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8,428,944 | 2 | 3 | 2. A method according to claim 1 wherein compensated speech recognition is performed on both the first user utterance, resulting in a first compensated recognition result comprising a first confidence score, and the second user utterance, resulting in a second compensated recognition result comprising a second confidence score, and the compensated recognition result with the best confidence score is used. | 2. A method according to claim 1 wherein compensated speech recognition is performed on both the first user utterance, resulting in a first compensated recognition result comprising a first confidence score, and the second user utterance, resulting in a second compensated recognition result comprising a second confidence score, and the compensated recognition result with the best confidence score is used. 3. A method according to claim 2 wherein the compensated speech recognition takes the acoustic difference into account by assuming the second user utterance has an amplified or diminished acoustic difference. | 0.5 |
9,355,089 | 10 | 18 | 10. A computer usable program product comprising a computer readable storage device including computer usable code for intention detection in information, the computer usable code comprising: computer usable code for parsing a new information into a constituent set of complete grammatical constructs, the new information being in a language and relating to a subject matter domain; computer usable code for identifying, in a subset of the complete grammatical constructs, a set of linguistic styles of the language according to a subset of a set of word-style associations related to the language and independent of the subject matter domain; computer usable code for assigning a first weight to a first linguistic style and a second weight to a second linguistic style, the set of linguistic styles including the first linguistic style and the second linguistic style; computer usable code for constructing, using second set of linguistic styles of the language, and using a taxonomy of intentions present in a training information relating to the subject matter domain, a set of style-intention rules, the set of style-intention rules including the style-intention rule, the style-intention rule relating a selected intention from the taxonomy of intentions with a selected linguistic style in the set of linguistic styles to indicate that the selected intention is present where the selected linguistic style appears in any information related to the subject matter domain; computer usable code for mapping a first intention information to the first style using a first style-intention rule, and a second intention information to the second style using a second style-intention rule; and computer usable code for tagging a complete grammatical construct in the subset with the first intention information responsive to a weight associated with the first intention information exceeding an intention selection threshold. | 10. A computer usable program product comprising a computer readable storage device including computer usable code for intention detection in information, the computer usable code comprising: computer usable code for parsing a new information into a constituent set of complete grammatical constructs, the new information being in a language and relating to a subject matter domain; computer usable code for identifying, in a subset of the complete grammatical constructs, a set of linguistic styles of the language according to a subset of a set of word-style associations related to the language and independent of the subject matter domain; computer usable code for assigning a first weight to a first linguistic style and a second weight to a second linguistic style, the set of linguistic styles including the first linguistic style and the second linguistic style; computer usable code for constructing, using second set of linguistic styles of the language, and using a taxonomy of intentions present in a training information relating to the subject matter domain, a set of style-intention rules, the set of style-intention rules including the style-intention rule, the style-intention rule relating a selected intention from the taxonomy of intentions with a selected linguistic style in the set of linguistic styles to indicate that the selected intention is present where the selected linguistic style appears in any information related to the subject matter domain; computer usable code for mapping a first intention information to the first style using a first style-intention rule, and a second intention information to the second style using a second style-intention rule; and computer usable code for tagging a complete grammatical construct in the subset with the first intention information responsive to a weight associated with the first intention information exceeding an intention selection threshold. 18. The computer usable program product of claim 10 , wherein the computer usable code is stored in a computer readable storage device in a server data processing system, and wherein the computer usable code is downloaded over a network to a remote data processing system for use in a computer readable storage device associated with the remote data processing system. | 0.739377 |
10,067,937 | 1 | 3 | 1. A non-transitory computer-readable medium embodying program code executable in a first computing device that, when executed by at least one hardware processor of the first computing device, causes the first computing device to: execute an instance of a video messaging application to provide a live conference call between at least the first computing device and a second computing device, the conference call comprising audio and video communication generated through the first computing device and the second computing device; generate at least a portion of a data stream comprising audio data and video data during the live conference call, wherein the audio data embodies speech associated with a first language; transmit a signal to the second computing device to turn on an indicator that indicates that a language translation is being performed; cause a remote computing device to start the language translation using the audio data where the speech associated with the first language is translated to a translation output associated with a second language, wherein the language translation performed by the remote computing device comprises: converting the speech made in the first language to text; converting the text to the translation output made in the second language; determining a time delay needed for the remote computing device to complete the language translation where the speech made in the first language is translated to the translation output; and imposing the time delay in a video signal for transmission to the first computing device and the second computing device; determine that a predefined amount of the speech associated with the first language has been translated to the translation output associated with the second language sufficient to prevent a discontinuity in speech segments; and in response to the predefined amount of the speech having been translated to the translation output, using the video signal, render the translation output and the video data on at least the first computing device, wherein the video data is rendered in a display associated with the first computing device after an elapse of the time delay and completion of the language translation, wherein the translation output is rendered as text in the display or played as audio on the first computing device. | 1. A non-transitory computer-readable medium embodying program code executable in a first computing device that, when executed by at least one hardware processor of the first computing device, causes the first computing device to: execute an instance of a video messaging application to provide a live conference call between at least the first computing device and a second computing device, the conference call comprising audio and video communication generated through the first computing device and the second computing device; generate at least a portion of a data stream comprising audio data and video data during the live conference call, wherein the audio data embodies speech associated with a first language; transmit a signal to the second computing device to turn on an indicator that indicates that a language translation is being performed; cause a remote computing device to start the language translation using the audio data where the speech associated with the first language is translated to a translation output associated with a second language, wherein the language translation performed by the remote computing device comprises: converting the speech made in the first language to text; converting the text to the translation output made in the second language; determining a time delay needed for the remote computing device to complete the language translation where the speech made in the first language is translated to the translation output; and imposing the time delay in a video signal for transmission to the first computing device and the second computing device; determine that a predefined amount of the speech associated with the first language has been translated to the translation output associated with the second language sufficient to prevent a discontinuity in speech segments; and in response to the predefined amount of the speech having been translated to the translation output, using the video signal, render the translation output and the video data on at least the first computing device, wherein the video data is rendered in a display associated with the first computing device after an elapse of the time delay and completion of the language translation, wherein the translation output is rendered as text in the display or played as audio on the first computing device. 3. The non-transitory computer-readable medium of claim 1 , wherein the second language is identified based at least in part on a setting predefined in the instance of the video messaging application executing on the first computing device. | 0.597315 |
9,098,773 | 1 | 14 | 1. A method of detecting one or more objects in a three-dimensional point cloud scene, the method being implemented by a computer system that includes one or more processors configured to execute computer modules, the method comprising: receiving, by one or more processors, a three-dimensional point cloud scene, the three-dimensional point cloud scene comprising a plurality of points; classifying, by the one or more processors, at least a portion of the plurality of points in the three-dimensional point cloud into two or more categories by applying a classifying-oriented three-dimensional local descriptor and learning-based classifier; extracting, by the one or more processors, from the three-dimensional point cloud scene one or more clusters of points utilizing the two or more categories by applying at least one of segmenting and clustering; and matching, by the one or more processors, the extracted clusters with objects within a library by applying a matching-oriented three-dimensional local descriptor. | 1. A method of detecting one or more objects in a three-dimensional point cloud scene, the method being implemented by a computer system that includes one or more processors configured to execute computer modules, the method comprising: receiving, by one or more processors, a three-dimensional point cloud scene, the three-dimensional point cloud scene comprising a plurality of points; classifying, by the one or more processors, at least a portion of the plurality of points in the three-dimensional point cloud into two or more categories by applying a classifying-oriented three-dimensional local descriptor and learning-based classifier; extracting, by the one or more processors, from the three-dimensional point cloud scene one or more clusters of points utilizing the two or more categories by applying at least one of segmenting and clustering; and matching, by the one or more processors, the extracted clusters with objects within a library by applying a matching-oriented three-dimensional local descriptor. 14. The method according to claim 1 , wherein clustering is applied by evaluating a linearity of each cluster by an absolute value of a correlation coefficient in a least square fitting on three-dimensional points of three projections in three orthogonal planes. | 0.688095 |
8,932,229 | 1 | 5 | 1. An apparatus for recognizing an emotion, the apparatus comprising: an input signal generation unit configured to receive a plurality of heart rate data and generate an input signal; a signal classification unit configured to classify prospective input signals into groups; and an emotion recognition unit configured to find a group to which the input signal generated by the input signal generation unit belongs, among the groups classified by the signal classification unit, and recognize a user emotion corresponding to the found group, wherein the input signal generation unit checks whether a current input heart rate differs from a previously input heart rate and represents an increase or a decrease of the current heart rate in the input signal with a binary form sequence. | 1. An apparatus for recognizing an emotion, the apparatus comprising: an input signal generation unit configured to receive a plurality of heart rate data and generate an input signal; a signal classification unit configured to classify prospective input signals into groups; and an emotion recognition unit configured to find a group to which the input signal generated by the input signal generation unit belongs, among the groups classified by the signal classification unit, and recognize a user emotion corresponding to the found group, wherein the input signal generation unit checks whether a current input heart rate differs from a previously input heart rate and represents an increase or a decrease of the current heart rate in the input signal with a binary form sequence. 5. The apparatus of claim 1 , wherein the signal classification unit generates a mapping table in which the prospective input signals are classified in groups. | 0.685771 |
8,799,793 | 8 | 10 | 8. A physical computer readable medium including computer executable instructions that, when executed on a computer system including a display, provide an editor interface facilitating creating customized definitions for user interfaces provided by a field device editor, the computer executable instructions facilitating performing the steps of: obtaining, from a device definition database, a first device template corresponding to a device type, wherein the first device template includes a first definition of an editor interface for the device type; modifying the first definition of the editor interface via a customization tool associated with the editor interface for the device type, thereby rendering a modified version of the first definition of the editor interface; wherein the modifying step comprises customizing a download operation for commissioning device instances; and storing the modified version. | 8. A physical computer readable medium including computer executable instructions that, when executed on a computer system including a display, provide an editor interface facilitating creating customized definitions for user interfaces provided by a field device editor, the computer executable instructions facilitating performing the steps of: obtaining, from a device definition database, a first device template corresponding to a device type, wherein the first device template includes a first definition of an editor interface for the device type; modifying the first definition of the editor interface via a customization tool associated with the editor interface for the device type, thereby rendering a modified version of the first definition of the editor interface; wherein the modifying step comprises customizing a download operation for commissioning device instances; and storing the modified version. 10. The computer-readable medium of claim 8 wherein the customization tool is invoked via a control exposed by the editor interface for the device type. | 0.512821 |
7,610,194 | 1 | 9 | 1. A computer-implemented process for reordering items in a database to be retrieved for display to a user, comprising the steps of: storing a plurality of words in a linguistic database (LDB), said plurality of words ordered in said LDB according to a predefined linguistics frequency of use model; accepting with a processor user input from a keyboard, said user input comprising at least one keypress; retrieving any words from said LDB that matches at least one letter corresponding to said at least one keypress; displaying a list of said retrieved words as ordered in said LDB; accepting a user-defined word as input by said user; storing said user-defined word in a user database (UDB); assigning a frequency count to said user-defined word; storing said frequency count for said user-defined word in said UDB; enabling said user to select a word from said displayed list; assigning a frequency count to every selected word in a non first order position in said displayed list and a frequency count to a first order word, if a non first order word is selected, said frequency count for said non first order selected word being different than said frequency count for said first order non selected word; storing said frequency count of each word in association with each word in said UDB; accepting a subsequent user input from a keyboard, said user input comprising at least one keypress; retrieving any words from said LDB and any user-defined words from said UDB that match at least one letter corresponding to said at least one keypress; if more than one word from any of said LDB and said UDB is retrieved and at least one retrieved word is associated with a frequency count, dynamically reordering for display said retrieved words as a function of said predefined linguistics frequency of use model and each frequency count associated with any of said retrieved words; displaying a list of said reordered matching words if more than one word matches said user's subsequent input; and updating a frequency count associated with a word each time a non first order word is selected from a displayed list of matching words. | 1. A computer-implemented process for reordering items in a database to be retrieved for display to a user, comprising the steps of: storing a plurality of words in a linguistic database (LDB), said plurality of words ordered in said LDB according to a predefined linguistics frequency of use model; accepting with a processor user input from a keyboard, said user input comprising at least one keypress; retrieving any words from said LDB that matches at least one letter corresponding to said at least one keypress; displaying a list of said retrieved words as ordered in said LDB; accepting a user-defined word as input by said user; storing said user-defined word in a user database (UDB); assigning a frequency count to said user-defined word; storing said frequency count for said user-defined word in said UDB; enabling said user to select a word from said displayed list; assigning a frequency count to every selected word in a non first order position in said displayed list and a frequency count to a first order word, if a non first order word is selected, said frequency count for said non first order selected word being different than said frequency count for said first order non selected word; storing said frequency count of each word in association with each word in said UDB; accepting a subsequent user input from a keyboard, said user input comprising at least one keypress; retrieving any words from said LDB and any user-defined words from said UDB that match at least one letter corresponding to said at least one keypress; if more than one word from any of said LDB and said UDB is retrieved and at least one retrieved word is associated with a frequency count, dynamically reordering for display said retrieved words as a function of said predefined linguistics frequency of use model and each frequency count associated with any of said retrieved words; displaying a list of said reordered matching words if more than one word matches said user's subsequent input; and updating a frequency count associated with a word each time a non first order word is selected from a displayed list of matching words. 9. The process of claim 1 , further comprising the step of: resolving frequency collisions when two words in said list of reordered words are associated with equal frequency counts by ordering said word having a higher initial ordering in said LDB first. | 0.573826 |
8,768,910 | 9 | 13 | 9. A system comprising: one or more devices to: obtain a search query, obtain search results based on the search query and a search index that includes information regarding documents, determine a category associated with a set of results of the search results, identify candidate queries for the search query, determine whether the category matches one of the candidate queries or one or more terms of the search query, determine a first ratio based on a first quantity of times that the search query is submitted to a web search engine interface, determine a second ratio based on a second quantity of times that the search query is submitted to a specialized search engine interface that is used to search for information associated with the category or to search for information associated with news, identify, based on the first ratio and the second ratio, the search query as a media query associated with the category when the category matches the one of the candidate queries, and provide a result document based on the media query and based on identifying the search query as the media query. | 9. A system comprising: one or more devices to: obtain a search query, obtain search results based on the search query and a search index that includes information regarding documents, determine a category associated with a set of results of the search results, identify candidate queries for the search query, determine whether the category matches one of the candidate queries or one or more terms of the search query, determine a first ratio based on a first quantity of times that the search query is submitted to a web search engine interface, determine a second ratio based on a second quantity of times that the search query is submitted to a specialized search engine interface that is used to search for information associated with the category or to search for information associated with news, identify, based on the first ratio and the second ratio, the search query as a media query associated with the category when the category matches the one of the candidate queries, and provide a result document based on the media query and based on identifying the search query as the media query. 13. The system of claim 9 , where the information associated with the category includes information associated with books, and where, when identifying the search query as the media query, the one or more devices are to: determine a third ratio based on the first ratio and the second ratio, and identify the search query as the media query, associated with a book type of media, when the third ratio satisfies a particular threshold. | 0.528322 |
9,280,908 | 12 | 14 | 12. The computer program product of claim 11 , wherein modifying, using a machine learning technique, at least one of logic or configuration parameters of the QA system comprises: presenting the candidate answers via a user interface comprising elements for receiving user feedback ratings of the candidate answers; receiving, via the user interface, user input specifying user feedback rating values for at least one of the candidate answers; and modifying at least one of the logic or configuration parameters of the QA system based on the received user input specifying the user feedback rating values. | 12. The computer program product of claim 11 , wherein modifying, using a machine learning technique, at least one of logic or configuration parameters of the QA system comprises: presenting the candidate answers via a user interface comprising elements for receiving user feedback ratings of the candidate answers; receiving, via the user interface, user input specifying user feedback rating values for at least one of the candidate answers; and modifying at least one of the logic or configuration parameters of the QA system based on the received user input specifying the user feedback rating values. 14. The computer program product of claim 12 , wherein modifying at least one of the logic or configuration parameters of the QA system, comprises, for each candidate answer in the candidate answers: determining a difference between the candidate answer acid the known correct answer; determining a user feedback rating value corresponding to the candidate answer; and modifying logic or configuration parameters of the QA system so as to modify a computation of a confidence measure associated with the candidate answer based on both the determined difference and the user feedback rating value. | 0.5 |
8,855,998 | 6 | 9 | 6. A computer program product for parsing a name, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, wherein the computer readable program code, when executed by a processor of a computer, is configured to perform: receiving a name to be parsed; identifying a culture of the name; identifying one or more name phrases from the name; associating the name phrases with fields, wherein each of the fields is one of a given name field and a surname field; identifying statistics for the one or more name phrases; providing different parsing techniques that parse different types of name elements differently within at least one of the fields; determining whether to select a first parsing technique among the different parsing techniques based on the culture; in response to determining that the first parsing technique is to be performed selected, parsing the name using the statistics and the first parsing technique to parse at least one field of the name into the different types of name elements based on the culture; providing the name phrases in the given name field and the surname field; and for the at least one field of the name, providing the name elements and their types; and in response to determining that the first parsing technique is not to be selected, parsing the name using the statistics and a second parsing technique. | 6. A computer program product for parsing a name, the computer program product comprising: a non-transitory computer readable storage medium having computer readable program code embodied therewith, wherein the computer readable program code, when executed by a processor of a computer, is configured to perform: receiving a name to be parsed; identifying a culture of the name; identifying one or more name phrases from the name; associating the name phrases with fields, wherein each of the fields is one of a given name field and a surname field; identifying statistics for the one or more name phrases; providing different parsing techniques that parse different types of name elements differently within at least one of the fields; determining whether to select a first parsing technique among the different parsing techniques based on the culture; in response to determining that the first parsing technique is to be performed selected, parsing the name using the statistics and the first parsing technique to parse at least one field of the name into the different types of name elements based on the culture; providing the name phrases in the given name field and the surname field; and for the at least one field of the name, providing the name elements and their types; and in response to determining that the first parsing technique is not to be selected, parsing the name using the statistics and a second parsing technique. 9. The computer program product of claim 6 , wherein the computer readable program code, when executed by the processor of the computer, is configured to perform: determining whether the parsed name is valid; and in response to determining that the parsed name is not valid, reordering name phrases of the name to form a reordered name; determining whether to perform the first parsing technique; in response to determining that the first parsing technique is to be performed, parsing the reordered name using the statistics and the first parsing technique; and in response to determining that the first parsing technique is not to be performed, parsing the reordered name using the statistics and a second parsing technique. | 0.5 |
8,392,173 | 7 | 10 | 7. A method for establishing language preferences, comprising: accessing a storage device on a server processing device to identify language preference for a plurality of users and to identify a preferred language from a particular user of the plurality of users; saving an indication of the preferred language; and receiving and providing authorization information for accessing an instant message account of the particular user. | 7. A method for establishing language preferences, comprising: accessing a storage device on a server processing device to identify language preference for a plurality of users and to identify a preferred language from a particular user of the plurality of users; saving an indication of the preferred language; and receiving and providing authorization information for accessing an instant message account of the particular user. 10. The method of claim 7 , further comprising providing a set of preferred languages for selection by the particular user. | 0.625 |
9,936,201 | 31 | 32 | 31. The device of claim 30 , wherein the video coder is further configured to: select the context from a group of at least four possible contexts. | 31. The device of claim 30 , wherein the video coder is further configured to: select the context from a group of at least four possible contexts. 32. The device of claim 31 , wherein the group of at least four possible contexts comprises six possible contexts. | 0.5 |
9,275,046 | 1 | 13 | 1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: providing an interface for selecting a vertical language text translation box corresponding to one or more words in the first language, wherein the first language is an Asian language comprising a plurality of characters having a vertical alignment; cropping a frame of the real-time video feed of the one or more words of the first language to fit inside the vertical language text translation box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments; performing character recognition on the merged character segments to produce a plurality of recognized characters; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language in augmented reality in the real-time video feed. | 1. A method for providing one or more translations in a real-time video feed of a first language into a second language, comprising: providing an interface for selecting a vertical language text translation box corresponding to one or more words in the first language, wherein the first language is an Asian language comprising a plurality of characters having a vertical alignment; cropping a frame of the real-time video feed of the one or more words of the first language to fit inside the vertical language text translation box to produce a cropped frame; performing character segment detection on the cropped frame to produce a plurality character segments; performing character merging on the character segments to produce a plurality of merged character segments; performing character recognition on the merged character segments to produce a plurality of recognized characters; performing one or more translations on the recognized characters of the first language into one or more translated words of the second language; and displaying the translated words of the second language in augmented reality in the real-time video feed. 13. The method of claim 1 , further comprising: moving the one or more translated words of the second language when a mobile device is moved without recalculating the one or more translations. | 0.829787 |
8,117,208 | 1 | 16 | 1. A method comprising: (a) receiving an input query q including one or more keywords and one or more entity types; (b) searching a database D that indexes keywords and instances of entities having entity types in a collection of documents, the searching including searching for documents having the keywords and entities with the entity types in the input query; (c) aggregating a respective score p o (q(t)) for each q(t) of a plurality of resultant entity tuples, where t consists of entities of the types in the input query, across the plurality of document d in the database D, where p(d) is a discriminative measure of d and p(q(t)|d) a local score of q(t), as follows: p o ( q ( t ) ) = p ( q ( t ) | D ) = ∑ d ∈ D p ( d ) · p ( q ( t ) | d ) ; (d) normalizing the aggregated scores by statistically validating the significance of said score over the database, each respective normalized score providing a ranking of a respective entity tuple, relative to other entity tuples, as an answer to the input query; and (e) outputting a list, including a subset of the entity tuples having the highest normalized scores among the plurality of entity tuples, to a storage or display device or a network. | 1. A method comprising: (a) receiving an input query q including one or more keywords and one or more entity types; (b) searching a database D that indexes keywords and instances of entities having entity types in a collection of documents, the searching including searching for documents having the keywords and entities with the entity types in the input query; (c) aggregating a respective score p o (q(t)) for each q(t) of a plurality of resultant entity tuples, where t consists of entities of the types in the input query, across the plurality of document d in the database D, where p(d) is a discriminative measure of d and p(q(t)|d) a local score of q(t), as follows: p o ( q ( t ) ) = p ( q ( t ) | D ) = ∑ d ∈ D p ( d ) · p ( q ( t ) | d ) ; (d) normalizing the aggregated scores by statistically validating the significance of said score over the database, each respective normalized score providing a ranking of a respective entity tuple, relative to other entity tuples, as an answer to the input query; and (e) outputting a list, including a subset of the entity tuples having the highest normalized scores among the plurality of entity tuples, to a storage or display device or a network. 16. The method of claim 1 , further comprising providing an index of the document database before performing the searching. | 0.839005 |
9,305,091 | 10 | 11 | 10. A non-transitory computer readable storage medium storing one or more programs, for processing information about documents in a collection of linked documents, for execution by a computer system, the one or more programs comprising instructions for: crawling at least a subset of the documents in the collection of linked documents; extracting, from the crawled subset of the documents in the collection of linked documents, information concerning a plurality of outbound links between documents in the collection of linked documents; generating an anchor map based on the information extracted from the collection of linked documents that concerns the plurality of outbound links between documents in the collection of linked documents, wherein the anchor map comprises a plurality of anchor records, and wherein a respective anchor record of the plurality of anchor records identifies: (A) a respective target document, wherein the respective target document is pointed to by one or more outbound links among the plurality of outbound links, (B) a list of inbound links identifying a set of source documents in the collection of linked documents that contain the one or more outbound links to the respective target document, and (C) a list of annotations corresponding to the respective target document, wherein a respective annotation in the list of annotations includes a text passage extracted from a respective source document of the set of source documents that is determined from text of the respective source document, and wherein the text passage is within a predetermined distance of a respective outbound link, from among the one or more outbound links pointing to the respective target document, in the respective source document that points to the respective target document; and processing at least a subset of the plurality of anchor records, including, for each anchor record in the subset of the plurality of anchor records, adding to a document index entries for terms in the list of annotations in the anchor record, wherein the entries correspond to the target document identified by the anchor record. | 10. A non-transitory computer readable storage medium storing one or more programs, for processing information about documents in a collection of linked documents, for execution by a computer system, the one or more programs comprising instructions for: crawling at least a subset of the documents in the collection of linked documents; extracting, from the crawled subset of the documents in the collection of linked documents, information concerning a plurality of outbound links between documents in the collection of linked documents; generating an anchor map based on the information extracted from the collection of linked documents that concerns the plurality of outbound links between documents in the collection of linked documents, wherein the anchor map comprises a plurality of anchor records, and wherein a respective anchor record of the plurality of anchor records identifies: (A) a respective target document, wherein the respective target document is pointed to by one or more outbound links among the plurality of outbound links, (B) a list of inbound links identifying a set of source documents in the collection of linked documents that contain the one or more outbound links to the respective target document, and (C) a list of annotations corresponding to the respective target document, wherein a respective annotation in the list of annotations includes a text passage extracted from a respective source document of the set of source documents that is determined from text of the respective source document, and wherein the text passage is within a predetermined distance of a respective outbound link, from among the one or more outbound links pointing to the respective target document, in the respective source document that points to the respective target document; and processing at least a subset of the plurality of anchor records, including, for each anchor record in the subset of the plurality of anchor records, adding to a document index entries for terms in the list of annotations in the anchor record, wherein the entries correspond to the target document identified by the anchor record. 11. The non-transitory computer readable storage medium of claim 10 , wherein a respective entry in the list of annotations for the respective anchor record in the anchor maps includes a text passage and a list of attributes of the text passage. | 0.780859 |
8,972,416 | 12 | 13 | 12. The system of claim 11 , wherein the application further comprises: logic that obtains a cue via the administrative user interface; logic that identifies at least one other time code; wherein the cue corresponds to the content anomaly associated with the at least one other time code; and logic that preforms another action to the other portion of the content item associated with the at least one other time code. | 12. The system of claim 11 , wherein the application further comprises: logic that obtains a cue via the administrative user interface; logic that identifies at least one other time code; wherein the cue corresponds to the content anomaly associated with the at least one other time code; and logic that preforms another action to the other portion of the content item associated with the at least one other time code. 13. The system of claim 12 , wherein the other action comprises logic that removes the other portion of the content item. | 0.5 |
8,923,491 | 21 | 22 | 21. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving a spoken communication from a first user, the spoken communication comprising an address; extracting, via a processor, the address automatically from the spoken communication, to yield an extracted address; displaying to a second user a selection of addresses, the selection of addresses comprising the extracted address and an alternate address for the first user, the alternate address being stored in a contacts list, the selection of addresses displayed in an order prioritizing a preferred address of the extracted address and the alternate address, where the preferred address is determined based on a user history of the first user by the computing device; and receiving from the second user a selection of a selected address from the selection of addresses to initiate communication with the first user. | 21. A computer-readable storage device having instructions stored which, when executed by a computing device, cause the computing device to perform operations comprising: receiving a spoken communication from a first user, the spoken communication comprising an address; extracting, via a processor, the address automatically from the spoken communication, to yield an extracted address; displaying to a second user a selection of addresses, the selection of addresses comprising the extracted address and an alternate address for the first user, the alternate address being stored in a contacts list, the selection of addresses displayed in an order prioritizing a preferred address of the extracted address and the alternate address, where the preferred address is determined based on a user history of the first user by the computing device; and receiving from the second user a selection of a selected address from the selection of addresses to initiate communication with the first user. 22. The computer-readable storage device of claim 21 , wherein the extracted address is displayed in the selection of addresses during playback of the spoken communication. | 0.856427 |
4,670,848 | 1 | 13 | 1. An artificial intelligence system for accepting a statement, understanding the meaning of the statement and making a response to the statement based upon at least a partial understanding of the statement comprising: (a) an input means for providing an initial statement and additional statements which provide information for determining the response to the statement; (b) an output means for providing any response to the initial statement and any inquiries requesting additional statements to be inputted on the input means; (c) a knowledge base having a plurality of addressable nodes, each node representing a current concept of the initial statement and having stored thereat either zero patterns or, if any, at least two sets of patterns with each set of patterns identifying a distinct new node within the knowledge base where a new concept of the initial statement is represented and, optionally, a response based upon at least a partial understanding of the initial statement and the new concept of the initial statement augmenting the current and previous concepts and additionally optionally identifying a final concept; (d) means for storing the initial statement and each additional statement and any sets of patterns fetched from the node of the knowledge base associated with the current concept; (e) means for matching the initial statement and each additional statement which has been inputted by the input means with sets of patterns which are stored from the node associated with the current concept to determine when a match occurs between any one of the stored statements and any one of the patterns stored within the sets of patterns for identifying the new concept associated with the matched pattern; and (f) a control means for controlling the inputting of statements, the outputting of any response to the initial statement and any inquiries requesting the input of additional statements, the storage of the statements and patterns fetched from the node associated with the current concept by the storage means, the transmission of the statements and any patterns from the node associated with the current concept from the storage means to the means for matching and the transmission of an identification of the new node to the knowledge base. | 1. An artificial intelligence system for accepting a statement, understanding the meaning of the statement and making a response to the statement based upon at least a partial understanding of the statement comprising: (a) an input means for providing an initial statement and additional statements which provide information for determining the response to the statement; (b) an output means for providing any response to the initial statement and any inquiries requesting additional statements to be inputted on the input means; (c) a knowledge base having a plurality of addressable nodes, each node representing a current concept of the initial statement and having stored thereat either zero patterns or, if any, at least two sets of patterns with each set of patterns identifying a distinct new node within the knowledge base where a new concept of the initial statement is represented and, optionally, a response based upon at least a partial understanding of the initial statement and the new concept of the initial statement augmenting the current and previous concepts and additionally optionally identifying a final concept; (d) means for storing the initial statement and each additional statement and any sets of patterns fetched from the node of the knowledge base associated with the current concept; (e) means for matching the initial statement and each additional statement which has been inputted by the input means with sets of patterns which are stored from the node associated with the current concept to determine when a match occurs between any one of the stored statements and any one of the patterns stored within the sets of patterns for identifying the new concept associated with the matched pattern; and (f) a control means for controlling the inputting of statements, the outputting of any response to the initial statement and any inquiries requesting the input of additional statements, the storage of the statements and patterns fetched from the node associated with the current concept by the storage means, the transmission of the statements and any patterns from the node associated with the current concept from the storage means to the means for matching and the transmission of an identification of the new node to the knowledge base. 13. An artificial intelligence system in accordance with claim 1 wherein: (a) the natural language statements are stored in the means for storing in the form of a list in the order of their input; and (b) the means for matching matches the list of statements with the sets of patterns in a last in first out order. | 0.733898 |
7,996,379 | 26 | 27 | 26. The computer program product of claim 21 , wherein determining relationships among the documents based on the local term relationships comprises: selecting at least a subset of the local term relationships in accordance with predefined criteria; and determining the document relationships using the selected local term relationships. | 26. The computer program product of claim 21 , wherein determining relationships among the documents based on the local term relationships comprises: selecting at least a subset of the local term relationships in accordance with predefined criteria; and determining the document relationships using the selected local term relationships. 27. The computer program product of claim 26 , the operations further comprising determining a magnitude for each of the identified local term relationships, wherein a magnitude for a respective local term relationship is determined based on at least one of a difference between positions in the document of the pair of terms in the respective local term relationship, and positions in the document of the pair of terms in the respective local term relationship; and wherein selecting at least a subset of the local term relationships in accordance with predefined criteria comprises selecting the subset of the local term relationships based on the magnitudes of the local term relationships. | 0.5 |
9,569,540 | 17 | 19 | 17. A method for providing uniform resource locators (URLs) related to search results determined for search queries input by users, the method comprising: receiving a search query, the search query indicating the user intends to engage in a particular task comprising one of shopping, social networking, researching a topic, reading news, reviewing blogs, searching for reviews, or booking a trip; identifying a plurality of search results that satisfies the search query; identifying a related URL that is related to one of the plurality of search results; providing an indication of the related URL in association with an identifier for the at least one search result; providing a control that corresponds with the related URL, the control permitting user input of an additional query; receiving, via the control, user input of the an additional query; and searching web site content associated with the related URL to determine if any of the website content matches the additional query. | 17. A method for providing uniform resource locators (URLs) related to search results determined for search queries input by users, the method comprising: receiving a search query, the search query indicating the user intends to engage in a particular task comprising one of shopping, social networking, researching a topic, reading news, reviewing blogs, searching for reviews, or booking a trip; identifying a plurality of search results that satisfies the search query; identifying a related URL that is related to one of the plurality of search results; providing an indication of the related URL in association with an identifier for the at least one search result; providing a control that corresponds with the related URL, the control permitting user input of an additional query; receiving, via the control, user input of the an additional query; and searching web site content associated with the related URL to determine if any of the website content matches the additional query. 19. The method of claim 17 further comprising navigating to the related URL upon user selection of the related URL. | 0.592199 |
7,765,241 | 10 | 13 | 10. A system for referencing a pre-defined data type definition associated with an entity to define target data types describing relationships of the entity, said system comprising: a memory area for storing a markup language schema corresponding to a model representing objects in a system; and a processor configured to execute computer-executable instructions for: identifying a data type definition from the markup language schema, said data type definition corresponding to a reference entity in the model; defining one or more elements describing one or more entities expected to be associated with the reference entity in the model; identifying predefined entity relationships for use in associating the expected entities with the reference entity, said expected entities having a target data type definition associated therewith, said reference entity having a reference data type definition associated therewith, said expected entities not being required entities for the target data type definition; associating the defined elements and the defined relationships with a tag; inserting the tag with the associated elements and relationships into an instance of the target data type definition in the markup language schema corresponding to the model; and locating the instance of the target data type definition in the reference data type definition to relate the expected entities with the reference entity in the model. | 10. A system for referencing a pre-defined data type definition associated with an entity to define target data types describing relationships of the entity, said system comprising: a memory area for storing a markup language schema corresponding to a model representing objects in a system; and a processor configured to execute computer-executable instructions for: identifying a data type definition from the markup language schema, said data type definition corresponding to a reference entity in the model; defining one or more elements describing one or more entities expected to be associated with the reference entity in the model; identifying predefined entity relationships for use in associating the expected entities with the reference entity, said expected entities having a target data type definition associated therewith, said reference entity having a reference data type definition associated therewith, said expected entities not being required entities for the target data type definition; associating the defined elements and the defined relationships with a tag; inserting the tag with the associated elements and relationships into an instance of the target data type definition in the markup language schema corresponding to the model; and locating the instance of the target data type definition in the reference data type definition to relate the expected entities with the reference entity in the model. 13. The system of claim 10 , wherein the processor is further configured to execute computer-executable instructions for displaying the reference data type definition in the model. | 0.705882 |
8,315,870 | 9 | 10 | 9. A speech recognition apparatus according to claim 4 , wherein said prosodic recognition unit performs prosodic recognition using a tone model which is modeled using a time-rate change of a pitch in the vowel interval as a feature amount and a context model created by modeling context information serving as prosodic history information. | 9. A speech recognition apparatus according to claim 4 , wherein said prosodic recognition unit performs prosodic recognition using a tone model which is modeled using a time-rate change of a pitch in the vowel interval as a feature amount and a context model created by modeling context information serving as prosodic history information. 10. A speech recognition apparatus according to claim 9 , wherein the context model is created by modeling a chain probability of a tone of a vowel. | 0.5 |
8,934,652 | 8 | 12 | 8. The method of claim 1 , further comprising: audibly notifying the user to view the speaker-related information on a display device. | 8. The method of claim 1 , further comprising: audibly notifying the user to view the speaker-related information on a display device. 12. The method of claim 8 , wherein the audibly notifying the user includes: audibly notifying the user in a manner that is not audible to the speaker. | 0.719331 |
8,073,818 | 1 | 8 | 1. In a computing environment, a computer-implemented method comprising: performing near-duplicate image retrieval with a computer processor, including detecting, with the computer processor, visual patterns in images, representing the visual patterns as visual pattern vectors, and using the visual pattern vectors and visual word vectors to determine, with the computer processor, similarity between images by ranking database images according to a similarity of each given database image with a query image, including by obtaining a query visual pattern vector for the query image, and for each given image, determining a visual pattern vector and computing a visual pattern-based similarity score for the given image by selecting a set of most similar database images based on a ranking of the database images according to the visual pattern-based similarity scores, and re-ranking the set of most similar database images by evaluating similarity for each specific image in the set of most similar database images via a visual word vector corresponding to the specific image and a query visual word vector corresponding to the query image. | 1. In a computing environment, a computer-implemented method comprising: performing near-duplicate image retrieval with a computer processor, including detecting, with the computer processor, visual patterns in images, representing the visual patterns as visual pattern vectors, and using the visual pattern vectors and visual word vectors to determine, with the computer processor, similarity between images by ranking database images according to a similarity of each given database image with a query image, including by obtaining a query visual pattern vector for the query image, and for each given image, determining a visual pattern vector and computing a visual pattern-based similarity score for the given image by selecting a set of most similar database images based on a ranking of the database images according to the visual pattern-based similarity scores, and re-ranking the set of most similar database images by evaluating similarity for each specific image in the set of most similar database images via a visual word vector corresponding to the specific image and a query visual word vector corresponding to the query image. 8. The computer-implemented method of claim 1 further comprising, mining quantitative patterns from database images, including images in which the patterns contain duplicate items. | 0.83871 |
9,740,731 | 1 | 6 | 1. A method of automatically sorting sports related news stories by their temporal characteristics using a computing system comprising: a) identifying a first sporting event; wherein said first sporting event is assigned by the computing system to a plurality of different event status states each representing a different temporal period within a temporal sequence defined for such first sporting event; b) analyzing a first electronic document describing said first sporting event with the computing system to identify first content snippets determinative of a first status state of said sporting event relative to completion and/or resolution; c) analyzing a second electronic document with second content snippets describing a second status state for said first sporting event with the computing system; and d) determining which of said first and second electronic documents contains content describing a more current status of said sporting event by comparing said first status state to said second status state and generating an output with the computing system indicating which of said electronic documents describes the more current status; wherein changes in corresponding content snippets relating to completion and/or resolution of such first sporting event are tracked between documents and used by the computing system to derive a relative temporal relationship between said first electronic document and said second electronic document. | 1. A method of automatically sorting sports related news stories by their temporal characteristics using a computing system comprising: a) identifying a first sporting event; wherein said first sporting event is assigned by the computing system to a plurality of different event status states each representing a different temporal period within a temporal sequence defined for such first sporting event; b) analyzing a first electronic document describing said first sporting event with the computing system to identify first content snippets determinative of a first status state of said sporting event relative to completion and/or resolution; c) analyzing a second electronic document with second content snippets describing a second status state for said first sporting event with the computing system; and d) determining which of said first and second electronic documents contains content describing a more current status of said sporting event by comparing said first status state to said second status state and generating an output with the computing system indicating which of said electronic documents describes the more current status; wherein changes in corresponding content snippets relating to completion and/or resolution of such first sporting event are tracked between documents and used by the computing system to derive a relative temporal relationship between said first electronic document and said second electronic document. 6. The method of claim 1 wherein advertising is presented to viewers of said first or second electronic documents based on a temporal sequence identified for such electronic documents. | 0.72619 |
9,860,337 | 9 | 10 | 9. The method of claim 6 , wherein the computing system acts as an intermediary between client computing devices and content sources. | 9. The method of claim 6 , wherein the computing system acts as an intermediary between client computing devices and content sources. 10. The method of claim 9 , wherein generating opinion data comprises retrieving at least a portion of the plurality of content pages in response to content requests received from client computing devices. | 0.5 |
9,208,405 | 1 | 6 | 1. A computer-implemented feature extraction method for classifying pixels of a digitized pathology image, the method comprising: generating a plurality of characterized pixels from a digitized pathology image; determining in a first layer feature analysis a plurality of first layer confidence scores based on the plurality of characterized pixels, wherein the confidence scores represent a first likelihood of each pixel belonging to a specific classification; determining in a second layer feature analysis a plurality of final recognition scores based on the plurality of characterized pixels and the plurality of first layer confidence scores by applying a second layer model to the plurality of first layer confidence scores, wherein the second layer model is selected from a plurality of second layer models each of which is targeted to perform a specific classification task, wherein the recognition scores represent a final likelihood of each pixel belonging to a specific classification; and classifying part or all of the digitized pathology image based on the final recognition scores, wherein each pixel of the plurality of pixels is labeled with a ground truth; each first layer model from among a plurality of first layer models is generated by machine-learning algorithms based on a correspondence between the ground truth of each pixel of the plurality of pixels and feature descriptor values of a feature of each pixel of the plurality of pixels corresponding to a designated feature type from among a plurality of feature types; and a different first layer model is generated to correspond to each feature type from among the plurality of feature types. | 1. A computer-implemented feature extraction method for classifying pixels of a digitized pathology image, the method comprising: generating a plurality of characterized pixels from a digitized pathology image; determining in a first layer feature analysis a plurality of first layer confidence scores based on the plurality of characterized pixels, wherein the confidence scores represent a first likelihood of each pixel belonging to a specific classification; determining in a second layer feature analysis a plurality of final recognition scores based on the plurality of characterized pixels and the plurality of first layer confidence scores by applying a second layer model to the plurality of first layer confidence scores, wherein the second layer model is selected from a plurality of second layer models each of which is targeted to perform a specific classification task, wherein the recognition scores represent a final likelihood of each pixel belonging to a specific classification; and classifying part or all of the digitized pathology image based on the final recognition scores, wherein each pixel of the plurality of pixels is labeled with a ground truth; each first layer model from among a plurality of first layer models is generated by machine-learning algorithms based on a correspondence between the ground truth of each pixel of the plurality of pixels and feature descriptor values of a feature of each pixel of the plurality of pixels corresponding to a designated feature type from among a plurality of feature types; and a different first layer model is generated to correspond to each feature type from among the plurality of feature types. 6. The method of claim 1 , wherein the second layer feature analysis further comprises: determining each of the plurality of final recognition scores based on a second layer model and the plurality of first layer confidence scores. | 0.786111 |
9,626,581 | 6 | 7 | 6. The method of claim 1 , wherein the plurality of feature cues is generated by at least a first plurality of detectors, wherein a first view of the target for each detector of the first plurality of detectors is substantially the same, and a second plurality of detectors, wherein a second view of the target for each detector of the second plurality of detectors is substantially the same, wherein the first and second views are different. | 6. The method of claim 1 , wherein the plurality of feature cues is generated by at least a first plurality of detectors, wherein a first view of the target for each detector of the first plurality of detectors is substantially the same, and a second plurality of detectors, wherein a second view of the target for each detector of the second plurality of detectors is substantially the same, wherein the first and second views are different. 7. The method of claim 6 , wherein fusing the plurality of feature cues to form a set of target hypotheses comprises fusing a first output of the first plurality of detectors with a second output of the second plurality of detectors. | 0.5 |
9,191,639 | 16 | 19 | 16. A hardware computer system configured to perform operations comprising: receiving time-aligned script data comprising dialogue words of a script and timecodes corresponding to the dialogue words; comparing pauses between timecodes of adjacent dialogue words to a gap threshold that corresponds to a pre-specified period of time; ignoring pauses that do not meet or exceed the gap threshold; identifying pauses that meet or exceed the gap threshold as gaps between dialogue words for the insertion of video description content; aligning segments of video description content with corresponding gaps in dialogue, wherein the video description content for the segments is derived from corresponding script elements of the script; comparing a duration of a gap to a length of corresponding video description content to determine if the gap is of sufficient length for the insertion of the corresponding video description content; in an event that the gap is not of sufficient length, processing, responsive to determining that the gap is not of sufficient length and independent of user input, one or more of the gap length or the corresponding video description content such that the corresponding video description content is insertable into the gap; and generating a script document comprising the aligned segments of video description content. | 16. A hardware computer system configured to perform operations comprising: receiving time-aligned script data comprising dialogue words of a script and timecodes corresponding to the dialogue words; comparing pauses between timecodes of adjacent dialogue words to a gap threshold that corresponds to a pre-specified period of time; ignoring pauses that do not meet or exceed the gap threshold; identifying pauses that meet or exceed the gap threshold as gaps between dialogue words for the insertion of video description content; aligning segments of video description content with corresponding gaps in dialogue, wherein the video description content for the segments is derived from corresponding script elements of the script; comparing a duration of a gap to a length of corresponding video description content to determine if the gap is of sufficient length for the insertion of the corresponding video description content; in an event that the gap is not of sufficient length, processing, responsive to determining that the gap is not of sufficient length and independent of user input, one or more of the gap length or the corresponding video description content such that the corresponding video description content is insertable into the gap; and generating a script document comprising the aligned segments of video description content. 19. The system of claim 16 , wherein processing one or more of the gap length or the corresponding video description content comprises automatically increasing the gap length such that the video description content fits within the corresponding gap. | 0.547273 |
9,478,059 | 3 | 4 | 3. The method of claim 1 , wherein the plurality of natural language statements included in the script file comprises one or more dialog natural language statements, and wherein dynamically generating and displaying the one or more visually animated graphical elements comprises dynamically generating and displaying one or more visually animated speech bubbles according to the one or more dialog natural language statements. | 3. The method of claim 1 , wherein the plurality of natural language statements included in the script file comprises one or more dialog natural language statements, and wherein dynamically generating and displaying the one or more visually animated graphical elements comprises dynamically generating and displaying one or more visually animated speech bubbles according to the one or more dialog natural language statements. 4. The method of claim 3 , wherein the one or more dialog natural language statements is associated with a narrator of a story. | 0.5 |
5,493,675 | 1 | 2 | 1. A method executed in a computer system, the method comprising the steps: generating a flow graph for a source program that is being compiled using a compiler front end which performs syntactic and semantic processing of a programing language, said flow graph comprising tuples, each tuple representing a single expression in said source program, said flow graph being a representation of said source program in an intermediate language; determining, by said compiler front end for each tuple which can have an effect on another tuple and which is included in said first flow graph, an effect indicator that represents an effect said each tuple has on said another tuple, said effect indicator being associated with said each tuple; determining, by said compiler front end for each tuple which can have a dependency on another tuple and which is included in said flow graph, a dependency indicator that represents a dependency said each tuple on said another tuple, said dependency indicator being associated with said each tuple; and optimizing said flow graph by a compiler back end calling one or more predetermined routines in said compiler front end, said predetermined routines using effect and dependency information from said determining effect and said determining dependency steps to provide return information to said compiler back end wherein said compiler back end uses said return information to determine whether an optimization is valid for one of said tuples comprising said flow graph. | 1. A method executed in a computer system, the method comprising the steps: generating a flow graph for a source program that is being compiled using a compiler front end which performs syntactic and semantic processing of a programing language, said flow graph comprising tuples, each tuple representing a single expression in said source program, said flow graph being a representation of said source program in an intermediate language; determining, by said compiler front end for each tuple which can have an effect on another tuple and which is included in said first flow graph, an effect indicator that represents an effect said each tuple has on said another tuple, said effect indicator being associated with said each tuple; determining, by said compiler front end for each tuple which can have a dependency on another tuple and which is included in said flow graph, a dependency indicator that represents a dependency said each tuple on said another tuple, said dependency indicator being associated with said each tuple; and optimizing said flow graph by a compiler back end calling one or more predetermined routines in said compiler front end, said predetermined routines using effect and dependency information from said determining effect and said determining dependency steps to provide return information to said compiler back end wherein said compiler back end uses said return information to determine whether an optimization is valid for one of said tuples comprising said flow graph. 2. The method of claim 1 further comprising said compiler back end, during said optimizing step, using and modifying an effects stack that is managed by said compiler front end and that includes tuples stored in a predetermined order representing tuples that have effects on other tuples, the step of said compiler back end using and modifying said effects stack comprising: calling a first one of said predetermined routines that pushes a tuple with an associated effect indicator on said effects stack; calling a second one of said predetermined routines that returns, for a first tuple with an associated dependency indicator, a second tuple which is a topmost tuple on said effects stack and upon which said first tuple depends if said second tuple exists; and calling a third one of said predetermined routines that pops said effects stack by removing the topmost tuple with an associated effect indicator. | 0.759631 |
9,268,878 | 1 | 8 | 1. A computer-implemented method executed by a processing unit coupled to memory for determining an entity category for an entity, the entity comprising a subject of a web page, comprising: extracting a set of potential categories relating to an entity, wherein the set of potential categories is extracted from a first portion of a web page and the entity comprises a subject of the web page; extracting summary text relating to the entity from a second portion of the web page, wherein the first portion is disposed at a first region of the web page and the second portion is disposed at a second region of the webpage separate from the first region; comparing at least some of the set of potential categories to the summary text to determine a set of candidate categories for the entity, wherein the set of candidate categories is a subset of the set of potential categories, and wherein the comparing includes A) performing a morphological analysis upon one or more category words of a potential category of the set of potential categories to generate a set of variation category words of the potential category, and B) identifying a match between one or more variation category words of the set of variation category words and one or more summary words of the summary text; ranking a first candidate category of the set of candidate categories relative to a second candidate category of the set of candidate categories based upon one or more ranking features to generate a ranked set of candidate categories; determining an entity category for the entity from the ranked set of candidate categories, wherein the entity category has a first rank within the ranked set of candidate categories, wherein the first rank is above a threshold; and presenting the entity category having the first rank in a search result page. | 1. A computer-implemented method executed by a processing unit coupled to memory for determining an entity category for an entity, the entity comprising a subject of a web page, comprising: extracting a set of potential categories relating to an entity, wherein the set of potential categories is extracted from a first portion of a web page and the entity comprises a subject of the web page; extracting summary text relating to the entity from a second portion of the web page, wherein the first portion is disposed at a first region of the web page and the second portion is disposed at a second region of the webpage separate from the first region; comparing at least some of the set of potential categories to the summary text to determine a set of candidate categories for the entity, wherein the set of candidate categories is a subset of the set of potential categories, and wherein the comparing includes A) performing a morphological analysis upon one or more category words of a potential category of the set of potential categories to generate a set of variation category words of the potential category, and B) identifying a match between one or more variation category words of the set of variation category words and one or more summary words of the summary text; ranking a first candidate category of the set of candidate categories relative to a second candidate category of the set of candidate categories based upon one or more ranking features to generate a ranked set of candidate categories; determining an entity category for the entity from the ranked set of candidate categories, wherein the entity category has a first rank within the ranked set of candidate categories, wherein the first rank is above a threshold; and presenting the entity category having the first rank in a search result page. 8. The computer-implemented method of claim 1 , the comparing comprising: identifying a second match between one or more category words of a second potential category of the set of potential categories and one or more summary words of the summary text; and identifying the second potential category as the first candidate category responsive to the identifying a second match. | 0.546988 |
9,817,802 | 1 | 5 | 1. A method comprising: identifying at least one abbreviation element in a received text-based electronic communication that is addressed to at least one recipient; determining a presentation preference of the at least one recipient for the at least one identified abbreviation element from an abbreviation usage history data, wherein the abbreviation usage history data represents a preference of a sender for the abbreviation element when sending text-based electronic communications to others; creating an abbreviation-adjusted text-based electronic communication for each recipient using the received text-based electronic communication and the determined presentation preference for a recipient for the at least one abbreviation element; and modifying abbreviation elements based on the preference of the sender, for generating the abbreviated-adjusted text-based electronic communication, when presentation preference of the recipient for the at least one abbreviation element is not present in the recipient's abbreviation usage history data. | 1. A method comprising: identifying at least one abbreviation element in a received text-based electronic communication that is addressed to at least one recipient; determining a presentation preference of the at least one recipient for the at least one identified abbreviation element from an abbreviation usage history data, wherein the abbreviation usage history data represents a preference of a sender for the abbreviation element when sending text-based electronic communications to others; creating an abbreviation-adjusted text-based electronic communication for each recipient using the received text-based electronic communication and the determined presentation preference for a recipient for the at least one abbreviation element; and modifying abbreviation elements based on the preference of the sender, for generating the abbreviated-adjusted text-based electronic communication, when presentation preference of the recipient for the at least one abbreviation element is not present in the recipient's abbreviation usage history data. 5. The method of claim 1 , wherein the abbreviation element is presented in one of a condensed format and an expanded format, wherein the expanded format expresses a full meaning of the condensed format of the abbreviation element. | 0.827869 |
7,617,469 | 1 | 4 | 1. An assertion description conversion device comprising: verification target identification unit parsing the syntax of a high-level assertion description described by a high-level assertion description language for verification of an inputted design description of a broader term to identify a verification target; design description searching unit searching a description on the verification target in a design description of a broader term; verification target description conversion unit converting the description of the verification target into a design description of a narrower term according to the design description of the narrower term corresponding to the description searched by the design description searching unit; verification content analysis unit for analyzing verification contents for the verification target described in the high-level assertion description; verification content description conversion unit for converting the verification contents analyzed by the verification content analysis unit into the description format of a low-level assertion description language for verification of a design description of the narrower term; and wherein, in the verification target description conversion unit, when converting the description of the verification target description into the design description of the narrower term, a description for timing adjustment is added according to synthesis result information at the time when synthesizing the design description of the narrower term according to the design description of the broader term. | 1. An assertion description conversion device comprising: verification target identification unit parsing the syntax of a high-level assertion description described by a high-level assertion description language for verification of an inputted design description of a broader term to identify a verification target; design description searching unit searching a description on the verification target in a design description of a broader term; verification target description conversion unit converting the description of the verification target into a design description of a narrower term according to the design description of the narrower term corresponding to the description searched by the design description searching unit; verification content analysis unit for analyzing verification contents for the verification target described in the high-level assertion description; verification content description conversion unit for converting the verification contents analyzed by the verification content analysis unit into the description format of a low-level assertion description language for verification of a design description of the narrower term; and wherein, in the verification target description conversion unit, when converting the description of the verification target description into the design description of the narrower term, a description for timing adjustment is added according to synthesis result information at the time when synthesizing the design description of the narrower term according to the design description of the broader term. 4. The assertion description conversion device according to claim 1 , wherein the high-level assertion description is an assertion description of the transaction level and the low-level assertion description is an assertion description of the I/O cycle operation level. | 0.67823 |
8,290,977 | 60 | 78 | 60. In a database system, a method for executing an XPath built-in function in an XPath-based query requesting data from an Extensible Markup Language (XML) document, the method comprising: receiving the XPath-based query requesting data from an XML document, the XPath-based query including an XPath built-in function to be executed on data from an XML document which includes a plurality of hierarchically arranged elements, said XPath built-in function operating within a particular context of the XML document during execution of the XPath-based query; during execution of the XPath-based query: determining elements of the XML document satisfying the XPath- based query, obtaining values of said elements of the XML document, associating said values with elements of the XML document, and executing the XPath built-in function with said values and associated elements. | 60. In a database system, a method for executing an XPath built-in function in an XPath-based query requesting data from an Extensible Markup Language (XML) document, the method comprising: receiving the XPath-based query requesting data from an XML document, the XPath-based query including an XPath built-in function to be executed on data from an XML document which includes a plurality of hierarchically arranged elements, said XPath built-in function operating within a particular context of the XML document during execution of the XPath-based query; during execution of the XPath-based query: determining elements of the XML document satisfying the XPath- based query, obtaining values of said elements of the XML document, associating said values with elements of the XML document, and executing the XPath built-in function with said values and associated elements. 78. The method of claim 60 , further comprising: returning results of execution of the XPath built-in function. | 0.63 |
8,214,212 | 1 | 4 | 1. A method of recognizing an utterance comprising: receiving an utterance comprising a first portion having a first mode and a second portion having a second mode; generating, at a multimodal recognition system comprising a processor, a first mode recognition lattice and a first finite-state transducer based on the first mode; and generating a recognition model comprising: relating the first portion of the utterance to the second portion of the utterance using the first finite-state transducer; and generating a second finite-state transducer, the second finite-state transducer comprising a gesture and speech recognition model finite-state transducer, based on the first mode recognition lattice and the first finite-state transducer. | 1. A method of recognizing an utterance comprising: receiving an utterance comprising a first portion having a first mode and a second portion having a second mode; generating, at a multimodal recognition system comprising a processor, a first mode recognition lattice and a first finite-state transducer based on the first mode; and generating a recognition model comprising: relating the first portion of the utterance to the second portion of the utterance using the first finite-state transducer; and generating a second finite-state transducer, the second finite-state transducer comprising a gesture and speech recognition model finite-state transducer, based on the first mode recognition lattice and the first finite-state transducer. 4. The method of claim 1 wherein the second mode is a speech mode. | 0.744186 |
8,112,714 | 13 | 14 | 13. A computer-readable storage medium storing computer-executable instructions that, when executed by a client computer system, causes the client computer system to perform a computer process that presents a customized user interface page in an application, the computer process comprising: receiving an application package from a communications network at the client computer system, the application package containing markup data of the customized user interface page, the markup data defining a user interface element that is potentially available to a user of the client computer system in the customized user interface page and one or more constraints associated with the user interface element for selectively presenting or hiding the user interface element based on properties of the application or the client computer system; searching the markup data of the customized user interface page for the one or more constraints associated with the user interface element, wherein each of the one or more constraints associated with the user interface element in the markup data specifies a condition for presenting the user interface element which is to be evaluated against a configuration parameter that identifies one or more configuration-specific characteristics of the application or the client computer system; compiling the one or more constraints associated with the user interface element into a constraint expression; determining whether the constraint expression is satisfied by evaluating each of the one or more constraints in the constraint expression against the corresponding configuration parameter; rendering the customized user interface page to include the user interface element in a display, if the constraint expression is satisfied; and rendering the customized user interface page to hide or omit the user interface element, if the constraint expression is not satisfied. | 13. A computer-readable storage medium storing computer-executable instructions that, when executed by a client computer system, causes the client computer system to perform a computer process that presents a customized user interface page in an application, the computer process comprising: receiving an application package from a communications network at the client computer system, the application package containing markup data of the customized user interface page, the markup data defining a user interface element that is potentially available to a user of the client computer system in the customized user interface page and one or more constraints associated with the user interface element for selectively presenting or hiding the user interface element based on properties of the application or the client computer system; searching the markup data of the customized user interface page for the one or more constraints associated with the user interface element, wherein each of the one or more constraints associated with the user interface element in the markup data specifies a condition for presenting the user interface element which is to be evaluated against a configuration parameter that identifies one or more configuration-specific characteristics of the application or the client computer system; compiling the one or more constraints associated with the user interface element into a constraint expression; determining whether the constraint expression is satisfied by evaluating each of the one or more constraints in the constraint expression against the corresponding configuration parameter; rendering the customized user interface page to include the user interface element in a display, if the constraint expression is satisfied; and rendering the customized user interface page to hide or omit the user interface element, if the constraint expression is not satisfied. 14. The computer-readable storage medium of claim 13 wherein the application is executed by the client computer system and the determining operation comprises: evaluating a constraint in the constraint expression against a configuration parameter of the client computer system. | 0.796024 |
8,249,830 | 4 | 9 | 4. A computer-implemented method for automatically diagnosing new faults in a device, said method comprising: said computer mapping known faults to user-defined classes to derive a plurality of known classes; said computer configuring a classifier based on training data, wherein said classifier assigns image quality based feature vectors to at least one known class among said plurality of known classes; said computer generating a measure of membership with respect to each feature vector belonging to said at least one known class utilizing said classifier; said computer clustering a plurality of members associated with said at least one known class into two clusters including core class members and at least one outlier cluster in order to detect a presence of a new defect and a drift in the probabilistic distribution of the plurality of members between the core class and the at least one outlier cluster in a known defect in the device overtime, wherein the device is a rendering device and the known defect is an image quality defect; and said computer determining if a probabilistic distribution of said plurality members of said outlier cluster associated with said class quantifies a change in distribution when a set of spurious features becomes sufficiently different from said corresponding distribution of said core class members to therefore indicate said new faults and said drift in said known defect and thereafter diagnose said new faults and said drift in said known defect in said device, wherein said new faults are unknown image quality defects; and said computer retraining said classifier with updated characteristics of said new defect. | 4. A computer-implemented method for automatically diagnosing new faults in a device, said method comprising: said computer mapping known faults to user-defined classes to derive a plurality of known classes; said computer configuring a classifier based on training data, wherein said classifier assigns image quality based feature vectors to at least one known class among said plurality of known classes; said computer generating a measure of membership with respect to each feature vector belonging to said at least one known class utilizing said classifier; said computer clustering a plurality of members associated with said at least one known class into two clusters including core class members and at least one outlier cluster in order to detect a presence of a new defect and a drift in the probabilistic distribution of the plurality of members between the core class and the at least one outlier cluster in a known defect in the device overtime, wherein the device is a rendering device and the known defect is an image quality defect; and said computer determining if a probabilistic distribution of said plurality members of said outlier cluster associated with said class quantifies a change in distribution when a set of spurious features becomes sufficiently different from said corresponding distribution of said core class members to therefore indicate said new faults and said drift in said known defect and thereafter diagnose said new faults and said drift in said known defect in said device, wherein said new faults are unknown image quality defects; and said computer retraining said classifier with updated characteristics of said new defect. 9. The method of claim 4 further comprising: said computer extracting a raw image from a test pattern; and said computer transmitting said raw image to said classifier in the event said new defect is identified with respect to an image quality associated with said device. | 0.5 |
9,990,434 | 1 | 3 | 1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: analyzing a plurality of posts included in one or more threads of an online forum, wherein the analyzing further comprises: identifying a main topic related to a parent post of the thread; selecting a plurality child posts of the thread, wherein the parent post is a parent to each of the child posts; identifying any referential types corresponding to a plurality of words included in the parent post; identifying any anaphora types corresponding to a plurality of words included in each of the child posts; associating each of the plurality of child posts with the parent post as a relationship; resolving the anaphora types included in the child posts with at least one of the referential types included in the parent post; determining a sentiment between each of the child posts and the parent post; identifying a plurality of child topics, wherein each of the plurality of child topics corresponds to one of the child posts and the determined sentiment; and determining a relevance of each of the child posts by comparing the identified main topic to each of the identified child topics; selecting one or more of the child posts based on the relevance of the child posts; ingesting data from the parent post into a corpus utilized by a question answering (QA) system; ingesting data from the one or more selected child posts into the corpus; and building a forum tree corresponding to the online forum, wherein the forum tree includes the parent post and the selected one or more child posts, the relationships between the parent post and each of the selected child posts, and the resolved anaphora types included in each of the selected child posts. | 1. A method implemented by an information handling system that includes a memory and a processor, the method comprising: analyzing a plurality of posts included in one or more threads of an online forum, wherein the analyzing further comprises: identifying a main topic related to a parent post of the thread; selecting a plurality child posts of the thread, wherein the parent post is a parent to each of the child posts; identifying any referential types corresponding to a plurality of words included in the parent post; identifying any anaphora types corresponding to a plurality of words included in each of the child posts; associating each of the plurality of child posts with the parent post as a relationship; resolving the anaphora types included in the child posts with at least one of the referential types included in the parent post; determining a sentiment between each of the child posts and the parent post; identifying a plurality of child topics, wherein each of the plurality of child topics corresponds to one of the child posts and the determined sentiment; and determining a relevance of each of the child posts by comparing the identified main topic to each of the identified child topics; selecting one or more of the child posts based on the relevance of the child posts; ingesting data from the parent post into a corpus utilized by a question answering (QA) system; ingesting data from the one or more selected child posts into the corpus; and building a forum tree corresponding to the online forum, wherein the forum tree includes the parent post and the selected one or more child posts, the relationships between the parent post and each of the selected child posts, and the resolved anaphora types included in each of the selected child posts. 3. The method of claim 1 wherein the actions determining a sentiment between each of the child posts and the parent post further comprise: establishing a sentiment score of each of the child posts based on an identified sentiment of each of the child posts to the parent post. | 0.627027 |
8,572,013 | 15 | 16 | 15. A method, comprising: identifying, in at least one computing device, one of a plurality of classifications based at least in part on a plurality of tokens associated with an item and a data dictionary, thereby producing an identified classification that is associated with a confidence score; automatically assigning, in the at least one computing device, the identified classification to the item when the confidence score meets a threshold; and obtaining, in the at least one computing device, a manual confirmation of the identified classification when the confidence score is below the threshold, the manual confirmation indicating whether the identified classification is erroneous; building, in the at least one computing device, the data dictionary based at least in part on data describing a plurality of preclassified items, each one of the preclassified items being assigned a manually determined one of the classifications; and periodically rebuilding, in the at least one computing device, the data dictionary based at least in part on data associated with automatically classified items having manually confirmed classifications. | 15. A method, comprising: identifying, in at least one computing device, one of a plurality of classifications based at least in part on a plurality of tokens associated with an item and a data dictionary, thereby producing an identified classification that is associated with a confidence score; automatically assigning, in the at least one computing device, the identified classification to the item when the confidence score meets a threshold; and obtaining, in the at least one computing device, a manual confirmation of the identified classification when the confidence score is below the threshold, the manual confirmation indicating whether the identified classification is erroneous; building, in the at least one computing device, the data dictionary based at least in part on data describing a plurality of preclassified items, each one of the preclassified items being assigned a manually determined one of the classifications; and periodically rebuilding, in the at least one computing device, the data dictionary based at least in part on data associated with automatically classified items having manually confirmed classifications. 16. The method of claim 15 , wherein identifying, in the at least one computing device, the one of the classifications further comprises identifying the one of the classifications using a naïve Bayes classifier. | 0.829011 |
9,542,291 | 7 | 9 | 7. The event-based system of claim 1 , wherein the CEP engine is configured to produce an event of a third event type indicating a performance issue, if an event is received out of sequence by the CEP engine. | 7. The event-based system of claim 1 , wherein the CEP engine is configured to produce an event of a third event type indicating a performance issue, if an event is received out of sequence by the CEP engine. 9. The event-based system of claim 7 , wherein events of the third event type indicate the time of detection of the performance issue, the event type of the event that was received out of sequence, event data, a host identifier of the CEP engine, and/or a process identifier of the CEP engine. | 0.5 |
7,716,038 | 8 | 13 | 8. A system for providing translated web pages to a web browser user of a computer network comprising: at least one computer on the network: (a) determining the user's preferred language; (b) receiving a request from the user's web browser for a first web page, the first web page comprising text in a source language and at least one link to a second web page comprising text in the source language; (c) preserving said link during translation of said first web page from said source language to said user's preferred language; (d) transmitting to the user's web browser a first translated web page comprising the text of the first web page translated from the source language to the user's preferred language, the first translated web page including the at least one link to the second web page preserved during translation; (e) receiving a request from the user's web browser for the second web page when the link to the second web page is selected; and (f) transmitting to the user's web browser a second translated web page comprising text translated from the source language to the user's preferred language; and at least one user computer with a web browser: (g) transmitting requests for a first web page and a second web page in a source language; and (h) receiving a first translated web page and a second translated web page, the translated web pages comprising the text from the first and second web pages translated to the user's preferred language. | 8. A system for providing translated web pages to a web browser user of a computer network comprising: at least one computer on the network: (a) determining the user's preferred language; (b) receiving a request from the user's web browser for a first web page, the first web page comprising text in a source language and at least one link to a second web page comprising text in the source language; (c) preserving said link during translation of said first web page from said source language to said user's preferred language; (d) transmitting to the user's web browser a first translated web page comprising the text of the first web page translated from the source language to the user's preferred language, the first translated web page including the at least one link to the second web page preserved during translation; (e) receiving a request from the user's web browser for the second web page when the link to the second web page is selected; and (f) transmitting to the user's web browser a second translated web page comprising text translated from the source language to the user's preferred language; and at least one user computer with a web browser: (g) transmitting requests for a first web page and a second web page in a source language; and (h) receiving a first translated web page and a second translated web page, the translated web pages comprising the text from the first and second web pages translated to the user's preferred language. 13. The system of claim 8 wherein the user's preferred language is selected by the user via the web browser. | 0.818182 |
9,529,833 | 17 | 18 | 17. A computing system for graph pruning, the system comprising: one or more processors; a storage device; a computer-readable medium coupled to the one or more processors having instructions stored thereon that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: storing in the storage device a data set comprising a plurality of data elements; determining, by the computing system, a type and strength of relationship between a data element pair in the plurality of data elements; representing the type and strength of relationship as an edge between a vertex pair representing the data element pair in a graph; determining a minimum graph traversal threshold associated with an input query received by the computer for the graph, wherein the minimum graph traversal threshold indicates a minimum number of traversal steps needed for the input query in the graph; identifying that a number of traversal steps for a first connected component in the graph is greater than or equal to a minimum graph traversal threshold, and wherein a connected component includes a set of one or more vertices, which are couple to each other via edges and are not couple to a vertex outside of the set; identifying that a number of traversal steps for a second connected component in the graph is smaller than the minimum graph traversal threshold; generating a second graph comprising the first connected component by pruning the connected component from the graph; and processing the input query on the second graph to extract information of interest from the data set. | 17. A computing system for graph pruning, the system comprising: one or more processors; a storage device; a computer-readable medium coupled to the one or more processors having instructions stored thereon that, when executed by the one or more processors, cause the one or more processors to perform operations comprising: storing in the storage device a data set comprising a plurality of data elements; determining, by the computing system, a type and strength of relationship between a data element pair in the plurality of data elements; representing the type and strength of relationship as an edge between a vertex pair representing the data element pair in a graph; determining a minimum graph traversal threshold associated with an input query received by the computer for the graph, wherein the minimum graph traversal threshold indicates a minimum number of traversal steps needed for the input query in the graph; identifying that a number of traversal steps for a first connected component in the graph is greater than or equal to a minimum graph traversal threshold, and wherein a connected component includes a set of one or more vertices, which are couple to each other via edges and are not couple to a vertex outside of the set; identifying that a number of traversal steps for a second connected component in the graph is smaller than the minimum graph traversal threshold; generating a second graph comprising the first connected component by pruning the connected component from the graph; and processing the input query on the second graph to extract information of interest from the data set. 18. The computing system of claim 17 , wherein a respective element in the data set is stored on one or more tables in the storage device, wherein the element is identified based on a first identifier; and wherein identifying that a number of traversal steps for the second connected component is smaller than the minimum graph traversal threshold comprises one or more tabular operations performed on the one or more tables. | 0.60206 |
8,126,701 | 9 | 11 | 9. A system comprising: a database comprising data in a plurality of languages; and at least one processor configured to: determine that a first reader has an associated language choice comprising a first language; receive a request from the first reader to access data in the first language; determine that the data is available, in the database, in a second language and is not available in the first language; and render the data in the second language to the first reader and render a field descriptive of the data in the first language. | 9. A system comprising: a database comprising data in a plurality of languages; and at least one processor configured to: determine that a first reader has an associated language choice comprising a first language; receive a request from the first reader to access data in the first language; determine that the data is available, in the database, in a second language and is not available in the first language; and render the data in the second language to the first reader and render a field descriptive of the data in the first language. 11. The system of claim 9 wherein the data comprises at least one of a description, commercial terms, lot details, and desired bidders. | 0.622905 |
9,020,212 | 1 | 10 | 1. A computer-implemented method of automatically determining a name of a person appearing in an image, comprising: receiving a collection of web pages containing a plurality of images; for each of the images, identifying a set of names associated with the image based on a text analysis of at least one of the web pages; performing face detection and clustering on the plurality of images to generate a plurality of face clusters, wherein each of the face clusters is associated with one person and includes a set of at least one image from the plurality of images in which a face of the one person was detected; for each of the face clusters, identifying a label for the face cluster based on the set of names associated with each image in the face cluster; determining a name of a first person appearing in at least one of the images based on the identified label for one of the face clusters associated with the first person; and wherein the receiving, identifying a set of names, performing face detection and clustering, identifying a label, and determining a name are performed by at least one processor. | 1. A computer-implemented method of automatically determining a name of a person appearing in an image, comprising: receiving a collection of web pages containing a plurality of images; for each of the images, identifying a set of names associated with the image based on a text analysis of at least one of the web pages; performing face detection and clustering on the plurality of images to generate a plurality of face clusters, wherein each of the face clusters is associated with one person and includes a set of at least one image from the plurality of images in which a face of the one person was detected; for each of the face clusters, identifying a label for the face cluster based on the set of names associated with each image in the face cluster; determining a name of a first person appearing in at least one of the images based on the identified label for one of the face clusters associated with the first person; and wherein the receiving, identifying a set of names, performing face detection and clustering, identifying a label, and determining a name are performed by at least one processor. 10. The computer-implemented method of claim 1 , and further comprising: automatically adding the name of the first person to the at least one image in which the first person appears. | 0.768939 |
6,029,171 | 7 | 9 | 7. The method of claim 4, further comprising: continuing a collaboration when the selection is the other, until the selection is the affirmative or the negative; completing the collaboration when the reply option is the affirmative; and aborting the collaboration when the reply option is the negative. | 7. The method of claim 4, further comprising: continuing a collaboration when the selection is the other, until the selection is the affirmative or the negative; completing the collaboration when the reply option is the affirmative; and aborting the collaboration when the reply option is the negative. 9. The method of claim 7 wherein said step of completing the collaboration comprises: updating the entry in the first calendar and the first list based on the reply from the second instance of the messaging system; and updating the entry in the second calendar and the second list based on the reply. | 0.637681 |
7,849,104 | 1 | 9 | 1. A method implemented on a computing device by a processor for searching heterogeneous interrelated entities comprising: receiving a heterogeneous interrelated entities search query; searching, in a unified space, for results to the heterogeneous interrelated entities search query, the results including a set of heterogeneous interrelated entities having a plurality of entity types, the unified space based on one or more relationships between multiple heterogeneous entities; constructing a multiple-type graph for one or more heterogeneous entity types; extracting co-occurrence matrices from the multiple-type graph based on interactions between pairs of the one or more heterogeneous entity types; forming one or more entity vectors for each of the one or more heterogeneous entity types based on the co-occurrence matrices; concatenating the one or more entity vectors to form a unified matrix that represents the multiple heterogeneous entities in the unified space; and presenting the results as a plurality of lists, each list of the plurality of lists comprising search result entities of a same entity type. | 1. A method implemented on a computing device by a processor for searching heterogeneous interrelated entities comprising: receiving a heterogeneous interrelated entities search query; searching, in a unified space, for results to the heterogeneous interrelated entities search query, the results including a set of heterogeneous interrelated entities having a plurality of entity types, the unified space based on one or more relationships between multiple heterogeneous entities; constructing a multiple-type graph for one or more heterogeneous entity types; extracting co-occurrence matrices from the multiple-type graph based on interactions between pairs of the one or more heterogeneous entity types; forming one or more entity vectors for each of the one or more heterogeneous entity types based on the co-occurrence matrices; concatenating the one or more entity vectors to form a unified matrix that represents the multiple heterogeneous entities in the unified space; and presenting the results as a plurality of lists, each list of the plurality of lists comprising search result entities of a same entity type. 9. The method of claim 1 , further comprising utilizing feedback by: identifying a set of semantically related entities based on the heterogeneous interrelated entities search query; evaluating an expanded query vector based on the heterogeneous interrelated entities search query, the set of semantically related entities, and one or more weighting factors, the one or more weighing factor based on a heterogeneous entity type; and determining refined results using the expanded query vector. | 0.572049 |
9,569,334 | 1 | 8 | 1. A method of traversing a representation of an application source code, comprising: specifying a plurality of runtime binding rules, each runtime binding rule of the plurality of runtime binding rules configured to augment the representation of the application source code using code slicing techniques, each runtime binding rule of the plurality of runtime binding rules associated with one or more locations within the representation of the application source code, at least one runtime binding rule of the plurality of runtime binding rules associated with a method invocation and a concrete implementation and specifying that the concrete implementation be visited either before or after the method invocation, the concrete implementation is visited before the method invocation when a first location of the one or more locations is before the method innovation and the concrete implementation is visited after the method invocation when a second location of the one or more locations is after the method innovation; beginning to traverse, using one or more computer processors, the representation of the application source code; monitoring a history of the traverse; continuing to traverse the representation of the application source code based at least in part on the history of the traverse, wherein continuing to traverse the representation of the application source code includes: a) identifying a plurality of concrete implementations of a method invocation; b) selecting, based at least in part on the history of the traverse, a set of concrete implementations from the plurality of concrete implementations of the method invocation; c) traversing, based at least in part on the one or more of the plurality of runtime binding rules, one or more concrete implementations of the set of concrete implementations; and d) updating the history of the traverse; and providing a set of identified vulnerabilities, the set of identified vulnerabilities based at least in part on the history of the traverse. | 1. A method of traversing a representation of an application source code, comprising: specifying a plurality of runtime binding rules, each runtime binding rule of the plurality of runtime binding rules configured to augment the representation of the application source code using code slicing techniques, each runtime binding rule of the plurality of runtime binding rules associated with one or more locations within the representation of the application source code, at least one runtime binding rule of the plurality of runtime binding rules associated with a method invocation and a concrete implementation and specifying that the concrete implementation be visited either before or after the method invocation, the concrete implementation is visited before the method invocation when a first location of the one or more locations is before the method innovation and the concrete implementation is visited after the method invocation when a second location of the one or more locations is after the method innovation; beginning to traverse, using one or more computer processors, the representation of the application source code; monitoring a history of the traverse; continuing to traverse the representation of the application source code based at least in part on the history of the traverse, wherein continuing to traverse the representation of the application source code includes: a) identifying a plurality of concrete implementations of a method invocation; b) selecting, based at least in part on the history of the traverse, a set of concrete implementations from the plurality of concrete implementations of the method invocation; c) traversing, based at least in part on the one or more of the plurality of runtime binding rules, one or more concrete implementations of the set of concrete implementations; and d) updating the history of the traverse; and providing a set of identified vulnerabilities, the set of identified vulnerabilities based at least in part on the history of the traverse. 8. The method of claim 1 , further comprising: determining whether a method invocation or its corresponding concrete implementation has an associated runtime binding rule; and when it is determined that the method invocation or its corresponding concrete implementation has an associated runtime binding rule, jumping to a method declaration specified by the runtime binding rule. | 0.535452 |
8,510,095 | 1 | 4 | 1. A method comprising: detecting one or more character inputs in a first character alphabet as a preceding character string, the preceding character string corresponding to one or more valid characters in a second alphabet according to a transliteration operation; detecting a current character input in the first character alphabet following input of the preceding character string; determining whether the combination of the current character input with the preceding character string would result in an invalid transliteration result; and automatically performing, via a processor, an operation on the preceding character string to replace the preceding character string with a replacement character selected from among the one or more valid characters in the second alphabet if the combination would result in an invalid transliteration result. | 1. A method comprising: detecting one or more character inputs in a first character alphabet as a preceding character string, the preceding character string corresponding to one or more valid characters in a second alphabet according to a transliteration operation; detecting a current character input in the first character alphabet following input of the preceding character string; determining whether the combination of the current character input with the preceding character string would result in an invalid transliteration result; and automatically performing, via a processor, an operation on the preceding character string to replace the preceding character string with a replacement character selected from among the one or more valid characters in the second alphabet if the combination would result in an invalid transliteration result. 4. The method of claim 1 , wherein the replacement character is selected from among the one or more valid characters according to a value representing frequency of usage of the one or more valid characters. | 0.642361 |
8,788,270 | 27 | 44 | 27. A method for determining an emotion state of a speaker, comprising: providing an acoustic space having one or more dimensions, wherein each dimension of the one or more dimensions of the acoustic space corresponds to at least one baseline acoustic characteristic; receiving a subject utterance of speech by a speaker; measuring, via one or more processors, one or more acoustic characteristic of the subject utterance of speech; comparing, via the one or more processors, each acoustic characteristic of the one or more acoustic characteristic of the subject utterance of speech to a corresponding one or more baseline acoustic characteristic; and determining, via the one or more processors, an emotion state of the speaker based on the comparison, wherein the emotion state of the speaker comprises at least one magnitude along a corresponding at least one of the one or more dimensions within the acoustic space. | 27. A method for determining an emotion state of a speaker, comprising: providing an acoustic space having one or more dimensions, wherein each dimension of the one or more dimensions of the acoustic space corresponds to at least one baseline acoustic characteristic; receiving a subject utterance of speech by a speaker; measuring, via one or more processors, one or more acoustic characteristic of the subject utterance of speech; comparing, via the one or more processors, each acoustic characteristic of the one or more acoustic characteristic of the subject utterance of speech to a corresponding one or more baseline acoustic characteristic; and determining, via the one or more processors, an emotion state of the speaker based on the comparison, wherein the emotion state of the speaker comprises at least one magnitude along a corresponding at least one of the one or more dimensions within the acoustic space. 44. The method according to claim 27 , wherein each of the one or more acoustic characteristic of the subject utterance of speech comprises a suprasegmental property of the subject utterance of speech, and each of the at least one baseline acoustic characteristic comprises a corresponding suprasegmental property. | 0.775393 |
8,972,324 | 1 | 5 | 1. A method comprising: receiving sensor data generated by a sensor of a synthetic character, the synthetic character comprising an animation module configured to control the interactions of the synthetic character based on instructions from a traversable script; generating, at an analytics engine, an activity index, wherein the activity, index includes a set of script analytics generated by a logical analysis of the sensor data, and further wherein the analytics engine calculates normative variations in the set of script analytics compared to an aggregated data set; generating a traversable script update by automatically generating new traversable behavior based on the normative variations detected in the activity index, and enabling manual updates by generating a script editor that allows a user to modify the traversable script; sending the traversable script update to the synthetic character; and causing the traversable script update to be implemented by the synthetic character. | 1. A method comprising: receiving sensor data generated by a sensor of a synthetic character, the synthetic character comprising an animation module configured to control the interactions of the synthetic character based on instructions from a traversable script; generating, at an analytics engine, an activity index, wherein the activity, index includes a set of script analytics generated by a logical analysis of the sensor data, and further wherein the analytics engine calculates normative variations in the set of script analytics compared to an aggregated data set; generating a traversable script update by automatically generating new traversable behavior based on the normative variations detected in the activity index, and enabling manual updates by generating a script editor that allows a user to modify the traversable script; sending the traversable script update to the synthetic character; and causing the traversable script update to be implemented by the synthetic character. 5. The method of claim 1 , wherein the synthetic character is a physical toy. | 0.751613 |
8,136,033 | 1 | 6 | 1. A computer-implemented method comprising: obtaining an electronic document in a first format, the electronic document comprising a graphic object represented using a main dataset and a private dataset; normalizing the main dataset of the graphic object of the electronic document stored in an object model in memory; computing a checksum for the normalized main dataset of the graphic object; comparing the computed checksum with a stored checksum located in the private dataset of the electronic document; and converting the electronic document from the first format to a second format based in part on a result of the comparing, wherein the converting comprises, when the computed checksum and the stored checksum do not match, propagating a change from the main dataset to the private dataset. | 1. A computer-implemented method comprising: obtaining an electronic document in a first format, the electronic document comprising a graphic object represented using a main dataset and a private dataset; normalizing the main dataset of the graphic object of the electronic document stored in an object model in memory; computing a checksum for the normalized main dataset of the graphic object; comparing the computed checksum with a stored checksum located in the private dataset of the electronic document; and converting the electronic document from the first format to a second format based in part on a result of the comparing, wherein the converting comprises, when the computed checksum and the stored checksum do not match, propagating a change from the main dataset to the private dataset. 6. The method of claim 1 , wherein the main dataset of the graphic object comprises code in an open data format and the private dataset of the graphic object comprises code in a proprietary data format. | 0.754258 |
10,062,031 | 3 | 4 | 3. The method of claim 1 , wherein: the personal data is distributed among the plurality of data sources. | 3. The method of claim 1 , wherein: the personal data is distributed among the plurality of data sources. 4. The method of claim 3 , further comprising: aggregating the personal data distributed among the plurality of data sources to define the cognitive profile. | 0.5 |
9,401,142 | 21 | 22 | 21. A system comprising: one or more physical processors programmed with one or more computer program instructions which, when executed, program the one or more physical processors to: obtain a transcription pair comprising natural language content and text, wherein the natural language content comprises audio content received from one or more audio input components, and wherein the text corresponds to a transcription of the natural language content; create a first crowdsourced validation job to be performed at one or more first validation devices, the first crowdsourced validation job providing the one or more first validation devices with first instructions for a crowd user to provide a determination of whether or not the text is an accurate transcription of the natural language content; cause the first crowdsourced validation job to be provided to the one or more first validation devices; receive, from each of the one or more first validation devices, a vote representing the determination of whether or not the text is an accurate transcription of the natural language content; assign a validation score to the transcription pair based, at least in part, on votes received from the one or more first validation devices with respect to the transcription pair; and store the transcription pair in a validated transcription library if the validation score of the transcription pair exceeds a validation threshold. | 21. A system comprising: one or more physical processors programmed with one or more computer program instructions which, when executed, program the one or more physical processors to: obtain a transcription pair comprising natural language content and text, wherein the natural language content comprises audio content received from one or more audio input components, and wherein the text corresponds to a transcription of the natural language content; create a first crowdsourced validation job to be performed at one or more first validation devices, the first crowdsourced validation job providing the one or more first validation devices with first instructions for a crowd user to provide a determination of whether or not the text is an accurate transcription of the natural language content; cause the first crowdsourced validation job to be provided to the one or more first validation devices; receive, from each of the one or more first validation devices, a vote representing the determination of whether or not the text is an accurate transcription of the natural language content; assign a validation score to the transcription pair based, at least in part, on votes received from the one or more first validation devices with respect to the transcription pair; and store the transcription pair in a validated transcription library if the validation score of the transcription pair exceeds a validation threshold. 22. The system of claim 21 , wherein the computer program instructions cause the one or more physical processors to use the transcription pair from the validated transcription to transcribe end-user voice data in real-time. | 0.5 |
9,092,478 | 5 | 9 | 5. The method of claim 1 , wherein searching one or more business objects data sources to identify data items of the plurality of data items stored in each of the searched one or more business objects data sources for data items that satisfy the identified metadata comprises identifying a plurality of tuples, each tuple including a first metadata portion and a second metadata portion, each of which satisfies the respective query term. | 5. The method of claim 1 , wherein searching one or more business objects data sources to identify data items of the plurality of data items stored in each of the searched one or more business objects data sources for data items that satisfy the identified metadata comprises identifying a plurality of tuples, each tuple including a first metadata portion and a second metadata portion, each of which satisfies the respective query term. 9. The method of claim 5 , further comprising ranking the plurality of tuples according to a relevance to the search query. | 0.726667 |
8,250,072 | 10 | 11 | 10. A computer-readable storage medium, having embodied thereon a program, the program being executable by a processor to perform a method for detecting real-word typos, the method comprising: receiving text designated for evaluation, the designated text comprising a plurality of words; parsing the plurality of words into a plurality of word groups, each word group comprising a number of consecutive words found in the designated text, identifying a database for comparison to the text, the database comprising a plurality of word groups previously identified in one or more source texts, each word group in the database comprising the number of consecutive words found in the one or more source texts, analyzing the word groups parsed from the designated text based on a comparison to the word groups in the identified database; and generating an indication that a word group from the designated text may include an error based on the analysis of the word group in comparison to the identified database, wherein the analysis comprises generating a typo likelihood value for each word group parsed from the designated text, and wherein the typo likelihood value of a word group parsed from the designated text is based on a product of a number of times each word in the word group appears in the database, the product divided by a number of times the word group comprising the consecutive words appears in the database. | 10. A computer-readable storage medium, having embodied thereon a program, the program being executable by a processor to perform a method for detecting real-word typos, the method comprising: receiving text designated for evaluation, the designated text comprising a plurality of words; parsing the plurality of words into a plurality of word groups, each word group comprising a number of consecutive words found in the designated text, identifying a database for comparison to the text, the database comprising a plurality of word groups previously identified in one or more source texts, each word group in the database comprising the number of consecutive words found in the one or more source texts, analyzing the word groups parsed from the designated text based on a comparison to the word groups in the identified database; and generating an indication that a word group from the designated text may include an error based on the analysis of the word group in comparison to the identified database, wherein the analysis comprises generating a typo likelihood value for each word group parsed from the designated text, and wherein the typo likelihood value of a word group parsed from the designated text is based on a product of a number of times each word in the word group appears in the database, the product divided by a number of times the word group comprising the consecutive words appears in the database. 11. The computer-readable storage medium of claim 10 , further comprising instructions for generating the database by: receiving a designated source text, the source text comprising a plurality of words; parsing the plurality of words into a plurality of word pairs, each word pair comprising two consecutive words found in the source text; and storing the parsed plurality of word pairs in a database. | 0.5 |
8,978,140 | 1 | 4 | 1. A computer-implemented method of categorizing a uniform resource locator (URL) based on web content associated with the URL, the method comprising: identifying a first URL using a first collection method of a plurality of collection methods, wherein each of the plurality of collection methods is performed using at least one electronic processor; determining, using an electronic processor, whether the first URL contains a malicious data element; categorizing, using an electronic processor, the first URL in response to a determination that the first URL contains a malicious data element; in response to determining the first URL does not contain a malicious data element: assigning, using an electronic processor, a first categorization priority to the first URL based on the first URL being identified using the first collection method, and categorizing, using an electronic processor, the first URL based on the first categorization priority, wherein categorization of a URL comprises assigning a category to the URL based on a classification of at least one of web content or an Internet Protocol (IP) address identified by the URL; identifying a second URL using a second collection method, wherein the first collection method and the second collection method are different and each are one of a web crawler, a Domain Name Server (DNS) database, and a honey client; determining, using an electronic processor, whether the second URL contains a malicious data element; categorizing, using an electronic processor, the second URL in response to a determination that the second URL contains a malicious data element; in response to determining the second URL does not contain a malicious data element: assigning, using an electronic processor, a second categorization priority different than the first categorization priority based on the second URL having been identified using the second collection method, and categorizing, using an electronic processor, the second URL based on the second categorization priority. | 1. A computer-implemented method of categorizing a uniform resource locator (URL) based on web content associated with the URL, the method comprising: identifying a first URL using a first collection method of a plurality of collection methods, wherein each of the plurality of collection methods is performed using at least one electronic processor; determining, using an electronic processor, whether the first URL contains a malicious data element; categorizing, using an electronic processor, the first URL in response to a determination that the first URL contains a malicious data element; in response to determining the first URL does not contain a malicious data element: assigning, using an electronic processor, a first categorization priority to the first URL based on the first URL being identified using the first collection method, and categorizing, using an electronic processor, the first URL based on the first categorization priority, wherein categorization of a URL comprises assigning a category to the URL based on a classification of at least one of web content or an Internet Protocol (IP) address identified by the URL; identifying a second URL using a second collection method, wherein the first collection method and the second collection method are different and each are one of a web crawler, a Domain Name Server (DNS) database, and a honey client; determining, using an electronic processor, whether the second URL contains a malicious data element; categorizing, using an electronic processor, the second URL in response to a determination that the second URL contains a malicious data element; in response to determining the second URL does not contain a malicious data element: assigning, using an electronic processor, a second categorization priority different than the first categorization priority based on the second URL having been identified using the second collection method, and categorizing, using an electronic processor, the second URL based on the second categorization priority. 4. The computer-implemented method of claim 1 , further comprising: identifying a third URL using a third collection method, and categorizing the third URL at a different priority than categorization of the first and second URLs based on the third URL having been identified using the third collection method, wherein the third collection method includes one of a known malicious URL received from an external organization, and an email module configured to receive URLs via email. | 0.5 |
4,090,173 | 15 | 17 | 15. A vital decoder for a digital message which digital message includes a pair of multi-bit words separated from other words by a predetermined multi-bit framing sequence, a second word of said message complementary to a first word, said decoder including a single central processing means, said central processing means including: means responsive to said framing sequence for identifying each multi-bit word; means responsive to each said multi-bit word for determining a command represented thereby; checking means for checking control of said central processing means over its own output ports, said checking means producing one of two distinctive multi-bit words in response to completion of said checking after receipt of each said message word, said distinctive multi-bit words being complementary if said message words are valid and said checks are favorable, said decoder further including; logic means responsive to said distinctive multi-bit words for validating operation of said central processing means, said logic means including a multi-bit comparator for comparing said distinctive words to predetermined bit patterns and validating said operation if, and only if, said distinctive words are produced alternately and in sequence, and means responsive to validation by said logic means for enabling utilization of a command provided by said central processing means. | 15. A vital decoder for a digital message which digital message includes a pair of multi-bit words separated from other words by a predetermined multi-bit framing sequence, a second word of said message complementary to a first word, said decoder including a single central processing means, said central processing means including: means responsive to said framing sequence for identifying each multi-bit word; means responsive to each said multi-bit word for determining a command represented thereby; checking means for checking control of said central processing means over its own output ports, said checking means producing one of two distinctive multi-bit words in response to completion of said checking after receipt of each said message word, said distinctive multi-bit words being complementary if said message words are valid and said checks are favorable, said decoder further including; logic means responsive to said distinctive multi-bit words for validating operation of said central processing means, said logic means including a multi-bit comparator for comparing said distinctive words to predetermined bit patterns and validating said operation if, and only if, said distinctive words are produced alternately and in sequence, and means responsive to validation by said logic means for enabling utilization of a command provided by said central processing means. 17. The apparatus of claim 15 in which said central processing means modifies each multibit word, derives, from a table, a numerical quantity corresponding to said modified multibit word, and uses said numerical quantity in producing said distinctive multibit word. | 0.748099 |
8,275,613 | 7 | 14 | 7. The voice recording recited in claim 1 is transcribed/proofread by any source or system so a subsequent transcript can be submitted by the means recited computer processing for use by the dictationbase system comprising steps of: Including: a) creating the dictationbase dictation application for one or more documents wherein the tagged subject identifiers are stored in the dictationbase by the means computer processing from preformatted word processing templates or list to be used to assemble documents including matching dictated subject captions together with prose, type once data subject identifiers for subsequent transcript processing, including a plurality of tagged subject identifiers comprised of each subject, document element, database field and prescribed connections to resource systems, type once data fields, industry standard identification or staff assigned document data subject/elements; b) the dictation user designated for each application assigns and enters familiar (one or more words) comprising subject identification for dictated subject captions in their dictation routine or uses the subject identifiers absent any assigned entry as the dictated subject captions; c) the dictationbase application produces the reminder list of dictation subject captions to guide the user for the voice recording technique recited in claim 1 comprised of uttering the dictation subject captions with or without modifiers followed by free expression information relevant to said subjects and at least one term indicating an end of said information “end-it”; d) the voice recording dictated in claim 1 is transcribed so the subsequent transcript text file with dictated subject captions including prose can be processed by submitting for computer processing including dictated subject captions review for user dictated modifiers and assembly functions for preformatted documents as well as storing each captured dictated subject caption with dictated prose in the dictationbase by all identifications. e) the computer processing recited in claim 1 comprised of assembling one or more documents while capturing and storing a plurality of dictated subject captions with prose as computable data in the dictationbase including executing prescribed connection updates for resource database fields. | 7. The voice recording recited in claim 1 is transcribed/proofread by any source or system so a subsequent transcript can be submitted by the means recited computer processing for use by the dictationbase system comprising steps of: Including: a) creating the dictationbase dictation application for one or more documents wherein the tagged subject identifiers are stored in the dictationbase by the means computer processing from preformatted word processing templates or list to be used to assemble documents including matching dictated subject captions together with prose, type once data subject identifiers for subsequent transcript processing, including a plurality of tagged subject identifiers comprised of each subject, document element, database field and prescribed connections to resource systems, type once data fields, industry standard identification or staff assigned document data subject/elements; b) the dictation user designated for each application assigns and enters familiar (one or more words) comprising subject identification for dictated subject captions in their dictation routine or uses the subject identifiers absent any assigned entry as the dictated subject captions; c) the dictationbase application produces the reminder list of dictation subject captions to guide the user for the voice recording technique recited in claim 1 comprised of uttering the dictation subject captions with or without modifiers followed by free expression information relevant to said subjects and at least one term indicating an end of said information “end-it”; d) the voice recording dictated in claim 1 is transcribed so the subsequent transcript text file with dictated subject captions including prose can be processed by submitting for computer processing including dictated subject captions review for user dictated modifiers and assembly functions for preformatted documents as well as storing each captured dictated subject caption with dictated prose in the dictationbase by all identifications. e) the computer processing recited in claim 1 comprised of assembling one or more documents while capturing and storing a plurality of dictated subject captions with prose as computable data in the dictationbase including executing prescribed connection updates for resource database fields. 14. The system of claim 7 , wherein users organize, define, and automate dictation applications to capture identified data while assembling formatted documents. | 0.782609 |
8,943,089 | 18 | 19 | 18. A non-transitory computer readable storage medium storing one or more programs configured for execution by a client device, the one or more programs comprising instructions for: sending, to the online media store, a search hints request from a client application operating on the client device at a location, the search hints request including at least a character string including at least one character, the online media store having a hints data structure that includes a set of search hints matching the character string, wherein the set of search hints correspond to digital media assets available in an online media repository of the online media store; receiving, at the client application on the client device, a portion of the search hints in the set of search hints, the portion of the search hints sent to the client application being less than all the search hints in the set of search hints, and wherein the received portion does not include search hints in the set of search hints that are associated with a location other than the location of the client device; and displaying search hints from the portion of the search hints. | 18. A non-transitory computer readable storage medium storing one or more programs configured for execution by a client device, the one or more programs comprising instructions for: sending, to the online media store, a search hints request from a client application operating on the client device at a location, the search hints request including at least a character string including at least one character, the online media store having a hints data structure that includes a set of search hints matching the character string, wherein the set of search hints correspond to digital media assets available in an online media repository of the online media store; receiving, at the client application on the client device, a portion of the search hints in the set of search hints, the portion of the search hints sent to the client application being less than all the search hints in the set of search hints, and wherein the received portion does not include search hints in the set of search hints that are associated with a location other than the location of the client device; and displaying search hints from the portion of the search hints. 19. The non-transitory computer readable storage medium of claim 18 , wherein the received portion is limited to a maximum number of search hints, and wherein the displayed words are ordered based on sales popularity data. | 0.626263 |
9,436,452 | 8 | 10 | 8. A non-transitory computer readable medium that includes instructions that cause a data processing system to examine a compiled program for violations of a set of rules that do not constitute violations detected by the compiler that compiled the compiled program using a method comprising: obtaining a restricted rule set defined in terms of rules in a decompiled representation of said program, said restricted rule set prohibiting language commands that would otherwise be allowed by said compiler in a subset of classes in said compiled program while allowing said language commands in another class of said program; decompiling said compiled program to said decompiled representation of said compiled program in which said restricted rule set is defined; examining said decompiled representation of said compiled program for a violation of said restricted rule set to determine if any of said rules are violated; and providing an output indicating that one of said rules was violated, wherein said restricted rule set only applies to a portion of said compiled program and wherein decompiling said compiled program comprises decompiling said portion of said compiled program while not decompiling another portion of said compiled program, said portion of said compiled program comprising a set of sub-classes of a class, and wherein decompiling said program comprises identifying a location in said compiled program of instructions pertaining to said set of sub-classes, said data processing system generating a certificate if said compiled program does not violate said restricted rule set. | 8. A non-transitory computer readable medium that includes instructions that cause a data processing system to examine a compiled program for violations of a set of rules that do not constitute violations detected by the compiler that compiled the compiled program using a method comprising: obtaining a restricted rule set defined in terms of rules in a decompiled representation of said program, said restricted rule set prohibiting language commands that would otherwise be allowed by said compiler in a subset of classes in said compiled program while allowing said language commands in another class of said program; decompiling said compiled program to said decompiled representation of said compiled program in which said restricted rule set is defined; examining said decompiled representation of said compiled program for a violation of said restricted rule set to determine if any of said rules are violated; and providing an output indicating that one of said rules was violated, wherein said restricted rule set only applies to a portion of said compiled program and wherein decompiling said compiled program comprises decompiling said portion of said compiled program while not decompiling another portion of said compiled program, said portion of said compiled program comprising a set of sub-classes of a class, and wherein decompiling said program comprises identifying a location in said compiled program of instructions pertaining to said set of sub-classes, said data processing system generating a certificate if said compiled program does not violate said restricted rule set. 10. The computer readable medium of claim 8 wherein said compiled program further comprises metadata that identifies locations in said compiled program of methods pertaining to said set of sub-classes. | 0.7 |
7,856,472 | 6 | 10 | 6. The method of claim 5 , and further comprising, utilizing the at least one window, displaying, in response to a second user interaction, the second additional information associated with the second message. | 6. The method of claim 5 , and further comprising, utilizing the at least one window, displaying, in response to a second user interaction, the second additional information associated with the second message. 10. The method of claim 6 , wherein the first additional information and the second additional information are displayed utilizing a tooltip. | 0.670561 |
8,229,883 | 5 | 6 | 5. The non-transitory computer-readable storage medium of claim 4 having instructions that when executed further cause the machine to: create a set of unambiguous graph variants for each graph in the set of entity graphs; and create a set of groups, each group including a subset of the set of entity graphs and representing interpretations of the at least one of the queried plurality of text segments. | 5. The non-transitory computer-readable storage medium of claim 4 having instructions that when executed further cause the machine to: create a set of unambiguous graph variants for each graph in the set of entity graphs; and create a set of groups, each group including a subset of the set of entity graphs and representing interpretations of the at least one of the queried plurality of text segments. 6. The non-transitory computer-readable storage medium of claim 5 having instructions that when executed further cause the machine to: sum the weight values for the matching attributes and associated relationships in each entity graph of the set of groups; and select an entity graph from each group of the set of groups, the entity graph having a best weight value and representing a best interpretation of the at least one of the queried plurality of text segments. | 0.5 |
9,977,715 | 11 | 13 | 11. An apparatus, comprising: a processor circuit coupled to memory; and an application program stored in the memory and operative to: retrieve, by the processor circuit, a set of undo records of a local undo stack, each undo record comprising information to undo a modification made to a construct of a first document instance of a collaborative document, retrieve, by the processor circuit, a set of change records of a document update list, each change record comprising information for a modification made to a construct of a second document instance of the collaborative document, determine, by the processor circuit, whether a time stamp of an undo record and a time stamp of a change record are both within a synchronization interval when the undo record and the change record have matching constructs, and if so, annotate the undo record as a conflict record and delete the local undo stack, compare, by the processor circuit, the set of undo records and the set of change records to produce comparison results, and determine whether to preserve, by the processor circuit, one or more of the undo records of the local undo stack based on the comparison results. | 11. An apparatus, comprising: a processor circuit coupled to memory; and an application program stored in the memory and operative to: retrieve, by the processor circuit, a set of undo records of a local undo stack, each undo record comprising information to undo a modification made to a construct of a first document instance of a collaborative document, retrieve, by the processor circuit, a set of change records of a document update list, each change record comprising information for a modification made to a construct of a second document instance of the collaborative document, determine, by the processor circuit, whether a time stamp of an undo record and a time stamp of a change record are both within a synchronization interval when the undo record and the change record have matching constructs, and if so, annotate the undo record as a conflict record and delete the local undo stack, compare, by the processor circuit, the set of undo records and the set of change records to produce comparison results, and determine whether to preserve, by the processor circuit, one or more of the undo records of the local undo stack based on the comparison results. 13. The apparatus of claim 11 , wherein the application program is further operative to remove an undo record from the local undo stack when the undo record is annotated as a conflict record. | 0.602083 |
7,645,294 | 30 | 32 | 30. The spinal fixation system of claim 29 , wherein the proximal surface of the rod receiving portion is spherical and has a radius of curvature that extends from the point about which the bone screw portion pivots. | 30. The spinal fixation system of claim 29 , wherein the proximal surface of the rod receiving portion is spherical and has a radius of curvature that extends from the point about which the bone screw portion pivots. 32. The spinal fixation system of claim 30 , further includes a set screw that threadably engages the rod receiving portion and a cap that threadably engages the set screw, the cap including a distal bearing surface that has a radius of curvature that extends from the point about which the bone screw portion pivots. | 0.5 |
9,915,548 | 1 | 3 | 1. A method for presenting a contextual menu in a map user interface, comprising: receiving a user input that is drawn over the map user interface to delineate a route, a geographical area, or a combination thereof depicted in the map user interface; identifying contextual information associated with mapping data of the route, the geographical area, or a combination thereof; determining one or more functions of one or more services based on the contextual information; and initiating a presentation of the one or more functions as one or more contextual menu options of a contextual menu, wherein the contextual menu is rendered over the map user interface. | 1. A method for presenting a contextual menu in a map user interface, comprising: receiving a user input that is drawn over the map user interface to delineate a route, a geographical area, or a combination thereof depicted in the map user interface; identifying contextual information associated with mapping data of the route, the geographical area, or a combination thereof; determining one or more functions of one or more services based on the contextual information; and initiating a presentation of the one or more functions as one or more contextual menu options of a contextual menu, wherein the contextual menu is rendered over the map user interface. 3. The method of claim 1 , wherein the one or more functions includes at least one of performing a search, exploring the route or the geographical area, retrieving transit information, sharing the route or the geographical area, collecting the route or the geographical area, viewing social graphs based on the route or the geographical area, initiating a meeting based on the route or the geographical area, and initiating an application based on the route or the geographical area. | 0.5 |
10,032,191 | 19 | 20 | 19. The method of claim 12 , further comprising: accessing a pairing server when processing an identification data associated with the sandbox reachable service of the networked device that shares a public address with the client device, wherein the pairing server performs a discovery lookup of any device that has announced that it shares the public address associated with the client device, and wherein the sandbox reachable service announces itself to the pairing server prior to establishment of a communication session between the sandboxed application and the sandbox reachable service; appending a header of a hypertext transfer protocol to permit the networked device to communicate with the sandboxed application as a permitted origin domain through a CORS algorithm, the header being either one of a origin header when the CORS algorithm is applied and a referrer header in an alternate algorithm in accordance with the client device: processing the identification data associated with the sandbox reachable service sharing the public address with the client device; determining a private address pair of the sandbox reachable service based on the identification data; and establishing the communication session between the sandboxed application and the sandbox reachable service using a cross-site scripting technique of the security sandbox, wherein the sandboxed application queries a MAC address of the sandbox reachable service in a common private network, wherein the method further comprises the sandbox reachable service optionally verifying that the sandboxed application is in the common private network, wherein the method further comprises the sandbox reachable service communicating a MAC address of the sandboxed application to the sandboxed application when the common private network is shared, wherein the sandboxed application stores the MAC address of the sandboxed application and a unique identifier derived from the MAC address of the sandboxed application, and wherein the sandboxed application communicates the MAC address and the unique identifier to the pairing server; and automatically regenerating the script embedded in the at least one of the client device, the supply-side platform, and the data provider integrated with the supply side platform when the common private network is shared by the sandboxed application and the sandbox reachable service based on the MAC address of the sandboxed application and the unique identifier communicated to the pairing server. | 19. The method of claim 12 , further comprising: accessing a pairing server when processing an identification data associated with the sandbox reachable service of the networked device that shares a public address with the client device, wherein the pairing server performs a discovery lookup of any device that has announced that it shares the public address associated with the client device, and wherein the sandbox reachable service announces itself to the pairing server prior to establishment of a communication session between the sandboxed application and the sandbox reachable service; appending a header of a hypertext transfer protocol to permit the networked device to communicate with the sandboxed application as a permitted origin domain through a CORS algorithm, the header being either one of a origin header when the CORS algorithm is applied and a referrer header in an alternate algorithm in accordance with the client device: processing the identification data associated with the sandbox reachable service sharing the public address with the client device; determining a private address pair of the sandbox reachable service based on the identification data; and establishing the communication session between the sandboxed application and the sandbox reachable service using a cross-site scripting technique of the security sandbox, wherein the sandboxed application queries a MAC address of the sandbox reachable service in a common private network, wherein the method further comprises the sandbox reachable service optionally verifying that the sandboxed application is in the common private network, wherein the method further comprises the sandbox reachable service communicating a MAC address of the sandboxed application to the sandboxed application when the common private network is shared, wherein the sandboxed application stores the MAC address of the sandboxed application and a unique identifier derived from the MAC address of the sandboxed application, and wherein the sandboxed application communicates the MAC address and the unique identifier to the pairing server; and automatically regenerating the script embedded in the at least one of the client device, the supply-side platform, and the data provider integrated with the supply side platform when the common private network is shared by the sandboxed application and the sandbox reachable service based on the MAC address of the sandboxed application and the unique identifier communicated to the pairing server. 20. The method of claim 19 , wherein the communication session is established between the sandboxed application and the sandbox reachable service in accordance with the client device: extending the security sandbox with a discovery algorithm and a relay algorithm through a discovery module and a relay module added to the security sandbox; and bypassing the pairing server having a discovery algorithm and a relay algorithm when establishing the communication session between the sandboxed application and the sandbox reachable service when the security sandbox is extended with the discovery algorithm and the relay algorithm through the discovery module and the relay module added to the security sandbox. | 0.622199 |
9,350,753 | 3 | 6 | 3. The method of claim 1 , further comprising: providing the invited researcher, prior to receiving the report, an indication of an award to be awarded in response to finding target system vulnerabilities that are subsequently validated through attempted duplication; and crediting the invited researcher with the award after validation of finding of the target system vulnerabilities. | 3. The method of claim 1 , further comprising: providing the invited researcher, prior to receiving the report, an indication of an award to be awarded in response to finding target system vulnerabilities that are subsequently validated through attempted duplication; and crediting the invited researcher with the award after validation of finding of the target system vulnerabilities. 6. The method of claim 3 , wherein the award for a given target system vulnerability is calculated according to a weighted impact score and an exploitability score, wherein the weighted impact score is a function of an impact score that is a function of a confidentiality impact metric, an integrity impact metric, and an availability impact metric, and wherein the exploitability score is a function of an access complexity metric, an authentication metric, and an access weighting. | 0.648983 |
9,864,803 | 7 | 11 | 7. A system for multimodal clue based personalized app function recommendation, comprising: a mobile clues module configured to obtain a plurality of real-time clues collected from a user; a user preference repository module configured to: extract a plurality of features to represent the plurality of real-time clues collected from the user, wherein the plurality of features include structured features and text features; use a multimodal Deep Boltzmann Machine (DBM) to construct two separate two-layer DBMs to model distribution over the structured features and the text features, respectively; and combine the two separate two-layer DBMs by adding an additional layer of binary hidden units on the top of the two-layer DBMs; and based on the plurality of extracted features, generate a joint representation of a multimodal clue; an app function recommendation module configured to create a logistic regression model based on the joint representation of the multimodal clue and rank a list of app functions using the logistic regression model; and an app functions module configured to display a ranked app function list for the user. | 7. A system for multimodal clue based personalized app function recommendation, comprising: a mobile clues module configured to obtain a plurality of real-time clues collected from a user; a user preference repository module configured to: extract a plurality of features to represent the plurality of real-time clues collected from the user, wherein the plurality of features include structured features and text features; use a multimodal Deep Boltzmann Machine (DBM) to construct two separate two-layer DBMs to model distribution over the structured features and the text features, respectively; and combine the two separate two-layer DBMs by adding an additional layer of binary hidden units on the top of the two-layer DBMs; and based on the plurality of extracted features, generate a joint representation of a multimodal clue; an app function recommendation module configured to create a logistic regression model based on the joint representation of the multimodal clue and rank a list of app functions using the logistic regression model; and an app functions module configured to display a ranked app function list for the user. 11. The system according to claim 7 , wherein: based on the size of a display screen of a mobile device, the user sets a total number of recommended app functions included in the ranked app function list. | 0.861413 |
8,523,572 | 41 | 54 | 41. A system for communicating visual images to a handicapped person, said system comprising: at least one device for physically transmitting information about said visual images to said handicapped person; and said at least one device including means for delivering a physical signal representative of a key word associated with said visual images to a first part of a body of said handicapped person, wherein said at least one device further comprises means for delivering at least one physical input describing a dynamic element associated with said key word to a palm of said handicapped person; and wherein Dividing the fingers of a hand of said handicapped person into a first group consisting of a pointer finger and a middle finger and into a second group consisting of a ring finger and a pinky and said transmitting step comprises transmitting information about a bad character to one of said fingers of said first group and transmitting information about a good character to one of said fingers of said second group. | 41. A system for communicating visual images to a handicapped person, said system comprising: at least one device for physically transmitting information about said visual images to said handicapped person; and said at least one device including means for delivering a physical signal representative of a key word associated with said visual images to a first part of a body of said handicapped person, wherein said at least one device further comprises means for delivering at least one physical input describing a dynamic element associated with said key word to a palm of said handicapped person; and wherein Dividing the fingers of a hand of said handicapped person into a first group consisting of a pointer finger and a middle finger and into a second group consisting of a ring finger and a pinky and said transmitting step comprises transmitting information about a bad character to one of said fingers of said first group and transmitting information about a good character to one of said fingers of said second group. 54. A system according to claim 41 , wherein said at least one device comprises means for transmitting information about said visual images to a front portion of at least one finger. | 0.669091 |
9,710,613 | 18 | 22 | 18. A method for guiding operation of an application on a first device, the method performed by a second device and comprising: entering into a session with the first device, wherein, during the session, a user of the second device specifies a phrase that is spoken by a character to a user of the first device and wherein the user of the first device and the user of the second device participate simultaneously in the session; receiving audio data, wherein the audio data represents speech of the user of the first device; causing audio to be played using the audio data; receiving a plurality of phrases as suggestions of phrases to be spoken by the character displayed on the first device; presenting the plurality of phrases on a display of the second device; receiving an input from the user of the second device that specifies a selected phrase; and causing phrase data to be transmitted to the first device, wherein the phrase data corresponds to the selected phrase. | 18. A method for guiding operation of an application on a first device, the method performed by a second device and comprising: entering into a session with the first device, wherein, during the session, a user of the second device specifies a phrase that is spoken by a character to a user of the first device and wherein the user of the first device and the user of the second device participate simultaneously in the session; receiving audio data, wherein the audio data represents speech of the user of the first device; causing audio to be played using the audio data; receiving a plurality of phrases as suggestions of phrases to be spoken by the character displayed on the first device; presenting the plurality of phrases on a display of the second device; receiving an input from the user of the second device that specifies a selected phrase; and causing phrase data to be transmitted to the first device, wherein the phrase data corresponds to the selected phrase. 22. The method of claim 18 , wherein the audio data is received in real time. | 0.910465 |
9,697,099 | 12 | 15 | 12. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: identify a set of features that contribute to generating candidate answers for input questions; identify a set of annotation engines in the ingestion pipeline that contribute to each of the set of features and at least one annotation engine on which the one or more annotation engines depend; generate a sub-pipeline for each set of annotation engines to form a plurality of sub-pipelines of annotation engines; receive new content to be ingested into a corpus of information; apply a plurality of sub-pipelines of annotation engines against the new content in order of effectiveness, wherein the plurality of sub-pipelines include all annotation engines of an ingestion pipeline and wherein each sub-pipeline within the plurality of sub-pipelines generates one or more intermediate output objects; and provide access to the one or more intermediate output objects, wherein the one or more intermediate output objects represent the partially ingested new content. | 12. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to: identify a set of features that contribute to generating candidate answers for input questions; identify a set of annotation engines in the ingestion pipeline that contribute to each of the set of features and at least one annotation engine on which the one or more annotation engines depend; generate a sub-pipeline for each set of annotation engines to form a plurality of sub-pipelines of annotation engines; receive new content to be ingested into a corpus of information; apply a plurality of sub-pipelines of annotation engines against the new content in order of effectiveness, wherein the plurality of sub-pipelines include all annotation engines of an ingestion pipeline and wherein each sub-pipeline within the plurality of sub-pipelines generates one or more intermediate output objects; and provide access to the one or more intermediate output objects, wherein the one or more intermediate output objects represent the partially ingested new content. 15. The computer program product of claim 12 , wherein providing access to the one or more intermediate output objects comprises mapping the new content being ingested to the one or more intermediate output objects, wherein the computer readable program further causes the computing device to: responsive to receiving an input question in a question answering system, run a question answering pipeline of software engines against available partially and fully ingested content according to the mapping; generate one or more candidate answers for the input question; rank the one or more candidate answers; and present the ranked one or more candidate answers. | 0.5 |
9,965,468 | 4 | 5 | 4. The method according to claim 1 , wherein matching the value of the language attribute of the specified resource element in the media element with the language information in the language list, and wherein selecting the media resource address comprises: successively extracting the language information in the language list when the specified resource element in the media element has the language attribute; successively matching the extracted language information with values of language attributes of all specified resource elements in the media element; selecting the media resource address specified by a value of a resource address attribute of a first specified resource element when there is a matched value of the language attribute of the first specified resource element; selecting the media resource address specified by the value of the resource address attribute of the resource element that is first specified in the media element when there is no matched value of the language attribute of the first specified resource element; and selecting the media resource address specified by the value of the resource address attribute of the resource element that is first specified in the media element when the specified resource element in the media element has no language attribute. | 4. The method according to claim 1 , wherein matching the value of the language attribute of the specified resource element in the media element with the language information in the language list, and wherein selecting the media resource address comprises: successively extracting the language information in the language list when the specified resource element in the media element has the language attribute; successively matching the extracted language information with values of language attributes of all specified resource elements in the media element; selecting the media resource address specified by a value of a resource address attribute of a first specified resource element when there is a matched value of the language attribute of the first specified resource element; selecting the media resource address specified by the value of the resource address attribute of the resource element that is first specified in the media element when there is no matched value of the language attribute of the first specified resource element; and selecting the media resource address specified by the value of the resource address attribute of the resource element that is first specified in the media element when the specified resource element in the media element has no language attribute. 5. The method according to claim 4 , wherein the media element comprises a video element, an audio element, and a subtitle element. | 0.5 |
9,020,911 | 10 | 13 | 10. A computer system for matching names, comprising: a processor; and a storage device coupled to the processor, wherein the storage device has stored thereon a program, and wherein the processor is configured to execute instructions of the program to perform operations, wherein the operations comprise: creating a first bitmap distribution of character n-grams distributed into bitmap positions in descending order of frequency of occurrence of the character n-grams in a set of names based on bitmap positions with a lowest cumulative frequency, wherein at least two distinct character n-grams are assigned to a same bitmap position of the bitmap positions; creating a second bitmap distribution of the character n-grams distributed into the bitmap positions so that the at least two distinct character n-grams are assigned to different bitmap positions and so that any overlapping character n-grams in the first bitmap distribution do not overlap in the second bitmap distribution; using the first bitmap distribution, determining whether a first bitmap signature of a query name and a second bitmap signature of a target name in a set of names have a number of character n-grams overlapping that meet or exceed a first configurable threshold to generate a first preliminary value; using the second bitmap distribution, determining whether a third bitmap signature of the query name and a fourth bitmap signature of the target name have a number of character n-grams overlapping that meet or exceed a second configurable threshold to generate a second preliminary value; and in response to determining that a logical operation applied to the first preliminary value and the second preliminary value results in a value of true, determining that the query name and the target name are to be processed for further comparisons. | 10. A computer system for matching names, comprising: a processor; and a storage device coupled to the processor, wherein the storage device has stored thereon a program, and wherein the processor is configured to execute instructions of the program to perform operations, wherein the operations comprise: creating a first bitmap distribution of character n-grams distributed into bitmap positions in descending order of frequency of occurrence of the character n-grams in a set of names based on bitmap positions with a lowest cumulative frequency, wherein at least two distinct character n-grams are assigned to a same bitmap position of the bitmap positions; creating a second bitmap distribution of the character n-grams distributed into the bitmap positions so that the at least two distinct character n-grams are assigned to different bitmap positions and so that any overlapping character n-grams in the first bitmap distribution do not overlap in the second bitmap distribution; using the first bitmap distribution, determining whether a first bitmap signature of a query name and a second bitmap signature of a target name in a set of names have a number of character n-grams overlapping that meet or exceed a first configurable threshold to generate a first preliminary value; using the second bitmap distribution, determining whether a third bitmap signature of the query name and a fourth bitmap signature of the target name have a number of character n-grams overlapping that meet or exceed a second configurable threshold to generate a second preliminary value; and in response to determining that a logical operation applied to the first preliminary value and the second preliminary value results in a value of true, determining that the query name and the target name are to be processed for further comparisons. 13. The computer system of claim 10 , wherein the logical operation comprises a logical AND operation between the first preliminary value and the second preliminary value. | 0.881906 |
8,639,493 | 1 | 9 | 1. A method for natural language processing on a computing device, comprising: receiving a free text document; parsing, on a computing device, the free text document for gross structure, wherein the gross structure comprises sections, paragraphs and sentences; determining, on the computing device, an application of at least one knowledge base; parsing the free text document for fine structure on the computing device, wherein the fine structure comprises sub-sentences; applying, on the computing device, the parsed document and at least one likelihood vector to a Bayesian network, wherein applying the parsed document and the at least one likelihood vector to the Bayesian network comprises: identifying, on the computing device, possible sets of word-level network assignments for lowest-level phrases in a parse tree; identifying, on the computing device, assignments that have multiple different potential assignments; creating, on the computing device, likelihood vectors for all nodes of the Bayesian network, wherein the likelihood vectors cover all potential assignments; instantiating the likelihood vectors on the computing device; identifying, on the computing device, optimal null assignments for unassigned word-level nodes; and selecting, on the computing device, the highest probability state for each node to obtain an interpretation of the free text document; and outputting meanings and probabilities from the computing device. | 1. A method for natural language processing on a computing device, comprising: receiving a free text document; parsing, on a computing device, the free text document for gross structure, wherein the gross structure comprises sections, paragraphs and sentences; determining, on the computing device, an application of at least one knowledge base; parsing the free text document for fine structure on the computing device, wherein the fine structure comprises sub-sentences; applying, on the computing device, the parsed document and at least one likelihood vector to a Bayesian network, wherein applying the parsed document and the at least one likelihood vector to the Bayesian network comprises: identifying, on the computing device, possible sets of word-level network assignments for lowest-level phrases in a parse tree; identifying, on the computing device, assignments that have multiple different potential assignments; creating, on the computing device, likelihood vectors for all nodes of the Bayesian network, wherein the likelihood vectors cover all potential assignments; instantiating the likelihood vectors on the computing device; identifying, on the computing device, optimal null assignments for unassigned word-level nodes; and selecting, on the computing device, the highest probability state for each node to obtain an interpretation of the free text document; and outputting meanings and probabilities from the computing device. 9. The method of claim 1 , wherein applying the at least one likelihood vector allows multiple nodes to be replaced with a signal node, wherein at least one token may be slotted without concern for multiple choices. | 0.646382 |
7,640,235 | 3 | 4 | 3. The method of claim 2 , wherein binding the web application context, to the SQL query, further comprises: receiving a SQL query; converting the SQL query to a SQL template; searching in a SQL NBP for URLs that correlate to the SQL template; for HTTP request with a correlated URL, matching between parameters of the HTTP request and literals of the SQL query; computing a matching score for each HTTP request; selecting the HTTP request with the highest correlate score; and binding the web context web application context of the selected HTTP request to the incoming SQL query. | 3. The method of claim 2 , wherein binding the web application context, to the SQL query, further comprises: receiving a SQL query; converting the SQL query to a SQL template; searching in a SQL NBP for URLs that correlate to the SQL template; for HTTP request with a correlated URL, matching between parameters of the HTTP request and literals of the SQL query; computing a matching score for each HTTP request; selecting the HTTP request with the highest correlate score; and binding the web context web application context of the selected HTTP request to the incoming SQL query. 4. The method of claim 3 , wherein the web application context includes at least one of: a session identifier (sessionID), and a user identity. | 0.5 |
9,514,219 | 5 | 6 | 5. A system according to claim 4 , further comprising: a further document selection module to select the unclassified documents with similar text when the text is less inclusive of the words in the search string than the text that is the same as the compared portion of the highlighted text in the document. | 5. A system according to claim 4 , further comprising: a further document selection module to select the unclassified documents with similar text when the text is less inclusive of the words in the search string than the text that is the same as the compared portion of the highlighted text in the document. 6. A system according to claim 5 , further comprising: a review module to perform quality control review of the search string via at least one of sensitivity analysis and sampling. | 0.694915 |
8,849,693 | 39 | 41 | 39. A tangible computer-readable medium comprising computer-executable instructions that when executed on a processor performs the following steps: managing electronic advertisement service orders selected from a menu providing a plurality of advertisement services, each of said advertisement services including: an advertisement format specific to the advertisement service, an associated display area in which the advertising service is to be presented, the associated display area corresponding to one of a plurality of display areas, where the plurality of display areas include: a priority placement area, and at least one other placement area, and an associated advertiser priority indicating a particular order for presenting the advertising service relative to other advertising services; establishing the advertisement format as including presentation information specific to the advertising service such that the plurality of advertising services collectively include a plurality of different advertisement formats; providing secure access to advertisements and business information; providing automated payment transactions generated in accordance with a predetermined advertisement payment schedule; managing advertising services presented to an advertiser in accordance with a particular business listing; managing advertisement content and business listing selection activity associated with a particular advertiser; posting and verifying charges electronically; and publishing the advertisement in said display area associated with said selected advertising service, said advertisement presented in a particular order relative to other advertisements based on said advertiser priority associated with said selected advertising service. | 39. A tangible computer-readable medium comprising computer-executable instructions that when executed on a processor performs the following steps: managing electronic advertisement service orders selected from a menu providing a plurality of advertisement services, each of said advertisement services including: an advertisement format specific to the advertisement service, an associated display area in which the advertising service is to be presented, the associated display area corresponding to one of a plurality of display areas, where the plurality of display areas include: a priority placement area, and at least one other placement area, and an associated advertiser priority indicating a particular order for presenting the advertising service relative to other advertising services; establishing the advertisement format as including presentation information specific to the advertising service such that the plurality of advertising services collectively include a plurality of different advertisement formats; providing secure access to advertisements and business information; providing automated payment transactions generated in accordance with a predetermined advertisement payment schedule; managing advertising services presented to an advertiser in accordance with a particular business listing; managing advertisement content and business listing selection activity associated with a particular advertiser; posting and verifying charges electronically; and publishing the advertisement in said display area associated with said selected advertising service, said advertisement presented in a particular order relative to other advertisements based on said advertiser priority associated with said selected advertising service. 41. The system of claim 39 , the instructions further including instructions for: enabling the advertiser to securely connect through a network to communicate with other components of the system. | 0.76335 |
8,706,740 | 13 | 17 | 13. A method for synthesizing a new image, comprising: displaying on a display a window for entering a concept-structured query in the form of a concept-structured layout of an image to be synthesized from a set of images; receiving a concept-structured layout via a window by placing one or more image concepts in locations on the window using a user interface data entry device; using the input concept-structured layout to find a group of representative images in the image set for each concept in each location in the window; determining the best representative image from each group of representative images; finding the image center for each best representative image; aligning each located image center with the location of a corresponding concept in the window; and seamlessly stitching the aligned best representative images to output a synthesized image on the display. | 13. A method for synthesizing a new image, comprising: displaying on a display a window for entering a concept-structured query in the form of a concept-structured layout of an image to be synthesized from a set of images; receiving a concept-structured layout via a window by placing one or more image concepts in locations on the window using a user interface data entry device; using the input concept-structured layout to find a group of representative images in the image set for each concept in each location in the window; determining the best representative image from each group of representative images; finding the image center for each best representative image; aligning each located image center with the location of a corresponding concept in the window; and seamlessly stitching the aligned best representative images to output a synthesized image on the display. 17. The method of claim 13 further comprising the user manually selecting an image to replace a representative image in the synthesized image. | 0.648515 |
9,911,418 | 1 | 5 | 1. A method comprising: receiving, by a wearable computing device, input data from one or more input source devices; determining that the received input data includes both a first data pattern representing an explicit command and a second data pattern representing an implicit search request, wherein the first data pattern representing the explicit command comprises the first data pattern indicating that the wearable computing device should carry out a particular operation, and wherein the second data pattern representing the implicit search request comprises the second data pattern indicating that the wearable computing device should provide search results based on particular content even though the input data is without an explicit indication to provide the search results based on the particular content; and in response to determining that the received input data includes both the first data pattern representing the explicit command and the second data pattern representing the implicit search request, the wearable computing device prioritizing the explicit command over the implicit search request by carrying out the particular operation. | 1. A method comprising: receiving, by a wearable computing device, input data from one or more input source devices; determining that the received input data includes both a first data pattern representing an explicit command and a second data pattern representing an implicit search request, wherein the first data pattern representing the explicit command comprises the first data pattern indicating that the wearable computing device should carry out a particular operation, and wherein the second data pattern representing the implicit search request comprises the second data pattern indicating that the wearable computing device should provide search results based on particular content even though the input data is without an explicit indication to provide the search results based on the particular content; and in response to determining that the received input data includes both the first data pattern representing the explicit command and the second data pattern representing the implicit search request, the wearable computing device prioritizing the explicit command over the implicit search request by carrying out the particular operation. 5. The method of claim 1 , wherein the wearable computing device is configured to carry out the particular operation by communicating with at least one database that is not resident on the wearable computing device. | 0.725765 |
7,930,302 | 1 | 10 | 1. A method for analyzing user-generated content, comprising: collecting, by a processor, a review of a business from a website; extracting, by the processor, a sentence from the review; identifying, processor and within the sentence, an attribute-value comprising a noun and a descriptive term describing the noun, wherein the descriptive term comprises an adjective and an adverb corresponding to the adjective; obtaining, by the processor, an adjective score for the adjective from a rating system lookup table; assigning, by the processor, a heuristic rule score to the adverb; and calculating, by the processor, a sentence review score for the sentence by summing the adjective score and the heuristic rule score. | 1. A method for analyzing user-generated content, comprising: collecting, by a processor, a review of a business from a website; extracting, by the processor, a sentence from the review; identifying, processor and within the sentence, an attribute-value comprising a noun and a descriptive term describing the noun, wherein the descriptive term comprises an adjective and an adverb corresponding to the adjective; obtaining, by the processor, an adjective score for the adjective from a rating system lookup table; assigning, by the processor, a heuristic rule score to the adverb; and calculating, by the processor, a sentence review score for the sentence by summing the adjective score and the heuristic rule score. 10. The method of claim 1 , wherein the rating system lookup table uses a third party lexical reference system. | 0.89684 |
8,356,057 | 16 | 17 | 16. A data processing system for information gap filling, comprising: a processor; a memory accessible to the processor storing programs and data objects therein, the programs including a metadata gathering component, an online user identification component, a person request component, a user interface, an information gathering component, and a scoring component, wherein execution of the programs cause the processor to perform the steps of: invoking the metadata gathering component for collecting respective amounts of details concerning members of a set of persons in a social network, wherein additional details are desired regarding the members of the set of persons; with the online user identification component identifying online participants in a gap-filling game; using the person request component, defining for the online participants respective sets of candidates, the sets of candidates being subsets of the set of persons, wherein defining comprises computing a candidate score for each member of the set of persons, the candidate score being computed as an increasing function of a relationship strength between the member of the set of persons and the online participants, respectively and a decreasing function of the collected amount of details of the member of the set of persons; presenting the sets of candidates via the user interface to other online participants, respectively; receiving in the information gathering component information items regarding members of the presented sets of candidates from the other online participants, respectively, the information items comprising relationships between the candidates and other entities in the social network; and evaluating the online participants using the scoring component by identifying respective validated information items that are contributed by the online participants, the validated information items being identified with a predefined number of corresponding information items that are contributed by the other online participants; and computing a participant score, wherein the participant score increases according to a number of the validated information items, and for each of the validated information items, the participant score decreases according to a total number of occurrences of the corresponding information items. | 16. A data processing system for information gap filling, comprising: a processor; a memory accessible to the processor storing programs and data objects therein, the programs including a metadata gathering component, an online user identification component, a person request component, a user interface, an information gathering component, and a scoring component, wherein execution of the programs cause the processor to perform the steps of: invoking the metadata gathering component for collecting respective amounts of details concerning members of a set of persons in a social network, wherein additional details are desired regarding the members of the set of persons; with the online user identification component identifying online participants in a gap-filling game; using the person request component, defining for the online participants respective sets of candidates, the sets of candidates being subsets of the set of persons, wherein defining comprises computing a candidate score for each member of the set of persons, the candidate score being computed as an increasing function of a relationship strength between the member of the set of persons and the online participants, respectively and a decreasing function of the collected amount of details of the member of the set of persons; presenting the sets of candidates via the user interface to other online participants, respectively; receiving in the information gathering component information items regarding members of the presented sets of candidates from the other online participants, respectively, the information items comprising relationships between the candidates and other entities in the social network; and evaluating the online participants using the scoring component by identifying respective validated information items that are contributed by the online participants, the validated information items being identified with a predefined number of corresponding information items that are contributed by the other online participants; and computing a participant score, wherein the participant score increases according to a number of the validated information items, and for each of the validated information items, the participant score decreases according to a total number of occurrences of the corresponding information items. 17. The data processing system according to claim 16 , wherein the candidate score of one of the members of the set of persons is computed as a function F=(1−F data )+F rel , wherein F rel is a first function that retrieves the relationship strength between the one member of the set of persons and one of the online participants; and Fdata is a second function that retrieves the collected amount of data concerning the one member of the set of persons. | 0.638535 |
7,596,548 | 7 | 9 | 7. A computer program product for processing a query comprising a computer useable medium for storing a computer readable program, wherein the computer readable program when executed by a processor on a computer causes the computer to: receive the query, wherein the query is formed by one or more paths, and wherein each path includes one or more steps; receive a hierarchical document including one or more document nodes; and while processing the query and traversing the hierarchical document: construct a LookingFor structure, wherein the LookingFor structure includes Looking For nodes, wherein each Looking For node includes a next step in a path of the query, at least one of a minimum level and an absolute level for a next step instance, a level of an end event, a parent step instance identifier of a next step instance, and a matched step instance identifier when a match is found, wherein a document node in the hierarchical document that is described by a step in the query is called a step instance candidate, and wherein a step instance candidate is assigned a unique identifier called a step instance identifier; construct one or more extraction entries constructed from the LookingFor structure, wherein each extraction entry includes a step instance match candidate identifying a document node and a step instance ancestor path for the document node; and construct one or more tuples using the one or more extraction entries by associating the step instance match candidate from one of the one or more extraction entries with the step instance match candidate from at least one of the one or more other extraction entries, wherein the constructing of the one or more tuples includes determining which step instance match candidates are to be paired, in which order the step instance match candidates are to be paired to form tuples, and which ancestors are to be compared for each pair of step instance match candidates. | 7. A computer program product for processing a query comprising a computer useable medium for storing a computer readable program, wherein the computer readable program when executed by a processor on a computer causes the computer to: receive the query, wherein the query is formed by one or more paths, and wherein each path includes one or more steps; receive a hierarchical document including one or more document nodes; and while processing the query and traversing the hierarchical document: construct a LookingFor structure, wherein the LookingFor structure includes Looking For nodes, wherein each Looking For node includes a next step in a path of the query, at least one of a minimum level and an absolute level for a next step instance, a level of an end event, a parent step instance identifier of a next step instance, and a matched step instance identifier when a match is found, wherein a document node in the hierarchical document that is described by a step in the query is called a step instance candidate, and wherein a step instance candidate is assigned a unique identifier called a step instance identifier; construct one or more extraction entries constructed from the LookingFor structure, wherein each extraction entry includes a step instance match candidate identifying a document node and a step instance ancestor path for the document node; and construct one or more tuples using the one or more extraction entries by associating the step instance match candidate from one of the one or more extraction entries with the step instance match candidate from at least one of the one or more other extraction entries, wherein the constructing of the one or more tuples includes determining which step instance match candidates are to be paired, in which order the step instance match candidates are to be paired to form tuples, and which ancestors are to be compared for each pair of step instance match candidates. 9. The computer program product of claim 7 , wherein the computer readable program when executed on a computer causes the computer to: for each document node in the hierarchical document that is a start event or an end event, add one or more LookingFor nodes to the LookingFor structure upon finding one or more document nodes in the hierarchical document described by one or more steps of the one or more paths in the query. | 0.630435 |
8,695,096 | 10 | 13 | 10. A method, comprising: parsing a PDF file to extract script stream data embedded in the PDF file, wherein the PDF file is known to include malicious content; and determining whether to generate a signature associated with the PDF file based at least in part on at least a portion of the extracted script stream data: in the event that the signature associated with the PDF file is determined to be based at least in part on the at least portion of the extracted script stream data, automatically generating the signature associated with the PDF file based at least in part on the at least portion of the extracted script stream data, wherein the signature is configured to be matched against a potentially malicious PDF; and in the event that the signature associated with the PDF file is determined not to be based at least in part on the at least portion of the extracted script stream data, automatically generating the signature associated with the PDF file from an identified cross-reference table from a plurality of cross-reference tables within the PDF file, wherein the identified cross-reference table is identified from the plurality of cross-reference tables based at least in part on a position of the identified cross-reference table relative to respective positions associated with one or more cross-reference tables other than the identified cross-reference table from the plurality of cross-reference tables. | 10. A method, comprising: parsing a PDF file to extract script stream data embedded in the PDF file, wherein the PDF file is known to include malicious content; and determining whether to generate a signature associated with the PDF file based at least in part on at least a portion of the extracted script stream data: in the event that the signature associated with the PDF file is determined to be based at least in part on the at least portion of the extracted script stream data, automatically generating the signature associated with the PDF file based at least in part on the at least portion of the extracted script stream data, wherein the signature is configured to be matched against a potentially malicious PDF; and in the event that the signature associated with the PDF file is determined not to be based at least in part on the at least portion of the extracted script stream data, automatically generating the signature associated with the PDF file from an identified cross-reference table from a plurality of cross-reference tables within the PDF file, wherein the identified cross-reference table is identified from the plurality of cross-reference tables based at least in part on a position of the identified cross-reference table relative to respective positions associated with one or more cross-reference tables other than the identified cross-reference table from the plurality of cross-reference tables. 13. The method of claim 10 , wherein determining whether to generate the signature associated with the PDF file based at least in part on the at least portion of the extracted script stream data includes: detecting one or more portions of the extracted script stream data that are potentially malicious; assigning one or more numeric values corresponding to the one or more portions of the extracted script stream data that are potentially malicious, wherein the one or more numeric values are determined based on heuristics; aggregating the one or more numeric values into an aggregate numeric value; and determining whether the aggregate numeric value exceeds a threshold numeric value: in the event that the aggregate numeric value exceeds the threshold numeric value, determining to generate the signature based at least in part on the at least portion of the extracted script stream data; and in the event that the aggregate numeric value is equal to or less than the threshold numeric value, determining not to generate the signature based at least in part on the at least portion of the extracted script stream data. | 0.5 |
9,722,957 | 11 | 13 | 11. The method of claim 1 , wherein the generating of the third latent topic prediction includes computing a function of a fourth latent topic prediction, the fourth latent topic prediction being based on a representation of words of a current sentence of the agent's reply. | 11. The method of claim 1 , wherein the generating of the third latent topic prediction includes computing a function of a fourth latent topic prediction, the fourth latent topic prediction being based on a representation of words of a current sentence of the agent's reply. 13. The method of claim 11 , wherein the generating of the third latent topic prediction includes computing a function of the form:
{circumflex over (τ)} S M ( A i,j+1 )= f (ω( C i ),τ CA M ( C i ),ω( A i ),τ S M ( A i,j ), j ) where j is the sentence position (index) in the agent's reply, ω(C i ) is the representation of words of the customer's email, τ CA M (C i ) is the latent topic prediction for the customer's inquiry, ω(A i ) is the representation of words of at least one sentence of the agent's email, and τ S M (A i,j ) is the fourth latent topic prediction, generated based on the current sentence of the agent's email. | 0.5 |
9,201,592 | 7 | 9 | 7. The method of claim 4 , further comprising: determining whether the second handwritten input comprises at least one of a strikethrough input or a leaping input; and identifying the candidate word associated with a maximum of the rankings as the selected candidate word, when the second handwritten input includes at least one of the strikethrough input or the leaping input. | 7. The method of claim 4 , further comprising: determining whether the second handwritten input comprises at least one of a strikethrough input or a leaping input; and identifying the candidate word associated with a maximum of the rankings as the selected candidate word, when the second handwritten input includes at least one of the strikethrough input or the leaping input. 9. The method of claim 7 , wherein: the second handwritten input comprises a handwritten line connecting the one or more handwritten characters with the information identifying a corresponding one of the candidate words; and the method further comprises identifying the corresponding candidate word as the selected candidate word. | 0.5 |
8,775,439 | 1 | 5 | 1. A method performed by a system comprising one or more computers, the method comprising: determining that a first search query includes a respective text reference to each of one or more predetermined attributes, wherein each attribute is associated with a first entity type; for each of a plurality of entities of the first entity type, generating a combined search query that includes the first search query and a name of the entity; obtaining search results from a search engine for each of the plurality of entities using the combined search query for each respective entity; and using the obtained search results to generate combined search results to include in a response to the first search query, wherein using the obtained search results to generate combined search results comprises: generating a respective combined score for each of a plurality of resources identified by the obtained search results, wherein the respective combined score for each resource is a combination of scores associated with obtained search results identifying the resource, and wherein generating the respective combined score for each of the resources comprises: identifying a plurality of search results identifying the resource, wherein each search result identifying the resource is obtained from the search engine in response to a respective combined query, and wherein each search result identifying the resource is associated with a respective first score, and generating the combined score for the resource by combining the first scores associated with the search results identifying the resource; and ranking the obtained search results based on the combined scores for the respective resources identified by each search result. | 1. A method performed by a system comprising one or more computers, the method comprising: determining that a first search query includes a respective text reference to each of one or more predetermined attributes, wherein each attribute is associated with a first entity type; for each of a plurality of entities of the first entity type, generating a combined search query that includes the first search query and a name of the entity; obtaining search results from a search engine for each of the plurality of entities using the combined search query for each respective entity; and using the obtained search results to generate combined search results to include in a response to the first search query, wherein using the obtained search results to generate combined search results comprises: generating a respective combined score for each of a plurality of resources identified by the obtained search results, wherein the respective combined score for each resource is a combination of scores associated with obtained search results identifying the resource, and wherein generating the respective combined score for each of the resources comprises: identifying a plurality of search results identifying the resource, wherein each search result identifying the resource is obtained from the search engine in response to a respective combined query, and wherein each search result identifying the resource is associated with a respective first score, and generating the combined score for the resource by combining the first scores associated with the search results identifying the resource; and ranking the obtained search results based on the combined scores for the respective resources identified by each search result. 5. The method of claim 1 , wherein determining that the first search query includes a reference to one or more attributes associated with a first entity type comprises: determining that at least one term in the first search query appears in an attribute data store. | 0.727366 |
8,949,287 | 1 | 2 | 1. A computer-implemented method of adding a hotspot definition to an imaged document to create a mixed media document, the method executed by a computer and comprising: converting a source document into the imaged document from which a feature representation can be extracted; extracting features from the imaged document to create the feature representation; receiving a first user input for the hotspot definition that comprises a first coordinate location of a first bounding box for a hotspot in the imaged document and at least one of a media or an action that is associated with the first coordinate location, wherein the hotspot comprises a portion of the imaged document that is included in the first bounding box; determining whether the portion of the imaged document that is included in the first bounding box uniquely identifies the hotspot is in a database based on an amount of information included in the first bounding box; in response to determining that the portion of the imaged document that is included in the first bounding box does not uniquely identify the hotspot in the database, receiving a second user input to change the hotspot definition to a second coordinate location of a second bounding box, the second bounding box comprising the first bounding box and containing a larger amount of information than the first bounding box, wherein the larger amount of information contained in the second bounding box uniquely identifies the hotspot in the database; and storing, as the mixed media document, the imaged document, the hotspot definition, and the feature representation. | 1. A computer-implemented method of adding a hotspot definition to an imaged document to create a mixed media document, the method executed by a computer and comprising: converting a source document into the imaged document from which a feature representation can be extracted; extracting features from the imaged document to create the feature representation; receiving a first user input for the hotspot definition that comprises a first coordinate location of a first bounding box for a hotspot in the imaged document and at least one of a media or an action that is associated with the first coordinate location, wherein the hotspot comprises a portion of the imaged document that is included in the first bounding box; determining whether the portion of the imaged document that is included in the first bounding box uniquely identifies the hotspot is in a database based on an amount of information included in the first bounding box; in response to determining that the portion of the imaged document that is included in the first bounding box does not uniquely identify the hotspot in the database, receiving a second user input to change the hotspot definition to a second coordinate location of a second bounding box, the second bounding box comprising the first bounding box and containing a larger amount of information than the first bounding box, wherein the larger amount of information contained in the second bounding box uniquely identifies the hotspot in the database; and storing, as the mixed media document, the imaged document, the hotspot definition, and the feature representation. 2. The method of claim 1 , wherein converting comprises scanning the source document. | 0.789604 |
8,532,333 | 10 | 14 | 10. A computer system, comprising: a non-transitory computer-readable storage medium comprising executable computer program code for: recognizing one or more text strings in each of a plurality of geo-tagged images, each of the plurality of geo-tagged images indicating a geographical location of its corresponding geo-tagged image, identifying one or more establishments near the geographical locations of the plurality of geo-tagged images, for each specific establishment of the one or more establishments: (i) extracting one or more phrases from information associated with the specific establishment, (ii) comparing the one or more text strings recognized in the plurality of geo-tagged images with the extracted one or more phrases to derive one or more matches, (iii) determining one or more image-establishment pairs based on the one or more matches, each image-establishment pair pairing a specific geo-tagged image with the specific establishment, and (iv) selecting a representative geo-tagged image for the specific establishment from among the plurality of geo-tagged images based on the one or more image-establishment pairs; and at least one processor for executing the executable computer program code. | 10. A computer system, comprising: a non-transitory computer-readable storage medium comprising executable computer program code for: recognizing one or more text strings in each of a plurality of geo-tagged images, each of the plurality of geo-tagged images indicating a geographical location of its corresponding geo-tagged image, identifying one or more establishments near the geographical locations of the plurality of geo-tagged images, for each specific establishment of the one or more establishments: (i) extracting one or more phrases from information associated with the specific establishment, (ii) comparing the one or more text strings recognized in the plurality of geo-tagged images with the extracted one or more phrases to derive one or more matches, (iii) determining one or more image-establishment pairs based on the one or more matches, each image-establishment pair pairing a specific geo-tagged image with the specific establishment, and (iv) selecting a representative geo-tagged image for the specific establishment from among the plurality of geo-tagged images based on the one or more image-establishment pairs; and at least one processor for executing the executable computer program code. 14. The computer system of claim 10 , wherein the information associated with the specific establishment comprises at least one of (i) a name of the specific establishment, (ii) a category of the specific establishment, (iii) a phone number of the specific establishment, and (iv) an address of the specific establishment. | 0.662474 |
7,793,224 | 1 | 3 | 1. A method in which at least one computer system accesses instructions from computer storage and executes the instructions to perform steps comprising: receiving a selection of content displayed in a first portion of a first document; identifying a reference in the first document to first formatting information currently applied to the selected content; identifying second formatting information in the first portion of the first document that currently formats non-selected content displayed in a second portion of the first document, the non-selected content exclusive of the selected content; including an identification of the non-selected content in the first formatting information; upon receiving a request to paste the selected content into a second document, pasting the selected content into the second document, the selected content formatted in the second document according to the first formatting information; based on the identification of the non-selected content in the first formatting information, carrying over the non-selected content from the first document into the second document; wherein identifying the reference in the first document includes: identifying a reference to a source located outside of the first document, the source providing the first formatting information currently applied to the selected content; accessing the first formatting information from the source; displaying the first formatting information via a prompt; receiving a selection of a subset of the first formatting information; wherein pasting the selected content into the second document includes: formatting the selected content according to the subset of the first formatting information; wherein including the identification of the non-selected content in the first formatting information includes: including, in the subset of the first formatting information, an identification of: (i) a displayed first document title and (ii) a graphic located, in the first document, within a particular distance from the selected content; and wherein carrying over the non-selected content includes: pasting the graphic in the second document; and pasting the first document title as a title of the second document. | 1. A method in which at least one computer system accesses instructions from computer storage and executes the instructions to perform steps comprising: receiving a selection of content displayed in a first portion of a first document; identifying a reference in the first document to first formatting information currently applied to the selected content; identifying second formatting information in the first portion of the first document that currently formats non-selected content displayed in a second portion of the first document, the non-selected content exclusive of the selected content; including an identification of the non-selected content in the first formatting information; upon receiving a request to paste the selected content into a second document, pasting the selected content into the second document, the selected content formatted in the second document according to the first formatting information; based on the identification of the non-selected content in the first formatting information, carrying over the non-selected content from the first document into the second document; wherein identifying the reference in the first document includes: identifying a reference to a source located outside of the first document, the source providing the first formatting information currently applied to the selected content; accessing the first formatting information from the source; displaying the first formatting information via a prompt; receiving a selection of a subset of the first formatting information; wherein pasting the selected content into the second document includes: formatting the selected content according to the subset of the first formatting information; wherein including the identification of the non-selected content in the first formatting information includes: including, in the subset of the first formatting information, an identification of: (i) a displayed first document title and (ii) a graphic located, in the first document, within a particular distance from the selected content; and wherein carrying over the non-selected content includes: pasting the graphic in the second document; and pasting the first document title as a title of the second document. 3. The method as in claim 1 , wherein receiving the selection of a subset of the first formatting information includes: receiving a user selection applied in response to the prompt, the user selection indicating which part of the first formatting information to apply to the selected content upon pasting the selected content into the second document. | 0.5 |
7,818,348 | 1 | 2 | 1. A system for processing abstract queries, comprising: a computer processor; a database system; a database abstraction model comprising definitions for a plurality logical fields, wherein each logical field specifies at least an access method mapping the logical field to data in the database system, and wherein at least one logical field includes timeline metadata indicating where data elements retrieved for the at least one logical field occur on a timeline; and a runtime component which, when executed by the computer processor, receives an abstract query composed from the plurality of logical fields that specifies (i) a set of conditional expressions, wherein each conditional expression includes a logical field, a conditional operator, and a comparison value, and wherein at least one conditional expression specifies a temporal operator relating the logical field and comparison value, wherein the temporal operator comprises at least one of the following: a) a first operator specifying that data corresponding to the logical field included by at least one conditional expression occurred at a single point on the timeline before the comparison value; b) a second operator specifying that data corresponding to the logical field included by at least one conditional expression occurred at a single point on the timeline after the comparison value; c) a third operator specifying that data corresponding to the logical field occurs at any point on a segment of the timeline; and d) a fourth operator specifying that data corresponding to the logical field occurs within a certain distance from another point on the timeline; and (ii) a set of logical fields defining result fields for which query results, satisfying the set of conditional expressions, are returned, wherein the runtime component further (i) generates an equivalent conditional expression corresponding to the at least one conditional expression, wherein the generated equivalent conditional expression does not include the temporal operator, and wherein the equivalent conditional expression is composed from numerical or logical operators; (ii) merges other conditional expressions specified by the abstract query with the equivalent conditional expression, and (iii) generates, from the merged conditional expressions and the set of logical fields used to retrieve a set of query results, a resolved query of the database system, and wherein the computer processor issues the resolved query to the database system to retrieve the set of query results and displays a graphical representation of the set of query results that indicates a position of data elements included in the query results on a timeline according to the timeline metadata. | 1. A system for processing abstract queries, comprising: a computer processor; a database system; a database abstraction model comprising definitions for a plurality logical fields, wherein each logical field specifies at least an access method mapping the logical field to data in the database system, and wherein at least one logical field includes timeline metadata indicating where data elements retrieved for the at least one logical field occur on a timeline; and a runtime component which, when executed by the computer processor, receives an abstract query composed from the plurality of logical fields that specifies (i) a set of conditional expressions, wherein each conditional expression includes a logical field, a conditional operator, and a comparison value, and wherein at least one conditional expression specifies a temporal operator relating the logical field and comparison value, wherein the temporal operator comprises at least one of the following: a) a first operator specifying that data corresponding to the logical field included by at least one conditional expression occurred at a single point on the timeline before the comparison value; b) a second operator specifying that data corresponding to the logical field included by at least one conditional expression occurred at a single point on the timeline after the comparison value; c) a third operator specifying that data corresponding to the logical field occurs at any point on a segment of the timeline; and d) a fourth operator specifying that data corresponding to the logical field occurs within a certain distance from another point on the timeline; and (ii) a set of logical fields defining result fields for which query results, satisfying the set of conditional expressions, are returned, wherein the runtime component further (i) generates an equivalent conditional expression corresponding to the at least one conditional expression, wherein the generated equivalent conditional expression does not include the temporal operator, and wherein the equivalent conditional expression is composed from numerical or logical operators; (ii) merges other conditional expressions specified by the abstract query with the equivalent conditional expression, and (iii) generates, from the merged conditional expressions and the set of logical fields used to retrieve a set of query results, a resolved query of the database system, and wherein the computer processor issues the resolved query to the database system to retrieve the set of query results and displays a graphical representation of the set of query results that indicates a position of data elements included in the query results on a timeline according to the timeline metadata. 2. The system of claim 1 , wherein the system further comprises an abstract query interface for composing the abstract query, and wherein the abstract query interface communicates with the runtime component over a computer network. | 0.5 |
7,996,375 | 23 | 25 | 23. A method for delivery of content from a corpus of data, the method implemented by a computer system including a search engine, a result processor, an interface, and a memory, the method comprising: receiving a search query for searching the corpus; generating a result set in response to the search query, the search query result set including one or more items from the corpus; identifying a characteristic corresponding to a plurality of items in the search query result set; identifying a rule corresponding to said characteristic, said rule defining a content presentation action; determining a percentage of items in the search query result set that correspond to said characteristic; comparing the determined percentage of items to a threshold percentage, wherein the threshold percentage is a predetermined percentage of the total number of items in the search query result set; and presenting content in accordance with the content specification action when the determined percentage of items exceeds the threshold percentage. | 23. A method for delivery of content from a corpus of data, the method implemented by a computer system including a search engine, a result processor, an interface, and a memory, the method comprising: receiving a search query for searching the corpus; generating a result set in response to the search query, the search query result set including one or more items from the corpus; identifying a characteristic corresponding to a plurality of items in the search query result set; identifying a rule corresponding to said characteristic, said rule defining a content presentation action; determining a percentage of items in the search query result set that correspond to said characteristic; comparing the determined percentage of items to a threshold percentage, wherein the threshold percentage is a predetermined percentage of the total number of items in the search query result set; and presenting content in accordance with the content specification action when the determined percentage of items exceeds the threshold percentage. 25. The method of claim 23 , wherein presenting content in accordance with the content specification action comprises modifying the order of the search query result set. | 0.583744 |
7,496,828 | 10 | 12 | 10. A method of communicating between a client process and a server process in a distributed processing system, comprising the steps of: issuing, by the client process, a call to map a tag in an ML document to a common language runtime class, wherein the ML document includes a definition file location attribute that is associated with the tag; receiving, by the server process, the call and retrieving a definition file associated with the definition file location attribute, wherein the definition file includes: a list of assemblies that reference the definition file, a list of common language runtime namespaces for each assembly of the list of assemblies referenced in the definition file, wherein each common language runtime namespace includes a list of classes associated with the common language runtime namespace, and an installation tag that includes a uniform resource identifier for installing the assemblies of the list of assemblies; referencing the list of common language runtime namespaces of the retrieved definition file to determine a common language runtime class associated with the tag; locating the determined common language runtime class in the assembly of the retrieved definition file; accessing code of the assembly of the determined common language runtime class via the uniform resource locator of the installation tag; installing the assembly of the determined common language runtime class; and building the ML document with the tag mapped to the common language runtime class of the assembly of the retrieved definition file. | 10. A method of communicating between a client process and a server process in a distributed processing system, comprising the steps of: issuing, by the client process, a call to map a tag in an ML document to a common language runtime class, wherein the ML document includes a definition file location attribute that is associated with the tag; receiving, by the server process, the call and retrieving a definition file associated with the definition file location attribute, wherein the definition file includes: a list of assemblies that reference the definition file, a list of common language runtime namespaces for each assembly of the list of assemblies referenced in the definition file, wherein each common language runtime namespace includes a list of classes associated with the common language runtime namespace, and an installation tag that includes a uniform resource identifier for installing the assemblies of the list of assemblies; referencing the list of common language runtime namespaces of the retrieved definition file to determine a common language runtime class associated with the tag; locating the determined common language runtime class in the assembly of the retrieved definition file; accessing code of the assembly of the determined common language runtime class via the uniform resource locator of the installation tag; installing the assembly of the determined common language runtime class; and building the ML document with the tag mapped to the common language runtime class of the assembly of the retrieved definition file. 12. The method of claim 10 , wherein the server process further comprises retrieving the definition file from a network location specified by the definition file location attribute. | 0.645098 |
8,346,794 | 12 | 14 | 12. An apparatus for database querying, the apparatus comprising: means for receiving an input data query from a requesting source from a plurality of requesting sources, wherein the input data query having input data and an input data type and wherein a first input data query from a first requesting source has a form different from a second input data query from a second requesting source; means for querying a reference database containing validated data, the reference database selected based on the input data type from among a plurality of reference databases, the querying comprising seeking a reference database record that matches the input data; wherein the means for querying further comprises means for seeking a reference database record by applying a set of reference-based mapping rules for matching input data queries from one of the plurality of requesting sources to an associated one of the plurality of reference databases; means for finding a matching reference database record; means for applying at least one transformation rule to convert the matching reference database record to a plurality of forms, wherein individual ones of the plurality of forms correspond to individual target databases of a plurality of target databases; means for querying at least one of the plurality of target databases for one or more target database records that correspond to the at least one of the individual ones of the plurality of forms; and means for retrieving corresponding records comprising target database records that correspond to the at least one of the individual ones of the plurality of forms and transferring the corresponding records to the requesting source. | 12. An apparatus for database querying, the apparatus comprising: means for receiving an input data query from a requesting source from a plurality of requesting sources, wherein the input data query having input data and an input data type and wherein a first input data query from a first requesting source has a form different from a second input data query from a second requesting source; means for querying a reference database containing validated data, the reference database selected based on the input data type from among a plurality of reference databases, the querying comprising seeking a reference database record that matches the input data; wherein the means for querying further comprises means for seeking a reference database record by applying a set of reference-based mapping rules for matching input data queries from one of the plurality of requesting sources to an associated one of the plurality of reference databases; means for finding a matching reference database record; means for applying at least one transformation rule to convert the matching reference database record to a plurality of forms, wherein individual ones of the plurality of forms correspond to individual target databases of a plurality of target databases; means for querying at least one of the plurality of target databases for one or more target database records that correspond to the at least one of the individual ones of the plurality of forms; and means for retrieving corresponding records comprising target database records that correspond to the at least one of the individual ones of the plurality of forms and transferring the corresponding records to the requesting source. 14. The apparatus of claim 12 further comprising: means for determining whether a possibly matching record can be considered a near-matching record to the input data, in response to failing to find a matching reference database record but finding one or more possibly matching reference database records; and means for applying at least one transformation rule to convert the chosen reference database record to a plurality of forms, wherein individual ones of the plurality of forms correspond to individual target databases of a plurality of target databases; means for querying at least one of the plurality of target databases for the one or more target database record that corresponds to the at least one of the individual ones of the plurality of forms, in response to failing to identify a near-matching record, generating a selection request to choose from among the one or more possibly matching records a record that corresponds to the input data and in response to selection of a chosen record from among the one or more possibly matching records. | 0.5 |
8,862,566 | 18 | 19 | 18. The system of claim 16 , wherein returning the output comprises returning the target data from at least two data sources of the plurality of data sources and a relationship between the target data from the at least two data sources. | 18. The system of claim 16 , wherein returning the output comprises returning the target data from at least two data sources of the plurality of data sources and a relationship between the target data from the at least two data sources. 19. The system of claim 18 , wherein the target data and the relationship between the target data are usable for identity resolution. | 0.5 |
9,785,948 | 7 | 10 | 7. The method of claim 1 , wherein the task instance comprises a plurality of steps associated with completing the task, and wherein at least one step of the plurality of steps is a prerequisite step of at least one other step of the plurality of steps. | 7. The method of claim 1 , wherein the task instance comprises a plurality of steps associated with completing the task, and wherein at least one step of the plurality of steps is a prerequisite step of at least one other step of the plurality of steps. 10. The method of claim 7 , further comprising: providing the prerequisite step for display such that the prerequisite step is accessible to be completed; and providing the at least one other step for display as inaccessible to be completed until the status indicator indicates that the prerequisite step is complete. | 0.573925 |
9,390,195 | 5 | 7 | 5. The method of claim 4 , wherein identifying the set of quota cells further comprises determining an incomplete match to a quota cell in response to an edge of the quota cell vertex for the quota cell encountering a profile parameter value vertex representing a value of a profile parameter that is not determined for the panelist. | 5. The method of claim 4 , wherein identifying the set of quota cells further comprises determining an incomplete match to a quota cell in response to an edge of the quota cell vertex for the quota cell encountering a profile parameter value vertex representing a value of a profile parameter that is not determined for the panelist. 7. The method of claim 5 , further comprising: determining whether matches are complete for each quota cell of the set associated with the project and, if not, obtaining additional information from the panelist with respect to each of the incompletely matched quota cells and determining whether a fit exists based on the additional information; and responding to a determination that a fit does not exist by eliminating all quota cells from the set that are associated with the incompletely matched project, and selecting another one of the quota cells of the set. | 0.5 |
7,836,049 | 1 | 6 | 1. A method comprising: a computing device receiving a search string including an ordered sequence of syllable counts; comparing the ordered sequence of syllable counts with the contents of a database of analyzed documents, each document comprising a plurality of words; and retrieving from the database a document uniquely represented by the search string. | 1. A method comprising: a computing device receiving a search string including an ordered sequence of syllable counts; comparing the ordered sequence of syllable counts with the contents of a database of analyzed documents, each document comprising a plurality of words; and retrieving from the database a document uniquely represented by the search string. 6. The method recited in claim 1 wherein, in using, the input ordered sequence of syllable counts is matched with at least one corresponding ordered sequence of syllable counts within the database. | 0.5 |
9,535,896 | 1 | 7 | 1. A computer-implemented method of identifying a language of a message, the method comprising: performing a plurality of language detection tests on text, each language detection test determining a respective set of scores, each score in the set of scores representing a likelihood that the message is in a respective language of a plurality of different languages; providing one or more combinations of the score sets as input to one or more distinct classifiers including a first classifier and a second classifier, wherein the first classifier was trained using outputs from a first combination of the language detection tests and the second classifier was trained using outputs from a different second combination of the language detection tests; obtaining as output from each of the one or more classifiers a respective indication that the message is in one of the plurality of different languages, the indication comprising a confidence score; and identifying the language of the message based on one of the confidence scores. | 1. A computer-implemented method of identifying a language of a message, the method comprising: performing a plurality of language detection tests on text, each language detection test determining a respective set of scores, each score in the set of scores representing a likelihood that the message is in a respective language of a plurality of different languages; providing one or more combinations of the score sets as input to one or more distinct classifiers including a first classifier and a second classifier, wherein the first classifier was trained using outputs from a first combination of the language detection tests and the second classifier was trained using outputs from a different second combination of the language detection tests; obtaining as output from each of the one or more classifiers a respective indication that the message is in one of the plurality of different languages, the indication comprising a confidence score; and identifying the language of the message based on one of the confidence scores. 7. The method of claim 1 , wherein a particular language detection test is a byte n-gram method, a dictionary-based method, an alphabet-based method, or a script-based method. | 0.519231 |
9,020,924 | 15 | 21 | 15. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: obtaining a plurality of queries received from a user in a current query session, wherein a most recent query received from the user in the current query session includes a first sequence of terms; identifying a plurality of second sequences of terms having highest-ranked measures of similarity with the first sequence of terms, the respective measures of similarity being determined between (1) a first feature vector for the first sequence of terms and (2) respective second feature vectors for each of the second sequences of terms, each of the one or more second sequences of terms being a subsequence of the first sequence of terms or being a sequence of which the first sequence of terms is a subsequence, wherein each value of the first feature vector and the respective second feature vectors is based on a count of a corresponding co-occurring term occurring in a corpus adjacent to each respective sequence of terms; generating a plurality of query suggestions for a particular query received in the current query session, including replacing the first sequence of terms in the most recent query with each of the plurality of highest-ranked second sequences of terms, wherein the first sequence of terms in the most recent query is a subsequence of the second sequence of terms or the second sequence of terms is a subsequence of the first sequence of terms in the most recent query; determining a respective score for each of the plurality of query suggestions, where the score is based on a relevance between each query suggestion and the plurality of queries received from the user in the current query session; and ranking the query suggestions by the determined scores. | 15. A computer program product, encoded on one or more non-transitory computer storage media, comprising instructions that when executed by one or more computers cause the one or more computers to perform operations comprising: obtaining a plurality of queries received from a user in a current query session, wherein a most recent query received from the user in the current query session includes a first sequence of terms; identifying a plurality of second sequences of terms having highest-ranked measures of similarity with the first sequence of terms, the respective measures of similarity being determined between (1) a first feature vector for the first sequence of terms and (2) respective second feature vectors for each of the second sequences of terms, each of the one or more second sequences of terms being a subsequence of the first sequence of terms or being a sequence of which the first sequence of terms is a subsequence, wherein each value of the first feature vector and the respective second feature vectors is based on a count of a corresponding co-occurring term occurring in a corpus adjacent to each respective sequence of terms; generating a plurality of query suggestions for a particular query received in the current query session, including replacing the first sequence of terms in the most recent query with each of the plurality of highest-ranked second sequences of terms, wherein the first sequence of terms in the most recent query is a subsequence of the second sequence of terms or the second sequence of terms is a subsequence of the first sequence of terms in the most recent query; determining a respective score for each of the plurality of query suggestions, where the score is based on a relevance between each query suggestion and the plurality of queries received from the user in the current query session; and ranking the query suggestions by the determined scores. 21. The computer program product of claim 15 , wherein the operations further comprise determining the relevance between each query suggestion and the plurality of queries received form the user in the current query session, including determining correlation values between aligned terms of each query suggestion and each query in the plurality of queries received from the user in the current query session. | 0.5 |
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