite number of points of a universe of discourse, appears in the preposition of at least one of the rules, the membership function having a value for each of the finite number of points, which value is indicative of a degree of membership, wherein the memory section stores for each point of the finite number of points the values of only those membership functions for the point which are not zero. 22. The memory section of claim 21 which stores, for each point of the finite number of points, a memory word comprising an indication of the membership functions with non-zero values for the point and the corresponding non-zero values. | 0.5 |
10,133,814 | 1 | 6 | 1. A computer-implemented method for providing an explanatory electronic document, the method being executed by one or more processors and comprising: receiving, by the one or more processors, input from a user, the input comprising data that is at least partially representative of a subject; performing, by the one or more processors, semantic context association based on the user input, one or more computer-readable ontologies, and a computer-readable knowledge graph to provide a target subject profile, the target subject profile comprising two or more associations describing the subject at respective degrees of specificity, at least one association comprising concepts from the knowledge graph that are more general than respective entities provided in the input; providing, by the one or more processors, a set of peer user profiles based on a user profile and a superset of peer user profiles using semantic user profile association between the user profile and each peer user profile in the superset of peer user profiles; retrieving, by the one or more processors, one or more peer subject profiles from computer-readable memory, each peer subject profile being associated with a peer user profile in the set of peer user profiles, and comprising one or more associations, each association describing a past subject experienced by a peer user; filtering, by the one or more processors, at least one association from a peer subject profile based on a comparison with a respective association in the target subject profile and data provided in the knowledge graph; providing, by the one or more processors, at least one explanatory text string associated with the subject based on at least one remaining association in the peer subject profile; and providing, by the one or more processors, the explanatory electronic document comprising the at least one explanatory text string. | 1. A computer-implemented method for providing an explanatory electronic document, the method being executed by one or more processors and comprising: receiving, by the one or more processors, input from a user, the input comprising data that is at least partially representative of a subject; performing, by the one or more processors, semantic context association based on the user input, one or more computer-readable ontologies, and a computer-readable knowledge graph to provide a target subject profile, the target subject profile comprising two or more associations describing the subject at respective degrees of specificity, at least one association comprising concepts from the knowledge graph that are more general than respective entities provided in the input; providing, by the one or more processors, a set of peer user profiles based on a user profile and a superset of peer user profiles using semantic user profile association between the user profile and each peer user profile in the superset of peer user profiles; retrieving, by the one or more processors, one or more peer subject profiles from computer-readable memory, each peer subject profile being associated with a peer user profile in the set of peer user profiles, and comprising one or more associations, each association describing a past subject experienced by a peer user; filtering, by the one or more processors, at least one association from a peer subject profile based on a comparison with a respective association in the target subject profile and data provided in the knowledge graph; providing, by the one or more processors, at least one explanatory text string associated with the subject based on at least one remaining association in the peer subject profile; and providing, by the one or more processors, the explanatory electronic document comprising the at least one explanatory text string. 6. The method of claim 1 , wherein the subject comprises a trip and the input comprises trip details and one or more expenses incurred. | 0.82 |
8,935,299 | 14 | 15 | 14. The non-transitory computer-readable storage medium of claim 11 , wherein initiating the addition comprises: providing, within a user interface used by the first administrator to administer the first page, a selector having an associated context that includes field types; receiving textual input that was entered into the selector on a client device; forming a result set by identifying field types matching the textual input; and providing the result set to the client device for display in visual association with the selector. | 14. The non-transitory computer-readable storage medium of claim 11 , wherein initiating the addition comprises: providing, within a user interface used by the first administrator to administer the first page, a selector having an associated context that includes field types; receiving textual input that was entered into the selector on a client device; forming a result set by identifying field types matching the textual input; and providing the result set to the client device for display in visual association with the selector. 15. The non-transitory computer-readable storage medium of claim 14 , further comprising: instructions for determining whether the field types of the result set are associated with a page type of the first page; and instructions for ranking the field types of the result set based on the determination. | 0.5 |
9,063,535 | 12 | 14 | 12. A system for controlling a robot based upon a numerical control language program comprising: a robot; a robot controller connected to the robot for controlling the robot according to a robot language program; a mass storage device connected to the robot controller for storing the numerical control language program; and a control program executed by the robot controller for converting the numerical control language program into the robot language program based upon a pre-defined conversion configuration table having discrete configuration instructions for converting each numerical control language positional command to a robot language positional command and converting each numerical control language miscellaneous code command to a robot language sub-program. | 12. A system for controlling a robot based upon a numerical control language program comprising: a robot; a robot controller connected to the robot for controlling the robot according to a robot language program; a mass storage device connected to the robot controller for storing the numerical control language program; and a control program executed by the robot controller for converting the numerical control language program into the robot language program based upon a pre-defined conversion configuration table having discrete configuration instructions for converting each numerical control language positional command to a robot language positional command and converting each numerical control language miscellaneous code command to a robot language sub-program. 14. The system according to claim 12 wherein the mass storage device stores an XML file of conversion rules for creating a conversion configuration table containing rules for converting the numerical control language program into the robot language program. | 0.5 |
9,483,738 | 16 | 17 | 16. A non-transitory computer-readable storage medium containing instructions, that when executed, control a computer system to be configured for: defining information for a set of genomes, the set of genomes describing characteristics of media programs; defining which genomes in the set of genomes correspond to which topics in a set of topics; inputting textual information for a plurality of media programs and the information for the set of genomes into a model; training the model to determine a probability distribution of terms for the set of topics based on analyzing the textual information and the information for the set of genomes, wherein training comprises incorporating a parameter that prevents topics from being submerged by other topics that are larger via a first item in the model; and outputting the trained model, wherein the probability distribution of terms is usable to determine genomes for each of the plurality of media programs, wherein a genome corresponds to a topic and is associated with a media program based on terms found in the textual information for the media program and the probability distribution of terms for the topic corresponding to the genome. | 16. A non-transitory computer-readable storage medium containing instructions, that when executed, control a computer system to be configured for: defining information for a set of genomes, the set of genomes describing characteristics of media programs; defining which genomes in the set of genomes correspond to which topics in a set of topics; inputting textual information for a plurality of media programs and the information for the set of genomes into a model; training the model to determine a probability distribution of terms for the set of topics based on analyzing the textual information and the information for the set of genomes, wherein training comprises incorporating a parameter that prevents topics from being submerged by other topics that are larger via a first item in the model; and outputting the trained model, wherein the probability distribution of terms is usable to determine genomes for each of the plurality of media programs, wherein a genome corresponds to a topic and is associated with a media program based on terms found in the textual information for the media program and the probability distribution of terms for the topic corresponding to the genome. 17. The non-transitory computer-readable storage medium of claim 16 , further configured for scoring terms for each of the plurality of media programs based on the trained model to rank topics for each media program. | 0.524229 |
8,806,304 | 8 | 11 | 8. A method comprising: receiving, from an optical receiver and by a device, a word, of a block of words within traffic, on which to perform forward error correction, each word of the block of words including respective encoded bits and respective sets of reliability bits for identifying a respective level of reliability of each one of the respective encoded bits; identifying, by the device, least reliable positions, within the word, that correspond to a subset of encoded bits, within the word, associated with one or more lowest levels of reliability; generating, by the device, a set of candidate words based on different combinations in which the subset of encoded bits can be inverted; identifying, by the device, a first pair of candidate words, within the set of candidate words, the first pair including a first word and a second word, the first word including a first bit, the first bit not being an inverted bit and being most reliable within the subset of encoded bits associated with the first word; identifying, by the device, a first quantity of errors associated with the first word and a second quantity of errors associated with the second word; determining, by the device, whether the first quantity of errors is greater than the second quantity of errors; selecting, by the device, the first word when the first quantity of errors is not greater than the second quantity of errors; identifying, by the device, a second pair of candidate words, within selected words of the set of candidate words, the second pair including the first word and a third word, the third word including a second bit that is most reliable within the subset of encoded bits associated with the third word; determining, by the device, whether the second bit is an inverted bit; selecting, by the device, the first word when the second bit is an inverted bit; and performing, by the device, forward error correction on the word based on the selected first word. | 8. A method comprising: receiving, from an optical receiver and by a device, a word, of a block of words within traffic, on which to perform forward error correction, each word of the block of words including respective encoded bits and respective sets of reliability bits for identifying a respective level of reliability of each one of the respective encoded bits; identifying, by the device, least reliable positions, within the word, that correspond to a subset of encoded bits, within the word, associated with one or more lowest levels of reliability; generating, by the device, a set of candidate words based on different combinations in which the subset of encoded bits can be inverted; identifying, by the device, a first pair of candidate words, within the set of candidate words, the first pair including a first word and a second word, the first word including a first bit, the first bit not being an inverted bit and being most reliable within the subset of encoded bits associated with the first word; identifying, by the device, a first quantity of errors associated with the first word and a second quantity of errors associated with the second word; determining, by the device, whether the first quantity of errors is greater than the second quantity of errors; selecting, by the device, the first word when the first quantity of errors is not greater than the second quantity of errors; identifying, by the device, a second pair of candidate words, within selected words of the set of candidate words, the second pair including the first word and a third word, the third word including a second bit that is most reliable within the subset of encoded bits associated with the third word; determining, by the device, whether the second bit is an inverted bit; selecting, by the device, the first word when the second bit is an inverted bit; and performing, by the device, forward error correction on the word based on the selected first word. 11. The method of claim 8 , further comprising: identifying a distance between a fourth word, of the set of candidate words, and the first word; and discarding the fourth word based on a determination that the distance is based on a difference in inverted bits between the subset of encoded bits associated with the first word and a subset of encoded bits associated with the fourth word. | 0.739946 |
7,945,896 | 12 | 13 | 12. The method of claim 11 , wherein said step of registering further comprises: receiving by the middleware program a callback object, wherein said callback object directs requests from other distributed application components to said first distributed application component. | 12. The method of claim 11 , wherein said step of registering further comprises: receiving by the middleware program a callback object, wherein said callback object directs requests from other distributed application components to said first distributed application component. 13. The method of claim 12 , further comprising the step of, invoking by the middleware program said callback object to deliver said request to said first distributed application component. | 0.5 |
8,150,830 | 24 | 30 | 24. A computer program product, tangibly embodied on a machine readable medium, the computer program product comprising instructions that, when read by a machine, operate to cause data processing apparatus to: provide an association of a term and a primary resource identifier, the association input by a user; receive a search query input from a user; determine whether the search query matches the term; if the search query matches the term, present the primary resource identifier without initiating a search; and if the search query does not match the term, initiate a search and present a search result based on the search query. | 24. A computer program product, tangibly embodied on a machine readable medium, the computer program product comprising instructions that, when read by a machine, operate to cause data processing apparatus to: provide an association of a term and a primary resource identifier, the association input by a user; receive a search query input from a user; determine whether the search query matches the term; if the search query matches the term, present the primary resource identifier without initiating a search; and if the search query does not match the term, initiate a search and present a search result based on the search query. 30. The computer program product of claim 24 , wherein the search query is received in an address field of a browser. | 0.801695 |
9,683,862 | 7 | 10 | 7. A computer system for internationalization of navigation, the computer system comprising: one or more computer processors; one or more computer readable storage media; program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to receive, from a requestor, a request comprising a target destination and a native language; program instructions to retrieve, from a database, a plurality of keywords, wherein the plurality of keywords are associated with the native language and a destination language; program instructions to score each of the plurality of keywords; program instructions to determine whether a score associated with each of the plurality of keywords exceeds a threshold value; program instructions to, responsive to determining that a score associated with each of the plurality of keywords exceeds the threshold value, translate the plurality of keywords from the destination language to the native language; program instructions to send the translated plurality of keywords to the requestor, wherein the translated plurality of keywords are used to navigate to the target destination; program instructions to navigate to the target destination using GPS signals and the translated plurality of keywords; program instructions to receive location information associated with a destination; program instructions to retrieve social media data associated with the destination, based on a native language of a user; program instructions to extract a set of keywords associated with the destination; program instructions to translate the set of keywords associated with the destination to the native language; and program instructions to store the translated set of keywords associated with the destination, in a database. | 7. A computer system for internationalization of navigation, the computer system comprising: one or more computer processors; one or more computer readable storage media; program instructions stored on the one or more computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to receive, from a requestor, a request comprising a target destination and a native language; program instructions to retrieve, from a database, a plurality of keywords, wherein the plurality of keywords are associated with the native language and a destination language; program instructions to score each of the plurality of keywords; program instructions to determine whether a score associated with each of the plurality of keywords exceeds a threshold value; program instructions to, responsive to determining that a score associated with each of the plurality of keywords exceeds the threshold value, translate the plurality of keywords from the destination language to the native language; program instructions to send the translated plurality of keywords to the requestor, wherein the translated plurality of keywords are used to navigate to the target destination; program instructions to navigate to the target destination using GPS signals and the translated plurality of keywords; program instructions to receive location information associated with a destination; program instructions to retrieve social media data associated with the destination, based on a native language of a user; program instructions to extract a set of keywords associated with the destination; program instructions to translate the set of keywords associated with the destination to the native language; and program instructions to store the translated set of keywords associated with the destination, in a database. 10. The computer system of claim 7 , wherein the program instructions to score each of the plurality of keywords comprise: program instructions to retrieve a level of recognition of the plurality of keywords and a level of relevance of the plurality of keywords, wherein the level of recognition of the plurality of keywords is based in part on the native language of a user; and program instructions to generate a list of results, wherein each keyword from the list of results is associated with a recognition value score. | 0.5 |
8,037,357 | 23 | 24 | 23. The medium of claim 22 , further comprising instructions to load the procedures referenced by the plurality of jobs onto another file. | 23. The medium of claim 22 , further comprising instructions to load the procedures referenced by the plurality of jobs onto another file. 24. The medium of claim 23 , wherein the separate file and the another file comprise flat files. | 0.5 |
10,115,202 | 4 | 6 | 4. The apparatus of claim 1 , wherein the first cluster is a first set of one or more attributes of interest and the second cluster is a second set of attributes of interest. | 4. The apparatus of claim 1 , wherein the first cluster is a first set of one or more attributes of interest and the second cluster is a second set of attributes of interest. 6. The apparatus of claim 4 , wherein the first cluster represents two or more merged clusters. | 0.834495 |
7,917,460 | 16 | 17 | 16. A method for generating a decision network from a plurality of computer readable text documents, comprising: retrieving a given computer readable text document of the plurality of computer readable text documents from a memory of a computer system; reducing the given computer readable text document of the plurality of computer readable text documents into one or more text segments, the one or more text segments being stored in the memory; forming an evidence template in the memory for each of the one or more text segments, the forming comprising: identifying hedge words and qualifying words in the at least one text segment that relate to one or more words in the text segment, the one or more words comprising at least one of a noun, a pronoun and a verb; and assigning a confidence value to each identified hedge word and qualifying word in the at least one text segment, wherein each confidence value represents a degree of belief or disbelief for the one or more words related to each identified hedge word and qualifying word; and assigning each evidence template in the memory to one of a plurality of hypotheses stored in the memory by employing at least one classification technique, wherein each of the hypotheses are configured to define nodes in a given decision network generating a decision network from each evidence template and the plurality of hypotheses, such that each of the plurality hypotheses represent nodes in the decision network, wherein the decision network is stored in the memory; adding an additional hypothesis to the decision network that represents an additional node of the decision network, the additional hypothesis being associated with a previously generated decision network; and displaying the generated decision network to a user. | 16. A method for generating a decision network from a plurality of computer readable text documents, comprising: retrieving a given computer readable text document of the plurality of computer readable text documents from a memory of a computer system; reducing the given computer readable text document of the plurality of computer readable text documents into one or more text segments, the one or more text segments being stored in the memory; forming an evidence template in the memory for each of the one or more text segments, the forming comprising: identifying hedge words and qualifying words in the at least one text segment that relate to one or more words in the text segment, the one or more words comprising at least one of a noun, a pronoun and a verb; and assigning a confidence value to each identified hedge word and qualifying word in the at least one text segment, wherein each confidence value represents a degree of belief or disbelief for the one or more words related to each identified hedge word and qualifying word; and assigning each evidence template in the memory to one of a plurality of hypotheses stored in the memory by employing at least one classification technique, wherein each of the hypotheses are configured to define nodes in a given decision network generating a decision network from each evidence template and the plurality of hypotheses, such that each of the plurality hypotheses represent nodes in the decision network, wherein the decision network is stored in the memory; adding an additional hypothesis to the decision network that represents an additional node of the decision network, the additional hypothesis being associated with a previously generated decision network; and displaying the generated decision network to a user. 17. The method of claim 16 , further comprising scanning a paper document to form the given computer readable text document of the plurality of computer readable text documents, such that the given computer readable text document of the plurality of computer readable text documents is an optical character recognition conversion of the paper document. | 0.5 |
9,159,057 | 1 | 10 | 1. A method, comprising: scanning, by a computing apparatus, a set of messages of a user to identify a plurality of addresses; identifying, by the computing apparatus, names of persons at the addresses to generate a plurality of profiles for the persons, each profile of the plurality of profiles comprising a name of a respective person, and at least one address for the respective person; determining that the user has entered a first person in an address field of a new message being composed by the user; and computing, by the computing apparatus, scores of the persons using data in the plurality of profiles to determine relevancy of the persons to the user, wherein the scores are based at least in part on the determining that the user entered the first person in the address field, and wherein the computing the scores comprises applying a time-decay factor to each message of the set of messages. | 1. A method, comprising: scanning, by a computing apparatus, a set of messages of a user to identify a plurality of addresses; identifying, by the computing apparatus, names of persons at the addresses to generate a plurality of profiles for the persons, each profile of the plurality of profiles comprising a name of a respective person, and at least one address for the respective person; determining that the user has entered a first person in an address field of a new message being composed by the user; and computing, by the computing apparatus, scores of the persons using data in the plurality of profiles to determine relevancy of the persons to the user, wherein the scores are based at least in part on the determining that the user entered the first person in the address field, and wherein the computing the scores comprises applying a time-decay factor to each message of the set of messages. 10. The method of claim 1 , wherein the plurality of profiles contains prior associations between the persons, and the scores are further based on the prior associations. | 0.848214 |
8,126,308 | 2 | 6 | 2. The video signal processing apparatus according to claim 1 , wherein said predetermined language is a markup language. | 2. The video signal processing apparatus according to claim 1 , wherein said predetermined language is a markup language. 6. The video signal processing apparatus according to claim 2 , wherein said markup language is XML. | 0.8 |
8,914,414 | 7 | 12 | 7. A non-transitory storage medium storing computer instructions operable to cause one or more processors to perform operations comprising: receiving, from a client, a search request, the search request comprising a search query; performing a first search using the search query and one or more search indices stored on a server, the one or more search indices comprising a collection index generated from structured data and a document index generated from unstructured data; receiving, as a result of the first search, a collection of record identifiers, each record identifier comprising a tuple of data including a file identifier identifying a document that is hit by the first search in the unstructured data and a row identifier identifying a record in the structured data, the record having a data field referencing the document; performing a second search using the file identifier and the document index, including retrieving a search hit context from the document, the search hit context comprising one or more words in the document surrounding a term in the search query; merging the record identified by the row identifier and the search hit context into a search result; and providing the search result to the client as a response to the search request. | 7. A non-transitory storage medium storing computer instructions operable to cause one or more processors to perform operations comprising: receiving, from a client, a search request, the search request comprising a search query; performing a first search using the search query and one or more search indices stored on a server, the one or more search indices comprising a collection index generated from structured data and a document index generated from unstructured data; receiving, as a result of the first search, a collection of record identifiers, each record identifier comprising a tuple of data including a file identifier identifying a document that is hit by the first search in the unstructured data and a row identifier identifying a record in the structured data, the record having a data field referencing the document; performing a second search using the file identifier and the document index, including retrieving a search hit context from the document, the search hit context comprising one or more words in the document surrounding a term in the search query; merging the record identified by the row identifier and the search hit context into a search result; and providing the search result to the client as a response to the search request. 12. The non-transitory storage medium of claim 7 , the operations comprising: determining a content type of the document using a content type mapping table specifying a file extension name of the document and the content type corresponding to the file extension name; generating a thumbnail image of the document based on the content type; and providing the thumbnail image to the client in association with the search result. | 0.5 |
9,600,543 | 1 | 3 | 1. A machine-implemented method, comprising: receiving an indication of a request from a user to view a stream associated with the user; generating a request for one or more items, of a plurality of items, that are visible to the user for display within the stream, wherein each of the plurality of items includes one or more user tokens up to a threshold number of user tokens, the one or more user tokens indicate viewability of the item by users associated with the one or more user tokens, wherein the request comprises a search query identifying search criteria including one or more tokens up to a threshold number of tokens, the one or more tokens includes at least a user token identifying the user, and wherein generating the request comprises: determining that a super followee token is to be included in the search query, the super followee token corresponding to a super followee user that owns an item visible to a number of users that meets a threshold number of users, replacing the super followee token with a super doc token when the included super followee token causes the one or more tokens to exceed the threshold number of tokens, the super doc token identifying a type of item owned by the super followee user; receiving one or more items in response to the request, the one or more items including at least one of the one or more tokens and further being visible to the user; and providing the one or more items for display to the user within the stream in response to the request. | 1. A machine-implemented method, comprising: receiving an indication of a request from a user to view a stream associated with the user; generating a request for one or more items, of a plurality of items, that are visible to the user for display within the stream, wherein each of the plurality of items includes one or more user tokens up to a threshold number of user tokens, the one or more user tokens indicate viewability of the item by users associated with the one or more user tokens, wherein the request comprises a search query identifying search criteria including one or more tokens up to a threshold number of tokens, the one or more tokens includes at least a user token identifying the user, and wherein generating the request comprises: determining that a super followee token is to be included in the search query, the super followee token corresponding to a super followee user that owns an item visible to a number of users that meets a threshold number of users, replacing the super followee token with a super doc token when the included super followee token causes the one or more tokens to exceed the threshold number of tokens, the super doc token identifying a type of item owned by the super followee user; receiving one or more items in response to the request, the one or more items including at least one of the one or more tokens and further being visible to the user; and providing the one or more items for display to the user within the stream in response to the request. 3. The method of claim 1 , the one or more tokens further including at least one owner token, the owner token identifying a second user associated with the first user. | 0.878102 |
7,584,455 | 10 | 23 | 10. In a computer system, a method of modeling behavior of a computer program: generating a Boolean abstraction of the computer program, wherein the generating comprises deriving an initial plurality of predicates; wherein a predicate is derived from at least one of a conditional statement, an assertion, or a run-time safety check of the computer program; performing a state reachability analysis of the computer program, wherein performing the state reachability analysis comprises defining an upper bound for a set of reachable observable states in the computer program wherein the reachable observable states comprise an evaluation of a state of the predicate at a statement in the computer program; defining a lower bound for the set of reachable observable states in the computer program; using the upper bound and the lower bound to form a static coverage metric of the computer program, which measures an amount of test coverage; forming a behavior model of the computer program using the upper and lower bound, wherein forming the behavior model comprises outputting a set of oaths that covers states in the lower bound for the set of reachable observable states in the computer program; performing symbolic execution, wherein the symbolic execution determines whether the paths are feasible and generates inputs for the computer program to cover a path out of the paths when the path is feasible and comprises performing test generation of reachable states based at least in part on the behavior model wherein a percentage of reachable observable states are covered by a generated test; and adding new predicates to the initial plurality of predicates to increase percentage of reachable observable states covered by a generated test. | 10. In a computer system, a method of modeling behavior of a computer program: generating a Boolean abstraction of the computer program, wherein the generating comprises deriving an initial plurality of predicates; wherein a predicate is derived from at least one of a conditional statement, an assertion, or a run-time safety check of the computer program; performing a state reachability analysis of the computer program, wherein performing the state reachability analysis comprises defining an upper bound for a set of reachable observable states in the computer program wherein the reachable observable states comprise an evaluation of a state of the predicate at a statement in the computer program; defining a lower bound for the set of reachable observable states in the computer program; using the upper bound and the lower bound to form a static coverage metric of the computer program, which measures an amount of test coverage; forming a behavior model of the computer program using the upper and lower bound, wherein forming the behavior model comprises outputting a set of oaths that covers states in the lower bound for the set of reachable observable states in the computer program; performing symbolic execution, wherein the symbolic execution determines whether the paths are feasible and generates inputs for the computer program to cover a path out of the paths when the path is feasible and comprises performing test generation of reachable states based at least in part on the behavior model wherein a percentage of reachable observable states are covered by a generated test; and adding new predicates to the initial plurality of predicates to increase percentage of reachable observable states covered by a generated test. 23. The method of claim 10 wherein a reachable state is a state without an inherent logical contradiction between predicates. | 0.817251 |
7,991,607 | 10 | 11 | 10. A computer-implemented method of translating data, comprising: receiving one or more input data from one or more sensing sources, wherein the one or more sensing sources comprise at least one of audio, video, global positioning, or image sensing sources; generating context data of at least one of the one or more input data, the generating context data including: extracting text from at least one of the one or more input data to generate query terms and employing the query terms with a search engine to determine a first linguistic language; translating one or more results from the search engine into a translated output in a second linguistic language; presenting the translated output to a recipient in the second linguistic language that is understandable by the recipient; receiving a user feedback in the second linguistic language from the recipient, wherein the user feedback includes an indication that the translation is successful or unsuccessful; establishing the context of the at least one of the one or more input data based on the user feedback; and employing the established context as an additional input for translating the content. | 10. A computer-implemented method of translating data, comprising: receiving one or more input data from one or more sensing sources, wherein the one or more sensing sources comprise at least one of audio, video, global positioning, or image sensing sources; generating context data of at least one of the one or more input data, the generating context data including: extracting text from at least one of the one or more input data to generate query terms and employing the query terms with a search engine to determine a first linguistic language; translating one or more results from the search engine into a translated output in a second linguistic language; presenting the translated output to a recipient in the second linguistic language that is understandable by the recipient; receiving a user feedback in the second linguistic language from the recipient, wherein the user feedback includes an indication that the translation is successful or unsuccessful; establishing the context of the at least one of the one or more input data based on the user feedback; and employing the established context as an additional input for translating the content. 11. The method of claim 10 , further comprising an act of selecting the translated output to be formatted as audio signals in a form of speech in the second linguistic language. | 0.705 |
8,533,206 | 17 | 21 | 17. A computer program product including instructions, stored on a non-transitory computer-readable storage medium, that when executed by one or more computers, cause the one or more computers to perform operations comprising: maintaining a collection of uniform resource locator (URL) patterns, wherein each URL pattern is associated with a respective label; receiving a search query that includes a query term and a label of interest from a client device; generating, for the label of interest, a domain filter that satisfies a maximum size threshold and a maximum false positive error rate threshold, wherein generating the domain filter includes: iteratively adjusting a size of the domain filter, wherein in each iteration, the method comprises: identifying a new set of one or more URL patterns as a current set of offsets, wherein each of the one or more URL patterns is associated with a respective label that matches the label of interest; processing the URL patterns in the collection of URL patterns to generate an offset error for the current set of offsets; and determining whether or not the offset error for the current set of offsets is greater than an offset error for a best set of offsets, (i) and if so, performing a next iteration unless no new set of one or more URL patterns is identifiable, (ii) and otherwise, determining whether or not a current size of the domain filter satisfies the maximum size threshold and a current error rate for the domain filter satisfies the maximum false positive error rate threshold, (a) and if so, replacing values of the best set of offsets with values of the current set of offsets and performing the next iteration unless no new set of one or more URL patterns is identifiable, (b) and otherwise, performing the next iteration unless no new set of one or more URL patterns is identifiable; and upon determining that no new set of one or more URL patterns is identifiable, generating the domain filter for the label of interest using values of the best set of offsets; and filtering search results that are relevant to the query term with the domain filter to generate a plurality of filtered search results. | 17. A computer program product including instructions, stored on a non-transitory computer-readable storage medium, that when executed by one or more computers, cause the one or more computers to perform operations comprising: maintaining a collection of uniform resource locator (URL) patterns, wherein each URL pattern is associated with a respective label; receiving a search query that includes a query term and a label of interest from a client device; generating, for the label of interest, a domain filter that satisfies a maximum size threshold and a maximum false positive error rate threshold, wherein generating the domain filter includes: iteratively adjusting a size of the domain filter, wherein in each iteration, the method comprises: identifying a new set of one or more URL patterns as a current set of offsets, wherein each of the one or more URL patterns is associated with a respective label that matches the label of interest; processing the URL patterns in the collection of URL patterns to generate an offset error for the current set of offsets; and determining whether or not the offset error for the current set of offsets is greater than an offset error for a best set of offsets, (i) and if so, performing a next iteration unless no new set of one or more URL patterns is identifiable, (ii) and otherwise, determining whether or not a current size of the domain filter satisfies the maximum size threshold and a current error rate for the domain filter satisfies the maximum false positive error rate threshold, (a) and if so, replacing values of the best set of offsets with values of the current set of offsets and performing the next iteration unless no new set of one or more URL patterns is identifiable, (b) and otherwise, performing the next iteration unless no new set of one or more URL patterns is identifiable; and upon determining that no new set of one or more URL patterns is identifiable, generating the domain filter for the label of interest using values of the best set of offsets; and filtering search results that are relevant to the query term with the domain filter to generate a plurality of filtered search results. 21. The product of claim 17 , wherein the operations further comprise: determining a respective URL pattern length of each URL pattern in the collection of URL patterns, wherein the URL pattern length of a particular URL pattern is a value corresponding to a number of alphanumeric characters that appears after a domain name in the particular URL pattern. | 0.596372 |
8,984,476 | 8 | 10 | 8. A computer program product for target application creation, the computer program product comprising: a non-transitory computer recordable-type media containing computer executable program code stored thereon, the computer executable program code comprising: computer executable program code for receiving a representation of a logical topology diagram for an application architecture to form a source input; computer executable program code for locating part type information in a part type dictionary using the source input; computer executable program code for locating application parts in an application parts repository for each located part type; computer executable program code for composing a subset of identified parts; computer executable program code for determining whether integration dependencies are met; computer executable program code responsive to a determination that the integration dependencies are met, for consolidating parts into a first application structure; computer executable program code for determining whether to exclude parts from the first application structure; and computer executable program code responsive to a determination to exclude parts, excluding the parts from the first application structure to create a second application structure; and computer executable program code for building a target application based on the second application structure. | 8. A computer program product for target application creation, the computer program product comprising: a non-transitory computer recordable-type media containing computer executable program code stored thereon, the computer executable program code comprising: computer executable program code for receiving a representation of a logical topology diagram for an application architecture to form a source input; computer executable program code for locating part type information in a part type dictionary using the source input; computer executable program code for locating application parts in an application parts repository for each located part type; computer executable program code for composing a subset of identified parts; computer executable program code for determining whether integration dependencies are met; computer executable program code responsive to a determination that the integration dependencies are met, for consolidating parts into a first application structure; computer executable program code for determining whether to exclude parts from the first application structure; and computer executable program code responsive to a determination to exclude parts, excluding the parts from the first application structure to create a second application structure; and computer executable program code for building a target application based on the second application structure. 10. The computer program product of claim 8 wherein computer executable program code for composing a subset of identified parts further comprises: computer executable program code for determining whether the application parts representative of the source input are located; and computer executable program code responsive to a determination that the application parts representative of the source input are not located, for identifying required missing parts. | 0.744432 |
9,798,722 | 1 | 7 | 1. A method, comprising: establishing, by a processor, a communication, wherein the communication includes an audio communication from a first communication device; receiving, by the processor, an audio stream from the first communication device, wherein the audio stream comprises speech of a plurality of users of the first communication device; translating, by the processor, speech from the audio stream from the first communication device into a plurality of text streams, wherein the plurality of text streams are in different languages, and wherein each of the plurality of text streams in the different languages are directly translated from the audio stream from the first communication device; filtering, by the processor, a specific translated word, in a specific language, from a specific user of the plurality of users, in a specific one of the plurality of text steams based on a user definable list; and transmitting, by the processor, the plurality of text streams to at least one communication device involved in the communication. | 1. A method, comprising: establishing, by a processor, a communication, wherein the communication includes an audio communication from a first communication device; receiving, by the processor, an audio stream from the first communication device, wherein the audio stream comprises speech of a plurality of users of the first communication device; translating, by the processor, speech from the audio stream from the first communication device into a plurality of text streams, wherein the plurality of text streams are in different languages, and wherein each of the plurality of text streams in the different languages are directly translated from the audio stream from the first communication device; filtering, by the processor, a specific translated word, in a specific language, from a specific user of the plurality of users, in a specific one of the plurality of text steams based on a user definable list; and transmitting, by the processor, the plurality of text streams to at least one communication device involved in the communication. 7. The method of claim 1 , wherein each of the plurality of text streams are transmitted as individual characters. | 0.854592 |
4,553,860 | 1 | 8 | 1. A method of printing a plurality of documents based on a text, with alterations of phrases from one document to another in at least one phrase-inserting part of the text, comprising the steps of: storing into a phrase memory plural sets of phrase data representing plural different phrases to be inserted into the respective documents, said sets of phrase data being designated by respective phrase-indicating codes each consisting of at least one character the number of which is smaller than the number of characters constituting each of said plural different phrases; storing into a work memory at least one set of work data comprising selected plural ones of said phrase-indicating codes in such manner as to specify the order in which said phrase-indicating codes are read out, said work data being designated by a working-group code; storing into a text memory at least one set of text data representing a text of document, said text data including said working-group code at a position corresponding to said at least one phrase-inserting part of the text; printing out said text data to produce a first one of said plurality of documents, while upon reading of said working-group code, reading out from said phrase memory and printing out the first set of said phrase data designated by a first one of said phrase-indicating codes of said work data, so as to insert the first phrase into said at least one phrase-inserting part of the text of the first document; and printing out said text data to produce second and subsequent ones of said documents, while printing out second and subsequent sets of said phrase data which are designated by second and subsequent ones of said phrase-indicating codes of said work data, so as to insert the second and subsequent phrases into said at least one phrase-inserting part of the text of the second and subsequent documents. | 1. A method of printing a plurality of documents based on a text, with alterations of phrases from one document to another in at least one phrase-inserting part of the text, comprising the steps of: storing into a phrase memory plural sets of phrase data representing plural different phrases to be inserted into the respective documents, said sets of phrase data being designated by respective phrase-indicating codes each consisting of at least one character the number of which is smaller than the number of characters constituting each of said plural different phrases; storing into a work memory at least one set of work data comprising selected plural ones of said phrase-indicating codes in such manner as to specify the order in which said phrase-indicating codes are read out, said work data being designated by a working-group code; storing into a text memory at least one set of text data representing a text of document, said text data including said working-group code at a position corresponding to said at least one phrase-inserting part of the text; printing out said text data to produce a first one of said plurality of documents, while upon reading of said working-group code, reading out from said phrase memory and printing out the first set of said phrase data designated by a first one of said phrase-indicating codes of said work data, so as to insert the first phrase into said at least one phrase-inserting part of the text of the first document; and printing out said text data to produce second and subsequent ones of said documents, while printing out second and subsequent sets of said phrase data which are designated by second and subsequent ones of said phrase-indicating codes of said work data, so as to insert the second and subsequent phrases into said at least one phrase-inserting part of the text of the second and subsequent documents. 8. A method as recited in claim 1, further comprising the step of indicating alternately at predetermined intervals said phrase-indicating code, and a predetermined number of leading characters of said phrase data designated by the phrase-indicating code, when the phrase-indicating code is entered after the phrase data has been stored in the phrase memory. | 0.800668 |
9,690,780 | 13 | 16 | 13. A computer system for document analysis, the computer system comprising: one or more computer processors; one or more computer readable storage media; and program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to receive a request to translate a document; program instructions to determine usage information corresponding to the document, wherein the usage information includes information corresponding to a current viewing session of the document for a user, and a mode of usage corresponding to the current viewing session of the document, the mode of usage indicating user activity that corresponds to how the user is currently interacting with the document in the current viewing session of the document, and the mode of usage indicating at least a speed at which the user is scrolling through the document, and wherein the usage information includes historical usage information corresponding to one or more previous viewing sessions of the document; and program instructions to determine one or more sections of the document to translate based on the determined usage information corresponding to the document, wherein the program instructions to determine one or more sections of the document to translate based on the determined usage information corresponding to the document, further comprise program instructions to: determine a probability corresponding to each section of the one or more sections of the document that indicate the probability that a user will access and view a respective section of the document, wherein the probabilities are determined based on at least: the determined usage information corresponding to the document, data indicating relationships of sections of the document, and browsing history of the document; and determine the one or more sections of the document to translate, wherein the one or more sections of the document to translate each have a determined corresponding probability exceeding a minimum threshold condition. | 13. A computer system for document analysis, the computer system comprising: one or more computer processors; one or more computer readable storage media; and program instructions stored on the computer readable storage media for execution by at least one of the one or more processors, the program instructions comprising: program instructions to receive a request to translate a document; program instructions to determine usage information corresponding to the document, wherein the usage information includes information corresponding to a current viewing session of the document for a user, and a mode of usage corresponding to the current viewing session of the document, the mode of usage indicating user activity that corresponds to how the user is currently interacting with the document in the current viewing session of the document, and the mode of usage indicating at least a speed at which the user is scrolling through the document, and wherein the usage information includes historical usage information corresponding to one or more previous viewing sessions of the document; and program instructions to determine one or more sections of the document to translate based on the determined usage information corresponding to the document, wherein the program instructions to determine one or more sections of the document to translate based on the determined usage information corresponding to the document, further comprise program instructions to: determine a probability corresponding to each section of the one or more sections of the document that indicate the probability that a user will access and view a respective section of the document, wherein the probabilities are determined based on at least: the determined usage information corresponding to the document, data indicating relationships of sections of the document, and browsing history of the document; and determine the one or more sections of the document to translate, wherein the one or more sections of the document to translate each have a determined corresponding probability exceeding a minimum threshold condition. 16. The computer system of claim 13 , wherein the historical usage information corresponding to previous viewing sessions of the document includes previous usage information associated with a current user of the document and statistical information indicating previous navigation paths through sections of the document taken by previous users of the document. | 0.760347 |
9,367,522 | 21 | 29 | 21. A non-transitory computer readable medium storing computer executable instructions, which, when executed by a processor, cause the processor to carry out a method for editing an electronic presentation, comprising: providing an electronic presentation editing interface for editing an electronic presentation, wherein the interface comprises: a digital canvas comprising a plurality of canvas objects in a plurality of canvas layers; a digital timeline comprising a plurality of timeline objects, a time axis, and a graphical indicia on the time axis that represents a pause in the electronic presentation, wherein: each canvas object in the plurality of canvas objects is linked to a respective timeline object; a position of a timeline object on the digital timeline is indicative of a time and a canvas layer that a linked canvas object is displayed on the digital canvas; the position of the timeline object includes a first time coordinate on the time axis indicative of when the linked canvas object appears in the digital canvas, a second time coordinate on the time axis indicative of when the linked canvas object disappears from the digital canvas, and a layer coordinate indicative of a canvas layer in which the linked canvas object appears in the digital canvas; the graphical indicia extends over all layer coordinates that are displayed in the digital timeline; and the digital timeline further comprises a marker on the digital timeline, wherein a position of the marker is indicative of a time corresponding to a current view of the digital canvas, and wherein when the position of the marker coincides with the graphical indicia on the time axis, each canvas object linked to a timeline object that coincides with the position of the marker is paused. | 21. A non-transitory computer readable medium storing computer executable instructions, which, when executed by a processor, cause the processor to carry out a method for editing an electronic presentation, comprising: providing an electronic presentation editing interface for editing an electronic presentation, wherein the interface comprises: a digital canvas comprising a plurality of canvas objects in a plurality of canvas layers; a digital timeline comprising a plurality of timeline objects, a time axis, and a graphical indicia on the time axis that represents a pause in the electronic presentation, wherein: each canvas object in the plurality of canvas objects is linked to a respective timeline object; a position of a timeline object on the digital timeline is indicative of a time and a canvas layer that a linked canvas object is displayed on the digital canvas; the position of the timeline object includes a first time coordinate on the time axis indicative of when the linked canvas object appears in the digital canvas, a second time coordinate on the time axis indicative of when the linked canvas object disappears from the digital canvas, and a layer coordinate indicative of a canvas layer in which the linked canvas object appears in the digital canvas; the graphical indicia extends over all layer coordinates that are displayed in the digital timeline; and the digital timeline further comprises a marker on the digital timeline, wherein a position of the marker is indicative of a time corresponding to a current view of the digital canvas, and wherein when the position of the marker coincides with the graphical indicia on the time axis, each canvas object linked to a timeline object that coincides with the position of the marker is paused. 29. The non-transitory computer readable medium of claim 21 , wherein a canvas object in the plurality of canvas objects comprises a shape, a portion of text, a figure, a hyperlink, a background, an image, a graphic, a video file, or an audio file. | 0.793333 |
7,630,959 | 6 | 7 | 6. The method of claim 1 , further comprising mapping the retrieved information objects into corresponding mapped information objects. | 6. The method of claim 1 , further comprising mapping the retrieved information objects into corresponding mapped information objects. 7. The method of claim 6 , wherein the corresponding mapped information objects are numbers corresponding to the retrieved information objects. | 0.5 |
5,555,343 | 64 | 65 | 64. A text-to-speech processing apparatus according to claim 59, wherein said look-up table is comprised by format templates. | 64. A text-to-speech processing apparatus according to claim 59, wherein said look-up table is comprised by format templates. 65. A text-to-speech processing apparatus according to claim 64, wherein said format templates further include speech commands having embedded pre-designated text, and wherein text is generated based on said embedded pre-designated text. | 0.5 |
9,245,278 | 38 | 41 | 38. A method comprising: one or more computer processors programmed to perform operations comprising: obtaining an original text message in a first language authored by a first user: obtaining an initial translation of the original text message in a second language; obtaining a translation correction of the initial translation, wherein the translation correction is authored by a second user; calculating at least one metric associated with the translation correction, the at least one metric being based on a comparison of a language-based feature of the original text and the translation correction, wherein the at least one metric is based on the comparison of the language-based feature, and wherein calculating the at least one metric comprises determining a difference in a number of occurrences of a part of speech in the original text and in the translation correction; and determining an accuracy of the translation correction based on the at least one metric. | 38. A method comprising: one or more computer processors programmed to perform operations comprising: obtaining an original text message in a first language authored by a first user: obtaining an initial translation of the original text message in a second language; obtaining a translation correction of the initial translation, wherein the translation correction is authored by a second user; calculating at least one metric associated with the translation correction, the at least one metric being based on a comparison of a language-based feature of the original text and the translation correction, wherein the at least one metric is based on the comparison of the language-based feature, and wherein calculating the at least one metric comprises determining a difference in a number of occurrences of a part of speech in the original text and in the translation correction; and determining an accuracy of the translation correction based on the at least one metric. 41. The system of claim 38 wherein the operations further comprise: offering an incentive to the second user to provide the translation correction; and rewarding the second user with the respective incentive when the translation correction is determined to be accurate. | 0.579688 |
10,135,955 | 1 | 3 | 1. A method to control compression of data for transmission over a serial data link, the method comprising: adjusting, at a parameter estimation processor, a target compression ratio by a first compression ratio to determine a remaining compression ratio, wherein the first compression ratio was performed by a resampling operation; estimating, at the parameter estimation processor, a set of compression parameters that are used to achieve the remaining compression ratio, the set of compression parameters includes N attenuation values, a filter order and a type of encoding; and sending the set of compression parameters to a data sample compressor, the data sample compressor applies the compression parameters to a packet of input data and outputs a plurality of compressed data words, and wherein an attenuator of the data sample compressor divides the packet of input data into N segments and applies an attenuation value from the set of N attenuation values to the data samples in one of the N segments. | 1. A method to control compression of data for transmission over a serial data link, the method comprising: adjusting, at a parameter estimation processor, a target compression ratio by a first compression ratio to determine a remaining compression ratio, wherein the first compression ratio was performed by a resampling operation; estimating, at the parameter estimation processor, a set of compression parameters that are used to achieve the remaining compression ratio, the set of compression parameters includes N attenuation values, a filter order and a type of encoding; and sending the set of compression parameters to a data sample compressor, the data sample compressor applies the compression parameters to a packet of input data and outputs a plurality of compressed data words, and wherein an attenuator of the data sample compressor divides the packet of input data into N segments and applies an attenuation value from the set of N attenuation values to the data samples in one of the N segments. 3. The method of claim 1 , wherein the sending changes the set of compression parameters for the packet-of input data. | 0.827485 |
8,775,184 | 12 | 15 | 12. A computer program product comprising a tangible computer readable storage memory device having computer readable program code for evaluating one or more spoken language skills of a speaker, said computer program product including: computer readable program code for identifying one or more temporal locations of interest in an output of a spoken language skill evaluation performed on a speech passage spoken by a speaker; computer readable program code for computing one or more acoustic parameters to capture one or more properties of one or more acoustic-phonetic features of the one or more locations of interest, said computing comprising determining one or more spectral differences between the onset of a fricative, a vowel and a stop burst by computing a ratio of energy in a high frequency region of the speech passage to energy in a low frequency region of the speech passage over a predetermined time period via 1 N f ∑ f = 1 N f [ Δ ( f , l ) - μΔ , l ] 2 , wherein f is a given frequency channel, N f is a total number of frequency channels, l is a given frame number, Δ(f, l) is an energy difference in adjacent frames for the given frequency channel f, and μΔ,l is the mean of Δ (f, l) over all frequency channels for the given l; and computer readable program code for combining the one or more acoustic parameters with the output of an automatic speech recognizer to generate a modified output of the spoken language skill evaluation. | 12. A computer program product comprising a tangible computer readable storage memory device having computer readable program code for evaluating one or more spoken language skills of a speaker, said computer program product including: computer readable program code for identifying one or more temporal locations of interest in an output of a spoken language skill evaluation performed on a speech passage spoken by a speaker; computer readable program code for computing one or more acoustic parameters to capture one or more properties of one or more acoustic-phonetic features of the one or more locations of interest, said computing comprising determining one or more spectral differences between the onset of a fricative, a vowel and a stop burst by computing a ratio of energy in a high frequency region of the speech passage to energy in a low frequency region of the speech passage over a predetermined time period via 1 N f ∑ f = 1 N f [ Δ ( f , l ) - μΔ , l ] 2 , wherein f is a given frequency channel, N f is a total number of frequency channels, l is a given frame number, Δ(f, l) is an energy difference in adjacent frames for the given frequency channel f, and μΔ,l is the mean of Δ (f, l) over all frequency channels for the given l; and computer readable program code for combining the one or more acoustic parameters with the output of an automatic speech recognizer to generate a modified output of the spoken language skill evaluation. 15. The computer program product of claim 12 , wherein the one or more spoken language skills of a speaker comprise at least one of grammatical skill of the speaker and pronunciation skill of the speaker. | 0.678233 |
9,449,288 | 5 | 6 | 5. The method of claim 1 , further comprising classifying a first bucket, the classifying based on a model function of the first bucket. | 5. The method of claim 1 , further comprising classifying a first bucket, the classifying based on a model function of the first bucket. 6. The method of claim 5 , wherein the classifying of the first bucket is further based on attributes associated with the travel options. | 0.5 |
9,240,016 | 17 | 18 | 17. The method of claim 1 , further comprising: performing a join operation against two or more tables within the host organization and accessible to the authenticated subscriber; capturing the output of the join operation as the dataset of rows and columns; and processing the dataset to generate the indices representing the probabilistic relationships between the rows and the columns of the dataset. | 17. The method of claim 1 , further comprising: performing a join operation against two or more tables within the host organization and accessible to the authenticated subscriber; capturing the output of the join operation as the dataset of rows and columns; and processing the dataset to generate the indices representing the probabilistic relationships between the rows and the columns of the dataset. 18. The method of claim 17 , wherein the authenticated subscriber specifies the two or more tables as input and wherein the host organization generates a query to perform the join operation and automatically initiates processing against the dataset on behalf of the authenticated subscriber. | 0.5 |
8,712,317 | 15 | 16 | 15. A system in accordance with claim 13 , wherein an assessor icon is displayed, the computer further performing the step of activating the assessor icon to reveal a list of assessors. | 15. A system in accordance with claim 13 , wherein an assessor icon is displayed, the computer further performing the step of activating the assessor icon to reveal a list of assessors. 16. A system in accordance with claim 15 , wherein each assessor listed in said list of assessors has a color associated therewith, the outcome statement placed on the representation of the coursework answer appearing in said color. | 0.5 |
9,367,629 | 1 | 2 | 1. A method comprising, by a computing device: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; generating a plurality of cards, each card comprising a suggested query referencing a query-domain associated with the online social network and zero or more query-filters for the query-domain, wherein each query-filter references one or more nodes of the plurality of nodes or one or more edges of the plurality of edges; calculating a card-affinity for each card of the plurality of cards with respect to the other cards of the plurality of cards; generating one or more card clusters from the plurality of cards, each card cluster comprising one or more cards that each have a card-affinity with respect to the other cards in the card cluster that is greater than a threshold card-affinity; and sending one or more card clusters to the first user for display on a page currently accessed by the first user. | 1. A method comprising, by a computing device: accessing a social graph comprising a plurality of nodes and a plurality of edges connecting the nodes, each of the edges between two of the nodes representing a single degree of separation between them, the nodes comprising: a first node corresponding to a first user associated with an online social network; and a plurality of second nodes that each correspond to a concept or a second user associated with the online social network; generating a plurality of cards, each card comprising a suggested query referencing a query-domain associated with the online social network and zero or more query-filters for the query-domain, wherein each query-filter references one or more nodes of the plurality of nodes or one or more edges of the plurality of edges; calculating a card-affinity for each card of the plurality of cards with respect to the other cards of the plurality of cards; generating one or more card clusters from the plurality of cards, each card cluster comprising one or more cards that each have a card-affinity with respect to the other cards in the card cluster that is greater than a threshold card-affinity; and sending one or more card clusters to the first user for display on a page currently accessed by the first user. 2. The method of claim 1 , further comprising modifying one or more of the query-filters of one or more cards of the card cluster based on previous actions of the first user in relation to one or more of the cards. | 0.712366 |
9,002,873 | 1 | 5 | 1. A method of filtering a corpus of documents relevant to a litigation, comprising: identifying the corpus of documents to be filtered, wherein the documents are relevant to a litigation; generating a first modifiable query, wherein the first modifiable query comprises desired characteristics of the documents in the corpus; filtering the corpus of documents in accordance with the first modifiable query into a first result set; naming the first result set of the first modifiable query with a first name that identifies the first result set; generating a second modifiable query, wherein the second modifiable query comprises desired characteristics of the documents in the first result set; filtering the first result set in accordance with the second modifiable query to generate a second result set based on the first modifiable query and the second modifiable query, the filtering the first result set further comprising: applying the second modifiable query to the first result set by using the first result set, specified by the first name that identifies the first result set, as a source of documents for the applying the second modifiable query; naming the second result set with a second name that identifies the second result set; labeling elements of the second result set with the second name that identifies the second result set, wherein the labeling enables presentation of the first and second modifiable queries in response to a user selection; determining a change in either the first modifiable query or second modifiable query; and automatically updating the second result set, without additional user involvement, to reflect the change in either the first modifiable query or the second modifiable query. | 1. A method of filtering a corpus of documents relevant to a litigation, comprising: identifying the corpus of documents to be filtered, wherein the documents are relevant to a litigation; generating a first modifiable query, wherein the first modifiable query comprises desired characteristics of the documents in the corpus; filtering the corpus of documents in accordance with the first modifiable query into a first result set; naming the first result set of the first modifiable query with a first name that identifies the first result set; generating a second modifiable query, wherein the second modifiable query comprises desired characteristics of the documents in the first result set; filtering the first result set in accordance with the second modifiable query to generate a second result set based on the first modifiable query and the second modifiable query, the filtering the first result set further comprising: applying the second modifiable query to the first result set by using the first result set, specified by the first name that identifies the first result set, as a source of documents for the applying the second modifiable query; naming the second result set with a second name that identifies the second result set; labeling elements of the second result set with the second name that identifies the second result set, wherein the labeling enables presentation of the first and second modifiable queries in response to a user selection; determining a change in either the first modifiable query or second modifiable query; and automatically updating the second result set, without additional user involvement, to reflect the change in either the first modifiable query or the second modifiable query. 5. The method of claim 1 , wherein each modifiable query may be used on separate document sets. | 0.679054 |
9,665,499 | 1 | 3 | 1. A computer program product for facilitating memory access, said computer program product comprising: a non-transitory computer readable storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: providing a first partition within a system configuration, the first partition configured to support an operating system (OS) designed for a first address translation architecture, wherein configuration of the first partition to support the OS designed for the first address translation architecture is indicated in configuration information in a configuration data structure, and wherein the first partition is not configured to support an OS designed for a second address translation architecture; providing a second partition within the system configuration, the second partition configured to support the OS designed for the second address translation architecture, wherein configuration of the second partition to support the OS designed for the second address translation architecture is indicated in the configuration information in the configuration data structure, wherein the second partition is not configured to support the OS designed for the first address translation architecture, wherein the first address translation architecture is structurally different from the second address translation architecture; based on obtaining, as part of an address translation request of the first partition or second partition, an address for translation, determining, based on the configuration information in the configuration data structure, an address translation architecture to use to translate the address; and translating the address via the determined address translation architecture. | 1. A computer program product for facilitating memory access, said computer program product comprising: a non-transitory computer readable storage medium readable by a processing circuit and storing instructions for execution by the processing circuit for performing a method comprising: providing a first partition within a system configuration, the first partition configured to support an operating system (OS) designed for a first address translation architecture, wherein configuration of the first partition to support the OS designed for the first address translation architecture is indicated in configuration information in a configuration data structure, and wherein the first partition is not configured to support an OS designed for a second address translation architecture; providing a second partition within the system configuration, the second partition configured to support the OS designed for the second address translation architecture, wherein configuration of the second partition to support the OS designed for the second address translation architecture is indicated in the configuration information in the configuration data structure, wherein the second partition is not configured to support the OS designed for the first address translation architecture, wherein the first address translation architecture is structurally different from the second address translation architecture; based on obtaining, as part of an address translation request of the first partition or second partition, an address for translation, determining, based on the configuration information in the configuration data structure, an address translation architecture to use to translate the address; and translating the address via the determined address translation architecture. 3. The computer program product of claim 1 , wherein the first address translation architecture uses a hash structure and the second address translation architecture uses a hierarchical table structure. | 0.708934 |
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