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7,953,713 | 5 | 6 | 5. The management system according to claim 1 , wherein said core engine includes one or more processing modules, and said hierarchical semantic tags are used for routing said data to said processing modules. | 5. The management system according to claim 1 , wherein said core engine includes one or more processing modules, and said hierarchical semantic tags are used for routing said data to said processing modules. 6. The management system according to claim 5 , wherein said routing is via a publish-subscribe messaging backbone. | 0.967587 |
8,806,401 | 7 | 8 | 7. The method of claim 1 , further comprising determining by the programmable system a coverage metric that is a ratio between a number of operations actually performed for functional verification and a minimum number of operations necessary for a desired level of coverage. | 7. The method of claim 1 , further comprising determining by the programmable system a coverage metric that is a ratio between a number of operations actually performed for functional verification and a minimum number of operations necessary for a desired level of coverage. 8. The method of claim 7 , further comprising reporting by the programmable system the coverage metric. | 0.943531 |
9,111,319 | 6 | 9 | 6. A non-transitory computer-readable medium storing a computer program product comprised of a series of instructions executable on a computer, the computer program product performing a process for gathering data related to a plurality of academic users and a process for determining a reputation ranking an academic user, the computer program product implementing the steps of: for each user, determining whether the user is an academic user or a non-academic user, creating an academic user profile for each of the academic users from attribute information gathered from a user profile prompt displayed on user computers associated with the academic users, allowing the academic users to upload academic articles, enabling the academic user profiles to be viewed by both other academic users and non-academic users, allowing each of the academic users to comment on the academic articles uploaded by other academic users while restricting the non-academic users from commenting on the articles, enabling email communications between the academic users while restricting the non-academic users from emailing the academic users, enabling the academic user profile of each academic user to be selected for ranking by other academic users and enabling the other academic users to provide rank selections for the academic user profile according to at least one of research quality, credentials, research articles, and user activity of the academic user associated with the academic user profile, assigning each of the rank selections a ranking weight based upon at least one of academic credentials or publication volume of the respective selecting academic user and multiplying the rank selection by the ranking weight to create a weighted rank selection, and determining reputation rankings for the academic user profiles from the weighted rank selections. | 6. A non-transitory computer-readable medium storing a computer program product comprised of a series of instructions executable on a computer, the computer program product performing a process for gathering data related to a plurality of academic users and a process for determining a reputation ranking an academic user, the computer program product implementing the steps of: for each user, determining whether the user is an academic user or a non-academic user, creating an academic user profile for each of the academic users from attribute information gathered from a user profile prompt displayed on user computers associated with the academic users, allowing the academic users to upload academic articles, enabling the academic user profiles to be viewed by both other academic users and non-academic users, allowing each of the academic users to comment on the academic articles uploaded by other academic users while restricting the non-academic users from commenting on the articles, enabling email communications between the academic users while restricting the non-academic users from emailing the academic users, enabling the academic user profile of each academic user to be selected for ranking by other academic users and enabling the other academic users to provide rank selections for the academic user profile according to at least one of research quality, credentials, research articles, and user activity of the academic user associated with the academic user profile, assigning each of the rank selections a ranking weight based upon at least one of academic credentials or publication volume of the respective selecting academic user and multiplying the rank selection by the ranking weight to create a weighted rank selection, and determining reputation rankings for the academic user profiles from the weighted rank selections. 9. The computer program product of claim 6 , further including instructions for: publishing the new reputation rankings on the user profiles. | 0.8639 |
10,067,939 | 1 | 2 | 1. A machine translation method comprising: converting, using a processor, a source sentence written in a first language to language-independent information using an encoder for the first language, information for which is stored in non-volatile and volatile memory; and converting, using the processor, the language-independent information to a target sentence corresponding to the source sentence and written in a second language different from the first language using a decoder for the second language, information for which is stored in the nonvolatile and volatile memory, in response to a similarity being higher than a preset threshold, wherein the similarity is determined from a comparison between pixel values of the language-independent information of the source sentence and pixel values of the language-independent information of the target sentence; wherein the encoder for the first language is trained to output language-independent information corresponding to the target sentence in response to an input of the source sentence, using the processor, wherein the processor communicates with the nonvolatile and volatile memory via a bus. | 1. A machine translation method comprising: converting, using a processor, a source sentence written in a first language to language-independent information using an encoder for the first language, information for which is stored in non-volatile and volatile memory; and converting, using the processor, the language-independent information to a target sentence corresponding to the source sentence and written in a second language different from the first language using a decoder for the second language, information for which is stored in the nonvolatile and volatile memory, in response to a similarity being higher than a preset threshold, wherein the similarity is determined from a comparison between pixel values of the language-independent information of the source sentence and pixel values of the language-independent information of the target sentence; wherein the encoder for the first language is trained to output language-independent information corresponding to the target sentence in response to an input of the source sentence, using the processor, wherein the processor communicates with the nonvolatile and volatile memory via a bus. 2. The machine translation method of claim 1 , wherein the converting of the source sentence to the language-independent information comprises converting the source sentence to language-independent information having a similarity to the language-independent information corresponding to the target sentence higher than a preset threshold. | 0.837187 |
9,870,633 | 1 | 2 | 1. A non-transitory computer-readable storage medium storing instructions that, when executed by at least one processor, cause a computing device to: receive a user preference, the user preference selected for an individual user; access a user identified word of a plurality of user identified words, the user identified word associated with the user preference and a color selected for the individual user; obtain image data that includes a representation of text; use an object recognition algorithm to determine a recognized word represented in the image data; associate the user identified word with the recognized word; display the recognized word emphasized by a visual color attribute, the visual color attribute matching the color associated with the user identified word; and arrange the recognized word with respect to a plurality of recognized words, individual recognized words of the plurality of recognized words associated with individual user preferences and individual colors selected for individual users, the plurality of recognized words arranged based on the color, thereby ascertaining a group preference associated with group behavior based on the individual recognized words with respect to the plurality of recognized words. | 1. A non-transitory computer-readable storage medium storing instructions that, when executed by at least one processor, cause a computing device to: receive a user preference, the user preference selected for an individual user; access a user identified word of a plurality of user identified words, the user identified word associated with the user preference and a color selected for the individual user; obtain image data that includes a representation of text; use an object recognition algorithm to determine a recognized word represented in the image data; associate the user identified word with the recognized word; display the recognized word emphasized by a visual color attribute, the visual color attribute matching the color associated with the user identified word; and arrange the recognized word with respect to a plurality of recognized words, individual recognized words of the plurality of recognized words associated with individual user preferences and individual colors selected for individual users, the plurality of recognized words arranged based on the color, thereby ascertaining a group preference associated with group behavior based on the individual recognized words with respect to the plurality of recognized words. 2. The non-transitory computer-readable storage medium of claim 1 , wherein the visual color attribute comprises at least one of a bounding box around the recognized word, a graphical representation of the recognized word in color, or a highlighting of the recognized word with a color. | 0.587896 |
9,607,081 | 16 | 17 | 16. The system of claim 11 , further including: a database that stores the user's usage of the one or more marked GUI features; and a repository that stores the one or more generated user-specific ontologies. | 16. The system of claim 11 , further including: a database that stores the user's usage of the one or more marked GUI features; and a repository that stores the one or more generated user-specific ontologies. 17. The system of claim 16 , wherein the database is a NoSQL database. | 0.981865 |
8,868,637 | 1 | 12 | 1. A method comprising: by a code segment executing on a client computing device and embedded in a first structured document rendered by the client computing device, detecting an event on the first structured document, the event directing the client application to generate a first request for a second structured document from a remote server; by the code segment, intercepting the first request; by the code segment, identifying one or more resources specified in the first request that are not currently stored on the client computing device; by the code segment, generating a second request for resources to be sent to the remote server, wherein the second request specifies only one or more of the resources specified in the first request that are not currently stored on the client computing device; sending the second request to the remote server; receiving, in response to the second request, one or more of the resources specified in the second request; and rendering the second structured document with: one or more of the resources specified in the first request that are currently stored on the client computing device; and one or more of the resources received in response to the second request. | 1. A method comprising: by a code segment executing on a client computing device and embedded in a first structured document rendered by the client computing device, detecting an event on the first structured document, the event directing the client application to generate a first request for a second structured document from a remote server; by the code segment, intercepting the first request; by the code segment, identifying one or more resources specified in the first request that are not currently stored on the client computing device; by the code segment, generating a second request for resources to be sent to the remote server, wherein the second request specifies only one or more of the resources specified in the first request that are not currently stored on the client computing device; sending the second request to the remote server; receiving, in response to the second request, one or more of the resources specified in the second request; and rendering the second structured document with: one or more of the resources specified in the first request that are currently stored on the client computing device; and one or more of the resources received in response to the second request. 12. The method of claim 1 , further comprising, by the code segment, inserting an iframe in a frame of the first structured document. | 0.881038 |
6,141,621 | 4 | 5 | 4. The method of claim 3, wherein step (G) is performed by the further substeps of determining whether any street within the second possible street set has an associated speed range that corresponds to the speed of travel of the vehicle and placing such streets within a third possible street set; and determining which street from within the third possible street set is closest to the placement of the vehicle and defining the street where the vehicle is located as the closest street from within the third possible street set. | 4. The method of claim 3, wherein step (G) is performed by the further substeps of determining whether any street within the second possible street set has an associated speed range that corresponds to the speed of travel of the vehicle and placing such streets within a third possible street set; and determining which street from within the third possible street set is closest to the placement of the vehicle and defining the street where the vehicle is located as the closest street from within the third possible street set. 5. The method of claim 4, wherein the third possible street set contains no streets and wherein step (G) is performed by the further substeps of determining which street from within the second possible street set is closest to the placement of the vehicle and defining the street where the vehicle is located as the closest street from within the second possible street set. | 0.820365 |
8,959,103 | 5 | 6 | 5. The method of claim 2 , comprising associating a first weight with the click count and a second weight with the skip count. | 5. The method of claim 2 , comprising associating a first weight with the click count and a second weight with the skip count. 6. The method of claim 5 , wherein the score assigned to the query term reordering rule satisfies: W 1 ( click count ) W 1 ( click count ) + W 2 ( skip count ) wherein W1 represents the first weight associated with the click count and W2 represents the second weight associated with the skip count. | 0.89008 |
9,263,048 | 2 | 3 | 2. The computer-implemented method of claim 1 , wherein the one or more words are selected from a hierarchical word lattice. | 2. The computer-implemented method of claim 1 , wherein the one or more words are selected from a hierarchical word lattice. 3. The computer-implemented method of claim 2 , wherein the hierarchical word lattice comprises nodes corresponding to the one or more words of the first transcription of the utterance and words of the second transcription of the utterance, and edges between the nodes that identify possible paths through the word lattice, wherein each path has an associated probability of being correct. | 0.906804 |
8,595,222 | 16 | 21 | 16. A non-transitory computer-readable medium comprising instructions for controlling a processor to use Resource Description Framework (RDF) reification to associate Semantic Web statements with start properties and stop properties related to lifetimes of the Semantic Web statements by: accessing an RDF statement from a Semantic Web resource wherein the RDF statement includes a subject, a predicate, and an object; determining a lifetime of the subject of the RDF statement, wherein determining the lifetime of the subject is based on at least one of a start property of the subject and a stop property of the subject; determining a lifetime of the predicate of the RDF statement, wherein determining the lifetime of the predicate is based on at least one of a start property of the predicate and a stop property the predicate; determining a lifetime of the object of the RDF statement, wherein determining the lifetime of the object is based on at least one of a start property of the object and a stop property of the object; automatically determining a lifetime of the RDF statement based on an overlap of the lifetime of the subject, the lifetime of the predicate, and the lifetime of the object; generating a reified RDF statement, using a reification processor, wherein the reified RDF statement includes the subject, the predicate, the object and the lifetime of the RDF statement; and storing the reified RDF statement in the Semantic Web resource. | 16. A non-transitory computer-readable medium comprising instructions for controlling a processor to use Resource Description Framework (RDF) reification to associate Semantic Web statements with start properties and stop properties related to lifetimes of the Semantic Web statements by: accessing an RDF statement from a Semantic Web resource wherein the RDF statement includes a subject, a predicate, and an object; determining a lifetime of the subject of the RDF statement, wherein determining the lifetime of the subject is based on at least one of a start property of the subject and a stop property of the subject; determining a lifetime of the predicate of the RDF statement, wherein determining the lifetime of the predicate is based on at least one of a start property of the predicate and a stop property the predicate; determining a lifetime of the object of the RDF statement, wherein determining the lifetime of the object is based on at least one of a start property of the object and a stop property of the object; automatically determining a lifetime of the RDF statement based on an overlap of the lifetime of the subject, the lifetime of the predicate, and the lifetime of the object; generating a reified RDF statement, using a reification processor, wherein the reified RDF statement includes the subject, the predicate, the object and the lifetime of the RDF statement; and storing the reified RDF statement in the Semantic Web resource. 21. The non-transitory computer-readable medium of claim 16 further comprising instructions for controlling the processor to: compare the lifetime of the object and the lifetime of the subject; and in response to the comparison, select an intersection of the compared lifetimes as the lifetime of the RDF statement. | 0.678571 |
7,483,908 | 3 | 26 | 3. A computer-implemented method for assessing compliance with the HIPAA, in a context management system, the method comprising: (A) collecting context data from a plurality of applications that use the context management system; (B) storing data corresponding to the collected context data on a centralized storage location; and (C) extracting audit information by processing at least a subset of the data stored on the centralized storage location, the audit information suitable for making an assessment of compliance with a provision of the HIPAA; wherein any of the plurality of applications supports the CCOW standard set. | 3. A computer-implemented method for assessing compliance with the HIPAA, in a context management system, the method comprising: (A) collecting context data from a plurality of applications that use the context management system; (B) storing data corresponding to the collected context data on a centralized storage location; and (C) extracting audit information by processing at least a subset of the data stored on the centralized storage location, the audit information suitable for making an assessment of compliance with a provision of the HIPAA; wherein any of the plurality of applications supports the CCOW standard set. 26. The method of claim 3 , wherein the centralized storage location is a database. | 0.923148 |
8,560,326 | 12 | 13 | 12. An apparatus for use in indicating a dialogue turn in an automated speech-to-speech translation system, comprising: a memory; and at least one processor coupled to the memory and operative to: (i) translate speech input from a plurality of speakers having a multilingual conversation using an automated speech-to-speech translation system; (ii) provide an indication to each speaker of the plurality of speakers of when it is a turn of each speaker to commence speaking in a dialog interact between the plurality of speakers and provide speech input to the automated speech-to-speech translation system, wherein the at least one processor is operative to provide an indication by: obtaining one or more previously-generated text-based scripts, the one or more text-based scripts being synthesizable into one or more voice prompts in different languages of the plurality of speakers, wherein the voice prompts are audible messages that notify a given speaker when it is a turn of the given speaker for inputting speech to the automated speech-to-speech translation system; synthesizing for playback at least one of the one or more voice prompts from at least one of the one or more text-based scripts, the at least one synthesized voice prompt comprising an audible message in a language understandable to the given speaker to notify the given speaker when it is a turn of the given speaker for inputting speech to the automated speech-to-speech translation system; and playing the at least one synthesized voice prompt to provide the audible message to the given speaker to notify the given speaker that it is the given speaker's turn for inputting speech to the automated speech-to-speech translation system. | 12. An apparatus for use in indicating a dialogue turn in an automated speech-to-speech translation system, comprising: a memory; and at least one processor coupled to the memory and operative to: (i) translate speech input from a plurality of speakers having a multilingual conversation using an automated speech-to-speech translation system; (ii) provide an indication to each speaker of the plurality of speakers of when it is a turn of each speaker to commence speaking in a dialog interact between the plurality of speakers and provide speech input to the automated speech-to-speech translation system, wherein the at least one processor is operative to provide an indication by: obtaining one or more previously-generated text-based scripts, the one or more text-based scripts being synthesizable into one or more voice prompts in different languages of the plurality of speakers, wherein the voice prompts are audible messages that notify a given speaker when it is a turn of the given speaker for inputting speech to the automated speech-to-speech translation system; synthesizing for playback at least one of the one or more voice prompts from at least one of the one or more text-based scripts, the at least one synthesized voice prompt comprising an audible message in a language understandable to the given speaker to notify the given speaker when it is a turn of the given speaker for inputting speech to the automated speech-to-speech translation system; and playing the at least one synthesized voice prompt to provide the audible message to the given speaker to notify the given speaker that it is the given speaker's turn for inputting speech to the automated speech-to-speech translation system. 13. The apparatus of claim 12 , wherein the at least one processor is further operative to detect a language spoken by the given speaker interacting with the speech-to-speech translation system such that a voice prompt in the detected language is synthesized for playback to the given speaker. | 0.501701 |
9,824,480 | 1 | 4 | 1. A method for chaining animations, the method comprising: receiving image data that is representative of captured motion; selecting a pre-canned animation; based at least in part on a transition point, generating a chained animation wherein: the transition point is based, at least in part, on one or more parameters of the captured motion; at least a first portion of the captured motion is represented by the pre-canned animation that replaces the first portion of the captured motion; and at least a second portion of the captured motion is represented by an animation that corresponds to the captured motion; and rendering the chained animation, wherein the chained animation comprises a blending of the first and second portions. | 1. A method for chaining animations, the method comprising: receiving image data that is representative of captured motion; selecting a pre-canned animation; based at least in part on a transition point, generating a chained animation wherein: the transition point is based, at least in part, on one or more parameters of the captured motion; at least a first portion of the captured motion is represented by the pre-canned animation that replaces the first portion of the captured motion; and at least a second portion of the captured motion is represented by an animation that corresponds to the captured motion; and rendering the chained animation, wherein the chained animation comprises a blending of the first and second portions. 4. The method of claim 1 , wherein selecting the pre-canned animation comprises selecting a pre-canned animation from a plurality of pre-canned animations. | 0.864035 |
7,856,472 | 1 | 62 | 1. In a computer system including a plurality of n-tuples, each of the plurality of n-tuples including n>1 text strings, a computer-implemented method comprising: displaying at least one window in connection with a website; displaying, utilizing the at least one window, a stock-related field; receiving a plurality of characters of text from a user as the user is typing the text utilizing the stock-related field; after the user types each character in the received text, dynamically determining whether the characters typed so far match one or more text strings in a first one of a plurality of n-tuples including n>1 text strings, each of the plurality of n-tuples including first text representing a stock ticker symbol and second text representing a company name corresponding to the stock ticker symbol; if it is determined that the characters typed so far match the one or more text strings in the one of the plurality of n-tuples, indicating to the user that a match has been found, utilizing the at least one window; displaying, utilizing the at least one window, a plurality of message summaries; wherein the plurality of message summaries comprise first information derived from a first message of a plurality of first messages and second information derived from a second message of a plurality of second messages associated with at least one online forum; displaying, utilizing the at least one window, a first set of representations; receiving first input from the user indicating a selection of one of the first set of representations; displaying a second set of representations representing a set of hyperlinks, utilizing the at least one window, in response to receiving the first input; receiving second input from the user indicating a selection of one of the second set of representations; and navigating to a destination specified by the selected one of the second set of representations, in response to receiving the second input. | 1. In a computer system including a plurality of n-tuples, each of the plurality of n-tuples including n>1 text strings, a computer-implemented method comprising: displaying at least one window in connection with a website; displaying, utilizing the at least one window, a stock-related field; receiving a plurality of characters of text from a user as the user is typing the text utilizing the stock-related field; after the user types each character in the received text, dynamically determining whether the characters typed so far match one or more text strings in a first one of a plurality of n-tuples including n>1 text strings, each of the plurality of n-tuples including first text representing a stock ticker symbol and second text representing a company name corresponding to the stock ticker symbol; if it is determined that the characters typed so far match the one or more text strings in the one of the plurality of n-tuples, indicating to the user that a match has been found, utilizing the at least one window; displaying, utilizing the at least one window, a plurality of message summaries; wherein the plurality of message summaries comprise first information derived from a first message of a plurality of first messages and second information derived from a second message of a plurality of second messages associated with at least one online forum; displaying, utilizing the at least one window, a first set of representations; receiving first input from the user indicating a selection of one of the first set of representations; displaying a second set of representations representing a set of hyperlinks, utilizing the at least one window, in response to receiving the first input; receiving second input from the user indicating a selection of one of the second set of representations; and navigating to a destination specified by the selected one of the second set of representations, in response to receiving the second input. 62. The method of claim 1 , wherein the user is allowed to control a number of the message summaries that are displayed by selecting the number. | 0.864151 |
8,881,041 | 3 | 9 | 3. The method of claim 1 , wherein, if the current UI mode is the non-physics animation mode, the animation type comprises at least one of a translation type, a rotation type, a scale type, an alpha variation type, and a shape modification type, and if the current UI mode is the physics animation mode, the animation type comprises at least one of the alpha variation type and the shape modification type. | 3. The method of claim 1 , wherein, if the current UI mode is the non-physics animation mode, the animation type comprises at least one of a translation type, a rotation type, a scale type, an alpha variation type, and a shape modification type, and if the current UI mode is the physics animation mode, the animation type comprises at least one of the alpha variation type and the shape modification type. 9. The method of claim 3 , wherein, if the current UI mode is the physics animation mode and the animation type is the alpha variation type, the at least one property comprises physical UI elements and the extracting of the current UI information comprises extracting the physical UI elements, the physical UI elements comprising whether the UI object is visible, a location, and mass of the UI object, and the translating comprises translating the current UI information to non-physical elements, the non-physical UI elements comprising a transparency, a location, and a size of the UI object. | 0.770656 |
7,523,440 | 33 | 39 | 33. A method for generating a formatted user interface for editing information associated with entities in model loaded in a modeling environment, the method comprising: loading one or more models in the modeling environment; displaying a first user interface element displaying entities of the one or more models loaded in the modeling environment, wherein the first user interface element enables users to select multiple entities displayed in the first interface element; selecting a plurality of entities in the loaded models in response to user input in the first user interface element; identifying editable information associated with the selected plurality of entities; identifying common data associated with the selected plurality of entities, the identifying including classifying data in an intersection of data associated with the selected plurality of entities as common data; and dynamically generating from the identified editable information and the identified common data using a computational device a formatted second user interface element displaying at least a portion of the identified editable information and the identified common data associated with the selected plurality of entities, the formatted second user interface element enabling the users to distinguish data associated with the selected plurality of entities that is common data from data associated with the selected plurality of entities that in not common data, the formatted second user interface element enabling the users to edit data that is common data. | 33. A method for generating a formatted user interface for editing information associated with entities in model loaded in a modeling environment, the method comprising: loading one or more models in the modeling environment; displaying a first user interface element displaying entities of the one or more models loaded in the modeling environment, wherein the first user interface element enables users to select multiple entities displayed in the first interface element; selecting a plurality of entities in the loaded models in response to user input in the first user interface element; identifying editable information associated with the selected plurality of entities; identifying common data associated with the selected plurality of entities, the identifying including classifying data in an intersection of data associated with the selected plurality of entities as common data; and dynamically generating from the identified editable information and the identified common data using a computational device a formatted second user interface element displaying at least a portion of the identified editable information and the identified common data associated with the selected plurality of entities, the formatted second user interface element enabling the users to distinguish data associated with the selected plurality of entities that is common data from data associated with the selected plurality of entities that in not common data, the formatted second user interface element enabling the users to edit data that is common data. 39. The method of claim 33 wherein the modeling environment includes a block diagram modeling environment. | 0.83121 |
8,516,585 | 1 | 6 | 1. A computer-implemented method for detecting malicious software agents, the method comprising: (a) constructing an association based on a plurality of failed queries for domain names sent to one or more domain-name servers by a plurality of hosts during a time period; (b) deriving, from the association, one or more candidate clusters of hosts; (c) determining, for each candidate cluster and for each of a plurality of time intervals during the time period, a number of new domain names appearing in the failed queries of the candidate cluster during the time interval; (d) determining, for each candidate cluster, a freshness metric based on the numbers of new domain names for the plurality of time intervals in the time period; and (e) detecting one or more malicious software agents on the hosts based on the one or more freshness metrics. | 1. A computer-implemented method for detecting malicious software agents, the method comprising: (a) constructing an association based on a plurality of failed queries for domain names sent to one or more domain-name servers by a plurality of hosts during a time period; (b) deriving, from the association, one or more candidate clusters of hosts; (c) determining, for each candidate cluster and for each of a plurality of time intervals during the time period, a number of new domain names appearing in the failed queries of the candidate cluster during the time interval; (d) determining, for each candidate cluster, a freshness metric based on the numbers of new domain names for the plurality of time intervals in the time period; and (e) detecting one or more malicious software agents on the hosts based on the one or more freshness metrics. 6. The invention of claim 1 , further comprising: (f) constructing an association based on a plurality of successful queries for domain names sent to one or more domain-name servers by hosts on which one or more malicious software agents are detected in step (e); and (g) querying one or more domain-name servers to identify one or more registrants of domain names corresponding to the successful queries in the association constructed in step (f). | 0.815486 |
10,163,440 | 1 | 13 | 1. A method for assisting a user with one or more desired tasks within a domain, the method comprising: receiving, by a computing system comprising one or more computing devices, a verbal language input and at least one of a plurality of different kinds of non-verbal input from the user; determining, by the computing system, from the verbal language input and the at least one of a plurality of different kinds of non-verbal input, an intention of the user with respect to the one or more desired tasks, by an executable generic language understanding module and a run-time specification comprising a model configured to a specific field of use; and performing, by the computing system, a domain-specific task in accordance with the intention of the user, by an executable generic task reasoning module and a run-time specification comprising a task flow configured to the specific field of use. | 1. A method for assisting a user with one or more desired tasks within a domain, the method comprising: receiving, by a computing system comprising one or more computing devices, a verbal language input and at least one of a plurality of different kinds of non-verbal input from the user; determining, by the computing system, from the verbal language input and the at least one of a plurality of different kinds of non-verbal input, an intention of the user with respect to the one or more desired tasks, by an executable generic language understanding module and a run-time specification comprising a model configured to a specific field of use; and performing, by the computing system, a domain-specific task in accordance with the intention of the user, by an executable generic task reasoning module and a run-time specification comprising a task flow configured to the specific field of use. 13. The method of claim 1 , wherein determining the intention of the user includes considering feedback from the generic task reasoning module. | 0.824755 |
10,026,398 | 10 | 11 | 10. The method of claim 8 , wherein adjusting the initial language model comprises: accessing a database including one or more follow-up query mappings, each follow-up query mapping specifying a list of candidate follow-up queries for (i) prior transcriptions of utterances of the user, (ii) prior search results associated with the user, and (iii) data associated with the prior search results associated the user; determining that one or more terms of the transcription of the initial utterance of the user are included within the one or more follow-up query mappings; and adjusting the initial language model to increase the respective probability associated with the list of candidate follow-up queries that correspond to the one or more terms of the transcription of the initial utterance of the user that are included within the one or more follow-up query mappings. | 10. The method of claim 8 , wherein adjusting the initial language model comprises: accessing a database including one or more follow-up query mappings, each follow-up query mapping specifying a list of candidate follow-up queries for (i) prior transcriptions of utterances of the user, (ii) prior search results associated with the user, and (iii) data associated with the prior search results associated the user; determining that one or more terms of the transcription of the initial utterance of the user are included within the one or more follow-up query mappings; and adjusting the initial language model to increase the respective probability associated with the list of candidate follow-up queries that correspond to the one or more terms of the transcription of the initial utterance of the user that are included within the one or more follow-up query mappings. 11. The method of claim 10 , wherein the list of candidate follow-up queries that are included within the one or more follow-up query mappings is based at least on a user location associated with the initial utterance of the user. | 0.904643 |
9,367,603 | 9 | 12 | 9. A non-transitory computer readable medium comprising computer executable instructions, for when executed by one or more processors are configured for analyzing data from a plurality of users within a social data network, said computer executable instructions configured for: receiving, via a communication device, a query for a topic associated with the social data network; responsive to the query, accessing a data store that stores the data from the plurality of users to determine a set of users in the social data network having at least one social networking behaviour on the social data network related to the queried topic, and determining the set of users further comprises segmenting the set of users from the plurality of users in accordance with at least one common attribute of the social networking behaviour related to the queried topic; for each user from the set of users, applying text processing to posts for each user to extract a list of topic words and associating each of the topic words with the respective user, the posts obtained by accessing the data store; for each user, segmenting each of the topic words into letter segments and computing a statistical likelihood value of each of the letter segments for the respective user; using the statistical likelihood values of each of the letter segments, clustering the topic words to define a plurality of clusters and determining a mapping from each user to at least one of the plurality of clusters; labeling each cluster with one or more highest ranked topic words within the respective cluster used by users mapped to the respective cluster; and outputting the one or more highest ranked topic words mapped to each cluster via the communication device. | 9. A non-transitory computer readable medium comprising computer executable instructions, for when executed by one or more processors are configured for analyzing data from a plurality of users within a social data network, said computer executable instructions configured for: receiving, via a communication device, a query for a topic associated with the social data network; responsive to the query, accessing a data store that stores the data from the plurality of users to determine a set of users in the social data network having at least one social networking behaviour on the social data network related to the queried topic, and determining the set of users further comprises segmenting the set of users from the plurality of users in accordance with at least one common attribute of the social networking behaviour related to the queried topic; for each user from the set of users, applying text processing to posts for each user to extract a list of topic words and associating each of the topic words with the respective user, the posts obtained by accessing the data store; for each user, segmenting each of the topic words into letter segments and computing a statistical likelihood value of each of the letter segments for the respective user; using the statistical likelihood values of each of the letter segments, clustering the topic words to define a plurality of clusters and determining a mapping from each user to at least one of the plurality of clusters; labeling each cluster with one or more highest ranked topic words within the respective cluster used by users mapped to the respective cluster; and outputting the one or more highest ranked topic words mapped to each cluster via the communication device. 12. The non-transitory computer readable medium of claim 9 , wherein the number of letters in each letter segment is three. | 0.894511 |
9,262,553 | 1 | 3 | 1. A method for generating a recommendation, the method comprising: selecting a plurality of members from a user defined community; retrieving a rating for a particular interest from each of the plurality of members, the particular interest based on a user-defined recommendation request; generating a respective perturbed rating for each rating from the plurality of members such that there is a predetermined probability that each rating is different from its respective perturbed rating; aggregating each of the perturbed ratings to generate an aggregated perturbed rating; and generating the recommendation based on the aggregated perturbed rating. | 1. A method for generating a recommendation, the method comprising: selecting a plurality of members from a user defined community; retrieving a rating for a particular interest from each of the plurality of members, the particular interest based on a user-defined recommendation request; generating a respective perturbed rating for each rating from the plurality of members such that there is a predetermined probability that each rating is different from its respective perturbed rating; aggregating each of the perturbed ratings to generate an aggregated perturbed rating; and generating the recommendation based on the aggregated perturbed rating. 3. The method of claim 1 , wherein the user defined community is defined based on a user defined declarative community definition comprising a predicate on user attributes. | 0.879213 |
8,799,658 | 37 | 40 | 37. A computer-implemented method comprising: under control of one or more computer systems configured with executable instructions, receiving, at a server, a request from a first user to store a copy of a media item that is stored on a client device of the first user by an electronic book reader device associated with a second user, wherein the request from the first user does not include information identifying the second user or the electronic book reader device associated with the second user as an intended recipient of the media item; in response to receiving the request at the server, associating a pass phrase with the request to store the copy of the media item; sending the pass phrase from the server to the client device of the first user; after sending the pass phrase, receiving, at the server, the copy of the media item from the client device of the first user; after receiving the copy of the media item at the server, storing the copy of the media item at the server, storing the copy of the media item in association with the pass phrase; and making the copy of the media item available to the electronic book reader device associated with the second user in response to receiving the pass phrase within a predetermined amount of time. | 37. A computer-implemented method comprising: under control of one or more computer systems configured with executable instructions, receiving, at a server, a request from a first user to store a copy of a media item that is stored on a client device of the first user by an electronic book reader device associated with a second user, wherein the request from the first user does not include information identifying the second user or the electronic book reader device associated with the second user as an intended recipient of the media item; in response to receiving the request at the server, associating a pass phrase with the request to store the copy of the media item; sending the pass phrase from the server to the client device of the first user; after sending the pass phrase, receiving, at the server, the copy of the media item from the client device of the first user; after receiving the copy of the media item at the server, storing the copy of the media item at the server, storing the copy of the media item in association with the pass phrase; and making the copy of the media item available to the electronic book reader device associated with the second user in response to receiving the pass phrase within a predetermined amount of time. 40. The computer-implemented method of claim 37 , further comprising erasing the copy of the media item from the server after the predetermined amount of time elapses. | 0.913829 |
8,738,486 | 7 | 9 | 7. A computer-based method according to claim 6 wherein computing a relevance for a single merchant location relative to a set of merchant locations comprises: extracting relevant features from a plurality of merchant locations grouped into sets to generate a document for each set; collecting the generated documents within a dictionary; forming a sparse matrix utilizing the dictionary whereby the relevance of each field value and tokenized field value in the generated documents is computed, utilizing the extracted relevant features based on at least one of a term frequency and an inverse document frequency; and joining a matrix of merchant location level weights to a matrix of merchant group weights based on field types and field values within the sparse matrix. | 7. A computer-based method according to claim 6 wherein computing a relevance for a single merchant location relative to a set of merchant locations comprises: extracting relevant features from a plurality of merchant locations grouped into sets to generate a document for each set; collecting the generated documents within a dictionary; forming a sparse matrix utilizing the dictionary whereby the relevance of each field value and tokenized field value in the generated documents is computed, utilizing the extracted relevant features based on at least one of a term frequency and an inverse document frequency; and joining a matrix of merchant location level weights to a matrix of merchant group weights based on field types and field values within the sparse matrix. 9. A computer-based method according to claim 7 wherein forming the sparse matrix includes a merchant category code, an Interbank card association (ICA) code, a business region, a merchant name, a merchant phone number, an acquiring merchant identifier, a tier merchant identifier, a merchant legal name, and a federal tax identifier. | 0.882062 |
9,721,563 | 13 | 15 | 13. The method as in claim 12 , wherein the plurality of pronunciation guessers comprise pronunciation guessers for a plurality of locales, each locale having its own pronunciation guesser. | 13. The method as in claim 12 , wherein the plurality of pronunciation guessers comprise pronunciation guessers for a plurality of locales, each locale having its own pronunciation guesser. 15. The method as in claim 13 wherein the method is performed by a server that is coupled through a wireless network to the user's device which includes the contacts database and wherein the server obtains the words in the contacts database from the user's device through the wireless network and wherein the server receives the speech input from the user's device through the wireless network and wherein the server transmits the best match to the user's device through the wireless network. | 0.787013 |
9,031,918 | 10 | 16 | 10. The system of claim 9 , further comprising: triggering at least one asynchronous update function upon receiving the request for metadata. | 10. The system of claim 9 , further comprising: triggering at least one asynchronous update function upon receiving the request for metadata. 16. The system of claim 10 , further comprising: inserting the changed metadata into a data view of the personalized user site without reloading the entire site. | 0.9292 |
8,384,917 | 10 | 11 | 10. The method as claimed in claim 1 , wherein the character pairs are extracted by an optical character recognition process with a confidence measure of a character recognition. | 10. The method as claimed in claim 1 , wherein the character pairs are extracted by an optical character recognition process with a confidence measure of a character recognition. 11. The method as claimed in claim 10 , wherein user input is made to confirm a character recognition. | 0.923308 |
8,856,111 | 3 | 4 | 3. The method of claim 1 comprising: receiving a request for videos related to a requested video; and determining the primary entity related to the requested video. | 3. The method of claim 1 comprising: receiving a request for videos related to a requested video; and determining the primary entity related to the requested video. 4. The method of claim 3 comprising: selecting an entity from the ranked list of secondary entities; selecting a video associated the selected entity; and providing the selected video as a recommendation. | 0.934066 |
9,275,115 | 7 | 10 | 7. The method of claim 1 , wherein generating the ranked listing of candidate answer sources based on the entries in the at least one log data structure comprises: generating, for each candidate answer source, a rating of the candidate answer source based on information in the entries of the at least one log data structure for candidate answers generated by the candidate answer source; and generating the ranked listing of candidate answer sources based on a relative comparison of the ratings of each of the candidate answer sources. | 7. The method of claim 1 , wherein generating the ranked listing of candidate answer sources based on the entries in the at least one log data structure comprises: generating, for each candidate answer source, a rating of the candidate answer source based on information in the entries of the at least one log data structure for candidate answers generated by the candidate answer source; and generating the ranked listing of candidate answer sources based on a relative comparison of the ratings of each of the candidate answer sources. 10. The method of claim 7 , wherein generating the rating for the candidate answer source comprises generating the rating for the candidate answer source based on an average amount of time that the candidate answer source required to generate candidate answers for the previously input questions. | 0.919783 |
8,768,868 | 20 | 24 | 20. The computer program product for multi-class classifier threshold-offset estimation as set forth in claim 19 , further comprising instruction means for causing the processor to perform an operation of: generating a vote designating the set of input features as belonging to one object class of each pair of the plurality of object classes M or the other to generate a set of votes; collecting the set of votes to determine which object class of the plurality of object classes M received a majority of the set of votes; classifying the set of input features as belonging to the object class receiving the majority of the set of votes. | 20. The computer program product for multi-class classifier threshold-offset estimation as set forth in claim 19 , further comprising instruction means for causing the processor to perform an operation of: generating a vote designating the set of input features as belonging to one object class of each pair of the plurality of object classes M or the other to generate a set of votes; collecting the set of votes to determine which object class of the plurality of object classes M received a majority of the set of votes; classifying the set of input features as belonging to the object class receiving the majority of the set of votes. 24. The computer program product for multi-class classifier threshold-offset estimation as set forth in claim 20 , further comprising instruction means for causing the processor to perform operations of: extracting an area under the ROC curve (AUC) to determine a true-positive (TP) rate for a given false-positive rate; and defining the objective function as:
f 4 ( x )= TP 1 ( r ′( x ))* TP 2 ( r ′( x ))* TP 3 ( r ′( x ))* . . . , wherein each subscript denotes an object class and * denotes multiplication. | 0.724731 |
9,020,207 | 1 | 15 | 1. A biometric authentication system comprising: a biometric enrollment system configured to determine, for each person in a group of multiple, different people, a similarity score that represents a similarity between a biometric image of at least a portion of the corresponding person from the group of multiple, different people and a reference image and sort biometric data that includes all of the determined similarity scores using the determined similarity scores, wherein the reference image is used in determining all of the similarity scores included in the biometric data; a data storage system configured to maintain, for the group of multiple, different people, biometric data that includes all of the sorted similarity scores; and a biometric verification system that includes at least one processor, the biometric verification system being configured to: access a particular biometric image of at least a portion of a particular person; access the reference image used in computing all of the similarity scores maintained in the data storage system; compute a particular similarity score that represents similarity between the accessed particular biometric image and the reference image; search, using the computed particular similarity score, the sorted similarity scores included in the biometric data for the group of multiple, different people; determine whether the data storage system includes data for the particular person in the biometric data based on the search of the sorted similarity scores included in the biometric data using the computed particular similarity score; and output a result based on the determination of whether the data storage system includes data for the particular person in the biometric data. | 1. A biometric authentication system comprising: a biometric enrollment system configured to determine, for each person in a group of multiple, different people, a similarity score that represents a similarity between a biometric image of at least a portion of the corresponding person from the group of multiple, different people and a reference image and sort biometric data that includes all of the determined similarity scores using the determined similarity scores, wherein the reference image is used in determining all of the similarity scores included in the biometric data; a data storage system configured to maintain, for the group of multiple, different people, biometric data that includes all of the sorted similarity scores; and a biometric verification system that includes at least one processor, the biometric verification system being configured to: access a particular biometric image of at least a portion of a particular person; access the reference image used in computing all of the similarity scores maintained in the data storage system; compute a particular similarity score that represents similarity between the accessed particular biometric image and the reference image; search, using the computed particular similarity score, the sorted similarity scores included in the biometric data for the group of multiple, different people; determine whether the data storage system includes data for the particular person in the biometric data based on the search of the sorted similarity scores included in the biometric data using the computed particular similarity score; and output a result based on the determination of whether the data storage system includes data for the particular person in the biometric data. 15. The biometric authentication system of claim 1 : wherein the biometric verification system is configured to search the sorted similarity scores included in the biometric data using the computed particular similarity score by: using a search process that leverages knowledge of how the similarity scores included in the biometric data are sorted to find a closest match to the computed particular similarity score; computing a difference between the computed particular similarity score and a similarity score of the closest match; comparing the difference to a threshold; and based on comparison results, determining whether the difference is within the threshold; and wherein the biometric verification system is configured to output a result based on the determination of whether the data storage system includes data for the particular person in the biometric data by outputting the closest match based on a determination that the difference is within the threshold. | 0.649496 |
9,645,989 | 23 | 27 | 23. An article of manufacture comprising a non-transitory storage medium containing instructions that when executed enable a system to: determine an application context interface is available for a dynamic form prompt of a new form; determine a custom language interface is available for the dynamic form prompt of the electronic form; receive, from a first device over a network, a form prompt query for the new form, the form prompt query comprising a form prompt identifier and a location identifier, the form prompt identifier to uniquely identify the dynamic form prompt, and the location identifier to uniquely identify a geographic location; determine a previous delegate is set for a previous form; void, via a destroy method, the previous delegate used for the previous form set, by the custom language interface, a new delegate to automatically retrieve, from a second device over the network, custom content utilizing the form prompt identifier and the location identifier for the new form; automatically retrieve, for the new form, the custom content in a custom presentation language for the dynamic form prompt from a form information source using the new delegate; present the dynamic form prompt with the custom content in the custom presentation language in the new form on an electronic display; determine a user session has terminated for the new form; and release resources used by the application context interface and the custom language interface when a user session for the new form has terminated. | 23. An article of manufacture comprising a non-transitory storage medium containing instructions that when executed enable a system to: determine an application context interface is available for a dynamic form prompt of a new form; determine a custom language interface is available for the dynamic form prompt of the electronic form; receive, from a first device over a network, a form prompt query for the new form, the form prompt query comprising a form prompt identifier and a location identifier, the form prompt identifier to uniquely identify the dynamic form prompt, and the location identifier to uniquely identify a geographic location; determine a previous delegate is set for a previous form; void, via a destroy method, the previous delegate used for the previous form set, by the custom language interface, a new delegate to automatically retrieve, from a second device over the network, custom content utilizing the form prompt identifier and the location identifier for the new form; automatically retrieve, for the new form, the custom content in a custom presentation language for the dynamic form prompt from a form information source using the new delegate; present the dynamic form prompt with the custom content in the custom presentation language in the new form on an electronic display; determine a user session has terminated for the new form; and release resources used by the application context interface and the custom language interface when a user session for the new form has terminated. 27. The article of claim 23 further comprising instructions that when executed enable the system to void the new delegate for the new form and set a different delegate for a different form or a different dynamic form prompt. | 0.85696 |
7,711,565 | 46 | 48 | 46. Apparatus adapted to provide information to one or more of a plurality of passengers of a transport apparatus, comprising: first computerized apparatus configured to sample the conversational speech between at least two of said passengers; second computerized apparatus configured to retrieve stored information based on said sampled speech, said stored information being contextually related to at least portions of said sampled speech; and display generation apparatus configured to generate signals relating to at least a portion of said stored information for use on a display device. | 46. Apparatus adapted to provide information to one or more of a plurality of passengers of a transport apparatus, comprising: first computerized apparatus configured to sample the conversational speech between at least two of said passengers; second computerized apparatus configured to retrieve stored information based on said sampled speech, said stored information being contextually related to at least portions of said sampled speech; and display generation apparatus configured to generate signals relating to at least a portion of said stored information for use on a display device. 48. The apparatus of claim 46 , wherein said one or more of said plurality of passengers comprises at least one of said at least two passengers between which said conversational speech occurs. | 0.832753 |
9,009,142 | 1 | 9 | 1. A method comprising: at a server having one or more processors and memory storing one or more programs for execution by the one or more processors so as to perform the method: storing a plurality of index entries in an index, a respective index entry corresponding to a respective term and having a plurality of index components, a respective index component of the respective index entry identifying a message that is associated with the respective term; receiving a first message; associating the first message with a conversation having at least one other message; and storing, in the index, a plurality of first-message index components that each include an identifier of the first message, including: one or more index components indicative of a plurality of message terms in the first message; and one or more index components indicative of one or more conversation terms in the conversation, the one or more conversation terms comprising one or more terms that are not in the first message; wherein a respective first-message index component indicative of a conversation term in the conversation includes a value identifying the respective index component as being associated with a conversation term not in the first message. | 1. A method comprising: at a server having one or more processors and memory storing one or more programs for execution by the one or more processors so as to perform the method: storing a plurality of index entries in an index, a respective index entry corresponding to a respective term and having a plurality of index components, a respective index component of the respective index entry identifying a message that is associated with the respective term; receiving a first message; associating the first message with a conversation having at least one other message; and storing, in the index, a plurality of first-message index components that each include an identifier of the first message, including: one or more index components indicative of a plurality of message terms in the first message; and one or more index components indicative of one or more conversation terms in the conversation, the one or more conversation terms comprising one or more terms that are not in the first message; wherein a respective first-message index component indicative of a conversation term in the conversation includes a value identifying the respective index component as being associated with a conversation term not in the first message. 9. The method of claim 1 , wherein: the one or more first-message index components include one or more index components indicative of message terms in original text in the first message and one or more index components indicative of message terms in quoted text of the first message; and in the index, the index components indicative of message terms in the quoted text of the first message are distinguished from the index components indicative of message terms in the original text of the first message. | 0.661981 |
7,849,148 | 3 | 45 | 3. The method of claim 2 , wherein the plurality of message summaries comprise first information derived from a first message of a plurality of first messages associated with a first online forum. | 3. The method of claim 2 , wherein the plurality of message summaries comprise first information derived from a first message of a plurality of first messages associated with a first online forum. 45. The method of claim 3 , wherein a user is allowed to control a number of the message summaries that are displayed by selecting the number. | 0.966351 |
9,721,559 | 1 | 5 | 1. A method of augmenting training data comprising: receiving, by a computer system, a training set of sampled audio data including speech of a plurality of source speakers; for each of the plurality of source speakers; converting, by the computer system, a feature sequence of a source speaker, of the plurality of source speakers, determined from a plurality of utterances of scripted speech within the training set, to a feature sequence of a respective target speaker under the same scripted speech, wherein the feature sequence of the respective target speaker is added to the training set; training, by the computer system, a speaker-dependent acoustic model for the respective target speaker for corresponding speaker-specific acoustic characteristics; and estimating, by the computer system, a mapping function between the feature sequence of the source speaker and the speaker-dependent acoustic model of the respective target speaker; and for each of the plurality of source speakers: mapping, by the computer system, each of the utterances from each of the plurality of source speakers in the training set using the mapping function to a plurality of other source speakers of the plurality of source speakers, wherein the mapping is added to the training set to generate augmented training data configured to train an automatic system recognition computer system. | 1. A method of augmenting training data comprising: receiving, by a computer system, a training set of sampled audio data including speech of a plurality of source speakers; for each of the plurality of source speakers; converting, by the computer system, a feature sequence of a source speaker, of the plurality of source speakers, determined from a plurality of utterances of scripted speech within the training set, to a feature sequence of a respective target speaker under the same scripted speech, wherein the feature sequence of the respective target speaker is added to the training set; training, by the computer system, a speaker-dependent acoustic model for the respective target speaker for corresponding speaker-specific acoustic characteristics; and estimating, by the computer system, a mapping function between the feature sequence of the source speaker and the speaker-dependent acoustic model of the respective target speaker; and for each of the plurality of source speakers: mapping, by the computer system, each of the utterances from each of the plurality of source speakers in the training set using the mapping function to a plurality of other source speakers of the plurality of source speakers, wherein the mapping is added to the training set to generate augmented training data configured to train an automatic system recognition computer system. 5. The method of claim 1 , further comprising selecting the plurality of the source speakers randomly. | 0.782979 |
9,760,586 | 1 | 12 | 1. An automated method in a computing system for facilitating cooperative and/or competitive searches for publications, comprising: generating a search result snapshot history representation that is a data structure comprising a plurality of nodes that represent search result snapshot objects, each search result snapshot object storing data that corresponds to search results of a specific iteration of a search project, storing data sufficient to restore the specific iteration, and comprising a forward reference and a backward reference, wherein at least some of the plurality of search result snapshot objects are linked to some other of the plurality of search result snapshot objects through the respective forward and backward references of each of the linked search result snapshot objects, and wherein at least two of the plurality of search result snapshot objects have been produced to correspond to search iterations by different individuals or entities; and sharing the generated search result snapshot history between a plurality of different individuals and/or entities. | 1. An automated method in a computing system for facilitating cooperative and/or competitive searches for publications, comprising: generating a search result snapshot history representation that is a data structure comprising a plurality of nodes that represent search result snapshot objects, each search result snapshot object storing data that corresponds to search results of a specific iteration of a search project, storing data sufficient to restore the specific iteration, and comprising a forward reference and a backward reference, wherein at least some of the plurality of search result snapshot objects are linked to some other of the plurality of search result snapshot objects through the respective forward and backward references of each of the linked search result snapshot objects, and wherein at least two of the plurality of search result snapshot objects have been produced to correspond to search iterations by different individuals or entities; and sharing the generated search result snapshot history between a plurality of different individuals and/or entities. 12. The method of claim 1 , further comprising: receiving a designation of one or more of the plurality of search result snapshot objects; and associating one or more ratings with each of the designated search result snapshot objects. | 0.842953 |
7,668,889 | 1 | 9 | 1. A computer-implemented method, comprising: receiving a search query from a single input field of a user interface; performing a keyword search based on the search query to generate keyword search results; performing a natural language search of a frequently-asked question (FAQ) database based on the search query to generate FAQ search results; outputting a first display page that combines the keyword search results and the FAQ search results; wherein the first display page categorizes the keyword search results and the FAQ search results into a plurality of categories including a first category and a second category; wherein the first display page displays the first category and the second category in a particular order, wherein the particular order is based on the keyword search results and the FAQ search results for the first category and for the second category and based on a correlation between the search query, the keyword search results, and the FAQ search results for the first category and for the second category; and outputting for display at a computer display device a second display page that expands the keyword search results and the FAQ search results that are displayed for the first category in the first display page, wherein the expanded keyword search results include a plurality of lines of text for at least one keyword search result. | 1. A computer-implemented method, comprising: receiving a search query from a single input field of a user interface; performing a keyword search based on the search query to generate keyword search results; performing a natural language search of a frequently-asked question (FAQ) database based on the search query to generate FAQ search results; outputting a first display page that combines the keyword search results and the FAQ search results; wherein the first display page categorizes the keyword search results and the FAQ search results into a plurality of categories including a first category and a second category; wherein the first display page displays the first category and the second category in a particular order, wherein the particular order is based on the keyword search results and the FAQ search results for the first category and for the second category and based on a correlation between the search query, the keyword search results, and the FAQ search results for the first category and for the second category; and outputting for display at a computer display device a second display page that expands the keyword search results and the FAQ search results that are displayed for the first category in the first display page, wherein the expanded keyword search results include a plurality of lines of text for at least one keyword search result. 9. The computer-implemented method of claim 1 , wherein the user interface accompanies the single input field with a display of “search or ask a question.” | 0.857798 |
9,626,610 | 1 | 2 | 1. A barcoded quality indicator operative to provide a machine-readable indication of exceedance of at least one threshold by one or more product quality affecting parameters, said barcoded quality indicator comprising: a first barcode being machine readable before actuation of said barcoded quality indicator; a second barcode not being machine readable before actuation of said barcoded quality indicator, said second barcode being machine readable following actuation of said barcoded quality indicator and prior to exceedance of said at least one threshold; and at least one third barcode not being machine readable before actuation of said barcoded quality indicator, said at least one third barcode not being machine readable before exceedance of said at least one threshold and being machine readable following exceedance of said at least one threshold. | 1. A barcoded quality indicator operative to provide a machine-readable indication of exceedance of at least one threshold by one or more product quality affecting parameters, said barcoded quality indicator comprising: a first barcode being machine readable before actuation of said barcoded quality indicator; a second barcode not being machine readable before actuation of said barcoded quality indicator, said second barcode being machine readable following actuation of said barcoded quality indicator and prior to exceedance of said at least one threshold; and at least one third barcode not being machine readable before actuation of said barcoded quality indicator, said at least one third barcode not being machine readable before exceedance of said at least one threshold and being machine readable following exceedance of said at least one threshold. 2. A barcoded quality indicator according to claim 1 and also comprising a pull strip, said pull strip being suitable to prevent the passage of solvents and coloring agents therethrough before removal thereof, and wherein removal of said pull strip actuates said barcoded quality indicator. | 0.501718 |
8,803,812 | 19 | 20 | 19. The mobile communication device of claim 18 , wherein said instructions, when executed on said processor, further cause said mobile communication device to perform operations comprising: displaying a list of symbol variants, wherein the list of symbol variants comprises the plurality of sets of symbol variants in order of decreasing priority. | 19. The mobile communication device of claim 18 , wherein said instructions, when executed on said processor, further cause said mobile communication device to perform operations comprising: displaying a list of symbol variants, wherein the list of symbol variants comprises the plurality of sets of symbol variants in order of decreasing priority. 20. The mobile communication device of claim 19 , wherein the symbol variants of the at least one of the plurality of sets of symbol variants are sorted by both priority and frequency of use. | 0.905352 |
9,760,862 | 3 | 4 | 3. The method of claim 2 , further comprising identifying the editing conflict to distinguish the editing conflict from the non-conflicting content. | 3. The method of claim 2 , further comprising identifying the editing conflict to distinguish the editing conflict from the non-conflicting content. 4. The method of claim 3 , further comprising displaying an origin of the editing conflict. | 0.959447 |
8,572,511 | 1 | 11 | 1. A non-transitory computer readable medium including a sequence of instructions stored thereon for causing a computer to execute a method, comprising: generating a search term entry area operable to allow a user to enter text as a search term; generating a hierarchical tree area operable to display data elements in a multi-level hierarchical tree structure, wherein the data elements are representative of searchable data in a database; generating a search result area operable to display a result of a search query; and generating a search criteria tree area operable to allow a user to enter a new search query of the searchable data in response to the user's selection of one or more of the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area, wherein the search criteria tree area enables the user to select the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area for the new search query, and wherein the search term entry area, hierarchical tree area, search results area, and search criteria tree area are displayed together in a single window on a graphical user interface. | 1. A non-transitory computer readable medium including a sequence of instructions stored thereon for causing a computer to execute a method, comprising: generating a search term entry area operable to allow a user to enter text as a search term; generating a hierarchical tree area operable to display data elements in a multi-level hierarchical tree structure, wherein the data elements are representative of searchable data in a database; generating a search result area operable to display a result of a search query; and generating a search criteria tree area operable to allow a user to enter a new search query of the searchable data in response to the user's selection of one or more of the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area, wherein the search criteria tree area enables the user to select the search term from the search term entry area, the data elements from the hierarchical tree area, and the result from the search result area for the new search query, and wherein the search term entry area, hierarchical tree area, search results area, and search criteria tree area are displayed together in a single window on a graphical user interface. 11. The non-transitory computer readable medium of claim 1 , wherein the new search query is a Boolean search query that includes AND, OR, and NOT functions. | 0.829718 |
10,007,863 | 1 | 10 | 1. A method to detect a logo in images in video frames selected from a video stream, comprising: applying a saliency analysis and segmentation of selected regions in a selected video frame to determine segmented likely logo regions; processing the segmented likely logo regions with feature matching using correlation to generate a first match, neural network classification using a convolutional neural network to generate a second match, and text recognition using character segmentation and string matching to generate a third match; and deciding a most likely logo match by combining results from the first match, the second match, and the third match. | 1. A method to detect a logo in images in video frames selected from a video stream, comprising: applying a saliency analysis and segmentation of selected regions in a selected video frame to determine segmented likely logo regions; processing the segmented likely logo regions with feature matching using correlation to generate a first match, neural network classification using a convolutional neural network to generate a second match, and text recognition using character segmentation and string matching to generate a third match; and deciding a most likely logo match by combining results from the first match, the second match, and the third match. 10. The method of claim 1 further comprising: using N-gram matching to recognize a segment. | 0.911822 |
4,503,420 | 1 | 2 | 1. A circuitry arrangement for effecting an encoding operation by translating data word signals into coded word signals for use with a memory medium, communication channel and the like, comprising in combination: input means to receive data word signals; translating circuitry means coupled to said input means and formed to translate data word signals representing first and second bits into coded word signals representing first, second and third bits in such a manner that the first and second bits of said data word are respectively identical to the second and third bits of said coded word and further formed to translate data word signals representing first, second, third and fourth bits into coded word signals representing first, second, third, fourth, fifth and sixth bits in such a manner that the third and fourth bits of said data word are respectively identical to the second and sixth bits of said coded words; and output means coupled to said translating means to receive coded word signals therefrom to be transmitted to said memory medium, or the like. | 1. A circuitry arrangement for effecting an encoding operation by translating data word signals into coded word signals for use with a memory medium, communication channel and the like, comprising in combination: input means to receive data word signals; translating circuitry means coupled to said input means and formed to translate data word signals representing first and second bits into coded word signals representing first, second and third bits in such a manner that the first and second bits of said data word are respectively identical to the second and third bits of said coded word and further formed to translate data word signals representing first, second, third and fourth bits into coded word signals representing first, second, third, fourth, fifth and sixth bits in such a manner that the third and fourth bits of said data word are respectively identical to the second and sixth bits of said coded words; and output means coupled to said translating means to receive coded word signals therefrom to be transmitted to said memory medium, or the like. 2. A circuit arrangement according claim 1 wherein said output means is formed and coupled to provide input signals to said translating means to affect a translation of said data word signals. | 0.854325 |
8,037,147 | 8 | 9 | 8. The medium of claim 1 wherein the messaging robot is further configured to: present questions to the second messaging identity, at least one of the questions including selectable responses associated with the question; receive, from second messaging identity, responses to the questions; access, from computer-accessible memory, stored responses to the questions, at least one of the stored response having been received from another messaging identity and being associated with the other instant messaging identity who provided the response; compare responses received from the second instant messaging identity to the accessed stored responses; identify, based at least in part on results of the comparison, a group of less than all messaging identities who are currently connected to the chat room system, the group including the first messaging identity; and use the third messaging identity to introduce the identified group of messaging identities who are currently connected to the chat room system to the second messaging identity and to introduce the second messaging identity to the identified group of messaging identities who are connected to the chat room system. | 8. The medium of claim 1 wherein the messaging robot is further configured to: present questions to the second messaging identity, at least one of the questions including selectable responses associated with the question; receive, from second messaging identity, responses to the questions; access, from computer-accessible memory, stored responses to the questions, at least one of the stored response having been received from another messaging identity and being associated with the other instant messaging identity who provided the response; compare responses received from the second instant messaging identity to the accessed stored responses; identify, based at least in part on results of the comparison, a group of less than all messaging identities who are currently connected to the chat room system, the group including the first messaging identity; and use the third messaging identity to introduce the identified group of messaging identities who are currently connected to the chat room system to the second messaging identity and to introduce the second messaging identity to the identified group of messaging identities who are connected to the chat room system. 9. The medium of claim 8 wherein the messaging robot is further configured to: access, from computer-accessible storage, interaction ratings about interactions between the second messaging identity and at least one other messaging identity in the identified group of messaging identities; and identify, based on results of the comparison and the accessed interaction ratings, a group of less than all messaging identities who are currently connected to the chat room system such that the identified group does not include a messaging identity with whom the second messaging identity reported a prior negative interaction. | 0.789349 |
9,612,032 | 8 | 13 | 8. A method for using a wall-mounted device for sensing and control for one or more systems in a home environment, said method comprising: detecting a user rotation of an outer ring that laterally surrounds a body of said device to form a circular lateral periphery of said device, said body having a circular cross-section, a wall-facing rear surface, and a user-facing front surface, said outer ring being user-rotatable around said body for enabling said user rotation, said device having a user-facing circular display component, said user-facing circular display component and said outer ring forming a user input component, wherein at least one environmental sensing component is disposed within said body of said device, wherein said device includes a communication component configured for providing wired or wireless sensing and/or control-related communications with said one or more systems in the home environment, wherein said device includes a processor in operative communication with said at least one environmental sensing component, said communication component, and said user input component; highlighting, based on said user rotation of said outer ring, respective ones of a circular arrangement of display elements appearing near a periphery of said user-facing circular display component; detecting an inward pressing of said outer ring, said outer ring being inwardly pressable for enabling said inward pressing; identifying as a user selection one of said display elements that is highlighted when said inward pressing of said outer ring is detected, wherein plural respective user selections of different ones of said display elements are identified responsive to repeated user rotations and/or inward pressings of said outer ring; and permitting user access to the control of one or more sensing or control functions of said device if said plural respective user selections corresponds to a password or combination. | 8. A method for using a wall-mounted device for sensing and control for one or more systems in a home environment, said method comprising: detecting a user rotation of an outer ring that laterally surrounds a body of said device to form a circular lateral periphery of said device, said body having a circular cross-section, a wall-facing rear surface, and a user-facing front surface, said outer ring being user-rotatable around said body for enabling said user rotation, said device having a user-facing circular display component, said user-facing circular display component and said outer ring forming a user input component, wherein at least one environmental sensing component is disposed within said body of said device, wherein said device includes a communication component configured for providing wired or wireless sensing and/or control-related communications with said one or more systems in the home environment, wherein said device includes a processor in operative communication with said at least one environmental sensing component, said communication component, and said user input component; highlighting, based on said user rotation of said outer ring, respective ones of a circular arrangement of display elements appearing near a periphery of said user-facing circular display component; detecting an inward pressing of said outer ring, said outer ring being inwardly pressable for enabling said inward pressing; identifying as a user selection one of said display elements that is highlighted when said inward pressing of said outer ring is detected, wherein plural respective user selections of different ones of said display elements are identified responsive to repeated user rotations and/or inward pressings of said outer ring; and permitting user access to the control of one or more sensing or control functions of said device if said plural respective user selections corresponds to a password or combination. 13. The method of claim 8 , wherein said user-facing front surface provides a darker background against which one or more of said plurality of display elements is highlighted. | 0.910532 |
9,271,050 | 10 | 13 | 10. A method comprising: authenticating a user login for a localized process system; presenting a user with a project, comprising an asset, wherein the project is a movie, and wherein the asset is created for an original geographical territory; presenting a user with a display to order a localized version of the asset, wherein the localized version of the asset is a version of the asset that is customized for a second geographical territory that is different than the original geographical territory; receiving user input to create subtitles for the localized version of the asset, wherein the user selects himself to enter the subtitles presenting the user with a display of a timed-text script that displays a time of the asset, and the dialogue of the asset receiving user input of a new subtitle that the user entered on the display generating a new timed-text script with the new subtitle receiving an order to create the localized version of the asset, wherein the localized version of the asset is created using the new timed-text script. | 10. A method comprising: authenticating a user login for a localized process system; presenting a user with a project, comprising an asset, wherein the project is a movie, and wherein the asset is created for an original geographical territory; presenting a user with a display to order a localized version of the asset, wherein the localized version of the asset is a version of the asset that is customized for a second geographical territory that is different than the original geographical territory; receiving user input to create subtitles for the localized version of the asset, wherein the user selects himself to enter the subtitles presenting the user with a display of a timed-text script that displays a time of the asset, and the dialogue of the asset receiving user input of a new subtitle that the user entered on the display generating a new timed-text script with the new subtitle receiving an order to create the localized version of the asset, wherein the localized version of the asset is created using the new timed-text script. 13. The method of claim 10 wherein the asset is a red carpet interview recorded from a movie premier for the movie. | 0.748908 |
8,209,672 | 1 | 9 | 1. A computerized method for transforming an event-driven process chain (EPC) modeled business process into an executable business process, the method comprising: providing a plurality of graphical constructs in a database, the plurality of graphical constructs representing elements in the EPC modeled business process; providing a set of transformation rules in the database, the set of transformation rules including rules for converting the graphical constructs into programming constructs for the executable business process, wherein the set of transformation rules further include rules for converting a loop into programming constructs for the executable business process; applying the set of transformation rules to the graphical constructs to generate the executable business process comprising an ordered sequence of programming constructs, wherein the ordered sequence of programming constructs comprises business process execution language (BPEL) representation; and storing the ordered sequence of programming constructs in the database for subsequent execution of the executable business process. | 1. A computerized method for transforming an event-driven process chain (EPC) modeled business process into an executable business process, the method comprising: providing a plurality of graphical constructs in a database, the plurality of graphical constructs representing elements in the EPC modeled business process; providing a set of transformation rules in the database, the set of transformation rules including rules for converting the graphical constructs into programming constructs for the executable business process, wherein the set of transformation rules further include rules for converting a loop into programming constructs for the executable business process; applying the set of transformation rules to the graphical constructs to generate the executable business process comprising an ordered sequence of programming constructs, wherein the ordered sequence of programming constructs comprises business process execution language (BPEL) representation; and storing the ordered sequence of programming constructs in the database for subsequent execution of the executable business process. 9. The method according to claim 1 , wherein one of the transformation rules indicates that a decision path with no business process steps in the EPC modeled business process is transformed into a programming construct corresponding to an Empty BPEL activity. | 0.67132 |
9,043,257 | 1 | 2 | 1. An application server for matching a plurality of users within a domain, said application server configured to: (A) implement a social network having a plurality of users; (B) observe network behaviors of at least some of said plurality of users of said social network; (C) develop profiles of at least some of said plurality of users within at least one of a plurality of domains using a profile function, wherein (i) said profile function defines a level of relevance of network behaviors for said domain, (ii) said profile function maps said observed network behaviors to said profiles for said domain and (iii) each of said profiles stores a descriptor representing one of said plurality of users for said domain; and (D) compute matches of two or more of said plurality of users with respect to one of said domains, wherein said matches are based on a relation of common descriptors of said profiles for said domain. | 1. An application server for matching a plurality of users within a domain, said application server configured to: (A) implement a social network having a plurality of users; (B) observe network behaviors of at least some of said plurality of users of said social network; (C) develop profiles of at least some of said plurality of users within at least one of a plurality of domains using a profile function, wherein (i) said profile function defines a level of relevance of network behaviors for said domain, (ii) said profile function maps said observed network behaviors to said profiles for said domain and (iii) each of said profiles stores a descriptor representing one of said plurality of users for said domain; and (D) compute matches of two or more of said plurality of users with respect to one of said domains, wherein said matches are based on a relation of common descriptors of said profiles for said domain. 2. The application server according to claim 1 , wherein said plurality of domains comprises at least one of an activity, a goal, a need and an interest. | 0.802326 |
7,509,328 | 14 | 19 | 14. The computer program product of claim 13 wherein the method is performed multiple times to select multiple attributes to be used during execution of the selected procedure. | 14. The computer program product of claim 13 wherein the method is performed multiple times to select multiple attributes to be used during execution of the selected procedure. 19. The computer program product of claim 14 wherein multiple different business processes within the same software application program each provide for communication with the same electronic database of product data. | 0.939823 |
9,781,178 | 1 | 10 | 1. A method comprising: generating a template for a publication, the template including a plurality of content frames, a portion of the plurality of content frames being prepopulated with content, the remainder of the plurality of content frames providing an empty placeholder for populating content; receiving a content item from a first user of a group of users designated as contributors to the publication; receiving, from a second user of the group of users designated as contributors to the publication, rating information comprising a first rating for the content item and a second rating for a placement of the content item within a particular content frame from among the remainder of the plurality of content frames; and generating the publication using the template and the received content item, the generating of the publication including determining placement of the content item in one of the remainder of the plurality of content frames based on the first and second ratings received from the second user. | 1. A method comprising: generating a template for a publication, the template including a plurality of content frames, a portion of the plurality of content frames being prepopulated with content, the remainder of the plurality of content frames providing an empty placeholder for populating content; receiving a content item from a first user of a group of users designated as contributors to the publication; receiving, from a second user of the group of users designated as contributors to the publication, rating information comprising a first rating for the content item and a second rating for a placement of the content item within a particular content frame from among the remainder of the plurality of content frames; and generating the publication using the template and the received content item, the generating of the publication including determining placement of the content item in one of the remainder of the plurality of content frames based on the first and second ratings received from the second user. 10. The method of claim 1 , further comprising: receiving an identifier of a third user linked to the content item; and transmitting, to the third user, an invitation to contribute to the publication based on the third user being linked to the content item. | 0.792071 |
7,490,034 | 1 | 18 | 1. A computer readable storage medium having a lexicon for storing word information and adapted for use with a text analyzer in a language processing system, wherein the lexicon is adapted to be used in a plurality of language processing tasks, the lexicon comprising: a word list section for storing a list of words; a set of data sections corresponding with each word on the word list, wherein the data sections store substantially different selected information about the corresponding word in the word list; and for each word on the word list, a plurality of pointers stored in an indices table apart from the sets of data sections, each of the pointers pointing to a different data section related to different information about the corresponding word, wherein the plurality of pointers comprises a first set and a second set of the pointers, the first set used to access information related to a first natural language processing task and the second set used to access information related to a second natural language processing task, wherein the first set of the pointers is not the same as the second set of the pointers. | 1. A computer readable storage medium having a lexicon for storing word information and adapted for use with a text analyzer in a language processing system, wherein the lexicon is adapted to be used in a plurality of language processing tasks, the lexicon comprising: a word list section for storing a list of words; a set of data sections corresponding with each word on the word list, wherein the data sections store substantially different selected information about the corresponding word in the word list; and for each word on the word list, a plurality of pointers stored in an indices table apart from the sets of data sections, each of the pointers pointing to a different data section related to different information about the corresponding word, wherein the plurality of pointers comprises a first set and a second set of the pointers, the first set used to access information related to a first natural language processing task and the second set used to access information related to a second natural language processing task, wherein the first set of the pointers is not the same as the second set of the pointers. 18. The computer readable storage medium of claim 1 wherein two data sections of the set of data sections corresponding to each word separately store information selected from the group consisting of spell checking information, morphology information, linguistic information and multiple word expression information. | 0.854378 |
8,533,130 | 1 | 10 | 1. An apparatus comprising: a memory; a processor operatively coupled to the memory; and a neural network comprising: a plurality of word neurons; a plurality of sentence neurons; at least one document neuron; a plurality of first connections between at least a portion of the plurality of word neurons and the plurality of sentence neurons; and a plurality of second connections between at least a portion of the word neurons and the at least one document neuron, wherein the neural network is configured to excite a first sentence neuron of the plurality of sentence neurons in response to excitation of the at least one document neuron; wherein the processor is configured to change a position of the plurality of word neurons on a display based on an input, and wherein the change in the position of one word neuron changes annotation corresponding to at least one of the plurality of sentence neurons. | 1. An apparatus comprising: a memory; a processor operatively coupled to the memory; and a neural network comprising: a plurality of word neurons; a plurality of sentence neurons; at least one document neuron; a plurality of first connections between at least a portion of the plurality of word neurons and the plurality of sentence neurons; and a plurality of second connections between at least a portion of the word neurons and the at least one document neuron, wherein the neural network is configured to excite a first sentence neuron of the plurality of sentence neurons in response to excitation of the at least one document neuron; wherein the processor is configured to change a position of the plurality of word neurons on a display based on an input, and wherein the change in the position of one word neuron changes annotation corresponding to at least one of the plurality of sentence neurons. 10. The apparatus of claim 1 , wherein the processor is configured to receive the input, wherein the input comprises an indication of irrelevance of a sentence neuron, and wherein the indication of the irrelevance of the sentence neuron inhibits neurons of the neural network. | 0.711297 |
8,024,733 | 1 | 11 | 1. A computer-implemented method of batch processing in a batch component model within a distributed object environment, the computer-implemented method comprising: instantiating a batch component by a processor of a data processing system, for use with a batch job within the distributed object environment; initializing the batch component with a set of deployment descriptors and an instance of a batch container to form a contractual relationship between the batch component and the batch container, wherein the set of deployment descriptors is a set of declarative policies for the batch component; wrapping the contractual relationship between the batch component and the batch container to form an adapter, wherein the adapter isolates the batch component from different implementations of the batch container; dynamically computing by the batch container, for each use of a checkpoint interval, a size of the checkpoint interval for the batch job based on the set of deployment descriptors and other processing workloads; managing operation of the batch component in the batch component model by the batch container in accordance with the set of deployment descriptors and the other processing workloads; and committing, by the batch container on the processor, at an end of the checkpoint interval, checkpoint cursors and data of the batch job that are updated during the batch processing to a storage of the data processing system, wherein context information, including the size of the checkpoint interval and resource dependencies, is persisted and passed to downstream batch containers. | 1. A computer-implemented method of batch processing in a batch component model within a distributed object environment, the computer-implemented method comprising: instantiating a batch component by a processor of a data processing system, for use with a batch job within the distributed object environment; initializing the batch component with a set of deployment descriptors and an instance of a batch container to form a contractual relationship between the batch component and the batch container, wherein the set of deployment descriptors is a set of declarative policies for the batch component; wrapping the contractual relationship between the batch component and the batch container to form an adapter, wherein the adapter isolates the batch component from different implementations of the batch container; dynamically computing by the batch container, for each use of a checkpoint interval, a size of the checkpoint interval for the batch job based on the set of deployment descriptors and other processing workloads; managing operation of the batch component in the batch component model by the batch container in accordance with the set of deployment descriptors and the other processing workloads; and committing, by the batch container on the processor, at an end of the checkpoint interval, checkpoint cursors and data of the batch job that are updated during the batch processing to a storage of the data processing system, wherein context information, including the size of the checkpoint interval and resource dependencies, is persisted and passed to downstream batch containers. 11. The computer-implemented method of claim 1 , wherein the batch component shares business logic and data components within the distributed object environment with other batch jobs or online transaction processing components. | 0.8865 |
9,170,785 | 8 | 9 | 8. The method of claim 7 , wherein the input statement comprises the symbolic variable. | 8. The method of claim 7 , wherein the input statement comprises the symbolic variable. 9. The method of claim 8 , wherein modifying further comprises: substituting the associated value for the symbolic variable. | 0.954277 |
8,620,928 | 9 | 16 | 9. A computer system comprising: a central processing unit (CPU); a memory coupled to the CPU; a computer-readable, tangible storage device coupled to the CPU, the storage device containing instructions that, when carried out by the CPU via the memory, implement a method of generating a log parser, the method comprising the steps of: the computer system receiving a sample log whose parts are delimited by one or more occurrences of a delimiter in the sample log; the computer system retrieving a plurality of tokens; the computer system generating a tokenized log by delimiting the received sample log based on a token included in the retrieved plurality of tokens, the tokenized log comprising a plurality of elements, each element delimited in the tokenized log by the token; the computer system determining one or more matches between respective one or more elements in the plurality of elements and respective one or more attributes, each attribute being an attribute of a field included in one or more fields of the sample log; based on the one or more matches and based on the token, the computer system determining one or more positions of the respective one or more elements within the tokenized log; based on the one or more matches, the computer system determining a ranking of the token, the ranking indicating a first likelihood that the token is the delimiter that delimits the parts of the sample log; the computer system determining a second ranking of another token included in the retrieved plurality of tokens, the second ranking indicating a second likelihood that the other token is the delimiter; the computer system determining the first likelihood is greater than the second likelihood; based on the one or more positions, the one or more matches, and the token, the computer system generating a first parser by generating one or more parser patterns for the one or more matches, respectively; the computer system generating a second parser based in part on the other token; the computer system parsing the sample log based on the generated first parser; and based on the first likelihood being greater than the second likelihood, the computer system presenting a result of the step of parsing the sample log and the computer system receiving a validation of the presented result without the computer system presenting another result of parsing the sample log based on the second parser. | 9. A computer system comprising: a central processing unit (CPU); a memory coupled to the CPU; a computer-readable, tangible storage device coupled to the CPU, the storage device containing instructions that, when carried out by the CPU via the memory, implement a method of generating a log parser, the method comprising the steps of: the computer system receiving a sample log whose parts are delimited by one or more occurrences of a delimiter in the sample log; the computer system retrieving a plurality of tokens; the computer system generating a tokenized log by delimiting the received sample log based on a token included in the retrieved plurality of tokens, the tokenized log comprising a plurality of elements, each element delimited in the tokenized log by the token; the computer system determining one or more matches between respective one or more elements in the plurality of elements and respective one or more attributes, each attribute being an attribute of a field included in one or more fields of the sample log; based on the one or more matches and based on the token, the computer system determining one or more positions of the respective one or more elements within the tokenized log; based on the one or more matches, the computer system determining a ranking of the token, the ranking indicating a first likelihood that the token is the delimiter that delimits the parts of the sample log; the computer system determining a second ranking of another token included in the retrieved plurality of tokens, the second ranking indicating a second likelihood that the other token is the delimiter; the computer system determining the first likelihood is greater than the second likelihood; based on the one or more positions, the one or more matches, and the token, the computer system generating a first parser by generating one or more parser patterns for the one or more matches, respectively; the computer system generating a second parser based in part on the other token; the computer system parsing the sample log based on the generated first parser; and based on the first likelihood being greater than the second likelihood, the computer system presenting a result of the step of parsing the sample log and the computer system receiving a validation of the presented result without the computer system presenting another result of parsing the sample log based on the second parser. 16. The computer system of claim 9 , wherein the method further comprises the steps of: the computer system receiving a type of the sample log; based on the received type of the sample log, the computer system receiving a plurality of names of fields and a plurality of value patterns for values of the fields; the computer system determining that no match exists between an element in the plurality of elements and any name in the received plurality of names of fields; the computer system selecting a value pattern from the plurality of value patterns, the selected value pattern being an attribute included in the one or more attributes; the computer system determining a match between the element and the selected value pattern; based on the match between the element and the selected value pattern, the computer system determining a position of the element within the tokenized log, wherein the step of generating the first parser includes: based on the token, the position and the selected value pattern, and not based on any name included in the plurality of names of fields, the computer system generating a parser pattern specifying a pattern of the field. | 0.500429 |
7,961,143 | 1 | 5 | 1. A method for performing integer ambiguity resolution in a global navigation satellite system, comprising: identifying a set of satellites from which carrier signals are received; identifying a set of ambiguities associated with carrier phase measurements of at least some of the signals received from the satellites in the identified set of satellites; estimating integer ambiguities in the set of ambiguities, including determining a best candidate set and a second best candidate set of integer ambiguity values for each of the ambiguities in the set of ambiguities; upon determining that the best candidate set of integer ambiguity values fails to meet a discrimination test with respect to the second best candidate set, removing from the set of ambiguities each ambiguity for which integer ambiguity values in the best candidate set and second best candidate set fail to meet predefined criteria to produce a reduced set of ambiguities; performing operations to resolve the ambiguities in the reduced set of ambiguities; and generating an output in accordance with a result of the operations performed to resolve the ambiguities in the reduced set of ambiguities. | 1. A method for performing integer ambiguity resolution in a global navigation satellite system, comprising: identifying a set of satellites from which carrier signals are received; identifying a set of ambiguities associated with carrier phase measurements of at least some of the signals received from the satellites in the identified set of satellites; estimating integer ambiguities in the set of ambiguities, including determining a best candidate set and a second best candidate set of integer ambiguity values for each of the ambiguities in the set of ambiguities; upon determining that the best candidate set of integer ambiguity values fails to meet a discrimination test with respect to the second best candidate set, removing from the set of ambiguities each ambiguity for which integer ambiguity values in the best candidate set and second best candidate set fail to meet predefined criteria to produce a reduced set of ambiguities; performing operations to resolve the ambiguities in the reduced set of ambiguities; and generating an output in accordance with a result of the operations performed to resolve the ambiguities in the reduced set of ambiguities. 5. The method of claim 1 , wherein the best candidate set and second best candidate set each include, for each ambiguity in the set of ambiguities, an integer ambiguity value for a respective carrier signal. | 0.944265 |
9,177,551 | 1 | 13 | 1. A method comprising: receiving, via touch provided on a touch screen of a device, an indication associated with a specific field displayed in a user interface on the touch screen, the indication signaling that speech, which is associated with the specific field, will follow; receiving the speech via the device and generating speech data based on the speech; generating, by the device, a request for speech recognition, wherein the request comprises: (1) an application identifier identifying a speech recognizer on a public network node; (2) a location parameter specific to a current location of the device, the device being associated with a speaker of the speech; and (3) a grammar parameter associated with a home location of the speaker of the speech, the grammar parameter identifying a particular grammar; transmitting the speech data and the request to the public network node for speech recognition using the speech recognizer; receiving, at the device, text associated with the speech data from the speech recognizer; and inserting the text into the specific field. | 1. A method comprising: receiving, via touch provided on a touch screen of a device, an indication associated with a specific field displayed in a user interface on the touch screen, the indication signaling that speech, which is associated with the specific field, will follow; receiving the speech via the device and generating speech data based on the speech; generating, by the device, a request for speech recognition, wherein the request comprises: (1) an application identifier identifying a speech recognizer on a public network node; (2) a location parameter specific to a current location of the device, the device being associated with a speaker of the speech; and (3) a grammar parameter associated with a home location of the speaker of the speech, the grammar parameter identifying a particular grammar; transmitting the speech data and the request to the public network node for speech recognition using the speech recognizer; receiving, at the device, text associated with the speech data from the speech recognizer; and inserting the text into the specific field. 13. The method of claim 1 , further comprising presenting an action button associated with the text in the specific field only when a confidence level from the speech recognizer is below a threshold. | 0.818099 |
10,114,817 | 22 | 25 | 22. A system comprising: one or more processors; one or more storage media storing instructions which, when executed by the one or more processors, cause: storing a plurality of multi-language profiles of a plurality of users; identifying one or more multilingual cognates in each profile of the plurality of multi-language profiles; based on the one or more multilingual cognates identified in each profile of the plurality of multi-language profiles, generating one or more translation models; receiving input that indicates a selection, by a second user, of data that is associated with a first user that is different than the second user, wherein the plurality of users includes users other than the second user and the first user; determining a first language that is associated with the first user; determining a second language that is different than the first language and that is associated with the second user; wherein a plurality of data items in a profile of the first user are in the first language; translating the plurality of data items into the second language using the one or more translation models; in response to receiving the input, causing a translated version of the plurality of data items to be displayed to the second user, wherein the translated version is in the second language. | 22. A system comprising: one or more processors; one or more storage media storing instructions which, when executed by the one or more processors, cause: storing a plurality of multi-language profiles of a plurality of users; identifying one or more multilingual cognates in each profile of the plurality of multi-language profiles; based on the one or more multilingual cognates identified in each profile of the plurality of multi-language profiles, generating one or more translation models; receiving input that indicates a selection, by a second user, of data that is associated with a first user that is different than the second user, wherein the plurality of users includes users other than the second user and the first user; determining a first language that is associated with the first user; determining a second language that is different than the first language and that is associated with the second user; wherein a plurality of data items in a profile of the first user are in the first language; translating the plurality of data items into the second language using the one or more translation models; in response to receiving the input, causing a translated version of the plurality of data items to be displayed to the second user, wherein the translated version is in the second language. 25. The system of claim 22 , wherein the instructions, when executed by the one or more processors, further cause: identifying a first user profile that includes a first plurality of data items in the first language and a second plurality of data items in the second language, wherein the first plurality of data items correspond to the second plurality of data items; identifying a second user profile that is different than the first user profile and that includes a third plurality of data items in the first language and a fourth plurality of data items in the second language, wherein the third plurality of data items correspond to the fourth plurality of data items; generating multilingual cognates based on a correspondence between the first plurality of data items and the second plurality of data items and based on a correspondence between the third plurality of data items and the fourth plurality of data items. | 0.50054 |
8,006,138 | 1 | 4 | 1. A method for software processing, comprising: accepting quality information comprising names of elements of software code and respective quality indications regarding tested acceptability of the elements; processing the names to extract a list of substrings that occur in the names; assigning respective metrics to the substrings responsively to the quality indications of the elements in whose names the substrings occur; and presenting at least some of the substrings to a user in accordance with the assigned metrics, wherein the quality indications are indicative of known faults in the respective elements, and wherein the quality indications are indicative of the known faults in the respective elements that were expected to be initially found by a first testing phase but were initially found by a second testing phase subsequent to the first testing phase. | 1. A method for software processing, comprising: accepting quality information comprising names of elements of software code and respective quality indications regarding tested acceptability of the elements; processing the names to extract a list of substrings that occur in the names; assigning respective metrics to the substrings responsively to the quality indications of the elements in whose names the substrings occur; and presenting at least some of the substrings to a user in accordance with the assigned metrics, wherein the quality indications are indicative of known faults in the respective elements, and wherein the quality indications are indicative of the known faults in the respective elements that were expected to be initially found by a first testing phase but were initially found by a second testing phase subsequent to the first testing phase. 4. The method according to claim 1 , wherein processing the names comprises extracting only a subset of the substrings that occur in the names in accordance with a predefined criterion. | 0.818627 |
7,603,345 | 1 | 6 | 1. A computer implemented method for identifying spam documents in an information retrieval system, the method comprising: maintaining a list of phrases in a memory, each phrase associated with a list of related phrases; determining, for a document that contains a first phrase from the list of phrases, a number of the related phrases related to the first phrase expected to be present in the document; determining for the document, and for the first phrase in the document, an actual number of related phrases present in the document; and identifying the document as a spam document by comparing the actual number of related phrases present in the document with the expected number of related phrases, wherein determining the number of related phrases related to the first phrase expected to be present in the document includes: traversing an index of a plurality of documents; for each of the indexed documents: determining a set of phrases in the indexed document from the list of phrases, and for each phrase in the set, determining a number of related phrases also in the indexed document; and determining the expected number of related phrases based on the determined number of related phrases, related to the first phrase, in the indexed documents. | 1. A computer implemented method for identifying spam documents in an information retrieval system, the method comprising: maintaining a list of phrases in a memory, each phrase associated with a list of related phrases; determining, for a document that contains a first phrase from the list of phrases, a number of the related phrases related to the first phrase expected to be present in the document; determining for the document, and for the first phrase in the document, an actual number of related phrases present in the document; and identifying the document as a spam document by comparing the actual number of related phrases present in the document with the expected number of related phrases, wherein determining the number of related phrases related to the first phrase expected to be present in the document includes: traversing an index of a plurality of documents; for each of the indexed documents: determining a set of phrases in the indexed document from the list of phrases, and for each phrase in the set, determining a number of related phrases also in the indexed document; and determining the expected number of related phrases based on the determined number of related phrases, related to the first phrase, in the indexed documents. 6. The method of claim 1 , wherein identifying the document as a spam document, further comprises: determining, for a second phrase contained in the document, a number of the related phrases related to a second phrase expected to be present in the document; determining for the document, and for the second phrase in the document, an actual number of related phrases present in the document; determining, for a third phrase contained in the document, a number of the related phrases related to a third phrase expected to be present in the document; determining for the document, and for the third phrase in the document, an actual number of related phrases present in the document; identifying the document as a spam document where, for each of the first phrase, the second phrase, and the third phrase, the actual number of related phrases present in the document exceeds the expected number of related phrases based on a threshold. | 0.515576 |
8,326,686 | 1 | 16 | 1. A computer-implemented method comprising: a) accepting, for each of at least one advertiser, by an advertising system including one or more computers, information from at least one advertiser document, wherein the at least one advertiser document defines an inventory of at least one of products and services offered on an online Website of the at least one advertiser; b) generating ads for the at least one advertiser, by the advertising system, each of the generated ads including i) a creative, and ii) offer information, using the accepted information from the at least one advertiser document; c) generating, by the advertising system, an index mapping information extracted from the at least one advertiser document to one of (A) advertiser document identifiers for the at least one advertiser document on which the extracted information is found, and (B) ad identifiers for ads generated from the at least one advertiser document on which the extracted information is found; d) accepting, by the advertising system, additional information, wherein the additional information is one of (A) search query information and (B) document relevance information; e) determining, by the advertising system, one or more ads relevant to the additional information using the index generated and the additional information; and f) serving at least one of the determined one or more relevant ads for rendering on a client device, wherein the offer information is expressed procedurally. | 1. A computer-implemented method comprising: a) accepting, for each of at least one advertiser, by an advertising system including one or more computers, information from at least one advertiser document, wherein the at least one advertiser document defines an inventory of at least one of products and services offered on an online Website of the at least one advertiser; b) generating ads for the at least one advertiser, by the advertising system, each of the generated ads including i) a creative, and ii) offer information, using the accepted information from the at least one advertiser document; c) generating, by the advertising system, an index mapping information extracted from the at least one advertiser document to one of (A) advertiser document identifiers for the at least one advertiser document on which the extracted information is found, and (B) ad identifiers for ads generated from the at least one advertiser document on which the extracted information is found; d) accepting, by the advertising system, additional information, wherein the additional information is one of (A) search query information and (B) document relevance information; e) determining, by the advertising system, one or more ads relevant to the additional information using the index generated and the additional information; and f) serving at least one of the determined one or more relevant ads for rendering on a client device, wherein the offer information is expressed procedurally. 16. The computer-implemented method of claim 1 , wherein the information from the at least one advertiser document includes terms, each of the terms including one of a word and a phrase, wherein the index generated maps the terms extracted from the at least one advertiser document back to one of (A) advertiser document identifiers for the at least one advertiser document on which such terms are found, and (B) ad identifiers for ads generated from the at least one advertiser document on which such terms are found such that the terms are used as targeting keywords, wherein the at least one advertiser document is a plurality of product Web pages of an e-commerce Website, which Web pages are arranged in a hierarchy defined by product categories, and wherein at least one of the terms is inherited from an ancestor Web page. | 0.500602 |
5,495,604 | 1 | 11 | 1. Apparatus for specifying database designs including a general purpose programmable digital computer, said computer having central processing unit, bus, display device, data entry device, memory, graphical user interface, and repository means, said apparatus further comprising: diagram means for producing a diagram on said display device; cursor control means, responsive to said data entry device, for controlling movement of a cursor over said diagram; text input means, responsive to said data entry device, for entering text into an edit window, items of said text including objects, facts about said objects, and constraints on said objects; text translation means for translating a text item from said edit window into said diagram, including (a) capture means, responsive to a first selector means of said data entry device, for capturing an item of said text from within said edit window, (b) item test means, responsive to said capture means, for testing whether a text item is an object, a fact or a constraint, (c) cursor change means, responsive to said item test means, for changing said cursor to reflect whether said text item is an object, a fact or a constraint, (d) cursor release means, further responsive to said first selector means of said data entry device, for dropping said text item onto said diagram, (e) text collection means for collecting said text item at said edit window, (f) parsing means, responsive to said text collection means, for parsing said text item into objects, facts, and constraints, (g) first update means for updating said repository by copying said objects, facts and constraints into said repository as records, (h) said diagram means, further responsive to said cursor control device, said capture means, said item test means, said cursor change means, said cursor release means, and said parsing means, for drawing said objects, facts and constraints on said diagram; text validation means including (a) first text combining means for combining said text from said edit window, (b) said parsing means, further responsive to said first text combining means, for parsing said text into said objects, facts and constraints, (c) first error checking means, further responsive to said parsing means, for determining if an error exists in said objects, facts or constraints; and text compilation means for compiling said text only into said repository means. | 1. Apparatus for specifying database designs including a general purpose programmable digital computer, said computer having central processing unit, bus, display device, data entry device, memory, graphical user interface, and repository means, said apparatus further comprising: diagram means for producing a diagram on said display device; cursor control means, responsive to said data entry device, for controlling movement of a cursor over said diagram; text input means, responsive to said data entry device, for entering text into an edit window, items of said text including objects, facts about said objects, and constraints on said objects; text translation means for translating a text item from said edit window into said diagram, including (a) capture means, responsive to a first selector means of said data entry device, for capturing an item of said text from within said edit window, (b) item test means, responsive to said capture means, for testing whether a text item is an object, a fact or a constraint, (c) cursor change means, responsive to said item test means, for changing said cursor to reflect whether said text item is an object, a fact or a constraint, (d) cursor release means, further responsive to said first selector means of said data entry device, for dropping said text item onto said diagram, (e) text collection means for collecting said text item at said edit window, (f) parsing means, responsive to said text collection means, for parsing said text item into objects, facts, and constraints, (g) first update means for updating said repository by copying said objects, facts and constraints into said repository as records, (h) said diagram means, further responsive to said cursor control device, said capture means, said item test means, said cursor change means, said cursor release means, and said parsing means, for drawing said objects, facts and constraints on said diagram; text validation means including (a) first text combining means for combining said text from said edit window, (b) said parsing means, further responsive to said first text combining means, for parsing said text into said objects, facts and constraints, (c) first error checking means, further responsive to said parsing means, for determining if an error exists in said objects, facts or constraints; and text compilation means for compiling said text only into said repository means. 11. The apparatus of claim 1, wherein said text translation means further comprises edit window clearing means, responsive to movement of said cursor over said diagram, for causing said edit window to disappear from said display means while said cursor is being moved. | 0.927174 |
8,381,095 | 2 | 3 | 2. The method of claim 1 , further comprising: separating out table segments from the merged node list into a table node list; recovering the cached emphasis data for the table segments in the table node list, wherein the step of refining the table comparisons in the merged node list via the at least one additional longest common subsequence process is performed on the table node list table segments comprising the recovered cached emphasis data; and embedding the refined table comparisons into the merged node list in combination with the non-table node list prior to the building of the merged document object model from the merged node list. | 2. The method of claim 1 , further comprising: separating out table segments from the merged node list into a table node list; recovering the cached emphasis data for the table segments in the table node list, wherein the step of refining the table comparisons in the merged node list via the at least one additional longest common subsequence process is performed on the table node list table segments comprising the recovered cached emphasis data; and embedding the refined table comparisons into the merged node list in combination with the non-table node list prior to the building of the merged document object model from the merged node list. 3. The method of claim 2 , wherein the step of refining table comparisons in the merged node list via the at least one additional longest common subsequence process comprises: constructing unique table header labels for the table segments in the table node list; comparing the constructed header labels of the tables via a second phase longest common subsequence process to generate column header text for merged table column names in a merged header node list; analyzing the column header text to distinguish between new and modified columns; and generating a first column name map for the first DITA document and a second column name map for the second DITA document from old column names for each input table to the merged table column names. | 0.829675 |
7,715,629 | 10 | 14 | 10. The method of training a handwriting recognition application recited in claim 8 , further comprising analyzing handwriting collected from a user; associating at least one of the determined styles with the user; and training the handwriting recognition application using training samples selected from at least one of the determined writing styles associated with the user. | 10. The method of training a handwriting recognition application recited in claim 8 , further comprising analyzing handwriting collected from a user; associating at least one of the determined styles with the user; and training the handwriting recognition application using training samples selected from at least one of the determined writing styles associated with the user. 14. The method of training a handwriting recognition application recited in claim 10 , wherein the associated at least one of the determined styles is a handedness revealing style. | 0.90566 |
10,002,182 | 1 | 2 | 1. A method for computerized identification and presentation of semantic themes occurring in a set of electronic documents, the method comprising: generating one or more topics by performing topic modeling on the set of electronic documents; outputting, using the topic modeling, a plurality of ordered lists of words, individual ones of the plurality of ordered lists of words corresponding to individual ones of the one or more topics, the ordered lists of words being arranged from top to bottom corresponding to highest to lowest probability in relation to the one or more topics; determining a first unused theme name from a first list of the plurality of ordered lists of words, wherein the determining the first unused theme name is a first iterative process based on identifying a first unused word that is not on an already-used list starting from a top of the first list and moving toward a bottom of the first list; adding the first unused theme name to the already-used list; determining a second unused theme name from a second list of the plurality of ordered lists of words, wherein the determining the second unused theme name is a second iterative process based on identifying a second unused word that is not on the already-used list starting from a top of the second list and moving toward a bottom of the second list; adding the second unused theme name to the already-used list; removing, for the individual ones of the plurality of ordered lists of words, one or more words at a bottom of an ordered list of words thereby providing a plurality of ordered lists of top keywords corresponding to individual ones of the one or more topics, wherein individual ones of the plurality of ordered lists of top keywords have up to a predetermined number of top keywords; and applying a matching algorithm to the plurality of ordered lists of top keywords to produce a plurality of reduced lists of keywords, individual ones of the plurality of reduced lists of keywords (i) including a subset of keywords of the individual ones of the plurality of ordered lists of top keywords and (ii) corresponding to the individual ones of the plurality of ordered lists of top keywords, such that a keyword from the plurality of ordered lists of top keywords appears in no more than a predetermined number of reduced lists of keywords of the plurality of reduced lists of keywords. | 1. A method for computerized identification and presentation of semantic themes occurring in a set of electronic documents, the method comprising: generating one or more topics by performing topic modeling on the set of electronic documents; outputting, using the topic modeling, a plurality of ordered lists of words, individual ones of the plurality of ordered lists of words corresponding to individual ones of the one or more topics, the ordered lists of words being arranged from top to bottom corresponding to highest to lowest probability in relation to the one or more topics; determining a first unused theme name from a first list of the plurality of ordered lists of words, wherein the determining the first unused theme name is a first iterative process based on identifying a first unused word that is not on an already-used list starting from a top of the first list and moving toward a bottom of the first list; adding the first unused theme name to the already-used list; determining a second unused theme name from a second list of the plurality of ordered lists of words, wherein the determining the second unused theme name is a second iterative process based on identifying a second unused word that is not on the already-used list starting from a top of the second list and moving toward a bottom of the second list; adding the second unused theme name to the already-used list; removing, for the individual ones of the plurality of ordered lists of words, one or more words at a bottom of an ordered list of words thereby providing a plurality of ordered lists of top keywords corresponding to individual ones of the one or more topics, wherein individual ones of the plurality of ordered lists of top keywords have up to a predetermined number of top keywords; and applying a matching algorithm to the plurality of ordered lists of top keywords to produce a plurality of reduced lists of keywords, individual ones of the plurality of reduced lists of keywords (i) including a subset of keywords of the individual ones of the plurality of ordered lists of top keywords and (ii) corresponding to the individual ones of the plurality of ordered lists of top keywords, such that a keyword from the plurality of ordered lists of top keywords appears in no more than a predetermined number of reduced lists of keywords of the plurality of reduced lists of keywords. 2. The method according to claim 1 wherein matching algorithm comprises a hospital-residents matching algorithm and the individual ones of the plurality of ordered lists of top keywords are used to indicate topic preferences for keywords. | 0.740741 |
8,826,430 | 11 | 12 | 11. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for tracing information leaks, the method comprising: obtaining a disseminated document to analyze; determining, from a collection of original documents, an original document that is most similar to the disseminated document; comparing the disseminated document to the most similar original document to determine differences between the disseminated document and the most similar original document; querying a database containing changes to documents, using the determined differences, to determine a most similar changed document; determining a distance value by comparing changes from the most similar changed document with the determined differences from the disseminated document; and responsive to determining that the distance value is less than a threshold value, determining a user identifier for a user associated with the most similar changed document. | 11. A non-transitory computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for tracing information leaks, the method comprising: obtaining a disseminated document to analyze; determining, from a collection of original documents, an original document that is most similar to the disseminated document; comparing the disseminated document to the most similar original document to determine differences between the disseminated document and the most similar original document; querying a database containing changes to documents, using the determined differences, to determine a most similar changed document; determining a distance value by comparing changes from the most similar changed document with the determined differences from the disseminated document; and responsive to determining that the distance value is less than a threshold value, determining a user identifier for a user associated with the most similar changed document. 12. The non-transitory computer-readable storage medium of claim 11 , wherein the method further comprises: searching among change records for changes that are most similar to a determined difference between a second most similar original document and a second disseminated document; and determining a second user identifier associated with the changes that are most similar to the determined difference. | 0.669394 |
8,396,856 | 21 | 39 | 21. A system for building, managing, and sharing a searchable personalized database, the system comprising at least one processor and one or more modules for: enabling users with personal computers having a local storage system and access to the Internet to create selectively shareable personalized databases of a plurality of selected source files, including files originating from the user's local storage system, files located in access-restricted databases, accessed through the Internet, to which the users have obtained personalized access permission, and selectively shareable files the users create; enabling users to annotate files in the their personalized databases and incorporating those annotations into the personalized databases; generating one or more word level inverted indices of the personalized databases to support text searching of database source files and in-context highlighting of search terms during display of database source files; enabling users to register selected ones of a plurality of selectively shareable personalized databases; enabling users to unregister selected ones of a plurality of selectively shareable personalized databases; selectively searching registered ones of the plurality of personalized databases, using the one or more indices, according to a search criterion, to locate words and phrases in the source files of the registered databases; and sending information for the display of at least portions of files in the plurality of selected source files that meet the search criterion with in-context highlighting of search terms consistent with the search criterion. | 21. A system for building, managing, and sharing a searchable personalized database, the system comprising at least one processor and one or more modules for: enabling users with personal computers having a local storage system and access to the Internet to create selectively shareable personalized databases of a plurality of selected source files, including files originating from the user's local storage system, files located in access-restricted databases, accessed through the Internet, to which the users have obtained personalized access permission, and selectively shareable files the users create; enabling users to annotate files in the their personalized databases and incorporating those annotations into the personalized databases; generating one or more word level inverted indices of the personalized databases to support text searching of database source files and in-context highlighting of search terms during display of database source files; enabling users to register selected ones of a plurality of selectively shareable personalized databases; enabling users to unregister selected ones of a plurality of selectively shareable personalized databases; selectively searching registered ones of the plurality of personalized databases, using the one or more indices, according to a search criterion, to locate words and phrases in the source files of the registered databases; and sending information for the display of at least portions of files in the plurality of selected source files that meet the search criterion with in-context highlighting of search terms consistent with the search criterion. 39. The system of claim 21 , wherein the one or more modules enable users to edit selected source files. | 0.777778 |
8,738,403 | 26 | 27 | 26. The apparatus of claim 24 , wherein the updating further comprises adding the generated text to a location, in the textual representation of the free-form narration, specified by the user. | 26. The apparatus of claim 24 , wherein the updating further comprises adding the generated text to a location, in the textual representation of the free-form narration, specified by the user. 27. The apparatus of claim 26 , wherein the updating further comprises adjusting the generated text in accordance with the location specified by the user. | 0.947043 |
8,676,583 | 2 | 4 | 2. The method of claim 1 , wherein the selected action comprises an action requiring additional feedback from the user. | 2. The method of claim 1 , wherein the selected action comprises an action requiring additional feedback from the user. 4. The method of claim 2 , wherein the selected action comprises a request for confirmation of all or part of the spoken utterance from the user. | 0.948654 |
8,812,966 | 13 | 15 | 13. The computer program product of claim 12 , wherein the port comprises a cardinality attribute, and the cardinality attribute is configured to constrain the number of component products to be added by the first configurator. | 13. The computer program product of claim 12 , wherein the port comprises a cardinality attribute, and the cardinality attribute is configured to constrain the number of component products to be added by the first configurator. 15. The computer program product of claim 13 , wherein the cardinality attribute comprises a default cardinality, and the default cardinality defines a quantity of the component product class to be added by the first configurator. | 0.952907 |
8,055,669 | 1 | 13 | 1. A method of modifying a search query, performed by a server device, the method comprising: determining, by the server device, one or more alternative terms for one or more terms in the search query; obtaining, by the server device, search results based on the search query and based on an indexed corpus of documents, each search result identifying one or more documents in the indexed corpus of documents; defining, by the server device, a query context as a plurality of the documents identified by the search results; comparing, by the server device, the query context to the alternative terms to generate one or more valid ones of the alternative terms; and incorporating, by the server device, one or more of the valid ones of the alternative terms into the search query to obtain a modified search query. | 1. A method of modifying a search query, performed by a server device, the method comprising: determining, by the server device, one or more alternative terms for one or more terms in the search query; obtaining, by the server device, search results based on the search query and based on an indexed corpus of documents, each search result identifying one or more documents in the indexed corpus of documents; defining, by the server device, a query context as a plurality of the documents identified by the search results; comparing, by the server device, the query context to the alternative terms to generate one or more valid ones of the alternative terms; and incorporating, by the server device, one or more of the valid ones of the alternative terms into the search query to obtain a modified search query. 13. The method of claim 1 , where the query context includes information relating to phrases and/or pairs of words that occur within predetermined distances of one another in the plurality of documents. | 0.760664 |
8,274,520 | 25 | 26 | 25. A non-transitory computer-readable storage medium containing instructions that when executed by a computer cause the computer to perform a method for performing caching in an image-processing system, the method comprising: receiving a filtering query for resources in a cache; returning a subcache in response to the filtering query, wherein the subcache is a new subcache descending from the cache in tree of caches to which the cache and the subcache belong, and wherein returning the subcache comprises adding the new subcache to the tree of caches; and upon receiving a resource query for resources in the subcache, performing the filtering query on the cache, populating the subcache with addresses of resources returned by the filtering query until the resource query is satisfied, and returning available resources from the subcache in response to the resource query. | 25. A non-transitory computer-readable storage medium containing instructions that when executed by a computer cause the computer to perform a method for performing caching in an image-processing system, the method comprising: receiving a filtering query for resources in a cache; returning a subcache in response to the filtering query, wherein the subcache is a new subcache descending from the cache in tree of caches to which the cache and the subcache belong, and wherein returning the subcache comprises adding the new subcache to the tree of caches; and upon receiving a resource query for resources in the subcache, performing the filtering query on the cache, populating the subcache with addresses of resources returned by the filtering query until the resource query is satisfied, and returning available resources from the subcache in response to the resource query. 26. The computer-readable storage medium of claim 25 , wherein the method further comprises: receiving a second filtering query for resources in the subcache; returning a second subcache in response to the second filtering query; and upon receiving a second resource query for resources from the second subcache, performing the second filtering query on the subcache, populating the second subcache with resources returned from the second filtering query until the resource query is satisfied, and returning available resources from the second subcache in response to the second resource query. | 0.50084 |
8,307,372 | 1 | 19 | 1. A method for constructing a processing request so that an information processing application satisfying the processing request can be assembled, comprising: inputting a processing request, wherein the processing request includes a goal that is represented by a graph pattern that semantically describes a desired processing outcome, and assembling a processing graph that includes at least one component that satisfies the desired processing outcome, wherein the processing graph is assembled by associating the graph pattern that semantically describes the desired processing outcome with a graph pattern that semantically describes an applicability condition of the at least one component, wherein the association between the graph pattern that semantically describes the desired processing outcome and the graph pattern that semantically describes an applicability condition of the at least one component is based on a determination, which is performed during the assembly of the processing graph, that the at least one component is permitted to receive data produced by part of the processing graph as input, wherein the processing request further includes a constraint that is represented by a graph pattern that semantically describes constraints on the components to be used in the assembly of the processing graph and the determination that the at least one component is permitted to receive data produced by part of the processing graph as input is made in response to the applicability condition of the at least one component satisfying the constraints, and wherein the method is performed using a processor; wherein the method further comprises: deploying an information processing application embodying the at least one component of the processing graph; and operating the information processing application; wherein result data is produced when operating the information processing application; wherein when the goal is a goal that requests the production of data, the result data includes an element that is a requested data item. | 1. A method for constructing a processing request so that an information processing application satisfying the processing request can be assembled, comprising: inputting a processing request, wherein the processing request includes a goal that is represented by a graph pattern that semantically describes a desired processing outcome, and assembling a processing graph that includes at least one component that satisfies the desired processing outcome, wherein the processing graph is assembled by associating the graph pattern that semantically describes the desired processing outcome with a graph pattern that semantically describes an applicability condition of the at least one component, wherein the association between the graph pattern that semantically describes the desired processing outcome and the graph pattern that semantically describes an applicability condition of the at least one component is based on a determination, which is performed during the assembly of the processing graph, that the at least one component is permitted to receive data produced by part of the processing graph as input, wherein the processing request further includes a constraint that is represented by a graph pattern that semantically describes constraints on the components to be used in the assembly of the processing graph and the determination that the at least one component is permitted to receive data produced by part of the processing graph as input is made in response to the applicability condition of the at least one component satisfying the constraints, and wherein the method is performed using a processor; wherein the method further comprises: deploying an information processing application embodying the at least one component of the processing graph; and operating the information processing application; wherein result data is produced when operating the information processing application; wherein when the goal is a goal that requests the production of data, the result data includes an element that is a requested data item. 19. The method of claim 1 , wherein the applicability condition of the component is a semantic description of criteria that must be satisfied in order to include the component into the processing graph. | 0.751843 |
8,676,582 | 15 | 17 | 15. A speech recognition method, comprising: converting a speech into an electric signal and inputting the converted speech as an input speech into a speech input device; extracting words related to the input speech from a user dictionary for speech recognition included in the speech input device to create a reduced user dictionary; transmitting the input speech and the reduced user dictionary from the speech input device to a speech recognition device; receiving at the speech recognition device the input speech and the reduced user dictionary; and at the speech recognition device, performing speech recognition on the input speech based on a system dictionary for speech recognition included in the speech recognition device and the received reduced user dictionary, wherein the extracting includes: comparing the input speech and a word in the user dictionary and compiling a likelihood of each word appearing in the input speech, temporarily storing a set of each word and a corresponding likelihood compiled, and selecting one or a plurality of words having high usage to thereby create the reduced user dictionary. | 15. A speech recognition method, comprising: converting a speech into an electric signal and inputting the converted speech as an input speech into a speech input device; extracting words related to the input speech from a user dictionary for speech recognition included in the speech input device to create a reduced user dictionary; transmitting the input speech and the reduced user dictionary from the speech input device to a speech recognition device; receiving at the speech recognition device the input speech and the reduced user dictionary; and at the speech recognition device, performing speech recognition on the input speech based on a system dictionary for speech recognition included in the speech recognition device and the received reduced user dictionary, wherein the extracting includes: comparing the input speech and a word in the user dictionary and compiling a likelihood of each word appearing in the input speech, temporarily storing a set of each word and a corresponding likelihood compiled, and selecting one or a plurality of words having high usage to thereby create the reduced user dictionary. 17. The speech recognition method as claimed in claim 15 , wherein the reduced user dictionary is created from the user dictionary by word spotting. | 0.92695 |
10,057,317 | 9 | 14 | 9. In controlling video data transmitted from a source device, a sink device comprising: an interface unit configured to communicate with the source device by Wi-Fi Direct; a receiving unit configured to receive a voice signal from a remote controller that is wirelessly connected to the sink device; a display unit; and a controller configured to: output the video data received from the source device through the network interface unit to the display unit, recognize a text from a screen corresponding to the video data outputted to the display unit, save the recognized text to a memory to correspond to location information on the screen corresponding to the video data, convert the voice signal received through the voice signal receiving unit into a text using a speech-to-text (STT) function at the sink device, and if a specific text including at least one portion of the converted text exists in the recognized text, send a message corresponding to a user input of selecting the specific text from the screen corresponding to the video data to the source device through the network interface unit via a user input back channel (UIBC), wherein the UIBC is not configured to transmit the voice signal. | 9. In controlling video data transmitted from a source device, a sink device comprising: an interface unit configured to communicate with the source device by Wi-Fi Direct; a receiving unit configured to receive a voice signal from a remote controller that is wirelessly connected to the sink device; a display unit; and a controller configured to: output the video data received from the source device through the network interface unit to the display unit, recognize a text from a screen corresponding to the video data outputted to the display unit, save the recognized text to a memory to correspond to location information on the screen corresponding to the video data, convert the voice signal received through the voice signal receiving unit into a text using a speech-to-text (STT) function at the sink device, and if a specific text including at least one portion of the converted text exists in the recognized text, send a message corresponding to a user input of selecting the specific text from the screen corresponding to the video data to the source device through the network interface unit via a user input back channel (UIBC), wherein the UIBC is not configured to transmit the voice signal. 14. The sink device of claim 9 , wherein if the converted text comprises a first text included in the recognized text and a second text corresponding to a count of a user input for selecting the first text, the controller is further configured to cause the network interface unit to send the message corresponding to the user input of selecting the first text from the screen corresponding to the video data to the source device a number of times corresponding to the second text. | 0.720605 |
5,495,604 | 19 | 21 | 19. The method of claim 12, wherein said step translating a text item from said edit window into said diagram further comprises the steps of: rotating said cursor 90.degree. each time said second selector of said cursor control device is actuated; and further responsive to said step of rotating said cursor, said step of drawing said objects, facts and constraints on said diagram, for drawing said text item on said diagram. | 19. The method of claim 12, wherein said step translating a text item from said edit window into said diagram further comprises the steps of: rotating said cursor 90.degree. each time said second selector of said cursor control device is actuated; and further responsive to said step of rotating said cursor, said step of drawing said objects, facts and constraints on said diagram, for drawing said text item on said diagram. 21. The method of claim 19, wherein said step of rotating said cursor rotates said cursor 90.degree. in a counterclockwise direction each time said second selector of said cursor control device is actuated. | 0.973058 |
7,676,517 | 1 | 6 | 1. A system embodied in a computer readable storage medium that, when executed by one or more processors, facilitates query processing, the system comprising the following computer executable components: a query component that facilitates input of a portion of query data into a client application during a query generation process, wherein the query generation process comprises automatic injection of additional query data into the client application; a search component that executes a query against an indexed network based service in real time to suggest the additional query data in response to receiving the portion of the query data and communicates the additional query data to the query component for presentation to a user; a trigger component that facilitates the inclusion of one or more additional data elements to affect the query generation process and facilitates one or more of impacting, refining, and filtering the additional query data; an adaptive component that adapts the query generation process to a skill level of the user, wherein the query generation process is more automated when the user is determined to be more skillful and the query generation process is less automated when the user is determined to be more novice; and a machine learning and reasoning component that employs a probabilistic or statistical-based analysis, or a combination thereof, to prognose or infer an action that a user desires to be automatically performed. | 1. A system embodied in a computer readable storage medium that, when executed by one or more processors, facilitates query processing, the system comprising the following computer executable components: a query component that facilitates input of a portion of query data into a client application during a query generation process, wherein the query generation process comprises automatic injection of additional query data into the client application; a search component that executes a query against an indexed network based service in real time to suggest the additional query data in response to receiving the portion of the query data and communicates the additional query data to the query component for presentation to a user; a trigger component that facilitates the inclusion of one or more additional data elements to affect the query generation process and facilitates one or more of impacting, refining, and filtering the additional query data; an adaptive component that adapts the query generation process to a skill level of the user, wherein the query generation process is more automated when the user is determined to be more skillful and the query generation process is less automated when the user is determined to be more novice; and a machine learning and reasoning component that employs a probabilistic or statistical-based analysis, or a combination thereof, to prognose or infer an action that a user desires to be automatically performed. 6. The system of claim 1 , the query data is a single character that is entered into an input box of the client application. | 0.756863 |
7,823,061 | 8 | 11 | 8. A computer readable medium containing computer code comprising a system for segmenting claims from a patent document, the system comprising: a display device; a segmentation engine configured to receive the claims from the patent document and to divide the claims to provide a plurality of segments, each of which consist of at least one substantive claim limitation, wherein said at least one substantive claim limitation recites a limitation to an invention; wherein the segmentation engine is further configured to segment the claims into at least one element phrase; wherein the segmentation engine is further configured to segment the at least one element phrase into at least one elemental phrase and at least one attribute phrase, wherein the at least one attribute phrase comprises the at least one substantive claim limitation; and a display engine configured to receive the segments and to carry out one of displaying and hiding each of the segments, according to at least one user-adjustable display setting; wherein the display engine is capable of displaying each of the segments independently of the other segments. | 8. A computer readable medium containing computer code comprising a system for segmenting claims from a patent document, the system comprising: a display device; a segmentation engine configured to receive the claims from the patent document and to divide the claims to provide a plurality of segments, each of which consist of at least one substantive claim limitation, wherein said at least one substantive claim limitation recites a limitation to an invention; wherein the segmentation engine is further configured to segment the claims into at least one element phrase; wherein the segmentation engine is further configured to segment the at least one element phrase into at least one elemental phrase and at least one attribute phrase, wherein the at least one attribute phrase comprises the at least one substantive claim limitation; and a display engine configured to receive the segments and to carry out one of displaying and hiding each of the segments, according to at least one user-adjustable display setting; wherein the display engine is capable of displaying each of the segments independently of the other segments. 11. The computer readable medium of claim 8 , wherein the display engine is further configured to display a symbolic representation in place of at least one of the segments of the plurality of segments. | 0.869001 |
8,229,976 | 3 | 4 | 3. The method of claim 1 further comprising: receiving a user interface descriptor; and using said user interface descriptor to generate at least a portion of said user interface. | 3. The method of claim 1 further comprising: receiving a user interface descriptor; and using said user interface descriptor to generate at least a portion of said user interface. 4. The method of claim 3 , said user interface descriptor comprising HTML. | 0.967199 |
8,260,774 | 1 | 2 | 1. A method comprising: receiving at least one search criteria from a first source; identifying multiple portions of indexed content, each respective portion of indexed content related to at least one characteristic of the search criteria, each respective portion of indexed content referencing metadata; determining a relevance of each respective portion of indexed content to the first source who provided the search criteria, the relevance based on user feedback associated with an online version of the portion of indexed content; ranking the multiple portions of indexed content according to their respective relevance to the first source who provided the search criteria; and creating a search result based on ranking the multiple portions of indexed content. | 1. A method comprising: receiving at least one search criteria from a first source; identifying multiple portions of indexed content, each respective portion of indexed content related to at least one characteristic of the search criteria, each respective portion of indexed content referencing metadata; determining a relevance of each respective portion of indexed content to the first source who provided the search criteria, the relevance based on user feedback associated with an online version of the portion of indexed content; ranking the multiple portions of indexed content according to their respective relevance to the first source who provided the search criteria; and creating a search result based on ranking the multiple portions of indexed content. 2. The method as in claim 1 , wherein identifying multiple portions of indexed content includes: identifying at least one search constraint; and identifying at least one portion of indexed local content that satisfies the search constraint. | 0.913669 |
8,943,042 | 8 | 12 | 8. A computer program product tangibly embodied in a non-transitory computer-readable storage medium and comprising instructions that when executed by a processor perform a method for analyzing and representing interpersonal relations, the method comprising: receiving, by a computer server system and as having been sent from a client device, a request for information that specifies relationships of a first person, wherein the request includes: (i) information that identifies the first person, and (ii) information that indicates a user-specified number of relationship separations extending from the first person from which other persons are to be identified; automatically creating, by the computer server system and in response to receiving the request, a single database query that: (i) when executed, causes a database system to identify a particular group of persons in a relational database that are related to the first person due to the particular group of persons being within the user-specified number of relationship separations from the first person, and (ii) is structured to cause the database system to identify the particular group of persons by: (a) identifying a first group of persons in the relational database to include in the particular group of persons, the identifying of the first group of persons including an identification of persons who are directly related, through a single relationship type from among multiple relationship types, to the first person, and (b) identifying additional persons in the relational database to add to the particular group of persons by performing, for each relationship separation in the user-specified number of relationship separations that extend from the identified first group of persons, a database left join operation that joins a respective additional group of persons in the relational database who are directly related, through the single relationship type, to any person in a previously joined group of persons until the number of relationship separations extending from the first person, through the single relationship type, is determined to satisfy the user-specified number of relationship separations indicated in the request, wherein performing a first of the database left join operations comprises identifying a first additional group of multiple persons to add to the particular group of persons, wherein the first additional group of multiple persons are identified for addition to the particular group of persons based on the first additional group of multiple persons being directly related to the persons in the first group of persons and also being indirectly related to the first person; providing, by the computer server system and to the database system in response to receiving the request, the single database query for execution by the database system, and in response, receiving results obtained by the database system from execution of the single database query, wherein the results specify the particular group of persons, wherein the database system is configured to execute the single database query in-memory; generating, by the computer server system and based on the results obtained by the database system, the information that specifies the relationships of the first person; and providing, by the computer server system and to the client device in response to receiving the request, the information that specifies the relationships of the first person for display. | 8. A computer program product tangibly embodied in a non-transitory computer-readable storage medium and comprising instructions that when executed by a processor perform a method for analyzing and representing interpersonal relations, the method comprising: receiving, by a computer server system and as having been sent from a client device, a request for information that specifies relationships of a first person, wherein the request includes: (i) information that identifies the first person, and (ii) information that indicates a user-specified number of relationship separations extending from the first person from which other persons are to be identified; automatically creating, by the computer server system and in response to receiving the request, a single database query that: (i) when executed, causes a database system to identify a particular group of persons in a relational database that are related to the first person due to the particular group of persons being within the user-specified number of relationship separations from the first person, and (ii) is structured to cause the database system to identify the particular group of persons by: (a) identifying a first group of persons in the relational database to include in the particular group of persons, the identifying of the first group of persons including an identification of persons who are directly related, through a single relationship type from among multiple relationship types, to the first person, and (b) identifying additional persons in the relational database to add to the particular group of persons by performing, for each relationship separation in the user-specified number of relationship separations that extend from the identified first group of persons, a database left join operation that joins a respective additional group of persons in the relational database who are directly related, through the single relationship type, to any person in a previously joined group of persons until the number of relationship separations extending from the first person, through the single relationship type, is determined to satisfy the user-specified number of relationship separations indicated in the request, wherein performing a first of the database left join operations comprises identifying a first additional group of multiple persons to add to the particular group of persons, wherein the first additional group of multiple persons are identified for addition to the particular group of persons based on the first additional group of multiple persons being directly related to the persons in the first group of persons and also being indirectly related to the first person; providing, by the computer server system and to the database system in response to receiving the request, the single database query for execution by the database system, and in response, receiving results obtained by the database system from execution of the single database query, wherein the results specify the particular group of persons, wherein the database system is configured to execute the single database query in-memory; generating, by the computer server system and based on the results obtained by the database system, the information that specifies the relationships of the first person; and providing, by the computer server system and to the client device in response to receiving the request, the information that specifies the relationships of the first person for display. 12. The computer program product of claim 8 , wherein the request further includes information that specifies the single relationship type. | 0.910783 |
8,209,660 | 7 | 8 | 7. The method of claim 1 , further comprising using the knowledge repository to examine proper technology mapping in response to the changes. | 7. The method of claim 1 , further comprising using the knowledge repository to examine proper technology mapping in response to the changes. 8. The method of claim 7 , further comprising changing the impacted items based on the changes identified. | 0.986623 |
8,805,756 | 3 | 6 | 3. The method as set forth in claim 1 wherein the automatically performing a crowd sourcing operation comprises performing a historical analysis of similar questions, clues or combination of questions and clues to determine potentially missing information from the received question or received clue, and performing an action to collect the missing information, and wherein the supplying a crowd-sourced enhancement to the deep question-answer computing system comprises including the collected missing information with the a crowd-sourced enhancement. | 3. The method as set forth in claim 1 wherein the automatically performing a crowd sourcing operation comprises performing a historical analysis of similar questions, clues or combination of questions and clues to determine potentially missing information from the received question or received clue, and performing an action to collect the missing information, and wherein the supplying a crowd-sourced enhancement to the deep question-answer computing system comprises including the collected missing information with the a crowd-sourced enhancement. 6. The method as set forth in claim 3 wherein the collection of missing information comprises querying one or more domain expert users via communications devices for the missing information, wherein the queried domain expert users are selected from a list of subject domain experts. | 0.910077 |
10,157,426 | 27 | 28 | 27. The method of claim 26 , the prioritization data comprising: ranking data, wherein each question or topic is assigned a ranking or score; and categorization data, wherein each question or topic is assigned a category from a plurality of categories. | 27. The method of claim 26 , the prioritization data comprising: ranking data, wherein each question or topic is assigned a ranking or score; and categorization data, wherein each question or topic is assigned a category from a plurality of categories. 28. The method of claim 27 , the first paginated screen being structured based at least in part upon ranking data taking priority over categorization data. | 0.980883 |
9,342,504 | 1 | 5 | 1. A voice-interactive dialog system for facilitating conversational speech across different domains, comprising: a phrase database storing (i) phrases grouped into equivalence classes and (ii) a probability of occurrence for each phrase within a corpus; wherein each equivalence class is associated with one or more domains; a user interface configured to allow interaction with an interactive part of the system; a recognition server coupled with the phrase database and the user interface and configured to: identify a user request upon receiving a user utterance via the user interface, wherein the user request is associated with a domain; formulate a system prompt in response to the user utterance, the prompt comprising a combination of one or more phrases from the phrase database that are associated with the domain; upon receiving a user response to the system prompt via the user interface, generate a recognition grammar from phrases in the phrase database that fall within an equivalent class associated with the user response; and generate a recommendation to the user via the user interface, wherein the recommendation is associated with the domain. | 1. A voice-interactive dialog system for facilitating conversational speech across different domains, comprising: a phrase database storing (i) phrases grouped into equivalence classes and (ii) a probability of occurrence for each phrase within a corpus; wherein each equivalence class is associated with one or more domains; a user interface configured to allow interaction with an interactive part of the system; a recognition server coupled with the phrase database and the user interface and configured to: identify a user request upon receiving a user utterance via the user interface, wherein the user request is associated with a domain; formulate a system prompt in response to the user utterance, the prompt comprising a combination of one or more phrases from the phrase database that are associated with the domain; upon receiving a user response to the system prompt via the user interface, generate a recognition grammar from phrases in the phrase database that fall within an equivalent class associated with the user response; and generate a recommendation to the user via the user interface, wherein the recommendation is associated with the domain. 5. The system of claim 1 , wherein the recognition grammar is representative of anticipated user responses. | 0.50463 |
8,412,524 | 11 | 17 | 11. An apparatus for use with a document tangibly stored in a first computer-readable medium, the apparatus comprising: means for accessing the first computer-readable medium to identify a first phrase within the document, the first phrase representing a first written form of a concept; means for identifying a plurality of phrases tangibly stored in a second computer-readable medium, each of the plurality of phrases representing an alternative written form of the concept; means for displaying at least some of the plurality of phrases to a user; and means for receiving an instruction to replace the first phrase with one of the plurality of phrases in the document on the first computer-readable medium, wherein the instruction does not include the one of the plurality of phrases. | 11. An apparatus for use with a document tangibly stored in a first computer-readable medium, the apparatus comprising: means for accessing the first computer-readable medium to identify a first phrase within the document, the first phrase representing a first written form of a concept; means for identifying a plurality of phrases tangibly stored in a second computer-readable medium, each of the plurality of phrases representing an alternative written form of the concept; means for displaying at least some of the plurality of phrases to a user; and means for receiving an instruction to replace the first phrase with one of the plurality of phrases in the document on the first computer-readable medium, wherein the instruction does not include the one of the plurality of phrases. 17. The apparatus of claim 11 , further comprising means for displaying multiple ones of the plurality of phrases to the user. | 0.776596 |
8,719,696 | 7 | 8 | 7. The system of claim 1 , wherein said implicit linguistic content includes one or more of a meaning and a grammatical type of said words. | 7. The system of claim 1 , wherein said implicit linguistic content includes one or more of a meaning and a grammatical type of said words. 8. The system of claim 7 , wherein the grammatical type includes a noun or a verb. | 0.976163 |
8,880,520 | 1 | 4 | 1. A network device comprising: a transceiver to send and receive data over the network; and a processor configured to execute computer instructions, the instructions comprising the steps of: receiving a search query from a search user; classifying the search query into at least one query-class from a plurality of query-classes; performing a search using the search query over a plurality of non-trust data sources to obtain a plurality of non-trust search results; selectively performing another search using the search query over a plurality of identified trust data sources to obtain a plurality of trust search results, wherein the identified trust data sources include explicit trusted data sources that are trusted specifically by the search user and wherein the non-trust data sources are non-trusted specifically by the search user; categorizing the plurality of trust search results based on the search user's respective relationship with each identified trust data source, the search user's respective relationship being one from a group of relationships comprising an explicit trust data source relationship, an implicit trust data source relationship, and another trust data source relationship having a correspondence with a social networking source for which the search user is not a member; determining, based on the at least one query-class for the search query and the trust search results categorization, a number and a position for selectively displaying each of the plurality of trust search results in a rank order; and selectively displaying the plurality of trust search results distinct from a display of the plurality of non-trust search results, wherein the selectively displayed plurality of trust search results is in accordance with the determination and includes display of information indicating an identified trust data source of each of the plurality of trust search results. | 1. A network device comprising: a transceiver to send and receive data over the network; and a processor configured to execute computer instructions, the instructions comprising the steps of: receiving a search query from a search user; classifying the search query into at least one query-class from a plurality of query-classes; performing a search using the search query over a plurality of non-trust data sources to obtain a plurality of non-trust search results; selectively performing another search using the search query over a plurality of identified trust data sources to obtain a plurality of trust search results, wherein the identified trust data sources include explicit trusted data sources that are trusted specifically by the search user and wherein the non-trust data sources are non-trusted specifically by the search user; categorizing the plurality of trust search results based on the search user's respective relationship with each identified trust data source, the search user's respective relationship being one from a group of relationships comprising an explicit trust data source relationship, an implicit trust data source relationship, and another trust data source relationship having a correspondence with a social networking source for which the search user is not a member; determining, based on the at least one query-class for the search query and the trust search results categorization, a number and a position for selectively displaying each of the plurality of trust search results in a rank order; and selectively displaying the plurality of trust search results distinct from a display of the plurality of non-trust search results, wherein the selectively displayed plurality of trust search results is in accordance with the determination and includes display of information indicating an identified trust data source of each of the plurality of trust search results. 4. The network device of claim 1 , wherein each query-class has a number and position for selectively displaying the plurality of trust search results, and where in the number and position for each query-class is determined by: tracking a plurality of clickthrough rates from a plurality of search query users over a plurality of trust results; aggregating tracked clickthrough rates over each of the plurality of query-classes; and determining an optimal number and position for each of the plurality of query-classes using search query users' feedback that indicates a number and position for which a most frequent number of selections are made as indicated in part by the aggregated tracked clickthrough rates. | 0.683111 |
9,472,209 | 12 | 14 | 12. A computer program product for deep tagging a recording, the computer program product comprising: one or more computer-readable storage media; and program instructions stored on at least one of the one or more computer-readable storage media, the program instructions comprising: program instructions to filter, from recorded audio of a communication between a plurality of participants, wherein the recorded audio comprises speech from one or more of the plurality of participants, a non-speech sound that was transmitted to the plurality of participants; program instructions to automatically determine that the non-speech sound corresponds to a type of sound, and in response, to automatically associate a descriptive term with a time of occurrence of the non-speech sound within the recorded audio to form a searchable tag, wherein the descriptive term includes a phonetic translation of the non-speech sound; and program instructions to store the searchable tag as metadata of the recorded audio. | 12. A computer program product for deep tagging a recording, the computer program product comprising: one or more computer-readable storage media; and program instructions stored on at least one of the one or more computer-readable storage media, the program instructions comprising: program instructions to filter, from recorded audio of a communication between a plurality of participants, wherein the recorded audio comprises speech from one or more of the plurality of participants, a non-speech sound that was transmitted to the plurality of participants; program instructions to automatically determine that the non-speech sound corresponds to a type of sound, and in response, to automatically associate a descriptive term with a time of occurrence of the non-speech sound within the recorded audio to form a searchable tag, wherein the descriptive term includes a phonetic translation of the non-speech sound; and program instructions to store the searchable tag as metadata of the recorded audio. 14. The computer program product of claim 12 , further comprising program instructions to receive an input from one or more of the plurality of participants to assist in tagging the non-speech sound. | 0.776404 |
8,364,670 | 1 | 22 | 1. A method for electronically searching for an item, the method comprising the steps of: providing a search index comprising a set of predefined categories, wherein each predefined category is defined by a taxonomy of attributes comprising a set of predefined attributes, wherein each predefined attribute is defined by at least one question and one or more answers to each question; receiving a search request for the item from a user, wherein the search request comprises a requested category for the item selected from the set of predefined item categories, and one or more requested attributes of the item selected from the set of predefined attributes by providing at least one of the answers to at least one of the questions defining the requested attribute of the item; storing the search request for the item in the search index based on the requested category for the item and the requested attribute(s) of the item; searching the search index for any previously stored search requests from other users that match the requested category and the requested attribute(s); determining a result of the search; sending a search response comprising the result of the search; persistently searching the search index for the item by monitoring the search index for a trigger event until the search request is terminated; whenever the trigger event is detected, searching the search index for any stored search results that match the requested category and the requested attributes, and determining a new result of the search; whenever the new result differs from the result, sending an updated search response comprising the new result of the search; determining a relevancy score for each found stored search request; wherein the step of determining the relevancy score for each found stored result comprises the step of summing the relevancy scores for each requested attribute in the search request divided by the number of requested attributes in the search request; and wherein the relevancy score for each requested attribute comprises a first value whenever the requested attribute is not specified in the stored search request, a second value whenever the requested attribute matches the attribute of the stored search request and the requested attribute is Must Have, a third value whenever the requested attribute that matches the attribute of the stored search request and the requested attribute is not Must Have, a fourth value whenever the requested attribute that does not match the attribute of the stored search request and the requested attribute is Must Have, and a fifth value whenever the requested attribute does not match the attribute of the stored search request and the requested attribute is not Must Have. | 1. A method for electronically searching for an item, the method comprising the steps of: providing a search index comprising a set of predefined categories, wherein each predefined category is defined by a taxonomy of attributes comprising a set of predefined attributes, wherein each predefined attribute is defined by at least one question and one or more answers to each question; receiving a search request for the item from a user, wherein the search request comprises a requested category for the item selected from the set of predefined item categories, and one or more requested attributes of the item selected from the set of predefined attributes by providing at least one of the answers to at least one of the questions defining the requested attribute of the item; storing the search request for the item in the search index based on the requested category for the item and the requested attribute(s) of the item; searching the search index for any previously stored search requests from other users that match the requested category and the requested attribute(s); determining a result of the search; sending a search response comprising the result of the search; persistently searching the search index for the item by monitoring the search index for a trigger event until the search request is terminated; whenever the trigger event is detected, searching the search index for any stored search results that match the requested category and the requested attributes, and determining a new result of the search; whenever the new result differs from the result, sending an updated search response comprising the new result of the search; determining a relevancy score for each found stored search request; wherein the step of determining the relevancy score for each found stored result comprises the step of summing the relevancy scores for each requested attribute in the search request divided by the number of requested attributes in the search request; and wherein the relevancy score for each requested attribute comprises a first value whenever the requested attribute is not specified in the stored search request, a second value whenever the requested attribute matches the attribute of the stored search request and the requested attribute is Must Have, a third value whenever the requested attribute that matches the attribute of the stored search request and the requested attribute is not Must Have, a fourth value whenever the requested attribute that does not match the attribute of the stored search request and the requested attribute is Must Have, and a fifth value whenever the requested attribute does not match the attribute of the stored search request and the requested attribute is not Must Have. 22. The method as recited in claim 1 , further comprising the step of updating the search index whenever a stored search request is added, changed or deleted. | 0.936699 |
9,703,394 | 8 | 11 | 8. A computing device comprising: one or more computer processors; an output component; a presence-sensitive input component; and a memory comprising instructions that when executed cause the one or more computer processors to: output, for display at the output component, a graphical user interface that includes a text edit region and a graphical keyboard; receive an indication of a first input detected at a first location of the presence-sensitive input component, wherein the first location of the presence-sensitive input component corresponds to a region of the output component at which the graphical keyboard is displayed; determine, based at least in part on the indication of the first input, a new character string that is not included in a language model of the computing device; add, to the language model, the new character string and a corresponding likelihood value associated with the new character string; receive an indication of a second input detected at a second location of the presence-sensitive input component, wherein the second location of the presence-sensitive input component corresponds to the region of the output component at which the graphical keyboard is displayed; predict, based on the indication of the second input and the likelihood value associated with the new character string, the new character string and an input context associated with the second input; responsive to predicting the new character string, output, for display within the text edit region, the new character string; receive an indication of a third input detected at a third location of the presence-sensitive input component, wherein the third location of the presence-sensitive input component corresponds to the region of the output component at which the graphical keyboard is displayed; and responsive to determining that the third input deletes the new character string from the text edit region after being output for display: remove, from the text input region, the new character string; and decrease, at a rate or magnitude that is adapted to the input context, the likelihood value associated with the new character string without removing the new character string from the language model. | 8. A computing device comprising: one or more computer processors; an output component; a presence-sensitive input component; and a memory comprising instructions that when executed cause the one or more computer processors to: output, for display at the output component, a graphical user interface that includes a text edit region and a graphical keyboard; receive an indication of a first input detected at a first location of the presence-sensitive input component, wherein the first location of the presence-sensitive input component corresponds to a region of the output component at which the graphical keyboard is displayed; determine, based at least in part on the indication of the first input, a new character string that is not included in a language model of the computing device; add, to the language model, the new character string and a corresponding likelihood value associated with the new character string; receive an indication of a second input detected at a second location of the presence-sensitive input component, wherein the second location of the presence-sensitive input component corresponds to the region of the output component at which the graphical keyboard is displayed; predict, based on the indication of the second input and the likelihood value associated with the new character string, the new character string and an input context associated with the second input; responsive to predicting the new character string, output, for display within the text edit region, the new character string; receive an indication of a third input detected at a third location of the presence-sensitive input component, wherein the third location of the presence-sensitive input component corresponds to the region of the output component at which the graphical keyboard is displayed; and responsive to determining that the third input deletes the new character string from the text edit region after being output for display: remove, from the text input region, the new character string; and decrease, at a rate or magnitude that is adapted to the input context, the likelihood value associated with the new character string without removing the new character string from the language model. 11. The computing device of claim 8 , wherein the input context comprises one or more previously inputted character strings that are outputted for display when predicting the new character string; and the memory comprises instructions that when executed by the one or more computer processors cause the one or more computer processors to decrease the likelihood value associated with the new character string for only the input context. | 0.875713 |
9,710,243 | 5 | 6 | 5. A computing device comprising: hardware for running computer programs; memory, for storing computer programs and data; a grammar of a first programming language represented in member fields and data types of object-oriented classes of a second programming language as an empty program semantic tree, the grammar being stored in the memory; and, a parser, run on the hardware, that builds a new program semantic tree that represents source code written in the first programming language, the new program semantic tree being built by a reflection technique in which the member fields and data types of the object-oriented classes of the second programming language as set out in the empty program semantic tree are modified during the building of the new program semantic tree, wherein the parser includes one or more of: a top level parsing routine to call token specific parsers, a parser to handle tokens in a token sequence, and/or a precedence chooser parser to parse programming syntax involving mathematical operators. | 5. A computing device comprising: hardware for running computer programs; memory, for storing computer programs and data; a grammar of a first programming language represented in member fields and data types of object-oriented classes of a second programming language as an empty program semantic tree, the grammar being stored in the memory; and, a parser, run on the hardware, that builds a new program semantic tree that represents source code written in the first programming language, the new program semantic tree being built by a reflection technique in which the member fields and data types of the object-oriented classes of the second programming language as set out in the empty program semantic tree are modified during the building of the new program semantic tree, wherein the parser includes one or more of: a top level parsing routine to call token specific parsers, a parser to handle tokens in a token sequence, and/or a precedence chooser parser to parse programming syntax involving mathematical operators. 6. A computing device as in claim 5 wherein the parsing program converts the source code into abstract tokens, the abstract tokens including: token sequences; token choosers; precedence tokens; unparsed tokens; token lists; and terminal tokens. | 0.573427 |
9,966,065 | 1 | 3 | 1. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the electronic device to: receive speech input from a user, wherein the speech input comprises a single utterance having one or more actionable commands; in direct response to receiving the speech input comprising the single utterance: generate a text string based on the speech input using a speech transcription process; parse the text string into at least a first candidate substring and a second candidate substring; determine a first probability that the first candidate substring corresponds to a first actionable command and a second probability that the second candidate sub string corresponds to a second actionable command; in response to the first probability and the second probability exceeding a threshold, determine a first intent associated with the first candidate substring and a second intent associated with the second candidate substring; execute a first process identified by the first intent and a second process identified by the second intent; and provide to the user an acknowledgment that the first process and the second process have at least begun execution. | 1. A non-transitory computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by one or more processors of an electronic device, cause the electronic device to: receive speech input from a user, wherein the speech input comprises a single utterance having one or more actionable commands; in direct response to receiving the speech input comprising the single utterance: generate a text string based on the speech input using a speech transcription process; parse the text string into at least a first candidate substring and a second candidate substring; determine a first probability that the first candidate substring corresponds to a first actionable command and a second probability that the second candidate sub string corresponds to a second actionable command; in response to the first probability and the second probability exceeding a threshold, determine a first intent associated with the first candidate substring and a second intent associated with the second candidate substring; execute a first process identified by the first intent and a second process identified by the second intent; and provide to the user an acknowledgment that the first process and the second process have at least begun execution. 3. The computer readable storage medium of claim 1 , wherein parsing the text string into at least the first candidate substring and the second candidate substring comprises: identifying a first imperative verb in the text string to determine the first candidate substring; and identifying a second imperative verb in the text string to determine the second candidate substring. | 0.750988 |
9,286,292 | 8 | 10 | 8. A computer program product for identifying and translating jargon, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer, the program instructions comprising: program instructions to retrieve a profile information of a first participant of a multi-party communication, wherein the profile information of the first participant i) includes demographic information related to the first participant, and ii) indicates a location of the first participant; program instructions to identify an original jargon submitted by a second participant included in the multi-party communication based, at least in part, on the profile information of the first participant; program instructions to predict whether the first participant will understand the original jargon based, at least in part, on the demographic information related to the first participant and the location of the first participant; program instructions to respond to a prediction that the first participant will not understand the original jargon by generating a translated jargon by translating the original jargon based, at least in part, on the profile information of the first participant, wherein the translated jargon can be understood by the first participant of the multi-party communication; and program instructions to send the translated jargon to the first participant of the multi-party communication. | 8. A computer program product for identifying and translating jargon, the computer program product comprising a computer readable storage medium having program instructions embodied therewith, the program instructions executable by a computer, the program instructions comprising: program instructions to retrieve a profile information of a first participant of a multi-party communication, wherein the profile information of the first participant i) includes demographic information related to the first participant, and ii) indicates a location of the first participant; program instructions to identify an original jargon submitted by a second participant included in the multi-party communication based, at least in part, on the profile information of the first participant; program instructions to predict whether the first participant will understand the original jargon based, at least in part, on the demographic information related to the first participant and the location of the first participant; program instructions to respond to a prediction that the first participant will not understand the original jargon by generating a translated jargon by translating the original jargon based, at least in part, on the profile information of the first participant, wherein the translated jargon can be understood by the first participant of the multi-party communication; and program instructions to send the translated jargon to the first participant of the multi-party communication. 10. The computer program product of claim 8 , the program instructions further comprising: program instructions to receive a request for translation of the original jargon from a third participant included in the multi-party communication; program instructions to translate the original jargon for which translation was requested based at least in part on a profile information of the third participant, wherein the profile information of the third participant includes a location of the third participant and a primary language used for communication by the third participant; and program instructions to send the original jargon and the translated jargon to the third participant of the multi-party communication that submitted the request for jargon translation. | 0.53125 |
9,448,992 | 9 | 14 | 9. A computer system comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the computer system to perform operations comprising: parse a document from an authoritative source to generate at least one heading-text pair, the text appearing under the heading in the document, assign a topic and a question category to the heading-text pair, store the heading-text pair in a data store keyed by the topic and the question category, determine that a query corresponds to the topic and the question category, generate snippet-based search results by searching an index of documents for documents responsive to the query; and provide the heading-text pair as a natural language search result for the query with the snippet-based search results. | 9. A computer system comprising: at least one processor; and memory storing instructions that, when executed by the at least one processor, cause the computer system to perform operations comprising: parse a document from an authoritative source to generate at least one heading-text pair, the text appearing under the heading in the document, assign a topic and a question category to the heading-text pair, store the heading-text pair in a data store keyed by the topic and the question category, determine that a query corresponds to the topic and the question category, generate snippet-based search results by searching an index of documents for documents responsive to the query; and provide the heading-text pair as a natural language search result for the query with the snippet-based search results. 14. The system of claim 9 , further comprising memory storing a plurality of intent templates and wherein the heading-text pair is generated when the heading conforms to one of the plurality of intent templates. | 0.896467 |
9,234,763 | 1 | 9 | 1. A host server for providing geographic information comprising: one or more computing devices associated with the host server, the one or more computing devices being configured to perform operations comprising: receiving a search query from a client device, the client device having been associated with user account; in response to the received search query, identifying a point of interest for display on a map; and obtaining a plurality of candidate waypoints from a database, each of the candidate waypoints having been identified by analyzing data associated with the user account; determining a score for each of the candidate waypoints using a scoring formula, wherein the scoring formula includes scoring components that are based at least in part on a first category defining the type of entity of each candidate waypoint being scored and a second category defining the type of entity of the point of interest, and wherein the scoring formula includes a distance scaling component, the distance scaling component comprising a weighted distance divided by a distance between the candidate waypoint being scored and the point of interest, the weighted distance providing a number based on the second category associated with the point of interest; and selecting, based on the determined scores, at least one of the candidate waypoints for presentation on the map displaying the point of interest. | 1. A host server for providing geographic information comprising: one or more computing devices associated with the host server, the one or more computing devices being configured to perform operations comprising: receiving a search query from a client device, the client device having been associated with user account; in response to the received search query, identifying a point of interest for display on a map; and obtaining a plurality of candidate waypoints from a database, each of the candidate waypoints having been identified by analyzing data associated with the user account; determining a score for each of the candidate waypoints using a scoring formula, wherein the scoring formula includes scoring components that are based at least in part on a first category defining the type of entity of each candidate waypoint being scored and a second category defining the type of entity of the point of interest, and wherein the scoring formula includes a distance scaling component, the distance scaling component comprising a weighted distance divided by a distance between the candidate waypoint being scored and the point of interest, the weighted distance providing a number based on the second category associated with the point of interest; and selecting, based on the determined scores, at least one of the candidate waypoints for presentation on the map displaying the point of interest. 9. The host server of claim 1 , wherein the scoring formula includes a suitability component, the suitability component providing a likelihood that directions between the candidate waypoint being scored and the point of interest are desired by a user. | 0.775893 |
8,291,014 | 1 | 7 | 1. A method, comprising: receiving, by a processor and from a first user, one or more comments related to a first document; identifying, by the processor, a second document that is not identical to the first document and includes at least a threshold amount of content from the first document; determining, by the processor, a document identifier associated with the second document; storing, by the processor, information that includes the one or more comments related to the first document and the document identifier associated with the second document, the stored information associating the one or more comments related to the first document and the document identifier associated with the second document; forming, by the processor and using the stored information, a web document that, when rendered, includes a first portion to present content associated with the second document and a second portion to present information associated with the one or more comments related to the first document, the first portion and the second portion being different; and enabling, by the processor, a second user to access the web document. | 1. A method, comprising: receiving, by a processor and from a first user, one or more comments related to a first document; identifying, by the processor, a second document that is not identical to the first document and includes at least a threshold amount of content from the first document; determining, by the processor, a document identifier associated with the second document; storing, by the processor, information that includes the one or more comments related to the first document and the document identifier associated with the second document, the stored information associating the one or more comments related to the first document and the document identifier associated with the second document; forming, by the processor and using the stored information, a web document that, when rendered, includes a first portion to present content associated with the second document and a second portion to present information associated with the one or more comments related to the first document, the first portion and the second portion being different; and enabling, by the processor, a second user to access the web document. 7. The method of claim 1 , further comprising: indexing the information, where enabling the second user to access the stored information includes: receiving a query from the second user, determining that at least one of the one or more comments or contents of the second document are relevant to the query, and providing the information as part of search results associated with the query. | 0.840443 |
8,024,193 | 54 | 55 | 54. The machine-readable medium of claim 47 wherein creating feature vectors comprises: constructing a matrix W from the instances; and decomposing the matrix W. | 54. The machine-readable medium of claim 47 wherein creating feature vectors comprises: constructing a matrix W from the instances; and decomposing the matrix W. 55. The machine-readable medium of claim 54 wherein the matrix W is an M×N matrix where M is the number of instances, N is the maximum number of segment samples corresponding to an instance, wherein constructing the matrix W comprises inputting the numbers of segment samples corresponding to the instances. | 0.926555 |
9,760,641 | 21 | 24 | 21. A computer program product encoded on one or more non-transitory computer storage media, the computer program product storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving a search query; obtaining a plurality of search results for the search query from a search engine, wherein each search result identifies a respective search result resource, and wherein the plurality of search results includes one or more search results that identify search result resources that are in a particular site; using a site quality score for the particular site to rank the plurality of search results; and determining the site quality score for the particular site, comprising: determining a numerator that is a function of a first count of textually unique queries submitted to the search engine that have been categorized as referring to the particular site, wherein each such textually unique query is counted once in the first count; determining a denominator that is a function of a second count of textually unique queries submitted to the search engine that have been associated with resources in the particular sites, wherein each such textually unique query is counted once in the second count; and determining the site quality score for the particular site as a ratio of the numerator and the denominator. | 21. A computer program product encoded on one or more non-transitory computer storage media, the computer program product storing instructions that when executed by the one or more computers cause the one or more computers to perform operations comprising: receiving a search query; obtaining a plurality of search results for the search query from a search engine, wherein each search result identifies a respective search result resource, and wherein the plurality of search results includes one or more search results that identify search result resources that are in a particular site; using a site quality score for the particular site to rank the plurality of search results; and determining the site quality score for the particular site, comprising: determining a numerator that is a function of a first count of textually unique queries submitted to the search engine that have been categorized as referring to the particular site, wherein each such textually unique query is counted once in the first count; determining a denominator that is a function of a second count of textually unique queries submitted to the search engine that have been associated with resources in the particular sites, wherein each such textually unique query is counted once in the second count; and determining the site quality score for the particular site as a ratio of the numerator and the denominator. 24. The computer program product of claim 21 , wherein two queries that have the same terms and differ only in the order of the terms are counted as the different unique queries. | 0.720126 |
Subsets and Splits