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9,679,256 | 5 | 6 | 5. The method of claim 1 , further comprising analyzing one or more training texts to generate the training linguistic vectors. | 5. The method of claim 1 , further comprising analyzing one or more training texts to generate the training linguistic vectors. 6. The method of claim 5 wherein analyzing the one or more training texts comprises performing one or more lexical, part-of-speech, or parsing analyses on the training texts. | 0.977219 |
9,582,503 | 13 | 17 | 13. A computer-readable storage device comprising instructions, which when executed at least in part via a processing unit perform a method, comprising: identifying a first unique term in a document authored by a user, wherein the document is part of a document corpus and the first unique term is identified by the frequency of use of the first unique term in the document corpus; providing to the user a first notification indicating multiple semantic concepts associated with the first unique term; receiving a selection, by the user, of a first semantic concept in the multiple semantic concepts; in response to receiving the selection, generating a first query to identify a set of semantic concepts comprising the first semantic concept associated with the first unique term and a second semantic concept associated with the first unique term; providing, for display to the user, a second notification indicative of the set of semantic concepts comprising the first semantic concept and the second semantic concept, the first unique term not comprising the first semantic concept and not comprising the second semantic concept; receiving a selection, by the user, of the first semantic concept in the set of semantic concepts; and responsive to the receiving, associating the first semantic concept with the first unique term as an annotation to the first unique term such that the first unique term remains visible in the document after the associating. | 13. A computer-readable storage device comprising instructions, which when executed at least in part via a processing unit perform a method, comprising: identifying a first unique term in a document authored by a user, wherein the document is part of a document corpus and the first unique term is identified by the frequency of use of the first unique term in the document corpus; providing to the user a first notification indicating multiple semantic concepts associated with the first unique term; receiving a selection, by the user, of a first semantic concept in the multiple semantic concepts; in response to receiving the selection, generating a first query to identify a set of semantic concepts comprising the first semantic concept associated with the first unique term and a second semantic concept associated with the first unique term; providing, for display to the user, a second notification indicative of the set of semantic concepts comprising the first semantic concept and the second semantic concept, the first unique term not comprising the first semantic concept and not comprising the second semantic concept; receiving a selection, by the user, of the first semantic concept in the set of semantic concepts; and responsive to the receiving, associating the first semantic concept with the first unique term as an annotation to the first unique term such that the first unique term remains visible in the document after the associating. 17. The computer-readable storage device of claim 13 , the first semantic concept corresponding to a link to a webpage comprising content associated with the first unique term. | 0.825397 |
7,552,398 | 16 | 20 | 16. A system for semantically zooming information for display comprising: a database that maintains citations, which each citation semantically represents a textual document and each citation comprises a plurality of sections, wherein each section comprises data associated with characteristic information, the characteristic information comprises at least one of a role and data type in the citation associated with that section; a memory; and a processor that determines bounds of a display area; different length representations of the data for each section in one or more of the citations based on the characteristic information, wherein the different length representations reflect an application of various reduction transformations to the plurality of sections and a semantic zoom display of the one or more citations, wherein the semantic zoom display is determined by selecting one of the different length representations for each of the plurality of sections in the one or more citations based on the bounds of the display area, by combining the selected different length representations as the semantic zoom display of the one or more citations, and by presenting the semantic zoom display of the one or more citations for the textual document in the display area. | 16. A system for semantically zooming information for display comprising: a database that maintains citations, which each citation semantically represents a textual document and each citation comprises a plurality of sections, wherein each section comprises data associated with characteristic information, the characteristic information comprises at least one of a role and data type in the citation associated with that section; a memory; and a processor that determines bounds of a display area; different length representations of the data for each section in one or more of the citations based on the characteristic information, wherein the different length representations reflect an application of various reduction transformations to the plurality of sections and a semantic zoom display of the one or more citations, wherein the semantic zoom display is determined by selecting one of the different length representations for each of the plurality of sections in the one or more citations based on the bounds of the display area, by combining the selected different length representations as the semantic zoom display of the one or more citations, and by presenting the semantic zoom display of the one or more citations for the textual document in the display area. 20. The system of claim 16 , in which the citations each comprise at least one of reference, descriptive and bibliographic information. | 0.799107 |
7,692,573 | 9 | 10 | 9. The computer readable storage medium of claim 1 , wherein a weight w j for a j th candidate target is based upon a minimal required speed s j =max[s 1 ,s 2 ], where s 1 is the speed-of-advance for the candidate target to travel from a point P 1 to a point P that is subject to both obstacle avoidance and status transition time constraints, where point P 1 is the “just before target history location” for the j th candidate target and where point P is a target location provided by the sensor data, and s 2 is the speed-of-advance for the candidate target to travel from the point P to a point P 2 that is subject to both obstacle avoidance and status transition time constraints, where point P 2 is the “just after target location” for the j th candidate target. | 9. The computer readable storage medium of claim 1 , wherein a weight w j for a j th candidate target is based upon a minimal required speed s j =max[s 1 ,s 2 ], where s 1 is the speed-of-advance for the candidate target to travel from a point P 1 to a point P that is subject to both obstacle avoidance and status transition time constraints, where point P 1 is the “just before target history location” for the j th candidate target and where point P is a target location provided by the sensor data, and s 2 is the speed-of-advance for the candidate target to travel from the point P to a point P 2 that is subject to both obstacle avoidance and status transition time constraints, where point P 2 is the “just after target location” for the j th candidate target. 10. The computer readable storage medium of claim 9 , wherein if s j ≦s max-sustainable , where s max-sustainable is a maximum speed of the j th candidate target that can be sustained over an indefinite period of time, then w j =w 1 . | 0.952497 |
8,374,996 | 1 | 6 | 1. A computer-implemented method for identifying contact information for an author of content that is relevant to a topic of interest to a user, the method comprising: receiving, by one or more processors at a first computing system and from a second computing system that is distinct from the first computing system, an indication of a topic of interest to a user; accessing, from a computer memory storage system, multiple pieces of content; in response to receiving the indication of the topic of interest, comparing the indication of the topic of interest to the multiple pieces of content accessed from the computer memory storage system; based on results of comparing the indication of the topic of interest to the multiple pieces of content accessed from the computer memory storage system, identifying a piece of content as being relevant to the topic of interest, wherein identifying a piece of content as being relevant to the topic of interest includes: identifying a first piece of content as being relevant to the topic of interest, and identifying a second piece of content as being relevant to the topic of interest, the second piece of content being different from the first piece of content; in response to identifying the piece of content as being relevant to the topic of interest, identifying an identifier for an author of the piece of content identified as being relevant to the topic of interest, wherein identifying an identifier for an author of the piece of content identified as being relevant to the topic of interest includes: identifying a byline for the first piece of content, the byline for the first piece of content specifying an identifier for an author who authored the first piece of content and a first media outlet in which the first piece of content appeared, and identifying a byline for the second piece of content, the byline for the second piece of content specifying an identifier for an author who authored the second piece of content and a second media outlet in which the second piece of content appeared, the second media outlet being different from the first media outlet and the identifier for the author who authored the second piece of content being the same as the identifier for the author who authored the first piece of content; accessing, from the computer memory storage system, contact information for each of multiple authors including identifiers therefor; comparing the identifier for the author to the identifiers included in the accessed contact information; based on results of comparing the identifier for the author to the identifiers included in the accessed contact information, identifying contact information corresponding to the author from within the accessed contact information, wherein identifying contact information corresponding to the author from within the accessed contact information includes identifying contact information at the first media outlet corresponding to the author; and returning, to the second computing system, an indication of the identity of the author and at least some of the identified contact information corresponding to the author, wherein returning, to the second computing system, at least some of the identified contact information corresponding to the author includes returning, to the second computing system, at least some of the identified contact information at the first media outlet corresponding to the author. | 1. A computer-implemented method for identifying contact information for an author of content that is relevant to a topic of interest to a user, the method comprising: receiving, by one or more processors at a first computing system and from a second computing system that is distinct from the first computing system, an indication of a topic of interest to a user; accessing, from a computer memory storage system, multiple pieces of content; in response to receiving the indication of the topic of interest, comparing the indication of the topic of interest to the multiple pieces of content accessed from the computer memory storage system; based on results of comparing the indication of the topic of interest to the multiple pieces of content accessed from the computer memory storage system, identifying a piece of content as being relevant to the topic of interest, wherein identifying a piece of content as being relevant to the topic of interest includes: identifying a first piece of content as being relevant to the topic of interest, and identifying a second piece of content as being relevant to the topic of interest, the second piece of content being different from the first piece of content; in response to identifying the piece of content as being relevant to the topic of interest, identifying an identifier for an author of the piece of content identified as being relevant to the topic of interest, wherein identifying an identifier for an author of the piece of content identified as being relevant to the topic of interest includes: identifying a byline for the first piece of content, the byline for the first piece of content specifying an identifier for an author who authored the first piece of content and a first media outlet in which the first piece of content appeared, and identifying a byline for the second piece of content, the byline for the second piece of content specifying an identifier for an author who authored the second piece of content and a second media outlet in which the second piece of content appeared, the second media outlet being different from the first media outlet and the identifier for the author who authored the second piece of content being the same as the identifier for the author who authored the first piece of content; accessing, from the computer memory storage system, contact information for each of multiple authors including identifiers therefor; comparing the identifier for the author to the identifiers included in the accessed contact information; based on results of comparing the identifier for the author to the identifiers included in the accessed contact information, identifying contact information corresponding to the author from within the accessed contact information, wherein identifying contact information corresponding to the author from within the accessed contact information includes identifying contact information at the first media outlet corresponding to the author; and returning, to the second computing system, an indication of the identity of the author and at least some of the identified contact information corresponding to the author, wherein returning, to the second computing system, at least some of the identified contact information corresponding to the author includes returning, to the second computing system, at least some of the identified contact information at the first media outlet corresponding to the author. 6. The method of claim 1 wherein: the piece of content identified as being relevant to the topic of interest includes a byline specifying an identifier for the author of the piece of content and a media outlet in which the piece of content appeared; identifying an identifier for the author of the piece of content identified as being relevant to the topic of interest includes identifying a unique identifier for the byline for the piece of content identified as being relevant to the topic of interest; accessing, from a computer memory storage system, contact information for each of multiple authors includes accessing, from the computer memory storage system, database entries that link unique identifiers for bylines of individual pieces of content to corresponding contact information for the authors of the individual pieces of content; comparing the identifier for the author to the identifiers included in the accessed contact information includes comparing the unique identifier for the byline for the piece of content identified as being relevant to the topic of interest to the unique identifiers for bylines included within the accessed database entries; and identifying contact information corresponding to the author from within the accessed contact information based on results of comparing the identifier for the author to the identifiers included in the accessed contact information includes: determining that the unique identifier for the byline for the piece of content identified as being relevant to the topic of interest matches a particular one of the unique identifiers for bylines included within the accessed database entries, and identifying the contact information to which the particular one of the unique identifiers is linked by the database entries as contact information for the author. | 0.711227 |
9,424,167 | 1 | 9 | 1. A method for automatically testing an application system graphical user interface (GUI), the method comprising: retrieving, in a computer communicatively connected to an application server providing the application system, a GUI page provided by the application server as part of the application system; automatically identifying, based on image-analysis of an image of the retrieved GUI page, a plurality of text elements of the GUI page; automatically identifying, based on image-analysis of the image of the retrieved GUI page, a plurality of user input objects of the GUI page; automatically associating with each of the plurality of automatically identified user input objects a text element of the plurality of automatically identified text elements; retrieving, based on the text elements associated with each of the plurality of user input objects, a plurality of test parameter values from a database storing test parameter data, wherein each test parameter value of the plurality of test parameter values is associated in the database storing test parameter data with a corresponding text element associated with one of the plurality of user input objects; testing the application system provided by the application server by, for each respective user input object identified in the GUI page, performing a function to: provide, in the respective user input object of the GUI page, the respective test parameter value that is associated in the database storing test parameter data with a same text element as is associated with the respective user input object of the GUI page; and monitoring a response of the application system to the providing of the respective test parameter value to each user input object identified in the GUI page. | 1. A method for automatically testing an application system graphical user interface (GUI), the method comprising: retrieving, in a computer communicatively connected to an application server providing the application system, a GUI page provided by the application server as part of the application system; automatically identifying, based on image-analysis of an image of the retrieved GUI page, a plurality of text elements of the GUI page; automatically identifying, based on image-analysis of the image of the retrieved GUI page, a plurality of user input objects of the GUI page; automatically associating with each of the plurality of automatically identified user input objects a text element of the plurality of automatically identified text elements; retrieving, based on the text elements associated with each of the plurality of user input objects, a plurality of test parameter values from a database storing test parameter data, wherein each test parameter value of the plurality of test parameter values is associated in the database storing test parameter data with a corresponding text element associated with one of the plurality of user input objects; testing the application system provided by the application server by, for each respective user input object identified in the GUI page, performing a function to: provide, in the respective user input object of the GUI page, the respective test parameter value that is associated in the database storing test parameter data with a same text element as is associated with the respective user input object of the GUI page; and monitoring a response of the application system to the providing of the respective test parameter value to each user input object identified in the GUI page. 9. The method of claim 1 , wherein the monitoring of the response of the application system comprises storing a log of monitored responses of the application system including stored screenshots of the GUI page following the providing of the respective test parameter values in the respective user input objects of the GUI page. | 0.783444 |
7,644,058 | 14 | 18 | 14. The method of claim 1 , each equation in said series comprising at least one target variable and at least one non-target variable, wherein said step of deriving a solution wording from said removed equation comprises the steps of: finding a target variable in said removed equation; creating a list of positive non-target variables in said removed equation; creating a list of negative non-target variables in said removed equation; determining if said target is positive or negative; if said target is positive, generating a negative plain language expression of said target, otherwise generating a positive plain language expression of said target; for each variable in said list of positive non-target variables, generating a plain language statement of system condition; for each variable in said list of negative non-target variables, generating a plain language statement of omitted condition; generating a compound statement of system conditions by joining together said statements of system condition using a first logical operator between each of said statements of system condition, said first logical operator being “and”; and generating a compound statement of system omitted conditions by joining together said statements of system omitted condition using a second logical operator between each of said statements of system omitted condition, said second logical operator being “or”. | 14. The method of claim 1 , each equation in said series comprising at least one target variable and at least one non-target variable, wherein said step of deriving a solution wording from said removed equation comprises the steps of: finding a target variable in said removed equation; creating a list of positive non-target variables in said removed equation; creating a list of negative non-target variables in said removed equation; determining if said target is positive or negative; if said target is positive, generating a negative plain language expression of said target, otherwise generating a positive plain language expression of said target; for each variable in said list of positive non-target variables, generating a plain language statement of system condition; for each variable in said list of negative non-target variables, generating a plain language statement of omitted condition; generating a compound statement of system conditions by joining together said statements of system condition using a first logical operator between each of said statements of system condition, said first logical operator being “and”; and generating a compound statement of system omitted conditions by joining together said statements of system omitted condition using a second logical operator between each of said statements of system omitted condition, said second logical operator being “or”. 18. The method of claim 14 , wherein said step of parsing said user input includes the steps of: determining at least one function contained in said user input; determining at least one connector for each of said functions; and determining a target for each of said connectors. | 0.807371 |
7,801,722 | 10 | 11 | 10. The computer-readable storage medium of claim 9 , wherein the phonetic scheme is stored in a user-readable file format. | 10. The computer-readable storage medium of claim 9 , wherein the phonetic scheme is stored in a user-readable file format. 11. The computer-readable storage medium of claim 10 , wherein the user-readable file format is an XML file format. | 0.959104 |
8,996,560 | 18 | 19 | 18. A system comprising: at least one processor; and at least one non-transitory computer readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the system to: receive, at a first point in time, a first query from a user; track navigation of the user through a first plurality of query results associated with the first query, wherein tracking navigation of the user through the first plurality of query results comprises tracking one or more query results with which the user does not interact; access information associated with the tracked navigation of the first plurality of query results; identify a topic based on the information associated with the tracked navigation of the user through the first plurality of query results; receive, at a second point in time subsequent to the first point in time, a second query from the user; generate a second plurality of query results based on the second query; and modify, without user intervention, the second plurality of query results based on the information associated with the tracked navigation of the first plurality of query results, wherein the modified second plurality of query results reflects a disinterest of the user in the identified topic. | 18. A system comprising: at least one processor; and at least one non-transitory computer readable storage medium storing instructions thereon that, when executed by the at least one processor, cause the system to: receive, at a first point in time, a first query from a user; track navigation of the user through a first plurality of query results associated with the first query, wherein tracking navigation of the user through the first plurality of query results comprises tracking one or more query results with which the user does not interact; access information associated with the tracked navigation of the first plurality of query results; identify a topic based on the information associated with the tracked navigation of the user through the first plurality of query results; receive, at a second point in time subsequent to the first point in time, a second query from the user; generate a second plurality of query results based on the second query; and modify, without user intervention, the second plurality of query results based on the information associated with the tracked navigation of the first plurality of query results, wherein the modified second plurality of query results reflects a disinterest of the user in the identified topic. 19. The system of claim 18 , further comprising instructions that, when executed by the at least one processor, cause the system to: analyze the information associated with the tracked navigation of the user through the first plurality of query results; and predict a user interest based on the analysis of the information associated with the tracked navigation of the user through the first plurality of query results. | 0.694161 |
9,858,313 | 13 | 14 | 13. The method of claim 11 , further comprising presenting the suggestion set via the mobile device. | 13. The method of claim 11 , further comprising presenting the suggestion set via the mobile device. 14. The method of claim 13 , wherein the suggestion set comprises a specified number of query suggestions. | 0.97346 |
7,783,972 | 8 | 9 | 8. The product of claim 7 , wherein the means for detecting edits not made by the product comprises a checksum. | 8. The product of claim 7 , wherein the means for detecting edits not made by the product comprises a checksum. 9. The product of claim 8 wherein the checksum comprises a message digest algorithm selected from a group consisting of MD2, MD4 and MD5. | 0.970913 |
6,055,498 | 30 | 35 | 30. In an automatic speech processing system, a method for grading the pronunciation of a student speech sample, the method comprising: accepting said student speech sample which comprises a sequence of words spoken by a student speaker; operating a set of trained speech models to compute at least one posterior probability from said speech sample, each of said posterior probabilities being a probability that a particular portion of said student speech sample corresponds to a particular known model given said particular portion of said speech sample; and computing an evaluation score, herein referred to as the posterior-based evaluation score, of pronunciation quality for said student speech sample from said posterior probabilities wherein: said trained speech models comprise a set of phone models; said student speech sample comprises phones; and the step of operating said speech models comprises computing a frame-based posterior probability for each frame yt within a phone i of a phone type qi: ##EQU14## wherein: p(yt.vertline.qi, . . . ) is the probability of the frame yt according to a model corresponding to phone type qi; the sum over q runs over all phone types; and P(qi) represents the prior probability of the phone type qi. | 30. In an automatic speech processing system, a method for grading the pronunciation of a student speech sample, the method comprising: accepting said student speech sample which comprises a sequence of words spoken by a student speaker; operating a set of trained speech models to compute at least one posterior probability from said speech sample, each of said posterior probabilities being a probability that a particular portion of said student speech sample corresponds to a particular known model given said particular portion of said speech sample; and computing an evaluation score, herein referred to as the posterior-based evaluation score, of pronunciation quality for said student speech sample from said posterior probabilities wherein: said trained speech models comprise a set of phone models; said student speech sample comprises phones; and the step of operating said speech models comprises computing a frame-based posterior probability for each frame yt within a phone i of a phone type qi: ##EQU14## wherein: p(yt.vertline.qi, . . . ) is the probability of the frame yt according to a model corresponding to phone type qi; the sum over q runs over all phone types; and P(qi) represents the prior probability of the phone type qi. 35. The method according to claim 30 wherein the model corresponding to each phone type is a context-independent phone model. | 0.856322 |
8,321,398 | 23 | 24 | 23. The method of claim 15 further comprising determining a combined relevancy score associated with the entity based on the term aggregate relevancy score and at least one additional factor. | 23. The method of claim 15 further comprising determining a combined relevancy score associated with the entity based on the term aggregate relevancy score and at least one additional factor. 24. The method of claim 23 , wherein the at least one additional factor comprises TFIDF. | 0.965997 |
8,615,389 | 1 | 8 | 1. A method comprising: executing instructions via a processor of a computing system for: generating a language model according to an approximate hashing technique, the language model comprising a plurality of event sequences in a target language, each member of the plurality of the event sequences associated with at least one count, the language model comprising a set of data structures organized in a hierarchy with lower levels corresponding to event sequences occurring less frequently being stored using fewer bits, the hierarchy having three or more levels; querying the language model for a member of the plurality of event sequences; and determining a probability associated with the member of the plurality of event sequences based on results of the query. | 1. A method comprising: executing instructions via a processor of a computing system for: generating a language model according to an approximate hashing technique, the language model comprising a plurality of event sequences in a target language, each member of the plurality of the event sequences associated with at least one count, the language model comprising a set of data structures organized in a hierarchy with lower levels corresponding to event sequences occurring less frequently being stored using fewer bits, the hierarchy having three or more levels; querying the language model for a member of the plurality of event sequences; and determining a probability associated with the member of the plurality of event sequences based on results of the query. 8. The method of claim 1 , wherein determining the probability is based on a first value associated with event information and a second value associated with history information. | 0.813025 |
9,389,872 | 5 | 6 | 5. A non-transitory computer readable storage medium comprising instructions that, when executed by a processor, cause the processor to generate and test a sequence of user interface (UI) pages of a software wizard, by performing the steps of: generating UI pages of the software wizard that includes a first UI page and other UI pages of the software wizard, wherein the first UI page is associated with one or more constraint functions which, when triggered, cause a transition from the first UI page to another UI page of the software wizard; and testing the constraint functions independently of the UI pages of the software wizard to determine that the software wizard executes as expected, wherein inputs to the constraint functions include UI input elements, properties of a data structure that stores data relied upon by the constraint functions to generate content for the UI pages of the software wizard, and external data, and outputs of the constraint functions include validation results, a set of values to be presented on one or more of the UI pages of the software wizard, a value to be assigned to a particular property of the data structure, and a page flow map change that modifies one or more transitions between the UI pages of the software wizard, and wherein the constraint functions include a first constraint function, a second constraint function, and a third constraint function, the output of the first constraint function including a value for a particular property of the data structure, that is an input to the second constraint function and triggers the second constraint function, and wherein an input of the third constraint function is a UI input element and a validation result of the third constraint function is an error message that causes the UI input element to be disabled. | 5. A non-transitory computer readable storage medium comprising instructions that, when executed by a processor, cause the processor to generate and test a sequence of user interface (UI) pages of a software wizard, by performing the steps of: generating UI pages of the software wizard that includes a first UI page and other UI pages of the software wizard, wherein the first UI page is associated with one or more constraint functions which, when triggered, cause a transition from the first UI page to another UI page of the software wizard; and testing the constraint functions independently of the UI pages of the software wizard to determine that the software wizard executes as expected, wherein inputs to the constraint functions include UI input elements, properties of a data structure that stores data relied upon by the constraint functions to generate content for the UI pages of the software wizard, and external data, and outputs of the constraint functions include validation results, a set of values to be presented on one or more of the UI pages of the software wizard, a value to be assigned to a particular property of the data structure, and a page flow map change that modifies one or more transitions between the UI pages of the software wizard, and wherein the constraint functions include a first constraint function, a second constraint function, and a third constraint function, the output of the first constraint function including a value for a particular property of the data structure, that is an input to the second constraint function and triggers the second constraint function, and wherein an input of the third constraint function is a UI input element and a validation result of the third constraint function is an error message that causes the UI input element to be disabled. 6. The non-transitory computer readable storage medium of claim 5 , wherein testing the constraint functions comprises causing a change to a UI input element associated with the first UI page. | 0.636364 |
9,304,614 | 13 | 20 | 13. A system for providing a custom action for post in an online social network, the system comprising: a client machine having a display device; and one or more servers in communication with the client machine via a network, the one or more servers including memory and one or more processors, the one or more servers being configured to: transmit, from the server to the client machine, data implementing a user interface component for display at the client machine in accordance with first computing programming language instructions provided by a first entity: the user interface component displays at least one feed item record authored by a user and a plurality of responsive posts in a thread about the feed item record, each post of the plurality of responsive posts having a feed item ID and being posted by a user with information about the feed item record, and each post of the plurality of responsive posts contains a custom action activation mechanism indexed by the feed item ID, wherein the custom action activation mechanism is customized based on a state of the post indexed by the feed item ID and is customizable with second computer programming language instructions provided by a second entity; receive a message transmitted from the client machine to the server, the message indicating detection of a custom action activation event generated responsive to activation of the custom action activation mechanism associated with a first one of the responsive posts; and perform the custom action at the server in response to receiving the message: the custom action modifying data related to the first responsive post at the server, and the custom action being performed in accordance with the second computer programming language instructions provided by the second entity. | 13. A system for providing a custom action for post in an online social network, the system comprising: a client machine having a display device; and one or more servers in communication with the client machine via a network, the one or more servers including memory and one or more processors, the one or more servers being configured to: transmit, from the server to the client machine, data implementing a user interface component for display at the client machine in accordance with first computing programming language instructions provided by a first entity: the user interface component displays at least one feed item record authored by a user and a plurality of responsive posts in a thread about the feed item record, each post of the plurality of responsive posts having a feed item ID and being posted by a user with information about the feed item record, and each post of the plurality of responsive posts contains a custom action activation mechanism indexed by the feed item ID, wherein the custom action activation mechanism is customized based on a state of the post indexed by the feed item ID and is customizable with second computer programming language instructions provided by a second entity; receive a message transmitted from the client machine to the server, the message indicating detection of a custom action activation event generated responsive to activation of the custom action activation mechanism associated with a first one of the responsive posts; and perform the custom action at the server in response to receiving the message: the custom action modifying data related to the first responsive post at the server, and the custom action being performed in accordance with the second computer programming language instructions provided by the second entity. 20. The system recited in claim 13 , further configured to: include a re-post custom action that posts the first responsive post to a feed different than the thread. | 0.837598 |
8,495,735 | 9 | 10 | 9. The method as recited in claim 1 , wherein said step of using the processor portion to compare said hash value set to prior saved hash value sets and calculating a similarity value for each said comparison comprises using comparison models selected from the group consisting of the Simpson method, the Bruan-Blanquet method, the Kulczynski 1 method, and the Kulczynski 2 method. | 9. The method as recited in claim 1 , wherein said step of using the processor portion to compare said hash value set to prior saved hash value sets and calculating a similarity value for each said comparison comprises using comparison models selected from the group consisting of the Simpson method, the Bruan-Blanquet method, the Kulczynski 1 method, and the Kulczynski 2 method. 10. The method as recited in claim 9 , wherein said step of calculating a hash value comprises the step of calculating a hash value based upon methodologies selected from the group consisting of MD5, WHIRLPOOL, SHA-1, SHA-256, and RIPEMD-160. | 0.939379 |
8,290,930 | 1 | 9 | 1. A computer-readable storage medium storing computer-executable instructions for performing a method comprising: receiving a query that identifies a first input data source; identifying a query category from a group of query categories for a first query operator in the received query based on whether the first query operator provides an output that supports random access, wherein the query categories include a first category for query operators that provide an output that supports random access, a second category for query operators that provide an output that supports random access when an input of the query operator supports random access, and a third category for query operators that provide an output that does not support random access; identifying a data source category for the first input data source from a group of data source categories, wherein the data source categories include a first category for input data sources that support random access to the data source, and a second category for input data sources that do not support random access to the data source; and generating a first results object based on the identified query category and the identified data source category, wherein the first results object supports at least one of random access and sequential access to results produced by the first query operator, and wherein the first results object supports random access to results produced by the first query operator by providing a first method for returning a value representing a number of elements in the results produced by the first query operator, and a second method for returning an indexed element from the results produced by the first query operator. | 1. A computer-readable storage medium storing computer-executable instructions for performing a method comprising: receiving a query that identifies a first input data source; identifying a query category from a group of query categories for a first query operator in the received query based on whether the first query operator provides an output that supports random access, wherein the query categories include a first category for query operators that provide an output that supports random access, a second category for query operators that provide an output that supports random access when an input of the query operator supports random access, and a third category for query operators that provide an output that does not support random access; identifying a data source category for the first input data source from a group of data source categories, wherein the data source categories include a first category for input data sources that support random access to the data source, and a second category for input data sources that do not support random access to the data source; and generating a first results object based on the identified query category and the identified data source category, wherein the first results object supports at least one of random access and sequential access to results produced by the first query operator, and wherein the first results object supports random access to results produced by the first query operator by providing a first method for returning a value representing a number of elements in the results produced by the first query operator, and a second method for returning an indexed element from the results produced by the first query operator. 9. The computer-readable storage medium of claim 1 , wherein the method further comprises: executing the query in a parallel manner with a plurality of processors. | 0.778533 |
9,871,918 | 15 | 18 | 15. A non-transitory computer-readable medium with an executable program stored thereon for providing an evaluation to a customer service representative regarding his performance during an interaction with a customer, wherein the program instructs a processing element of a computing device to perform the following: comparing a customer service representative transcript that includes words which are spoken by the customer service representative during an oral conversation between the customer service representative and the customer with a plurality of positive words and a plurality of negative words; generating and displaying on a display a first score that varies according to the occurrence of each word spoken by the customer service representative that matches one of the positive words and the occurrence of each word spoken by the customer service representative that matches one of the negative words to facilitate an objective evaluation of the customer interaction; generating a plurality of voice prints, each voice print derived from one of a plurality of periods of time during the conversation, comparing each voice print with a voice print of the customer service representative to determine an identity of the voice print, indicating a first set of voice prints that are associated with the customer service representative and a second set of voice prints that are associated with the customer, matching the first set of voice prints with words from a text stream that are spoken by the customer service representative, and displaying on the display a list of words from the customer service representative transcript that match one or more positive words, and a list of words from the customer service representative transcript that match one or more negative words. | 15. A non-transitory computer-readable medium with an executable program stored thereon for providing an evaluation to a customer service representative regarding his performance during an interaction with a customer, wherein the program instructs a processing element of a computing device to perform the following: comparing a customer service representative transcript that includes words which are spoken by the customer service representative during an oral conversation between the customer service representative and the customer with a plurality of positive words and a plurality of negative words; generating and displaying on a display a first score that varies according to the occurrence of each word spoken by the customer service representative that matches one of the positive words and the occurrence of each word spoken by the customer service representative that matches one of the negative words to facilitate an objective evaluation of the customer interaction; generating a plurality of voice prints, each voice print derived from one of a plurality of periods of time during the conversation, comparing each voice print with a voice print of the customer service representative to determine an identity of the voice print, indicating a first set of voice prints that are associated with the customer service representative and a second set of voice prints that are associated with the customer, matching the first set of voice prints with words from a text stream that are spoken by the customer service representative, and displaying on the display a list of words from the customer service representative transcript that match one or more positive words, and a list of words from the customer service representative transcript that match one or more negative words. 18. The non-transitory computer-readable medium of claim 15 , wherein the program further instructs the processing element to analyze a data stream to determine a plurality of tone of voice values for the customer service representative, each tone of voice value derived from one of a plurality of periods of time during the conversation, the data stream being digitized and corresponding to the oral conversation between the customer and the customer service representative, analyze the data stream to determine a plurality of tone of voice values for the customer, each tone of voice value derived from one of a plurality of periods of time during the conversation, generate and display on the display a second score that varies according to whether the customer service representative changed his tone of voice in response to a change in tone of voice of the customer to facilitate the objective evaluation of a customer interaction, and determine each occurrence when the customer's tone of voice value is above a first threshold and determine whether the tone of voice value for the customer service representative increases above a second threshold within a first time period after each occurrence. | 0.500415 |
9,639,898 | 1 | 4 | 1. A non-transitory computer-readable medium storing computer-executable instructions that when executed by a computer cause the computer to: extract tax related data from a tax transaction database that stores a plurality of data records describing a plurality of tax return forms filed by a plurality of taxpayers, where each record includes values in tax return fields describing a taxpayer who filed the tax return form, further where the tax return fields include tax return lines; transform and store the extracted tax related data in a tax data warehouse that includes fact tables and dimension tables in at least one star schema by populating a fact table with i) values in the tax return form lines and ii) a form type identifier that identifies a type of the tax return form, where populating the fact table with values according to tax return form lines improves a granularity of analysis that can be performed using the tax data warehouse as compared to the tax transaction database; where the tax data warehouse includes a dimension table that has i) a row for each tax form type and ii) columns storing contextual information about tax return form lines; generate and store a plurality of key performance indicator (KPI) queries where each KPI query includes a different combination of tax metrics from the tax transaction database and one or more query elements associated with a criteria from the tax metrics; generate a plurality of materialized views where each materialized view corresponds to one of the plurality of KPI queries and stores aggregated key performance indicator (KPI) values for the corresponding KPI query; store the plurality of materialized views in the tax data warehouse for use in processing KPI queries; provide and display an interface that displays one or more of the plurality of KPI queries for selection; and in response to a first KPI query being selected, cause the first KPI query to be executed on at least a first materialized view from the plurality of materialized views that corresponds to the first KPI query to return results corresponding to the first KPI query. | 1. A non-transitory computer-readable medium storing computer-executable instructions that when executed by a computer cause the computer to: extract tax related data from a tax transaction database that stores a plurality of data records describing a plurality of tax return forms filed by a plurality of taxpayers, where each record includes values in tax return fields describing a taxpayer who filed the tax return form, further where the tax return fields include tax return lines; transform and store the extracted tax related data in a tax data warehouse that includes fact tables and dimension tables in at least one star schema by populating a fact table with i) values in the tax return form lines and ii) a form type identifier that identifies a type of the tax return form, where populating the fact table with values according to tax return form lines improves a granularity of analysis that can be performed using the tax data warehouse as compared to the tax transaction database; where the tax data warehouse includes a dimension table that has i) a row for each tax form type and ii) columns storing contextual information about tax return form lines; generate and store a plurality of key performance indicator (KPI) queries where each KPI query includes a different combination of tax metrics from the tax transaction database and one or more query elements associated with a criteria from the tax metrics; generate a plurality of materialized views where each materialized view corresponds to one of the plurality of KPI queries and stores aggregated key performance indicator (KPI) values for the corresponding KPI query; store the plurality of materialized views in the tax data warehouse for use in processing KPI queries; provide and display an interface that displays one or more of the plurality of KPI queries for selection; and in response to a first KPI query being selected, cause the first KPI query to be executed on at least a first materialized view from the plurality of materialized views that corresponds to the first KPI query to return results corresponding to the first KPI query. 4. The non-transitory computer-readable medium of claim 1 , further comprising instructions configured to cause the computer to: receive a user specified query element for a KPI query; execute the KPI query with the received query element; and return a KPI query result. | 0.793262 |
9,798,767 | 30 | 36 | 30. A computer-readable computer memory medium selected from the group consisting of: application-specific integrated circuits, standard integrated circuits, field-programmable gate arrays, complex programmable logic devices, hard disks, and memory, wherein the computer-readable computer memory medium is storing or executing instructions that, when executed, controls a computer processor to facilitate patent related searches from a patent corpus of patent related publications, by automatically performing citation analysis upon each iteration of a patent related search, the citation analysis comprising citations from a respective face of each patent publication, which lists backward references as well as forward references to patents and/or patent publications, by performing a method comprising: receiving an indication of input text and/or patent related publications as input; automatically analyzing the indicated input using semantic analysis of the indicated source input to automatically extract a first set of search-based keywords and/or phrases that are present in the indicated input, wherein the automatically analyzing the indicated input using semantic analysis parses the indicated source input to determine grammatical usage to automatically extract the first set of search-based keywords and/or phrases; from the automatically determined first set of keywords, performing an initial search iteration automatically, and wherein the initial search iteration is performed without additional user input, by performing the steps of: automatically determining an initial set of patent related publications that include the automatically extracted first set of search-based keywords; automatically determining a correlated set of patent related publications that are correlated to the initial set of patent related publications using automatic citation analysis of the initial set of patent related publications, wherein the correlated set is determined to be one or more patent related publications from the corpus that have unique citation relationships to any one of the patent related publications of the initial set, and wherein the correlated set is automatically sorted based upon the correlated patent related publications that involve the most number of citation paths with the initial set of patent related publications; and automatically extracting from the automatically determined initial set of patent related publications a set of related keywords not found in the first set of keywords or in the source input; and presenting indicators to the determined initial set and the sorted determined correlated set of patent related publications and the set of related keywords as output from the initial search iteration. | 30. A computer-readable computer memory medium selected from the group consisting of: application-specific integrated circuits, standard integrated circuits, field-programmable gate arrays, complex programmable logic devices, hard disks, and memory, wherein the computer-readable computer memory medium is storing or executing instructions that, when executed, controls a computer processor to facilitate patent related searches from a patent corpus of patent related publications, by automatically performing citation analysis upon each iteration of a patent related search, the citation analysis comprising citations from a respective face of each patent publication, which lists backward references as well as forward references to patents and/or patent publications, by performing a method comprising: receiving an indication of input text and/or patent related publications as input; automatically analyzing the indicated input using semantic analysis of the indicated source input to automatically extract a first set of search-based keywords and/or phrases that are present in the indicated input, wherein the automatically analyzing the indicated input using semantic analysis parses the indicated source input to determine grammatical usage to automatically extract the first set of search-based keywords and/or phrases; from the automatically determined first set of keywords, performing an initial search iteration automatically, and wherein the initial search iteration is performed without additional user input, by performing the steps of: automatically determining an initial set of patent related publications that include the automatically extracted first set of search-based keywords; automatically determining a correlated set of patent related publications that are correlated to the initial set of patent related publications using automatic citation analysis of the initial set of patent related publications, wherein the correlated set is determined to be one or more patent related publications from the corpus that have unique citation relationships to any one of the patent related publications of the initial set, and wherein the correlated set is automatically sorted based upon the correlated patent related publications that involve the most number of citation paths with the initial set of patent related publications; and automatically extracting from the automatically determined initial set of patent related publications a set of related keywords not found in the first set of keywords or in the source input; and presenting indicators to the determined initial set and the sorted determined correlated set of patent related publications and the set of related keywords as output from the initial search iteration. 36. The computer-readable computer memory medium of claim 30 wherein the citation analysis considers only patent related publications that have more than one unique citation relationship to any one of the intermediate set of patent related publications. | 0.904887 |
8,862,594 | 2 | 8 | 2. The method of claim 1 , further comprising: receiving the query, the query including multiple keywords; wherein the analyzing the digital information comprises generating multiple initial rankings corresponding to the multiple keywords, each of the multiple initial rankings indicating authority of the nodes with respect to each respective keyword; and wherein the generating the keyword-specific ranking comprises combining the multiple initial rankings. | 2. The method of claim 1 , further comprising: receiving the query, the query including multiple keywords; wherein the analyzing the digital information comprises generating multiple initial rankings corresponding to the multiple keywords, each of the multiple initial rankings indicating authority of the nodes with respect to each respective keyword; and wherein the generating the keyword-specific ranking comprises combining the multiple initial rankings. 8. The method of claim 2 , wherein the digital information comprises a database having a structural relationship among the nodes defined by semantic contents of the database, and the generating the multiple initial rankings comprises setting initial conditions for iterative processing based on the semantic contents and stored values for a subset of the nodes. | 0.859751 |
8,266,173 | 4 | 5 | 4. The method of claim 1 , wherein the displaying comprises displaying a set of results including a predetermined number of electronic items having at least one instance of the query terms located within the predetermined proximity of each other, and wherein the determining is iteratively performed on the electronic items in order of the sorted list until the predetermined number of electronic items having at least one instance of the query terms located within the predetermined proximity of each other is reached. | 4. The method of claim 1 , wherein the displaying comprises displaying a set of results including a predetermined number of electronic items having at least one instance of the query terms located within the predetermined proximity of each other, and wherein the determining is iteratively performed on the electronic items in order of the sorted list until the predetermined number of electronic items having at least one instance of the query terms located within the predetermined proximity of each other is reached. 5. The method of claim 4 , further comprising: receiving a request to view a next set of search results; beginning with a next electronic item in the sorted list and continuing in order of the sorted list, iteratively determining electronic items having at least one instance of the query terms located within the predetermined proximity of each other until the predetermined number of electronic items for the next set of search results is reached; and displaying the next set of results on the display of the handheld electronic book reader device. | 0.830561 |
8,271,261 | 9 | 15 | 9. A computer system, comprising: i) memory having at least one region for storing computer executable program code; and ii) a processor for executing the program code stored in the memory, wherein the program code comprising: software code to provide a website; software code to tabulate text elements used through the website into message tokens composed of a hierarchical string of descriptors, wherein each message token comprises at least one descriptor of each of the following types: i) application-specific, ii) context-specific, and iii) content-specific; software code to store data indicative of an interpretation of each text element in a first language in a translation sheet database; software code to store data indicative of the interpretation of each text element in a second language in the translation sheet database, wherein the second language is different from the first language and wherein each language is associated with at least one language-specific key; software code to determine whether to display data to the user of the website in the first language or the second language; software code to interpret a combination of a message token of a text element and the at least one language-specific key to identify the interpretation of the text element in the determined language; software code to incorporate the identified interpretation of the text element into a graphical user interface element; and software code to display to the user of the website the graphical user interface element with the identified interpretation of the text element. | 9. A computer system, comprising: i) memory having at least one region for storing computer executable program code; and ii) a processor for executing the program code stored in the memory, wherein the program code comprising: software code to provide a website; software code to tabulate text elements used through the website into message tokens composed of a hierarchical string of descriptors, wherein each message token comprises at least one descriptor of each of the following types: i) application-specific, ii) context-specific, and iii) content-specific; software code to store data indicative of an interpretation of each text element in a first language in a translation sheet database; software code to store data indicative of the interpretation of each text element in a second language in the translation sheet database, wherein the second language is different from the first language and wherein each language is associated with at least one language-specific key; software code to determine whether to display data to the user of the website in the first language or the second language; software code to interpret a combination of a message token of a text element and the at least one language-specific key to identify the interpretation of the text element in the determined language; software code to incorporate the identified interpretation of the text element into a graphical user interface element; and software code to display to the user of the website the graphical user interface element with the identified interpretation of the text element. 15. The system of claim 9 , wherein the determination of whether to display data to the user of the website in the first language or the second language is subsequently changed by the user. | 0.807143 |
9,876,814 | 1 | 4 | 1. A method comprising: at a computing device, classifying each one of first domain names as either a likely domain generation algorithm (DGA) domain name or a likely non-DGA domain name, based on one or more features of the first domain names, the classifying producing a first pool of likely DGA domain names; determining statistics regarding requests for the likely DGA domain names in the first pool to identify a second pool of likely DGA domain names out of the first pool, wherein, for each of the likely DGA domain names in the second pool, the statistics of the requests indicate a spike over a period of time, wherein a number of the likely DGA domain names in the second pool is less than a number of the likely DGA domain names in the first pool; identifying additional domain names that share an infrastructure with the likely DGA domain names in the second pool; and mitigating a security vulnerability related to one or more of the likely DGA domain names in the second pool and the additional domain names. | 1. A method comprising: at a computing device, classifying each one of first domain names as either a likely domain generation algorithm (DGA) domain name or a likely non-DGA domain name, based on one or more features of the first domain names, the classifying producing a first pool of likely DGA domain names; determining statistics regarding requests for the likely DGA domain names in the first pool to identify a second pool of likely DGA domain names out of the first pool, wherein, for each of the likely DGA domain names in the second pool, the statistics of the requests indicate a spike over a period of time, wherein a number of the likely DGA domain names in the second pool is less than a number of the likely DGA domain names in the first pool; identifying additional domain names that share an infrastructure with the likely DGA domain names in the second pool; and mitigating a security vulnerability related to one or more of the likely DGA domain names in the second pool and the additional domain names. 4. The method of claim 1 , wherein classifying comprises evaluating one or more properties of a string of characters in the first domain names. | 0.920556 |
9,053,358 | 15 | 19 | 15. A non-transitory computer readable medium storing computer readable instructions that, when executed by a computer, cause the computer to perform a process, the process comprising: extracting a feature quantity from a feature point of each learning image of a plurality of learning images, the plurality of learning images including a first learning image including a detection target and a second learning image not including the detection target; acquiring, from an external device, a transfer classifier for detecting the detection target; calculating a classification result of the detection target according to a weak classifier for each learning image by substituting the extracted feature quantity that corresponds to the weak classifier into the weak classifier with respect to each of a plurality of weak classifiers constituting the transfer classifier; and generating a classifier using the transfer classifier and the weak classifier selected from the plurality of weak classifiers based on the classification result of each of the plurality of weak classifiers. | 15. A non-transitory computer readable medium storing computer readable instructions that, when executed by a computer, cause the computer to perform a process, the process comprising: extracting a feature quantity from a feature point of each learning image of a plurality of learning images, the plurality of learning images including a first learning image including a detection target and a second learning image not including the detection target; acquiring, from an external device, a transfer classifier for detecting the detection target; calculating a classification result of the detection target according to a weak classifier for each learning image by substituting the extracted feature quantity that corresponds to the weak classifier into the weak classifier with respect to each of a plurality of weak classifiers constituting the transfer classifier; and generating a classifier using the transfer classifier and the weak classifier selected from the plurality of weak classifiers based on the classification result of each of the plurality of weak classifiers. 19. The non-transitory computer readable medium according to claim 15 , wherein the transfer classifier detects the detection target when the detection target is in a first state, and wherein the generated classifier detects the detection target when the detection target is in a second state different from the first state. | 0.676 |
8,688,457 | 2 | 6 | 2. The transmitting apparatus according to claim 1 , wherein the creating means generates a DSM-CC event message as control information including the generated chronologically-ordered sign language word identification information; wherein the storing means stores the sign language word images for displaying the sign language video corresponding to the sign language words by grouping the sign language word images into a plurality of DSM-CC data carousel modules according to a frequency of appearance of the sign language words in the speech in the content. | 2. The transmitting apparatus according to claim 1 , wherein the creating means generates a DSM-CC event message as control information including the generated chronologically-ordered sign language word identification information; wherein the storing means stores the sign language word images for displaying the sign language video corresponding to the sign language words by grouping the sign language word images into a plurality of DSM-CC data carousel modules according to a frequency of appearance of the sign language words in the speech in the content. 6. The transmitting apparatus according to claim 2 , wherein the sign language word images are in a multiple-image network graphics, portable network graphics, or joint photographic experts group format. | 0.906019 |
8,145,993 | 1 | 2 | 1. A computer-implemented method, comprising: accessing a translation-capable XML document, where the translation-capable XML document stores translatable data; establishing a session language identifier; and providing a virtual view of the translation-capable XML document, where the virtual view is determined, at least in part, by the session language identifier, and where the virtual view presents one or more of, the translatable data, and a translation for the translatable data, and where the providing includes controlling database query rewrite logic to rewrite a non-translation-capable query expression to produce a translation-capable query expression and providing the translation-capable query expression to an XML database logic, where the non-translation-capable query expression is part of a query to retrieve information from the translation-capable XML document; wherein producing the translation-capable query expression includes receiving a non-translation-capable query that includes the non-translation-capable query expression and rewriting the non-translation-capable query expression to be translation-capable by adding at least a predicate to the non-translation-capable query where the predicate includes attributes for translating portions of the translation-capable query expression or portions of the translation-capable XML document. | 1. A computer-implemented method, comprising: accessing a translation-capable XML document, where the translation-capable XML document stores translatable data; establishing a session language identifier; and providing a virtual view of the translation-capable XML document, where the virtual view is determined, at least in part, by the session language identifier, and where the virtual view presents one or more of, the translatable data, and a translation for the translatable data, and where the providing includes controlling database query rewrite logic to rewrite a non-translation-capable query expression to produce a translation-capable query expression and providing the translation-capable query expression to an XML database logic, where the non-translation-capable query expression is part of a query to retrieve information from the translation-capable XML document; wherein producing the translation-capable query expression includes receiving a non-translation-capable query that includes the non-translation-capable query expression and rewriting the non-translation-capable query expression to be translation-capable by adding at least a predicate to the non-translation-capable query where the predicate includes attributes for translating portions of the translation-capable query expression or portions of the translation-capable XML document. 2. The method of claim 1 , including providing an XML schema that describes an XML document for which the virtual view is provided. | 0.88549 |
7,886,137 | 1 | 3 | 1. A method of creating a basic input/output system (BIOS) project file, comprising: receiving a BIOS project type; identifying a BIOS component category corresponding to the BIOS project type from a script file; searching for BIOS components corresponding to the BIOS component category; presenting any located BIOS components for selection; receiving a selection corresponding to any number of presented BIOS components for inclusion within the BIOS project file; determining whether the selection of any number of presented BIOS components is valid according to component category selection criteria stored within the script file; if the selection is determined not to be valid, then requesting an alternative selection that is consistent with the component category selection criteria; and if the selection is determined to be valid, then creating the BIOS project file utilizing selected BIOS components. | 1. A method of creating a basic input/output system (BIOS) project file, comprising: receiving a BIOS project type; identifying a BIOS component category corresponding to the BIOS project type from a script file; searching for BIOS components corresponding to the BIOS component category; presenting any located BIOS components for selection; receiving a selection corresponding to any number of presented BIOS components for inclusion within the BIOS project file; determining whether the selection of any number of presented BIOS components is valid according to component category selection criteria stored within the script file; if the selection is determined not to be valid, then requesting an alternative selection that is consistent with the component category selection criteria; and if the selection is determined to be valid, then creating the BIOS project file utilizing selected BIOS components. 3. The method of claim 1 , wherein the component category selection criteria comprises an indicator as to whether more than one BIOS component from the BIOS component category may be included in the BIOS project file. | 0.888489 |
6,098,081 | 17 | 21 | 17. A method of resolving a hyperlink, comprising the following steps: receiving a hyperlinked document from a remote server, the hyperlinked document containing one or more hyperlinks, at least one of the hyperlinks containing a query formulation; in response to selection of said at least one of the hyperlinks by a user, reading the query formulation from the selected hyperlink; maintaining a list of bound attributes on an individual computer; maintaining a rule base of executable rules on the individual computer, wherein an executable rule is associated with a set of mandatory attributes, and wherein executing a rule potentially adds search predicates to the query formulation depending on the bound attributes on the individual computer; stepping through the rules of the rule base and executing any rule whose mandatory attributes are in the list of bound attributes maintained on the individual computer; querying a database of available hyperlink targets with the query formulation to locate one or more hyperlink targets that satisfy the query formulation. | 17. A method of resolving a hyperlink, comprising the following steps: receiving a hyperlinked document from a remote server, the hyperlinked document containing one or more hyperlinks, at least one of the hyperlinks containing a query formulation; in response to selection of said at least one of the hyperlinks by a user, reading the query formulation from the selected hyperlink; maintaining a list of bound attributes on an individual computer; maintaining a rule base of executable rules on the individual computer, wherein an executable rule is associated with a set of mandatory attributes, and wherein executing a rule potentially adds search predicates to the query formulation depending on the bound attributes on the individual computer; stepping through the rules of the rule base and executing any rule whose mandatory attributes are in the list of bound attributes maintained on the individual computer; querying a database of available hyperlink targets with the query formulation to locate one or more hyperlink targets that satisfy the query formulation. 21. A method as recited in claim 17, wherein executing a rule includes a step of examining the list of bound attributes to determine whether to add a search predicate to the query formulation. | 0.884754 |
7,933,783 | 1 | 4 | 1. A computer-implemented method for determining topics in which a patient could benefit from additional medical information, the method comprising: receiving over a network a real-time text-based communication between a medical service provider and the patient; parsing the real-time text-based communication between the medical service provider and the patient into one or more text units; comparing, by one or more computers, the one or more text units to a list of triggering keywords, the triggering keywords including words that indicate a potential medical issue, to detect one or more triggering keywords in the communication, with the triggering keywords associated with one or more health care topics; determining, based on the triggering keywords detected by the comparing, one or more health care topics that are associated with the detected triggering keywords; retrieving by the one or more computers a list of the determined one or more health care topics for the patient and the medical service provider to discuss during the real-time communication; generating, by the one or more computers, a graphical user interface that when rendered on a display device, renders a visual representation of the list of the one or more health care topics; and sending, over the network by the one or more computers during the real-time communication between the medical service provider and the patient, the graphical user interface to a computing device being used by the medical service provider. | 1. A computer-implemented method for determining topics in which a patient could benefit from additional medical information, the method comprising: receiving over a network a real-time text-based communication between a medical service provider and the patient; parsing the real-time text-based communication between the medical service provider and the patient into one or more text units; comparing, by one or more computers, the one or more text units to a list of triggering keywords, the triggering keywords including words that indicate a potential medical issue, to detect one or more triggering keywords in the communication, with the triggering keywords associated with one or more health care topics; determining, based on the triggering keywords detected by the comparing, one or more health care topics that are associated with the detected triggering keywords; retrieving by the one or more computers a list of the determined one or more health care topics for the patient and the medical service provider to discuss during the real-time communication; generating, by the one or more computers, a graphical user interface that when rendered on a display device, renders a visual representation of the list of the one or more health care topics; and sending, over the network by the one or more computers during the real-time communication between the medical service provider and the patient, the graphical user interface to a computing device being used by the medical service provider. 4. The method of claim 1 , wherein comparing the one or more first values associated with the one or more text units to one or more second values associated with the list of triggering keywords comprises comparing at least a portion of the real-time communication to a numerical threshold. | 0.670843 |
9,900,498 | 1 | 5 | 1. A glass-type mobile terminal, comprising: a frame body configured to be worn as glasses by a user; a display mounted on the frame body; a camera mounted on the frame body; and a controller configured to: detect user's emotion information and user's linguistic expression information on an object, and control the camera to automatically capture an image corresponding to the object currently viewed with the glass-type mobile terminal based on the linguistic expression information and the emotion information of the user on the currently viewed object, wherein the controller is configured to detect a user's facial expression when the user is viewing the object and output the detected facial expression as the emotion information on the object and to recognize an utterance of the user when the user is viewing the object, and detect the recognized utterance as the user's linguistic expression information, wherein the controller is further configured to detect a user's gazing time at the currently viewed object, store the detected gazing time to a memory together with the image corresponding to the currently viewed object, set an order of priority on the at least one image based on the user's gazing time with respect to the currently viewed object, and differently display the at least one image in the order of priority, and wherein the controller is further configured to: display the emotion information of the user, the image and the linguistic expression information of the user on the display, display a plurality of images related to the emotion information on the display when a user gazes at the emotion information for a preset time, and differently change a display size of each of the plurality of images according to an order of interest of the user. | 1. A glass-type mobile terminal, comprising: a frame body configured to be worn as glasses by a user; a display mounted on the frame body; a camera mounted on the frame body; and a controller configured to: detect user's emotion information and user's linguistic expression information on an object, and control the camera to automatically capture an image corresponding to the object currently viewed with the glass-type mobile terminal based on the linguistic expression information and the emotion information of the user on the currently viewed object, wherein the controller is configured to detect a user's facial expression when the user is viewing the object and output the detected facial expression as the emotion information on the object and to recognize an utterance of the user when the user is viewing the object, and detect the recognized utterance as the user's linguistic expression information, wherein the controller is further configured to detect a user's gazing time at the currently viewed object, store the detected gazing time to a memory together with the image corresponding to the currently viewed object, set an order of priority on the at least one image based on the user's gazing time with respect to the currently viewed object, and differently display the at least one image in the order of priority, and wherein the controller is further configured to: display the emotion information of the user, the image and the linguistic expression information of the user on the display, display a plurality of images related to the emotion information on the display when a user gazes at the emotion information for a preset time, and differently change a display size of each of the plurality of images according to an order of interest of the user. 5. The glass-type mobile terminal of claim 1 , wherein the controller is further configured to: control the camera to automatically capture the image of the object, based on the user's biological signal. | 0.790289 |
8,949,255 | 1 | 8 | 1. A method for storing at least one file generated by a distributed application in a parallel computing system, wherein said file comprises a plurality of sub-files, said method comprising the steps of: obtaining a user specification of semantic information related to said file; determining semantically meaningful sub-file boundaries for said plurality of sub-files based on said semantic information; providing said semantic information as a data structure description to a data formatting library write function, wherein said semantic information is dependent upon a content of said file; and storing said semantic information related to said file with additional metadata related to said file and with one or more of said sub-files using said determined semantically meaningful sub-file boundaries in one or more storage nodes of said parallel computing system. | 1. A method for storing at least one file generated by a distributed application in a parallel computing system, wherein said file comprises a plurality of sub-files, said method comprising the steps of: obtaining a user specification of semantic information related to said file; determining semantically meaningful sub-file boundaries for said plurality of sub-files based on said semantic information; providing said semantic information as a data structure description to a data formatting library write function, wherein said semantic information is dependent upon a content of said file; and storing said semantic information related to said file with additional metadata related to said file and with one or more of said sub-files using said determined semantically meaningful sub-file boundaries in one or more storage nodes of said parallel computing system. 8. The method of claim 1 , wherein said semantic information related to a given sub-file is stored with said corresponding sub-file. | 0.713043 |
9,047,278 | 16 | 20 | 16. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: identifying queries in query data; determining, in each of the queries, (i) an entity-descriptive portion that refers to an entity and (ii) a suffix; determining query counts of a number of times that the respective queries were submitted; for at least a particular query of the identified queries, distributing the query count for the particular query among multiple different entities by assigning, to each of the multiple different entities, a partial query count that is an estimate of a number of submissions of the particular query that refer to the entity; estimating, based at least in part on one or more of the partial query counts, an entity-level count of query submissions that include a particular suffix and are considered to refer to a first entity of the multiple different entities; determining that the first entity is a particular type of entity; determining a type-level count of the query submissions that include the particular suffix and are estimated to refer to entities of the particular type of entity; and assigning, based on the entity-level count and the type-level count, a score for the particular suffix with respect to the first entity. | 16. A system comprising: one or more computers and one or more storage devices storing instructions that are operable, when executed by the one or more computers, to cause the one or more computers to perform operations comprising: identifying queries in query data; determining, in each of the queries, (i) an entity-descriptive portion that refers to an entity and (ii) a suffix; determining query counts of a number of times that the respective queries were submitted; for at least a particular query of the identified queries, distributing the query count for the particular query among multiple different entities by assigning, to each of the multiple different entities, a partial query count that is an estimate of a number of submissions of the particular query that refer to the entity; estimating, based at least in part on one or more of the partial query counts, an entity-level count of query submissions that include a particular suffix and are considered to refer to a first entity of the multiple different entities; determining that the first entity is a particular type of entity; determining a type-level count of the query submissions that include the particular suffix and are estimated to refer to entities of the particular type of entity; and assigning, based on the entity-level count and the type-level count, a score for the particular suffix with respect to the first entity. 20. The system of claim 16 , wherein the operations further comprise: based on the score assigned to the particular suffix, selecting an attribute corresponding to the particular suffix as an attribute for the first entity; receiving a query submission that refers to the first entity; and in response to receiving the query submission that refers to the first entity, providing data that identifies the attribute and a value of the attribute for the first entity. | 0.619048 |
8,606,554 | 7 | 11 | 7. A building Heating, Ventilation and Air Conditioning (HVAC) fault detection system comprising: an interface configured to access a Building Information Model (BIM) file library and import the building HVAC system BIM files; an HFM node library configured to store a plurality of different predefined HFM node types wherein an HFM node models the dynamic physical behavior parameters of air and water flows in predefined HVAC components as derived from the BIM files; a Graphic User Interface (GUI) configured to input and edit HFM node and linkage configuration data during an HFM graph assembly; a compiler coupled to the interface and GUI, configured to compose together the BIM file data with the additional linkage configuration data; and a Fault Detection and Diagnosis (FDD) generator coupled to the compiler and HFM node library, configured to compare the BIM file types for the building HVAC system with the predefined HFM node types and select from the predefined HFM node types, the HFM nodes that correspond and generate an HFM graph wherein the HFM graph is by mass air flow path corresponding to the building HVAC system components and behavior. | 7. A building Heating, Ventilation and Air Conditioning (HVAC) fault detection system comprising: an interface configured to access a Building Information Model (BIM) file library and import the building HVAC system BIM files; an HFM node library configured to store a plurality of different predefined HFM node types wherein an HFM node models the dynamic physical behavior parameters of air and water flows in predefined HVAC components as derived from the BIM files; a Graphic User Interface (GUI) configured to input and edit HFM node and linkage configuration data during an HFM graph assembly; a compiler coupled to the interface and GUI, configured to compose together the BIM file data with the additional linkage configuration data; and a Fault Detection and Diagnosis (FDD) generator coupled to the compiler and HFM node library, configured to compare the BIM file types for the building HVAC system with the predefined HFM node types and select from the predefined HFM node types, the HFM nodes that correspond and generate an HFM graph wherein the HFM graph is by mass air flow path corresponding to the building HVAC system components and behavior. 11. The system according to claim 7 wherein the BIM files further comprise Industrial Foundation Class (IFC) files. | 0.956961 |
9,959,361 | 1 | 8 | 1. A computer-implemented method comprising: receiving, by an application of a computing device, user input in the form of text; processing, by the application, the text to ascertain whether the text is associated with a search or a navigation; responsive to the text being associated with a navigation; selecting, by the application, a navigation URL that is configured to provide to a search provider both the text and an indication that the text is associated with an attempted navigation to a site associated with a web address and using the navigation URL to communicate the text to the search provider along with the indication; and automatically navigating, by the application, to the site associated with the web address: and responsive to the text being associated with a search, selecting, by the application, a different URL to provide to the search provider both the text associated with a search and an indication that the text appears to be a search. | 1. A computer-implemented method comprising: receiving, by an application of a computing device, user input in the form of text; processing, by the application, the text to ascertain whether the text is associated with a search or a navigation; responsive to the text being associated with a navigation; selecting, by the application, a navigation URL that is configured to provide to a search provider both the text and an indication that the text is associated with an attempted navigation to a site associated with a web address and using the navigation URL to communicate the text to the search provider along with the indication; and automatically navigating, by the application, to the site associated with the web address: and responsive to the text being associated with a search, selecting, by the application, a different URL to provide to the search provider both the text associated with a search and an indication that the text appears to be a search. 8. The computer-implemented method of claim 1 , wherein the selected navigation URL is part of an OpenSearch description file that defines how a web browser interfaces with the search provider. | 0.854887 |
8,510,321 | 14 | 28 | 14. A method of accessing and managing a relational database comprising: executing a program of instructions with a machine, the program of instructions being configured to: query a relational database; and access semantically relevant query results from the relational database, wherein to access query results from the relational database further comprises; accessing at least one ontology; extracting domain knowledge from at least one ontology and; employing the domain knowledge in obtaining the semantically relevant query results from the relational database; wherein said semantically relevant query results comprise direct results obtained directly from relational database tables, inferred results inferred utilizing information explicitly listed in the relational database and the at least one ontology, and related results obtained utilizing data in the relational database tables and one or more definitions of similarity of concepts and individuals based on the at least one ontology; and wherein to access semantically relevant query results comprises: applying a query generalization strategy, the query generalization strategy comprising applying strategies to an original query to obtain a generalized level of queries comprising one or more general queries and repeatedly applying the strategies to the generalized level of queries until a prespecified number of results is obtained; and ranking results obtained through the query generalization strategy based on a number generalizations performed. | 14. A method of accessing and managing a relational database comprising: executing a program of instructions with a machine, the program of instructions being configured to: query a relational database; and access semantically relevant query results from the relational database, wherein to access query results from the relational database further comprises; accessing at least one ontology; extracting domain knowledge from at least one ontology and; employing the domain knowledge in obtaining the semantically relevant query results from the relational database; wherein said semantically relevant query results comprise direct results obtained directly from relational database tables, inferred results inferred utilizing information explicitly listed in the relational database and the at least one ontology, and related results obtained utilizing data in the relational database tables and one or more definitions of similarity of concepts and individuals based on the at least one ontology; and wherein to access semantically relevant query results comprises: applying a query generalization strategy, the query generalization strategy comprising applying strategies to an original query to obtain a generalized level of queries comprising one or more general queries and repeatedly applying the strategies to the generalized level of queries until a prespecified number of results is obtained; and ranking results obtained through the query generalization strategy based on a number generalizations performed. 28. The method according to claim 14 , further comprising translating data from the relational database into a predetermined format. | 0.848624 |
9,020,972 | 1 | 5 | 1. A computer implemented method of constructing a database instruction, comprising: receiving a user-generated parameter from a user interface; constructing, in a memory of a computer, an information object based on an element of the user interface associated with the user-generated parameter, the information object including an object type and the user-generated parameter; associating, at runtime, the user-generated parameter with a first template instruction comprising one or more variable tokens each variable token having one or more variable token types, a first variable token occurring more than once in the first template instruction, and a first occurrence of the first variable token having a different variable token type than a second occurrence of the first variable token; determining that a section of a plurality of additional template instructions is defined as optional based on detecting an optional begin token and an optional end token that offset the section of additional template instructions, wherein each of the additional template instructions are associated with a respective variable; substituting, in the first template instruction, the user generated parameter of the information object for the first variable token; and generating a database instruction from at least the first template instruction, at least in part by excluding the additional template instructions from the database instruction based on determining that the information object does not include user-generated parameters for any of the respective variables associated with the additional template instructions. | 1. A computer implemented method of constructing a database instruction, comprising: receiving a user-generated parameter from a user interface; constructing, in a memory of a computer, an information object based on an element of the user interface associated with the user-generated parameter, the information object including an object type and the user-generated parameter; associating, at runtime, the user-generated parameter with a first template instruction comprising one or more variable tokens each variable token having one or more variable token types, a first variable token occurring more than once in the first template instruction, and a first occurrence of the first variable token having a different variable token type than a second occurrence of the first variable token; determining that a section of a plurality of additional template instructions is defined as optional based on detecting an optional begin token and an optional end token that offset the section of additional template instructions, wherein each of the additional template instructions are associated with a respective variable; substituting, in the first template instruction, the user generated parameter of the information object for the first variable token; and generating a database instruction from at least the first template instruction, at least in part by excluding the additional template instructions from the database instruction based on determining that the information object does not include user-generated parameters for any of the respective variables associated with the additional template instructions. 5. The computer implemented method of claim 1 , wherein the database instruction includes an aggregate function, the aggregate function including a command parameter. | 0.918627 |
6,081,665 | 24 | 47 | 24. The RTVMM of claim 12 wherein the implementing step comprises the steps: partitioning memory into at least three demi-spaces, at least one of the demi-spaces being a static space excluded from the garbage collection process; designating two of the demi-spaces as to-space and from-space at the beginning of a garbage collection cycle, live objects residing in from-space subsequently being copied into to-space; designating the remaining demi-spaces as mark-and-sweep spaces at the beginning of a garbage collection cycle, the mark-and-sweep spaces being garbage collected using a mark-and-sweep technique. | 24. The RTVMM of claim 12 wherein the implementing step comprises the steps: partitioning memory into at least three demi-spaces, at least one of the demi-spaces being a static space excluded from the garbage collection process; designating two of the demi-spaces as to-space and from-space at the beginning of a garbage collection cycle, live objects residing in from-space subsequently being copied into to-space; designating the remaining demi-spaces as mark-and-sweep spaces at the beginning of a garbage collection cycle, the mark-and-sweep spaces being garbage collected using a mark-and-sweep technique. 47. The RTVMM of claim 24 wherein the transfer of objects needing finalization from a list of finalizable objects to an activity's finalizee list or an orphaned finalizee list has been accomplished, the implementing step comprising the steps: causing the mark-and-sweep spaces and to-space to be swept and identifying each object that is not marked, that is not on a free list, and that is a "hashlock object"; causing the garbage collection thread to copy the value of a "hash value" field of the "hashlock object" onto a list of recycled hash values if the list is not full; otherwise: causing the garbage collection thread to (1) make the "hashlock object" live, (2) change a "signature" field in the "hashlock object" to represent a "hashcache object", (3) add the "hashcache object" to the list of recycled hash values, and (4) copy the value of the "hash value" field of the original "hashlock object" onto a list of recycled hash values. | 0.75391 |
9,773,429 | 13 | 14 | 13. The welding system of claim 12 , wherein the automated audio coaching includes real-time feedback in the form of automated voice commands, and wherein the automated voice commands include prerecorded audio files that are played to the welding trainee based on predetermined variables being outside of set control limits. | 13. The welding system of claim 12 , wherein the automated audio coaching includes real-time feedback in the form of automated voice commands, and wherein the automated voice commands include prerecorded audio files that are played to the welding trainee based on predetermined variables being outside of set control limits. 14. The welding system of claim 13 , wherein the predetermined variables are arranged in a hierarchy of high-priority variables to low-priority variables, and wherein the predetermined variables include in descending order of priority: a tool placement, a tool offset, a travel speed, a work angle, and a travel angle. | 0.939909 |
9,330,136 | 1 | 3 | 1. A computer-implemented method comprising: receiving data provided by one or more mobile computing systems configured to determine a current location and a travel speed associated with a user, the data describing the current location and the travel speed associated with the user; determining a travel status associated with the user based on the current location and the travel speed, the travel status describing a current state of a journey of the user; creating a zone of relevance for the user based on the travel status, the zone of relevance including one or more regions with each region being mapped to one or more regional circles, creating the zone of relevance including determining a regional angle and a regional length for each region based on the travel status, and generating the one or more regions based on the regional angle and the regional length; generating one or more queries for the zone of relevance; retrieving one or more query results that match the zone of relevance using the one or more queries; processing the one or more query results to generate zone information relevant to the user; and providing the zone information to the user. | 1. A computer-implemented method comprising: receiving data provided by one or more mobile computing systems configured to determine a current location and a travel speed associated with a user, the data describing the current location and the travel speed associated with the user; determining a travel status associated with the user based on the current location and the travel speed, the travel status describing a current state of a journey of the user; creating a zone of relevance for the user based on the travel status, the zone of relevance including one or more regions with each region being mapped to one or more regional circles, creating the zone of relevance including determining a regional angle and a regional length for each region based on the travel status, and generating the one or more regions based on the regional angle and the regional length; generating one or more queries for the zone of relevance; retrieving one or more query results that match the zone of relevance using the one or more queries; processing the one or more query results to generate zone information relevant to the user; and providing the zone information to the user. 3. The method of claim 1 , wherein the one or more queries includes one or more circle queries with each circle query corresponding to one of the one or more regional circles in each region. | 0.857997 |
9,003,278 | 1 | 6 | 1. A computer implemented method comprising: receiving a markup language document specifying a user interface for interacting with a user; receiving a specification comprising a mapping from sets of node types to sets of handlers, wherein each set of node types specified in the mapping is mapped to a set of handlers; representing the markup language document using a hierarchical structure of nodes representing elements of the markup language document and edges connecting the nodes, wherein the hierarchical structure comprises: a subset of nodes mapped to node types; and a root node connected with other nodes via paths comprising nodes and edges; receiving a user input associated with a selected node; identifying a set of node types encountered in a path connecting the root node with the selected node; identifying a set of handlers mapped to the identified set of node types based on the mapping; and executing the handlers in the identified set of handlers. | 1. A computer implemented method comprising: receiving a markup language document specifying a user interface for interacting with a user; receiving a specification comprising a mapping from sets of node types to sets of handlers, wherein each set of node types specified in the mapping is mapped to a set of handlers; representing the markup language document using a hierarchical structure of nodes representing elements of the markup language document and edges connecting the nodes, wherein the hierarchical structure comprises: a subset of nodes mapped to node types; and a root node connected with other nodes via paths comprising nodes and edges; receiving a user input associated with a selected node; identifying a set of node types encountered in a path connecting the root node with the selected node; identifying a set of handlers mapped to the identified set of node types based on the mapping; and executing the handlers in the identified set of handlers. 6. The computer implemented method of claim 1 , wherein the selected node is displayed in the browser as one of a link, button, or image. | 0.857292 |
8,595,232 | 24 | 27 | 24. A method comprising: receiving data including first descriptive information associated with an electronic version of particular media content; searching a database, based at least in part on the first descriptive information, to identify second descriptive information, wherein the second descriptive information is associated with a physical media product, and wherein the physical media product stores the particular media content; storing a data record in memory relating the electronic version of the particular media content to the second descriptive information; and searching the database to identify third descriptive information, wherein the second descriptive information is associated with a first version of the physical media product released in a first geographic region, and wherein the third descriptive information is associated with a second version of the physical media product released in a second geographic region. | 24. A method comprising: receiving data including first descriptive information associated with an electronic version of particular media content; searching a database, based at least in part on the first descriptive information, to identify second descriptive information, wherein the second descriptive information is associated with a physical media product, and wherein the physical media product stores the particular media content; storing a data record in memory relating the electronic version of the particular media content to the second descriptive information; and searching the database to identify third descriptive information, wherein the second descriptive information is associated with a first version of the physical media product released in a first geographic region, and wherein the third descriptive information is associated with a second version of the physical media product released in a second geographic region. 27. The method of claim 24 , further comprising: sending, in response to a request for information related to the electronic version of particular media content, access information to permit access to a portion of a product catalog associated with the physical media product that stores the particular media content. | 0.905952 |
9,405,822 | 19 | 22 | 19. A computer-implemented method of facilitating comparisons of information item attributes based on queries of a topic-based-source-specific search system, the system being configured to collect information from predefined sources relating to a content topic prior to the queries, the method being implemented by the system that includes one or more processors executing one or more computer program modules which, when executed, perform the method, the method comprising: storing, by an indexing module, metadata in association with information items of the predefined sources, wherein the metadata indicate a first attribute relating to first ones of the information items and a second attribute relating to second ones of the information items; receiving, by a query input module, an input relating to a query; and determining, by an information retrieval module, a subset of the information items that relates to the received input; providing, by a user interface module, a display of a user interface that presents a comparison between the first attribute and the second attribute based on one or more first information items of the determined subset that relate to the first attribute and one or more second information items of the determined subset that relate to the second attribute; determining, by a suggestion module, suggested ones of the predefined sources and suggested ones of the information items of the predefined sources based on the received input; providing, by the user interface module, a set of suggestions including a group of suggestions relating to the suggested sources and a group of suggestions relating to the suggested information items for presentation on the user interface; providing, by the user interface module, a query input component on the display of the user interface, wherein the query input component is configured to receive the input; receiving, by the query input module, a second input relating to the query responsive to providing the set of suggestions; and determining, by an information retrieval module, a subset of the information items that relates to the received second input; determining, by the information retrieval module, one or more sources associated with the determined subset of the information items; and providing, by the user interface module, one or more representations of the determined subset of the information items and one or more representations of the determined sources on the display of the user interface simultaneously with the query input component. | 19. A computer-implemented method of facilitating comparisons of information item attributes based on queries of a topic-based-source-specific search system, the system being configured to collect information from predefined sources relating to a content topic prior to the queries, the method being implemented by the system that includes one or more processors executing one or more computer program modules which, when executed, perform the method, the method comprising: storing, by an indexing module, metadata in association with information items of the predefined sources, wherein the metadata indicate a first attribute relating to first ones of the information items and a second attribute relating to second ones of the information items; receiving, by a query input module, an input relating to a query; and determining, by an information retrieval module, a subset of the information items that relates to the received input; providing, by a user interface module, a display of a user interface that presents a comparison between the first attribute and the second attribute based on one or more first information items of the determined subset that relate to the first attribute and one or more second information items of the determined subset that relate to the second attribute; determining, by a suggestion module, suggested ones of the predefined sources and suggested ones of the information items of the predefined sources based on the received input; providing, by the user interface module, a set of suggestions including a group of suggestions relating to the suggested sources and a group of suggestions relating to the suggested information items for presentation on the user interface; providing, by the user interface module, a query input component on the display of the user interface, wherein the query input component is configured to receive the input; receiving, by the query input module, a second input relating to the query responsive to providing the set of suggestions; and determining, by an information retrieval module, a subset of the information items that relates to the received second input; determining, by the information retrieval module, one or more sources associated with the determined subset of the information items; and providing, by the user interface module, one or more representations of the determined subset of the information items and one or more representations of the determined sources on the display of the user interface simultaneously with the query input component. 22. The method of claim 19 , further comprising: providing, by the user interface module, one or more representations of the determined subset of the information items on the display of the user interface simultaneously with the presentation of the comparison. | 0.800919 |
6,067,523 | 9 | 10 | 9. A system for reporting behavioral health care and status of a patient comprising: a computer having resident therein a database comprising: at least one patient electronic chart including: patient demographic information; an answer to a behavioral health assessment question administered to the patient; at least one narrative note format, the narrative note format comprising: fixed text material; and link indicators interspersed within the text material having means for pointing to specific data in the chart database, at least one link indicator related to patient demographic information and at least one link indicator related to the assessment answer; input means for displaying a list of narrative note formats in the database and for selecting a narrative note format therefrom; software means for integrating the narrative note format with the patient chart data pointed to by the link indicators; and means for outputting a report comprising a narrative-style text including information specific to the patient from the patient chart. | 9. A system for reporting behavioral health care and status of a patient comprising: a computer having resident therein a database comprising: at least one patient electronic chart including: patient demographic information; an answer to a behavioral health assessment question administered to the patient; at least one narrative note format, the narrative note format comprising: fixed text material; and link indicators interspersed within the text material having means for pointing to specific data in the chart database, at least one link indicator related to patient demographic information and at least one link indicator related to the assessment answer; input means for displaying a list of narrative note formats in the database and for selecting a narrative note format therefrom; software means for integrating the narrative note format with the patient chart data pointed to by the link indicators; and means for outputting a report comprising a narrative-style text including information specific to the patient from the patient chart. 10. The system recited in claim 9, wherein: the answer comprises a plurality of numerically scaled answers; the narrative note format further includes a calculation indicator having a plurality of link indicators to, and a formula for, directing an arithmetic operation on at least two numerically scaled answers; and the integrating means further comprises means for utilizing the formula to perform the arithmetic operation on the indicated numerically scaled answers for including a result therefrom in the report. | 0.500965 |
8,738,355 | 69 | 74 | 69. An article comprising: a computer readable medium having stored therein computer-implementable instructions executable by one or more processing units in a mobile station to: generate a request for translation information from a translation information service, wherein said translation information is associated with a location and one or more written and/or spoken languages; initiate transmission of said request for translation information to said translation information service; access a response received from said translation information service, said response comprising requested translation information, said requested translation information being based, at least in part, on said request for translation information said location, and predicted information, wherein the predicted information is associated with the request for translation information, the location, and at least one other request for translation information associated with at least one other location and previously transmitted to said translation information service by at least one other mobile station; and initiate a presentation for a user based, at least in part, on said response. | 69. An article comprising: a computer readable medium having stored therein computer-implementable instructions executable by one or more processing units in a mobile station to: generate a request for translation information from a translation information service, wherein said translation information is associated with a location and one or more written and/or spoken languages; initiate transmission of said request for translation information to said translation information service; access a response received from said translation information service, said response comprising requested translation information, said requested translation information being based, at least in part, on said request for translation information said location, and predicted information, wherein the predicted information is associated with the request for translation information, the location, and at least one other request for translation information associated with at least one other location and previously transmitted to said translation information service by at least one other mobile station; and initiate a presentation for a user based, at least in part, on said response. 74. The article as recited in claim 69 , wherein said request for translation information further comprises metadata information. | 0.844952 |
8,965,129 | 1 | 18 | 1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: cropping a frame of the real-time video feed of one or more words of the first language to fit inside a bounding box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments while determining at least a shape score for at least one merged character segment; performing character recognition on the merged character segments by utilizing at least the shape score of the at least one merged character segment to produce a plurality of recognized characters with high scores; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language. | 1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: cropping a frame of the real-time video feed of one or more words of the first language to fit inside a bounding box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments while determining at least a shape score for at least one merged character segment; performing character recognition on the merged character segments by utilizing at least the shape score of the at least one merged character segment to produce a plurality of recognized characters with high scores; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language. 18. The method of claim 1 , further comprising: storing a paused language translation frame comprising the first language and the second language in memory for later review. | 0.877479 |
9,582,394 | 1 | 9 | 1. A method, comprising: detecting an event that causes a compiler to generate diagnostic information; storing the diagnostic information for the event in a manner that preserves semantic information associated with the event; receiving diagnostic information at a particular development tool, wherein the diagnostic information was generated by the compiler while compiling source code for a program created using the development tool, wherein the diagnostic information has a structured representation that is configured to be plugged into at least one diagnostic formatter from a set of diagnostic formatters, which comprises: a raw diagnostic formatter that outputs diagnostic information using an internal format of the compiler for diagnostic information; a tunneling diagnostic formatter that encodes the diagnostic information into a structured XML document; a rich diagnostic formatter that performs the following modifications to the diagnostic information: localizing the diagnostic output; shortening a unique name in the diagnostic information while preserving the name's uniqueness; lengthening a clashing name in the diagnostic information to make the clashing name unique; and adding a where clause to the diagnostic information that provides additional type information for variables in the diagnostic information; selecting the raw diagnostic formatter from the set of diagnostic formatters based on a particular output context for the particular development tool; using the raw diagnostic formatter to modify at least a particular part of the diagnostic information before presenting the particular part of the diagnostic information to a user through the particular development tool; selecting the rich diagnostic formatter from the set of diagnostic formatters; tunneling the diagnostic information through one or more intermediate application layers to a subsequent development tool; using the rich diagnostic formatter to modify at least a subsequent part of the diagnostic information before presenting the subsequent part of the diagnostic information to the user through the subsequent development tool; comparing the modified particular part of the diagnostic information or the modified subsequent part of the diagnostic information to a reference diagnostic output generated by a reference compiler; and presenting the modified particular part of the diagnostic information to the user through the particular development tool, the modified subsequent part of the diagnostic information to the user through the subsequent development tool and results of the comparison to the reference diagnostic output. | 1. A method, comprising: detecting an event that causes a compiler to generate diagnostic information; storing the diagnostic information for the event in a manner that preserves semantic information associated with the event; receiving diagnostic information at a particular development tool, wherein the diagnostic information was generated by the compiler while compiling source code for a program created using the development tool, wherein the diagnostic information has a structured representation that is configured to be plugged into at least one diagnostic formatter from a set of diagnostic formatters, which comprises: a raw diagnostic formatter that outputs diagnostic information using an internal format of the compiler for diagnostic information; a tunneling diagnostic formatter that encodes the diagnostic information into a structured XML document; a rich diagnostic formatter that performs the following modifications to the diagnostic information: localizing the diagnostic output; shortening a unique name in the diagnostic information while preserving the name's uniqueness; lengthening a clashing name in the diagnostic information to make the clashing name unique; and adding a where clause to the diagnostic information that provides additional type information for variables in the diagnostic information; selecting the raw diagnostic formatter from the set of diagnostic formatters based on a particular output context for the particular development tool; using the raw diagnostic formatter to modify at least a particular part of the diagnostic information before presenting the particular part of the diagnostic information to a user through the particular development tool; selecting the rich diagnostic formatter from the set of diagnostic formatters; tunneling the diagnostic information through one or more intermediate application layers to a subsequent development tool; using the rich diagnostic formatter to modify at least a subsequent part of the diagnostic information before presenting the subsequent part of the diagnostic information to the user through the subsequent development tool; comparing the modified particular part of the diagnostic information or the modified subsequent part of the diagnostic information to a reference diagnostic output generated by a reference compiler; and presenting the modified particular part of the diagnostic information to the user through the particular development tool, the modified subsequent part of the diagnostic information to the user through the subsequent development tool and results of the comparison to the reference diagnostic output. 9. The method of claim 1 , wherein at least one of the diagnostic formatters causes one or more filepaths within the diagnostic information to be canonicalized. | 0.898089 |
9,619,250 | 1 | 4 | 1. A computerized system for creating interactive electronic books over a network, comprising: a) an effects library module including a plurality of interactive effects wizard modules that automate code generation for customized interactive effects in electronic books, wherein one of the interactive effects wizard modules automates code generation for an effect selected from the group of effects consisting of: performing a mathematical function on user input; animating a graphic on a trigger; changing a background to a custom background on a trigger; changing text in a body of text to a user input text on a trigger; changing text in a body of text on a trigger; playing an author uploaded audio file on a trigger; and scrolling a user view on a trigger other than a usual scroll trigger; triggering code generated by an interactive effects wizard module; delaying operation of code generated by an interactive effects wizard module; requesting a user input and storing the same in memory; operating a user interface effect; changing a display characteristic of a displayed object; selecting a displayed item; sending data on a trigger; controlling the display of media by a user; and randomizing an effect; b) a first database module including a relational database stored in a memory device that stores information associated with electronic book generation including information related to selected interactive effects wizard modules; c) a second database module including a database; d) a database federation module including a processor functionally coupled between the first database and the second database such that changes to one of the first and second databases are automatically updated in the other; and e) a user interface module functionally coupled to each of the effects library module and the first database module such that a user is able to selectably manipulate the same in creation of an electronic book and including a network module including a network communication device over a network. | 1. A computerized system for creating interactive electronic books over a network, comprising: a) an effects library module including a plurality of interactive effects wizard modules that automate code generation for customized interactive effects in electronic books, wherein one of the interactive effects wizard modules automates code generation for an effect selected from the group of effects consisting of: performing a mathematical function on user input; animating a graphic on a trigger; changing a background to a custom background on a trigger; changing text in a body of text to a user input text on a trigger; changing text in a body of text on a trigger; playing an author uploaded audio file on a trigger; and scrolling a user view on a trigger other than a usual scroll trigger; triggering code generated by an interactive effects wizard module; delaying operation of code generated by an interactive effects wizard module; requesting a user input and storing the same in memory; operating a user interface effect; changing a display characteristic of a displayed object; selecting a displayed item; sending data on a trigger; controlling the display of media by a user; and randomizing an effect; b) a first database module including a relational database stored in a memory device that stores information associated with electronic book generation including information related to selected interactive effects wizard modules; c) a second database module including a database; d) a database federation module including a processor functionally coupled between the first database and the second database such that changes to one of the first and second databases are automatically updated in the other; and e) a user interface module functionally coupled to each of the effects library module and the first database module such that a user is able to selectably manipulate the same in creation of an electronic book and including a network module including a network communication device over a network. 4. The system of claim 1 , wherein the database is a textual data format. | 0.929537 |
7,870,085 | 18 | 19 | 18. A computing system comprising a processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the processor implement a risk assessment method, said method comprising: receiving, by an inference engine within said computing system, first sensor cohort data associated with a first cohort, said first cohort located within a first aircraft; receiving, by said inference engine, first group technology inferences associated with said first cohort; generating, by said inference engine, first risk cohort inferences, said generating said first risk cohort inferences based on said first group technology inferences and said first sensor cohort data; receiving, by said inference engine, first inference data generated by said inference engine, said first inference data comprising a first plurality of inferences associated with said first cohort and a security perimeter area surrounding an airport; receiving, by said inference engine, second inference data generated by said inference engine, said second inference data comprising a second of plurality of inferences associated with said first cohort and a pre/post security area within said airport; receiving, by said inference engine, third inference data generated by said inference engine, said third inference data comprising a third of plurality of inferences associated with said first cohort and a gate area within said airport; receiving, by said inference engine, fourth inference data generated by said inference engine, said fourth inference data comprising a fourth of plurality of inferences associated with said first cohort and a second aircraft; receiving, by said inference engine, fifth inference data generated by said inference engine, said fifth inference data comprising a fifth of plurality of inferences associated with said first cohort and first aircraft; generating, by said inference engine, sixth inference data, said sixth inference data comprising a sixth plurality of inferences associated with said first cohort and said first aircraft, wherein said generating said sixth inference data is based on said first risk cohort inferences, said first inference data, said second inference data, said third inference data, said fourth inference data, and said fifth inference data; generating, by said inference engine based on said sixth inference data, a first associated risk level score for said first cohort; and storing, by said computing system, said sixth inference data and said first associated risk level score. | 18. A computing system comprising a processor coupled to a computer-readable memory unit, said memory unit comprising instructions that when executed by the processor implement a risk assessment method, said method comprising: receiving, by an inference engine within said computing system, first sensor cohort data associated with a first cohort, said first cohort located within a first aircraft; receiving, by said inference engine, first group technology inferences associated with said first cohort; generating, by said inference engine, first risk cohort inferences, said generating said first risk cohort inferences based on said first group technology inferences and said first sensor cohort data; receiving, by said inference engine, first inference data generated by said inference engine, said first inference data comprising a first plurality of inferences associated with said first cohort and a security perimeter area surrounding an airport; receiving, by said inference engine, second inference data generated by said inference engine, said second inference data comprising a second of plurality of inferences associated with said first cohort and a pre/post security area within said airport; receiving, by said inference engine, third inference data generated by said inference engine, said third inference data comprising a third of plurality of inferences associated with said first cohort and a gate area within said airport; receiving, by said inference engine, fourth inference data generated by said inference engine, said fourth inference data comprising a fourth of plurality of inferences associated with said first cohort and a second aircraft; receiving, by said inference engine, fifth inference data generated by said inference engine, said fifth inference data comprising a fifth of plurality of inferences associated with said first cohort and first aircraft; generating, by said inference engine, sixth inference data, said sixth inference data comprising a sixth plurality of inferences associated with said first cohort and said first aircraft, wherein said generating said sixth inference data is based on said first risk cohort inferences, said first inference data, said second inference data, said third inference data, said fourth inference data, and said fifth inference data; generating, by said inference engine based on said sixth inference data, a first associated risk level score for said first cohort; and storing, by said computing system, said sixth inference data and said first associated risk level score. 19. The computing system of claim 18 , wherein said method further comprises: receiving, by said inference engine, second sensor cohort data associated with a second cohort, said second cohort located within said first aircraft; receiving, by said inference engine, second group technology inferences associated with said second cohort; generating, by said inference engine, second risk cohort inferences, said generating said second risk cohort inferences based on said second group technology inferences and said second sensor cohort data; receiving, by said inference engine, seventh inference data generated by said inference engine, said seventh inference data comprising a seventh plurality of inferences associated with said second cohort and said security perimeter area surrounding said airport; receiving, by said inference engine, eighth inference data generated by said inference engine, said eighth inference data comprising an eighth plurality of inferences associated with said second cohort and said pre/post security area within said airport; receiving, by said inference engine, ninth inference data generated by said inference engine, said ninth inference data comprising a ninth plurality of inferences associated with said second cohort and said gate area within said airport; receiving, by said inference engine, tenth inference data generated by said inference engine, said tenth inference data comprising a tenth of plurality of inferences associated with said second cohort and said second aircraft; generating, by said inference engine, eleventh inference data, said eleventh inference data comprising an eleventh plurality of inferences associated with said second cohort, wherein said generating said eleventh inference data is based on second risk cohort inferences, said seventh inference data, said eighth inference data, said ninth inference data, and said tenth inference data; generating, by said inference engine based on said eleventh inference data, a second associated risk level score for said second cohort; and storing, by said computing system, said eleventh inference data and said second associated risk level score. | 0.500231 |
5,560,009 | 24 | 25 | 24. A method for merging translator debug information and compiler debug information to form final debug information for a source code, adapted for use with an object code of the source code, wherein said final debug information completely and accurately represents the source code, the method comprising the steps of: (a) reading said translator and compiler debug information; (b) generating first and second debug data structures from said translator and compiler debug information; (c) generating a merged lookup table from said first and second debug data structures, wherein said merged lookup table comprises said final debug information; and (d) storing said object code and said final debug information in an object code file, wherein said object code file includes an object code file header. | 24. A method for merging translator debug information and compiler debug information to form final debug information for a source code, adapted for use with an object code of the source code, wherein said final debug information completely and accurately represents the source code, the method comprising the steps of: (a) reading said translator and compiler debug information; (b) generating first and second debug data structures from said translator and compiler debug information; (c) generating a merged lookup table from said first and second debug data structures, wherein said merged lookup table comprises said final debug information; and (d) storing said object code and said final debug information in an object code file, wherein said object code file includes an object code file header. 25. The method of claim 24, wherein said step for generating a merged lookup table comprises the steps of: (a) generating first and second lookup tables from said first and second debug data structures; (b) matching said first and second lookup tables so that entries in said first lookup table have corresponding entries in said second lookup table; (c) copying portions of said compiler debug information from said second lookup table to said first lookup table; (d) marking entries in said first lookup table for deletion; and (e) deleting said entries marked for deletion in said first lookup table; wherein said first lookup table comprises said merged lookup table. | 0.500744 |
8,838,688 | 13 | 14 | 13. The apparatus of claim 11 , wherein said inferred set is modified by selecting a set of social neighbors and selecting a set of attributes of said selected set of social neighbors. | 13. The apparatus of claim 11 , wherein said inferred set is modified by selecting a set of social neighbors and selecting a set of attributes of said selected set of social neighbors. 14. The apparatus of claim 13 , wherein said selection of said set of social neighbors further comprises selecting one or more of social neighbors based on a social influence model social neighbors that are active. | 0.855014 |
9,672,206 | 21 | 22 | 21. The method according to claim 20 , further comprising the step of converting characters to a uniform character set. | 21. The method according to claim 20 , further comprising the step of converting characters to a uniform character set. 22. The method according to claim 21 where the sample set of documents is segmented into sections. | 0.970267 |
9,613,374 | 15 | 16 | 15. A method of displaying candidate domain names for registration by a user, the method comprising: obtaining, by a computer server in electronic communication with a computer network, a web page comprising a user interface; receiving, by the computer server from a user via a user device in electronic communication with the computer network, a user query for a domain name comprising input data; and presenting, by the computer server to the user via the user device, the web page; the user interface comprising a carousel comprising a plurality of bundles, each bundle comprising a plurality of the candidate domain names, the plurality of bundles comprising a first set related to a characteristic of a website to be hosted at or accessible from the domain name and a second set, different from the first set, related to the input data, and the carousel enabling the user to paginate through the bundles; and the user interface further comprising a selection mechanism to permit the selection of at least one relevant bundle from the plurality of bundles, to thereby enable the user to formulate a request to register the candidate domain names in the relevant bundle. | 15. A method of displaying candidate domain names for registration by a user, the method comprising: obtaining, by a computer server in electronic communication with a computer network, a web page comprising a user interface; receiving, by the computer server from a user via a user device in electronic communication with the computer network, a user query for a domain name comprising input data; and presenting, by the computer server to the user via the user device, the web page; the user interface comprising a carousel comprising a plurality of bundles, each bundle comprising a plurality of the candidate domain names, the plurality of bundles comprising a first set related to a characteristic of a website to be hosted at or accessible from the domain name and a second set, different from the first set, related to the input data, and the carousel enabling the user to paginate through the bundles; and the user interface further comprising a selection mechanism to permit the selection of at least one relevant bundle from the plurality of bundles, to thereby enable the user to formulate a request to register the candidate domain names in the relevant bundle. 16. The method of claim 15 , wherein each bundle comprises a theme corresponding to the input data or a theme corresponding to the characteristic of the website to be hosted at or accessible from the domain name. | 0.502347 |
8,135,730 | 9 | 12 | 9. An information processing system adapted to retrieving data from a database, the information processing system comprises: a memory; a processor communicatively coupled to the memory; and a database manager communicatively coupled to the memory and the processor, wherein the database manager is configured to: receive, from a user, a search request for a set of data in at least one database; perform, in response to receiving the search request from the user, an ontology query over at least one ontology associated with at least one database resulting in an ontological dataset associated with the search request, wherein the ontological dataset comprises at least one of a set of synonyms, a set of hypernyms, and a set of hyponyms, associated with the search request; perform, in response to performing the ontology query, a data query over data in the at least one database using a union of the ontological dataset with the search keywords in the search request; provide to the user at least a portion of the set of data based on the data query that has been performed; and dynamically adding a column to a table comprising the set of data in the at least one database, wherein each row in the column that has been added comprises a grouping annotation associated with a corresponding data entry in the set of data. | 9. An information processing system adapted to retrieving data from a database, the information processing system comprises: a memory; a processor communicatively coupled to the memory; and a database manager communicatively coupled to the memory and the processor, wherein the database manager is configured to: receive, from a user, a search request for a set of data in at least one database; perform, in response to receiving the search request from the user, an ontology query over at least one ontology associated with at least one database resulting in an ontological dataset associated with the search request, wherein the ontological dataset comprises at least one of a set of synonyms, a set of hypernyms, and a set of hyponyms, associated with the search request; perform, in response to performing the ontology query, a data query over data in the at least one database using a union of the ontological dataset with the search keywords in the search request; provide to the user at least a portion of the set of data based on the data query that has been performed; and dynamically adding a column to a table comprising the set of data in the at least one database, wherein each row in the column that has been added comprises a grouping annotation associated with a corresponding data entry in the set of data. 12. The information processing system of claim 9 , wherein the database manager is further adapted to perform the data query by: identifying data within the at least one database corresponding to the ontological dataset. | 0.871043 |
8,724,441 | 13 | 14 | 13. A bulk type optical recording medium having a bulk layer for selectively performing mark recording at a plurality of positions in a depth direction, wherein a mark row is recorded in the bulk layer based at least in part on code words obtained by performing an encoding process of selecting and outputting a code word, in which an absolute value of a code string Digital Sum Value is smaller, from code words corresponding to the m-bit data words in a first encoding table in which 2 m code words selected from 2 n n-bit code words correspond to 2 m m-bit data words and code words corresponding to the m-bit data words in a second encoding table in which 2 m code words, which do not overlap with the code words in the first encoding table, of the 2 n n-bit code words correspond to 2 m m-bit data words, and both n and m are integers and 2 n ≧2 m ×2. | 13. A bulk type optical recording medium having a bulk layer for selectively performing mark recording at a plurality of positions in a depth direction, wherein a mark row is recorded in the bulk layer based at least in part on code words obtained by performing an encoding process of selecting and outputting a code word, in which an absolute value of a code string Digital Sum Value is smaller, from code words corresponding to the m-bit data words in a first encoding table in which 2 m code words selected from 2 n n-bit code words correspond to 2 m m-bit data words and code words corresponding to the m-bit data words in a second encoding table in which 2 m code words, which do not overlap with the code words in the first encoding table, of the 2 n n-bit code words correspond to 2 m m-bit data words, and both n and m are integers and 2 n ≧2 m ×2. 14. The optical recording medium according to claim 13 , wherein the mark row recorded in the bulk layer is a mark row based at least in part on NRZ data obtained by performing inverting to a symbol “1” and non-inverting to a symbol “0” with respect to an encoded string of encoded code words. | 0.822209 |
7,831,534 | 29 | 30 | 29. The method of claim 27 , further comprising: a) identifying a specific object; b) specializing properties of the object by selecting attributes of the stored plurality of criteria, wherein only attributes of applicable criterion may be selected; and c) composing the selected attributes into an attributive expression. | 29. The method of claim 27 , further comprising: a) identifying a specific object; b) specializing properties of the object by selecting attributes of the stored plurality of criteria, wherein only attributes of applicable criterion may be selected; and c) composing the selected attributes into an attributive expression. 30. The method of claim 29 , further comprising: a) storing the attributive expression composed of the selected attributes in a computer-readable medium, if that attributive expression is not currently stored; and b) storing in a computer-readable medium a link between the attributive expression and the data associated with the object. | 0.912285 |
10,007,680 | 8 | 14 | 8. A system, comprising: a processor; memory including instructions that, upon being executed by the processor, cause the system to: receive a search request specifying query content, the query content characterized by query descriptors at a plurality of scales; for each content piece of at least one portion of a content collection: identifying a subset of content descriptors of the content piece at each of the plurality of scales, the content descriptors characterizing and describing one or more regions of the content piece, each of the subset of the content descriptors at a respective scale of the plurality of scales corresponding to at least one portion of the query descriptors at the respective scale; determining a size of the query content to generate respective first proportion thresholds with respect to the size of the query content; determine whether a respective first proportion of the subset of the content descriptors at each respective scale is greater than the generated respective first proportion threshold corresponding to the respective scale, the respective first proportion threshold comprising a region size threshold corresponding to the respective scale; and select the content piece for inclusion in a matching content subset of the content collection when at least one of the one or more regions of the subset of content descriptors includes a proportionate size greater than the respective first proportion threshold; and provide the matching content subset in response to the search request. | 8. A system, comprising: a processor; memory including instructions that, upon being executed by the processor, cause the system to: receive a search request specifying query content, the query content characterized by query descriptors at a plurality of scales; for each content piece of at least one portion of a content collection: identifying a subset of content descriptors of the content piece at each of the plurality of scales, the content descriptors characterizing and describing one or more regions of the content piece, each of the subset of the content descriptors at a respective scale of the plurality of scales corresponding to at least one portion of the query descriptors at the respective scale; determining a size of the query content to generate respective first proportion thresholds with respect to the size of the query content; determine whether a respective first proportion of the subset of the content descriptors at each respective scale is greater than the generated respective first proportion threshold corresponding to the respective scale, the respective first proportion threshold comprising a region size threshold corresponding to the respective scale; and select the content piece for inclusion in a matching content subset of the content collection when at least one of the one or more regions of the subset of content descriptors includes a proportionate size greater than the respective first proportion threshold; and provide the matching content subset in response to the search request. 14. The system of claim 8 , wherein the respective first proportion threshold corresponding to each respective scale correspond to a same value. | 0.84 |
8,103,646 | 13 | 19 | 13. A computer-implemented system of information management executed by a processor, comprising: a search component for searching information sources containing audio data from which text is transcribed for tag and content relationship data; a tag classification model for producing tag information based on the relationship data comprising taxonomy between tags and an associated corpus of tagged content; a tag classifier for obtaining tag information from the produced tag information of the tag classification model and for applying at least one of probabilistic or statistical analysis to the transcribed text in order to classify the text for tagging, to implement a confidence threshold to reduce the likelihood of an inappropriate tag being selected for the transcribed text; a tag for new content based on the taxonomy employed in the tag classification model; and a processor that executes computer-executable instructions associated with at least one of the search component, the tag classification model, the tag classifier, or the tag. | 13. A computer-implemented system of information management executed by a processor, comprising: a search component for searching information sources containing audio data from which text is transcribed for tag and content relationship data; a tag classification model for producing tag information based on the relationship data comprising taxonomy between tags and an associated corpus of tagged content; a tag classifier for obtaining tag information from the produced tag information of the tag classification model and for applying at least one of probabilistic or statistical analysis to the transcribed text in order to classify the text for tagging, to implement a confidence threshold to reduce the likelihood of an inappropriate tag being selected for the transcribed text; a tag for new content based on the taxonomy employed in the tag classification model; and a processor that executes computer-executable instructions associated with at least one of the search component, the tag classification model, the tag classifier, or the tag. 19. The system of claim 13 , further comprising a machine learning and reasoning component for automating at least one feature of modeling and tagging. | 0.66886 |
5,588,056 | 44 | 45 | 44. A system for generating a pronounceable security password according to claim 43, further comprising means for determining if consecutive characters of said first pronounceable word segment correspond to a stored first word segment portion categorized in a non-selection category. | 44. A system for generating a pronounceable security password according to claim 43, further comprising means for determining if consecutive characters of said first pronounceable word segment correspond to a stored first word segment portion categorized in a non-selection category. 45. A system for generating a pronounceable security password according to claim 44, further comprising: means for identifying one of said stored first word segment portions categorized in said one or more selection categories and corresponding to consecutive characters at an end portion of said first pronounceable word segment; means for retrieving a second one of said stored second word segment portions from the set of stored second word segment portions associated with the identified stored first word segment portion, wherein selection of any one of said stored second word segment portions in said associated set of stored second word segment portions is of substantially equal probability; and means for combining said first pronounceable word segment with said second retrieved second word segment portion to form a part of said password; wherein said pronounceable security password also includes said second retrieved second word segment portion only if consecutive characters of said part of said password fail to correspond to those of said stored plurality of first word segment portions categorized in said non-selection category. | 0.822785 |
5,502,774 | 22 | 24 | 22. The system of claim 19 wherein said first transformation means comprises a plurality of transducers. | 22. The system of claim 19 wherein said first transformation means comprises a plurality of transducers. 24. The system of claim 22, wherein said organizing means comprises at least two feature vector processors, responsive to the output of said plurality of interfaces, and configured to represent said consistent message as multi-dimensional vectors. | 0.940425 |
8,589,371 | 13 | 14 | 13. The system of claim 8 wherein the at least one computing processor is operable to: retrieve one or more content items in a result set in response to receipt of a query from the user; for a given content item in the result set, determine a feature vector for the given content item; apply the relevance function trained with the query differentiation to the feature vector for the given content item; and generate a relevance score for the given content item. | 13. The system of claim 8 wherein the at least one computing processor is operable to: retrieve one or more content items in a result set in response to receipt of a query from the user; for a given content item in the result set, determine a feature vector for the given content item; apply the relevance function trained with the query differentiation to the feature vector for the given content item; and generate a relevance score for the given content item. 14. The system of claim 13 wherein the at least one computing processor is operable to order the given content item in the result set according to the relevance score for the given content item. | 0.914387 |
9,183,288 | 1 | 3 | 1. A computer-based method of organizing data for search, the method comprising the steps of: accessing a domain corpus; parsing the domain corpus into a plurality of documents; parsing each document into at least one term that corresponds to the document; generating a term-to-document matrix that correlates each document with the at least one term that corresponds to the document, the at least one term defining a document node for the document; performing a singular value decomposition and a dimension reduction on the term-to-document matrix to form a reformed term-to-document matrix having document nodes with fewer dimensions than the document nodes of the term-to-document matrix; comparing at least one document node of the reformed term-to-document matrix against another document node of the reformed term-to-document matrix; and combining at least one document node of the term-to-document matrix with another document node of the term-to-document matrix, based on the comparison of the at least one document node of the reformed tem-to-document matrix against the another document node of the reformed term-to-document matrix, to form a combined document node representing the combination of the at least one document node of the term-to-document matrix with the another document node of the term-to-document matrix, thereby clustering at least two document nodes of the term-to-document matrix. | 1. A computer-based method of organizing data for search, the method comprising the steps of: accessing a domain corpus; parsing the domain corpus into a plurality of documents; parsing each document into at least one term that corresponds to the document; generating a term-to-document matrix that correlates each document with the at least one term that corresponds to the document, the at least one term defining a document node for the document; performing a singular value decomposition and a dimension reduction on the term-to-document matrix to form a reformed term-to-document matrix having document nodes with fewer dimensions than the document nodes of the term-to-document matrix; comparing at least one document node of the reformed term-to-document matrix against another document node of the reformed term-to-document matrix; and combining at least one document node of the term-to-document matrix with another document node of the term-to-document matrix, based on the comparison of the at least one document node of the reformed tem-to-document matrix against the another document node of the reformed term-to-document matrix, to form a combined document node representing the combination of the at least one document node of the term-to-document matrix with the another document node of the term-to-document matrix, thereby clustering at least two document nodes of the term-to-document matrix. 3. The computer-based method of claim 1 , wherein the step of combining the at least one document node of the tem-to-document matrix with the another document node of the term-to-document matrix to form a combined document node representing the combination of the at least one document node of the term-to-document matrix with the another document node of the term-to-document matrix, includes summing the at least one document node of the term-to-document matrix with the another document node of the term-to-document matrix, | 0.737 |
8,082,277 | 1 | 5 | 1. A document generation system, comprising: a plurality of client computer systems; and a server computer system having memory for storing data defining a document, the document having a plurality of sections, the server computer system configured to communicate with the client computer systems via a network, the server computer system configured to define a plurality of permission levels, including at least a first permission level, a second permission level, and a third permission level, and to assign each of a plurality of users to a respective one of the permission levels, wherein users assigned to the first permission level are authorized by the server computer system to at least modify the document, wherein users assigned to the second permission level are authorized by the server computer system to at least review the document and make comments for reading by at least one user assigned to the first permission level, and wherein users assigned to the third permission level are authorized by the server computer system to at least review the document and approve the document on a section-by-section basis, the server computer system configured to permit a first user assigned to the first permission level to edit a first section of the document and to provide a first input for indicating that the first user deems the first section to be ready for review by at least one user assigned to the second permission level, the server computer system further configured to automatically send a notice to a second user assigned to the second permission level in response to the first input, the server computer system configured to permit the second user to review the first section, provide a comment related to the first section, and provide a second input for indicating that the second user approves the first section for review by at least one user assigned to the third permission level, the server computer system configured to provide the comment from the second user to the first user and to automatically send a notice to a third user assigned to the third permission level in response to the second user input, the server computer system configured to permit the third user to review the first section and provide a third input for indicating that the third user approves the first section, the server computer system configured to associate each section of the document with a respective status indicator indicating whether the respective section has been approved by at least one user assigned to the second permission level, the server computer system configured to update the status indicator assigned to the first section in response to the second input to indicate that the first section has been approved by at least one user assigned to the second permission level. | 1. A document generation system, comprising: a plurality of client computer systems; and a server computer system having memory for storing data defining a document, the document having a plurality of sections, the server computer system configured to communicate with the client computer systems via a network, the server computer system configured to define a plurality of permission levels, including at least a first permission level, a second permission level, and a third permission level, and to assign each of a plurality of users to a respective one of the permission levels, wherein users assigned to the first permission level are authorized by the server computer system to at least modify the document, wherein users assigned to the second permission level are authorized by the server computer system to at least review the document and make comments for reading by at least one user assigned to the first permission level, and wherein users assigned to the third permission level are authorized by the server computer system to at least review the document and approve the document on a section-by-section basis, the server computer system configured to permit a first user assigned to the first permission level to edit a first section of the document and to provide a first input for indicating that the first user deems the first section to be ready for review by at least one user assigned to the second permission level, the server computer system further configured to automatically send a notice to a second user assigned to the second permission level in response to the first input, the server computer system configured to permit the second user to review the first section, provide a comment related to the first section, and provide a second input for indicating that the second user approves the first section for review by at least one user assigned to the third permission level, the server computer system configured to provide the comment from the second user to the first user and to automatically send a notice to a third user assigned to the third permission level in response to the second user input, the server computer system configured to permit the third user to review the first section and provide a third input for indicating that the third user approves the first section, the server computer system configured to associate each section of the document with a respective status indicator indicating whether the respective section has been approved by at least one user assigned to the second permission level, the server computer system configured to update the status indicator assigned to the first section in response to the second input to indicate that the first section has been approved by at least one user assigned to the second permission level. 5. The document generation system of claim 1 , wherein the server computer system is configured to permit at least one user to access and modify a second section of the document while the first user is modifying the first section. | 0.524793 |
9,742,912 | 1 | 3 | 1. A computer implemented method, comprising: receiving, at an interactive voice response (IVR) system, a natural language query associated with a customer during a customer interaction; identifying, by the IVR system, a customer intent based on key features in the natural language query along with any of past interactions of said customer with the IVR system, customer relations management (CRM) system attributes, and customer segment attributes, said identifying including: converting speech associated with a natural language response of said customer into text, the natural language response received during the customer interaction; determining a predicted identity of the customer based on a gender of the customer and an age group of the customer; accessing a customer relations management (CRM) system to obtain the CRM attributes associated with the customer and the customer segment attributes, wherein the CRM attributes include the past interactions of the customer with the IVR system, wherein the customer segment attributes include attributes associated with the gender and the age group identified based on the natural language response; extracting at least one key feature from the text, wherein the at least one key feature is an identified keyword based on a statistical model; and computing a probability score of at least one intent associated with the at least one key feature, said computing the probability score comprising finding a best match, by a machine learning algorithm, between a first sequence of customer intents immediately preceding the customer intent and a second sequence of customer intents preceding the first sequence of customer intents, wherein the first sequence of customer intents and the second sequence of customer intents are ordered by a time and a date, wherein if the probability score of the at least one intent is greater than a threshold a journey of the IVR system of the customer is optimized and if the probability score of the at least one intent is less than the threshold a standard journey of the IVR system is offered to the customer. | 1. A computer implemented method, comprising: receiving, at an interactive voice response (IVR) system, a natural language query associated with a customer during a customer interaction; identifying, by the IVR system, a customer intent based on key features in the natural language query along with any of past interactions of said customer with the IVR system, customer relations management (CRM) system attributes, and customer segment attributes, said identifying including: converting speech associated with a natural language response of said customer into text, the natural language response received during the customer interaction; determining a predicted identity of the customer based on a gender of the customer and an age group of the customer; accessing a customer relations management (CRM) system to obtain the CRM attributes associated with the customer and the customer segment attributes, wherein the CRM attributes include the past interactions of the customer with the IVR system, wherein the customer segment attributes include attributes associated with the gender and the age group identified based on the natural language response; extracting at least one key feature from the text, wherein the at least one key feature is an identified keyword based on a statistical model; and computing a probability score of at least one intent associated with the at least one key feature, said computing the probability score comprising finding a best match, by a machine learning algorithm, between a first sequence of customer intents immediately preceding the customer intent and a second sequence of customer intents preceding the first sequence of customer intents, wherein the first sequence of customer intents and the second sequence of customer intents are ordered by a time and a date, wherein if the probability score of the at least one intent is greater than a threshold a journey of the IVR system of the customer is optimized and if the probability score of the at least one intent is less than the threshold a standard journey of the IVR system is offered to the customer. 3. The method of claim 1 , wherein said speech is converted into the text based on a statistical language mode. | 0.814381 |
9,575,969 | 16 | 17 | 16. A system for generating concept structures from signature reduced clusters (SRCs), comprising: a processor; and a memory, the memory containing instructions that, when executed by the processor, configure the system to: retrieve at least one current SRC comprising a cluster of signatures respective of a plurality of multimedia data dements (MMDEs); generate a plurality of metadata for each signature of the duster of signatures; identify a number of repetitions of each metadata, within the at least one current retrieved SRC, of the plurality of metadata; determine whether the number of repetitions of each metadata of the plurality of metadata exceeds a predefined repetition threshold; upon determining that the number of repetitions of a metadata of the plurality of metadata exceeds the predefined repetition threshold, identify the metadata as representative of the current retrieved SRC; determine an overlap level between all identified representative metadata of the current retrieved SRC and all metadata that is representative of at least one previously generated SRC; determine whether the overlap level exceeds a predetermined threshold; and upon determining that the overlap level exceeds a predetermined threshold, identify the retrieved SRC and the previously generated SRC as a concept structure, wherein the concept structure is represented by the representative matching metadata from both the current retrieved SRC and the at least one previously generated SRC. | 16. A system for generating concept structures from signature reduced clusters (SRCs), comprising: a processor; and a memory, the memory containing instructions that, when executed by the processor, configure the system to: retrieve at least one current SRC comprising a cluster of signatures respective of a plurality of multimedia data dements (MMDEs); generate a plurality of metadata for each signature of the duster of signatures; identify a number of repetitions of each metadata, within the at least one current retrieved SRC, of the plurality of metadata; determine whether the number of repetitions of each metadata of the plurality of metadata exceeds a predefined repetition threshold; upon determining that the number of repetitions of a metadata of the plurality of metadata exceeds the predefined repetition threshold, identify the metadata as representative of the current retrieved SRC; determine an overlap level between all identified representative metadata of the current retrieved SRC and all metadata that is representative of at least one previously generated SRC; determine whether the overlap level exceeds a predetermined threshold; and upon determining that the overlap level exceeds a predetermined threshold, identify the retrieved SRC and the previously generated SRC as a concept structure, wherein the concept structure is represented by the representative matching metadata from both the current retrieved SRC and the at least one previously generated SRC. 17. The system of claim 16 , wherein the system is further configured to: remove any repeat instances of each metadata of the plurality of metadata. | 0.897649 |
9,734,181 | 9 | 14 | 9. At a computer system, a method for detecting a column header for a table including one or more rows, the method comprising: constructing a set of candidate column names for the table from data defining the table; for each candidate column name in the set of candidate column names: calculating a candidate column name frequency for the candidate column name by identifying one or more other tables, from among a set of other tables, that also contain the candidate column name as a candidate column name; and calculating a non-candidate column name frequency for the candidate column name by identifying a second one or more other tables, from among the set of other tables, that contain the candidate column name other than as a candidate column name; and selecting a row of the table as a column header when at least a specified threshold of candidate column names contained in the row have a candidate column name frequency that is greater than a non-candidate column name frequency. | 9. At a computer system, a method for detecting a column header for a table including one or more rows, the method comprising: constructing a set of candidate column names for the table from data defining the table; for each candidate column name in the set of candidate column names: calculating a candidate column name frequency for the candidate column name by identifying one or more other tables, from among a set of other tables, that also contain the candidate column name as a candidate column name; and calculating a non-candidate column name frequency for the candidate column name by identifying a second one or more other tables, from among the set of other tables, that contain the candidate column name other than as a candidate column name; and selecting a row of the table as a column header when at least a specified threshold of candidate column names contained in the row have a candidate column name frequency that is greater than a non-candidate column name frequency. 14. The method of claim 9 , wherein constructing a set of candidate column names for the table comprises constructing a set of candidate column names for a relational web table. | 0.896612 |
6,134,235 | 36 | 40 | 36. A method of bridging a first communications network having a payload subnetwork and a signaling subnetwork with a second communications network that is packet-switched, comprising the steps of: a. establishing a first communications link to the payload subnetwork of the first communications network for communicating payload information; b. establishing a second communications link to the signaling subnetwork of the first communications network for communicating signaling information in accordance with a signaling protocol associated with the signaling subnetwork; c. establishing a third communications link to the second communications network for communicating information in accordance with a communications protocol associated with the second communications network; and d. coordinating the transfer of information between the first communications network and the second communications network using the first communications link, the second communications link and the third communications link, wherein the step of coordinating the transfer of information between the first communications network and the second communications network includes initiating at least one of the tasks of communications session setup, communications session tear down, bridging of two communications requests or routing of a communications to a communications access point in one of the first communications network or the second communications network. | 36. A method of bridging a first communications network having a payload subnetwork and a signaling subnetwork with a second communications network that is packet-switched, comprising the steps of: a. establishing a first communications link to the payload subnetwork of the first communications network for communicating payload information; b. establishing a second communications link to the signaling subnetwork of the first communications network for communicating signaling information in accordance with a signaling protocol associated with the signaling subnetwork; c. establishing a third communications link to the second communications network for communicating information in accordance with a communications protocol associated with the second communications network; and d. coordinating the transfer of information between the first communications network and the second communications network using the first communications link, the second communications link and the third communications link, wherein the step of coordinating the transfer of information between the first communications network and the second communications network includes initiating at least one of the tasks of communications session setup, communications session tear down, bridging of two communications requests or routing of a communications to a communications access point in one of the first communications network or the second communications network. 40. The method according to claim 36, further comprising the step of coordinating operations, administration, maintenance and provisioning functions. | 0.911415 |
8,214,217 | 1 | 5 | 1. A method comprising: extracting, via a processor, at a first time a plurality of phoneme sequences from a text corpus, where a phoneme sequence within the plurality of phoneme sequences occurs at least twice within the text corpus; identifying joins calculated to synthesize the phoneme sequence to yield identified joins; and storing the identified joins in a cache for use in speech synthesis at a second time that is later than the first time. | 1. A method comprising: extracting, via a processor, at a first time a plurality of phoneme sequences from a text corpus, where a phoneme sequence within the plurality of phoneme sequences occurs at least twice within the text corpus; identifying joins calculated to synthesize the phoneme sequence to yield identified joins; and storing the identified joins in a cache for use in speech synthesis at a second time that is later than the first time. 5. The method of claim 1 , further comprising: optimizing the cache based on frequency of occurrence of the identified joins. | 0.871399 |
8,606,728 | 17 | 19 | 17. A computer-readable storage device having stored thereon instructions, which, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: calculating one or more types of suggestion scores for each of a plurality of training examples, wherein each type of suggestion score is based at least in part on a plurality of computed predictions for each training example generated by a plurality of different trained models, including weighting each type of suggestion score by an accuracy of the trained model that generated the prediction; calculating an overall suggestion score for each training example based at least in part on a combination of the one or more types of suggestion scores for each training example; ranking the training examples by the corresponding overall suggestion scores; and providing one or more highest-ranked training examples as a set of suggested training examples. | 17. A computer-readable storage device having stored thereon instructions, which, when executed by data processing apparatus, cause the data processing apparatus to perform operations comprising: calculating one or more types of suggestion scores for each of a plurality of training examples, wherein each type of suggestion score is based at least in part on a plurality of computed predictions for each training example generated by a plurality of different trained models, including weighting each type of suggestion score by an accuracy of the trained model that generated the prediction; calculating an overall suggestion score for each training example based at least in part on a combination of the one or more types of suggestion scores for each training example; ranking the training examples by the corresponding overall suggestion scores; and providing one or more highest-ranked training examples as a set of suggested training examples. 19. The storage device of claim 17 , wherein one of the one or more types of suggestion scores is an ambiguity score, wherein the ambiguity score for a particular training example in the training examples is based on an answer distribution of a training example between two or more categories. | 0.786131 |
9,047,261 | 1 | 2 | 1. A method of editing a document, the method including: a) receiving data associated with the document, the data including mark-up language data; b) processing the received data to render at least part of the document for display in a first display area of a display, and displaying as rendered the at least part of the document in the first display area, wherein the rendering comprises formatting the at least part of the document based on the mark-up language data; c) processing the received data to render the at least part of the document for display in a second display area of the display, and displaying as rendered the at least part of the document in the second display area, wherein the rendering comprises formatting the at least part of the document based on the mark-up language data; d) receiving editing data; e) editing the at least part of the document displayed in the second display area using the editing data, and applying said editing to the at least part of the document displayed in the first display area; f) storing data associated with the at least part of the document edited in e) as a first edited version; g) receiving further editing data; h) further editing the at least part of the document displayed in the second display area using the further editing data and applying the further editing to the edited at least part of the document displayed in the first display area; and i) storing as a second edited version data associated with the further edited at least part of the document. | 1. A method of editing a document, the method including: a) receiving data associated with the document, the data including mark-up language data; b) processing the received data to render at least part of the document for display in a first display area of a display, and displaying as rendered the at least part of the document in the first display area, wherein the rendering comprises formatting the at least part of the document based on the mark-up language data; c) processing the received data to render the at least part of the document for display in a second display area of the display, and displaying as rendered the at least part of the document in the second display area, wherein the rendering comprises formatting the at least part of the document based on the mark-up language data; d) receiving editing data; e) editing the at least part of the document displayed in the second display area using the editing data, and applying said editing to the at least part of the document displayed in the first display area; f) storing data associated with the at least part of the document edited in e) as a first edited version; g) receiving further editing data; h) further editing the at least part of the document displayed in the second display area using the further editing data and applying the further editing to the edited at least part of the document displayed in the first display area; and i) storing as a second edited version data associated with the further edited at least part of the document. 2. A method according to claim 1 , including simultaneously displaying the first display area and the second display area. | 0.813456 |
9,361,887 | 1 | 7 | 1. A computer-implemented method, the method being implemented in a computer system having one or more physical processors programmed with computer program instructions that, when executed by the one or more physical processors, cause the computer system to perform the method, the method comprising: receiving from a natural language processing training device an identification token containing a first portion and a second portion, the first portion identifying a first file for a voice data collection campaign, and the second portion identifying a second file for a session script, the session script supporting a mobile application on the natural language processing training device; using the first file and the second file to configure the mobile application to display a sequence of screens, each of the sequence of screens containing text of at least one utterance specified in the voice data collection campaign; receiving voice data from the natural language processing training device in response to user interaction with the text of the at least one utterance; and storing the voice data and the text of the at least one utterance in a transcription library. | 1. A computer-implemented method, the method being implemented in a computer system having one or more physical processors programmed with computer program instructions that, when executed by the one or more physical processors, cause the computer system to perform the method, the method comprising: receiving from a natural language processing training device an identification token containing a first portion and a second portion, the first portion identifying a first file for a voice data collection campaign, and the second portion identifying a second file for a session script, the session script supporting a mobile application on the natural language processing training device; using the first file and the second file to configure the mobile application to display a sequence of screens, each of the sequence of screens containing text of at least one utterance specified in the voice data collection campaign; receiving voice data from the natural language processing training device in response to user interaction with the text of the at least one utterance; and storing the voice data and the text of the at least one utterance in a transcription library. 7. The method of claim 1 , wherein the user interaction comprises a selection of a touch-screen button instructing the mobile application to record the voice data. | 0.682879 |
8,933,962 | 3 | 5 | 3. A method as recited in claim 1 , wherein identifying the one or more clipart images comprises: determining whether individual images of the plurality of images include a simple background or a complex background; and identifying one or more images of the plurality of images as the one or more clipart images in response to determining that the one or images include the simple background. | 3. A method as recited in claim 1 , wherein identifying the one or more clipart images comprises: determining whether individual images of the plurality of images include a simple background or a complex background; and identifying one or more images of the plurality of images as the one or more clipart images in response to determining that the one or images include the simple background. 5. A method as recited in claim 3 , wherein searching the database or the network by using the keyword as the search query to provide the plurality of images comprises: automatically appending another keyword to the search query, the another keyword including “cartoon” or “clipart”; and specifying a characteristic of a respective image in the plurality of images, the characteristic including: a size or precision; or a style including line style or texture. | 0.813916 |
9,684,640 | 1 | 4 | 1. A method comprising: creating, by a computer-based system, a linkage data structure corresponding to a second programming language different from a markup language, wherein the linkage data structure includes a field for each tag in a set of tags associated with the markup language, wherein the set of tags is retrieved by parsing a document; generating, by the computer-based system, program code in the second programming language based on the set of tags, wherein the generating comprises: creating a procedure division statement in the second programming language; wherein the procedure division statement is capable of accepting a document written in the markup language, wherein the document is variable length, and wherein the procedure division statement is capable of returning a fixed format data structure corresponding to the linkage data structure, creating a second programming language section to contain the program code in the second programming language; and producing, by the procedure division statement and the second programming language section, the program code in the second programming language, wherein the program code is configured to extract, from the document written in the markup language, the set of tags associated with the markup language and at least one attribute associated with each tag; forming, by the computer-based system, an application programming interface (API) that includes the linkage data structure and the program code; and using, by the computer-based system, the application programming interface (API) to pass content from one or more documents written in the markup language to a program element of a program written in the second programming language. | 1. A method comprising: creating, by a computer-based system, a linkage data structure corresponding to a second programming language different from a markup language, wherein the linkage data structure includes a field for each tag in a set of tags associated with the markup language, wherein the set of tags is retrieved by parsing a document; generating, by the computer-based system, program code in the second programming language based on the set of tags, wherein the generating comprises: creating a procedure division statement in the second programming language; wherein the procedure division statement is capable of accepting a document written in the markup language, wherein the document is variable length, and wherein the procedure division statement is capable of returning a fixed format data structure corresponding to the linkage data structure, creating a second programming language section to contain the program code in the second programming language; and producing, by the procedure division statement and the second programming language section, the program code in the second programming language, wherein the program code is configured to extract, from the document written in the markup language, the set of tags associated with the markup language and at least one attribute associated with each tag; forming, by the computer-based system, an application programming interface (API) that includes the linkage data structure and the program code; and using, by the computer-based system, the application programming interface (API) to pass content from one or more documents written in the markup language to a program element of a program written in the second programming language. 4. The method of claim 1 , wherein the set of tags are associated with the markup language. | 0.902361 |
10,097,785 | 1 | 9 | 1. An apparatus for selectively supplementing main program video content with a sign language video content, comprising: a video receiver device configured to receive data representing audio and a frame of video content, the data having a plurality of packet identifiers (PIDs) where a first PID is associated with main program video content, and where a second PID is associated with sign language video content; where the main program video content comprises frames of video content in which a plurality of locations are processed to accept substitution of the sign language video content; a user interface forming a part of the video receiver device, configured to produce a signal indicative of selection of a first location of the plurality of locations for display of the sign language video content; and a content circuit forming a part of the video receiver device; where responsive to the signal indicative of the selection, the content circuit is configured to present at the first location the sign language video content to produce a video frame having a sub-frame containing the sign language video content at the first location; at least one scaler to re-scale video information, wherein the video receiver device is configured to, responsive to a signal to view the sign language video content, enable a picture-in-picture (PIP) circuit, the video receiver device also being configured to disable the video scaler when the PIP circuit is enabled, and wherein the video receiver device is configured to, responsive to a signal not to view the sign language video content, disable the picture-in-picture (PIP) circuit and enable the video scaler. | 1. An apparatus for selectively supplementing main program video content with a sign language video content, comprising: a video receiver device configured to receive data representing audio and a frame of video content, the data having a plurality of packet identifiers (PIDs) where a first PID is associated with main program video content, and where a second PID is associated with sign language video content; where the main program video content comprises frames of video content in which a plurality of locations are processed to accept substitution of the sign language video content; a user interface forming a part of the video receiver device, configured to produce a signal indicative of selection of a first location of the plurality of locations for display of the sign language video content; and a content circuit forming a part of the video receiver device; where responsive to the signal indicative of the selection, the content circuit is configured to present at the first location the sign language video content to produce a video frame having a sub-frame containing the sign language video content at the first location; at least one scaler to re-scale video information, wherein the video receiver device is configured to, responsive to a signal to view the sign language video content, enable a picture-in-picture (PIP) circuit, the video receiver device also being configured to disable the video scaler when the PIP circuit is enabled, and wherein the video receiver device is configured to, responsive to a signal not to view the sign language video content, disable the picture-in-picture (PIP) circuit and enable the video scaler. 9. The apparatus according to claim 1 , where the apparatus forms a part of a television Set-top box. | 0.874378 |
9,308,445 | 1 | 16 | 1. A game delivery system for delivering a plurality of games in a training program configured to systematically drive neurological changes to overcome cognitive deficits associated with a neurological disorder, the game delivery system comprising: a computerized game manager configured to assess a game participant and, in response to the assessment, calibrate a training program comprising games for the game participant; the computerized game manager also being configured to administer the games, manipulate a plurality of game stimuli, and receive input from a game piece; and a participant portal that provides remote access to and delivers the games to game participants; wherein the game manager is configured to administer games of the training program to the game participant by: presenting a plurality of target and/or distractor stimuli; prompting the game participant to respond to the target and/or distractor stimuli; receiving the game participant's input through the game piece; and repeating the presenting through providing a signal steps over multiple repetitions while adapting one or more difficulty parameters to target maintenance of a success rate within a predetermined range; wherein the game manager is further configured to administer an assessment, using at least one of the plurality of games, by administering a brief version of the game using mid-level game difficulty parameters. | 1. A game delivery system for delivering a plurality of games in a training program configured to systematically drive neurological changes to overcome cognitive deficits associated with a neurological disorder, the game delivery system comprising: a computerized game manager configured to assess a game participant and, in response to the assessment, calibrate a training program comprising games for the game participant; the computerized game manager also being configured to administer the games, manipulate a plurality of game stimuli, and receive input from a game piece; and a participant portal that provides remote access to and delivers the games to game participants; wherein the game manager is configured to administer games of the training program to the game participant by: presenting a plurality of target and/or distractor stimuli; prompting the game participant to respond to the target and/or distractor stimuli; receiving the game participant's input through the game piece; and repeating the presenting through providing a signal steps over multiple repetitions while adapting one or more difficulty parameters to target maintenance of a success rate within a predetermined range; wherein the game manager is further configured to administer an assessment, using at least one of the plurality of games, by administering a brief version of the game using mid-level game difficulty parameters. 16. The game delivery system of claim 1 , wherein the plurality of games are structured to progress, for each game participant, from a low initial difficulty level that is easily achievable by the game participant toward an approximate asymptotic limit of performance of the game participant. | 0.70082 |
9,646,606 | 1 | 14 | 1. A method of performing speech recognition that is performed by one or more computers of an automated speech recognizer, the method comprising: receiving, by the one or more computers, data that indicates multiple candidate transcriptions for an utterance, wherein the one or more computers are in communication with (i) a first search system that provides a search service of a first domain, and (ii) a second search system that provides a search service for a second domain, the second domain being different from the first domain; for each particular candidate transcription of the candidate transcriptions: receiving, by the one or more computers, data from the first search system that provides the search service for the first domain, the data from the first search system indicating first search results that the search service for the first domain identifies as relevant to the particular candidate transcription; determining, by the one or more computers, a first score based on the first search results that the search service for the first domain identifies as relevant to the particular candidate transcription; receiving, by the one or more computers, data from the second search system that provides the search service for the second domain, the data from the second search system indicating second search results that the search service for the second domain identifies as relevant to the particular candidate transcription; determining, by the one or more computers, a second score based on the second search results that the search service for the second domain identifies as relevant to the particular candidate transcription; providing, by the one or more computers, (i) the first score that is determined based on the first search results and (ii) the second score that is determined based on the second search results as input to a classifier, wherein the classifier has been trained, using scores that represent characteristics of different search results from different domains, to indicate a likelihood that a transcription is correct based on scores for multiple different domains; and receiving, by the one or more computers and from the trained classifier, a classifier output in response to at least the first score and the second score, the classifier output indicating a likelihood that the particular candidate transcription is correct; selecting, by the one or more computers, a transcription for the utterance, from among the multiple candidate transcriptions, based on the classifier outputs; and providing, by the one or more computers, the transcription as output of the automated speech recognizer. | 1. A method of performing speech recognition that is performed by one or more computers of an automated speech recognizer, the method comprising: receiving, by the one or more computers, data that indicates multiple candidate transcriptions for an utterance, wherein the one or more computers are in communication with (i) a first search system that provides a search service of a first domain, and (ii) a second search system that provides a search service for a second domain, the second domain being different from the first domain; for each particular candidate transcription of the candidate transcriptions: receiving, by the one or more computers, data from the first search system that provides the search service for the first domain, the data from the first search system indicating first search results that the search service for the first domain identifies as relevant to the particular candidate transcription; determining, by the one or more computers, a first score based on the first search results that the search service for the first domain identifies as relevant to the particular candidate transcription; receiving, by the one or more computers, data from the second search system that provides the search service for the second domain, the data from the second search system indicating second search results that the search service for the second domain identifies as relevant to the particular candidate transcription; determining, by the one or more computers, a second score based on the second search results that the search service for the second domain identifies as relevant to the particular candidate transcription; providing, by the one or more computers, (i) the first score that is determined based on the first search results and (ii) the second score that is determined based on the second search results as input to a classifier, wherein the classifier has been trained, using scores that represent characteristics of different search results from different domains, to indicate a likelihood that a transcription is correct based on scores for multiple different domains; and receiving, by the one or more computers and from the trained classifier, a classifier output in response to at least the first score and the second score, the classifier output indicating a likelihood that the particular candidate transcription is correct; selecting, by the one or more computers, a transcription for the utterance, from among the multiple candidate transcriptions, based on the classifier outputs; and providing, by the one or more computers, the transcription as output of the automated speech recognizer. 14. The method of claim 1 , wherein receiving, by the one or more computers, the data indicating the first search results that the search service for the first domain identifies as relevant to the particular candidate transcription comprises: receiving, by the one or more computers, data indicating first search results that the search service for the first domain identifies in a first data collection, wherein the first data collection is selected from a group consisting of (i) data associated with web documents, (ii) data associated with a set of media items, (iii) data associated with a set of applications, and (iv) data associated with a set of voice commands; and wherein receiving, by the one or more computers, the data indicating the second search results that the search service for the second domain identifies as relevant to the particular candidate transcription comprises: receiving, by the one or more computers, data indicating search results that the search service for the second domain identifies in a second data collection, wherein the second data collection is different from the first data collection and is selected from the group consisting of (i) data associated with web documents, (ii) data associated with a set of media items, (iii) data associated with a set of applications, and (iv) data associated with a set of voice commands. | 0.644456 |
9,953,085 | 8 | 9 | 8. The system of claim 7 , wherein the one or more processors and the memory are configured to: receive a data file from a computing device of a first third-party content provider comprising one or more content items including the first content item, each of the one or more content items comprising identification data, a respective content item type, and a respective online action, each of the one or more content items associated with a product or service of the first third-party content provider; identify the first search entity based on identification data and a content item type for the first content item in the data file, the first search entity corresponding to a named physical entity; generate, based on the data file, the first entity-action pair comprising the first search entity and the first online action, the first online action associated with the first content item in the data file; and associate the first entity-action pair with the first bidding parameter specific to the first entity-action pair. | 8. The system of claim 7 , wherein the one or more processors and the memory are configured to: receive a data file from a computing device of a first third-party content provider comprising one or more content items including the first content item, each of the one or more content items comprising identification data, a respective content item type, and a respective online action, each of the one or more content items associated with a product or service of the first third-party content provider; identify the first search entity based on identification data and a content item type for the first content item in the data file, the first search entity corresponding to a named physical entity; generate, based on the data file, the first entity-action pair comprising the first search entity and the first online action, the first online action associated with the first content item in the data file; and associate the first entity-action pair with the first bidding parameter specific to the first entity-action pair. 9. The system of claim 8 , wherein the one or more processors and the memory are configured to generate an error log comprising a content item of the one or more content items for which no search entities are identified. | 0.968883 |
7,647,415 | 11 | 19 | 11. A system, comprising: a processor; and a memory comprising program instructions, wherein the program instructions are executable by the processor to implement a Web services stack configured to: communicate with another Web services stack on another system according to a markup language protocol, wherein the markup language protocol is based on XML (eXtensible Markup Language); and dynamically switch to communicate with the other Web services stack according to the binary encoding protocol, wherein communication according to the binary encoding protocol comprises mapping from an XML schema to a binary encoding schema and generating a binary encoding from the binary encoding schema; wherein the Web services stack supports the markup language protocol and the binary encoding protocol with a single API (application programming interface). | 11. A system, comprising: a processor; and a memory comprising program instructions, wherein the program instructions are executable by the processor to implement a Web services stack configured to: communicate with another Web services stack on another system according to a markup language protocol, wherein the markup language protocol is based on XML (eXtensible Markup Language); and dynamically switch to communicate with the other Web services stack according to the binary encoding protocol, wherein communication according to the binary encoding protocol comprises mapping from an XML schema to a binary encoding schema and generating a binary encoding from the binary encoding schema; wherein the Web services stack supports the markup language protocol and the binary encoding protocol with a single API (application programming interface). 19. The system as recited in claim 11 , wherein, to communicate with the other Web services stack according to the binary encoding protocol, the Web services stack is further configured to serialize the markup language protocol to generate binary encoding protocol messages according to a self-describing binary format that preserves the markup language protocol information set. | 0.722141 |
9,633,010 | 1 | 6 | 1. A method implemented in a computer infrastructure, comprising: obtaining field oriented electronic document data from an input document, wherein the document data is in a non-natural language form; determining, using a translation engine, from one of a plurality of data types, a data type of the document data via communication with a detection and conversion database; selecting, based on the determined data type, appropriate conversion information records from plural different translation data stored in the detection and conversion database and corresponding to plural different data types; translating, using the translation engine and the appropriate conversion information records, based on the determined data type, the document data to a natural language form; and outputting, in natural language form, the translated document data to an output data stream, wherein the plurality of data types comprises: document header data; document field data; table header data; table detail data; and signature data. | 1. A method implemented in a computer infrastructure, comprising: obtaining field oriented electronic document data from an input document, wherein the document data is in a non-natural language form; determining, using a translation engine, from one of a plurality of data types, a data type of the document data via communication with a detection and conversion database; selecting, based on the determined data type, appropriate conversion information records from plural different translation data stored in the detection and conversion database and corresponding to plural different data types; translating, using the translation engine and the appropriate conversion information records, based on the determined data type, the document data to a natural language form; and outputting, in natural language form, the translated document data to an output data stream, wherein the plurality of data types comprises: document header data; document field data; table header data; table detail data; and signature data. 6. The method of claim 1 , further comprising providing the output data stream to a question-answering system. | 0.896617 |
9,720,984 | 9 | 12 | 9. A method, comprising: receiving, by a processor, a visualization request relating to information stored in an ontology; parsing, by the processor, the visualization request to generate a search query; submitting, by the processor, the search query to the ontology, wherein the ontology is dynamically created to store retrieved data that is collected from a data source; perform data mitigation to process the retrieved data to detect and resolve conflicts among classified tokens provided by data agent, wherein the data mitigation uses quality score, trust score, and rate of decay for the data source; receiving, by the processor, in response to the query, a result comprising a plurality of instances associated with the classified tokens and a plurality of relationships between the instances; and generating, by the processor, a visual representation of the result using visualization rules stored in a memory, the visualization rules comprising level of detail rules, reduction rules, and rewriting rules, wherein generating the visual representation of the result using the visualization rules comprises: identifying a relationship between a first instance and a second instance from the plurality of instances within the results; removing the relationship between the first instance and the second instance from the results; and removing the first instance from the results when the first instance has no relationships with any other instances from the plurality of instances. | 9. A method, comprising: receiving, by a processor, a visualization request relating to information stored in an ontology; parsing, by the processor, the visualization request to generate a search query; submitting, by the processor, the search query to the ontology, wherein the ontology is dynamically created to store retrieved data that is collected from a data source; perform data mitigation to process the retrieved data to detect and resolve conflicts among classified tokens provided by data agent, wherein the data mitigation uses quality score, trust score, and rate of decay for the data source; receiving, by the processor, in response to the query, a result comprising a plurality of instances associated with the classified tokens and a plurality of relationships between the instances; and generating, by the processor, a visual representation of the result using visualization rules stored in a memory, the visualization rules comprising level of detail rules, reduction rules, and rewriting rules, wherein generating the visual representation of the result using the visualization rules comprises: identifying a relationship between a first instance and a second instance from the plurality of instances within the results; removing the relationship between the first instance and the second instance from the results; and removing the first instance from the results when the first instance has no relationships with any other instances from the plurality of instances. 12. The method of claim 9 , wherein generating the visual representation of the result using the visualization rules comprises selecting a third instance and a fourth instance from the plurality of instances to be combined into a consolidated instance based on the visualization rules. | 0.53125 |
9,245,523 | 7 | 9 | 7. The method according to claim 1 wherein associating a topic from the topic model with the search term is performed by detecting keywords on the lists of keywords that are similar to the search term. | 7. The method according to claim 1 wherein associating a topic from the topic model with the search term is performed by detecting keywords on the lists of keywords that are similar to the search term. 9. The method according to claim 7 wherein more than one keyword is detected along with a weight of the detected keywords within each topic and wherein the search term is associated with the topic that comprises the detected keyword with the highest weight. | 0.843484 |
9,761,222 | 3 | 4 | 3. The system as recited in claim 1 , wherein the expert agent communicates with one or more participants in the conversation. | 3. The system as recited in claim 1 , wherein the expert agent communicates with one or more participants in the conversation. 4. The system as recited in claim 3 , wherein the expert agent communicates with a participant in the conversation without one or more other participants being aware of the communication. | 0.96006 |
9,710,447 | 5 | 7 | 5. The method of claim 1 , further comprising: training, by at least one computing device, the content kernel using at least the content feature information associated with each content item of the plurality of content items in the training set; training, by at least one computing device, the semantic kernel using at least the semantic feature information associated with each content item of the plurality of content items in the training set; and training, by at least one computing device, the social kernel using at least the social network feature information associated with each content item of the plurality of content items in the training set. | 5. The method of claim 1 , further comprising: training, by at least one computing device, the content kernel using at least the content feature information associated with each content item of the plurality of content items in the training set; training, by at least one computing device, the semantic kernel using at least the semantic feature information associated with each content item of the plurality of content items in the training set; and training, by at least one computing device, the social kernel using at least the social network feature information associated with each content item of the plurality of content items in the training set. 7. The method of claim 5 , the social network kernel comprising a network of nodes and edges, each node corresponding to an individual represented in at least one content item of the plurality and each edge indicating a relationship between two individuals represented together in at least one content item of the plurality of content items. | 0.882333 |
7,873,670 | 1 | 4 | 1. An example management system, comprising: at least one computer; an indexing engine executable by the at least one computer to index content of source business oriented metadata, the source business oriented metadata including an authored topic hierarchy, the indexing engine having a content scanner that reads the source business oriented metadata included in source metadata documents containing terms to be indexed, and builds a content index of the source business oriented metadata, wherein the content scanner builds, as the content index, one or more knowledge base documents, wherein, for each term in the source metadata documents, the content scanner stores, in the one or more knowledge base documents, a knowledge base representation of the term along with one or more references to content of the source business oriented metadata that uses the term, and wherein the one or more knowledge base documents include a representation of a structure of the authored topic hierarchy; an index store that stores the content index of the source business oriented metadata; and an example engine executable by the at least one computer to use the representation of the structure of the authored topic hierarchy to determine logical associations among the terms in the source metadata documents, store the logical associations in the one or more knowledge base documents, and manage logical associations of terms in a query using the one or more knowledge base documents of the content index, wherein the example engine determines an example association between two terms when a term is an example of another term, and wherein the example engine combines terms into phrases and determines, based on example associations between terms in the phrases, an example association between two phrases when a phrase is an example of another phrase. | 1. An example management system, comprising: at least one computer; an indexing engine executable by the at least one computer to index content of source business oriented metadata, the source business oriented metadata including an authored topic hierarchy, the indexing engine having a content scanner that reads the source business oriented metadata included in source metadata documents containing terms to be indexed, and builds a content index of the source business oriented metadata, wherein the content scanner builds, as the content index, one or more knowledge base documents, wherein, for each term in the source metadata documents, the content scanner stores, in the one or more knowledge base documents, a knowledge base representation of the term along with one or more references to content of the source business oriented metadata that uses the term, and wherein the one or more knowledge base documents include a representation of a structure of the authored topic hierarchy; an index store that stores the content index of the source business oriented metadata; and an example engine executable by the at least one computer to use the representation of the structure of the authored topic hierarchy to determine logical associations among the terms in the source metadata documents, store the logical associations in the one or more knowledge base documents, and manage logical associations of terms in a query using the one or more knowledge base documents of the content index, wherein the example engine determines an example association between two terms when a term is an example of another term, and wherein the example engine combines terms into phrases and determines, based on example associations between terms in the phrases, an example association between two phrases when a phrase is an example of another phrase. 4. The example management system as claimed in claim 1 , wherein the example engine interacts with a word stemming component that stems one or more terms in the query to manage logical associations of the terms based on the stemmed terms. | 0.570397 |
8,875,016 | 1 | 2 | 1. An image analysis and conversion method comprising: receiving a digital ink image having defined perceptually salient structures by an electronic device configured to perform the receiving; converting the digital ink image into multiple structured object representations of the digital ink image by the electronic device the multiple structured object representations correlating to ones of the defined perceptually salient structures of the digital ink image; and altering at least one of the structured object representations into multiple simultaneously existing structured alternative interpretations of the at least one structured object representations of the digital ink image by the electronic device, each of the alternative interpretations being viewable by a user and being plausible intended outputs of the user. | 1. An image analysis and conversion method comprising: receiving a digital ink image having defined perceptually salient structures by an electronic device configured to perform the receiving; converting the digital ink image into multiple structured object representations of the digital ink image by the electronic device the multiple structured object representations correlating to ones of the defined perceptually salient structures of the digital ink image; and altering at least one of the structured object representations into multiple simultaneously existing structured alternative interpretations of the at least one structured object representations of the digital ink image by the electronic device, each of the alternative interpretations being viewable by a user and being plausible intended outputs of the user. 2. The method according to claim 1 , wherein each of the multiple structured object representations is editable by a structured text/graphics editor. | 0.959156 |
8,447,603 | 16 | 21 | 16. A tangible computer program product for evaluating naturalness of speech utterances by using crowd wisdom models, the tangible computer program product comprising: a non-transitory computer readable storage medium having computer readable program embodied therewith, the computer readable program comprising: computer readable program configured to present a plurality of human-testers with some of the obtained speech utterances; computer readable program configured to receive, for each presented speech utterance, a plurality of corresponding human testers generated speech utterances being human repetitions of the presented speech utterance; computer readable program configured to generate, for each presented speech utterance, an utterance-specific scoring model that is based on the corresponding human-tester generated speech utterances, each scoring model being configured to estimate a level of speech naturalness for the presented speech utterances using at least crowd wisdom models; computer readable program configured to update the scoring model for each presented speech utterance, based on respective human-tester generated speech utterances; and computer readable program configured to derive a speech naturalness score for each presented speech utterance by respectively applying the updated utterance-specific scoring model to each presented speech utterance. | 16. A tangible computer program product for evaluating naturalness of speech utterances by using crowd wisdom models, the tangible computer program product comprising: a non-transitory computer readable storage medium having computer readable program embodied therewith, the computer readable program comprising: computer readable program configured to present a plurality of human-testers with some of the obtained speech utterances; computer readable program configured to receive, for each presented speech utterance, a plurality of corresponding human testers generated speech utterances being human repetitions of the presented speech utterance; computer readable program configured to generate, for each presented speech utterance, an utterance-specific scoring model that is based on the corresponding human-tester generated speech utterances, each scoring model being configured to estimate a level of speech naturalness for the presented speech utterances using at least crowd wisdom models; computer readable program configured to update the scoring model for each presented speech utterance, based on respective human-tester generated speech utterances; and computer readable program configured to derive a speech naturalness score for each presented speech utterance by respectively applying the updated utterance-specific scoring model to each presented speech utterance. 21. The tangible computer program product according to claim 16 , further comprising computer readable program configured to present the each obtained speech utterance by at least one of: playing the presented utterance, exhibiting a text that has a respective content of the presented speech utterance, and a simultaneous combination of the playing and the exhibiting. | 0.789384 |
9,824,304 | 16 | 17 | 16. In a digital medium environment to determine which fonts are similar to rendered text in an image, a system comprising one or more computing devices including a processing system and memory having instructions stored thereon that are executable by the processing system to perform operations comprising: selecting training images using font metadata associated with respective said fonts used to render text included in respective said training images, the selected training images including: an anchor image having text using a font type; a positive image having: text that is different than the text of the anchor image; or text having one or more applied perturbations; and a negative image having text that is not in the font type; controlling training of the model using machine learning using the anchor image, the positive image, and the negative image; determining similarity of a font used for the rendered text in the image to respective ones of a plurality of fonts using the model; and outputting one or more fonts that are similar to the rendered text in the image in a user interface based on the determining. | 16. In a digital medium environment to determine which fonts are similar to rendered text in an image, a system comprising one or more computing devices including a processing system and memory having instructions stored thereon that are executable by the processing system to perform operations comprising: selecting training images using font metadata associated with respective said fonts used to render text included in respective said training images, the selected training images including: an anchor image having text using a font type; a positive image having: text that is different than the text of the anchor image; or text having one or more applied perturbations; and a negative image having text that is not in the font type; controlling training of the model using machine learning using the anchor image, the positive image, and the negative image; determining similarity of a font used for the rendered text in the image to respective ones of a plurality of fonts using the model; and outputting one or more fonts that are similar to the rendered text in the image in a user interface based on the determining. 17. The system as described in claim 16 , wherein the selecting is performed based on a Hamming distance computed between metadata vectors that describe respective said font metadata. | 0.574419 |
8,886,519 | 3 | 4 | 3. The text processing apparatus according to claim 2 , wherein the descriptive content determination unit derives, based on the result of the determination by the segment determination unit, an extent to which the content of the homogeneous segment is included in the second text corresponding to the other first text which includes the homogeneous segment, further derives, based on the derived extent, a degree to which each segment constituting the first text which is set as the analysis target should be described in the second text corresponding to the first text which is set as the analysis target, and performs the determination using the degree. | 3. The text processing apparatus according to claim 2 , wherein the descriptive content determination unit derives, based on the result of the determination by the segment determination unit, an extent to which the content of the homogeneous segment is included in the second text corresponding to the other first text which includes the homogeneous segment, further derives, based on the derived extent, a degree to which each segment constituting the first text which is set as the analysis target should be described in the second text corresponding to the first text which is set as the analysis target, and performs the determination using the degree. 4. The text processing apparatus according to claim 3 , wherein the inclusion determination unit, in addition to the determination regarding the content of the homogeneous segment, computes, for each of the plurality of segments constituting the first text which is set as the analysis target and for the homogeneous segment, an inclusion score representing a possibility of a content of the segment being included in the second text corresponding to the first text which includes the segment, and the descriptive content determination unit further derives the degree using the inclusion score computed by the inclusion determination unit, such that the degree increase the higher the inclusion score. | 0.742658 |
7,831,584 | 1 | 9 | 1. A method for providing search result suggestions, comprising: providing an index to a product/service database; detecting an entered partial search query from a user; lexographically matching said partial search query to said index; identifying a matching subset of said index; ranking products/services in said subset according to a ranking database which includes (a) said user's history, (b) most popular sales data, (c) most often viewed products, and (d) lexographical weights to produce a highest ranked list of search results; and displaying said highest ranked list of search results. | 1. A method for providing search result suggestions, comprising: providing an index to a product/service database; detecting an entered partial search query from a user; lexographically matching said partial search query to said index; identifying a matching subset of said index; ranking products/services in said subset according to a ranking database which includes (a) said user's history, (b) most popular sales data, (c) most often viewed products, and (d) lexographical weights to produce a highest ranked list of search results; and displaying said highest ranked list of search results. 9. The method of claim 1 wherein the ranking database further includes (e) histories of similar users to said user, and (f) most often viewed product data by the similar users. | 0.879121 |
9,770,660 | 20 | 23 | 20. The system of claim 19 , wherein the scene recognition technology comprises image recognition. | 20. The system of claim 19 , wherein the scene recognition technology comprises image recognition. 23. The system of claim 20 , wherein the image recognition comprises recognition of the actual present location relative to the physical sports event. | 0.968802 |
9,973,464 | 14 | 19 | 14. A system comprising: a processor; and a memory storing an application program, which, when executed on the processor, performs an operation of addressing propagation of inaccurate information in a social networking environment, the operation comprising: identifying, via a communications network, inaccurate information within the social networking environment; facilitating creation of countering content to address the inaccurate information, wherein the countering content is determined by identifying behavior of one or more users among a plurality of users within the social networking environment, wherein identifying the behavior of the one or more users comprises establishing a pattern of monitoring respective actions of the one or more users and detecting at least one correlation between the respective actions of the one or more users and environmental stimuli, and wherein the at least one correlation includes a first user performing an action based upon an action of a second user; and disseminating the countering content by incorporating the countering content into at least one post within the social networking environment presented in response to one or more posts including the inaccurate information. | 14. A system comprising: a processor; and a memory storing an application program, which, when executed on the processor, performs an operation of addressing propagation of inaccurate information in a social networking environment, the operation comprising: identifying, via a communications network, inaccurate information within the social networking environment; facilitating creation of countering content to address the inaccurate information, wherein the countering content is determined by identifying behavior of one or more users among a plurality of users within the social networking environment, wherein identifying the behavior of the one or more users comprises establishing a pattern of monitoring respective actions of the one or more users and detecting at least one correlation between the respective actions of the one or more users and environmental stimuli, and wherein the at least one correlation includes a first user performing an action based upon an action of a second user; and disseminating the countering content by incorporating the countering content into at least one post within the social networking environment presented in response to one or more posts including the inaccurate information. 19. The system of claim 14 , wherein the countering content is further determined based upon branding within one or more images associated with the inaccurate information. | 0.858678 |
8,706,704 | 1 | 4 | 1. A computer system for creating a hyperlink together with an associated semantic link between selected text in a first, source document and related text in a second, target document, said source document including descriptive text, the computer system comprising: a computer processor; and a memory coupled to the computer processor having instructions stored therein which, when executed by the computer processor, causes the computer processor to perform the operations comprising: selecting text within the source document; selecting said target document; creating a hyperlink to navigate over the Internet from said selected text in the source document to said target document, wherein said hyperlink includes a URI identifying the target document; selecting a type of semantic link; and creating a semantic link of said type between said selected text in the source document and said target document to identify a specified semantic relationship between said selected text and said target-document, and including in said hyperlink a reference, different from said URI, for identifying said semantic relationship to facilitate using the hyperlink to identify and navigate to documents semantically related to said selected text; and wherein: the selecting said target document includes refining the selected text from the source document to form refined selected text, and putting the refined selected text into the target document; the hyperlink points from the selected text in the source document to the refined selected text in the target document; the source document has a source type and the target document has a target type; and the selecting the type of semantic link includes analyzing said source type and said target type, determining a plurality of candidate types of semantic links based on said analyzing said source type and said target type, and prompting a user to select from among the plurality of candidate types of semantic links, including selecting a word from the selected text, identifying a category for the word, consulting a metamodel to determine a type of relationship between the identified category and the selected text, and using the type of relationship determined from consulting the metamodel as the type of the semantic link between the selected text in the source document and the target document. | 1. A computer system for creating a hyperlink together with an associated semantic link between selected text in a first, source document and related text in a second, target document, said source document including descriptive text, the computer system comprising: a computer processor; and a memory coupled to the computer processor having instructions stored therein which, when executed by the computer processor, causes the computer processor to perform the operations comprising: selecting text within the source document; selecting said target document; creating a hyperlink to navigate over the Internet from said selected text in the source document to said target document, wherein said hyperlink includes a URI identifying the target document; selecting a type of semantic link; and creating a semantic link of said type between said selected text in the source document and said target document to identify a specified semantic relationship between said selected text and said target-document, and including in said hyperlink a reference, different from said URI, for identifying said semantic relationship to facilitate using the hyperlink to identify and navigate to documents semantically related to said selected text; and wherein: the selecting said target document includes refining the selected text from the source document to form refined selected text, and putting the refined selected text into the target document; the hyperlink points from the selected text in the source document to the refined selected text in the target document; the source document has a source type and the target document has a target type; and the selecting the type of semantic link includes analyzing said source type and said target type, determining a plurality of candidate types of semantic links based on said analyzing said source type and said target type, and prompting a user to select from among the plurality of candidate types of semantic links, including selecting a word from the selected text, identifying a category for the word, consulting a metamodel to determine a type of relationship between the identified category and the selected text, and using the type of relationship determined from consulting the metamodel as the type of the semantic link between the selected text in the source document and the target document. 4. The system according to claim 1 , wherein said reference to said semantic link describes a specific type of relationship in a given direction. | 0.835227 |
9,053,497 | 6 | 7 | 6. The method of claim 5 , further comprising generating an advertising strategy for each of the member groups based on the connectedness of a member group and the predicted interest level using the advertising targeting server system. | 6. The method of claim 5 , further comprising generating an advertising strategy for each of the member groups based on the connectedness of a member group and the predicted interest level using the advertising targeting server system. 7. The method of claim 6 , further comprising generating an advertising campaign budget based on the connectedness of a member group and the predicted interest level using the advertising targeting server system. | 0.965155 |
8,117,023 | 11 | 13 | 11. The language understanding apparatus according to claim 10 , wherein the semantic tree generator generates a semantic tree by arranging an enumeration of concept representations for which individual variables of a semantic frame is to be bidden at a lower node of a concept representation corresponding to the semantic frame, and, when the semantic frame corresponds to an arranged concept representation, repeating arranging the concept representations for which individual variables of the semantic frame of the arranged concept representation is to be bidden at a lower node of the arranged concept representation. | 11. The language understanding apparatus according to claim 10 , wherein the semantic tree generator generates a semantic tree by arranging an enumeration of concept representations for which individual variables of a semantic frame is to be bidden at a lower node of a concept representation corresponding to the semantic frame, and, when the semantic frame corresponds to an arranged concept representation, repeating arranging the concept representations for which individual variables of the semantic frame of the arranged concept representation is to be bidden at a lower node of the arranged concept representation. 13. The language understanding apparatus according to claim 11 , wherein when detecting a repetitive pattern comprised of a plurality of variables in a same semantic frame, the semantic tree generator groups the repetitive patter and generates the semantic tree for each group. | 0.938197 |
4,829,572 | 1 | 6 | 1. A method for recognizing speech containing a plurality of significant phonemes, said method comprising the steps of: constructing a profile of a characteristic of each significant phoneme; generating a difference profile for substantially each pair of significant phonemes by subtracting the profile of each significant phoneme from the profile of each other significant phoneme; identifying adjacent sections of each difference profile which exceed positive and negative thresholds respectively; computing the likelihood that an unknown phoneme will be one or the other of a phoneme pair based on the relative areas in the identified sections of the difference profile; constructing an equivalent profile of a phoneme of an unknown utterance; and choosing the more likely phoneme of each phoneme pair based onthe relative areas in the identified sections of the profile of the unknown phoneme. | 1. A method for recognizing speech containing a plurality of significant phonemes, said method comprising the steps of: constructing a profile of a characteristic of each significant phoneme; generating a difference profile for substantially each pair of significant phonemes by subtracting the profile of each significant phoneme from the profile of each other significant phoneme; identifying adjacent sections of each difference profile which exceed positive and negative thresholds respectively; computing the likelihood that an unknown phoneme will be one or the other of a phoneme pair based on the relative areas in the identified sections of the difference profile; constructing an equivalent profile of a phoneme of an unknown utterance; and choosing the more likely phoneme of each phoneme pair based onthe relative areas in the identified sections of the profile of the unknown phoneme. 6. The method of claim 1 wherein the profile constructing step comprises constructing a plurality of profiles based on different characteristics of each significant phoneme, and wherein the difference profile generating step includes generating a difference profile for each characteristic for substantially each pair of significant phonemes. | 0.865672 |
8,818,977 | 1 | 7 | 1. A computer-implemented method, comprising: determining, for a current user session and by one or more computers, a user context that is indicative of a category of user interest for the user session, the determination being based on content provided to a particular user during the current user session, wherein determining the user context comprises: determining that the content provided to the particular user during the current user session includes a hub page, the hub page being a page that has been identified as part of both a first context and a second context, the first context being different from the second context, and each of the first context and the second context being identified based at least in part on characteristics of the hub page; identifying previous user sessions that include requests for the hub page; obtaining a first metric for the first context, the first metric being calculated based on a frequency with which the previous user sessions that included requests for the hub page were determined to be part of the first context; obtaining a second metric for the second context, the second metric being calculated based on a frequency with which the previous user sessions that included requests for the hub page were determined to be part of the second context; and determining that the user context is one of the first context or second context based on the first metric and the second metric; and receiving, during the user session and after determining the user context, a user search query from the particular user; and providing, by one or more computers and in response to receiving the user search query, ranked search results for the user search query, the ranking being based at least in part on a first contextual click model for the user context. | 1. A computer-implemented method, comprising: determining, for a current user session and by one or more computers, a user context that is indicative of a category of user interest for the user session, the determination being based on content provided to a particular user during the current user session, wherein determining the user context comprises: determining that the content provided to the particular user during the current user session includes a hub page, the hub page being a page that has been identified as part of both a first context and a second context, the first context being different from the second context, and each of the first context and the second context being identified based at least in part on characteristics of the hub page; identifying previous user sessions that include requests for the hub page; obtaining a first metric for the first context, the first metric being calculated based on a frequency with which the previous user sessions that included requests for the hub page were determined to be part of the first context; obtaining a second metric for the second context, the second metric being calculated based on a frequency with which the previous user sessions that included requests for the hub page were determined to be part of the second context; and determining that the user context is one of the first context or second context based on the first metric and the second metric; and receiving, during the user session and after determining the user context, a user search query from the particular user; and providing, by one or more computers and in response to receiving the user search query, ranked search results for the user search query, the ranking being based at least in part on a first contextual click model for the user context. 7. The computer-implemented method of claim 1 , wherein the user context comprises one or more of a news context, a shopping context, a travel context or an educational context, wherein the news context is determined when it is identified that the user is navigating sites related to news content, the shopping context is determined when it is identified that the user is navigating sites related to shopping content, the travel context is determined when it is identified that the user is navigating travel content and the educational context is determined when it is identified that the user is navigating educational content; and wherein the first contextual click model associated with the user context is operable to increase the ranking of content related to the user context. | 0.581818 |
8,296,743 | 1 | 6 | 1. A computer-implemented method comprising: bundling two or more hardware-specific variants of a run-time function into a generic function that corresponds to a parallel programming keyword of a parallel programming language; generating one or more meta-wrappers for the generic function based on an annotation supplied for each of the two or more hardware-specific variants of the run-time function; compiling source code of a user program that comprises (i) statements from a high-level programming language and (ii) the parallel programming keyword of the parallel programming language to generate a compiled binary of the user program, the compiled binary comprises (i) compiled code that corresponds to the statements from the high-level programming language and (ii) a run-time function call to the generic function embedded in the compiled binary as a function of the one or more meta wrappers; during runtime execution of the compiled binary, (i) executing the run-time function call to the generic function and (ii) dynamically selecting a hardware-specific variant of the run-time function for a selected sub-task associated with the parallel programming keyword; and dispatching the selected hardware-specific variant for execution on a hardware processing element associated with the selected hardware-specific variant. | 1. A computer-implemented method comprising: bundling two or more hardware-specific variants of a run-time function into a generic function that corresponds to a parallel programming keyword of a parallel programming language; generating one or more meta-wrappers for the generic function based on an annotation supplied for each of the two or more hardware-specific variants of the run-time function; compiling source code of a user program that comprises (i) statements from a high-level programming language and (ii) the parallel programming keyword of the parallel programming language to generate a compiled binary of the user program, the compiled binary comprises (i) compiled code that corresponds to the statements from the high-level programming language and (ii) a run-time function call to the generic function embedded in the compiled binary as a function of the one or more meta wrappers; during runtime execution of the compiled binary, (i) executing the run-time function call to the generic function and (ii) dynamically selecting a hardware-specific variant of the run-time function for a selected sub-task associated with the parallel programming keyword; and dispatching the selected hardware-specific variant for execution on a hardware processing element associated with the selected hardware-specific variant. 6. The method of claim 1 , wherein: said dynamically selecting a hardware-specific variant further comprises dynamically selecting the processing element to perform the selected sub-task. | 0.847967 |
7,697,760 | 6 | 7 | 6. The method of claim 1 , wherein the step of determining which word from the first list or at least one second list should be selected as a best text word transcription of the handwritten word comprises the steps of providing a feature of the first and additional lists; and using the feature to select a best text word from the first and at least one additional lists. | 6. The method of claim 1 , wherein the step of determining which word from the first list or at least one second list should be selected as a best text word transcription of the handwritten word comprises the steps of providing a feature of the first and additional lists; and using the feature to select a best text word from the first and at least one additional lists. 7. The method of claim 6 , wherein the step of using the feature to select a best text word from the first and at least one additional lists further comprising the step of selecting the best text word according to at least one combination rule, the at least one combination rule using each of the at least one features. | 0.690291 |
9,681,016 | 23 | 26 | 23. A machine-implemented method for capturing one or more hand-written annotations on a physical document, comprising: receiving a physical document by a device, the physical document includes one or more hand-written annotations corresponding to at least a portion of the physical document; identifying the hand-written annotations from the physical document, wherein identifying includes separating background of the physical document from the hand-written annotations; extracting the identified hand-written annotations, first position information of the hand-written annotations, and second position information of the at least portion of the physical document; associating the hand-written annotations to the at least portion of the physical document; upon cropping a camera view of the physical document, obtaining a third position information of the at least portion of the physical document; determining a relative position of the hand-written annotations based on a relative position of the at least portion of the physical document in the camera view, wherein the relative position of the at least portion of the physical document is based on the third position information being relative to the second position information of the at least portion of the physical document, and wherein the relative position of the hand-written annotations is based on a fourth position information of the hand-written annotations relative to the first position information of the hand-written annotations; determining that a quantity of the hand-written annotations corresponding to the portion of the physical document exceeds a pre-defined quantity; displaying, within the camera view, a marker indicating a presence of the hand-written annotations; and storing the hand-written annotations along with the marker and the position information. | 23. A machine-implemented method for capturing one or more hand-written annotations on a physical document, comprising: receiving a physical document by a device, the physical document includes one or more hand-written annotations corresponding to at least a portion of the physical document; identifying the hand-written annotations from the physical document, wherein identifying includes separating background of the physical document from the hand-written annotations; extracting the identified hand-written annotations, first position information of the hand-written annotations, and second position information of the at least portion of the physical document; associating the hand-written annotations to the at least portion of the physical document; upon cropping a camera view of the physical document, obtaining a third position information of the at least portion of the physical document; determining a relative position of the hand-written annotations based on a relative position of the at least portion of the physical document in the camera view, wherein the relative position of the at least portion of the physical document is based on the third position information being relative to the second position information of the at least portion of the physical document, and wherein the relative position of the hand-written annotations is based on a fourth position information of the hand-written annotations relative to the first position information of the hand-written annotations; determining that a quantity of the hand-written annotations corresponding to the portion of the physical document exceeds a pre-defined quantity; displaying, within the camera view, a marker indicating a presence of the hand-written annotations; and storing the hand-written annotations along with the marker and the position information. 26. The machine-implemented method of claim 23 , further comprising scanning the physical document. | 0.888764 |
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