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9,535,909 | 19 | 22 | 19. A distributed computing collaboration system for facilitating event-based automation in a collaborative cloud-based platform, the system comprising: one or more processors associated with a front-end system and a back-end system, wherein the front-end system communicates with client systems via a first network for receiving events via the first network, wherein the back-end system communicates with the front-end system via a second network, the back-end system including one or more jobs manager systems and a rule manager system, wherein the back-end system supplements the one or more jobs manager systems with additional jobs manager systems in response to detecting an increase in the number of events received at the front end system; an interface receiving an event responsive to an action taken by a collaborator of the collaborative cloud-based platform on a content item stored in the back-end system of the collaborative cloud-based platform, wherein the content item comprises electronic content that is remotely accessible to the collaborator via a user device in communication with the collaborative cloud-based platform; and a memory unit having instructions stored thereon which, when executed by the one or more processors, cause the collaboration system to translate the event into one or more job requests by: parsing, by the back-end system, the event to identify event criteria; accessing, by the back-end system, pre-defined rules from a memory in communication with the one or more processors; scanning, by the back-end system, the pre-defined rules to select a first pre-defined rule that matches the event criteria; and generating a job request associated with the first pre-defined rule. | 19. A distributed computing collaboration system for facilitating event-based automation in a collaborative cloud-based platform, the system comprising: one or more processors associated with a front-end system and a back-end system, wherein the front-end system communicates with client systems via a first network for receiving events via the first network, wherein the back-end system communicates with the front-end system via a second network, the back-end system including one or more jobs manager systems and a rule manager system, wherein the back-end system supplements the one or more jobs manager systems with additional jobs manager systems in response to detecting an increase in the number of events received at the front end system; an interface receiving an event responsive to an action taken by a collaborator of the collaborative cloud-based platform on a content item stored in the back-end system of the collaborative cloud-based platform, wherein the content item comprises electronic content that is remotely accessible to the collaborator via a user device in communication with the collaborative cloud-based platform; and a memory unit having instructions stored thereon which, when executed by the one or more processors, cause the collaboration system to translate the event into one or more job requests by: parsing, by the back-end system, the event to identify event criteria; accessing, by the back-end system, pre-defined rules from a memory in communication with the one or more processors; scanning, by the back-end system, the pre-defined rules to select a first pre-defined rule that matches the event criteria; and generating a job request associated with the first pre-defined rule. 22. The collaboration system of claim 19 , wherein the instructions, when executed by the one or more processors, further cause the collaboration system to: batch multiple job requests by a jobs load balancer; and distribute the batched job requests to the additional jobs manager systems. | 0.721042 |
8,538,184 | 1 | 9 | 1. In a document analysis system including a server, a method of enhancing electronic documents to improve automatic recognition and classification of the electronic documents, the method comprising: receiving, by the server, jobs containing job documents from a plurality of users, wherein each received job document is a binarized, one-bit-per-document-pixel image version of an original grayscale or color image source document; filtering, by the server, each page of the received binarized document to infer binarized background artifacts which result from the binarization of the original grayscale or color image source document and reside in the vicinity of binarized text and binarized image features in the page; distinguishing, by the server, the binarized text and binarized image features from the binarized background artifacts; extracting, by the server, the binarized text and binarized image features from the received binarized document; automatically recognizing and classifying, by the server, the received binarized document into a document category by using the extracted binarized text and binarized image features; organizing, by the server, each received job according to the document category of the corresponding job document; and removing, by the server, the binarized background artifacts, wherein the removal of the binarized background artifacts is performed after the binarized document image is inverted to white-on-black. | 1. In a document analysis system including a server, a method of enhancing electronic documents to improve automatic recognition and classification of the electronic documents, the method comprising: receiving, by the server, jobs containing job documents from a plurality of users, wherein each received job document is a binarized, one-bit-per-document-pixel image version of an original grayscale or color image source document; filtering, by the server, each page of the received binarized document to infer binarized background artifacts which result from the binarization of the original grayscale or color image source document and reside in the vicinity of binarized text and binarized image features in the page; distinguishing, by the server, the binarized text and binarized image features from the binarized background artifacts; extracting, by the server, the binarized text and binarized image features from the received binarized document; automatically recognizing and classifying, by the server, the received binarized document into a document category by using the extracted binarized text and binarized image features; organizing, by the server, each received job according to the document category of the corresponding job document; and removing, by the server, the binarized background artifacts, wherein the removal of the binarized background artifacts is performed after the binarized document image is inverted to white-on-black. 9. The method of claim 1 further comprising automatically separating, by the server, each job into constituent electronic documents and automatically separating each electronic document into subsets of electronic pages. | 0.562 |
8,869,072 | 1 | 10 | 1. A method for providing gesture input to a plurality of applications, comprising: receiving data indicative of a user motion or pose, the data being captured by a camera; determining a result of processing the data, the result comprising a three-dimensional model of at least part of the user; sending the result to a first gesture filter of a first application of the plurality of applications, the first application being configured to process the result with the first gesture filter to determine a first output indicative of whether the result is indicative of the user performing a gesture represented by the first gesture filter; and sending the result to a second gesture filter of a second application of the plurality of applications, the second application being configured to process the result with the second gesture filter to determine a second output indicative of whether the result is indicative of the user performing a gesture represented by the second gesture filter. | 1. A method for providing gesture input to a plurality of applications, comprising: receiving data indicative of a user motion or pose, the data being captured by a camera; determining a result of processing the data, the result comprising a three-dimensional model of at least part of the user; sending the result to a first gesture filter of a first application of the plurality of applications, the first application being configured to process the result with the first gesture filter to determine a first output indicative of whether the result is indicative of the user performing a gesture represented by the first gesture filter; and sending the result to a second gesture filter of a second application of the plurality of applications, the second application being configured to process the result with the second gesture filter to determine a second output indicative of whether the result is indicative of the user performing a gesture represented by the second gesture filter. 10. The method of claim 1 , wherein the first gesture filter is a member of a genre package comprising a plurality of gesture filters representing gestures, the genre package comprising a first-person shooter, action, driving, or sports genre package. | 0.870885 |
8,825,639 | 21 | 26 | 21. 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: receiving machine-readable member profile information characterizing a first member and a second member in a member network; receiving a first search query submitted by the first member and a second search query submitted by the second member; responding to each of the first search query and the second search query with a) links to a collection of articles and b) one or more links for receiving input characterizing respectively ratings of the first member and ratings of the second member of articles in the collection; receiving a selection by the first member of a link for receiving input characterizing the first member's rating of a first of the articles in the collection; receiving a selection by the second member of a second link for receiving input characterizing the second member's rating of the first of the articles; storing machine-readable information characterizing the first member's rating and machine-readable information characterizing the second member's rating; receiving a third search query submitted by a third member, wherein the third search query is identical or relevant to the first search query and the second search query and the third member is not explicitly associated with the first member in the member network; determining a collection of articles that are responsive to the third search query, wherein the collection includes the first of the articles; identifying that the member profile information of the first member in the member network is associated with the third search query by virtue of the member profile information describing that the first member has expertise in a field associated with the third search query; and providing the third member with information describing the collection of articles responsive to the third search query and information describing an availability of the information characterizing the first member's rating of the first of the articles, wherein the information provided to the third member excludes any indication that information characterizing the second member's rating of the first of the articles has been received. | 21. 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: receiving machine-readable member profile information characterizing a first member and a second member in a member network; receiving a first search query submitted by the first member and a second search query submitted by the second member; responding to each of the first search query and the second search query with a) links to a collection of articles and b) one or more links for receiving input characterizing respectively ratings of the first member and ratings of the second member of articles in the collection; receiving a selection by the first member of a link for receiving input characterizing the first member's rating of a first of the articles in the collection; receiving a selection by the second member of a second link for receiving input characterizing the second member's rating of the first of the articles; storing machine-readable information characterizing the first member's rating and machine-readable information characterizing the second member's rating; receiving a third search query submitted by a third member, wherein the third search query is identical or relevant to the first search query and the second search query and the third member is not explicitly associated with the first member in the member network; determining a collection of articles that are responsive to the third search query, wherein the collection includes the first of the articles; identifying that the member profile information of the first member in the member network is associated with the third search query by virtue of the member profile information describing that the first member has expertise in a field associated with the third search query; and providing the third member with information describing the collection of articles responsive to the third search query and information describing an availability of the information characterizing the first member's rating of the first of the articles, wherein the information provided to the third member excludes any indication that information characterizing the second member's rating of the first of the articles has been received. 26. The system of claim 21 , wherein the first member's input characterizing the first of the articles comprises a comment characterizing the first member's rating of the first article. | 0.721386 |
9,827,017 | 9 | 13 | 9. The method of claim 5 , further comprising: securing a second transverse anchor on the second side of the spine; securing a second lateral coupling to the first rod and the second transverse anchor; and securing the second rod to the second transverse anchor. | 9. The method of claim 5 , further comprising: securing a second transverse anchor on the second side of the spine; securing a second lateral coupling to the first rod and the second transverse anchor; and securing the second rod to the second transverse anchor. 13. The method of claim 9 , wherein securing the second transverse anchor includes securing the second transverse anchor to a second vertebra inferior to a first vertebra to which the first transverse anchor is secured. | 0.5 |
9,256,582 | 7 | 11 | 7. A computer system for converting presentation file to Darwin Information Typing Architecture (DITA), the computer system comprising: one or more computer processors; one or more computer-readable tangible storage devices; program instructions stored on the one or more computer-readable tangible storage devices for execution by at least one of the one or more processors, the program instructions comprising: prior to receiving a command to convert one or more presentation slides to a DITA document, program instructions to receive a command to group graphical elements located on a presentation slide; responsive to receiving the command to group graphical elements located on the presentation slide, program instructions to assign metadata tags to the grouped graphical elements, the metadata tags comprising at least in part a file name for the group of graphical elements and an indication that the group is to be exported to a single image file; program instructions to receive a command to convert one or more presentation slides to a DITA document, wherein the one or more presentation slides to be converted have been tagged with metadata corresponding to topic type and grouped graphical element file names; program instructions responsive to receiving the command to convert one or more presentation slides to a DITA document, to compile information from the presentation slide, the information selected from the group consisting of the metadata tags, text in the presentation slide, text in a notes section of the presentation slide, and grouped graphical element file names from a first presentation slide of the one or more presentation slides into a string parsed with DITA markup; program instructions to access the metadata tags for a second presentation slide and determining whether the second presentation slide is a new topic; program instructions to determine that the second presentation slide is a new topic; and program instructions responsive to determining that the second presentation slide is a new topic, to convert the string parsed with DITA markup to a DITA topic defined by the metadata in the presentation slide. | 7. A computer system for converting presentation file to Darwin Information Typing Architecture (DITA), the computer system comprising: one or more computer processors; one or more computer-readable tangible storage devices; program instructions stored on the one or more computer-readable tangible storage devices for execution by at least one of the one or more processors, the program instructions comprising: prior to receiving a command to convert one or more presentation slides to a DITA document, program instructions to receive a command to group graphical elements located on a presentation slide; responsive to receiving the command to group graphical elements located on the presentation slide, program instructions to assign metadata tags to the grouped graphical elements, the metadata tags comprising at least in part a file name for the group of graphical elements and an indication that the group is to be exported to a single image file; program instructions to receive a command to convert one or more presentation slides to a DITA document, wherein the one or more presentation slides to be converted have been tagged with metadata corresponding to topic type and grouped graphical element file names; program instructions responsive to receiving the command to convert one or more presentation slides to a DITA document, to compile information from the presentation slide, the information selected from the group consisting of the metadata tags, text in the presentation slide, text in a notes section of the presentation slide, and grouped graphical element file names from a first presentation slide of the one or more presentation slides into a string parsed with DITA markup; program instructions to access the metadata tags for a second presentation slide and determining whether the second presentation slide is a new topic; program instructions to determine that the second presentation slide is a new topic; and program instructions responsive to determining that the second presentation slide is a new topic, to convert the string parsed with DITA markup to a DITA topic defined by the metadata in the presentation slide. 11. The computer system of claim 7 , wherein the command to convert one or more presentation slides to a DITA document is received as a user input in a presentation add-in toolbar. | 0.884763 |
7,685,150 | 1 | 19 | 1. A method comprising: a database server running on one or more computers; said database server receiving a first database statement; wherein the first database statement requires access to a view defined as combined results of a set of database statements; wherein the first database statement includes an expression that operates on an XML construct; and said database server generating a second database statement, based on the first database statement and the view, that includes a modified version of the set of database statements in the distributive form and rewritten to include the expression that operates on the XML construct. | 1. A method comprising: a database server running on one or more computers; said database server receiving a first database statement; wherein the first database statement requires access to a view defined as combined results of a set of database statements; wherein the first database statement includes an expression that operates on an XML construct; and said database server generating a second database statement, based on the first database statement and the view, that includes a modified version of the set of database statements in the distributive form and rewritten to include the expression that operates on the XML construct. 19. The method of claim 1 , wherein the expression is an XML component operation. | 0.897468 |
7,571,110 | 32 | 34 | 32. A computer implemented method for surveying a plurality of users with a sequence of questions that is automatically tailored per user to create a corresponding individualized compensation report, comprising the steps of: presenting to each user, with a collaborative filtering engine of a computer implemented survey engine, a tailored sequence of questions that is independently, asynchronous, and dynamically tailored for each and every user of the plurality of users on an individual basis from a source containing a plurality of different questions, each user's answer to each of said sequence of questions being stored in a corresponding user profile, said tailored sequence of questions directed towards determination of job information, career information, and potential profile matches responsive of a user profile and one or more affinity groups of said user; determining periodically, with said computer implemented survey engine, an affinity of each of said corresponding user profile to compensation within one or more affinity groups, wherein each affinity group comprises a plurality of user profiles and wherein a user profile corresponds to at least one affinity group, said one or more affinity groups being created independent of the order in which said tailored sequence of questions is presented to a user; receiving answers from each user; filtering said user profile, with a collaborative filtering engine of said computer implemented survey engine, wherein said filtering further comprises the application of a rules engine that compares said user profile to a set of predefined criteria; modifying an answer if it is inconsistent with at least one of: said user profile; and said affinity group; wherein determining an appropriate next question for said sequence of questions to be presented to said user on an individual basis, said appropriate next question, and a specific order in which said sequence of said questions are presented to each said user, being determined on an individual, user-by-user basis based on at least a particular affinity group or combination of affinity groups to which said user profile is associated and an answer to a previously presented question; storing said user profile of said each user in a storage associated with said computer implemented survey engine; wherein said affinity group comprises at least one of: profession; compensation; compensation range; experience; experience range; position; and position range; the steps repeated at least once more per user; determining, with said collaborative filtering engine of said computer implemented survey engine, when no additional questions are to be presented to said individual based upon said individual's response to said sequence of questions; capturing, with said collaborative filtering engine of said computer implemented survey engine, profile attributes comprising targeted compensation variables with regard to said individual user's profile responsive to an individual's answers to said sequence of questions; generating a personalized compensation report, which includes job information, career information, compensation, and potential profile matches for a user responding to said tailored sequence of questions responsive of a request from said user to generate said report; and creating, by the computer implemented survey engine, when applicable new affinity groups as additional users respond to respective tailored sequence of questions. | 32. A computer implemented method for surveying a plurality of users with a sequence of questions that is automatically tailored per user to create a corresponding individualized compensation report, comprising the steps of: presenting to each user, with a collaborative filtering engine of a computer implemented survey engine, a tailored sequence of questions that is independently, asynchronous, and dynamically tailored for each and every user of the plurality of users on an individual basis from a source containing a plurality of different questions, each user's answer to each of said sequence of questions being stored in a corresponding user profile, said tailored sequence of questions directed towards determination of job information, career information, and potential profile matches responsive of a user profile and one or more affinity groups of said user; determining periodically, with said computer implemented survey engine, an affinity of each of said corresponding user profile to compensation within one or more affinity groups, wherein each affinity group comprises a plurality of user profiles and wherein a user profile corresponds to at least one affinity group, said one or more affinity groups being created independent of the order in which said tailored sequence of questions is presented to a user; receiving answers from each user; filtering said user profile, with a collaborative filtering engine of said computer implemented survey engine, wherein said filtering further comprises the application of a rules engine that compares said user profile to a set of predefined criteria; modifying an answer if it is inconsistent with at least one of: said user profile; and said affinity group; wherein determining an appropriate next question for said sequence of questions to be presented to said user on an individual basis, said appropriate next question, and a specific order in which said sequence of said questions are presented to each said user, being determined on an individual, user-by-user basis based on at least a particular affinity group or combination of affinity groups to which said user profile is associated and an answer to a previously presented question; storing said user profile of said each user in a storage associated with said computer implemented survey engine; wherein said affinity group comprises at least one of: profession; compensation; compensation range; experience; experience range; position; and position range; the steps repeated at least once more per user; determining, with said collaborative filtering engine of said computer implemented survey engine, when no additional questions are to be presented to said individual based upon said individual's response to said sequence of questions; capturing, with said collaborative filtering engine of said computer implemented survey engine, profile attributes comprising targeted compensation variables with regard to said individual user's profile responsive to an individual's answers to said sequence of questions; generating a personalized compensation report, which includes job information, career information, compensation, and potential profile matches for a user responding to said tailored sequence of questions responsive of a request from said user to generate said report; and creating, by the computer implemented survey engine, when applicable new affinity groups as additional users respond to respective tailored sequence of questions. 34. The method of claim 32 , wherein a next question in said sequence of questions is determined based on at least one of: popularity of said question within said particular affinity group or combination of said affinity groups; a most frequently answered question within said particular affinity group or combination of said affinity groups; and a most recently answered question within said particular affinity group or combination of said affinity groups; and in relation to said question. | 0.5 |
8,074,184 | 16 | 20 | 16. A computer-implemented electronic document modification system having processor, memory, and data storage subsystems, the computer-implemented system, comprising: a processor programmed and adapted to: (a) maintain an electronic document, wherein at least a first portion of content in the electronic document includes content generated by a user via an input device and the content converted by a recognizer to recognized content as standard text, and (b) obtain data associated with the recognized content; and a text injector system to strip additional data from incoming input that is not supported in a data structure of the electronic document and move the stripped additional data to a supporting data structure, wherein: the data is stored in the data structure directly linked to the recognized content that includes information not included in the electronic document, the data structure including a plurality of different linked nodes, where each linked node stores additional information related to the data stored in the linked node including a location within the electronic document of the recognized content and a global unique identifier that identifies a source of the recognized content; the input device receives by the user, a selection of a segment that optionally includes the first portion of the content or the recognized content, the processor further is programmed and adapted to provide to the user, at least one selectable alternative for the first portion of the content or the recognized content selected by the user based at least in part on the data associated with the first portion where the user can modify the recognized content with the at least one selectable alternative; the data associated with the first portion of the content includes an expanded version of the electronic document separate from the electronic document; the expanded version is directly and exclusively linked to the electronic document, and the expanded version is saved and made available to the user upon subsequent access of the electronic document; the data associated with the first portion of the content includes properties associated with the first portion of the content that are not included in the electronic document; and the processor further is programmed and adapted to maintain synchronization between changes to either the content of the electronic document or the expanded version. | 16. A computer-implemented electronic document modification system having processor, memory, and data storage subsystems, the computer-implemented system, comprising: a processor programmed and adapted to: (a) maintain an electronic document, wherein at least a first portion of content in the electronic document includes content generated by a user via an input device and the content converted by a recognizer to recognized content as standard text, and (b) obtain data associated with the recognized content; and a text injector system to strip additional data from incoming input that is not supported in a data structure of the electronic document and move the stripped additional data to a supporting data structure, wherein: the data is stored in the data structure directly linked to the recognized content that includes information not included in the electronic document, the data structure including a plurality of different linked nodes, where each linked node stores additional information related to the data stored in the linked node including a location within the electronic document of the recognized content and a global unique identifier that identifies a source of the recognized content; the input device receives by the user, a selection of a segment that optionally includes the first portion of the content or the recognized content, the processor further is programmed and adapted to provide to the user, at least one selectable alternative for the first portion of the content or the recognized content selected by the user based at least in part on the data associated with the first portion where the user can modify the recognized content with the at least one selectable alternative; the data associated with the first portion of the content includes an expanded version of the electronic document separate from the electronic document; the expanded version is directly and exclusively linked to the electronic document, and the expanded version is saved and made available to the user upon subsequent access of the electronic document; the data associated with the first portion of the content includes properties associated with the first portion of the content that are not included in the electronic document; and the processor further is programmed and adapted to maintain synchronization between changes to either the content of the electronic document or the expanded version. 20. The computer-implemented system according to claim 16 , wherein the first portion of the content of the electronic document includes a word, character, or character string generated by a handwriting recognizer, and the data associated with the first portion of the content of the electronic document includes one or more potential alternative words, characters, or character strings generated by the handwriting recognizer. | 0.5 |
7,711,191 | 3 | 4 | 3. A secure document data capture system for generating a data structure, comprising a data field value associated with each of a plurality of identified data fields, from a document image comprising text representing each of such data field values, the secure document data capture system comprising: a character recognition system receiving the document image and recognizing characters within the text to generate, for each of the identified data fields, a data field value for association therewith; a validation engine for identifying a subset of the identified data fields, the subset of the identified data fields being those data fields with which its associated data field value includes at least one suspect character, a suspect character being a character which fails to comply with a validation rule thereby indicating that that character recognition system erred in recognizing such character; an exception handling system: distinguishing an exception portion of the document image from a redacted portion of the document image, the exception portion of the document image being a portion of the document image including the text of the at least suspect characters of a data field value and the redacted portion of the document image being a portion of the document image which comprises text which discloses the meaning of the data field value; providing an exception image to a first client system, the exception image comprising only the exception portion of the document image; and receiving from the first client system, user input of a replacement character for each suspect character; and the secure data capture system generating the data structure utilizing, for each identified data field, the data field values generated by the character recognition system with substitution of the replacement character from the exception handling system for each suspect character. | 3. A secure document data capture system for generating a data structure, comprising a data field value associated with each of a plurality of identified data fields, from a document image comprising text representing each of such data field values, the secure document data capture system comprising: a character recognition system receiving the document image and recognizing characters within the text to generate, for each of the identified data fields, a data field value for association therewith; a validation engine for identifying a subset of the identified data fields, the subset of the identified data fields being those data fields with which its associated data field value includes at least one suspect character, a suspect character being a character which fails to comply with a validation rule thereby indicating that that character recognition system erred in recognizing such character; an exception handling system: distinguishing an exception portion of the document image from a redacted portion of the document image, the exception portion of the document image being a portion of the document image including the text of the at least suspect characters of a data field value and the redacted portion of the document image being a portion of the document image which comprises text which discloses the meaning of the data field value; providing an exception image to a first client system, the exception image comprising only the exception portion of the document image; and receiving from the first client system, user input of a replacement character for each suspect character; and the secure data capture system generating the data structure utilizing, for each identified data field, the data field values generated by the character recognition system with substitution of the replacement character from the exception handling system for each suspect character. 4. The secure document data capture system of claim 3 , wherein: the exception handling system further: provides the exception image to a second client system; receives from the second client system, user input of a replacement character for each suspect character; and the secure data capture system substitutes the replacement character from the exception handling system for each suspect character only when the replacement character form the first client system and the replacement character from the second client system are the same. | 0.5 |
8,352,244 | 10 | 11 | 10. A method for training a machine translation system, comprising the steps of translating a test set from a first language to a second language using the existing parallel corpus stored in memory on the machine translation system; calculating a translation accuracy score for each item in the test set; comparing the translation accuracy score for each item to a desired performance score to determine whether the parallel corpus needs to be updated for that item; if the translation accuracy score for an item is equal to or greater than a desired performance score, removing that item from the test set, so as to create test set E; translating the test set E from a first language to a second language using a unidirectional translation corpus, so as to create set F in the second language; translating set F back to the first language using a unidirectional translation corpus so as to create set E′ in the first language; computing confidence scores for the translation of each item in the set based on the similarity of E and E′; creating a subset, H, of highest confidence scores; adding the translations in subset H directly to the parallel corpus without presenting the translations to a human translator for correction; creating a subset, L, of lowest confidence scores; presenting subset L to human translators for correction; and adding the human corrections to the parallel corpus. | 10. A method for training a machine translation system, comprising the steps of translating a test set from a first language to a second language using the existing parallel corpus stored in memory on the machine translation system; calculating a translation accuracy score for each item in the test set; comparing the translation accuracy score for each item to a desired performance score to determine whether the parallel corpus needs to be updated for that item; if the translation accuracy score for an item is equal to or greater than a desired performance score, removing that item from the test set, so as to create test set E; translating the test set E from a first language to a second language using a unidirectional translation corpus, so as to create set F in the second language; translating set F back to the first language using a unidirectional translation corpus so as to create set E′ in the first language; computing confidence scores for the translation of each item in the set based on the similarity of E and E′; creating a subset, H, of highest confidence scores; adding the translations in subset H directly to the parallel corpus without presenting the translations to a human translator for correction; creating a subset, L, of lowest confidence scores; presenting subset L to human translators for correction; and adding the human corrections to the parallel corpus. 11. The method of claim 10 wherein the scoring metric and threshold values used to compute confidence scores are defined by the user. | 0.775338 |
8,438,007 | 29 | 31 | 29. A computer-readable storage device encoded with a computer program product for use in generating a second human language user interface for a software product having a first human language user interface, the product comprising instructions operable to cause data processing apparatus to perform operations comprising: opening a glossary database that includes a plurality of string sets at least some of which include a user interface string in a first human language and a corresponding user interface string in a second human language, wherein a string set comprises user interface strings having the same set identifier, a set identifier comprising context information about a previous use of a user interface string in a user interface of a software product including a name of the software product and an identifier specifying a type of user interface string and each user interface string comprises a string displayed in a user interface of a software product; selecting a user interface string in the first human language user interface; finding, using a processor, a string set in the glossary database having the selected user interface string and a user interface string in the second human language, wherein the user interface strings in the string set were previously used in a software product different from the software product for which the second human language user interface is being generated; and using the user interface string in the second human language in the second human language user interface, wherein finding a string set in the glossary database having the selected user interface string comprises: searching for one or more literal user interface strings in the glossary database that matches the selected user interface string, generating a score for each matching user interface string based on a comparison of (i) context information about a previous use of the matching user interface string with (ii) context information about a previous use of the selected user interface string, and deciding, based on the score, whether or not to select a string set. | 29. A computer-readable storage device encoded with a computer program product for use in generating a second human language user interface for a software product having a first human language user interface, the product comprising instructions operable to cause data processing apparatus to perform operations comprising: opening a glossary database that includes a plurality of string sets at least some of which include a user interface string in a first human language and a corresponding user interface string in a second human language, wherein a string set comprises user interface strings having the same set identifier, a set identifier comprising context information about a previous use of a user interface string in a user interface of a software product including a name of the software product and an identifier specifying a type of user interface string and each user interface string comprises a string displayed in a user interface of a software product; selecting a user interface string in the first human language user interface; finding, using a processor, a string set in the glossary database having the selected user interface string and a user interface string in the second human language, wherein the user interface strings in the string set were previously used in a software product different from the software product for which the second human language user interface is being generated; and using the user interface string in the second human language in the second human language user interface, wherein finding a string set in the glossary database having the selected user interface string comprises: searching for one or more literal user interface strings in the glossary database that matches the selected user interface string, generating a score for each matching user interface string based on a comparison of (i) context information about a previous use of the matching user interface string with (ii) context information about a previous use of the selected user interface string, and deciding, based on the score, whether or not to select a string set. 31. The product encoded on the computer-readable storage device of claim 29 , wherein if a single match is found, selecting a string set that includes the matching user interface string if the score for the matching user interface string equals or exceeds a specified minimum score value and if the score for the matching user interface string is less than the specified minimum score value, then not selecting the string set and delegating to a human translator the translation of the user interface string in the first human language into the second human language. | 0.5 |
8,458,196 | 5 | 6 | 5. The method of claim 1 , further comprising: storing a plurality of authority signature values in a database; and retrieving and displaying information regarding one or more authors from the database having a predetermined rank or authority signature value for a query topic in response to a request regarding the query topic. | 5. The method of claim 1 , further comprising: storing a plurality of authority signature values in a database; and retrieving and displaying information regarding one or more authors from the database having a predetermined rank or authority signature value for a query topic in response to a request regarding the query topic. 6. The method of claim 5 , wherein the retrieving and displaying step comprises: outputting information regarding one or more users with highest ranked authority signature values for the query topic. | 0.5025 |
9,910,888 | 1 | 3 | 1. A method comprising: receiving a map-reduce job written in a first map-reduce language, wherein the map-reduce job is to be performed in parallel on a plurality of nodes of a plurality of clusters, wherein the first map-reduce language is a general map-reduce language that describes functions supported by multiple map-reduce frameworks but is not specific to any of the multiple map-reduce frameworks; selecting one or more clusters from the plurality of clusters to run the map-reduce job, wherein the selected one or more clusters of the plurality of clusters operate a different map-reduce framework from other clusters of the plurality of clusters; identifying a second map-reduce language associated with the selected one or more clusters; converting the first map-reduce language of the map-reduce job into the second map-reduce language; and causing the map-reduce job in the second map-reduce language to be run on the plurality of nodes of the selected one or more clusters. | 1. A method comprising: receiving a map-reduce job written in a first map-reduce language, wherein the map-reduce job is to be performed in parallel on a plurality of nodes of a plurality of clusters, wherein the first map-reduce language is a general map-reduce language that describes functions supported by multiple map-reduce frameworks but is not specific to any of the multiple map-reduce frameworks; selecting one or more clusters from the plurality of clusters to run the map-reduce job, wherein the selected one or more clusters of the plurality of clusters operate a different map-reduce framework from other clusters of the plurality of clusters; identifying a second map-reduce language associated with the selected one or more clusters; converting the first map-reduce language of the map-reduce job into the second map-reduce language; and causing the map-reduce job in the second map-reduce language to be run on the plurality of nodes of the selected one or more clusters. 3. The method of claim 1 , wherein the second map-reduce language is a framework-specific language that corresponds to a software framework running on the selected one or more clusters. | 0.733429 |
8,674,996 | 1 | 2 | 1. A method for controlling a rendering engine to produce audio, the method comprising: receiving commands at a user computing device specifying one or more character actions for a computer-modeled character displayed on a display device of the user computing device, wherein the commands are from a content provider at a first location and the user computing device is at a second location remote from the first location, wherein the commands comprise predetermined instructions in a control script for the one or more character actions and an electronic representation of human speech, and wherein one or more of the predetermined instructions include a specified duration; and animating lip movement of the computer-modeled character displayed on the display device of the user computing device at the second location, wherein the animating is performed according to the predetermined instructions in the control script received from the content provider and uses one or more pre-computed lip movements associated with selected phonetic sounds, wherein the animating comprises synchronizing an audio representation of a human speech with the animated lip movement of the computer modeled character, and wherein the synchronizing is performed by maintaining a constant playback rate by indicating a start time and duration time corresponding to a set of one or more of the predetermined instructions in the control script such that each resulting animation that comprises a pre-computed lip movement fits into the corresponding specified duration. | 1. A method for controlling a rendering engine to produce audio, the method comprising: receiving commands at a user computing device specifying one or more character actions for a computer-modeled character displayed on a display device of the user computing device, wherein the commands are from a content provider at a first location and the user computing device is at a second location remote from the first location, wherein the commands comprise predetermined instructions in a control script for the one or more character actions and an electronic representation of human speech, and wherein one or more of the predetermined instructions include a specified duration; and animating lip movement of the computer-modeled character displayed on the display device of the user computing device at the second location, wherein the animating is performed according to the predetermined instructions in the control script received from the content provider and uses one or more pre-computed lip movements associated with selected phonetic sounds, wherein the animating comprises synchronizing an audio representation of a human speech with the animated lip movement of the computer modeled character, and wherein the synchronizing is performed by maintaining a constant playback rate by indicating a start time and duration time corresponding to a set of one or more of the predetermined instructions in the control script such that each resulting animation that comprises a pre-computed lip movement fits into the corresponding specified duration. 2. The method of claim 1 wherein the electronic representation of human speech in the control script comprises an audio waveform. | 0.85 |
9,471,566 | 7 | 31 | 7. A system, comprising: a processor; a memory comprising program instructions, wherein the program instructions are executable by the processor to implement a language input mechanism for converting a phonetic language text to a written language text, wherein the language input mechanism is configured to: generate a plurality of possible phonetic language syllable segmentations for a phonetic language input text string; generate a plurality of possible written language sentences each including one or more written language words, wherein each sentence corresponds to one of the syllable segmentations, and wherein each word in each sentence corresponds to one or more of the syllables in the corresponding syllable segmentation; determine probability scores for the written language words and for sequences of two or more written language words in the plurality of possible written language sentences according to a language model comprising written language words and a history cache of previously selected written language words; generate a list of candidate output written language words for a current selection position in the phonetic language input text string from the plurality of possible written language sentences, wherein the list of candidate output written language words is sorted according to the probability scores; determine one of the possible written language sentences as a most probable candidate output written language sentence for the phonetic language input text string according to the probability scores; and output at least part of the list of sorted candidate output written language words and the candidate output written language sentence in a candidate output text user interface element. | 7. A system, comprising: a processor; a memory comprising program instructions, wherein the program instructions are executable by the processor to implement a language input mechanism for converting a phonetic language text to a written language text, wherein the language input mechanism is configured to: generate a plurality of possible phonetic language syllable segmentations for a phonetic language input text string; generate a plurality of possible written language sentences each including one or more written language words, wherein each sentence corresponds to one of the syllable segmentations, and wherein each word in each sentence corresponds to one or more of the syllables in the corresponding syllable segmentation; determine probability scores for the written language words and for sequences of two or more written language words in the plurality of possible written language sentences according to a language model comprising written language words and a history cache of previously selected written language words; generate a list of candidate output written language words for a current selection position in the phonetic language input text string from the plurality of possible written language sentences, wherein the list of candidate output written language words is sorted according to the probability scores; determine one of the possible written language sentences as a most probable candidate output written language sentence for the phonetic language input text string according to the probability scores; and output at least part of the list of sorted candidate output written language words and the candidate output written language sentence in a candidate output text user interface element. 31. The system as recited in claim 7 , wherein the phonetic language text is Hanyu Pinyin, and wherein the written language text is Mandarin Chinese. | 0.829128 |
7,877,421 | 25 | 30 | 25. A system for generating a transformation for transforming first data conforming with a source data schema to second data conforming to a target data schema, the system comprising: a memory for storing an ontology model including classes and properties of classes, the source data schema, and the target data schema; a schema parser for identifying a first primary data construct within the source data schema, for identifying a secondary data construct within the first primary data construct, for identifying a second primary data construct within a target data schema, and for identifying a second secondary data construct within the second primary data construct; a schema mapper for mapping the first primary data construct to a corresponding class of the ontology model, for mapping the first secondary data construct to a property of the corresponding class of the ontology model, for mapping the second primary data construct to a corresponding class of the ontology model, and for mapping the second secondary data construct to a property of the corresponding class of the ontology model; and a transformation generator for deriving the transformation from the first data into the second data, wherein the transformation is based on mappings mapped by the schema mapper. | 25. A system for generating a transformation for transforming first data conforming with a source data schema to second data conforming to a target data schema, the system comprising: a memory for storing an ontology model including classes and properties of classes, the source data schema, and the target data schema; a schema parser for identifying a first primary data construct within the source data schema, for identifying a secondary data construct within the first primary data construct, for identifying a second primary data construct within a target data schema, and for identifying a second secondary data construct within the second primary data construct; a schema mapper for mapping the first primary data construct to a corresponding class of the ontology model, for mapping the first secondary data construct to a property of the corresponding class of the ontology model, for mapping the second primary data construct to a corresponding class of the ontology model, and for mapping the second secondary data construct to a property of the corresponding class of the ontology model; and a transformation generator for deriving the transformation from the first data into the second data, wherein the transformation is based on mappings mapped by the schema mapper. 30. The system of claim 25 wherein the ontology model is a distributed model. | 0.89538 |
9,171,072 | 1 | 2 | 1. A computer implemented system for validating a document classification process for eDiscovery, internal investigations, law enforcement activities, compliance audits, records management, legacy data clean-up, or defensible dispositions, the system comprising: a document collection of N documents related to eDiscovery, internal investigations, law enforcement activities, compliance audits, records management, legacy data clean-up, or defensible dispositions; a document classification process performed on the document collection; a random selection module configured to automatically generate a random validation set S of documents based on a user selectable percentage P of the N documents from the document collection; and a manual document review process performed on the random validation set of documents to validate overall results of all of the documents classified by the document classification process, wherein the system is configured to dynamically and in real-time measure and display on a computer display device a best case estimate of a quality of the results of the overall document classification process based on the documents that are validated, given the size N of a total data set of the document collection, and based on a predetermined quality threshold for an overall classification quality desired for the document classification process. | 1. A computer implemented system for validating a document classification process for eDiscovery, internal investigations, law enforcement activities, compliance audits, records management, legacy data clean-up, or defensible dispositions, the system comprising: a document collection of N documents related to eDiscovery, internal investigations, law enforcement activities, compliance audits, records management, legacy data clean-up, or defensible dispositions; a document classification process performed on the document collection; a random selection module configured to automatically generate a random validation set S of documents based on a user selectable percentage P of the N documents from the document collection; and a manual document review process performed on the random validation set of documents to validate overall results of all of the documents classified by the document classification process, wherein the system is configured to dynamically and in real-time measure and display on a computer display device a best case estimate of a quality of the results of the overall document classification process based on the documents that are validated, given the size N of a total data set of the document collection, and based on a predetermined quality threshold for an overall classification quality desired for the document classification process. 2. The system of claim 1 , wherein the system is configured to allow a user to monitor the best case estimate of the overall classification quality and terminate the document review process and change parameters and/or instruction for the document classification process based on the best case estimate of the overall classification quality being equal to or lower than the predetermined quality threshold of the documents in the random selected document set. | 0.5 |
9,262,520 | 25 | 32 | 25. A system for executing a computer-implemented method for displaying a data structure including data entities and relationships between the data entities, and for enabling one or more users to interact with the data structure, the system comprising one or more computer devices including or being operatively linked to: (a) at least one display, and (b) a user interface utility operable to: (i) present to one or more users a user interface, by means of the at least one display; (ii) populate the user interface with text labels representing data entities from the data structure; (iii) enable a user to make a change to a first text label within the user interface, the user's change comprising a change to a position of the first text label from a first location on the user interface to a second location specified by the user on the user interface and one or more textual visual properties of the first text label within the user interface; and (iv) automatically determine, based on the user's change to the position and the one or more textual visual properties of the first text label, a relationship between a first data entity and a second data entity in the data structure, wherein the relationship was not represented in the data structure prior to the user's change to the first text label, wherein automatically determining the relationship comprises applying translation rules to a combination of (A) at least one positional visual property relating the position of the first text label to a position of a second text label in the user interface, and (B) at least one textual visual property of the first text label and/or the second text label, after the user's change to the first text label. | 25. A system for executing a computer-implemented method for displaying a data structure including data entities and relationships between the data entities, and for enabling one or more users to interact with the data structure, the system comprising one or more computer devices including or being operatively linked to: (a) at least one display, and (b) a user interface utility operable to: (i) present to one or more users a user interface, by means of the at least one display; (ii) populate the user interface with text labels representing data entities from the data structure; (iii) enable a user to make a change to a first text label within the user interface, the user's change comprising a change to a position of the first text label from a first location on the user interface to a second location specified by the user on the user interface and one or more textual visual properties of the first text label within the user interface; and (iv) automatically determine, based on the user's change to the position and the one or more textual visual properties of the first text label, a relationship between a first data entity and a second data entity in the data structure, wherein the relationship was not represented in the data structure prior to the user's change to the first text label, wherein automatically determining the relationship comprises applying translation rules to a combination of (A) at least one positional visual property relating the position of the first text label to a position of a second text label in the user interface, and (B) at least one textual visual property of the first text label and/or the second text label, after the user's change to the first text label. 32. The system of claim 25 , wherein the user interface utility is configured to enable the one or more users to zoom in and zoom out of a portion of the data structure. | 0.664683 |
8,051,045 | 8 | 12 | 8. A computer program product, encoded in an information carrier, operable to cause data processing apparatus to perform operations comprising: identifying a data record to be archived, the data record comprising a plurality of data record attributes and originally residing in a database; creating an archive record, the archive record comprising a first subset of the plurality of data record attributes, the first subset comprising at least some of the plurality of data record attributes; storing the archive record in a data archive, the data archive being maintained separately from the database; creating a new archive index record, the new archive index record comprising a reference to a location of the archive record in the data archive and a second plurality of attributes of the plurality of data record attributes, the second subset comprising selected attributes from the plurality of data record attributes, the selected attributes being those identified as necessary for access by users of the database; adding the new archive index record to a dictionary-based archive index, the dictionary-based archive index comprising a plurality of archive index records, being stored separately from the database, and comprising a dictionary storing every term used in the plurality of index records; deleting the data record from the database; determining whether an attribute value of the plurality of attribute values is required for frequent user read access; and if the attribute value is not required for frequent user read access, deleting the attribute value from the dictionary-based archive index. | 8. A computer program product, encoded in an information carrier, operable to cause data processing apparatus to perform operations comprising: identifying a data record to be archived, the data record comprising a plurality of data record attributes and originally residing in a database; creating an archive record, the archive record comprising a first subset of the plurality of data record attributes, the first subset comprising at least some of the plurality of data record attributes; storing the archive record in a data archive, the data archive being maintained separately from the database; creating a new archive index record, the new archive index record comprising a reference to a location of the archive record in the data archive and a second plurality of attributes of the plurality of data record attributes, the second subset comprising selected attributes from the plurality of data record attributes, the selected attributes being those identified as necessary for access by users of the database; adding the new archive index record to a dictionary-based archive index, the dictionary-based archive index comprising a plurality of archive index records, being stored separately from the database, and comprising a dictionary storing every term used in the plurality of index records; deleting the data record from the database; determining whether an attribute value of the plurality of attribute values is required for frequent user read access; and if the attribute value is not required for frequent user read access, deleting the attribute value from the dictionary-based archive index. 12. The computer program product of claim 8 , wherein: the second plurality of attributes at least includes the first plurality of attributes. | 0.926653 |
8,121,985 | 15 | 18 | 15. A learning management system (LMS) comprising: a master repository storing an archived copy of each of a plurality of learning objects and an object version file, each learning object comprising at least one content file; an interface for receiving a second plurality of content files arranged in a second plurality of learning objects, at least a first subset of the plurality of content files corresponding to a second subset of the second plurality of content files, the object version file associated with the first subset; and one or more processors operable to: compare version information for each of the content files from the local content repository to versioning information obtained from an object version file identifying a prior version of the updated learning object, the object version file identifies aspects of the content files included in the prior version of the updated learning object; generate a new object version file associated with updating the master content repository with the updated learning object, the new object version file including pointers to prior versions of content files substantially matching content files from the local content repository; update the master content repository with new versions of the content files included in the updated learning object independent of updating the master repository with the content files from the local repository that substantially match content files currently stored in the master repository; and in response to at least a portion of the version information of a first of the content files matching a corresponding portion of the versioning information stored in the object version file, store in the new object version file a pointer to a corresponding content file in the prior version of the learning object stored in the master content repository. | 15. A learning management system (LMS) comprising: a master repository storing an archived copy of each of a plurality of learning objects and an object version file, each learning object comprising at least one content file; an interface for receiving a second plurality of content files arranged in a second plurality of learning objects, at least a first subset of the plurality of content files corresponding to a second subset of the second plurality of content files, the object version file associated with the first subset; and one or more processors operable to: compare version information for each of the content files from the local content repository to versioning information obtained from an object version file identifying a prior version of the updated learning object, the object version file identifies aspects of the content files included in the prior version of the updated learning object; generate a new object version file associated with updating the master content repository with the updated learning object, the new object version file including pointers to prior versions of content files substantially matching content files from the local content repository; update the master content repository with new versions of the content files included in the updated learning object independent of updating the master repository with the content files from the local repository that substantially match content files currently stored in the master repository; and in response to at least a portion of the version information of a first of the content files matching a corresponding portion of the versioning information stored in the object version file, store in the new object version file a pointer to a corresponding content file in the prior version of the learning object stored in the master content repository. 18. The LMS of claim 15 , the processors further operable to instantiate a versioning object storing the new object version file and wherein the processors operable to store the first content file comprises the processors operable to store the first content file in the versioning object and wherein the processors operable to store the pointer to the corresponding content file comprises the processors operable to store the pointer in the versioning object. | 0.5 |
8,736,553 | 27 | 31 | 27. A text input method executable by an electronic device connectable to a display and capable of detecting touch operations, comprising: displaying a virtual keyboard comprising a plurality of keys; utilizing the virtual keyboard as a base for one or more touch operations detectable by a touch detection function, wherein each key of the plurality of keys is operable as a toggle key and is associated with one or more characters for input to a text area; selecting a first initially selected character associated with a first activated key in response to a first touch operation based on the first activated key in the plurality of keys of the virtual keyboard, wherein the first touch operation is detectable by the touch detection function and comprises an operation of a press, an operation of a touch movement track, or a combination of an operation of a press and an operation of a touch movement track; selecting a second initially selected character associated with a second activated key in response to a second touch operation based on the second activated key in the plurality of keys of the virtual keyboard after the first touch operation, wherein the second touch operation is detectable by the touch detection function and comprises an operation of a press, an operation of a touch movement track, or a combination of an operation of a press and an operation of a touch movement track; utilizing the first initially selected character or a first related character associated with the first initially selected character as a first determined character; utilizing the second initially selected character or a second related character associated with the second initially selected character as a last determined character; generating an auto-completed word based on a database of words in response to the second touch operation, wherein the auto-completed word comprises the first determined character as a leftmost character of the auto-completed word and the last determined character as a rightmost character of the auto-completed word; presenting the auto-completed word as an option in a first graphical user interface component in response to activation of the second activated key; and entering the auto-completed word to the text area in response to an assistant touch operation associated with the option in the first graphical user interface component, wherein the assistant touch operation is detectable by the touch detection function. | 27. A text input method executable by an electronic device connectable to a display and capable of detecting touch operations, comprising: displaying a virtual keyboard comprising a plurality of keys; utilizing the virtual keyboard as a base for one or more touch operations detectable by a touch detection function, wherein each key of the plurality of keys is operable as a toggle key and is associated with one or more characters for input to a text area; selecting a first initially selected character associated with a first activated key in response to a first touch operation based on the first activated key in the plurality of keys of the virtual keyboard, wherein the first touch operation is detectable by the touch detection function and comprises an operation of a press, an operation of a touch movement track, or a combination of an operation of a press and an operation of a touch movement track; selecting a second initially selected character associated with a second activated key in response to a second touch operation based on the second activated key in the plurality of keys of the virtual keyboard after the first touch operation, wherein the second touch operation is detectable by the touch detection function and comprises an operation of a press, an operation of a touch movement track, or a combination of an operation of a press and an operation of a touch movement track; utilizing the first initially selected character or a first related character associated with the first initially selected character as a first determined character; utilizing the second initially selected character or a second related character associated with the second initially selected character as a last determined character; generating an auto-completed word based on a database of words in response to the second touch operation, wherein the auto-completed word comprises the first determined character as a leftmost character of the auto-completed word and the last determined character as a rightmost character of the auto-completed word; presenting the auto-completed word as an option in a first graphical user interface component in response to activation of the second activated key; and entering the auto-completed word to the text area in response to an assistant touch operation associated with the option in the first graphical user interface component, wherein the assistant touch operation is detectable by the touch detection function. 31. The text input method as claimed in claim 27 , wherein appearance of each of the first activated key and the second activated key shows at least two characters. | 0.881159 |
9,753,962 | 18 | 19 | 18. A system to operate within a host organization, the system comprising: a processor to execute instructions stored in memory of the system; a request interface to receive a request at the host organization from a user device to display a tabular dataset; a query interface to retrieve the tabular dataset from a database system executing at the host organization; the request interface to further display the tabular dataset as output to the user device, the displayed output including a plurality of data values depicted as known values and a plurality of null values depicted as unknown values; the request interface to further receive input from the user device to populate the tabular dataset to a specified fill percentage; the query interface to further query the database system for predicted values to populate a portion of the null values of the tabular dataset, wherein querying the database system comprises issuing a PREDICT command term and passing as a parameter one or more specified columns of the tabular dataset to be predicted, wherein the query interface is to receive a distribution for every one of the plurality of null values within the tabular dataset responsive to the query; an analysis engine to calculate a credible interval for each distribution received and wherein the analysis engine is to further populate the portion of the null values of the tabular dataset with the predicted values until the specified fill percentage is reached; and wherein the request interface is to further display the tabular dataset having the predicted values populated therein as updated output to the user device by displaying selected ones of the predicted values that correspond to a calculated credible interval in excess of a minimum threshold. | 18. A system to operate within a host organization, the system comprising: a processor to execute instructions stored in memory of the system; a request interface to receive a request at the host organization from a user device to display a tabular dataset; a query interface to retrieve the tabular dataset from a database system executing at the host organization; the request interface to further display the tabular dataset as output to the user device, the displayed output including a plurality of data values depicted as known values and a plurality of null values depicted as unknown values; the request interface to further receive input from the user device to populate the tabular dataset to a specified fill percentage; the query interface to further query the database system for predicted values to populate a portion of the null values of the tabular dataset, wherein querying the database system comprises issuing a PREDICT command term and passing as a parameter one or more specified columns of the tabular dataset to be predicted, wherein the query interface is to receive a distribution for every one of the plurality of null values within the tabular dataset responsive to the query; an analysis engine to calculate a credible interval for each distribution received and wherein the analysis engine is to further populate the portion of the null values of the tabular dataset with the predicted values until the specified fill percentage is reached; and wherein the request interface is to further display the tabular dataset having the predicted values populated therein as updated output to the user device by displaying selected ones of the predicted values that correspond to a calculated credible interval in excess of a minimum threshold. 19. The system of claim 18 : wherein the query interface is to query the database system comprises the query interface construct a query for the database system specifying at least (i) the PREDICT command term, (ii) the one or more specified columns of the tabular dataset to be predicted, and (iii) one or more column name=value pairs specifying column names to be fixed and corresponding values by which to fix the column names. | 0.5 |
9,947,119 | 1 | 8 | 1. A method comprising: obtaining graph data including information related to a plurality of nodes; the plurality of nodes corresponding to search queries performed on a host site; constructing a sub-graph of additional nodes that represent search results of the search queries, the constructing of the sub-graph including generating links between the additional nodes based on an amount of overlap among the search results produced from the search queries that correspond to the one or more of the plurality of nodes, the additional nodes included in the sub-graph being clusters of the search results; rendering a graph by displaying each node at a respective absolute position within the graph and generating a plurality of tiles that depict images of the sub-graph at each of a plurality of zoom levels; and displaying a sub-graph image corresponding to a selected position and zoom level. | 1. A method comprising: obtaining graph data including information related to a plurality of nodes; the plurality of nodes corresponding to search queries performed on a host site; constructing a sub-graph of additional nodes that represent search results of the search queries, the constructing of the sub-graph including generating links between the additional nodes based on an amount of overlap among the search results produced from the search queries that correspond to the one or more of the plurality of nodes, the additional nodes included in the sub-graph being clusters of the search results; rendering a graph by displaying each node at a respective absolute position within the graph and generating a plurality of tiles that depict images of the sub-graph at each of a plurality of zoom levels; and displaying a sub-graph image corresponding to a selected position and zoom level. 8. The method of claim 1 , further comprising: generating a global graph depicting a relationship between the plurality of nodes and the sub-graph related to the one or more of the plurality of nodes. | 0.698795 |
10,042,845 | 8 | 13 | 8. A method comprising: obtaining, by at least one hardware processor, primary language content written in a first spoken language; obtaining, by the at least one hardware processor, secondary language content written in a second spoken language; obtaining, by the at least one hardware processor, a machine translation of the primary language content by machine translating the primary language content from the first spoken language to the second spoken language; determining, by the at least one hardware processor, an initial language model, based on the second spoken language, from the machine translation of the primary language content; determining, by the at least one hardware processor, a language model perturbation using the initial language model, the language model perturbation accounting for a difference between the machine translation of the primary language content and the secondary language content; determining, by the at least one hardware processor, a classification model from the initial language model and the language model perturbation, the classification model being used to classify a given plurality of words written in the second spoken language to identify whether the given plurality of words written in the second spoken language are irrelevant to an item of interest provided by a social media networking site in the first spoken language; applying, by the at least one hardware processor, the classification model to a plurality of comments received in a written form of the second spoken language and associated with the item of interest; determining, by using the classification model, at least one comment selected from the plurality of comments as irrelevant to the item of interest; and preventing, by the at least one hardware processor, display of the at least one comment in response to classifying the at least one comment as irrelevant, wherein: the selected at least one comment was provided by a first member of the social networking service, and the selected at least one comment is prevented from being displayed to other members of the social networking service that request a display of the item of interest. | 8. A method comprising: obtaining, by at least one hardware processor, primary language content written in a first spoken language; obtaining, by the at least one hardware processor, secondary language content written in a second spoken language; obtaining, by the at least one hardware processor, a machine translation of the primary language content by machine translating the primary language content from the first spoken language to the second spoken language; determining, by the at least one hardware processor, an initial language model, based on the second spoken language, from the machine translation of the primary language content; determining, by the at least one hardware processor, a language model perturbation using the initial language model, the language model perturbation accounting for a difference between the machine translation of the primary language content and the secondary language content; determining, by the at least one hardware processor, a classification model from the initial language model and the language model perturbation, the classification model being used to classify a given plurality of words written in the second spoken language to identify whether the given plurality of words written in the second spoken language are irrelevant to an item of interest provided by a social media networking site in the first spoken language; applying, by the at least one hardware processor, the classification model to a plurality of comments received in a written form of the second spoken language and associated with the item of interest; determining, by using the classification model, at least one comment selected from the plurality of comments as irrelevant to the item of interest; and preventing, by the at least one hardware processor, display of the at least one comment in response to classifying the at least one comment as irrelevant, wherein: the selected at least one comment was provided by a first member of the social networking service, and the selected at least one comment is prevented from being displayed to other members of the social networking service that request a display of the item of interest. 13. The method of claim 8 , wherein the initial language model comprises a regularized logistic regression model. | 0.861858 |
9,747,377 | 10 | 11 | 10. A system comprising a processor in electronic communication with computer-readable storage media, the computer readable-storage media storing instructions that, when executed, perform a method, the method comprising: receiving a search query; responsive to receiving the query: obtaining a set of search results corresponding to the query; and displaying at least a portion of the set of search results within a main search engine results view; obtaining a set of related content corresponding to the query, the set of related content determined by narrowing the query; receiving a semantic zoom command associated with the main search engine results view; and in response to receiving the semantic zoom command, transitioning the search interface from the main search engine results view to a related content view. | 10. A system comprising a processor in electronic communication with computer-readable storage media, the computer readable-storage media storing instructions that, when executed, perform a method, the method comprising: receiving a search query; responsive to receiving the query: obtaining a set of search results corresponding to the query; and displaying at least a portion of the set of search results within a main search engine results view; obtaining a set of related content corresponding to the query, the set of related content determined by narrowing the query; receiving a semantic zoom command associated with the main search engine results view; and in response to receiving the semantic zoom command, transitioning the search interface from the main search engine results view to a related content view. 11. The system of claim 10 , the obtaining a set of related content comprising: obtaining the link to the application. | 0.670391 |
9,747,358 | 1 | 8 | 1. A method comprising: receiving a pattern selection from a user through a guided user interface that restricts the pattern selection to one of a set of available patterns in a multi-dimensional data source without requiring specific user knowledge of the set of available patterns; receiving a parameter selection from the user through the guided user interface that restricts the parameter selection to a set of available parameters in the multi-dimensional data source associated with the pattern selection; and executing by a computer system the pattern selection and the parameter selection on the multi-dimensional data source to obtain a report with deterministic values. | 1. A method comprising: receiving a pattern selection from a user through a guided user interface that restricts the pattern selection to one of a set of available patterns in a multi-dimensional data source without requiring specific user knowledge of the set of available patterns; receiving a parameter selection from the user through the guided user interface that restricts the parameter selection to a set of available parameters in the multi-dimensional data source associated with the pattern selection; and executing by a computer system the pattern selection and the parameter selection on the multi-dimensional data source to obtain a report with deterministic values. 8. The method of claim 1 wherein the at least one parameter specifies or limits data for the pattern. | 0.890456 |
10,147,427 | 9 | 15 | 9. A computer program product for electronically utilizing content in a communication between a customer and a service representative, the computer program product comprising: one or more non-transitory computer-readable storage devices and a plurality of program instructions stored on at least one of the one or more computer-readable storage devices, the plurality of program instructions comprising: program instructions to capture an audible conversation between a customer and a service representative; program instructions to convert the entire audible conversation into computer searchable text data; program instructions to store the entire audible conversation in an audio repository and the entire searchable text data representative of the entire audio conversation in a text repository; program instructions to analyze the computer searchable text data during the audible conversation to identify one or more meta tags previously stored in the text repository or generated during the audible conversation determined relevant to a current conversation between the service representative and the customer, wherein each of the one or more meta tags are associated with the customer and wherein each meta tag provides a contextual item determined from at least a portion of one of the current or previous conversation with the customer; program instructions to generate one or more recommendations of product offerings tailored to the customer based on the one or more meta tags, wherein the contextual item associated with the meta tag represents one or more topics discussed during one or more communication sessions and each contextual item includes one or more contextual keys; and program instructions to display, to the service representative, a meta tag and the one or more recommendations determined to be relevant to the current conversation between the service representative and the customer; and program instructions to determine sentiment toward the contextual item associated with the meta tag by detecting one or more words having a sentiment polarity using a sentiment dictionary containing sentiment related words having a particular polarity whereby once polarity has been determined, a number of positive and negative sentiment words spoken the customer in relation to identified contextual items are countered. | 9. A computer program product for electronically utilizing content in a communication between a customer and a service representative, the computer program product comprising: one or more non-transitory computer-readable storage devices and a plurality of program instructions stored on at least one of the one or more computer-readable storage devices, the plurality of program instructions comprising: program instructions to capture an audible conversation between a customer and a service representative; program instructions to convert the entire audible conversation into computer searchable text data; program instructions to store the entire audible conversation in an audio repository and the entire searchable text data representative of the entire audio conversation in a text repository; program instructions to analyze the computer searchable text data during the audible conversation to identify one or more meta tags previously stored in the text repository or generated during the audible conversation determined relevant to a current conversation between the service representative and the customer, wherein each of the one or more meta tags are associated with the customer and wherein each meta tag provides a contextual item determined from at least a portion of one of the current or previous conversation with the customer; program instructions to generate one or more recommendations of product offerings tailored to the customer based on the one or more meta tags, wherein the contextual item associated with the meta tag represents one or more topics discussed during one or more communication sessions and each contextual item includes one or more contextual keys; and program instructions to display, to the service representative, a meta tag and the one or more recommendations determined to be relevant to the current conversation between the service representative and the customer; and program instructions to determine sentiment toward the contextual item associated with the meta tag by detecting one or more words having a sentiment polarity using a sentiment dictionary containing sentiment related words having a particular polarity whereby once polarity has been determined, a number of positive and negative sentiment words spoken the customer in relation to identified contextual items are countered. 15. The computer program product of claim 9 , wherein the program instructions to analyze the stored voice data representing previous audible conversations with the customer and to simultaneously analyze at least a portion of the captured current audible conversation with the customer comprise program instructions to search combined voice data to identify customer's emotional states associated with the contextual item. | 0.656352 |
9,110,957 | 9 | 13 | 9. One or more computer storage memories, the memories being articles of manufacture, storing computer-executable instructions for executing, on a computer system, a computer process comprising: offloading data computation to a remote system in a business intelligence environment; receiving, via a user interface displaying data of a business intelligence document, a data mining assertion associated with the business intelligence document to identify relationships within the data, wherein the user interface displays the data of the business document in a tabular form comprising a plurality of cells displaying one or more data values and expressions disposed in a plurality of rows and columns, and wherein the data mining assertion is received in one or more cells of the plurality of cells, wherein the plurality of cells displayed in the user interface are capable of receiving the data mining assertion based on one or more user inputs, the business intelligence document specifying a directed acyclic graph connected of entities in a pipeline to produce a complex and arbitrary sequence of expressions designated for the computation; varying, via the user interface, the one or more data values and expressions of the one or more cells subject to the data mining assertion associated; solving the data mining assertion within a specified constraint based on the varying to identify individual data values that cause the data mining assertion received via the user interface to evaluate the data value and expressions variations available within the scope of the business intelligence document to iterate through the variations to determine the data and transformations that make the assertion true; presenting a solution of the solving in the user interface, the solution comprising a second plurality of cells displaying one or more data values or expressions disposed in the plurality of rows and columns; and receiving the data mining assertion by invoking an assertion mode on the row using a toolbar button or a menu item of the user interface associated with the business intelligence document, wherein the assertion mode provides a control on each cell of the row. | 9. One or more computer storage memories, the memories being articles of manufacture, storing computer-executable instructions for executing, on a computer system, a computer process comprising: offloading data computation to a remote system in a business intelligence environment; receiving, via a user interface displaying data of a business intelligence document, a data mining assertion associated with the business intelligence document to identify relationships within the data, wherein the user interface displays the data of the business document in a tabular form comprising a plurality of cells displaying one or more data values and expressions disposed in a plurality of rows and columns, and wherein the data mining assertion is received in one or more cells of the plurality of cells, wherein the plurality of cells displayed in the user interface are capable of receiving the data mining assertion based on one or more user inputs, the business intelligence document specifying a directed acyclic graph connected of entities in a pipeline to produce a complex and arbitrary sequence of expressions designated for the computation; varying, via the user interface, the one or more data values and expressions of the one or more cells subject to the data mining assertion associated; solving the data mining assertion within a specified constraint based on the varying to identify individual data values that cause the data mining assertion received via the user interface to evaluate the data value and expressions variations available within the scope of the business intelligence document to iterate through the variations to determine the data and transformations that make the assertion true; presenting a solution of the solving in the user interface, the solution comprising a second plurality of cells displaying one or more data values or expressions disposed in the plurality of rows and columns; and receiving the data mining assertion by invoking an assertion mode on the row using a toolbar button or a menu item of the user interface associated with the business intelligence document, wherein the assertion mode provides a control on each cell of the row. 13. The one or more computer storage memories of claim 9 wherein a constraint restricts the varying of at least one data value or at least one expression within a predetermined domain. | 0.674912 |
9,324,001 | 1 | 3 | 1. A character recognition device for use with a medium on which a character string is printed, the character recognition device comprising: an image reader structured to capture the character string on the medium as image data; an image memory structured to store the image which is read by said image reader; and a data processor structured to segment the character string from said image data stored in said image memory and segmenting characters from said character string for character recognition; wherein said data processor comprises: a character segmenting unit structured to detect boundary positions of neighboring characters in said character string and segment each character; and said character segmenting unit comprises: a boundary search range setting unit structured to set a range to search boundary position of neighboring characters in said character string and a boundary position setting unit structured to set a boundary position of characters by using a discriminant analysis method within said search range which has been set; and said boundary position setting unit is structured to divide a projection to said boundary search range by a predetermined width into two regions, calculate the within-region variance in each region, the between-region variance, and the variance ratio between the within-region variance and the between-region variance, and set a segmentation position of characters based on said calculated variance ratio. | 1. A character recognition device for use with a medium on which a character string is printed, the character recognition device comprising: an image reader structured to capture the character string on the medium as image data; an image memory structured to store the image which is read by said image reader; and a data processor structured to segment the character string from said image data stored in said image memory and segmenting characters from said character string for character recognition; wherein said data processor comprises: a character segmenting unit structured to detect boundary positions of neighboring characters in said character string and segment each character; and said character segmenting unit comprises: a boundary search range setting unit structured to set a range to search boundary position of neighboring characters in said character string and a boundary position setting unit structured to set a boundary position of characters by using a discriminant analysis method within said search range which has been set; and said boundary position setting unit is structured to divide a projection to said boundary search range by a predetermined width into two regions, calculate the within-region variance in each region, the between-region variance, and the variance ratio between the within-region variance and the between-region variance, and set a segmentation position of characters based on said calculated variance ratio. 3. The character recognition device as set forth in claim 1 , wherein said boundary search range setting unit sets said boundary search range from one end of said character string, and as a boundary position is set within said set boundary search range by said boundary position setting unit, a next boundary search range is set from said set boundary position; and said boundary position setting unit sets a boundary position for every boundary search range which is set sequentially. | 0.503074 |
9,098,473 | 1 | 7 | 1. A method for accessing an out-space user interface associated with an in-space user interface, comprising: displaying the in-space user interface, the in-space user interface comprising an in-space user interface area comprising in-space user interface elements and a document display area to display a document, wherein the in-space user interface area comprises a ribbon comprising ribbon tabs and authoring features for authoring the content of the document; displaying an out-space actuator with the in-space user interface; and in response to receiving a selection of the out-space actuator, removing at least a portion of the in-space user interface elements displayed in the in-space user interface area, removing the display of the document from the document display area, and displaying the out-space user interface within the document display area, the out-space user interface comprising out-space user interface elements that when selected do not affect the content of the document, and wherein the out-space user interface elements include non-authoring features associated with the document in the document display area. | 1. A method for accessing an out-space user interface associated with an in-space user interface, comprising: displaying the in-space user interface, the in-space user interface comprising an in-space user interface area comprising in-space user interface elements and a document display area to display a document, wherein the in-space user interface area comprises a ribbon comprising ribbon tabs and authoring features for authoring the content of the document; displaying an out-space actuator with the in-space user interface; and in response to receiving a selection of the out-space actuator, removing at least a portion of the in-space user interface elements displayed in the in-space user interface area, removing the display of the document from the document display area, and displaying the out-space user interface within the document display area, the out-space user interface comprising out-space user interface elements that when selected do not affect the content of the document, and wherein the out-space user interface elements include non-authoring features associated with the document in the document display area. 7. The method of claim 1 , wherein the out-space actuator is actuated in response to a single actuation. | 0.891667 |
8,768,707 | 1 | 10 | 1. A method comprising: receiving, by a computing device, an acoustic input signal at a speech recognizer; identifying, by the computing device, a user that is speaking based on the acoustic input signal; determining, by the computing device, speaker-specific information previously stored for the user; determining, by the computing device, a set of classifications, wherein the set of classifications are determined based on the speaker-specific information; classifying, by the computing device, portions of the acoustic input signal into different classifications in the set of classifications; selecting, by the computing device, a classification in the set of classifications based on a criterion associated with the classification; determining, by the computing device, a set of responses based on the recognized acoustic input signal, the classification, and the speaker-specific information for the user; determining, by the computing device, if the response should be output; and outputting, by the computing device, the response if it is determined the response should be output, wherein classifying portions is performed in an always on mode, and wherein identifying the user that is speaking is performed after receiving a trigger phrase to activate the speech recognizer. | 1. A method comprising: receiving, by a computing device, an acoustic input signal at a speech recognizer; identifying, by the computing device, a user that is speaking based on the acoustic input signal; determining, by the computing device, speaker-specific information previously stored for the user; determining, by the computing device, a set of classifications, wherein the set of classifications are determined based on the speaker-specific information; classifying, by the computing device, portions of the acoustic input signal into different classifications in the set of classifications; selecting, by the computing device, a classification in the set of classifications based on a criterion associated with the classification; determining, by the computing device, a set of responses based on the recognized acoustic input signal, the classification, and the speaker-specific information for the user; determining, by the computing device, if the response should be output; and outputting, by the computing device, the response if it is determined the response should be output, wherein classifying portions is performed in an always on mode, and wherein identifying the user that is speaking is performed after receiving a trigger phrase to activate the speech recognizer. 10. The method of claim 1 , wherein determining the set of responses comprises: determining user preferences in the speaker-specific information; and performing a search using the user preferences and the recognized acoustic input signal. | 0.674863 |
8,918,716 | 1 | 3 | 1. A computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to facilitate the application of context-based smart tags, the facilitating comprising: determining a type of a context object in a web page based on a context tag, comprising a start-tag and a matching end-tag, that surrounds the context object source code in the web page, the context tag defining the type of the context object; determining one or more context-specific actions that may be performed for the context object based on the context object type and a smart tag framework comprising: a type tag including a start-tag, a matching end-tag and a list of context object types, and a plurality of action tags, each action tag including a start-tag, a matching end-tag, a first parameter identifying one or more supported context object types and a second parameter identifying the name of an action class defining the action to be performed; receiving a selection from a user of the context object or a context indicator icon associated with, and displayed proximate to, the context object; providing the context-specific actions for the context object to the user; receiving a selection from the user of a context-specific action to be performed; and performing the selected context-specific action; wherein the smart tag framework is defined in one or more smart tag configuration files. | 1. A computer-readable medium having instructions stored thereon that, when executed by a processor, cause the processor to facilitate the application of context-based smart tags, the facilitating comprising: determining a type of a context object in a web page based on a context tag, comprising a start-tag and a matching end-tag, that surrounds the context object source code in the web page, the context tag defining the type of the context object; determining one or more context-specific actions that may be performed for the context object based on the context object type and a smart tag framework comprising: a type tag including a start-tag, a matching end-tag and a list of context object types, and a plurality of action tags, each action tag including a start-tag, a matching end-tag, a first parameter identifying one or more supported context object types and a second parameter identifying the name of an action class defining the action to be performed; receiving a selection from a user of the context object or a context indicator icon associated with, and displayed proximate to, the context object; providing the context-specific actions for the context object to the user; receiving a selection from the user of a context-specific action to be performed; and performing the selected context-specific action; wherein the smart tag framework is defined in one or more smart tag configuration files. 3. The computer-readable medium of claim 1 , wherein the selected action for the context object is performed based on an occurrence of an event detected by an action listener. | 0.763514 |
9,686,219 | 1 | 6 | 1. A method comprising: determining a message that is to be sent by a sender, wherein the sender is engaged in a plurality of active messaging conversations; identifying, in the message, a first key word that is related to a second key word found in another message, wherein the other message was sent in one of the plurality of conversations, wherein the first key word is identified as being related to the second key word, when the first key word and the second key word comprise a keyword pair, and wherein the key word pair is determined based at least on data from historical conversations; determining the message and the other message are both associated with the one of the plurality of conversations, wherein the determining comprises determining a relevance value corresponding to a degree of relevance of the message and the other message, wherein the relevance value is determined based at least on a quantity of key word pairs present in the message and the other message, a time interval between the message and the other message, and a probability associated with the keyword pair, and wherein the probability indicates a likelihood that a first message that includes the first key word is relevant to a second message that contains the second key word; determining the message is to be sent to at least one recipient, wherein the at least one recipient comprises a party participating in the one of the plurality of conversations; providing, to the sender, a suggestion to send the message to the at least one recipient, when the relevance value is less than a threshold value; and updating, based at least on the message being associated with the one of the plurality of conversations, the data from the historical conversations. | 1. A method comprising: determining a message that is to be sent by a sender, wherein the sender is engaged in a plurality of active messaging conversations; identifying, in the message, a first key word that is related to a second key word found in another message, wherein the other message was sent in one of the plurality of conversations, wherein the first key word is identified as being related to the second key word, when the first key word and the second key word comprise a keyword pair, and wherein the key word pair is determined based at least on data from historical conversations; determining the message and the other message are both associated with the one of the plurality of conversations, wherein the determining comprises determining a relevance value corresponding to a degree of relevance of the message and the other message, wherein the relevance value is determined based at least on a quantity of key word pairs present in the message and the other message, a time interval between the message and the other message, and a probability associated with the keyword pair, and wherein the probability indicates a likelihood that a first message that includes the first key word is relevant to a second message that contains the second key word; determining the message is to be sent to at least one recipient, wherein the at least one recipient comprises a party participating in the one of the plurality of conversations; providing, to the sender, a suggestion to send the message to the at least one recipient, when the relevance value is less than a threshold value; and updating, based at least on the message being associated with the one of the plurality of conversations, the data from the historical conversations. 6. The method of claim 1 , wherein the determining of the relevance value is further based at least on a temporal factor comprising a difference in time between the message and the other message. | 0.701835 |
8,335,683 | 4 | 6 | 4. The text classifier of claim 1 and further comprising: a pre-processor identifying words in the textual input having semantic content. | 4. The text classifier of claim 1 and further comprising: a pre-processor identifying words in the textual input having semantic content. 6. The text classifier of claim 4 wherein the preprocessor is configured to insert tags for words in the textual input, the tags being semantic labels for the words. | 0.5 |
7,647,415 | 11 | 12 | 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). 12. The system as recited in claim 11 , wherein the system is a JAX-RPC (Java API for XML (eXtensible Markup Language)-based RPC (Remote Procedure Call)) client. | 0.816629 |
9,720,907 | 9 | 10 | 9. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: analyzing a first natural language corpus to generate a latent representation for words in the first natural language corpus; calculating, for each word in the latent representation, a Euclidian distance between a left context of the each word and a right context of the each word, to yield a centroid of latent vectors for each word in the latent representation; analyzing a second natural language corpus having a target word, the target word being a word that is not in the first natural language corpus; and predicting a label for the target word based on the latent representation and the centroid of latent vectors for each word in the latent representation. | 9. A system comprising: a processor; and a computer-readable storage medium having instructions stored which, when executed by the processor, cause the processor to perform operations comprising: analyzing a first natural language corpus to generate a latent representation for words in the first natural language corpus; calculating, for each word in the latent representation, a Euclidian distance between a left context of the each word and a right context of the each word, to yield a centroid of latent vectors for each word in the latent representation; analyzing a second natural language corpus having a target word, the target word being a word that is not in the first natural language corpus; and predicting a label for the target word based on the latent representation and the centroid of latent vectors for each word in the latent representation. 10. The system of claim 9 , wherein the target word is one of a rare word and a word not encountered in the first natural language corpus. | 0.705128 |
8,032,860 | 34 | 35 | 34. The system of claim 33 , wherein after the compiler framework is notified of a change to a file, the information about the file is updated within a time limit for a single-file recompile. | 34. The system of claim 33 , wherein after the compiler framework is notified of a change to a file, the information about the file is updated within a time limit for a single-file recompile. 35. The system of claim 34 , wherein after the file is recompiled, the compiler framework provides the source code editor with a list of changes that occurred to the file information. | 0.5 |
5,486,111 | 2 | 5 | 2. A language translation teaching aid as in claim 1 wherein the first, second, third, and fourth presentations comprise printed words. | 2. A language translation teaching aid as in claim 1 wherein the first, second, third, and fourth presentations comprise printed words. 5. A language translation teaching aid as in claim 2 wherein: (a) the first and second presentations are arranged in a first volume; (b) the third and fourth presentations are arranged in a second volume; and (c) the arrangement of the first and second presentations in the first volume corresponds to the arrangement of corresponding third and fourth presentations in the second volume. | 0.529197 |
9,842,308 | 28 | 29 | 28. The system of claim 24 further comprising: means for establishing a hierarchy of said rules set. | 28. The system of claim 24 further comprising: means for establishing a hierarchy of said rules set. 29. The system of claim 28 wherein at least a portion of said hierarchy is automatically established by said means for analyzing said plurality of shipping processing rules to define said rules set. | 0.5 |
9,812,120 | 7 | 8 | 7. A non-transitory computer readable storage medium that stores a speech synthesis program, which when executed by a computer, causes the computer to function as: a receiver that receives an e-mail as a text content item; a content selection unit that selects the text content item to be converted into speech based on a vocal command from a user in which the user commands that the received e-mail be read aloud; a related information selection unit that selects related information which can be at least converted into text and which is related to the text content item selected by the content selection unit, wherein the related information includes at least identification of a sender of the e-mail, and wherein when the name of the sender is locally stored in association with an e-mail address of the sender prior to receipt of the e-mail, the name of the sender is used as the identification of the sender, and when the name of the sender is not locally stored in association with an e-mail address of the sender prior to receipt of the e-mail, the e-mail address is used as the identification of the sender; a data addition unit that converts the related information selected by the related information selection unit into text by inserting the related information into a predetermined type of phrase to form a text phrase, and adds text data of the text phrase to text data of the text content item selected by the content selection unit, wherein the predetermined type of phrase includes at least one predetermined location within the phrase at which the identification of the sender of the e-mail is inserted; a text-to-speech conversion unit that converts text data supplied from the data addition unit into a speech signal; and a speech output unit that outputs the speech signal supplied from the text-to-speech conversion unit. | 7. A non-transitory computer readable storage medium that stores a speech synthesis program, which when executed by a computer, causes the computer to function as: a receiver that receives an e-mail as a text content item; a content selection unit that selects the text content item to be converted into speech based on a vocal command from a user in which the user commands that the received e-mail be read aloud; a related information selection unit that selects related information which can be at least converted into text and which is related to the text content item selected by the content selection unit, wherein the related information includes at least identification of a sender of the e-mail, and wherein when the name of the sender is locally stored in association with an e-mail address of the sender prior to receipt of the e-mail, the name of the sender is used as the identification of the sender, and when the name of the sender is not locally stored in association with an e-mail address of the sender prior to receipt of the e-mail, the e-mail address is used as the identification of the sender; a data addition unit that converts the related information selected by the related information selection unit into text by inserting the related information into a predetermined type of phrase to form a text phrase, and adds text data of the text phrase to text data of the text content item selected by the content selection unit, wherein the predetermined type of phrase includes at least one predetermined location within the phrase at which the identification of the sender of the e-mail is inserted; a text-to-speech conversion unit that converts text data supplied from the data addition unit into a speech signal; and a speech output unit that outputs the speech signal supplied from the text-to-speech conversion unit. 8. The non-transitory computer readable storage medium according to claim 7 , wherein the related information selection unit selects music data related to the selected text content item, and the speech output unit mixes the speech signal supplied from the text-to-speech conversion unit and a music signal of the music data and outputs a resulting signal. | 0.5 |
10,014,076 | 3 | 12 | 3. The baggage system of claim 2 , where the server is further configured to: receive plurality of input attributes of the present event; performing pre-processing on the plurality of input attributes to generate an input data set; generating the output value from the trained model based upon the input data set; and predict an outcome associated with the present event based upon the output value. | 3. The baggage system of claim 2 , where the server is further configured to: receive plurality of input attributes of the present event; performing pre-processing on the plurality of input attributes to generate an input data set; generating the output value from the trained model based upon the input data set; and predict an outcome associated with the present event based upon the output value. 12. The baggage system of claim 3 , wherein the present event is a baggage item registering with the DCE and the output value is an indication of deviation or no deviation for the present event. | 0.744737 |
8,793,285 | 6 | 10 | 6. A computer implemented method for generating at least one multidimensional tag, the method comprising: defining at least one tag core corresponding to web content, wherein the at least one tag core comprises an effective semantic label identifying the web content; a computer, recording a plurality of predetermined tag dimensions and one or more predetermined measures associated with the at least one tag, wherein the plurality of predetermined tag dimensions comprise parameters of metrics describing evolution of the web content and the one or more predetermined measures comprise parameters of metrics describing consumption of the web content; the computer, assembling the at least one tag core with the corresponding recorded plurality of predetermined tag dimensions and the one or more predetermined measures to generate the at least one multidimensional tag; and updating the at least one multidimensional tag by recording latest at least one predetermined tag dimension and latest predetermined measure when the web content associated with the at least one multidimensional tag is consumed. | 6. A computer implemented method for generating at least one multidimensional tag, the method comprising: defining at least one tag core corresponding to web content, wherein the at least one tag core comprises an effective semantic label identifying the web content; a computer, recording a plurality of predetermined tag dimensions and one or more predetermined measures associated with the at least one tag, wherein the plurality of predetermined tag dimensions comprise parameters of metrics describing evolution of the web content and the one or more predetermined measures comprise parameters of metrics describing consumption of the web content; the computer, assembling the at least one tag core with the corresponding recorded plurality of predetermined tag dimensions and the one or more predetermined measures to generate the at least one multidimensional tag; and updating the at least one multidimensional tag by recording latest at least one predetermined tag dimension and latest predetermined measure when the web content associated with the at least one multidimensional tag is consumed. 10. The computerized method of claim 6 , wherein the recorded one or more predetermined measures and the associated plurality of predetermined tag dimensions are stored in a tag fact table in a predetermined structured format. | 0.817447 |
8,744,838 | 1 | 8 | 1. A method for contextualizing operating procedures, comprising: receiving a set of procedures, each procedure including text describing user actions which are to be performed on a physical device to implement the procedure; providing a model of the device which refers to a set of components of the physical device on which user actions are performable, for each of the components in the set, the device model providing a state chart which links an action performable on the component with states assumed by the component before and after the action is performed; for each procedure in the set, segmenting the text into a sequence of instruction steps, each instruction step including an action to be performed on one of the components of the device that is referred to in the device model, the segmenting of the text including natural language processing the text to identify action verbs and their objects in the text, and where an object of the action verb refers to a component in the device model, tagging the object with the referenced component; receiving a request for one of the procedures; retrieving the sequence of instruction steps for the requested procedure; receiving device data from the physical device; for each of a plurality of the instruction steps in the retrieved sequence, contextualizing a current one of the instruction steps, based on the device data and the state chart of the respective component referred to in the device model; and outputting a representation of the contextualized instruction step to a display device. | 1. A method for contextualizing operating procedures, comprising: receiving a set of procedures, each procedure including text describing user actions which are to be performed on a physical device to implement the procedure; providing a model of the device which refers to a set of components of the physical device on which user actions are performable, for each of the components in the set, the device model providing a state chart which links an action performable on the component with states assumed by the component before and after the action is performed; for each procedure in the set, segmenting the text into a sequence of instruction steps, each instruction step including an action to be performed on one of the components of the device that is referred to in the device model, the segmenting of the text including natural language processing the text to identify action verbs and their objects in the text, and where an object of the action verb refers to a component in the device model, tagging the object with the referenced component; receiving a request for one of the procedures; retrieving the sequence of instruction steps for the requested procedure; receiving device data from the physical device; for each of a plurality of the instruction steps in the retrieved sequence, contextualizing a current one of the instruction steps, based on the device data and the state chart of the respective component referred to in the device model; and outputting a representation of the contextualized instruction step to a display device. 8. The method of claim 1 , wherein the outputting of the representation of the contextualized procedure includes, for each of a plurality of instruction steps in the sequence of instructions, outputting a textual description of a current instruction step to the display device. | 0.536789 |
6,023,675 | 10 | 11 | 10. A method utilized during a testimonial proceeding using a remote system, a plurality of terminals coupled to the remote system, and a transcription system, the method comprising: converting, using the transcription system at a first premises, representations of spoken words to text in real time; delivering the text in real time to the remote system, the remote system being disposed at a second premises; delivering, by the remote system, at least portions of the text in real time to the plurality of terminals, the plurality of terminals being disposed at at least one premises other than the first or second premises; and displaying at the plurality of terminals the delivered text for real time review. | 10. A method utilized during a testimonial proceeding using a remote system, a plurality of terminals coupled to the remote system, and a transcription system, the method comprising: converting, using the transcription system at a first premises, representations of spoken words to text in real time; delivering the text in real time to the remote system, the remote system being disposed at a second premises; delivering, by the remote system, at least portions of the text in real time to the plurality of terminals, the plurality of terminals being disposed at at least one premises other than the first or second premises; and displaying at the plurality of terminals the delivered text for real time review. 11. The method of claim 10 further comprising: capturing audio corresponding to the spoken words; and associating the captured audio with the text. | 0.702429 |
7,970,601 | 2 | 3 | 2. The method according to claim 1 , further comprising assigning the text segments to classes of a stored requirement metamodel. | 2. The method according to claim 1 , further comprising assigning the text segments to classes of a stored requirement metamodel. 3. The method according to claim 2 , wherein for every text segment that is selected, an instance of the requirement metamodel is complemented by an instance of the requirement metamodel class linked to the text segment. | 0.5 |
9,135,912 | 9 | 10 | 9. 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, from among a set of query terms, a particular query term that (i) does not occur in a lexicon of terms, and (ii) has no designated, canonical phonetic representation in a pronunciation phonetic dictionary, wherein a canonical phonetic representation comprises a sequence of phonemes; generating a phonetic representation estimate for the particular query term that (i) does not occur in the lexicon of terms, and (ii) has no designated, canonical phonetic representation in the pronunciation phonetic dictionary; transmitting data identifying at least a portion of a term that does occur in the lexicon of terms and the particular query term to a spelling correction server; receiving, from the spelling correction server, data that specifies a spelling correction confidence score, wherein the spelling correction confidence score reflects a probability that the term that does occur in the lexicon of terms is a correct spelling of the particular query term; determining that the spelling correction confidence score satisfies a predetermined threshold; and in response to determining that the spelling correction confidence score satisfies a predetermined threshold, designating, by one or more computing devices, the phonetic representation estimate for the particular query term as a canonical phonetic representation, in the phonetic dictionary, of the term that does occur in the lexicon of terms. | 9. 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, from among a set of query terms, a particular query term that (i) does not occur in a lexicon of terms, and (ii) has no designated, canonical phonetic representation in a pronunciation phonetic dictionary, wherein a canonical phonetic representation comprises a sequence of phonemes; generating a phonetic representation estimate for the particular query term that (i) does not occur in the lexicon of terms, and (ii) has no designated, canonical phonetic representation in the pronunciation phonetic dictionary; transmitting data identifying at least a portion of a term that does occur in the lexicon of terms and the particular query term to a spelling correction server; receiving, from the spelling correction server, data that specifies a spelling correction confidence score, wherein the spelling correction confidence score reflects a probability that the term that does occur in the lexicon of terms is a correct spelling of the particular query term; determining that the spelling correction confidence score satisfies a predetermined threshold; and in response to determining that the spelling correction confidence score satisfies a predetermined threshold, designating, by one or more computing devices, the phonetic representation estimate for the particular query term as a canonical phonetic representation, in the phonetic dictionary, of the term that does occur in the lexicon of terms. 10. The system of claim 9 , wherein generating a phonetic representation estimate for the particular query term that (i) does not occur in the lexicon of terms, and (ii) has no designated, canonical phonetic representation in the phonetic pronunciation dictionary, comprises: estimating a pronunciation of the particular query term based on one or more phonic rules for graphemes included in the particular query term. | 0.688988 |
9,378,649 | 6 | 7 | 6. An apparatus configured to display digital document data with partial text data therein replaced with mask data, the apparatus comprising: a processor; and a non-transitory computer readable storage medium comprising modules executable by the processor, wherein the non-transitory computer readable storage medium comprises: a data acquisition module configured to acquire the digital document data; a designation acceptance module configured to accept designation of an instance of the partial text data to be replaced, the partial text data located within the digital document data; a replaced document data generating module configured to generate replacement document data that comprises a copy of the digital document data in which the instance of the partial text data is replaced with an identification information corresponding to said instance of the partial text data; a replaced document data storage unit configured to store a replaced document data, which comprises the replacement document data and an identification of a region of the replacement document data that includes the identification information corresponding to the instance of the partial text data, wherein the replacement document data comprises more than one region; a selection acceptance module configured to accept selection of a rule information piece from a plurality of rule information pieces, which comprises a replacement information that associates the identification information with a mask pattern, the rule information piece corresponding to said instance of the partial text data; and a replacing module configured to replace, based on the replacement information, the identification information of the instance of the partial text data included in the replaced document data with the mask pattern. | 6. An apparatus configured to display digital document data with partial text data therein replaced with mask data, the apparatus comprising: a processor; and a non-transitory computer readable storage medium comprising modules executable by the processor, wherein the non-transitory computer readable storage medium comprises: a data acquisition module configured to acquire the digital document data; a designation acceptance module configured to accept designation of an instance of the partial text data to be replaced, the partial text data located within the digital document data; a replaced document data generating module configured to generate replacement document data that comprises a copy of the digital document data in which the instance of the partial text data is replaced with an identification information corresponding to said instance of the partial text data; a replaced document data storage unit configured to store a replaced document data, which comprises the replacement document data and an identification of a region of the replacement document data that includes the identification information corresponding to the instance of the partial text data, wherein the replacement document data comprises more than one region; a selection acceptance module configured to accept selection of a rule information piece from a plurality of rule information pieces, which comprises a replacement information that associates the identification information with a mask pattern, the rule information piece corresponding to said instance of the partial text data; and a replacing module configured to replace, based on the replacement information, the identification information of the instance of the partial text data included in the replaced document data with the mask pattern. 7. The apparatus according to claim 6 , wherein the selection acceptance module is further configured to accept selection of two or more of the plurality of rule information pieces, each corresponding to separate instances of the partial text data. | 0.805031 |
9,542,066 | 10 | 11 | 10. The method of claim 9 where the displayed proximity over time is related to window content similarity. | 10. The method of claim 9 where the displayed proximity over time is related to window content similarity. 11. The method of claim 10 where stop words in the window content are not considered in the grouping. | 0.656463 |
8,375,008 | 1 | 8 | 1. A method, performed by a computer system, for managing information associated with an enterprise, the method comprising the steps of: obtaining original data from a plurality of different electronic data sources including at least two electronic data sources including a backup tape data source and a networked data source, wherein the original data includes a plurality of files having content portions and metadata portions; determining email files within the original data; extracting information from the email files using an email extraction engine; forwarding the information extracted from the email files to a de-duplication engine; separating the information extracted from the email files and other original data in content portions and metadata portions; analyzing the content portions and the metadata portions by hashing the content portions of the information extracted and the other original data to form hashed values using a de-duplication engine and comparing the hashed values using the de-duplication engine; placing, into a collective database, at least a single copy of unique content portions; and placing, into a collective database, at least one copy of the metadata portions including information on where the files were obtained; from a user of the computer system, receiving at least one rule, including: a retention policy for the data; and a query for the data, wherein the query is other than a search for duplicate portions of the data; using the rule, which includes a logical operation to segregate the targeted data and the compliant data from other data, identifying: compliant data that comply with the retention policy; and targeted data that correspond to the query; and using the rule, preserving the compliant data and the targeted data within the collective database, while deleting at least a portion of other data that are neither compliant data nor targeted data within the collective database. | 1. A method, performed by a computer system, for managing information associated with an enterprise, the method comprising the steps of: obtaining original data from a plurality of different electronic data sources including at least two electronic data sources including a backup tape data source and a networked data source, wherein the original data includes a plurality of files having content portions and metadata portions; determining email files within the original data; extracting information from the email files using an email extraction engine; forwarding the information extracted from the email files to a de-duplication engine; separating the information extracted from the email files and other original data in content portions and metadata portions; analyzing the content portions and the metadata portions by hashing the content portions of the information extracted and the other original data to form hashed values using a de-duplication engine and comparing the hashed values using the de-duplication engine; placing, into a collective database, at least a single copy of unique content portions; and placing, into a collective database, at least one copy of the metadata portions including information on where the files were obtained; from a user of the computer system, receiving at least one rule, including: a retention policy for the data; and a query for the data, wherein the query is other than a search for duplicate portions of the data; using the rule, which includes a logical operation to segregate the targeted data and the compliant data from other data, identifying: compliant data that comply with the retention policy; and targeted data that correspond to the query; and using the rule, preserving the compliant data and the targeted data within the collective database, while deleting at least a portion of other data that are neither compliant data nor targeted data within the collective database. 8. The method of claim 1 , wherein the query for the data includes a query of at least one of the following for the data: subject matter, author, type, and content. | 0.84381 |
8,644,488 | 13 | 14 | 13. A system for automatically generating a customer interaction log for an interaction between a customer and agent at a contact center comprising: at least one processing unit for executing components; a receiving component for receiving input comprising at least one spoken utterance from the customer and the agent; a call transcript component for processing received input and generating a call transcript; an analysis component for automatically analyzing the received input comprising analyzing at least said call transcript and, based on results of the analyzing, selecting at least a portion of the received input to generate a customer interaction log using at least one model; a display generation component for generating a display of said customer interaction log for agent review at a graphical user interface of an agent computer; a feedback collection component for receiving agent feedback to the displayed generated customer interaction log; and at least one learning component for analyzing agent feedback to determine updating of the customer interaction log and said at least one model based on agent feedback. | 13. A system for automatically generating a customer interaction log for an interaction between a customer and agent at a contact center comprising: at least one processing unit for executing components; a receiving component for receiving input comprising at least one spoken utterance from the customer and the agent; a call transcript component for processing received input and generating a call transcript; an analysis component for automatically analyzing the received input comprising analyzing at least said call transcript and, based on results of the analyzing, selecting at least a portion of the received input to generate a customer interaction log using at least one model; a display generation component for generating a display of said customer interaction log for agent review at a graphical user interface of an agent computer; a feedback collection component for receiving agent feedback to the displayed generated customer interaction log; and at least one learning component for analyzing agent feedback to determine updating of the customer interaction log and said at least one model based on agent feedback. 14. The system of claim 13 further comprising a text normalizing component for transforming received input comprising at least one of: a disfluency component removing disfluencies from the received text; a vocabulary normalizing component for normalizing vocabulary in said received text; a character normalizing component for normalizing alphanumeric characters in said received text; a word correction component for correcting misspellings or incorrectly recognized words in said received text; a sentence detection component for detecting sentence boundaries in said received text; a sentence capitalization component for capitalizing letters in sentences in said received text; and a call segment component for detecting call segment boundaries in said received text. | 0.5 |
9,875,740 | 16 | 17 | 16. A method comprising: receiving a first search request, the first search request associated with first audio input data from a device; identifying a first search query from the first search request; identifying a set of categories associated with the first search query, the set of categories including two or more categories, each of the two or more categories being ranked according to respective relevance scores to the first search query; identifying a first set of results associated with a first category, the first category having a highest relevance score to the first search query; causing the first set of results to be transmitted to the device, the first set of results being presented to the user of the device; receiving a second search request, the second search request associated with second audio input data from the device; analyzing the second search request for indicators that an incorrect category was presented; determining the second search request includes one or more of the indicators that the incorrect category was presented; and decreasing the relevance score of the first category for the first search query when a voice volume difference is determined to be above a volume difference threshold; identifying a second category of the set of categories associated with the first search query; and increasing the relevance score of the second category for the first search query when the voice volume difference is determined to be below the volume difference threshold. | 16. A method comprising: receiving a first search request, the first search request associated with first audio input data from a device; identifying a first search query from the first search request; identifying a set of categories associated with the first search query, the set of categories including two or more categories, each of the two or more categories being ranked according to respective relevance scores to the first search query; identifying a first set of results associated with a first category, the first category having a highest relevance score to the first search query; causing the first set of results to be transmitted to the device, the first set of results being presented to the user of the device; receiving a second search request, the second search request associated with second audio input data from the device; analyzing the second search request for indicators that an incorrect category was presented; determining the second search request includes one or more of the indicators that the incorrect category was presented; and decreasing the relevance score of the first category for the first search query when a voice volume difference is determined to be above a volume difference threshold; identifying a second category of the set of categories associated with the first search query; and increasing the relevance score of the second category for the first search query when the voice volume difference is determined to be below the volume difference threshold. 17. The method of claim 16 , further comprising: identifying a second category from the set of categories, the second category having a second highest relevance score to the first search query; identifying a second set of results associated with the second category; and causing the second set of results to be transmitted to the device, the second set of results being presented to the user of the device. | 0.595618 |
9,292,766 | 2 | 3 | 2. An apparatus for geo-locating a query ground level photo of an unknown location from combined elevation data and satellite imagery, the apparatus comprising: a memory; and at least one processor device, coupled to the memory, operative to: (a) parse the query ground level photo into one or more semantic regions; (b) assign semantic labels to the semantic regions; (c) use cross-modality semantic classifiers to identify geo-spatial regions in the combined elevation data and satellite imagery that have at least one semantic classifier in common with the query ground level photo; and (d) perform matches of the query ground level photo with the combined elevation data and satellite imagery for each of the geo-spatial regions identified in step (c). | 2. An apparatus for geo-locating a query ground level photo of an unknown location from combined elevation data and satellite imagery, the apparatus comprising: a memory; and at least one processor device, coupled to the memory, operative to: (a) parse the query ground level photo into one or more semantic regions; (b) assign semantic labels to the semantic regions; (c) use cross-modality semantic classifiers to identify geo-spatial regions in the combined elevation data and satellite imagery that have at least one semantic classifier in common with the query ground level photo; and (d) perform matches of the query ground level photo with the combined elevation data and satellite imagery for each of the geo-spatial regions identified in step (c). 3. The apparatus of claim 2 , wherein IMARS-based semantic classifiers are used to label the semantic regions. | 0.920977 |
8,615,389 | 10 | 14 | 10. A system comprising: a processor configured to generate a language model based on a training corpus using an approximate hashing technique, 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; and a memory configured to store the language model. | 10. A system comprising: a processor configured to generate a language model based on a training corpus using an approximate hashing technique, 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; and a memory configured to store the language model. 14. The system of claim 10 , wherein the size of the language model is less than six hundred fifty megabytes for a portion of a training corpus comprising ten million sentences. | 0.586449 |
9,064,489 | 17 | 19 | 17. The computer-implemented method of claim 6 , further comprising determining a level of compression to apply to the first compressed portion based at least in part on a linguistic feature of a text corresponding to the portion. | 17. The computer-implemented method of claim 6 , further comprising determining a level of compression to apply to the first compressed portion based at least in part on a linguistic feature of a text corresponding to the portion. 19. The computer-implemented method of claim 17 wherein the acoustic feature comprises an indication of a phoneme class, wherein the phoneme class is one of a voiced phoneme, an unvoiced phoneme, a plosive, a vowel, a consonant, a liquid, or a fricative. | 0.5 |
9,223,647 | 18 | 19 | 18. The system of claim 13 , wherein the at least one action comprises a second action classified as irrelevant, and wherein the second action is reclassified in response to the failure of the first action. | 18. The system of claim 13 , wherein the at least one action comprises a second action classified as irrelevant, and wherein the second action is reclassified in response to the failure of the first action. 19. The system of claim 18 , wherein the at least one action further comprises a third action classified as relevant, and wherein the third action is reclassified as irrelevant in response to the failure of the first action. | 0.5 |
7,668,787 | 20 | 21 | 20. The computer program product of claim 19 , wherein said entity/relationship object includes a reference to said electronic document. | 20. The computer program product of claim 19 , wherein said entity/relationship object includes a reference to said electronic document. 21. The computer program product of claim 20 , wherein said relationship data structure further comprises a second composite object and further comprising: adding said entity/relationship object to said second composite object; and storing said reference to said electronic document from said entity/relationship object in said second composite object. | 0.588785 |
8,356,030 | 27 | 29 | 27. The computer program product of claim 22 , wherein the classifier module is further configured to: build a model having n-grams of the domain-specific sentiment lexicon as features; and train the model on a training corpus having domain-specific documents having manually-labeled sentiment scores. | 27. The computer program product of claim 22 , wherein the classifier module is further configured to: build a model having n-grams of the domain-specific sentiment lexicon as features; and train the model on a training corpus having domain-specific documents having manually-labeled sentiment scores. 29. The computer program product of claim 27 , wherein the training generates sentiment scores for the n-grams of the domain-specific sentiment lexicon and wherein the storing module is further configured to: store the sentiment scores for the n-grams of the domain-specific sentiment lexicon with the domain-specific sentiment lexicon. | 0.5 |
9,690,768 | 1 | 5 | 1. A method for annotating a video, comprising: displaying by a computer on a device a video player graphical user interface, the user interface including a display area for presenting a video and associated control buttons, the video including a plurality of annotated intervals; displaying, by the computer, a timeline associated with the video; displaying, by the computer in the display area, a frame of the video ; receiving, by the computer, a user selection of a region of the displayed frame; responsive to receiving the selection of the region, displaying, by the computer in the displayed frame, an annotation definition image indicating the selected region; receiving, by the computer, a user selection of a control button to create an annotation; providing, by the computer, a display area for receiving user input of annotation content; receiving, by the computer in the display area, user input of annotation content; associating the received annotation content with the displayed frame of the video and the selected region to generate an annotated video frame; ranking the plurality of annotated intervals based on a number of annotations associated with each annotated interval; indicating on the timeline a marker associated with the annotated video frame; while displaying the timeline, displaying an annotated thumbnail associated with the annotated video frame in the user interface responsive to a user interaction with the marker; and displaying indications of ranked orders with markers associated with each of the annotated intervals on the timeline. | 1. A method for annotating a video, comprising: displaying by a computer on a device a video player graphical user interface, the user interface including a display area for presenting a video and associated control buttons, the video including a plurality of annotated intervals; displaying, by the computer, a timeline associated with the video; displaying, by the computer in the display area, a frame of the video ; receiving, by the computer, a user selection of a region of the displayed frame; responsive to receiving the selection of the region, displaying, by the computer in the displayed frame, an annotation definition image indicating the selected region; receiving, by the computer, a user selection of a control button to create an annotation; providing, by the computer, a display area for receiving user input of annotation content; receiving, by the computer in the display area, user input of annotation content; associating the received annotation content with the displayed frame of the video and the selected region to generate an annotated video frame; ranking the plurality of annotated intervals based on a number of annotations associated with each annotated interval; indicating on the timeline a marker associated with the annotated video frame; while displaying the timeline, displaying an annotated thumbnail associated with the annotated video frame in the user interface responsive to a user interaction with the marker; and displaying indications of ranked orders with markers associated with each of the annotated intervals on the timeline. 5. The method of claim 1 , wherein displaying the frame of the video further comprises: playing the video in the user interface; receiving, during playback of the video, user selection of a control button; ceasing playback of the video; selecting a frame of the video responsive to a portion of the video being played back at the time of receiving the user selection; and displaying the selected frame in the user interface. | 0.5 |
8,401,854 | 12 | 13 | 12. The method of claim 1 further comprising providing the fragments in a tree like structure. | 12. The method of claim 1 further comprising providing the fragments in a tree like structure. 13. The method of claim 12 further comprising adding the scores for the different fragments building the list of entries on the basis of the tree like structure of the fragments. | 0.5 |
8,661,332 | 1 | 2 | 1. A hardware system comprising: one or more computer-readable media; software instructions resident on the media which, when executed, are capable of enabling the hardware system to represent a document with a markup representation, wherein the document comprises part of a package that contains multiple payloads, each payload acting as a different representation of the document, the markup representation comprising: a first element that controls how an application reacts to an unknown attribute; a second element that declares that an associated namespace is ignorable; a third element that specifies behavior for ignorable content; a fourth element that reverses the effect of a namespace declared ignorable; a fifth element that specifies content that may be substituted for preferred content if the preferred content is unknown and the preferred content is associated with a namespace requiring that items must be understood; and a sixth element that specifies to document editing tools whether individual attributes in an ignorable namespace should be preserved when the document is modified. | 1. A hardware system comprising: one or more computer-readable media; software instructions resident on the media which, when executed, are capable of enabling the hardware system to represent a document with a markup representation, wherein the document comprises part of a package that contains multiple payloads, each payload acting as a different representation of the document, the markup representation comprising: a first element that controls how an application reacts to an unknown attribute; a second element that declares that an associated namespace is ignorable; a third element that specifies behavior for ignorable content; a fourth element that reverses the effect of a namespace declared ignorable; a fifth element that specifies content that may be substituted for preferred content if the preferred content is unknown and the preferred content is associated with a namespace requiring that items must be understood; and a sixth element that specifies to document editing tools whether individual attributes in an ignorable namespace should be preserved when the document is modified. 2. The system of claim 1 , wherein the markup representation is an XML markup representation. | 0.766332 |
8,296,142 | 6 | 17 | 6. A computer-implemented method, comprising: accessing audio data that includes encoded speech; accessing information that indicates a docking context of a client device, the docking context being associated with the audio data; identifying a plurality of language models; determining, for each of the plurality of language models, a weighting value based on the docking context, the weighting value indicating a probability that the language model will indicate a correct transcription for the encoded speech; selecting at least one of the plurality of language models based on the weighting values; and performing speech recognition on the audio data using the selected at least one language model to identify a transcription for a portion of the audio data. | 6. A computer-implemented method, comprising: accessing audio data that includes encoded speech; accessing information that indicates a docking context of a client device, the docking context being associated with the audio data; identifying a plurality of language models; determining, for each of the plurality of language models, a weighting value based on the docking context, the weighting value indicating a probability that the language model will indicate a correct transcription for the encoded speech; selecting at least one of the plurality of language models based on the weighting values; and performing speech recognition on the audio data using the selected at least one language model to identify a transcription for a portion of the audio data. 17. The computer-implemented method of claim 6 , wherein determining, for each of the plurality of language models, the weighting value based on the docking context comprises: determining the weighting value for each language model before using the language model to identify a transcription for the audio data. | 0.726232 |
8,275,602 | 1 | 5 | 1. A method for providing text-based dialogue between communicants in a portable environment, the method comprising: selecting a first dialogue language for a first communicant using a first text-based input communication device; selecting a second dialogue language for a second communicant using a second text-based input communication device; entering text-based communication data from the first communicant using the first text-based input communication device in the first dialogue language, wherein the text-based communication data from the first communicant is displayed on a first communicant display; entering text-based communication data from the second communicant using the second text-based input communication device in the second dialogue language, wherein the text-based communication data from the second communicant is displayed on a second communicant display; transmitting a copy of the text-based communication data from the first communicant to the second communicant while the text-based communication data is entered by the first communicant; receiving the text-based communication data from the first communicant by the second communicant; transmitting a copy of the text-based communication data from the second communicant to the first communicant while the text-based communication data is entered by the second communicant; receiving the text-based communication data from the second communicant by the first communicant; displaying the received text-based communication data from the first communicant on the second communicant display; and displaying the received text-based communication data from the second communicant on the first communicant display, wherein the first text-based input communication device and the first communicant display are comprised in a first communicant system, and wherein the second text-based input communication device and the second communicant display are comprised in a second communicant system separate from the first communicant system. | 1. A method for providing text-based dialogue between communicants in a portable environment, the method comprising: selecting a first dialogue language for a first communicant using a first text-based input communication device; selecting a second dialogue language for a second communicant using a second text-based input communication device; entering text-based communication data from the first communicant using the first text-based input communication device in the first dialogue language, wherein the text-based communication data from the first communicant is displayed on a first communicant display; entering text-based communication data from the second communicant using the second text-based input communication device in the second dialogue language, wherein the text-based communication data from the second communicant is displayed on a second communicant display; transmitting a copy of the text-based communication data from the first communicant to the second communicant while the text-based communication data is entered by the first communicant; receiving the text-based communication data from the first communicant by the second communicant; transmitting a copy of the text-based communication data from the second communicant to the first communicant while the text-based communication data is entered by the second communicant; receiving the text-based communication data from the second communicant by the first communicant; displaying the received text-based communication data from the first communicant on the second communicant display; and displaying the received text-based communication data from the second communicant on the first communicant display, wherein the first text-based input communication device and the first communicant display are comprised in a first communicant system, and wherein the second text-based input communication device and the second communicant display are comprised in a second communicant system separate from the first communicant system. 5. The method for providing text-based dialogue of claim 1 , wherein the steps of displaying the text-based communication data from the first communicant and displaying the text-based communication data from the second communicant include displaying the text-based communication data text in dialogue boxes arranged in a split side-by-side or a split top-bottom configuration on the first communicant display and on the second communicant display. | 0.765969 |
9,905,228 | 15 | 16 | 15. The system of claim 13 , wherein the computer-readable storage medium stores additional instructions which, when executed by the processor, cause the processor to perform operations further comprising: identifying a location of the system. | 15. The system of claim 13 , wherein the computer-readable storage medium stores additional instructions which, when executed by the processor, cause the processor to perform operations further comprising: identifying a location of the system. 16. The system of claim 15 , wherein the computer-readable storage medium stores additional instructions which, when executed by the processor, cause the processor to perform operations further comprising: determining a privacy level of the private user data according to the location of the system. | 0.5 |
8,717,367 | 23 | 24 | 23. The method of claim 1 , wherein one or more of the one or more selected design animation modules comprise one or more digital visual media item placeholders; wherein each placeholder of the one or more digital visual media item placeholders accepts a range of digital visual media items; wherein the one or more selected design animation modules that comprise the digital visual media item placeholders are associated with one or more particular metadata values, each particular metadata value of the one or more particular metadata values corresponding to one digital visual media item placeholder of the one or more digital visual media item placeholders; wherein each particular metadata value of the one or more particular metadata values indicates a range of digital visual media items that the corresponding digital visual media item placeholder accepts. | 23. The method of claim 1 , wherein one or more of the one or more selected design animation modules comprise one or more digital visual media item placeholders; wherein each placeholder of the one or more digital visual media item placeholders accepts a range of digital visual media items; wherein the one or more selected design animation modules that comprise the digital visual media item placeholders are associated with one or more particular metadata values, each particular metadata value of the one or more particular metadata values corresponding to one digital visual media item placeholder of the one or more digital visual media item placeholders; wherein each particular metadata value of the one or more particular metadata values indicates a range of digital visual media items that the corresponding digital visual media item placeholder accepts. 24. The method of claim 23 : wherein each of the one or more digital visual media items is a digital image; wherein each particular metadata value of the one or more particular metadata values indicates an image orientation of digital visual media items that the corresponding digital visual media item placeholder accepts. | 0.5 |
8,352,878 | 11 | 15 | 11. A computer program product for providing a navigation environment for a user to navigate a long list of selectable elements spanning at least two pages of a computer display, the computer program product comprising a tangible computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to provide a scrollable context menu; computer readable program code configured to determine whether at least one element has been selected on a page in a previous view; when at least one element is determined to have been selected in said previous view, computer readable program code configured to provide a first visual aid on said scrollable context menu to indicate said at least one element selected in said previous view; computer readable program code configured to determine whether at least one element has been selected on a page in a next view; when at least one element is determined to have been selected in said next view, computer readable program code configured to provide a second visual aid on said scrollable context menu to indicate said at least one element has been selected in said next view; computer readable program code configured to position a third visual aid on said scrollable context menu comprising a numerical count of a total number of elements selected in said previous view; and computer readable program code configured to position a fourth visual aid on said scrollable context menu comprising a numerical count of a total number of elements selected in said next view. | 11. A computer program product for providing a navigation environment for a user to navigate a long list of selectable elements spanning at least two pages of a computer display, the computer program product comprising a tangible computer readable storage medium having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code configured to provide a scrollable context menu; computer readable program code configured to determine whether at least one element has been selected on a page in a previous view; when at least one element is determined to have been selected in said previous view, computer readable program code configured to provide a first visual aid on said scrollable context menu to indicate said at least one element selected in said previous view; computer readable program code configured to determine whether at least one element has been selected on a page in a next view; when at least one element is determined to have been selected in said next view, computer readable program code configured to provide a second visual aid on said scrollable context menu to indicate said at least one element has been selected in said next view; computer readable program code configured to position a third visual aid on said scrollable context menu comprising a numerical count of a total number of elements selected in said previous view; and computer readable program code configured to position a fourth visual aid on said scrollable context menu comprising a numerical count of a total number of elements selected in said next view. 15. The computer program product of claim 11 , further comprising computer readable program code configured to display a first list of said at least one comprising all elements in said total number of elements selected in a said previous view by placing a cursor over said first visual aid on said scrollable context menu. | 0.5 |
9,521,133 | 7 | 12 | 7. A client device configured to implement a moving target defense against cross-site scripting, the client device comprising: a processor; and memory storing instructions that, when executed, cause the processor to: request a web page from a server, wherein the server mutates web content with JavaScript offline to provide N versions of the web page, each with a different mutated version of JavaScript, and wherein, upon the requesting, the server provides one of the N versions of the web page thereby providing the moving target defense against cross-site scripting; receive a response serving the web page from the server with a header comprising an indication of a mutated version of JavaScript for the web page of the N versions of the web page each with a different mutated version and replaced periodically to increase probability of vulnerability detection, wherein the mutated version of JavaScript comprises changes to one or more lexical tokens which are selected based on use in malicious JavaScript attacks, wherein the one or more lexical tokens are one or more of a left parenthesis and an assignment operator, wherein cross-site scripting requires use of the parenthesis or the assignment operator to maliciously manipulate behavior, and wherein the parenthesis or the assignment operator are randomized because they manipulate behavior or state in a cross-site scripting attack, and wherein the web page is randomly reselected from the N versions and replaced periodically by the server; adjust a JavaScript interpreter based on the mutated version of JavaScript for the web page; and detect any JavaScript not conforming to the mutated version of JavaScript and provide an indication of a violation including JavaScript not conforming to the mutated version of JavaScript associated with the web page, wherein the indication includes a page on which the violation occurred, the page's referrer, a resource that violated the page's policy, and a specific directive of the violation. | 7. A client device configured to implement a moving target defense against cross-site scripting, the client device comprising: a processor; and memory storing instructions that, when executed, cause the processor to: request a web page from a server, wherein the server mutates web content with JavaScript offline to provide N versions of the web page, each with a different mutated version of JavaScript, and wherein, upon the requesting, the server provides one of the N versions of the web page thereby providing the moving target defense against cross-site scripting; receive a response serving the web page from the server with a header comprising an indication of a mutated version of JavaScript for the web page of the N versions of the web page each with a different mutated version and replaced periodically to increase probability of vulnerability detection, wherein the mutated version of JavaScript comprises changes to one or more lexical tokens which are selected based on use in malicious JavaScript attacks, wherein the one or more lexical tokens are one or more of a left parenthesis and an assignment operator, wherein cross-site scripting requires use of the parenthesis or the assignment operator to maliciously manipulate behavior, and wherein the parenthesis or the assignment operator are randomized because they manipulate behavior or state in a cross-site scripting attack, and wherein the web page is randomly reselected from the N versions and replaced periodically by the server; adjust a JavaScript interpreter based on the mutated version of JavaScript for the web page; and detect any JavaScript not conforming to the mutated version of JavaScript and provide an indication of a violation including JavaScript not conforming to the mutated version of JavaScript associated with the web page, wherein the indication includes a page on which the violation occurred, the page's referrer, a resource that violated the page's policy, and a specific directive of the violation. 12. The client device of claim 7 , wherein the client device operates a browser program with a plugin for implementing adjustments to the JavaScript interpreter. | 0.771307 |
7,523,434 | 1 | 7 | 1. A method for implementing a symbolic specification using dynamically configurable arithmetic unit, the method comprising: receiving a plurality of mathematical expressions comprising a plurality of input variables; generating the symbolic specification from the plurality of mathematical expressions, wherein the symbolic specification is devoid of hardware description; assigning the plurality of input variables to input ports of the dynamically configurable arithmetic unit, wherein the dynamically reconfigurable arithmetic unit comprises a fixed number of components and a fixed number of input ports, wherein at least two input ports have different bit widths and at least two of the plurality of input variables have different binary point; determining from the symbolic specification a list of operations to be performed by the dynamically configurable arithmetic unit in order to sequentially execute the plurality of mathematical expressions; and generating an interface to the dynamically configurable arithmetic unit based on at least in part the assigning step and the list of operations, wherein the interface performs an alignment of selected ones of plurality of input variables for each mathematical expression to be sequentially executed, wherein at least two consecutive alignments of the plurality of input variables are performed differently, and wherein each alignment is performed according to the binary point of the input variables and which input ports are to be multiplied or added together for the mathematical expression to be executed, wherein the generating the interface comprises creating one or more multiplexers; and wherein one or more multiplexers are formed in programmable logic in an integrated circuit device. | 1. A method for implementing a symbolic specification using dynamically configurable arithmetic unit, the method comprising: receiving a plurality of mathematical expressions comprising a plurality of input variables; generating the symbolic specification from the plurality of mathematical expressions, wherein the symbolic specification is devoid of hardware description; assigning the plurality of input variables to input ports of the dynamically configurable arithmetic unit, wherein the dynamically reconfigurable arithmetic unit comprises a fixed number of components and a fixed number of input ports, wherein at least two input ports have different bit widths and at least two of the plurality of input variables have different binary point; determining from the symbolic specification a list of operations to be performed by the dynamically configurable arithmetic unit in order to sequentially execute the plurality of mathematical expressions; and generating an interface to the dynamically configurable arithmetic unit based on at least in part the assigning step and the list of operations, wherein the interface performs an alignment of selected ones of plurality of input variables for each mathematical expression to be sequentially executed, wherein at least two consecutive alignments of the plurality of input variables are performed differently, and wherein each alignment is performed according to the binary point of the input variables and which input ports are to be multiplied or added together for the mathematical expression to be executed, wherein the generating the interface comprises creating one or more multiplexers; and wherein one or more multiplexers are formed in programmable logic in an integrated circuit device. 7. The method of claim 1 wherein the list of operations comprises a list of operational modes selected from a plurality of predetermined operational modes for the dynamically configurable arithmetic unit, wherein the step of determining comprises: generating tokens from the symbolic specification; mapping each token of the symbolic specification to an operational modes of the plurality of predetermined operational modes; and generating the list of operations according to the mapped opmodes of the dynamically configurable arithmetic unit. | 0.588636 |
7,706,616 | 26 | 27 | 26. The method of claim 25 , wherein still another channel of the plurality of channels comprise a language context channel. | 26. The method of claim 25 , wherein still another channel of the plurality of channels comprise a language context channel. 27. The method of claim 26 , wherein yet another channel of the plurality of channels comprises shape information. | 0.5 |
9,032,362 | 6 | 8 | 6. A non-transitory computer readable medium comprising: computer readable code, that when executed causes a processor in a computer system to implement a method comprising: receiving a user-provided plain language calculation expression, wherein the user-provided plain language calculation expression specifies a plurality of calculation identifiers without specifying at least one calculational relationship between a first calculation identifier in the plurality of calculation identifiers and a second calculation identifier in the plurality of calculation identifiers; determining the at least one calculational relationship in accordance with system-provided definitions; generating a calculation definition table in accordance with the user-provided plain language calculation expression, wherein the calculation definition table comprises the plurality of calculation identifiers and the at least one calculational relationship; determining a calculational sequence associated with the plurality of calculation identifiers; generating a calculation input definition table in accordance with the calculation definition table, wherein the calculation input definition table comprises multiple calculation input definitions each associated with one of the calculation identifiers and the calculational sequence; and generating, a calculation execution graph in accordance with the calculation input definition table, wherein the calculation execution graph is readable by a plurality of enterprise applications and wherein generating the calculation execution graph comprises generating a calculation definition model comprising a plurality of calculation definitions, wherein each of the calculation definitions is associated with a calculation identifier and a length designation, wherein the length designation corresponds to a number of intermediate calculations required for an input required by the calculation definition. | 6. A non-transitory computer readable medium comprising: computer readable code, that when executed causes a processor in a computer system to implement a method comprising: receiving a user-provided plain language calculation expression, wherein the user-provided plain language calculation expression specifies a plurality of calculation identifiers without specifying at least one calculational relationship between a first calculation identifier in the plurality of calculation identifiers and a second calculation identifier in the plurality of calculation identifiers; determining the at least one calculational relationship in accordance with system-provided definitions; generating a calculation definition table in accordance with the user-provided plain language calculation expression, wherein the calculation definition table comprises the plurality of calculation identifiers and the at least one calculational relationship; determining a calculational sequence associated with the plurality of calculation identifiers; generating a calculation input definition table in accordance with the calculation definition table, wherein the calculation input definition table comprises multiple calculation input definitions each associated with one of the calculation identifiers and the calculational sequence; and generating, a calculation execution graph in accordance with the calculation input definition table, wherein the calculation execution graph is readable by a plurality of enterprise applications and wherein generating the calculation execution graph comprises generating a calculation definition model comprising a plurality of calculation definitions, wherein each of the calculation definitions is associated with a calculation identifier and a length designation, wherein the length designation corresponds to a number of intermediate calculations required for an input required by the calculation definition. 8. The non-transitory computer readable medium of claim 6 wherein generating the calculation execution graph further comprises sorting the plurality of calculation definitions based on the length designation associated which each of the calculation definitions. | 0.5 |
9,246,798 | 15 | 17 | 15. A network node comprising: a network interface; a memory; and a processor in communication with the network interface and the memory, wherein the processor is configured to: establish context objects in the memory in response to receiving a message via the network interface, wherein the context objects have respective context object types based on respective pre-stored context artifacts that define the respective context object types and the respective pre-stored context artifacts include computer code defining at least one new function, respectively; and process the received message comprising: evaluating a plurality of rules to identify an applicable rule of the plurality of rules, performing at least one action specified by the applicable rule, and executing computer code placed in memory from the pre-stored context artifact that defines the context object type of the established context object as part of at least one of evaluating the plurality of rules and performing at least one action. | 15. A network node comprising: a network interface; a memory; and a processor in communication with the network interface and the memory, wherein the processor is configured to: establish context objects in the memory in response to receiving a message via the network interface, wherein the context objects have respective context object types based on respective pre-stored context artifacts that define the respective context object types and the respective pre-stored context artifacts include computer code defining at least one new function, respectively; and process the received message comprising: evaluating a plurality of rules to identify an applicable rule of the plurality of rules, performing at least one action specified by the applicable rule, and executing computer code placed in memory from the pre-stored context artifact that defines the context object type of the established context object as part of at least one of evaluating the plurality of rules and performing at least one action. 17. The network node of claim 15 , wherein the processor is configured to executing computer code placed in memory from the pre-stored context artifact as part of performing the at least one action. | 0.784783 |
6,047,293 | 13 | 18 | 13. The semiconductor test system of claim 12 in which said Dcontainer stores an indicator of the position of said named data in said ordered sequence vector. | 13. The semiconductor test system of claim 12 in which said Dcontainer stores an indicator of the position of said named data in said ordered sequence vector. 18. The semiconductor test system of claim 13 in which a commercially available program stores and searches said named data in said tree according to a set of decision logic rules. | 0.567308 |
8,392,188 | 18 | 25 | 18. A method of task classification using a phonotactic model built for domain independent speech recognition, comprising: recognizing phones from a user's input communication using a current phonotactic model stored in a database; detecting morphemes from the recognized phones; creating, via a processor, a new phonotactic model using the detected morpheme, the creating the new phonotactic model comprising transforming a prior probability distribution associated with a first domain to a prior probability distribution associated with a second domain; replacing the current phonotactic model with the new phonotactic model in the database; and making a task-type classification decision based on the detected morphemes from the user's input communication. | 18. A method of task classification using a phonotactic model built for domain independent speech recognition, comprising: recognizing phones from a user's input communication using a current phonotactic model stored in a database; detecting morphemes from the recognized phones; creating, via a processor, a new phonotactic model using the detected morpheme, the creating the new phonotactic model comprising transforming a prior probability distribution associated with a first domain to a prior probability distribution associated with a second domain; replacing the current phonotactic model with the new phonotactic model in the database; and making a task-type classification decision based on the detected morphemes from the user's input communication. 25. The method of claim 18 , further comprising entering into a dialog with the user to obtain a feedback response from the user. | 0.790584 |
8,756,279 | 1 | 5 | 1. A method for evaluating content descriptors for online publications, comprising the operations of: receiving a list of websites having online publications; gathering counts of user signals for each online publication on each website; determining content descriptors for each online publication; counting the online publications at each website associated with each content descriptor; and counting the user signals at each website associated with each content descriptor, wherein each operation of the method is executed by one or more processors. | 1. A method for evaluating content descriptors for online publications, comprising the operations of: receiving a list of websites having online publications; gathering counts of user signals for each online publication on each website; determining content descriptors for each online publication; counting the online publications at each website associated with each content descriptor; and counting the user signals at each website associated with each content descriptor, wherein each operation of the method is executed by one or more processors. 5. The method of claim 1 , wherein the user signals are social signals. | 0.918764 |
8,478,052 | 21 | 22 | 21. The computer readable medium of claim 20 , wherein the instructions cause the computer to perform operations comprising: obtaining text associated with an image; obtaining a feature vector for the image; parsing, in a processing device, the text into candidate labels, each candidate label being a unique n-gram of the text; determining, in the processing device, that an image classification model is trained for an n-gram matching one or more candidate labels; and classifying, in the processing device, the image to the one or more candidate labels based on the feature vector and the image classification model for the n-gram matching the one or more candidate labels. | 21. The computer readable medium of claim 20 , wherein the instructions cause the computer to perform operations comprising: obtaining text associated with an image; obtaining a feature vector for the image; parsing, in a processing device, the text into candidate labels, each candidate label being a unique n-gram of the text; determining, in the processing device, that an image classification model is trained for an n-gram matching one or more candidate labels; and classifying, in the processing device, the image to the one or more candidate labels based on the feature vector and the image classification model for the n-gram matching the one or more candidate labels. 22. The computer readable medium of claim 21 , wherein the determining and classifying are performed for each of the candidate labels. | 0.827763 |
4,214,125 | 70 | 74 | 70. A system for processing information bearing input signals to initially compress said input signals by reducing the information content thereof without destroying the intelligibility thereof and subsequently synthesizing signals from said compressed signals, said system comprising: input means adapted to receive said input signals; means coupled to said input means for Mozer phase adjusting said input signals to produce equivalent signals having substantially symmetric portions; means for deleting selected redundant portions of said equivalent signals; means for X period zeroing the signals processed by said Mozer phase adjusting means and said deleting means by deleting preselected relatively low power portions of the processed signals; means for generating instruction signals specifying those portions of said input signals deleted by said deleting means and said X period zeroing means; means for reproducing the signals processed by said X period zeroing means; means for expanding the reproduced signals to supply said deleted redundant portions in accordance with said instruction signals; means for inserting substantially constant amplitude signals between the non-deleted portions of the signals generated by said expanding means in accordance with said instruction signals so that said deleted relatively low power signal portions are replaced by said signals of substantially constant amplitude; and means for converting the signals output from said inserting means to perceivable form. | 70. A system for processing information bearing input signals to initially compress said input signals by reducing the information content thereof without destroying the intelligibility thereof and subsequently synthesizing signals from said compressed signals, said system comprising: input means adapted to receive said input signals; means coupled to said input means for Mozer phase adjusting said input signals to produce equivalent signals having substantially symmetric portions; means for deleting selected redundant portions of said equivalent signals; means for X period zeroing the signals processed by said Mozer phase adjusting means and said deleting means by deleting preselected relatively low power portions of the processed signals; means for generating instruction signals specifying those portions of said input signals deleted by said deleting means and said X period zeroing means; means for reproducing the signals processed by said X period zeroing means; means for expanding the reproduced signals to supply said deleted redundant portions in accordance with said instruction signals; means for inserting substantially constant amplitude signals between the non-deleted portions of the signals generated by said expanding means in accordance with said instruction signals so that said deleted relatively low power signal portions are replaced by said signals of substantially constant amplitude; and means for converting the signals output from said inserting means to perceivable form. 74. The combination of claim 70 further including means coupled to said deleting means for delta modulating the signals output therefrom. | 0.919031 |
9,293,061 | 1 | 2 | 1. A method for creating a mnemonic experience for a user, which comprises: selecting a concentration of information to be remembered; gathering information on said concentration, said information being intended to be remembered by the user; providing a building; placing a display to be observed in said building, said display teaching said information when observed by the user; providing a character to interact with the user and said display, said character being contextually related to said display; interacting said character with the user with while the user observes said display; gathering further information on said concentration; determining an importance of said information relative to an importance of said further information; and not creating a display of said further information when said importance of said further information is less than the importance of said piece of information. | 1. A method for creating a mnemonic experience for a user, which comprises: selecting a concentration of information to be remembered; gathering information on said concentration, said information being intended to be remembered by the user; providing a building; placing a display to be observed in said building, said display teaching said information when observed by the user; providing a character to interact with the user and said display, said character being contextually related to said display; interacting said character with the user with while the user observes said display; gathering further information on said concentration; determining an importance of said information relative to an importance of said further information; and not creating a display of said further information when said importance of said further information is less than the importance of said piece of information. 2. The method according to claim 1 , wherein said importance of said further information and said importance of said information are based on a probability of the user learning about said concentration by remembering said information. | 0.611296 |
10,158,663 | 19 | 20 | 19. An apparatus to improve security incident responses for a computing environment comprising a plurality of computing assets, the apparatus comprising: one or more non-transitory computer readable storage media; and processing instructions stored on the one or more non-transitory computer readable storage media that, when executed by a processing system, direct the processing system to: maintain asset configuration data for the plurality of computing assets, the asset configuration data comprising characteristics for each of the one or more computing assets; in response to identifying a security incident in the computing environment, provide, for display, security incident information related to the security incident to an administrator associated with the computing environment; identify a selection of a security action from the administrator; identify one or more computing assets related to the security action; identify configuration data for the one or more computing assets from the maintained asset configuration data; identify one or more action procedures to support the action selection based on the identified configuration data; and initiate implementation of the one or more action procedures in the one or more computing assets. | 19. An apparatus to improve security incident responses for a computing environment comprising a plurality of computing assets, the apparatus comprising: one or more non-transitory computer readable storage media; and processing instructions stored on the one or more non-transitory computer readable storage media that, when executed by a processing system, direct the processing system to: maintain asset configuration data for the plurality of computing assets, the asset configuration data comprising characteristics for each of the one or more computing assets; in response to identifying a security incident in the computing environment, provide, for display, security incident information related to the security incident to an administrator associated with the computing environment; identify a selection of a security action from the administrator; identify one or more computing assets related to the security action; identify configuration data for the one or more computing assets from the maintained asset configuration data; identify one or more action procedures to support the action selection based on the identified configuration data; and initiate implementation of the one or more action procedures in the one or more computing assets. 20. The apparatus of claim 19 wherein the security incident information comprises suggestions of one or more security actions to be taken against the security incident, and wherein identifying the selection of the security action comprises identifying the selection of the security action from the one or more security actions. | 0.5 |
9,165,054 | 16 | 18 | 16. The method of claim 11 , further comprising: determining a context of a plurality of generated phrases. | 16. The method of claim 11 , further comprising: determining a context of a plurality of generated phrases. 18. The method of claim 16 , further comprising: determining a probability that at least a first phrase and at least a second phrase out of the plurality of generated phrases appear together. | 0.5 |
8,301,448 | 4 | 5 | 4. The method according to claim 2 , wherein the language model comprises an unsmoothed section language model, and wherein the performing comprises conducting speech recognition with said unsmoothed section language model. | 4. The method according to claim 2 , wherein the language model comprises an unsmoothed section language model, and wherein the performing comprises conducting speech recognition with said unsmoothed section language model. 5. The method according to claim 4 , wherein the performing generates a recognition output having an associated confidence level, and wherein the method further comprises an act of conducting a confidence level evaluation to determine whether the confidence level meets a predetermined threshold value. | 0.5 |
7,634,756 | 5 | 7 | 5. An article of manufacture including a tangible computer storage medium having instructions stored thereon that if executed by a processing device or multiple communicating processing devices, cause the processing device or the multiple communicating processing devices to perform a method comprising: graphically corresponding one or more splitter input terminals of a splitter component to a splitter input of a splitter algorithm associated with the splitter component of an executable component; receiving the splitter input at a single splitter input time at each of the one or more splitter input terminals; graphically corresponding one or more splitter output terminals to a splitter output generated by the splitter algorithm associated with the splitter component of the executable component, the splitter output terminals producing splitter outputs at a plurality of splitter output times; generating a plurality of consistent splitter output sets in a specific order by operating on the splitter input; separately providing each of the consistent splitter output sets to one or more other downstream executable components; graphically corresponding one or more joiner input terminals of a joiner component to a joiner input of a jointer algorithm associated with the joiner component; receiving the joiner input at a plurality of joiner input times at each joiner input terminal; graphically corresponding one or more joiner output terminals to a joiner output generated by the joiner algorithm associated with the joiner component; generating a plurality of consistent joiner input sets; providing exactly one consistent joiner input set at the joiner input terminals of the joiner component for each of the consistent splitter output sets generated by the splitter algorithm associated with the splitter component; and providing a single joiner output at the joiner output terminals upon completing execution of the joiner algorithm, the joiner output terminals producing the joiner output at a single joiner output time. | 5. An article of manufacture including a tangible computer storage medium having instructions stored thereon that if executed by a processing device or multiple communicating processing devices, cause the processing device or the multiple communicating processing devices to perform a method comprising: graphically corresponding one or more splitter input terminals of a splitter component to a splitter input of a splitter algorithm associated with the splitter component of an executable component; receiving the splitter input at a single splitter input time at each of the one or more splitter input terminals; graphically corresponding one or more splitter output terminals to a splitter output generated by the splitter algorithm associated with the splitter component of the executable component, the splitter output terminals producing splitter outputs at a plurality of splitter output times; generating a plurality of consistent splitter output sets in a specific order by operating on the splitter input; separately providing each of the consistent splitter output sets to one or more other downstream executable components; graphically corresponding one or more joiner input terminals of a joiner component to a joiner input of a jointer algorithm associated with the joiner component; receiving the joiner input at a plurality of joiner input times at each joiner input terminal; graphically corresponding one or more joiner output terminals to a joiner output generated by the joiner algorithm associated with the joiner component; generating a plurality of consistent joiner input sets; providing exactly one consistent joiner input set at the joiner input terminals of the joiner component for each of the consistent splitter output sets generated by the splitter algorithm associated with the splitter component; and providing a single joiner output at the joiner output terminals upon completing execution of the joiner algorithm, the joiner output terminals producing the joiner output at a single joiner output time. 7. The article of manufacture of claim 5 , wherein the method further comprises: beginning execution of the joiner algorithm associated with the joiner component when a first consistent joiner input set arrives at the joiner input terminals, the first consistent joiner input set corresponding to any consistent splitter output set generated by the splitter algorithm associated with the associated splitter component; continuing execution of the joiner algorithm as and when a second consistent joiner input set arrives at the joiner input terminal the second consistent joiner input set corresponding to any other consistent splitter output set generated by the splitter algorithm associated with the associated splitter component; and completing execution of the joiner algorithm after all consistent joiner input sets have arrived at the joiner input terminals, the all consistent joiner input sets corresponding to all consistent splitter output sets generated by the splitter algorithm associated with the associated splitter component. | 0.5 |
7,913,191 | 1 | 7 | 1. Apparatus which provides a common input/output interface to a plurality of application programs, comprising: a processing unit; and a computer readable storage medium including computer usable program code configured to be executed by the processing unit, the computer usable program code having, a document converting section which converts a plurality of objects contained in an application-specific document generated by each of the plurality of application programs and represented in a data structure specific to the application program to a common document represented in a common data structure that is to represent the objects as nodes of a tree structure; a structure converting section which, if at least one attribute of each of the plurality of objects contained in the common document with which the object is to be displayed by a relevant application program satisfies a condition predetermined for at least one predetermined data structure selected between a predetermined table structure and a predetermined list structure, assigns each of the plurality of objects to a node of the predetermined data structure that satisfies the condition to convert the data structure of the common document; an output section which presents the common document to a user in a common window and outputs text contained in the common document to a text reader capable of reading text aloud; an input section which inputs an operation performed by the user on the common document in the common window; an interface adapter section which converts an object contained in the common document to an object used in the output section; a modifying section which modifies the common document in accordance with the operation by the user; and a modification reflecting section which reflects a modification to the common document in the application-specific document, wherein the modification is to correspond to the operation by the user. | 1. Apparatus which provides a common input/output interface to a plurality of application programs, comprising: a processing unit; and a computer readable storage medium including computer usable program code configured to be executed by the processing unit, the computer usable program code having, a document converting section which converts a plurality of objects contained in an application-specific document generated by each of the plurality of application programs and represented in a data structure specific to the application program to a common document represented in a common data structure that is to represent the objects as nodes of a tree structure; a structure converting section which, if at least one attribute of each of the plurality of objects contained in the common document with which the object is to be displayed by a relevant application program satisfies a condition predetermined for at least one predetermined data structure selected between a predetermined table structure and a predetermined list structure, assigns each of the plurality of objects to a node of the predetermined data structure that satisfies the condition to convert the data structure of the common document; an output section which presents the common document to a user in a common window and outputs text contained in the common document to a text reader capable of reading text aloud; an input section which inputs an operation performed by the user on the common document in the common window; an interface adapter section which converts an object contained in the common document to an object used in the output section; a modifying section which modifies the common document in accordance with the operation by the user; and a modification reflecting section which reflects a modification to the common document in the application-specific document, wherein the modification is to correspond to the operation by the user. 7. The apparatus according to claim 1 , wherein: the output section converts the common document to an edit document represented in a data structure specific to an editing application program prespecified for editing the common document and outputs the resulting edit document to the editing application program; and the input section inputs the edit document modified by the user by using the editing application program as the modified common document. | 0.698539 |
7,765,271 | 43 | 44 | 43. A method as claimed in claim 35 , further comprising the step of: o) adjusting the display of the scanned document via a user's operation of a control element defined by the HTML document displayed by the web browser within the user interface. | 43. A method as claimed in claim 35 , further comprising the step of: o) adjusting the display of the scanned document via a user's operation of a control element defined by the HTML document displayed by the web browser within the user interface. 44. A method as claimed in claim 43 , wherein the adjusting of said step (o) includes increasing the scale of display of the scanned document (“zooming in”) on the user interface. | 0.807112 |
10,042,613 | 18 | 19 | 18. A computer documentation validation system, said system comprising: a processor: and a memory, the memory storing instructions to cause the processor to: translate a natural language of a computer software documentation into a machine instruction; detect an error in the natural language of the computer software documentation by executing the translated machine instruction on a software product for use of the computer software documentation; and highlight a location in the computer software documentation including the error detected by the detecting; wherein the translating performs the translating by a reinforcement learning agent that teams an accuracy of the translating through an iterative process of repeatedly executing, the machine instruction on the software that has been previously translated, and wherein the highlighting outputs the location to a user such that remedial action is executed by the user; wherein the machine instruction comprises a back pointer indicating the location in the computer software documentation from which the machine instruction is translated. | 18. A computer documentation validation system, said system comprising: a processor: and a memory, the memory storing instructions to cause the processor to: translate a natural language of a computer software documentation into a machine instruction; detect an error in the natural language of the computer software documentation by executing the translated machine instruction on a software product for use of the computer software documentation; and highlight a location in the computer software documentation including the error detected by the detecting; wherein the translating performs the translating by a reinforcement learning agent that teams an accuracy of the translating through an iterative process of repeatedly executing, the machine instruction on the software that has been previously translated, and wherein the highlighting outputs the location to a user such that remedial action is executed by the user; wherein the machine instruction comprises a back pointer indicating the location in the computer software documentation from which the machine instruction is translated. 19. The system of claim 18 , embodied in a cloud-computing environment. | 0.5 |
9,652,227 | 12 | 14 | 12. A system for assigning an annotation to a variable and a statement in a source code of a software application, the system comprising: a processor; and a memory coupled to the processor, wherein the processor is capable of executing a plurality of modules stored in the memory, and wherein the plurality of modules comprising: a generating module to generate an intermediate representation of the source code by parsing the source code, wherein the source code comprises a plurality of variables; an identifying module to identify: one or more instances of definition of the variable of the plurality of variables present in the intermediate representation, and one or more instances of use of the variable in the intermediate representation; a categorizing module to categorize the variable into a group of variables based on: a) the one or more instances of definition of the variable, b) the one or more instances of use of the variable, c) a description of the variable, and d) mathematical operators defining a correlation between the variable and one or more other variables of the plurality of variables, wherein the description of the variable indicates a nature of data stored in the variable, and wherein the group of variables comprises variables storing data of similar nature; a creating module to create: a data description table of the plurality of variables, wherein the data description table comprises the variable and the description of the variable; a data dictionary of the plurality of variables, wherein the data dictionary comprises the group of variables and the description of the variables present in the group of variables; and an assigning module to assign the annotation to the variable present in the statement of the source code based on the data description table and the data dictionary, thereby assigning the annotation to the statement in the source code of the software application. | 12. A system for assigning an annotation to a variable and a statement in a source code of a software application, the system comprising: a processor; and a memory coupled to the processor, wherein the processor is capable of executing a plurality of modules stored in the memory, and wherein the plurality of modules comprising: a generating module to generate an intermediate representation of the source code by parsing the source code, wherein the source code comprises a plurality of variables; an identifying module to identify: one or more instances of definition of the variable of the plurality of variables present in the intermediate representation, and one or more instances of use of the variable in the intermediate representation; a categorizing module to categorize the variable into a group of variables based on: a) the one or more instances of definition of the variable, b) the one or more instances of use of the variable, c) a description of the variable, and d) mathematical operators defining a correlation between the variable and one or more other variables of the plurality of variables, wherein the description of the variable indicates a nature of data stored in the variable, and wherein the group of variables comprises variables storing data of similar nature; a creating module to create: a data description table of the plurality of variables, wherein the data description table comprises the variable and the description of the variable; a data dictionary of the plurality of variables, wherein the data dictionary comprises the group of variables and the description of the variables present in the group of variables; and an assigning module to assign the annotation to the variable present in the statement of the source code based on the data description table and the data dictionary, thereby assigning the annotation to the statement in the source code of the software application. 14. The system of claim 12 , wherein the one or more instances of use of the variable are linked to the one or more instances of definition of the variable by performing static analysis on the intermediate representation of the source code. | 0.548872 |
9,978,364 | 1 | 3 | 1. A method for improving reading accuracy in speech recognition using processing by a computer, the method comprising computer-executed steps of: program instructions to obtain a plurality of candidate word strings from speech recognition results, wherein the speech recognition results contain a speech recognition score for each of the plurality of candidate work strings; program instructions to determine a reading of each of the plurality of candidate word strings, wherein two or more candidate word strings have the same reading, and wherein the two or more candidate word strings having the same reading are homophones; program instructions to determine a reading score for each candidate word string, wherein the reading score for each of the two or more candidate word strings with the same reading is based on a total value of the speech recognition scores for the two or more candidate word strings with the same reading, wherein determining the total value of the speech recognition scores for the two or more candidate word strings with the same reading includes computer-executed steps of: program instructions to determine two or more candidate word strings with partial tolerable different readings allowing for a partial difference in readings between two or more candidate word strings treated as having the same reading, partial tolerable different readings being a first predetermined value, the partial difference in readings range being a predetermined range of values; and program instructions to calculate the reading score total value of the speech recognition scores for the two or more candidate word strings with the same reading wherein the speech recognition scores for the two or more candidate word strings with partial tolerable different readings are to be treated as having the same reading, wherein calculating the reading score total value of the speech recognition scores for the two or more candidate word strings with the same reading includes: program instructions to receive a conversion table, wherein the conversion table includes word strings, wherein the word strings includes word notations and phoneme strings, and wherein the conversion table contains word strings with partial tolerable different readings allowing for a partial difference in readings between two or more candidate word strings treated as having the same reading, and wherein determining the two or more candidate word strings with partial tolerable different readings allowing for a partial difference in readings between two or more candidate word strings treated as having the same reading is based on the conversion table; program instructions to receive N-best lists from a plurality of speech recognition systems, wherein the N-best lists contain the two or more candidate word strings; program instructions to determine a match of the two or more candidate word strings within the N-best list and the conversion table of; and program instructions to convert the matched of the two or more candidate word strings according to the conversion table; and program instructions to select a candidate among the plurality of candidate word strings to output on the basis of the reading score and the speech recognition score corresponding to each word string, wherein program instructions to select the candidate includes a computer system-executed step selected from the group consisting of: program instructions to weight and add together the speech recognition score and the corresponding reading score for each candidate word string to obtain a new score, and program instructions to select the candidate word string with the highest new score; and program instructions to select a candidate word string with the highest speech recognition score from among the one or more candidate word strings with the highest reading score. | 1. A method for improving reading accuracy in speech recognition using processing by a computer, the method comprising computer-executed steps of: program instructions to obtain a plurality of candidate word strings from speech recognition results, wherein the speech recognition results contain a speech recognition score for each of the plurality of candidate work strings; program instructions to determine a reading of each of the plurality of candidate word strings, wherein two or more candidate word strings have the same reading, and wherein the two or more candidate word strings having the same reading are homophones; program instructions to determine a reading score for each candidate word string, wherein the reading score for each of the two or more candidate word strings with the same reading is based on a total value of the speech recognition scores for the two or more candidate word strings with the same reading, wherein determining the total value of the speech recognition scores for the two or more candidate word strings with the same reading includes computer-executed steps of: program instructions to determine two or more candidate word strings with partial tolerable different readings allowing for a partial difference in readings between two or more candidate word strings treated as having the same reading, partial tolerable different readings being a first predetermined value, the partial difference in readings range being a predetermined range of values; and program instructions to calculate the reading score total value of the speech recognition scores for the two or more candidate word strings with the same reading wherein the speech recognition scores for the two or more candidate word strings with partial tolerable different readings are to be treated as having the same reading, wherein calculating the reading score total value of the speech recognition scores for the two or more candidate word strings with the same reading includes: program instructions to receive a conversion table, wherein the conversion table includes word strings, wherein the word strings includes word notations and phoneme strings, and wherein the conversion table contains word strings with partial tolerable different readings allowing for a partial difference in readings between two or more candidate word strings treated as having the same reading, and wherein determining the two or more candidate word strings with partial tolerable different readings allowing for a partial difference in readings between two or more candidate word strings treated as having the same reading is based on the conversion table; program instructions to receive N-best lists from a plurality of speech recognition systems, wherein the N-best lists contain the two or more candidate word strings; program instructions to determine a match of the two or more candidate word strings within the N-best list and the conversion table of; and program instructions to convert the matched of the two or more candidate word strings according to the conversion table; and program instructions to select a candidate among the plurality of candidate word strings to output on the basis of the reading score and the speech recognition score corresponding to each word string, wherein program instructions to select the candidate includes a computer system-executed step selected from the group consisting of: program instructions to weight and add together the speech recognition score and the corresponding reading score for each candidate word string to obtain a new score, and program instructions to select the candidate word string with the highest new score; and program instructions to select a candidate word string with the highest speech recognition score from among the one or more candidate word strings with the highest reading score. 3. The method for improving reading accuracy according to claim 1 , wherein the plurality of candidate word strings in the speech recognition results are integrated with N-best lists from a plurality of speech recognition systems. | 0.694149 |
7,644,360 | 20 | 25 | 20. A method for displaying patent claims, the method steps comprising: selecting at least part of a patent claims series; importing the at least part of a patent claims series; parsing the at least part of a patent claims series into the claims hierarchy of at least part of a patent claims series; displaying the parsed at least part of a patent claims series in an interactive format that is operable to dynamically expand and compress the at least part of a patent claims series, including both the graphical claim structure and the fully included textual claim content, according to the hierarch of the at least part of a patent claims series, the textual content of each claim ending with a numerical representation of how many claims directly depend on that claim; wherein the graphical claim structure comprises multiple geometric outlines, each outline operable to fully contain the textual claim content of one claim and at least one line directly connecting the outlines to each other according the hierarch of the at least part of a patent claims series; wherein at least one of the multiple geometric outlines further has a visual emphasis, the visual emphasis indicating whether there are additional levels of the hierarchy of the at least part of a patent claims series directly connected to the at least one of the multiple geometric outlines that has a visual emphasis. | 20. A method for displaying patent claims, the method steps comprising: selecting at least part of a patent claims series; importing the at least part of a patent claims series; parsing the at least part of a patent claims series into the claims hierarchy of at least part of a patent claims series; displaying the parsed at least part of a patent claims series in an interactive format that is operable to dynamically expand and compress the at least part of a patent claims series, including both the graphical claim structure and the fully included textual claim content, according to the hierarch of the at least part of a patent claims series, the textual content of each claim ending with a numerical representation of how many claims directly depend on that claim; wherein the graphical claim structure comprises multiple geometric outlines, each outline operable to fully contain the textual claim content of one claim and at least one line directly connecting the outlines to each other according the hierarch of the at least part of a patent claims series; wherein at least one of the multiple geometric outlines further has a visual emphasis, the visual emphasis indicating whether there are additional levels of the hierarchy of the at least part of a patent claims series directly connected to the at least one of the multiple geometric outlines that has a visual emphasis. 25. The method of claim 20 , wherein the imported claims are an entire claims series. | 0.718543 |
8,700,544 | 14 | 17 | 14. A query processing system comprising: one or more modules; and one or more processing devices configured to execute the one or more modules, the one or more modules comprising: an interface module configured to receive a query q from a particular user u, the particular user u attempting to find an item d that satisfies the query q and has a desired characteristic V u , and the particular user u being characterized by user information θ u ; a feature determination module configured to generate features which characterize a context in which the particular user u is attempting to find the item d; a particular user predictor module configured to generate a user-specific query-dependent distribution Pr(V u |q,θ u ) associated with the query q for the particular user u; and a ranking module configured to generate personalized results for the particular user u based on at least the features and the user-specific query-dependent distribution Pr(V u |q,θ u ), wherein the interface module is configured to forward the personalized results to the particular user u. | 14. A query processing system comprising: one or more modules; and one or more processing devices configured to execute the one or more modules, the one or more modules comprising: an interface module configured to receive a query q from a particular user u, the particular user u attempting to find an item d that satisfies the query q and has a desired characteristic V u , and the particular user u being characterized by user information θ u ; a feature determination module configured to generate features which characterize a context in which the particular user u is attempting to find the item d; a particular user predictor module configured to generate a user-specific query-dependent distribution Pr(V u |q,θ u ) associated with the query q for the particular user u; and a ranking module configured to generate personalized results for the particular user u based on at least the features and the user-specific query-dependent distribution Pr(V u |q,θ u ), wherein the interface module is configured to forward the personalized results to the particular user u. 17. The query processing system of claim 14 , the one or more modules further comprising: a generic predictor module configured to generate a generic distribution Pr r (V|q) associated with the query q that is germane to a population of generic users, wherein the particular user predictor module is configured to reweight the generic distribution Pr r (V|q) by user-specific multipliers to provide the user-specific query-dependent distribution Pr(V u |q,θ u ). | 0.51875 |
7,672,846 | 2 | 7 | 2. The voice recognition system according to claim 1 , wherein the priority determining unit uses as the predetermined priority criterion at least one selected from (1) a length of the detected voice section, (2) a power or an S/N ratio of the detected voice section, and (3) a chronological order of the detected voice section. | 2. The voice recognition system according to claim 1 , wherein the priority determining unit uses as the predetermined priority criterion at least one selected from (1) a length of the detected voice section, (2) a power or an S/N ratio of the detected voice section, and (3) a chronological order of the detected voice section. 7. The voice recognition system according to claim 2 , wherein (3) the chronological order of the detected voice section is used as the predetermined priority criterion, and the priority determining unit selects a predetermined number of detected voice sections from a last voice section on the time series from among a plurality of the detected voice sections contained in the speech voice data. | 0.671096 |
8,150,816 | 1 | 6 | 1. A method of managing information comprising: providing a plurality of rules and a plurality of abstractions, wherein each of the plurality of abstractions represents at least one of a class of entities or a class of actions having a role in managing of the information and each of the plurality of rules comprises an expression having a variable, and the variable is defined in a first abstraction; determining a subset of the plurality of rules and abstractions relevant to a target; modifying the subset of rules and abstractions, wherein the modified subset of rules and abstractions is logically equivalent to the subset of rules and abstractions; associating the modified subset of rules and abstractions to the target; for the target, controlling access to the information based on the modified subset of rules and abstractions; providing a rule having a first variable defined in the first abstraction of the subset of the plurality of rules and abstractions, wherein the first abstraction has a second variable defined in a second abstraction; and evaluating the second variable, wherein when the second variable evaluates to a constant, and the modifying the subset of rules and abstractions comprises removing the second variable from the first abstraction. | 1. A method of managing information comprising: providing a plurality of rules and a plurality of abstractions, wherein each of the plurality of abstractions represents at least one of a class of entities or a class of actions having a role in managing of the information and each of the plurality of rules comprises an expression having a variable, and the variable is defined in a first abstraction; determining a subset of the plurality of rules and abstractions relevant to a target; modifying the subset of rules and abstractions, wherein the modified subset of rules and abstractions is logically equivalent to the subset of rules and abstractions; associating the modified subset of rules and abstractions to the target; for the target, controlling access to the information based on the modified subset of rules and abstractions; providing a rule having a first variable defined in the first abstraction of the subset of the plurality of rules and abstractions, wherein the first abstraction has a second variable defined in a second abstraction; and evaluating the second variable, wherein when the second variable evaluates to a constant, and the modifying the subset of rules and abstractions comprises removing the second variable from the first abstraction. 6. The method of claim 1 wherein the modifying the subset of rules and abstractions comprises replacing a constant subexpression in a rule with a constant, and an expression comprises at least one subexpression. | 0.609259 |
8,887,179 | 1 | 3 | 1. A command method for a command driven computer system, the command method comprising: presenting a list of command driven computer program products in response to activation of the command method; presenting a logical tree comprising commands, related operands, sub-operands and related parameters for a command driven computer program product in response to receiving a selection of the command driven computer program product from the list of command driven computer program products; identifying, in the commands, related operands, sub-operands and related parameters of the logical tree that is presented, parameters that can be overwritten and parameters that have predefined values; and identifying, in the commands, related operands, sub-operands and related parameters of the logical tree that is presented, other operands and sub-operands that are unavailable for selection in response to receiving a selection of an operand or a sub-operand in the logical tree. | 1. A command method for a command driven computer system, the command method comprising: presenting a list of command driven computer program products in response to activation of the command method; presenting a logical tree comprising commands, related operands, sub-operands and related parameters for a command driven computer program product in response to receiving a selection of the command driven computer program product from the list of command driven computer program products; identifying, in the commands, related operands, sub-operands and related parameters of the logical tree that is presented, parameters that can be overwritten and parameters that have predefined values; and identifying, in the commands, related operands, sub-operands and related parameters of the logical tree that is presented, other operands and sub-operands that are unavailable for selection in response to receiving a selection of an operand or a sub-operand in the logical tree. 3. The method according to claim 1 wherein identifying, in the commands, related operands, sub-operands and related parameters of the logical tree that is presented, other operands and sub-operands that are unavailable for selection in response to receiving a selection of an operand or sub-operand in the logical tree comprises: identifying, in the commands, related operands, sub-operands and related parameters of the logical tree that is presented, other operands and sub-operands that are required in response to the receiving the selection of the operand or sub-operand in the logical tree; and identifying, in the commands, related operands, sub-operands and related parameters of the logical tree that is presented, other operands and sub-operands that are mutually exclusive to the operand or sub-operand in response to the receiving the selection of the operand or sub-operand in the logical tree. | 0.5 |
7,523,102 | 9 | 11 | 9. A computer-implemented method for executing a search query, the method comprising: receiving a search query including a textual expression, wherein the textual expression is written in a language that at least occasionally lacks discrete boundaries between words or autonomous language units; referencing a structured vocabulary knowledge base to determine whether the textual expression comprises a keyword or synonym associated with the structured vocabulary knowledge base, wherein the structured vocabulary knowledge base is for storing vocabulary information associated with a language having multiple orthographic forms or scripts, and wherien the structured vocabulary knowledge base is generated prior to receiving the search query by a repeatable method comprising: assigning an identifier to a semantic concept that is usable as a keyword or key phrase; identifying a main written form for the semantic concept, wherein the main written form is based on at least one of the multiple written forms; for at least one of the multiple written forms associated with the complex language, associating at least one synonymous written form with the semantic concept, wherein the synonymous written form is at least partially distinct from the main written form; and storing the identifier, the main written form, and the at least one synonymous written form in a data storage component associated with the vocabulary knowledge base; if the textual expression does not comprise a keyword, key phrase or synonym associated with the structured vocabulary knowledge base, performing segmentation on the textual expression, wherein the segmentation includes systematically splitting the textual expression into two or more segments, and identifying at least one keyword from the vocabulary knowledge based on the textual expression and the two or more segments; performing the search query using the at least one identified keyword; and providing for display results of the search query. | 9. A computer-implemented method for executing a search query, the method comprising: receiving a search query including a textual expression, wherein the textual expression is written in a language that at least occasionally lacks discrete boundaries between words or autonomous language units; referencing a structured vocabulary knowledge base to determine whether the textual expression comprises a keyword or synonym associated with the structured vocabulary knowledge base, wherein the structured vocabulary knowledge base is for storing vocabulary information associated with a language having multiple orthographic forms or scripts, and wherien the structured vocabulary knowledge base is generated prior to receiving the search query by a repeatable method comprising: assigning an identifier to a semantic concept that is usable as a keyword or key phrase; identifying a main written form for the semantic concept, wherein the main written form is based on at least one of the multiple written forms; for at least one of the multiple written forms associated with the complex language, associating at least one synonymous written form with the semantic concept, wherein the synonymous written form is at least partially distinct from the main written form; and storing the identifier, the main written form, and the at least one synonymous written form in a data storage component associated with the vocabulary knowledge base; if the textual expression does not comprise a keyword, key phrase or synonym associated with the structured vocabulary knowledge base, performing segmentation on the textual expression, wherein the segmentation includes systematically splitting the textual expression into two or more segments, and identifying at least one keyword from the vocabulary knowledge based on the textual expression and the two or more segments; performing the search query using the at least one identified keyword; and providing for display results of the search query. 11. The method of claim 9 wherein the systematic splitting includes splitting the textual expression into the longest segments possible in an effort to preserve the intended meaning of the textual expression. | 0.718919 |
7,716,576 | 1 | 7 | 1. A method of processing Extensible Markup Language (XML) documents, said method comprising: parsing an XML document comprising content in an XML format; converting said content into pcodes according to a conversion key, wherein said conversion key comprises a lookup table (LUT) comprising a plurality of XML tags, said XML tags each having a corresponding pcode, wherein an XML tag is converted into a pcode according to said conversion key and wherein said content converted into pcodes is convertible back to XML using said conversion key; representing a recurring sequence of different XML source code segments comprising multiple XML tags as a single same pcode, wherein said LUT further comprises an entry comprising said recurring sequence and said single pcode; generating a pcode file comprising said XML document parsed and converted into pcode, wherein said pcode file comprises said single pcode in lieu of each occurrence of said recurring sequence of XML tags; and forwarding said conversion key with said pcode file from one computer system to another computer system. | 1. A method of processing Extensible Markup Language (XML) documents, said method comprising: parsing an XML document comprising content in an XML format; converting said content into pcodes according to a conversion key, wherein said conversion key comprises a lookup table (LUT) comprising a plurality of XML tags, said XML tags each having a corresponding pcode, wherein an XML tag is converted into a pcode according to said conversion key and wherein said content converted into pcodes is convertible back to XML using said conversion key; representing a recurring sequence of different XML source code segments comprising multiple XML tags as a single same pcode, wherein said LUT further comprises an entry comprising said recurring sequence and said single pcode; generating a pcode file comprising said XML document parsed and converted into pcode, wherein said pcode file comprises said single pcode in lieu of each occurrence of said recurring sequence of XML tags; and forwarding said conversion key with said pcode file from one computer system to another computer system. 7. The method of claim 1 , wherein said single same pcode comprises three or more XML tags. | 0.829588 |
9,836,452 | 11 | 13 | 11. One or more computer-readable storage media, having computer-executable instructions that, when executed by at least one processor, perform a method for training a dialog component to discriminate ambiguous requests, the method comprising: receiving a natural language expression, wherein the natural language expression includes at least one of words, terms, and phrases of text; creating a dialog hypothesis set from the natural language expression by using contextual information, wherein the dialog hypothesis set has a first dialog hypothesis corresponding to a first domain and a second hypothesis corresponding to a second domain; generating, from a first domain engine component and a second domain engine component, a plurality of dialog responses for the dialog hypothesis set; ranking by machine learning techniques the first domain engine component and the second domain engine component based on an analysis of the plurality of the dialog responses; and performing an action with the highest ranked domain engine component. | 11. One or more computer-readable storage media, having computer-executable instructions that, when executed by at least one processor, perform a method for training a dialog component to discriminate ambiguous requests, the method comprising: receiving a natural language expression, wherein the natural language expression includes at least one of words, terms, and phrases of text; creating a dialog hypothesis set from the natural language expression by using contextual information, wherein the dialog hypothesis set has a first dialog hypothesis corresponding to a first domain and a second hypothesis corresponding to a second domain; generating, from a first domain engine component and a second domain engine component, a plurality of dialog responses for the dialog hypothesis set; ranking by machine learning techniques the first domain engine component and the second domain engine component based on an analysis of the plurality of the dialog responses; and performing an action with the highest ranked domain engine component. 13. The computer-readable storage media of claim 11 , wherein creating the dialog hypothesis set comprises: extracting at least one feature from the natural language expression; and generating at least two dialog hypotheses, where each dialog hypothesis of the dialog hypothesis set includes a different natural language expression having at least one extracted feature. | 0.5 |
8,185,865 | 13 | 14 | 13. The method of claim 1 , wherein the gate-length biasing length is a predefined fraction of the nominal gate-length. | 13. The method of claim 1 , wherein the gate-length biasing length is a predefined fraction of the nominal gate-length. 14. The method of claim 13 , wherein the predefined fraction is equal to 10% of the nominal gate length. | 0.5 |
8,239,185 | 7 | 8 | 7. A method, comprising: a) obtaining in digital form by logic a choice of an interviewer language, and a choice of an interviewee language that is distinct from the interviewer language; b) obtaining, by an interviewer digital electronic system, a ranked list of topics, the topics expressed in the interviewer language, the ranking being determined at least in part upon a respective probability associated with each topic; c) displaying by logic the ranked list of topics on an interviewer graphics screen that is included in the interviewer digital electronic system; d) obtaining by logic in the interviewer digital electronic system from a user interface on the interviewer graphics screen a topic selection from the ranked list; e) obtaining by an interviewee digital electronic system a first interviewee information item expressed in the interviewee language, said first interviewee information item being associated with the topic selection; f) transmitting the first interviewee information item in audio form using interviewee sound equipment associated with the interviewee digital electronic system g) wherein the interviewee sound equipment includes a headset, adapted to transformation between a head-mount configuration and a broadcast configuration, the transformation involving apivoting of an ear cup of the headset relative to a headband of the headset, wherein the headset is adapted to automatically limiting transmission of audio information to amplitudes not exceeding a head-mount maximum amplitude in the head-mount form and to amplitudes not exceeding a broadcast maximum amplitude, larger than the head-mount maximum amplitude, in the broadcast form, and wherein the interviewee sound equipment in the step of transmitting the first interviewee information item is the headset in head-mount configuration, the method further comprising: h) transmitting a second interviewee information item expressed in the interviewee language in audio form using the headset in broadcast configuration. | 7. A method, comprising: a) obtaining in digital form by logic a choice of an interviewer language, and a choice of an interviewee language that is distinct from the interviewer language; b) obtaining, by an interviewer digital electronic system, a ranked list of topics, the topics expressed in the interviewer language, the ranking being determined at least in part upon a respective probability associated with each topic; c) displaying by logic the ranked list of topics on an interviewer graphics screen that is included in the interviewer digital electronic system; d) obtaining by logic in the interviewer digital electronic system from a user interface on the interviewer graphics screen a topic selection from the ranked list; e) obtaining by an interviewee digital electronic system a first interviewee information item expressed in the interviewee language, said first interviewee information item being associated with the topic selection; f) transmitting the first interviewee information item in audio form using interviewee sound equipment associated with the interviewee digital electronic system g) wherein the interviewee sound equipment includes a headset, adapted to transformation between a head-mount configuration and a broadcast configuration, the transformation involving apivoting of an ear cup of the headset relative to a headband of the headset, wherein the headset is adapted to automatically limiting transmission of audio information to amplitudes not exceeding a head-mount maximum amplitude in the head-mount form and to amplitudes not exceeding a broadcast maximum amplitude, larger than the head-mount maximum amplitude, in the broadcast form, and wherein the interviewee sound equipment in the step of transmitting the first interviewee information item is the headset in head-mount configuration, the method further comprising: h) transmitting a second interviewee information item expressed in the interviewee language in audio form using the headset in broadcast configuration. 8. The method of claim 7 , further comprising: g) creating the ranked list of topics. | 0.913793 |
9,798,768 | 1 | 10 | 1. A method comprising: displaying on a client computing device, via a graphical user interface provided by an application server, a graph comprising one or more graph nodes and one or more graph edges; receiving input from the client computing device via the graphical user interface indicating a selection of the graph, wherein each graph node of the one or more graph nodes represents a data object type, and wherein each graph edge of the one or more graph edges represents a data object link; receiving, via the graphical user interface, a selection of the one or more graph edges; displaying, via the graphical user interface, an interface element which enables input of a link strength value which represents a condition on a number of occurrences of a relationship between two or more graph nodes; receiving, via the interface element of the graphical user interface, input specifying a particular link strength value; based at least on the two or more graph nodes, the one or more graph edges, and the particular link strength value, the application server transforming the graph into a query template; wherein the query template represents one or more database queries which, when executed by the application server, returns a result set from a database, wherein each result in said result set includes a first data object, comprising one or more first data object properties and a first data object type, corresponding to a first corresponding data object type of the one or more graph nodes of the graph, and a second data object, comprising one or more second data object properties and a second data object type, corresponding to a second corresponding data object type of the two or more graph nodes of the graph, wherein the first data object and the second data object satisfy the condition on the number of occurrences of the relationship between the first data object and the second data object represented by the particular link strength value; wherein a data object represents a collection of information as part of a data object model. | 1. A method comprising: displaying on a client computing device, via a graphical user interface provided by an application server, a graph comprising one or more graph nodes and one or more graph edges; receiving input from the client computing device via the graphical user interface indicating a selection of the graph, wherein each graph node of the one or more graph nodes represents a data object type, and wherein each graph edge of the one or more graph edges represents a data object link; receiving, via the graphical user interface, a selection of the one or more graph edges; displaying, via the graphical user interface, an interface element which enables input of a link strength value which represents a condition on a number of occurrences of a relationship between two or more graph nodes; receiving, via the interface element of the graphical user interface, input specifying a particular link strength value; based at least on the two or more graph nodes, the one or more graph edges, and the particular link strength value, the application server transforming the graph into a query template; wherein the query template represents one or more database queries which, when executed by the application server, returns a result set from a database, wherein each result in said result set includes a first data object, comprising one or more first data object properties and a first data object type, corresponding to a first corresponding data object type of the one or more graph nodes of the graph, and a second data object, comprising one or more second data object properties and a second data object type, corresponding to a second corresponding data object type of the two or more graph nodes of the graph, wherein the first data object and the second data object satisfy the condition on the number of occurrences of the relationship between the first data object and the second data object represented by the particular link strength value; wherein a data object represents a collection of information as part of a data object model. 10. The method of claim 1 , wherein the query template is an Extensible Markup Language (XML) file and includes one or more XML elements corresponding to one or more graph elements of the graph. | 0.72905 |
8,219,981 | 10 | 11 | 10. The computer program product as described in claim 8 further comprising: prior to loading the virtual machine code into the common memory: running a first application program; in response to running the first application program, identifying a call to a software effect corresponding to the software code data; and loading the software code data into the common memory, wherein the processing of the software code data occurs during the running of the first application program and wherein the processing is completed prior to the first program calling the software effect. | 10. The computer program product as described in claim 8 further comprising: prior to loading the virtual machine code into the common memory: running a first application program; in response to running the first application program, identifying a call to a software effect corresponding to the software code data; and loading the software code data into the common memory, wherein the processing of the software code data occurs during the running of the first application program and wherein the processing is completed prior to the first program calling the software effect. 11. The computer program product as described in claim 10 further comprising: receiving, at the first processor, the executable instructions resulting from the processing performed by the second processor, wherein the executable instructions are adapted to perform a multimedia effect; and performing the multimedia effect on the first processor by executing the received executable instructions. | 0.5 |
8,965,919 | 15 | 17 | 15. A non-transitory computer readable medium storing instructions, the instructions comprising: one or more instructions which, when executed by at least one processor, cause the at least one processor to: receive a text string that includes a plurality of terms; identify first context data relevant to the text string; form, based on the text string, a modified text string, the modified text string including a subset of the plurality of terms, the subset of the plurality of terms including fewer than all of the plurality of terms; identify second context data relevant to the modified text string; compare information associated with the first context data and information associated with the second context data; determine, based on the comparing, that the text string and the modified text string are associated with a similar concept; and store information indicating that the text string and the modified text string are associated with the similar concept based on determining that the text string and the modified text string are associated with the similar concept. | 15. A non-transitory computer readable medium storing instructions, the instructions comprising: one or more instructions which, when executed by at least one processor, cause the at least one processor to: receive a text string that includes a plurality of terms; identify first context data relevant to the text string; form, based on the text string, a modified text string, the modified text string including a subset of the plurality of terms, the subset of the plurality of terms including fewer than all of the plurality of terms; identify second context data relevant to the modified text string; compare information associated with the first context data and information associated with the second context data; determine, based on the comparing, that the text string and the modified text string are associated with a similar concept; and store information indicating that the text string and the modified text string are associated with the similar concept based on determining that the text string and the modified text string are associated with the similar concept. 17. The non-transitory computer readable medium of claim 15 , where the instructions further include: one or more instructions to receive another text string; one or more instructions to determine that the other text string and the modified text string are associated with the similar concept; and one or more instructions to determine one or more search results for the other text string by using the modified text string. | 0.5 |
9,966,064 | 13 | 18 | 13. A method for automatic speech recognition comprising: identifying at least one dialect of a standard form language in input data by distinguishing phones of the standard form language and the at least one dialect, the identifying further comprising generating a phone decoder for building an acoustic input training data set; analyzing the acoustic input data set to compute probabilities that portions of the input data set conform to a standard form language and probabilities that the portions of the input data set conform to at least one dialect of the standard form language; performing automatic speech recognition by applying, with at least one hardware processor, a standard form language model and at least one dialect language model to the input data set, the performing including weighting the models in accordance with each of the computed probabilities; and outputting speech recognition results obtained in accordance with said applying. | 13. A method for automatic speech recognition comprising: identifying at least one dialect of a standard form language in input data by distinguishing phones of the standard form language and the at least one dialect, the identifying further comprising generating a phone decoder for building an acoustic input training data set; analyzing the acoustic input data set to compute probabilities that portions of the input data set conform to a standard form language and probabilities that the portions of the input data set conform to at least one dialect of the standard form language; performing automatic speech recognition by applying, with at least one hardware processor, a standard form language model and at least one dialect language model to the input data set, the performing including weighting the models in accordance with each of the computed probabilities; and outputting speech recognition results obtained in accordance with said applying. 18. The method of claim 13 , wherein the analyzing comprises employing general phone representations for the standard form language and phone representations for the at least one dialect that are constructed by adapting the general phone representations. | 0.5 |
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