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7,890,324 | 1 | 2 | 1. In a multi-modal dialog system, a method of providing widgets to a user, comprising, after first user input received in a combination of a first mode and a second mode in a map-based application, and where further user input will clarify the first user input during a multi-modal dialog: maintaining a current display screen context by only presenting additional data on a display in response to the first user input until further user input is received via interaction with the additional data that clarifies the further user input; maintaining a current dialog context; presenting speech to the user requesting the further user input to clarify the first user input; and presenting the slider widget in a corner of the display screen to elicit the first user input as directed by the presented speech, wherein the further user input is received via the widget in a non-speech mode and provides distance range data that is shown on the display screen as the slider widget is adjusted by the further user input. | 1. In a multi-modal dialog system, a method of providing widgets to a user, comprising, after first user input received in a combination of a first mode and a second mode in a map-based application, and where further user input will clarify the first user input during a multi-modal dialog: maintaining a current display screen context by only presenting additional data on a display in response to the first user input until further user input is received via interaction with the additional data that clarifies the further user input; maintaining a current dialog context; presenting speech to the user requesting the further user input to clarify the first user input; and presenting the slider widget in a corner of the display screen to elicit the first user input as directed by the presented speech, wherein the further user input is received via the widget in a non-speech mode and provides distance range data that is shown on the display screen as the slider widget is adjusted by the further user input. 2. The method of claim 1 , wherein the user may manipulate the widget using a stylus, mouse, or touch. | 0.640845 |
9,910,833 | 1 | 16 | 1. A method performed on a computing device comprising an operating system, comprising: causing elements to be recognized that correspond to one or more browser-supported programming languages in an application by traversing a model of at least a portion of the application, wherein the recognized elements are those elements in the model that can be converted to native user interface elements in the operating system and rendered on a display of the computing device; converting the elements in the one or more browser-supported programming languages to native user interface elements; causing the native user interface elements to be rendered on the display of the computing device, wherein a native rendering process performs at least the converting the elements and causing the native user interface elements to be rendered and a web rendering process performs at least the causing the elements to be recognized, and performing both a web rendering of the application and a native rendering of the application in parallel by performing at least the following: the web rendering process, in response to a change in the model, calling the native renderer process to cause the native rendering process to render native user interface elements corresponding to recognized elements in a changed portion of the model; and the native rendering process, in response to an event occurring in the native rendering, injecting code corresponding to the event into the web rendering causing the web rendering process to be hidden from the display. | 1. A method performed on a computing device comprising an operating system, comprising: causing elements to be recognized that correspond to one or more browser-supported programming languages in an application by traversing a model of at least a portion of the application, wherein the recognized elements are those elements in the model that can be converted to native user interface elements in the operating system and rendered on a display of the computing device; converting the elements in the one or more browser-supported programming languages to native user interface elements; causing the native user interface elements to be rendered on the display of the computing device, wherein a native rendering process performs at least the converting the elements and causing the native user interface elements to be rendered and a web rendering process performs at least the causing the elements to be recognized, and performing both a web rendering of the application and a native rendering of the application in parallel by performing at least the following: the web rendering process, in response to a change in the model, calling the native renderer process to cause the native rendering process to render native user interface elements corresponding to recognized elements in a changed portion of the model; and the native rendering process, in response to an event occurring in the native rendering, injecting code corresponding to the event into the web rendering causing the web rendering process to be hidden from the display. 16. The method of claim 1 , wherein performing a web rendering of the application and a native rendering of the application in parallel further comprises: the web rendering process handling the injected code and, for an event that modifies the model, notifying the native rendering process by using a callback. | 0.779516 |
9,177,066 | 1 | 3 | 1. A method of displaying comments associated with a query, the method comprising: receiving the query provided by a user, the query identifying an entity; retrieving a set of comment clusters from a comment cluster database, wherein each comment cluster of the set of comment clusters comprises a plurality of comments associated with the entity identified in the query; selecting engaging comments from each comment cluster in the set of comment clusters, wherein the engaging comments are identified based on the comment having a high number of interactions with the comment by other users relative to other comments in the plurality of comments; aggregating the engaging comments that are selected from each comment cluster with each other to form a list of aggregated comments; classifying each engaging comments in the list of aggregated comments as related to a plurality of independent topics associated with the query, wherein each independent topic in the plurality of independent topics is related to a distinct topic subject matter associated with the entity identified in the query; identifying a first set of independent comments related to a first distinct topic subject matter associated with the entity identified in the query and a second set of independent comments related to a second distinct topic subject matter associated with the entity identified in the query; determining a first relevance of the first distinct topic subject matter to the query; determining a second relevance of the second distinct topic subject matter to the query, determining a first predefined number of independent comments based on the first relevance; determining a second predefined number of independent comments based on the second relevance; and displaying the first predefined number of independent comments from the first set of independent comments related to the first distinct topic subject matter associated with the entity identified in the query and displaying the second predefined number of independent comments from the second set of independent comments related to the second distinct topic subject matter associated with the entity identified in the query. | 1. A method of displaying comments associated with a query, the method comprising: receiving the query provided by a user, the query identifying an entity; retrieving a set of comment clusters from a comment cluster database, wherein each comment cluster of the set of comment clusters comprises a plurality of comments associated with the entity identified in the query; selecting engaging comments from each comment cluster in the set of comment clusters, wherein the engaging comments are identified based on the comment having a high number of interactions with the comment by other users relative to other comments in the plurality of comments; aggregating the engaging comments that are selected from each comment cluster with each other to form a list of aggregated comments; classifying each engaging comments in the list of aggregated comments as related to a plurality of independent topics associated with the query, wherein each independent topic in the plurality of independent topics is related to a distinct topic subject matter associated with the entity identified in the query; identifying a first set of independent comments related to a first distinct topic subject matter associated with the entity identified in the query and a second set of independent comments related to a second distinct topic subject matter associated with the entity identified in the query; determining a first relevance of the first distinct topic subject matter to the query; determining a second relevance of the second distinct topic subject matter to the query, determining a first predefined number of independent comments based on the first relevance; determining a second predefined number of independent comments based on the second relevance; and displaying the first predefined number of independent comments from the first set of independent comments related to the first distinct topic subject matter associated with the entity identified in the query and displaying the second predefined number of independent comments from the second set of independent comments related to the second distinct topic subject matter associated with the entity identified in the query. 3. The method as claimed in claim 1 , wherein the comment cluster database comprises a plurality of comment clusters, the plurality of comment clusters being formed by combining the plurality of comments associated with the query. | 0.59507 |
9,245,524 | 1 | 2 | 1. A speech recognition device comprising: a coefficient storage unit which stores a suppression coefficient representing an amount of noise suppression and an adaptation coefficient representing an amount of adaptation which is generated on the basis of a predetermined noise and is synthesized to a clean acoustic model generated on the basis of a voice which does not include noise, in a manner to relate the suppression coefficient with the adaptation coefficient to each other; a noise estimation unit which estimates noise from an input signal; a noise suppression unit which suppresses a portion of the noise specified by a suppression amount specified on the basis of the suppression coefficient, among from the noise estimated by said noise estimation unit, from the input signal; an acoustic model adaptation unit which generates an adapted acoustic model which is noise-adapted, by synthesizing the noise model, which is generated on the basis of the noise estimated by said noise estimation unit in accordance with an amount of adaptation specified on the basis of the adaptation coefficient, to the clean acoustic model; and a search unit which recognizes voice on the basis of the input suppressed noise by said noise suppression unit and the adapted acoustic model generated by said acoustic model adaptation unit. | 1. A speech recognition device comprising: a coefficient storage unit which stores a suppression coefficient representing an amount of noise suppression and an adaptation coefficient representing an amount of adaptation which is generated on the basis of a predetermined noise and is synthesized to a clean acoustic model generated on the basis of a voice which does not include noise, in a manner to relate the suppression coefficient with the adaptation coefficient to each other; a noise estimation unit which estimates noise from an input signal; a noise suppression unit which suppresses a portion of the noise specified by a suppression amount specified on the basis of the suppression coefficient, among from the noise estimated by said noise estimation unit, from the input signal; an acoustic model adaptation unit which generates an adapted acoustic model which is noise-adapted, by synthesizing the noise model, which is generated on the basis of the noise estimated by said noise estimation unit in accordance with an amount of adaptation specified on the basis of the adaptation coefficient, to the clean acoustic model; and a search unit which recognizes voice on the basis of the input suppressed noise by said noise suppression unit and the adapted acoustic model generated by said acoustic model adaptation unit. 2. The speech recognition device according to claim 1 , wherein the sum of the suppression coefficient and the adaptation coefficient is a predetermined value or matrix. | 0.933725 |
7,831,534 | 15 | 16 | 15. The method of claim 14 , further comprising displaying only categories and criteria whose attributive expressions differ from the constructed attributive expression by only one attribute. | 15. The method of claim 14 , further comprising displaying only categories and criteria whose attributive expressions differ from the constructed attributive expression by only one attribute. 16. The method of claim 15 , comprising searching and retrieving the specific objects associated with attributive expressions. | 0.5 |
9,247,100 | 12 | 23 | 12. A system configured to route confirmation of receipt and/or delivery of a facsimile, the system comprising: a processor; and logic in and/or executable by the processor to cause the processor to: generate text of a facsimile in a computer readable format; ascertain one or more of a significance and a relevance of at least a portion of the text by locating one or more keywords in the text, wherein at least two of the keywords are not adjacent in the text; analyze the text for at least one of a meaning and a context of the text; attempting to initiate a business process; determining whether a problem exists with the attempted business process; in response to determining a problem exists with the attempted business process, generating a notification of the determined problem; and route at least one confirmation of receipt and/or delivery of the facsimile to one or more confirmation destinations based on the analysis, wherein the business process initiation attempt is based on the analysis, and wherein the problem comprises failure to initiate the business process. | 12. A system configured to route confirmation of receipt and/or delivery of a facsimile, the system comprising: a processor; and logic in and/or executable by the processor to cause the processor to: generate text of a facsimile in a computer readable format; ascertain one or more of a significance and a relevance of at least a portion of the text by locating one or more keywords in the text, wherein at least two of the keywords are not adjacent in the text; analyze the text for at least one of a meaning and a context of the text; attempting to initiate a business process; determining whether a problem exists with the attempted business process; in response to determining a problem exists with the attempted business process, generating a notification of the determined problem; and route at least one confirmation of receipt and/or delivery of the facsimile to one or more confirmation destinations based on the analysis, wherein the business process initiation attempt is based on the analysis, and wherein the problem comprises failure to initiate the business process. 23. A system as recited in claim 12 , wherein the logic configured to cause the processor to analyze further comprises logic configured to cause the processor to compare one or more of the keywords in the text to at least one other element in the text. | 0.509728 |
8,442,977 | 13 | 16 | 13. A tangible computer readable storage device storing instructions, which, when executed by a processor, cause the processor to perform a process comprising: receiving, at a computer processor, an archive of video data from which a plurality of archive descriptor types are extracted; applying, using the computer processor, a query to the archive, the query comprising a number of N query descriptor types for a query object; determining, using the computer processor, a difference between each query descriptor type and corresponding descriptor types of track segments in the archive, and storing the differences in one or more vectors; storing each vector of differences in a computer storage medium as a point in an N dimensional space; and identifying, using the computer processor, an archive object that is similar to the query object as a function of proximities of the differences to an origin in one or more dimensions of the N dimensional space. | 13. A tangible computer readable storage device storing instructions, which, when executed by a processor, cause the processor to perform a process comprising: receiving, at a computer processor, an archive of video data from which a plurality of archive descriptor types are extracted; applying, using the computer processor, a query to the archive, the query comprising a number of N query descriptor types for a query object; determining, using the computer processor, a difference between each query descriptor type and corresponding descriptor types of track segments in the archive, and storing the differences in one or more vectors; storing each vector of differences in a computer storage medium as a point in an N dimensional space; and identifying, using the computer processor, an archive object that is similar to the query object as a function of proximities of the differences to an origin in one or more dimensions of the N dimensional space. 16. The tangible computer readable storage device of claim 13 , comprising instructions which when executed by a processor perform a process comprising applying a relevance weight to a descriptor type such that the descriptor type has more or less relevance as compared to other descriptor types in the identification of the archive object. | 0.639831 |
8,380,650 | 12 | 15 | 12. An information extraction rule making support method comprising: storing an extraction object document, which is an electronic document of an information extraction object, in a storage unit; inputting a plurality of extraction rules, which are rules used to extract information from said extraction object document; respectively deriving extraction results matching each of said extraction rules from said extraction object document stored by said storage unit, using each of said extraction rules inputted; and creating a rule relation network indicating a relation between each of said extraction rules by analyzing an overlapping relation and including relation between extraction results derived and linking said extraction rules that the extraction results overlap or include, based on the result of the analysis; wherein said rule relation network derives an overlapping ratio indicating an overlapping relation between each of extraction results derived by said information extraction section, by analyzing an overlapping relation between said extraction results, and links corresponding extraction rules based on said overlapping ratio derived. | 12. An information extraction rule making support method comprising: storing an extraction object document, which is an electronic document of an information extraction object, in a storage unit; inputting a plurality of extraction rules, which are rules used to extract information from said extraction object document; respectively deriving extraction results matching each of said extraction rules from said extraction object document stored by said storage unit, using each of said extraction rules inputted; and creating a rule relation network indicating a relation between each of said extraction rules by analyzing an overlapping relation and including relation between extraction results derived and linking said extraction rules that the extraction results overlap or include, based on the result of the analysis; wherein said rule relation network derives an overlapping ratio indicating an overlapping relation between each of extraction results derived by said information extraction section, by analyzing an overlapping relation between said extraction results, and links corresponding extraction rules based on said overlapping ratio derived. 15. The information extraction rule making support method as defined in claim 12 , comprising: outputting said rule relation network created as rule relation information indicating relations between extraction rules. | 0.847887 |
7,707,252 | 7 | 9 | 7. A method as in claim 2 , further comprising using the computer to automatically classify an incoming message as a spam message, or not as a spam message, based on said rules in said database as changed by said first and second controls. | 7. A method as in claim 2 , further comprising using the computer to automatically classify an incoming message as a spam message, or not as a spam message, based on said rules in said database as changed by said first and second controls. 9. A method as in claim 7 , further comprising displaying messages that have not been classified to represent spam in a first view, and displaying messages that do represent spam in a second view. | 0.595041 |
6,141,016 | 1 | 4 | 1. A requirement input method, comprising the steps of: a) arranging components of a development on a screen of a computer terminal; b) specifying, for each of the arranged components, an attribute information relating to data and procedure to be held by said component; c) designating a procedure call sequence between the components by selecting a procedure from a list of procedures held by the component; and d) generating a scenario including component data and procedure call sequence data on the basis of said attribute information and said selected procedure call sequence. | 1. A requirement input method, comprising the steps of: a) arranging components of a development on a screen of a computer terminal; b) specifying, for each of the arranged components, an attribute information relating to data and procedure to be held by said component; c) designating a procedure call sequence between the components by selecting a procedure from a list of procedures held by the component; and d) generating a scenario including component data and procedure call sequence data on the basis of said attribute information and said selected procedure call sequence. 4. A requirement input method according to claim 1, wherein said step c) comprises specifying at least one of data item names held by the component holding said selected procedure, and inputting a value corresponding to said specified data item, and wherein said step d) comprises generating substitute data on the basis of said specified data item and said inputted value, and generating a component holding said specified data item as data of the component. | 0.621287 |
9,875,494 | 12 | 16 | 12. A computing device, comprising: one or more processors; and a non-transitory computer-readable medium including instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including: receiving verbal input, wherein the verbal input includes natural language; determining an input intent associated with the verbal input, wherein the input intent is associated with an action that can be performed by the computing device, wherein the intent is determined using a dialog context, and wherein the dialog context includes a history of a current dialog session; adding the input intent to a history of intents, wherein the history of intents includes one or more intents from one or more previous dialog sessions, wherein the one or more intents include a transient intent, and wherein a transient intent does not cause the computing device to perform an action; determining an unstated characteristic associated with the history of intents, wherein determining includes identifying a pattern associated with the one or more intents from the history of intents and associating the pattern with the transient intent; modifying the action associated with the input intent, wherein the action is modified using the unstated characteristic; and executing the modified action, wherein the modified action modifies an operation of the computing device, and wherein executing the modified action fulfills the associated input intent. | 12. A computing device, comprising: one or more processors; and a non-transitory computer-readable medium including instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including: receiving verbal input, wherein the verbal input includes natural language; determining an input intent associated with the verbal input, wherein the input intent is associated with an action that can be performed by the computing device, wherein the intent is determined using a dialog context, and wherein the dialog context includes a history of a current dialog session; adding the input intent to a history of intents, wherein the history of intents includes one or more intents from one or more previous dialog sessions, wherein the one or more intents include a transient intent, and wherein a transient intent does not cause the computing device to perform an action; determining an unstated characteristic associated with the history of intents, wherein determining includes identifying a pattern associated with the one or more intents from the history of intents and associating the pattern with the transient intent; modifying the action associated with the input intent, wherein the action is modified using the unstated characteristic; and executing the modified action, wherein the modified action modifies an operation of the computing device, and wherein executing the modified action fulfills the associated input intent. 16. The computing device of claim 12 , wherein the non-transitory computer-readable medium further includes instructions that, when executed by the one or more processors, cause the one or more processors to perform operations including: determining an objective associated with the current dialog session; and using the unstated characteristic to determine whether the objective associated with the current dialog session has been fulfilled. | 0.589981 |
9,135,915 | 15 | 16 | 15. An article of manufacture including a non-transitory computer-readable medium having instructions stored thereon that, when executed by a computing device, cause the computing device to perform functions comprising: receiving audio data representative of audio detected by a microphone, wherein the microphone is positioned on a head-mountable device (HMD); determining whether the received audio data comprises audio speech data in an audio-channel speech band or audio non-speech data outside the audio-channel speech band; receiving vibration data representative of vibrations detected by a sensor other than the microphone, wherein the sensor is positioned on the HMD; determining a degree of spectral coherency, with respect to a threshold, between the audio data and the vibration data; determining whether or not the audio data is causally related to the vibration data based on the determined degree of spectral coherency; and if the received audio data both: (a) comprises audio speech data in an audio-channel speech band and (b) is determined to be causally related to the vibration data based on the degree of spectral coherency, then generating an indication that the audio data contains HMD-wearer speech and conditioning at least one of the audio data and the vibration data as speech data, wherein the conditioning comprises amplifying at least one of the audio data and the vibration; if the received audio data both: (a) comprises audio non-speech data outside the audio-channel speech band and (b) is determined to be causally related to the vibration data based on the degree of spectral coherency, then conditioning at least one of the audio data and the vibration data as coherent non-speech data, wherein the conditioning comprises removing or replacing non-speech data from at least one of the audio data and the vibration data; and otherwise, determining that the received audio data and the vibration data are non-coherent and conditioning at least one of the audio data and the vibration data as non-speech data, wherein the conditioning comprises removing or replacing non-speech data from at least one of the audio data and the vibration data. | 15. An article of manufacture including a non-transitory computer-readable medium having instructions stored thereon that, when executed by a computing device, cause the computing device to perform functions comprising: receiving audio data representative of audio detected by a microphone, wherein the microphone is positioned on a head-mountable device (HMD); determining whether the received audio data comprises audio speech data in an audio-channel speech band or audio non-speech data outside the audio-channel speech band; receiving vibration data representative of vibrations detected by a sensor other than the microphone, wherein the sensor is positioned on the HMD; determining a degree of spectral coherency, with respect to a threshold, between the audio data and the vibration data; determining whether or not the audio data is causally related to the vibration data based on the determined degree of spectral coherency; and if the received audio data both: (a) comprises audio speech data in an audio-channel speech band and (b) is determined to be causally related to the vibration data based on the degree of spectral coherency, then generating an indication that the audio data contains HMD-wearer speech and conditioning at least one of the audio data and the vibration data as speech data, wherein the conditioning comprises amplifying at least one of the audio data and the vibration; if the received audio data both: (a) comprises audio non-speech data outside the audio-channel speech band and (b) is determined to be causally related to the vibration data based on the degree of spectral coherency, then conditioning at least one of the audio data and the vibration data as coherent non-speech data, wherein the conditioning comprises removing or replacing non-speech data from at least one of the audio data and the vibration data; and otherwise, determining that the received audio data and the vibration data are non-coherent and conditioning at least one of the audio data and the vibration data as non-speech data, wherein the conditioning comprises removing or replacing non-speech data from at least one of the audio data and the vibration data. 16. The article of manufacture of claim 15 , wherein the functions further comprise: determining a correlation delay between the microphone and the sensor. | 0.720217 |
9,672,817 | 1 | 4 | 1. An apparatus for optimizing a speech recognition result, comprising: a computer that, by using computer executable instructions, receives a speech recognition result from a speech recognition engine, calculates a phoneme acoustic distance between a phoneme sequence of a segment of the speech recognition result and a phoneme sequence of a key word in a keyword list, calculates a tone acoustic distance between a tone sequence of the segment and a tone sequence of the key word, calculates a weighted average of the phoneme acoustic distance and the tone acoustic distance, calculates an average acoustic distance which is obtained by dividing the weighted average by the number of characters, syllables or phonemes of the key word, calculates a language model score of the segment, based on a language model score of each word in the segment, replaces the segment with the key word in a case that the average acoustic distance is lower than a first threshold and the language model score is lower than a second threshold, and outputs the speech recognition result of which the segment is replaced with the keyword to the speech recognition engine. | 1. An apparatus for optimizing a speech recognition result, comprising: a computer that, by using computer executable instructions, receives a speech recognition result from a speech recognition engine, calculates a phoneme acoustic distance between a phoneme sequence of a segment of the speech recognition result and a phoneme sequence of a key word in a keyword list, calculates a tone acoustic distance between a tone sequence of the segment and a tone sequence of the key word, calculates a weighted average of the phoneme acoustic distance and the tone acoustic distance, calculates an average acoustic distance which is obtained by dividing the weighted average by the number of characters, syllables or phonemes of the key word, calculates a language model score of the segment, based on a language model score of each word in the segment, replaces the segment with the key word in a case that the average acoustic distance is lower than a first threshold and the language model score is lower than a second threshold, and outputs the speech recognition result of which the segment is replaced with the keyword to the speech recognition engine. 4. The apparatus according to claim 1 , wherein the computer calculates the tone acoustic distance between the tone sequence of the segment and the tone sequence of the key word by using a tone confusion matrix as a weight. | 0.591575 |
9,754,014 | 4 | 7 | 4. The method of claim 1 , further comprising generating a second binary decision model by training the binary classifier using the plurality of training documents and the confirmation or the negation of the classification label of the most relevant example of the classified test documents. | 4. The method of claim 1 , further comprising generating a second binary decision model by training the binary classifier using the plurality of training documents and the confirmation or the negation of the classification label of the most relevant example of the classified test documents. 7. The method of claim 4 , further comprising reclassifying the one or more test documents into one of a plurality of categories using the second binary decision model. | 0.658537 |
8,027,982 | 1 | 12 | 1. A computer-implemented method of providing user-subscribed sources for secure search, comprising: providing to a user a template for crawling a source, the template defining a location of and crawl settings for a target data repository source, the template not having specified security credentials for the source; allowing a user to subscribe to the source using the template; receiving user-specified security credentials from the user and applying the user-specified security credentials to an instance of the template to create a user-subscribed source; authenticating a crawler as the user on the source; crawling, using a processor associated with a computer system, the source as the user template with user-specified security credentials; indexing documents for the user during the crawling in an index; and stamping identification information for the user with each entry in the index such that the associated documents are only available for search in the index by the user. | 1. A computer-implemented method of providing user-subscribed sources for secure search, comprising: providing to a user a template for crawling a source, the template defining a location of and crawl settings for a target data repository source, the template not having specified security credentials for the source; allowing a user to subscribe to the source using the template; receiving user-specified security credentials from the user and applying the user-specified security credentials to an instance of the template to create a user-subscribed source; authenticating a crawler as the user on the source; crawling, using a processor associated with a computer system, the source as the user template with user-specified security credentials; indexing documents for the user during the crawling in an index; and stamping identification information for the user with each entry in the index such that the associated documents are only available for search in the index by the user. 12. A method according to claim 1 , further comprising: using a single sign-on service with the user-subscribed source. | 0.812303 |
7,647,212 | 4 | 5 | 4. The method according to claim 1 , wherein the set of domain constraints are first propagated across each constraint store of the graph before propagating the set of domain constraints to other participants of the negotiation. | 4. The method according to claim 1 , wherein the set of domain constraints are first propagated across each constraint store of the graph before propagating the set of domain constraints to other participants of the negotiation. 5. The method according to claim 4 , wherein the set of domain constraints are first propagated within each constraint store of the graph before propagating the set of domain constraints across each constraint store of the graph. | 0.5 |
10,057,707 | 1 | 13 | 1. A method for processing audio data, the method comprising: receiving audio data corresponding to a recording of a conference involving a plurality of conference participants, the audio data including at least one of: (a) audio data from multiple endpoints, the audio data for each of the multiple endpoints having been recorded separately or (b) audio data from a single endpoint corresponding to multiple conference participants and including spatial information for each conference participant of the multiple conference participants; analyzing the audio data to determine conversational dynamics data that includes at least one data type selected from a list of data types consisting of: data indicating the frequency and duration of conference participant speech; data indicating instances of conference participant doubletalk during which at least two conference participants are speaking simultaneously; and data indicating instances of conference participant conversations; applying the conversational dynamics data as one or more variables of a spatial optimization cost function of a vector describing a virtual conference participant position for each of the conference participants in a virtual acoustic space; applying an optimization technique to the spatial optimization cost function to determine a locally optimal solution; and assigning the virtual conference participant positions in the virtual acoustic space based, at least in part, on the locally optimal solution. | 1. A method for processing audio data, the method comprising: receiving audio data corresponding to a recording of a conference involving a plurality of conference participants, the audio data including at least one of: (a) audio data from multiple endpoints, the audio data for each of the multiple endpoints having been recorded separately or (b) audio data from a single endpoint corresponding to multiple conference participants and including spatial information for each conference participant of the multiple conference participants; analyzing the audio data to determine conversational dynamics data that includes at least one data type selected from a list of data types consisting of: data indicating the frequency and duration of conference participant speech; data indicating instances of conference participant doubletalk during which at least two conference participants are speaking simultaneously; and data indicating instances of conference participant conversations; applying the conversational dynamics data as one or more variables of a spatial optimization cost function of a vector describing a virtual conference participant position for each of the conference participants in a virtual acoustic space; applying an optimization technique to the spatial optimization cost function to determine a locally optimal solution; and assigning the virtual conference participant positions in the virtual acoustic space based, at least in part, on the locally optimal solution. 13. The method of claim 1 , wherein analyzing the audio data involves identifying speech corresponding to individual conference participants. | 0.887917 |
9,977,656 | 1 | 2 | 1. A method for providing one or more software components for developing a software application, comprising: receiving, by at least one processor, an input from a user via a user interface, the input including one or more requirements associated with the software application; determining, by the at least one processor, for each of a plurality of software components existing in an application development environment, a requirements matching score based on a comparison between the one or more requirements and a requirements model associated with the corresponding software component, wherein the requirements model is generated based on historic user requirements and historic usage of the software component; determining, by the at least one processor, a performance score for each of the plurality of software components based on a response time associated with the corresponding software component; determining, by the at least one processor, a weight corresponding to the requirements matching score and a weight corresponding to the performance score based on the requirements matching score; determining, by the at least one processor, a combined score for each of the plurality of software components based on the weight corresponding to the requirements matching score and the weight corresponding to the performance score; selecting, by the at least one processor, from the plurality of software components, the one or more software components for developing the software application based on the combined score for each of the plurality of software components; and providing, by the at least one processor, the one or more software components to the user via the user interface. | 1. A method for providing one or more software components for developing a software application, comprising: receiving, by at least one processor, an input from a user via a user interface, the input including one or more requirements associated with the software application; determining, by the at least one processor, for each of a plurality of software components existing in an application development environment, a requirements matching score based on a comparison between the one or more requirements and a requirements model associated with the corresponding software component, wherein the requirements model is generated based on historic user requirements and historic usage of the software component; determining, by the at least one processor, a performance score for each of the plurality of software components based on a response time associated with the corresponding software component; determining, by the at least one processor, a weight corresponding to the requirements matching score and a weight corresponding to the performance score based on the requirements matching score; determining, by the at least one processor, a combined score for each of the plurality of software components based on the weight corresponding to the requirements matching score and the weight corresponding to the performance score; selecting, by the at least one processor, from the plurality of software components, the one or more software components for developing the software application based on the combined score for each of the plurality of software components; and providing, by the at least one processor, the one or more software components to the user via the user interface. 2. The method of claim 1 , further comprising: determining a success rate score for each of the plurality of software components based on a rate of the corresponding software component being called and completed; determining a weight corresponding to the success rate score based on the requirements matching score; and determining a combined score for each of the plurality of software components based on the weight corresponding to the requirements matching score, the weight corresponding to the performance score, and the weight corresponding to the success rate score. | 0.57732 |
10,120,849 | 1 | 7 | 1. A method comprising: detecting, by one or more processors of a machine, a request for provision of a first document that is available for provision; updating a count of referrals based on determining the request was sent from a set of one or more networks, the count of referrals comprising a number of requests for provision of the first document received from the set of one or more networks; retrieving a second document based on the first document and on the count of referrals transgressing a threshold value; and providing the second document in response to a subsequent request for the first document, the subsequent request occurring after expiration of an availability of the first document. | 1. A method comprising: detecting, by one or more processors of a machine, a request for provision of a first document that is available for provision; updating a count of referrals based on determining the request was sent from a set of one or more networks, the count of referrals comprising a number of requests for provision of the first document received from the set of one or more networks; retrieving a second document based on the first document and on the count of referrals transgressing a threshold value; and providing the second document in response to a subsequent request for the first document, the subsequent request occurring after expiration of an availability of the first document. 7. The method of claim 1 , further comprising: determining a different request for provision of the first document is received from a web crawling operation of a search engine, the search engine excluded from the set of one or more networks; and excluding the different request for provision from updating the count of referrals for the first document. | 0.5 |
7,689,423 | 1 | 13 | 1. A method of repeating a computer recognized string in a telematics unit in a vehicle, comprising: receiving a user utterance at the telematics unit from a user, the user utterance including a plurality of segments including a user pause between each segment, each of the plurality of segments having a plurality of words and a plurality of user pauses between the words; parsing the user utterance into a plurality of phonemes; forming a data string, via a processor operatively associated with the telematics unit, in which each user pause is associated with a phoneme adjacent to the user pause by i) determining an average duration of each user pause between the plurality of words in each segment, ii) assigning a time duration for each of the user pauses based on the average duration determination of each user pause between the plurality of words, iii) determining an average duration of each user pause between each segment, iv) assigning a time duration for each of the user pauses based on the average duration determination of each user pause between each segment, v) associating each user pause with the phoneme adjacent to the user pause, and vi) concatenating each user pause and the associated phoneme, each user pause including its associated assigned time duration; generating a virtual utterance corresponding to the data string; and playing back the virtual utterance to the user. | 1. A method of repeating a computer recognized string in a telematics unit in a vehicle, comprising: receiving a user utterance at the telematics unit from a user, the user utterance including a plurality of segments including a user pause between each segment, each of the plurality of segments having a plurality of words and a plurality of user pauses between the words; parsing the user utterance into a plurality of phonemes; forming a data string, via a processor operatively associated with the telematics unit, in which each user pause is associated with a phoneme adjacent to the user pause by i) determining an average duration of each user pause between the plurality of words in each segment, ii) assigning a time duration for each of the user pauses based on the average duration determination of each user pause between the plurality of words, iii) determining an average duration of each user pause between each segment, iv) assigning a time duration for each of the user pauses based on the average duration determination of each user pause between each segment, v) associating each user pause with the phoneme adjacent to the user pause, and vi) concatenating each user pause and the associated phoneme, each user pause including its associated assigned time duration; generating a virtual utterance corresponding to the data string; and playing back the virtual utterance to the user. 13. The method of claim 1 wherein the virtual utterance mimics patterns established by a rhythm, a timing, or combinations thereof of the user utterance. | 0.826136 |
7,600,017 | 51 | 52 | 51. A method for processing messages from a plurality of electronic discussion forums, comprising: collecting messages from the plurality of electronic discussion forums; and processing with a processor the messages based on a series of topics in order to track a plurality of pseudonyms, wherein processing the messages comprises computing a relevance score for a collected message based on a topic and wherein the relevance score is determined based on a set of rules, the rules having a plurality of conditions defining information relevant to the topic and having an associated weighting to indicate the strength a particular condition should have in determining the relevance of the messages with respect to the topic, and wherein processing the messages comprises computing a buzz score for a set of collected messages; wherein processing the messages further comprises computing a migration score based on the set of messages; wherein the migration score provides a measurement of the movement of posting activity levels between topics or groups of topics from the series of topics; wherein the migration score is computed based on a change in buzz levels; wherein the migration score is computed based on the equation: M n =[B n −B n−1 ], wherein B n is the buzz level for day n and B n−1 is the buzz level for the previous day; the method further comprising storing a report in a tangible memory on, at least in part, the topic, wherein a report output is based upon, at least in part, the migration score. | 51. A method for processing messages from a plurality of electronic discussion forums, comprising: collecting messages from the plurality of electronic discussion forums; and processing with a processor the messages based on a series of topics in order to track a plurality of pseudonyms, wherein processing the messages comprises computing a relevance score for a collected message based on a topic and wherein the relevance score is determined based on a set of rules, the rules having a plurality of conditions defining information relevant to the topic and having an associated weighting to indicate the strength a particular condition should have in determining the relevance of the messages with respect to the topic, and wherein processing the messages comprises computing a buzz score for a set of collected messages; wherein processing the messages further comprises computing a migration score based on the set of messages; wherein the migration score provides a measurement of the movement of posting activity levels between topics or groups of topics from the series of topics; wherein the migration score is computed based on a change in buzz levels; wherein the migration score is computed based on the equation: M n =[B n −B n−1 ], wherein B n is the buzz level for day n and B n−1 is the buzz level for the previous day; the method further comprising storing a report in a tangible memory on, at least in part, the topic, wherein a report output is based upon, at least in part, the migration score. 52. The method of claim 51 , wherein processing the messages further comprises computing a sentiment score measuring a degree in which the collected message exhibits one or more of (a) positive sentiment, (b) negative sentiment and (c) no sentiment associated with the topic wherein the report output is further based upon, at least in part, the sentiment score. | 0.5 |
7,624,081 | 1 | 6 | 1. A computer system for identifying potential community members of a community, the system comprising: a data store that identifies objects of different types and relationships between objects of different types, one type of object representing a person, another type of object representing a community of persons, one relationship indicating that a person is a member of a community, each community having a ranking, each relationship having an associated time; a memory storing computer-executable instructions for a generate heterogeneous graph component that generates a heterogeneous graph with vertices representing distinct objects and edges representing the relationships between objects, each edge having a time period and a weight; and a generate time vector heterogeneous graph component that generates a time vector heterogeneous graph from the heterogeneous graph, the time vector heterogeneous graph having a vertex for each vertex of the heterogeneous graph and an edge between objects representing a relationship between the objects, each edge having a time vector representing the weights of the relationship over time periods; a component that extracts features relating to each person from the objects and their relationships as indicated by the generated time vector heterogeneous graph, the extracted features representing evolution of the features over time; a generate best community training data component that generates training data for a best community classifier having a label associated with a person, the label indicating potential to be a community member, the training data being generated by, for each time period and each person who is a community member of a community within that time period: setting best community training data to the extracted features for that person; labeling the best community training data for that person with a rank of the highest ranking community that that person is a community member; and setting a time period for the best community training data for that person; a train best community classifier component that trains a best community classifier using the best community training data to classify the potential for a person represented by their features to be a community member of a community; a generate multi-class community classifier training data component that generates training data for a multi-class community classifier having a label associated with a person, the label indicating potential to be a community member, the multi-class community training data being generated by, for each time period, each community, and community member of a community within that time period: setting multi-class community training data to the extracted features for that person; labeling the multi-class community training data for that person with the community; and setting a time period for the multi-class community training data for that person; a train multi-class community classifier component that trains a multi-class community classifier using the multi-class community training data to classify the potential for a person represented by their features to be a community member of a community; and a classify person component that classifies a person as a potential community member using the best community classifier and when the person is classified as a potential community member for multiple communities, using the multi-class community classifier to classify the person as a potential community member for a single community; and a processor for executing the computer-executable instructions stored in the memory. | 1. A computer system for identifying potential community members of a community, the system comprising: a data store that identifies objects of different types and relationships between objects of different types, one type of object representing a person, another type of object representing a community of persons, one relationship indicating that a person is a member of a community, each community having a ranking, each relationship having an associated time; a memory storing computer-executable instructions for a generate heterogeneous graph component that generates a heterogeneous graph with vertices representing distinct objects and edges representing the relationships between objects, each edge having a time period and a weight; and a generate time vector heterogeneous graph component that generates a time vector heterogeneous graph from the heterogeneous graph, the time vector heterogeneous graph having a vertex for each vertex of the heterogeneous graph and an edge between objects representing a relationship between the objects, each edge having a time vector representing the weights of the relationship over time periods; a component that extracts features relating to each person from the objects and their relationships as indicated by the generated time vector heterogeneous graph, the extracted features representing evolution of the features over time; a generate best community training data component that generates training data for a best community classifier having a label associated with a person, the label indicating potential to be a community member, the training data being generated by, for each time period and each person who is a community member of a community within that time period: setting best community training data to the extracted features for that person; labeling the best community training data for that person with a rank of the highest ranking community that that person is a community member; and setting a time period for the best community training data for that person; a train best community classifier component that trains a best community classifier using the best community training data to classify the potential for a person represented by their features to be a community member of a community; a generate multi-class community classifier training data component that generates training data for a multi-class community classifier having a label associated with a person, the label indicating potential to be a community member, the multi-class community training data being generated by, for each time period, each community, and community member of a community within that time period: setting multi-class community training data to the extracted features for that person; labeling the multi-class community training data for that person with the community; and setting a time period for the multi-class community training data for that person; a train multi-class community classifier component that trains a multi-class community classifier using the multi-class community training data to classify the potential for a person represented by their features to be a community member of a community; and a classify person component that classifies a person as a potential community member using the best community classifier and when the person is classified as a potential community member for multiple communities, using the multi-class community classifier to classify the person as a potential community member for a single community; and a processor for executing the computer-executable instructions stored in the memory. 6. The system of claim 1 wherein the community members are potential rising stars in a community and wherein the object types include person, paper, and conference and the relationships include person was committee member of conference, paper was cited in paper, paper was published in conference, person was author of paper, and person was co-author with person. | 0.506793 |
7,523,440 | 33 | 40 | 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. 40. The method of claim 33 wherein the selected plurality of entities includes configurations of the one or more models. | 0.76834 |
9,268,761 | 11 | 19 | 11. A document generator, comprising: at least one processing unit; at least one system memory, communicatively coupled to the at least one processing unit and containing computer-readable instructions that, when executed by the at least one processing unit, configure a document formatter; wherein the document formatter is configured to receive a dynamic document template and to generate a formatted document, the document formatter including: a static text recognizer configured to detect static text in the dynamic document template, a placeholder recognizer configured to detect one or more placeholders for dynamic text in the dynamic document template, an expression evaluator, and a text formatter; the document formatter being configured to include the static text in the formatted document and to retrieve from a data source associated with the dynamic document template at least one data element referenced by a first expression associated with a detected placeholder for dynamic text in the dynamic document template; wherein the expression evaluator is configured to: evaluate a second expression to select a first display attribute for the retrieved data element based at least on a data value of the data element determined by the expression evaluator; and evaluate a third expression to select a second display attribute for at least a portion of the detected static text, wherein the third expression is based on the data value for the placeholder for dynamic text; wherein the text formatter is configured to include the determined data value in the formatted document in place of the placeholder and apply the first display attribute to the determined data value included in place of the placeholder in the formatted document, wherein the formatted document is generated based on the dynamic document template; and wherein the text formatter is configured to apply the second display attribute to the at least a portion of detected static text included in the formatted document. | 11. A document generator, comprising: at least one processing unit; at least one system memory, communicatively coupled to the at least one processing unit and containing computer-readable instructions that, when executed by the at least one processing unit, configure a document formatter; wherein the document formatter is configured to receive a dynamic document template and to generate a formatted document, the document formatter including: a static text recognizer configured to detect static text in the dynamic document template, a placeholder recognizer configured to detect one or more placeholders for dynamic text in the dynamic document template, an expression evaluator, and a text formatter; the document formatter being configured to include the static text in the formatted document and to retrieve from a data source associated with the dynamic document template at least one data element referenced by a first expression associated with a detected placeholder for dynamic text in the dynamic document template; wherein the expression evaluator is configured to: evaluate a second expression to select a first display attribute for the retrieved data element based at least on a data value of the data element determined by the expression evaluator; and evaluate a third expression to select a second display attribute for at least a portion of the detected static text, wherein the third expression is based on the data value for the placeholder for dynamic text; wherein the text formatter is configured to include the determined data value in the formatted document in place of the placeholder and apply the first display attribute to the determined data value included in place of the placeholder in the formatted document, wherein the formatted document is generated based on the dynamic document template; and wherein the text formatter is configured to apply the second display attribute to the at least a portion of detected static text included in the formatted document. 19. The document generator of claim 11 , wherein the document formatter is further configured to generate a second formatted document, and the expression evaluator is further configured to: evaluate the first expression to determine a second data value for the placeholder to be included in the second formatted document; evaluate the a third expression to select an updated display attribute for the static text in the second formatted document. | 0.558416 |
9,031,999 | 1 | 4 | 1. A system for generating concept database respective of a plurality of multimedia data elements (MMDEs), comprising: a memory; an attention processor (AP) for generating a plurality of items from a received MMDE of the plurality of MMDEs and determining which of the generated items that are of interest for signature generation; a signature generator (SG) for generating at least a signature responsive to at least an item of interest of the received MMDE of the plurality of MMDEs; a clustering processor (CP) for clustering a plurality of signatures received from the signature generator responsive of the plurality of MMDEs and creating a signature reduced cluster (SRC), wherein the clustering processor is further configured to: generate a clustering score for each signature of an MMDE of the plurality of MMDEs versus all other MMDEs of the plurality of MMDEs; determine a size of a diagonal matrix having a size corresponding to the number of the plurality of MMDEs; place the clustering score in a diagonal matrix in storage, one clustering score for each pair of MMDEs; create a new cluster element for each two cluster elements in the diagonal matrix having a clustering score that exceeds a threshold; and repeat the process at the newly created cluster element level each time using the new cluster elements generated as the plurality of cluster elements for the subsequent sequence, until a single cluster is reached or it is determined that a single cluster cannot be reached; a concept generator (CG) for associating metadata with the SRC and forming a concept structure comprised of a plurality of SRCs and their associated metadata; and an index generator (IG) for generating at least one index for mapping the received MMDE to at least one concept structure, wherein the concept database includes concept structures and the generated indices for the plurality of MMDEs, wherein the attention processor, the signature generator, the clustering processor, the concept generator, and the index generator are connected to the memory. | 1. A system for generating concept database respective of a plurality of multimedia data elements (MMDEs), comprising: a memory; an attention processor (AP) for generating a plurality of items from a received MMDE of the plurality of MMDEs and determining which of the generated items that are of interest for signature generation; a signature generator (SG) for generating at least a signature responsive to at least an item of interest of the received MMDE of the plurality of MMDEs; a clustering processor (CP) for clustering a plurality of signatures received from the signature generator responsive of the plurality of MMDEs and creating a signature reduced cluster (SRC), wherein the clustering processor is further configured to: generate a clustering score for each signature of an MMDE of the plurality of MMDEs versus all other MMDEs of the plurality of MMDEs; determine a size of a diagonal matrix having a size corresponding to the number of the plurality of MMDEs; place the clustering score in a diagonal matrix in storage, one clustering score for each pair of MMDEs; create a new cluster element for each two cluster elements in the diagonal matrix having a clustering score that exceeds a threshold; and repeat the process at the newly created cluster element level each time using the new cluster elements generated as the plurality of cluster elements for the subsequent sequence, until a single cluster is reached or it is determined that a single cluster cannot be reached; a concept generator (CG) for associating metadata with the SRC and forming a concept structure comprised of a plurality of SRCs and their associated metadata; and an index generator (IG) for generating at least one index for mapping the received MMDE to at least one concept structure, wherein the concept database includes concept structures and the generated indices for the plurality of MMDEs, wherein the attention processor, the signature generator, the clustering processor, the concept generator, and the index generator are connected to the memory. 4. The system of claim 1 , wherein the AP is further configured to extract items in the form of patterns from the received MMDE. | 0.817143 |
7,877,421 | 40 | 41 | 40. The system of claim 25 further comprising a statistical processor calculating statistics for the source data schema. | 40. The system of claim 25 further comprising a statistical processor calculating statistics for the source data schema. 41. The system of claim 40 wherein the statistics for the source data schema include a number of primary data constructs within the first data schema that have been mapped to corresponding classes of the ontology model. | 0.521834 |
7,530,020 | 23 | 24 | 23. A system for visualization of a set of objects in a computer graphic interface, comprising: a hierarchy comprising a plurality of objects which satisfy a set of inclusion criteria and a respective hierarchal organization of the plurality of objects, the plurality of objects each having associated content, a placement position of an object within the hierarchal organization being related to a content of the respective object; at least one additional object, supplemental to the hierarchy, a placement position of the additional object within the hierarchal organization being selectively based on a relationship of content associated with respective nearby objects and a content associated with the additional object; and an output, adapted to present the hierarchy and the at least one additional object to the user. | 23. A system for visualization of a set of objects in a computer graphic interface, comprising: a hierarchy comprising a plurality of objects which satisfy a set of inclusion criteria and a respective hierarchal organization of the plurality of objects, the plurality of objects each having associated content, a placement position of an object within the hierarchal organization being related to a content of the respective object; at least one additional object, supplemental to the hierarchy, a placement position of the additional object within the hierarchal organization being selectively based on a relationship of content associated with respective nearby objects and a content associated with the additional object; and an output, adapted to present the hierarchy and the at least one additional object to the user. 24. The system according to claim 23 , wherein the at least one additional object is associated with an object based on a collaborative filter. | 0.75 |
9,721,017 | 5 | 7 | 5. The system of claim 4 , wherein the first action set comprises no more than one single action. | 5. The system of claim 4 , wherein the first action set comprises no more than one single action. 7. The system of claim 5 , wherein the effects of the first single action being performed include activation of a hyperlink. | 0.866667 |
9,190,055 | 4 | 12 | 4. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, training, based at least partly on user data regarding a user, a personal model for use in named entity recognition, the personal model comprising a named entity recognition model; interpolating the personal model and a general model to obtain a composite model, the general model comprising a named entity recognition model; receiving audio input of an utterance, the audio input captured via a microphone; generating a transcription of the utterance based at least partly on the audio input and performing named entity recognition on the transcription using the composite model to generate a sequence of named entities. | 4. A computer-implemented method comprising: under control of one or more computing devices configured with specific computer-executable instructions, training, based at least partly on user data regarding a user, a personal model for use in named entity recognition, the personal model comprising a named entity recognition model; interpolating the personal model and a general model to obtain a composite model, the general model comprising a named entity recognition model; receiving audio input of an utterance, the audio input captured via a microphone; generating a transcription of the utterance based at least partly on the audio input and performing named entity recognition on the transcription using the composite model to generate a sequence of named entities. 12. The computer-implemented method of claim 4 , wherein the user data comprises one of: geographic location, age, gender, occupation, or a personal interest. | 0.848659 |
9,183,288 | 7 | 8 | 7. The computer-based method of claim 1 , wherein the steps of comparing at least one document node of the reformed term-to-document matrix against another document node of the reformed term-to-document matrix; and combining at least one document node of the term-to-document matrix with another document node of the term-to-document matrix, based on the comparison of the at least one document node of the reformed term-to-document matrix against the another document node of the reformed term-to-document matrix, to form a combined document node representing the combination of the at least one document node of the term-to-document matrix with the another document node of the term-to-document matrix, thereby clustering at least two document nodes of the term-to-document matrix, are performed iteratively until each document node of the term-to-document matrix is combined with at least one other document node of the term-to-document matrix, thereby forming a combined term-to-document matrix. | 7. The computer-based method of claim 1 , wherein the steps of comparing at least one document node of the reformed term-to-document matrix against another document node of the reformed term-to-document matrix; and combining at least one document node of the term-to-document matrix with another document node of the term-to-document matrix, based on the comparison of the at least one document node of the reformed term-to-document matrix against the another document node of the reformed term-to-document matrix, to form a combined document node representing the combination of the at least one document node of the term-to-document matrix with the another document node of the term-to-document matrix, thereby clustering at least two document nodes of the term-to-document matrix, are performed iteratively until each document node of the term-to-document matrix is combined with at least one other document node of the term-to-document matrix, thereby forming a combined term-to-document matrix. 8. The computer-based method of claim 7 , further comprising querying the document nodes of the reformed term-to-document matrix to produce a retrieved document, and displaying on a graphical user interface, both an indicator of the retrieved document and an indicator of at least one other document that corresponds to a document node that is combined with a document node that corresponds to the retrieved document. | 0.5 |
8,078,552 | 27 | 28 | 27. The system of claim 25 , wherein the degradation condition includes a numeric value, the numeric value assesses a distance amongst two vectors of N tuples, wherein the N tuples are computed metrics of observed data and N is a positive integer. | 27. The system of claim 25 , wherein the degradation condition includes a numeric value, the numeric value assesses a distance amongst two vectors of N tuples, wherein the N tuples are computed metrics of observed data and N is a positive integer. 28. The system of claim 27 , wherein the numeric value is a Euclidean distance. | 0.565934 |
7,610,227 | 1 | 3 | 1. A processor-based method for creating a set of work papers with cross-reference links to tax documents comprising: receiving, at a computer, a tax document; displaying, on a display screen, a page of the tax document; receiving, at the computer, a form type corresponding to the page of the tax document; receiving, at the computer, a form name corresponding to the page of the tax document; displaying, on the display screen, a plurality of categories related to the form type; providing, at the computer, a category selection from the plurality of categories; providing, at the computer, a link corresponding to the selected category; receiving, at the computer, a number or a description corresponding to the link; providing, at the computer, a tax return reconciliation template that includes a tax item description field and a tax page identifier field; providing, at the computer, a tax return reconciliation page by populating the tax item description field and the tax page identifier field with information from the tax document; and displaying, on the display screen, the tax return reconciliation page, wherein the tax page identifier field includes a clickable link to the page of the tax document containing a value corresponding to the tax item description field. | 1. A processor-based method for creating a set of work papers with cross-reference links to tax documents comprising: receiving, at a computer, a tax document; displaying, on a display screen, a page of the tax document; receiving, at the computer, a form type corresponding to the page of the tax document; receiving, at the computer, a form name corresponding to the page of the tax document; displaying, on the display screen, a plurality of categories related to the form type; providing, at the computer, a category selection from the plurality of categories; providing, at the computer, a link corresponding to the selected category; receiving, at the computer, a number or a description corresponding to the link; providing, at the computer, a tax return reconciliation template that includes a tax item description field and a tax page identifier field; providing, at the computer, a tax return reconciliation page by populating the tax item description field and the tax page identifier field with information from the tax document; and displaying, on the display screen, the tax return reconciliation page, wherein the tax page identifier field includes a clickable link to the page of the tax document containing a value corresponding to the tax item description field. 3. The method of claim 1 wherein the receiving the form name includes providing a form name selection from a plurality of preexisting form names or inputting a form name. | 0.5 |
9,652,440 | 1 | 4 | 1. A method comprising: providing a non-active representation of a document, the non-active representation of the document comprising a piece descriptor and a piece descriptor index; executing, by a computing system, a builder thread to input or modify an element in the document, the builder thread creating a new piece descriptor for indicating a position where the element belongs in the document, the new piece descriptor and the piece descriptor index forming an active representation of the document, wherein the active representation of the document and the non-active representation of the document refer to the same data stored in memory; providing access to the non-active representation for use by a reader thread while the builder thread modifies the active representation of the document; after the builder thread modifies the document, updating the non-active representation of the document with the active representation of the document, such that modifications to the element at the position indicated by the new piece descriptor replaces a corresponding element at the position indicated by the piece descriptor in the non-active representation of the document; and after updating the non-active representation, providing access to the non-active representation of the document including the modifications to the element. | 1. A method comprising: providing a non-active representation of a document, the non-active representation of the document comprising a piece descriptor and a piece descriptor index; executing, by a computing system, a builder thread to input or modify an element in the document, the builder thread creating a new piece descriptor for indicating a position where the element belongs in the document, the new piece descriptor and the piece descriptor index forming an active representation of the document, wherein the active representation of the document and the non-active representation of the document refer to the same data stored in memory; providing access to the non-active representation for use by a reader thread while the builder thread modifies the active representation of the document; after the builder thread modifies the document, updating the non-active representation of the document with the active representation of the document, such that modifications to the element at the position indicated by the new piece descriptor replaces a corresponding element at the position indicated by the piece descriptor in the non-active representation of the document; and after updating the non-active representation, providing access to the non-active representation of the document including the modifications to the element. 4. The method of claim 1 , further comprising executing, by the computing system, another reader thread concurrently with the reader thread and the builder thread, the other reader thread performing another operation regarding the document using the non-active representation of the document. | 0.754209 |
7,788,253 | 17 | 23 | 17. A system for building a search index, comprising: hardware logic capable of performing operations, the operations comprising: while building the search index and using the search index to respond to one or more search requests and performing synchronous anchor text processing: maintaining an anchor information store, wherein each entry of the anchor information store identifies a referring document, a target document, and anchor text associated with a link from the referring document to the target document; maintaining a rebuild agenda, wherein each entry of the rebuild agenda identifies a target document that has an entry in the search index and whose anchor text is to be updated in the search index with asynchronous processing because there is at least one new or updated link pointing to the target document; receiving a document for processing; for each outgoing link in the document that points to a target document, adding an entry to the anchor information store that identifies the received document, the target document, and anchor text; and adding an entry to the rebuild agenda for the target document; and for each link pointing from a referring document to the document, locating one or more entries in the anchor information store for which the received document to be processed is identified as the target document; retrieving anchor text from each of the identified entries; and storing the retrieved anchor text in an entry of the search index for the received document; and performing asynchronous anchor text processing to incrementally update current entries in the search index for each document identified in each entry in the rebuild agenda in parallel with the building of the search index and in parallel with using the search index to respond to one or more search requests by: selecting a first target document in the rebuild agenda; using the anchor information store to find anchor text for the first target document by identifying one or more entries in the anchor information store for which the first target document is identified as the target document in the anchor information store; retrieving anchor text from each of the identified entries; and updating the anchor text in the entry of the search index for the first target document. | 17. A system for building a search index, comprising: hardware logic capable of performing operations, the operations comprising: while building the search index and using the search index to respond to one or more search requests and performing synchronous anchor text processing: maintaining an anchor information store, wherein each entry of the anchor information store identifies a referring document, a target document, and anchor text associated with a link from the referring document to the target document; maintaining a rebuild agenda, wherein each entry of the rebuild agenda identifies a target document that has an entry in the search index and whose anchor text is to be updated in the search index with asynchronous processing because there is at least one new or updated link pointing to the target document; receiving a document for processing; for each outgoing link in the document that points to a target document, adding an entry to the anchor information store that identifies the received document, the target document, and anchor text; and adding an entry to the rebuild agenda for the target document; and for each link pointing from a referring document to the document, locating one or more entries in the anchor information store for which the received document to be processed is identified as the target document; retrieving anchor text from each of the identified entries; and storing the retrieved anchor text in an entry of the search index for the received document; and performing asynchronous anchor text processing to incrementally update current entries in the search index for each document identified in each entry in the rebuild agenda in parallel with the building of the search index and in parallel with using the search index to respond to one or more search requests by: selecting a first target document in the rebuild agenda; using the anchor information store to find anchor text for the first target document by identifying one or more entries in the anchor information store for which the first target document is identified as the target document in the anchor information store; retrieving anchor text from each of the identified entries; and updating the anchor text in the entry of the search index for the first target document. 23. The system of claim 17 , wherein the anchor information store includes tags, which are user annotations of documents. | 0.899334 |
8,014,990 | 1 | 14 | 1. A field-based similarity search system, comprising: a feature database for storing data pertaining to a candidate molecule, said database comprising a hash table having entries which are generated based on: a set of descriptors generated from conformations of fragment graphs of said candidate molecule, said fragment graphs including plural fragment nodes connected by rotatable bond edges, a specific conformation of said fragment node comprising a fragment of said candidate molecule, and two neighboring fragments connected by a rotatable bond at a specific dihedral angle comprising a fragment pair; and a context-adapted descriptor-to-key mapping which maps said set of descriptors to a set of feature keys comprising indices that label grid cells in discriminant space; an input device for inputting data pertaining to a query molecule; a processor which identifies a candidate molecule which is similar to said query molecule by: generating scoops, descriptors and keys for said query molecule; identifying features of a candidate molecule fragment pair which correspond to features of a query molecule fragment pair, by comparing said keys of said query molecule to said keys in said feature database, a correspondence comprising a scoop for said candidate molecule stored in said feature database having a same key as a scoop for said query molecule, wherein the candidate molecule fragment pair is within a set of candidate molecule fragment pairs describing the candidate molecule wherein the number of candidate molecule fragment pairs in the set, C fp , is given by C fp =(n−1)·(C frag ) 2 ·C rbe , where n is a number of fragments in said candidate molecule and n−1 is a number of rotatable bond edges connecting said n fragments, C frag is a number of conformations in a fragment of said fragments, and C rbe is a number of steps in which said rotatable bond edges are sampled; and aligning said candidate molecule fragment pair to said query molecule by overlaying internal coordinate axes of said scoops for said candidate and query molecules, said correspondence implying an alignment of said candidate molecule and query molecule fragment pairs; and a display device for displaying an output of said processor, wherein said features of said candidate molecule fragment pair and query molecule fragment pair comprise generalizations of comparative molecular moment analysis (CoMMA) descriptors. | 1. A field-based similarity search system, comprising: a feature database for storing data pertaining to a candidate molecule, said database comprising a hash table having entries which are generated based on: a set of descriptors generated from conformations of fragment graphs of said candidate molecule, said fragment graphs including plural fragment nodes connected by rotatable bond edges, a specific conformation of said fragment node comprising a fragment of said candidate molecule, and two neighboring fragments connected by a rotatable bond at a specific dihedral angle comprising a fragment pair; and a context-adapted descriptor-to-key mapping which maps said set of descriptors to a set of feature keys comprising indices that label grid cells in discriminant space; an input device for inputting data pertaining to a query molecule; a processor which identifies a candidate molecule which is similar to said query molecule by: generating scoops, descriptors and keys for said query molecule; identifying features of a candidate molecule fragment pair which correspond to features of a query molecule fragment pair, by comparing said keys of said query molecule to said keys in said feature database, a correspondence comprising a scoop for said candidate molecule stored in said feature database having a same key as a scoop for said query molecule, wherein the candidate molecule fragment pair is within a set of candidate molecule fragment pairs describing the candidate molecule wherein the number of candidate molecule fragment pairs in the set, C fp , is given by C fp =(n−1)·(C frag ) 2 ·C rbe , where n is a number of fragments in said candidate molecule and n−1 is a number of rotatable bond edges connecting said n fragments, C frag is a number of conformations in a fragment of said fragments, and C rbe is a number of steps in which said rotatable bond edges are sampled; and aligning said candidate molecule fragment pair to said query molecule by overlaying internal coordinate axes of said scoops for said candidate and query molecules, said correspondence implying an alignment of said candidate molecule and query molecule fragment pairs; and a display device for displaying an output of said processor, wherein said features of said candidate molecule fragment pair and query molecule fragment pair comprise generalizations of comparative molecular moment analysis (CoMMA) descriptors. 14. The system according to claim 1 , wherein said processor identifies said corresponding features by comparing features of candidate molecule fragment pairs with features of query molecule fragment pairs. | 0.837283 |
9,594,831 | 14 | 15 | 14. The hardware computer readable storage medium of claim 13 , the computer readable instructions further comprising: logic configured to create nodes in a graph corresponding to the candidate mentions; logic configured to determine weights between the nodes in the graph based, in part, on the context similarity scores; logic configured to assign the weights to edges in the graph; logic configured to assign the co-occurrence scores to the nodes in the graph; and logic configured to derive the ranking scores by solving the graph, the ranking scores being associated with the nodes in the graph. | 14. The hardware computer readable storage medium of claim 13 , the computer readable instructions further comprising: logic configured to create nodes in a graph corresponding to the candidate mentions; logic configured to determine weights between the nodes in the graph based, in part, on the context similarity scores; logic configured to assign the weights to edges in the graph; logic configured to assign the co-occurrence scores to the nodes in the graph; and logic configured to derive the ranking scores by solving the graph, the ranking scores being associated with the nodes in the graph. 15. The hardware computer readable storage medium of claim 14 , the computer readable instructions further comprising: logic configured to create at least one virtual node, the at least one virtual node associated with an entity e i , the at least one virtual node conveying counterpart reference information about the entity e i ; and logic configured to link the at least one virtual node to the graph. | 0.5 |
7,734,996 | 7 | 11 | 7. The documentation browsing apparatus according to claim 1 , wherein the association displaying means displays a displaying location of a document included in document data on a display screen in association with time information which indicates an elapsed time of voices or images. | 7. The documentation browsing apparatus according to claim 1 , wherein the association displaying means displays a displaying location of a document included in document data on a display screen in association with time information which indicates an elapsed time of voices or images. 11. The documentation browsing apparatus according to claim 7 , comprising display type selection means for selecting a type of displaying the length of displaying each section of document data on a display screen; wherein said display type selection means selects a display type of a length in proportion to the playback time of the voices or the images associated with said each section, or a predetermined length, or a length in proportion to the amount of documents in documents associated with said each section according to a user's selecting instructions; and the association displaying means displays said each section according to the display type selected by said display type selection means. | 0.5 |
9,754,279 | 2 | 7 | 2. The method of claim 1 , wherein the sampling comprises monitoring, at one or multiple locations, multiple streams of electronic data during transmission of the data. | 2. The method of claim 1 , wherein the sampling comprises monitoring, at one or multiple locations, multiple streams of electronic data during transmission of the data. 7. The method of claim 2 , wherein the sampling comprises sampling one or more streams of electronic data from a cloud computing database or cloud computing data center, and wherein the sampling comprises sampling a plurality of streams from disparate geographic locations. | 0.532534 |
8,794,972 | 10 | 18 | 10. The method of claim 9 further comprising the steps of: determining whether one of the sentences in the legal text includes a secondary exception clause; and in response to a determination that one of the sentences in the legal text includes a secondary exception clause, applying the secondary exception marking to the legal text such that the secondary exception clause is visually enhanced. | 10. The method of claim 9 further comprising the steps of: determining whether one of the sentences in the legal text includes a secondary exception clause; and in response to a determination that one of the sentences in the legal text includes a secondary exception clause, applying the secondary exception marking to the legal text such that the secondary exception clause is visually enhanced. 18. The method of claim 10 wherein the secondary exception marking is less visually prominent relative to the primary exception marking. | 0.5 |
8,364,694 | 5 | 9 | 5. A method for searching for digital media information available from an online media store, said method comprising: receiving a search hints request from a client application operating on a client device, the search hints request including at least a character string including at least one character; determining a set of search hints based on the character string, wherein said determining of the set of search hints obtains the matching search hints from a hints data structure and wherein the set of search hints correspond to digital media assets available in an online media repository and at least sales popularity data; obtaining a location of the client device; eliminating from the set of search hints those of the search hints in the set of search hints that are associated with a location other than the location of the client device; obtaining a media popularity indication for each of a plurality of the search hints in the set of search hints; and sending a portion of the search hints in the set of search hints to the client application on the client device, the portion of the search hints sent to the client application being less than all the search hints in the set of search hints. | 5. A method for searching for digital media information available from an online media store, said method comprising: receiving a search hints request from a client application operating on a client device, the search hints request including at least a character string including at least one character; determining a set of search hints based on the character string, wherein said determining of the set of search hints obtains the matching search hints from a hints data structure and wherein the set of search hints correspond to digital media assets available in an online media repository and at least sales popularity data; obtaining a location of the client device; eliminating from the set of search hints those of the search hints in the set of search hints that are associated with a location other than the location of the client device; obtaining a media popularity indication for each of a plurality of the search hints in the set of search hints; and sending a portion of the search hints in the set of search hints to the client application on the client device, the portion of the search hints sent to the client application being less than all the search hints in the set of search hints. 9. The method of claim 5 , wherein the media popularity indication is based on sales, previews, downloads, ratings, and rankings of each of the plurality of search hints in the set of search hints. | 0.870395 |
8,650,089 | 15 | 16 | 15. A non-transitory computer-readable medium for providing dynamic content in a static electronic document that stores logic for causing a remote computing device to perform at least the following: create the static electronic document of a publication, wherein the publication comprises a replica of a paper-based printed publication, wherein the static electronic document is configured to be displayed with the same look and feel as the printed publication, and wherein the static electronic document functions as a locally stored software application; receive an indication to include the dynamic content into the static electronic document; create a computer program that defines functionality of the dynamic content; deploy the computer program into the static electronic document, wherein the computer program is linked to a remote file that contains the dynamic content; send the static electronic document to a user computing device, wherein at least a first portion of the static electronic document is configured to be viewed as a locally stored document and at least a second portion of the static electronic document receives the dynamic content from the remote computing device, wherein the static electronic document comprises a pointer that causes the user computing device to utilize the computer program for retrieving the dynamic content from the remote computing device; receive a request to provide the dynamic content, the request being provided in response to a user selection of a predetermined area of interest in the static electronic document; provide the dynamic content to the user computing device, wherein upon receipt of the dynamic content, the computer program causes the dynamic content to be provided within the predetermined area of interest in the static electronic document, wherein the dynamic content comprises an option to place an order; receiving a user selection of the option to purchase a product, wherein the user selection is performed via an interaction with the dynamic content within the static electronic document; and processing the user selection within the static electronic document to purchase the product with a vendor that is associated with the dynamic content. | 15. A non-transitory computer-readable medium for providing dynamic content in a static electronic document that stores logic for causing a remote computing device to perform at least the following: create the static electronic document of a publication, wherein the publication comprises a replica of a paper-based printed publication, wherein the static electronic document is configured to be displayed with the same look and feel as the printed publication, and wherein the static electronic document functions as a locally stored software application; receive an indication to include the dynamic content into the static electronic document; create a computer program that defines functionality of the dynamic content; deploy the computer program into the static electronic document, wherein the computer program is linked to a remote file that contains the dynamic content; send the static electronic document to a user computing device, wherein at least a first portion of the static electronic document is configured to be viewed as a locally stored document and at least a second portion of the static electronic document receives the dynamic content from the remote computing device, wherein the static electronic document comprises a pointer that causes the user computing device to utilize the computer program for retrieving the dynamic content from the remote computing device; receive a request to provide the dynamic content, the request being provided in response to a user selection of a predetermined area of interest in the static electronic document; provide the dynamic content to the user computing device, wherein upon receipt of the dynamic content, the computer program causes the dynamic content to be provided within the predetermined area of interest in the static electronic document, wherein the dynamic content comprises an option to place an order; receiving a user selection of the option to purchase a product, wherein the user selection is performed via an interaction with the dynamic content within the static electronic document; and processing the user selection within the static electronic document to purchase the product with a vendor that is associated with the dynamic content. 16. The non-transitory computer-readable medium of claim 15 , wherein the publication comprises at least one of the following: a magazine, a newspaper, a brochure, a pamphlet, a sales slick, a manual, an encyclopedia, an atlas, a resume, a deposition, a dossier, a report, and a book. | 0.791483 |
7,533,034 | 71 | 72 | 71. The computer program product according to claim 40 , further comprising: maintaining a user suggestion log in memory. | 71. The computer program product according to claim 40 , further comprising: maintaining a user suggestion log in memory. 72. The computer program product according to claim 71 , wherein the employee suggestion log contains information entered by the user on a series of templates, information regarding routing of the user suggestion and status of the user suggestion. | 0.511858 |
7,546,334 | 38 | 39 | 38. A computer readable storage medium having stored thereon programming instructions for filtering and securing from input data, one or more security sensitive words, characters or data objects with an adaptive filter in a computer system, said adaptive filter used in conjunction with a compilation of additional data, the instructions comprising: identifying said security sensitive words, characters or data objects in said compilation of additional data; retrieving related data from said compilation of additional data representative of at least one of: contextual characters or data objects related to said security sensitive words, characters or data objects; semiotic words, characters or data objects related to said security sensitive words, characters or data objects; taxonomic words, characters or data objects related to said security sensitive words, characters or data objects; compiling a filter with said security sensitive words, characters or data objects and the retrieved data related to said security sensitive words, characters or data objects; and extracting, from said input data, with said filter, said security sensitive words, characters or data objects and said retrieved data to obtain extracted data and remainder data therefrom; and storing either the extracted data separately from said remainder data or storing partial versions of said extracted data with said remainder data based upon multiple security levels unique to each partial version. | 38. A computer readable storage medium having stored thereon programming instructions for filtering and securing from input data, one or more security sensitive words, characters or data objects with an adaptive filter in a computer system, said adaptive filter used in conjunction with a compilation of additional data, the instructions comprising: identifying said security sensitive words, characters or data objects in said compilation of additional data; retrieving related data from said compilation of additional data representative of at least one of: contextual characters or data objects related to said security sensitive words, characters or data objects; semiotic words, characters or data objects related to said security sensitive words, characters or data objects; taxonomic words, characters or data objects related to said security sensitive words, characters or data objects; compiling a filter with said security sensitive words, characters or data objects and the retrieved data related to said security sensitive words, characters or data objects; and extracting, from said input data, with said filter, said security sensitive words, characters or data objects and said retrieved data to obtain extracted data and remainder data therefrom; and storing either the extracted data separately from said remainder data or storing partial versions of said extracted data with said remainder data based upon multiple security levels unique to each partial version. 39. A computer readable storage medium with programming instructions for filtering and securing data as claimed in claim 38 , including conducting a network search through said compilation of additional data during the retrieval of data. | 0.830714 |
8,676,567 | 1 | 4 | 1. A method for filtering adjectives from a lexical chain, the method comprising: receiving, at a processor, the lexical chain comprising an adjective, the lexical chain being a component of an input document; calculating a non-characteristic-ness score based on the adjective's usage within the input document according to linguistic tests, the non-characteristic-ness score being a function of at least a frequency of the adjective's usage in the input document and a gradability non-characteristic-ness score for the adjective; testing, by the processor, the adjective to determine if the adjective is at least one of the following: a characteristic adjective and a non-characteristic adjective, wherein testing the adjective comprises comparing the non-characteristic-ness score to a threshold score; removing, by the processor, the adjective from the lexical chain when the non-characteristic-ness score is above the threshold score; and leaving, by the processor, the adjective in the lexical chain when the non-characteristic-ness score is below the threshold score. | 1. A method for filtering adjectives from a lexical chain, the method comprising: receiving, at a processor, the lexical chain comprising an adjective, the lexical chain being a component of an input document; calculating a non-characteristic-ness score based on the adjective's usage within the input document according to linguistic tests, the non-characteristic-ness score being a function of at least a frequency of the adjective's usage in the input document and a gradability non-characteristic-ness score for the adjective; testing, by the processor, the adjective to determine if the adjective is at least one of the following: a characteristic adjective and a non-characteristic adjective, wherein testing the adjective comprises comparing the non-characteristic-ness score to a threshold score; removing, by the processor, the adjective from the lexical chain when the non-characteristic-ness score is above the threshold score; and leaving, by the processor, the adjective in the lexical chain when the non-characteristic-ness score is below the threshold score. 4. The method of claim 1 , wherein determining if the adjective is at least one of the following: the characteristic adjective and non-characteristic adjective comprises determining a nominalization property. | 0.587302 |
8,760,498 | 12 | 15 | 12. A television receiver device that processes disparity data for closed captions, comprising: circuitry configured to receive closed caption data including closed caption text within a first Standard service block associated with a first Standard caption service having a service number in the range of 1-6; receive closed caption disparity data within a second Standard service block associated with a second Standard caption service having a service number equal to n, where n is between 1 and 6; parse the disparity data from the second Standard caption service having the service number n, the disparity data including a linkage field which associates said disparity data with the first Standard caption service; and process the caption text and the disparity data to produce an output suitable for defining a display of the caption text. | 12. A television receiver device that processes disparity data for closed captions, comprising: circuitry configured to receive closed caption data including closed caption text within a first Standard service block associated with a first Standard caption service having a service number in the range of 1-6; receive closed caption disparity data within a second Standard service block associated with a second Standard caption service having a service number equal to n, where n is between 1 and 6; parse the disparity data from the second Standard caption service having the service number n, the disparity data including a linkage field which associates said disparity data with the first Standard caption service; and process the caption text and the disparity data to produce an output suitable for defining a display of the caption text. 15. The device according to claim 12 , further comprising a three dimensional television display configured to display the closed caption text as a stereoscopic image produced by the compositor. | 0.5 |
8,521,528 | 11 | 20 | 11. A method for distributed speech recognition, comprising: obtaining audio data from a caller participating in a call with an agent; receiving on a main recognizer, a main grammar template and the audio data; receiving on each of a plurality of secondary recognizers, the audio data and a reference that identifies a secondary grammar, wherein each secondary grammar is a non-overlapping section of the main grammar template; performing speech recognition on each of the secondary recognizers, comprising: identifying speech recognition results by applying the secondary grammar to the audio data; and selecting an n number of most likely speech recognition results; constructing by the main recognizer, a new grammar using the speech recognition results from each of the secondary recognizers as a new vocabulary based on the main grammar template; and identifying further speech recognition results by applying the new grammar to the audio data. | 11. A method for distributed speech recognition, comprising: obtaining audio data from a caller participating in a call with an agent; receiving on a main recognizer, a main grammar template and the audio data; receiving on each of a plurality of secondary recognizers, the audio data and a reference that identifies a secondary grammar, wherein each secondary grammar is a non-overlapping section of the main grammar template; performing speech recognition on each of the secondary recognizers, comprising: identifying speech recognition results by applying the secondary grammar to the audio data; and selecting an n number of most likely speech recognition results; constructing by the main recognizer, a new grammar using the speech recognition results from each of the secondary recognizers as a new vocabulary based on the main grammar template; and identifying further speech recognition results by applying the new grammar to the audio data. 20. A method according to claim 11 , wherein the main recognizer and each of the secondary recognizers simultaneously receive the audio data. | 0.896476 |
8,428,241 | 13 | 14 | 13. The apparatus of claim 11 , wherein the at least one processor is further programmed to associate the recorded speech that represents the request by the caller for the destination with the recorded destination identifying information, and update a destination map using the recorded speech that is associated with the recorded destination identifying information. | 13. The apparatus of claim 11 , wherein the at least one processor is further programmed to associate the recorded speech that represents the request by the caller for the destination with the recorded destination identifying information, and update a destination map using the recorded speech that is associated with the recorded destination identifying information. 14. The apparatus of claim 13 , wherein the at least one processor is further programmed to associate recognized speech from a subsequent caller with a corresponding destination using the updated destination map. | 0.5 |
7,818,663 | 48 | 56 | 48. A system according to claim 30 , wherein said add in is configured to communicate with a broker application configured to retrieve editable information from a database. | 48. A system according to claim 30 , wherein said add in is configured to communicate with a broker application configured to retrieve editable information from a database. 56. A system according to claim 48 , comprising a plurality of workstations configured to communicate with said database. | 0.850248 |
9,135,341 | 1 | 2 | 1. A method for paginating and previewing content within one or more data files received in response to an information search, the content within the one or more data files being in an essentially continuously-flowing non-paginated format, wherein information content within the one or more data files include content formatted by markup language code, the method comprising: entering a search query; sending the query to a search engine, and receiving a search result having a list of data files each of which comprises content represented in a markup language code matching the search query; and for each of the data files in the list: retrieving the data file; paginating the content of the retrieved data file into discrete pages by applying pagination rules for dividing the content of the retrieved data file into multiple parts each suitable for page-level previewing purposes; generating preview pages each for rendering the same visible content of the retrieved data file that has been paginated into a respective discrete page of the retrieved data file; sending the preview pages to a client device which constructs a data file preview for the data file that simultaneously displays a subset of the preview pages generated for the data file, each of which is automatically selected for display in the data file preview by virtue of containing content that matches the search query, wherein the constructed data file preview is configured to allow an end user of the client device to select preview pages, which are displayed in the data file preview, in order to view higher resolution versions of those preview pages matching the corresponding discrete pages of the retrieved data file. | 1. A method for paginating and previewing content within one or more data files received in response to an information search, the content within the one or more data files being in an essentially continuously-flowing non-paginated format, wherein information content within the one or more data files include content formatted by markup language code, the method comprising: entering a search query; sending the query to a search engine, and receiving a search result having a list of data files each of which comprises content represented in a markup language code matching the search query; and for each of the data files in the list: retrieving the data file; paginating the content of the retrieved data file into discrete pages by applying pagination rules for dividing the content of the retrieved data file into multiple parts each suitable for page-level previewing purposes; generating preview pages each for rendering the same visible content of the retrieved data file that has been paginated into a respective discrete page of the retrieved data file; sending the preview pages to a client device which constructs a data file preview for the data file that simultaneously displays a subset of the preview pages generated for the data file, each of which is automatically selected for display in the data file preview by virtue of containing content that matches the search query, wherein the constructed data file preview is configured to allow an end user of the client device to select preview pages, which are displayed in the data file preview, in order to view higher resolution versions of those preview pages matching the corresponding discrete pages of the retrieved data file. 2. The method of claim 1 , wherein the data file content is paginated into the discrete pages based on system rules, user configuration and operating environment preferences. | 0.704082 |
9,300,963 | 6 | 7 | 6. The method of claim 1 , the flag is in a sequence level, wherein the flag is used to indicate that the temporal MVP candidates are not to be utilized for motion vector prediction for all reference pictures in an entire sequence. | 6. The method of claim 1 , the flag is in a sequence level, wherein the flag is used to indicate that the temporal MVP candidates are not to be utilized for motion vector prediction for all reference pictures in an entire sequence. 7. The method of claim 6 , wherein a second flag exists in a picture level or a slice level, and wherein the second flag is used to indicate that the temporal MVP candidates are not to be utilized for motion vector prediction for the picture or the slice respective. | 0.5 |
9,129,011 | 7 | 9 | 7. A method of controlling a mobile terminal, the method comprising: displaying an accessed web page on a display of the mobile terminal; generating objects of the displayed web page as a database: receiving first input voice information for searching the database; converting the first input voice information into text information; searching the database including the objects representing the displayed web page for objects that include the converted text information; distinctively displaying found objects that include the converted text information from other information displayed on the web page, the found objects displayed on a corresponding location of each of the found objects on the displayed web page with changed object features; receiving second input voice information for selecting one of the distinctively displayed objects on the displayed web page; selecting one of the distinctively displayed objects based on the second input voice information and changing a display state of the selected object by at least one of changing to a highlighted state, overlaying an indicator having a specific shape, changing a color, changing a size, and changing a thickness of the selected object; displaying information linked to the selected object while displaying the web page and releasing the distinctively display state of other found objects; and releasing the distinctively display of the found objects while displaying the web page when the second input voice information is not received in a preset time after the found objects are displayed on the web page. | 7. A method of controlling a mobile terminal, the method comprising: displaying an accessed web page on a display of the mobile terminal; generating objects of the displayed web page as a database: receiving first input voice information for searching the database; converting the first input voice information into text information; searching the database including the objects representing the displayed web page for objects that include the converted text information; distinctively displaying found objects that include the converted text information from other information displayed on the web page, the found objects displayed on a corresponding location of each of the found objects on the displayed web page with changed object features; receiving second input voice information for selecting one of the distinctively displayed objects on the displayed web page; selecting one of the distinctively displayed objects based on the second input voice information and changing a display state of the selected object by at least one of changing to a highlighted state, overlaying an indicator having a specific shape, changing a color, changing a size, and changing a thickness of the selected object; displaying information linked to the selected object while displaying the web page and releasing the distinctively display state of other found objects; and releasing the distinctively display of the found objects while displaying the web page when the second input voice information is not received in a preset time after the found objects are displayed on the web page. 9. The method of claim 7 , wherein when a corresponding found object includes a link to a separate web page, the method further comprises automatically accessing the separate web page when the corresponding found object is selected with a voice command. | 0.591935 |
8,813,060 | 12 | 16 | 12. A computer system for context aware application model for connected devices, the system comprising: a processor and memory configured to execute software instructions embodied within the following components; an application data store that provides a repository of applications from which a user can select applications to install on the user's computing device; a context-detecting component that detects context information related to the computing device and one or more activities that the user is performing on the device; an application manifest component that accesses and stores application manifest information associated with an application that describes contextual associations associated with the application; an application identification component that identifies one or more applications for the user to install based on the detected user context information and the stored application manifest information; an application installation component that installs a selected application and configures the application based on detected context information related to the computing device; an application behavior component that modifies application behavior at run time based on detected context information; and a user interface component that provides a user interface through which the user or an application developer can interact with the system to configure how context information is used. | 12. A computer system for context aware application model for connected devices, the system comprising: a processor and memory configured to execute software instructions embodied within the following components; an application data store that provides a repository of applications from which a user can select applications to install on the user's computing device; a context-detecting component that detects context information related to the computing device and one or more activities that the user is performing on the device; an application manifest component that accesses and stores application manifest information associated with an application that describes contextual associations associated with the application; an application identification component that identifies one or more applications for the user to install based on the detected user context information and the stored application manifest information; an application installation component that installs a selected application and configures the application based on detected context information related to the computing device; an application behavior component that modifies application behavior at run time based on detected context information; and a user interface component that provides a user interface through which the user or an application developer can interact with the system to configure how context information is used. 16. The system of claim 12 wherein the application installation component communicates specific hardware, input paradigms, output paradigms, and platform expectations to newly installed applications. | 0.618774 |
9,824,128 | 1 | 11 | 1. A distributed computer apparatus configured to perform schema-less queries of heterogeneous databases comprising: at least one registrar computer configured with database management software to register a plurality of heterogeneous databases within an information grid by storing a URL at which each of said plurality of heterogeneous databases accepts search queries; at least one search query object which contains at least two user-defined schema values that define at least one relationship between two or more of said plurality of heterogeneous databases; and at least one API processing computer which provides a user interface for a user to instantiate a search query object, of said at least one search query object, which initiates and supports a search session with the information grid, wherein the user interface is updated in real time during the search session to display available context fields, wherein the search query object invokes functions to update said user interface to display results obtained from a first heterogeneous database within the information grid which are related to search results obtained from a second heterogeneous database within the information grid, wherein at least one of the first or second heterogeneous database is a schema-less database that stores data without using any schema relationships, and wherein at least the other of the first or second heterogeneous database stores data using a schema relationship. | 1. A distributed computer apparatus configured to perform schema-less queries of heterogeneous databases comprising: at least one registrar computer configured with database management software to register a plurality of heterogeneous databases within an information grid by storing a URL at which each of said plurality of heterogeneous databases accepts search queries; at least one search query object which contains at least two user-defined schema values that define at least one relationship between two or more of said plurality of heterogeneous databases; and at least one API processing computer which provides a user interface for a user to instantiate a search query object, of said at least one search query object, which initiates and supports a search session with the information grid, wherein the user interface is updated in real time during the search session to display available context fields, wherein the search query object invokes functions to update said user interface to display results obtained from a first heterogeneous database within the information grid which are related to search results obtained from a second heterogeneous database within the information grid, wherein at least one of the first or second heterogeneous database is a schema-less database that stores data without using any schema relationships, and wherein at least the other of the first or second heterogeneous database stores data using a schema relationship. 11. The distributed computer apparatus of claim 1 , wherein said API processing computer further includes a relationship processor configured to perform a relate function to define a relationship between data in at least two of said plurality of heterogeneous databases. | 0.595808 |
7,526,363 | 1 | 2 | 1. A robot comprising: a first analyzer for analyzing phrase and action of a human partner to detect a recognized behavior of the partner; a second analyzer for analyzing a state of a plurality of people listening to utterances from said partner and said robot to detect a recognized state of said people; a scenario memory for storing a scenario describing a dialogue between said partner and said robot; and a processor for making reference to a portion of said scenario in said memory according to the recognized behavior of said partner and the recognized state of said people, and determining a behavior of said robot according to the referenced portion of said scenario. | 1. A robot comprising: a first analyzer for analyzing phrase and action of a human partner to detect a recognized behavior of the partner; a second analyzer for analyzing a state of a plurality of people listening to utterances from said partner and said robot to detect a recognized state of said people; a scenario memory for storing a scenario describing a dialogue between said partner and said robot; and a processor for making reference to a portion of said scenario in said memory according to the recognized behavior of said partner and the recognized state of said people, and determining a behavior of said robot according to the referenced portion of said scenario. 2. The robot of claim 1 , wherein said scenario memory includes a plurality of entries, each of said entries containing a portion of said scenario to be uttered by one of said partner and said robot, wherein said processor successively makes reference to each of said entries, produces a predetermined utterance from the robot according to the referenced portion of said scenario and determines said behavior of said robot according to one of a recognized behavior of said partner currently detected by the first analyzer and a recognized state of said people currently detected by the second analyzer. | 0.5 |
8,511,565 | 1 | 8 | 1. A method of providing information to a user via a printed substrate, said substrate comprising a printed graphic image and printed coded data indicative of a region identity associated with the substrate and of a plurality of coordinate locations on the substrate, said method comprising the steps of: receiving, in a computer system, interaction data indicative of the region identity and at least one coordinate position of a sensing device relative to the printed graphic image, the sensing device generating the interaction data when operatively positioned or moved relative to the printed graphic image by optically reading at least some of the printed coded data; identifying and retrieving at least part of a page description corresponding to the printed substrate using the region identity, generating a query expression comprising one or more search terms, at least one of said search terms being associated, in the page description, with a zone of the printed graphic image containing the coordinate position of the sensing device; forming a request using the query expression; and sending the request, or a results resource including search results obtained using the request, to the user, wherein the page description is maintained solely on a computer system and comprises a description of a plurality of virtual overlapping and layered zones corresponding to the printed graphic image, each description of a respective zone in the page description containing at least one search term. | 1. A method of providing information to a user via a printed substrate, said substrate comprising a printed graphic image and printed coded data indicative of a region identity associated with the substrate and of a plurality of coordinate locations on the substrate, said method comprising the steps of: receiving, in a computer system, interaction data indicative of the region identity and at least one coordinate position of a sensing device relative to the printed graphic image, the sensing device generating the interaction data when operatively positioned or moved relative to the printed graphic image by optically reading at least some of the printed coded data; identifying and retrieving at least part of a page description corresponding to the printed substrate using the region identity, generating a query expression comprising one or more search terms, at least one of said search terms being associated, in the page description, with a zone of the printed graphic image containing the coordinate position of the sensing device; forming a request using the query expression; and sending the request, or a results resource including search results obtained using the request, to the user, wherein the page description is maintained solely on a computer system and comprises a description of a plurality of virtual overlapping and layered zones corresponding to the printed graphic image, each description of a respective zone in the page description containing at least one search term. 8. The method of claim 1 , wherein the graphic image is a photograph or a page image. | 0.897094 |
9,734,148 | 1 | 5 | 1. A computer-implemented method performed by data processing apparatus, the method comprising: receiving, by a data processing apparatus, an electronic document data collection generated from a first set of documents, the document data collection including a first set of fixed phrases extracted from the first set of documents, wherein each fixed phrase is a phrase of one or more terms that is determined to not present a personal information exposure risk, and wherein access to the document data collection for examination by a human reviewer is precluded; receiving, by the data processing apparatus, a second set of documents, the second set of documents including documents that are each a personal document of a user that has personal information of the user and for which the user has provided permission to use the document for processing of the fixed phrases extracted from the first set of documents; extracting, by the data processing apparatus, candidate phrases from the second set of documents, each candidate phrase being a phrase of one or more terms; identifying, by the data processing apparatus, fixed phrases extracted from the first set of documents that match candidate phrases extracted from the second set of documents; generating, from the document data collection, a redacted document data collection in which each fixed phrase that does not match a candidate phrase is redacted, and each fixed phrase that does match a candidate phrase is not redacted; and providing, by the data processing apparatus, access to the redacted document data collection for examination by the human reviewer. | 1. A computer-implemented method performed by data processing apparatus, the method comprising: receiving, by a data processing apparatus, an electronic document data collection generated from a first set of documents, the document data collection including a first set of fixed phrases extracted from the first set of documents, wherein each fixed phrase is a phrase of one or more terms that is determined to not present a personal information exposure risk, and wherein access to the document data collection for examination by a human reviewer is precluded; receiving, by the data processing apparatus, a second set of documents, the second set of documents including documents that are each a personal document of a user that has personal information of the user and for which the user has provided permission to use the document for processing of the fixed phrases extracted from the first set of documents; extracting, by the data processing apparatus, candidate phrases from the second set of documents, each candidate phrase being a phrase of one or more terms; identifying, by the data processing apparatus, fixed phrases extracted from the first set of documents that match candidate phrases extracted from the second set of documents; generating, from the document data collection, a redacted document data collection in which each fixed phrase that does not match a candidate phrase is redacted, and each fixed phrase that does match a candidate phrase is not redacted; and providing, by the data processing apparatus, access to the redacted document data collection for examination by the human reviewer. 5. The computer-implemented method of claim 1 , wherein the document data collection is a template that describes content of the first set of documents in the form of structural data. | 0.859877 |
7,761,843 | 29 | 31 | 29. A tangible computer-readable medium having computer-executable instructions for implementing a method of creating computer code for a target programming language, the computer executable instructions comprising instructions for: defining a programming command as a predefined command sentence comprising at least one constant word and at least one enterable word, wherein the predefined command sentence comprises a structure other than a syntax of the target programming language and wherein the computer executable instructions for defining the programming command comprise instructions for: inserting a word into the programming command; deleting a word from the programming command; modifying a definition of a word of the programming command; and writing a translation procedure for the programming command; receiving data relating to an input value for the enterable word; and converting the predefined command sentence and the input value for the enterable word into a completed programming command. | 29. A tangible computer-readable medium having computer-executable instructions for implementing a method of creating computer code for a target programming language, the computer executable instructions comprising instructions for: defining a programming command as a predefined command sentence comprising at least one constant word and at least one enterable word, wherein the predefined command sentence comprises a structure other than a syntax of the target programming language and wherein the computer executable instructions for defining the programming command comprise instructions for: inserting a word into the programming command; deleting a word from the programming command; modifying a definition of a word of the programming command; and writing a translation procedure for the programming command; receiving data relating to an input value for the enterable word; and converting the predefined command sentence and the input value for the enterable word into a completed programming command. 31. The tangible computer-readable medium having computer-executable instructions of claim 29 wherein defining the programming command further comprises defining a command block comprising a plurality of programming commands. | 0.81737 |
7,831,836 | 10 | 11 | 10. A computer implemented method comprising: under control of one or more processors configured with executable instructions: identifying a language usable for a password; identifying permissible characters that may be used in the password; identifying a maximum character position permissible for the password; determining, for each character position up to the maximum character position, a frequency at which each of the permissible characters is used at the respective character position in words of the identified language; for each position, arranging the permissible characters into character strings based on the determined frequency at which each character is used at the respective position in words of the identified language, such that each character string begins with a permissible character most frequently used at the respective position and ends with a permissible character least frequently used at the respective position; storing the character strings in memory; generating words, one after another, the words having at least one character position, each word being generated by selecting characters, one after another, for each character position of the word from the respective character strings stored in memory for that position and in an order based at least in part on a character string, beginning with the character that is most frequently used at the respective position in the words of the identified language; and entering each generated word, one after another and based on an order in which the words are generated, until the password is determined. | 10. A computer implemented method comprising: under control of one or more processors configured with executable instructions: identifying a language usable for a password; identifying permissible characters that may be used in the password; identifying a maximum character position permissible for the password; determining, for each character position up to the maximum character position, a frequency at which each of the permissible characters is used at the respective character position in words of the identified language; for each position, arranging the permissible characters into character strings based on the determined frequency at which each character is used at the respective position in words of the identified language, such that each character string begins with a permissible character most frequently used at the respective position and ends with a permissible character least frequently used at the respective position; storing the character strings in memory; generating words, one after another, the words having at least one character position, each word being generated by selecting characters, one after another, for each character position of the word from the respective character strings stored in memory for that position and in an order based at least in part on a character string, beginning with the character that is most frequently used at the respective position in the words of the identified language; and entering each generated word, one after another and based on an order in which the words are generated, until the password is determined. 11. The method of claim 10 , wherein the frequency that each of the characters occurs at each position is determined based on an English language dictionary. | 0.532738 |
8,477,331 | 18 | 22 | 18. A method for creating an electronic version of machine printed matter, the method including the steps of: optically obtaining image data which can be used to present an electronic image of the printed matter, the electronic image having substantially the same appearance as the printed matter, and a region containing machine printed information which cannot be readily discerned; obtaining and modifying text-based information data entered by a user and representing the information contained in the region containing machine printed information which cannot be readily discerned when viewed by a viewer different and remote from the user in a manner that allows the information to be readily discerned when viewed; creating a reference which can be used to retrieve the information data; and processing the image data and the reference in order to create presentation data, wherein the presentation data can be used to present the electronic image, and to retrieve the information data so that it can be used to present the information contained in the region to the viewer. | 18. A method for creating an electronic version of machine printed matter, the method including the steps of: optically obtaining image data which can be used to present an electronic image of the printed matter, the electronic image having substantially the same appearance as the printed matter, and a region containing machine printed information which cannot be readily discerned; obtaining and modifying text-based information data entered by a user and representing the information contained in the region containing machine printed information which cannot be readily discerned when viewed by a viewer different and remote from the user in a manner that allows the information to be readily discerned when viewed; creating a reference which can be used to retrieve the information data; and processing the image data and the reference in order to create presentation data, wherein the presentation data can be used to present the electronic image, and to retrieve the information data so that it can be used to present the information contained in the region to the viewer. 22. The method of claim 18 , wherein the step of obtaining the image data includes changing the image data in order to effect a change in a resolution of the electronic image. | 0.758287 |
10,055,641 | 11 | 16 | 11. A method comprising: via at least a camera module, receiving visual information indicative of a printed document being viewed by a user through a see through display; determining a printed document identifier based, at least in part, on the visual information received via the camera module; determining that the printed document identifier corresponds with a historical printed document record comprising information regarding previous user interactions with the printed document by the user during at least one previous session in which the user interacted with a document associated with the printed document identifier via the see through display or other see through display; retrieving, from the historical printed document record, at least one printed document interaction attribute associated with the previous user interactions by the user with the printed document; and causing rendering of information indicative of the printed document interaction attribute on the see through display according to the previous user interactions by the user with the printed document being viewed by the user through the see through display, such that the rendered information on the see through display corresponds to the printed document as provided in the historical printed document record. | 11. A method comprising: via at least a camera module, receiving visual information indicative of a printed document being viewed by a user through a see through display; determining a printed document identifier based, at least in part, on the visual information received via the camera module; determining that the printed document identifier corresponds with a historical printed document record comprising information regarding previous user interactions with the printed document by the user during at least one previous session in which the user interacted with a document associated with the printed document identifier via the see through display or other see through display; retrieving, from the historical printed document record, at least one printed document interaction attribute associated with the previous user interactions by the user with the printed document; and causing rendering of information indicative of the printed document interaction attribute on the see through display according to the previous user interactions by the user with the printed document being viewed by the user through the see through display, such that the rendered information on the see through display corresponds to the printed document as provided in the historical printed document record. 16. The method of claim 11 , further comprising: determining that a printed document reconfiguration has occurred; determining another printed document interaction attribute associated with the printed document based, at least in part, on the visual information; and causing storage of information indicative of the other printed document interaction attribute in the historical printed document record. | 0.749689 |
8,682,898 | 17 | 18 | 17. The computer program product according to claim 10 , wherein to cluster the plurality of the postal addresses further comprises utilizing a signature based clustering methodology. | 17. The computer program product according to claim 10 , wherein to cluster the plurality of the postal addresses further comprises utilizing a signature based clustering methodology. 18. The computer program product according to claim 17 , wherein the signature based clustering methodology further comprises computing a set of signatures for a postal address via shingling, said shingling comprising producing shingles via a moving window. | 0.5 |
10,067,918 | 6 | 9 | 6. A system, comprising: at least one computing device; and a plurality of computer instructions executable by the at least one computing device, wherein the plurality of computer instructions, when executed, cause the at least one computing device to at least: designate a series of characters in a text block as being a text unit; bind the series of characters together; encode the text block to generate an encoded text block, the encoded text block comprising a first signal indicating that an entirety of the series of characters in the text unit is to be selected in response to a subset of the series of characters being selected; select, in response to the first signal and at least a portion of the subset of the series of characters being selected, the entirety of the series of characters in the text unit; and encode, in response to an instruction to treat the series of characters as being unbound, the text block to generate a modified encoded text block, wherein the modified encoded text block comprises a second signal indicating that a portion of the series of characters is to be selected in response to the portion of the series of characters being selected. | 6. A system, comprising: at least one computing device; and a plurality of computer instructions executable by the at least one computing device, wherein the plurality of computer instructions, when executed, cause the at least one computing device to at least: designate a series of characters in a text block as being a text unit; bind the series of characters together; encode the text block to generate an encoded text block, the encoded text block comprising a first signal indicating that an entirety of the series of characters in the text unit is to be selected in response to a subset of the series of characters being selected; select, in response to the first signal and at least a portion of the subset of the series of characters being selected, the entirety of the series of characters in the text unit; and encode, in response to an instruction to treat the series of characters as being unbound, the text block to generate a modified encoded text block, wherein the modified encoded text block comprises a second signal indicating that a portion of the series of characters is to be selected in response to the portion of the series of characters being selected. 9. The system of claim 6 , wherein the plurality of computer instructions further cause the at least one computing device to at least designate an additional series of characters in the text block as an additional text unit. | 0.527426 |
7,634,403 | 2 | 5 | 2. The method as in claim 1 wherein at least one of the word transformation commands transforms the currently selected word to a different grammatical form. | 2. The method as in claim 1 wherein at least one of the word transformation commands transforms the currently selected word to a different grammatical form. 5. The method as in claim 2 wherein at least one of the word transformation commands transforms the currently selected word between a possessive and a non-possessive form. | 0.5 |
7,661,068 | 2 | 3 | 2. The method of claim 1 , wherein the erasure gesture comprises a scratchout gesture. | 2. The method of claim 1 , wherein the erasure gesture comprises a scratchout gesture. 3. The method of claim 2 , wherein the operation comprises an undo of a prior erasure operation. | 0.5 |
7,917,899 | 19 | 20 | 19. A non-transitory computer-readable medium storing a computer program that when executed by a program development apparatus, causes the programs development apparatus to execute instructions comprising: instructions configured to store a complex intrinsic function including both an operation definition defining a program description in a source program subjected to be optimized, and an inline clause describing statements including multiple extended instructions after the optimization, the multiple extended instructions being executed by an extended module of a target processor; instructions configured to perform a syntax analysis of the complex intrinsic function by reading the complex intrinsic function out of the storage device, so as to detect the operation definition and the inline clause; instructions configured to generate an object code from the source program by optimizing a program description corresponding to the operation definition in the source program into the multiple extended instructions included in the statements in the inline clause; instructions for defining a very long word (VLIW) instruction including a coprocessor instruction to be executed by a coprocessor of a VLIW type included in the extended module from instructions applicable to parallel execution; and instructions for generating the complex intrinsic function by describing the VLIW instruction as the statements in the inline clause, and by defining the program description in the source program subjected to be optimized to the VLIW instruction as the operation definition. | 19. A non-transitory computer-readable medium storing a computer program that when executed by a program development apparatus, causes the programs development apparatus to execute instructions comprising: instructions configured to store a complex intrinsic function including both an operation definition defining a program description in a source program subjected to be optimized, and an inline clause describing statements including multiple extended instructions after the optimization, the multiple extended instructions being executed by an extended module of a target processor; instructions configured to perform a syntax analysis of the complex intrinsic function by reading the complex intrinsic function out of the storage device, so as to detect the operation definition and the inline clause; instructions configured to generate an object code from the source program by optimizing a program description corresponding to the operation definition in the source program into the multiple extended instructions included in the statements in the inline clause; instructions for defining a very long word (VLIW) instruction including a coprocessor instruction to be executed by a coprocessor of a VLIW type included in the extended module from instructions applicable to parallel execution; and instructions for generating the complex intrinsic function by describing the VLIW instruction as the statements in the inline clause, and by defining the program description in the source program subjected to be optimized to the VLIW instruction as the operation definition. 20. The non-transitory computer-readable medium of claim 19 , further comprising: instructions configured to detect the instructions applicable to the parallel execution in the source program by generating a data flow graph from the source program. | 0.5 |
8,218,849 | 25 | 26 | 25. The computer readable medium of claim 19 , wherein the computer executable instructions defining the step of determining a best apex-base plane candidate pair based on the generated joint context using a trained joint context detector comprise computer executable instructions defining the step of: determining the best apex-base plane candidate based on fusion of a probability determined by the joint context detector, a probability determined by the apex detector, and a probability determined by the base plane detector. | 25. The computer readable medium of claim 19 , wherein the computer executable instructions defining the step of determining a best apex-base plane candidate pair based on the generated joint context using a trained joint context detector comprise computer executable instructions defining the step of: determining the best apex-base plane candidate based on fusion of a probability determined by the joint context detector, a probability determined by the apex detector, and a probability determined by the base plane detector. 26. The computer readable medium of claim 25 , wherein the computer executable instructions defining the step of determining the best apex-base plane candidate based on fusion of a probability determined by the joint context detector, a probability determined by the apex detector, and a probability determined by the base plane detector comprise computer executable instructions defining the step of: selecting an apex-base plane candidate with a best probability score:
p=p j *( p a +p b )/2, where p j denotes the probability determined by the joint context detector, p a denotes the probability determined by the apex detector, and p b denotes the probability determined by the base plane detector. | 0.5 |
9,390,165 | 1 | 5 | 1. A system comprising: a memory to store a plurality of comments, the plurality of comments respectively comprising an overall rating of an entity and at least one phrase, the at least one phrase comprising a head term and a modifier associated with the head term; and one or more processors to implement: an aspect module to map respective head terms of a portion of the plurality of comments to an aspect cluster corresponding to an attribute of the entity, and a rating module to determine an aspect rating corresponding to the attribute of the entity based on the respective overall rating of the portion of the plurality of comments, and a module to cause presentation, on a client machine, of a graphical representation of the determined aspect rating corresponding to the attribute of the entity. | 1. A system comprising: a memory to store a plurality of comments, the plurality of comments respectively comprising an overall rating of an entity and at least one phrase, the at least one phrase comprising a head term and a modifier associated with the head term; and one or more processors to implement: an aspect module to map respective head terms of a portion of the plurality of comments to an aspect cluster corresponding to an attribute of the entity, and a rating module to determine an aspect rating corresponding to the attribute of the entity based on the respective overall rating of the portion of the plurality of comments, and a module to cause presentation, on a client machine, of a graphical representation of the determined aspect rating corresponding to the attribute of the entity. 5. The system of claim 1 , wherein the aspect module further comprises an unstructured probabilistic latent semantic analysis (PLSA) calculator to identify the aspect cluster using an unstructured PLSA algorithm. | 0.613139 |
9,348,915 | 10 | 11 | 10. The computer-implemented method of claim 6 , wherein the first type of content item corresponds to movies and wherein the popularity value for movies is determined based on at least one of: gross earnings, votes by one or more users, movie release date, a number of awards received and a type of award received. | 10. The computer-implemented method of claim 6 , wherein the first type of content item corresponds to movies and wherein the popularity value for movies is determined based on at least one of: gross earnings, votes by one or more users, movie release date, a number of awards received and a type of award received. 11. The computer-implemented method of claim 10 , wherein the popularity value for movies is further determined based on a popularity value of an actor. | 0.5 |
9,836,453 | 1 | 4 | 1. An entity recognition method comprising: providing a named entity recognition model which has been trained on features extracted from training samples tagged with document-level entity tags, each training sample comprising at least one text sequence; receiving a text document to be labeled, the text document being tagged with at least one document-level entity tag; generating a document-specific gazetteer based on the at least one document-level entity tag, the document-specific gazetteer including a set of entries, one entry for each of a set of entity names; for a text sequence of the text document, extracting features for tokens of the text sequence, the features including document-specific features for tokens matching at least a part of the entity name of one of the gazetteer entries, the document-specific features comprising at least 12 document-specific features; predicting entity labels for tokens in the document text sequence with the named entity recognition model, based on the extracted features, and wherein at least one of the generating, extracting, and predicting is performed with a processor. | 1. An entity recognition method comprising: providing a named entity recognition model which has been trained on features extracted from training samples tagged with document-level entity tags, each training sample comprising at least one text sequence; receiving a text document to be labeled, the text document being tagged with at least one document-level entity tag; generating a document-specific gazetteer based on the at least one document-level entity tag, the document-specific gazetteer including a set of entries, one entry for each of a set of entity names; for a text sequence of the text document, extracting features for tokens of the text sequence, the features including document-specific features for tokens matching at least a part of the entity name of one of the gazetteer entries, the document-specific features comprising at least 12 document-specific features; predicting entity labels for tokens in the document text sequence with the named entity recognition model, based on the extracted features, and wherein at least one of the generating, extracting, and predicting is performed with a processor. 4. The method of claim 1 , wherein the named entity recognition module is a conditional random field model. | 0.902015 |
9,699,472 | 14 | 19 | 14. A device configured to decode video data, the device comprising: a storage medium configured to store the video data; and one or more processors configured to: determine that a coding unit (CU) in a B slice is partitioned into one or more prediction units (PUs); and for at least one of the PUs of the CU: determine, based on a size characteristic of the PU, that the PU is restricted to uni-directional inter prediction; and parse, from a bitstream, an inter prediction mode indicator for the PU, wherein when the PU is restricted to uni-directional inter prediction, the inter prediction mode indicator is able to indicate that the PU is either uni-directionally inter predicted based on a list 0 or uni-directionally inter predicted based on a list 1 , wherein when the PU is not restricted to uni-directional inter prediction, the inter prediction mode indicator is able to indicate the PU is either uni-directionally inter predicted based on the list 0 , uni-directionally inter predicted based on the list 1 , or bi-directionally predicted. | 14. A device configured to decode video data, the device comprising: a storage medium configured to store the video data; and one or more processors configured to: determine that a coding unit (CU) in a B slice is partitioned into one or more prediction units (PUs); and for at least one of the PUs of the CU: determine, based on a size characteristic of the PU, that the PU is restricted to uni-directional inter prediction; and parse, from a bitstream, an inter prediction mode indicator for the PU, wherein when the PU is restricted to uni-directional inter prediction, the inter prediction mode indicator is able to indicate that the PU is either uni-directionally inter predicted based on a list 0 or uni-directionally inter predicted based on a list 1 , wherein when the PU is not restricted to uni-directional inter prediction, the inter prediction mode indicator is able to indicate the PU is either uni-directionally inter predicted based on the list 0 , uni-directionally inter predicted based on the list 1 , or bi-directionally predicted. 19. The device of claim 14 , wherein the one or more processors are further configured to entropy decode the inter prediction mode indicator using different contexts depending on whether the PU is restricted to uni-directional inter prediction. | 0.645349 |
8,726,170 | 1 | 8 | 1. An article comprising a non-transitory machine-readable storage medium embodying instructions that when performed by one or more machines result in operations comprising: initiating a communication between a first user and a second user via a collaboration channel, the collaboration channel selected from a group consisting of: a telephone call, a Voice of Internet Protocol (VOIP) telephone call or an instant messaging session; automatically associating an identification of the second user relating to the collaboration channel with a business entity upon initiation of the communication; automatically initiating a service retrieving contextual information associated with the business entity in response to the initiation of the communication, a scope of the retrieved contextual information being based on a business partner type for the business entity; and presenting the first user with at least a portion of the retrieved contextual information concurrently with the communication between the first user and the second user via the collaboration channel. | 1. An article comprising a non-transitory machine-readable storage medium embodying instructions that when performed by one or more machines result in operations comprising: initiating a communication between a first user and a second user via a collaboration channel, the collaboration channel selected from a group consisting of: a telephone call, a Voice of Internet Protocol (VOIP) telephone call or an instant messaging session; automatically associating an identification of the second user relating to the collaboration channel with a business entity upon initiation of the communication; automatically initiating a service retrieving contextual information associated with the business entity in response to the initiation of the communication, a scope of the retrieved contextual information being based on a business partner type for the business entity; and presenting the first user with at least a portion of the retrieved contextual information concurrently with the communication between the first user and the second user via the collaboration channel. 8. An article as in claim 1 , wherein the retrieved contextual information is displayed as a plurality of links. | 0.757576 |
8,745,019 | 1 | 7 | 1. A method, implemented by one or more computer processors, comprising: providing an entity reference string r e that is associated with an entity; providing a set of candidate strings S e , comprising at least one candidate string s e ; generating, using query log data, similarity score information for respective pairs of individual candidate strings of the set of candidate strings S e and the entity reference string r e using at least two similarity analysis functions; and determining, using the similarity score information, whether the individual candidate strings are valid synonyms of the entity reference string r e , where a valid synonym refers to the entity and satisfies a core set of synonym-related properties jointly provided by said at least two similarity analysis functions. | 1. A method, implemented by one or more computer processors, comprising: providing an entity reference string r e that is associated with an entity; providing a set of candidate strings S e , comprising at least one candidate string s e ; generating, using query log data, similarity score information for respective pairs of individual candidate strings of the set of candidate strings S e and the entity reference string r e using at least two similarity analysis functions; and determining, using the similarity score information, whether the individual candidate strings are valid synonyms of the entity reference string r e , where a valid synonym refers to the entity and satisfies a core set of synonym-related properties jointly provided by said at least two similarity analysis functions. 7. The method of claim 1 , wherein at least one synonym-related property in the core set of synonym-related properties is a relatedness-of-class property, wherein a pair (r e , s e ) satisfies the relatedness-of-class property when the entity reference string r e and the at least one candidate string s e correspond to a same class of strings. | 0.646091 |
7,996,211 | 17 | 18 | 17. The data processing system of claim 15 , wherein the determining comprises: determining whether the plurality of sentence annotation models agree on a same parse tree; and if any of the plurality of sentence annotation models agree on the same parse tree, selecting the set of tags, labels, and/or connections resulting from application of one of the agreed sentence annotation models as the best set of tags, labels, and/or connections. | 17. The data processing system of claim 15 , wherein the determining comprises: determining whether the plurality of sentence annotation models agree on a same parse tree; and if any of the plurality of sentence annotation models agree on the same parse tree, selecting the set of tags, labels, and/or connections resulting from application of one of the agreed sentence annotation models as the best set of tags, labels, and/or connections. 18. The data processing system of claim 17 , wherein the determining further comprises: if none of the plurality of sentence annotation models agree on a same parse tree, selecting a set of tags, labels and/or connections resulting from application of a support vector machines model as the best set of tags, labels, and/or connections. | 0.5 |
9,633,661 | 3 | 8 | 3. A portable device comprising: a microphone; a talk actuator; a power detector configured to detect a first power state and a second power state of the portable device; the portable device being configured to operate in a first mode when in the first power state and a second mode when in the second power state; wherein operating in the first mode comprises: detecting actuation of the talk actuator; generating, based at least in part on the actuation of the talk actuator, first audio data corresponding to first speech input; sending the first audio data to a speech support service server that is external to the portable device; receiving second audio data from the speech support service server, wherein the second audio data is based at least in part on the first audio data; and outputting audible content corresponding to the second audio data; and wherein operating in the second mode comprises: receiving second speech input; generating third audio data corresponding to the second speech input; and analyzing the third audio data. | 3. A portable device comprising: a microphone; a talk actuator; a power detector configured to detect a first power state and a second power state of the portable device; the portable device being configured to operate in a first mode when in the first power state and a second mode when in the second power state; wherein operating in the first mode comprises: detecting actuation of the talk actuator; generating, based at least in part on the actuation of the talk actuator, first audio data corresponding to first speech input; sending the first audio data to a speech support service server that is external to the portable device; receiving second audio data from the speech support service server, wherein the second audio data is based at least in part on the first audio data; and outputting audible content corresponding to the second audio data; and wherein operating in the second mode comprises: receiving second speech input; generating third audio data corresponding to the second speech input; and analyzing the third audio data. 8. The portable device of claim 3 , further comprising: a wireless network interface configured to communicate over a wide-area network with a music service server to receive fourth audio data containing music; and a speaker configured to play the music. | 0.706697 |
8,180,164 | 1 | 4 | 1. An image processing method comprising: scanning an input image via an image input device; compressing the scanned image using an image compression tool by performing OCR (Optical Character Recognition) on each symbol in the scanned image to generate OCR results and then performing tokenization on the scanned image using the OCR results, wherein the following rules are applied during the tokenization process: the symbols with different primary OCR results are not clustered into the same group; and for symbols with the same primary OCR result: if both symbols have high confidence levels for primary results and low confidence levels for secondary results, use a loose matching criteria to allow large shape variation if both symbols have high confidence levels for primary results and at least one has a high confidence levels for its secondary results, use a tight matching criteria to avoid misclassification; if at least one symbol has a low confidence level for its primary result, use a moderate to tight matching criteria; and storing the compressed image in a storage device or printing the compressed image via an image output device after it has been decoded. | 1. An image processing method comprising: scanning an input image via an image input device; compressing the scanned image using an image compression tool by performing OCR (Optical Character Recognition) on each symbol in the scanned image to generate OCR results and then performing tokenization on the scanned image using the OCR results, wherein the following rules are applied during the tokenization process: the symbols with different primary OCR results are not clustered into the same group; and for symbols with the same primary OCR result: if both symbols have high confidence levels for primary results and low confidence levels for secondary results, use a loose matching criteria to allow large shape variation if both symbols have high confidence levels for primary results and at least one has a high confidence levels for its secondary results, use a tight matching criteria to avoid misclassification; if at least one symbol has a low confidence level for its primary result, use a moderate to tight matching criteria; and storing the compressed image in a storage device or printing the compressed image via an image output device after it has been decoded. 4. The method defined in claim 1 , further comprising: performing pre-filtering on the scanned image to remove noise in the background or to clean up noise on edges; and guiding the level of pre-filtering on a page basis using OCR results, wherein the level of pre-filtering can be set for a whole page or selected areas with the help of image segmentation. | 0.53876 |
8,812,496 | 9 | 12 | 9. A method to identify a relevant person from a set of persons of interest, the method operating on a set of documents annotated by metadata specifying persons associated with documents and their social context roles in the documents, the method comprising: (0) receiving or generating a query comprising a content query portion qx k representing textual content of the query, a social context query portion qr k specifying one or more persons associated with the query and their social context roles in the query wherein the social context query portion includes an aggregation of social context query portions pertaining to at least two different social context roles, and a target social context role r k ′ for the relevant person; (1) for each document, computing a content-based score respective to the content query portion of the query and a social context-based score respective to the social context query portion of the query; (2) for each document, computing an enrichment score quantifying similarity of the document with a sub-set of nearest neighbor documents selected from the set of documents based on scores computed in operation (1); (3) for each document, aggregating the scores computed in operations (1) and (2) to generate a query score for the document; (4) generating a relevance score for each person of interest of the set of persons of interest by aggregating the query scores computed in operation (3) over the documents of the set of documents that have the person of interest in the target social context role r k ′; and (5) displaying identification of at least the person of interest of the set of persons of interest having the highest relevance score computed in operation (4); wherein operations (1), (2), (3), (4), and (5) are performed by an electronic data processing device. | 9. A method to identify a relevant person from a set of persons of interest, the method operating on a set of documents annotated by metadata specifying persons associated with documents and their social context roles in the documents, the method comprising: (0) receiving or generating a query comprising a content query portion qx k representing textual content of the query, a social context query portion qr k specifying one or more persons associated with the query and their social context roles in the query wherein the social context query portion includes an aggregation of social context query portions pertaining to at least two different social context roles, and a target social context role r k ′ for the relevant person; (1) for each document, computing a content-based score respective to the content query portion of the query and a social context-based score respective to the social context query portion of the query; (2) for each document, computing an enrichment score quantifying similarity of the document with a sub-set of nearest neighbor documents selected from the set of documents based on scores computed in operation (1); (3) for each document, aggregating the scores computed in operations (1) and (2) to generate a query score for the document; (4) generating a relevance score for each person of interest of the set of persons of interest by aggregating the query scores computed in operation (3) over the documents of the set of documents that have the person of interest in the target social context role r k ′; and (5) displaying identification of at least the person of interest of the set of persons of interest having the highest relevance score computed in operation (4); wherein operations (1), (2), (3), (4), and (5) are performed by an electronic data processing device. 12. The method of claim 9 , wherein the content query portion of the query includes a keyword-based query. | 0.937574 |
8,825,631 | 1 | 5 | 1. A method for improved processing of structured query language (SQL) queries, the method comprising: parsing, with a query processing computing device, a received SQL query made against a relational database to obtain one or more operators and associated one or more operands and a sequence of execution of the operators; identifying, with the query processing computing device, one or more required closure-friendly operators based on the one or more operators obtained from the SQL query and determining whether each of the closure-friendly operators exist; obtaining, with the query processing computing device, any of the closure-friendly operators determined to exist from a pattern repository; dynamically generating, with the query processing computing device, any of the closure-friendly operators determined not to exist; grouping, with the query processing computing device, the obtained closure-friendly operators and the dynamically generated closure-friendly operators into one or more patterns; classifying, with the query processing computing device, an impact of each of the patterns on at least one of the relational database or a database schema of the relational database; and executing, with the query processing computing device, the SQL query using the patterns based on the sequence of the execution of the operators. | 1. A method for improved processing of structured query language (SQL) queries, the method comprising: parsing, with a query processing computing device, a received SQL query made against a relational database to obtain one or more operators and associated one or more operands and a sequence of execution of the operators; identifying, with the query processing computing device, one or more required closure-friendly operators based on the one or more operators obtained from the SQL query and determining whether each of the closure-friendly operators exist; obtaining, with the query processing computing device, any of the closure-friendly operators determined to exist from a pattern repository; dynamically generating, with the query processing computing device, any of the closure-friendly operators determined not to exist; grouping, with the query processing computing device, the obtained closure-friendly operators and the dynamically generated closure-friendly operators into one or more patterns; classifying, with the query processing computing device, an impact of each of the patterns on at least one of the relational database or a database schema of the relational database; and executing, with the query processing computing device, the SQL query using the patterns based on the sequence of the execution of the operators. 5. The method of claim 1 , further comprising: analyzing, with the query processing computing device, the SQL query using partitions of the required closure-friendly operators; and tracing/debugging, with the query processing computing device, the SQL query based on the analysis. | 0.5 |
6,067,348 | 5 | 6 | 5. The apparatus of claim 4, wherein said message body is contained within said storage area. | 5. The apparatus of claim 4, wherein said message body is contained within said storage area. 6. The apparatus of claim 5, wherein said storage area contains a plurality of said message bodies. | 0.5 |
7,496,599 | 16 | 20 | 16. A system for mapping hierarchical data from a relational table comprising: a schema stored in a memory for a hierarchical data structure wherein the schema defines a hierarchical relationship of data elements; processing means coupled to said memory for identifying from the schema a node within the hierarchical data structure corresponding to a column in the relational table; and processing means for copying a predefined number of data values from the relational table to the hierarchical data structure wherein the predefined number of data values are from the same column of the relational table and each data value has a child relationship with another one of the data value and wherein the predefined number is determined from the schema. | 16. A system for mapping hierarchical data from a relational table comprising: a schema stored in a memory for a hierarchical data structure wherein the schema defines a hierarchical relationship of data elements; processing means coupled to said memory for identifying from the schema a node within the hierarchical data structure corresponding to a column in the relational table; and processing means for copying a predefined number of data values from the relational table to the hierarchical data structure wherein the predefined number of data values are from the same column of the relational table and each data value has a child relationship with another one of the data value and wherein the predefined number is determined from the schema. 20. The system as recited in claim 16 wherein the copying act is performed in response to an XPath query. | 0.605263 |
9,619,488 | 1 | 3 | 1. A computing device having adaptable image search, the computing device comprising: non-volatile memory configured to store a plurality of image recognition models; an image recognition program executed by a processor of the computing device, the computing device being a user computing device, and the image recognition program configured to: receive a query from a user, the query comprising text that is typed or converted from speech; receive a target image within which a search based on the query is to be performed; rank the image recognition models by confidence level for performing the search based on at least a comparison between the query and respective text descriptions of the image recognition models; determine whether the confidence level of any of the image recognition models is above a confidence threshold; and upon determining that at least one confidence level of the image recognition models is above the confidence threshold, select at least one of the image recognition models whose confidence level is above the confidence threshold; perform the search within the target image for a target region of the target image using at least one selected image recognition model locally on the processor; and return a search result to the user. | 1. A computing device having adaptable image search, the computing device comprising: non-volatile memory configured to store a plurality of image recognition models; an image recognition program executed by a processor of the computing device, the computing device being a user computing device, and the image recognition program configured to: receive a query from a user, the query comprising text that is typed or converted from speech; receive a target image within which a search based on the query is to be performed; rank the image recognition models by confidence level for performing the search based on at least a comparison between the query and respective text descriptions of the image recognition models; determine whether the confidence level of any of the image recognition models is above a confidence threshold; and upon determining that at least one confidence level of the image recognition models is above the confidence threshold, select at least one of the image recognition models whose confidence level is above the confidence threshold; perform the search within the target image for a target region of the target image using at least one selected image recognition model locally on the processor; and return a search result to the user. 3. The computing device of claim 1 , wherein each image recognition model includes at least one of the following: an image recognition algorithm, an optical character recognition (OCR) algorithm, and a keyword matching algorithm. | 0.5 |
9,734,193 | 18 | 20 | 18. A system comprising: an electronic device having: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: receiving a textual representation of user speech; identifying a candidate named entity from the textual representation of user speech, wherein the candidate named entity is associated with a plurality of saliency scores, each saliency score of the plurality of saliency scores representing a relationship strength between the candidate named entity and a respective domain of a plurality of domains; determining possible parts of speech of the candidate named entity; determining whether the possible parts of speech of the candidate named entity comprises one or more of a predetermined set of parts of speech; in response to determining that the possible parts of speech of the candidate named entity do not comprise one or more of the predetermined set of parts of speech, lowering a saliency score of the plurality of saliency scores associated with the candidate named entity; identifying a domain of the plurality of domains for processing the textual representation of user speech based at least in part on the lowered saliency score associated with the candidate named entity; and performing, by a virtual assistant on the electronic device, one or more tasks based on the identified domain to present an output. | 18. A system comprising: an electronic device having: one or more processors; memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, the one or more programs including instructions for: receiving a textual representation of user speech; identifying a candidate named entity from the textual representation of user speech, wherein the candidate named entity is associated with a plurality of saliency scores, each saliency score of the plurality of saliency scores representing a relationship strength between the candidate named entity and a respective domain of a plurality of domains; determining possible parts of speech of the candidate named entity; determining whether the possible parts of speech of the candidate named entity comprises one or more of a predetermined set of parts of speech; in response to determining that the possible parts of speech of the candidate named entity do not comprise one or more of the predetermined set of parts of speech, lowering a saliency score of the plurality of saliency scores associated with the candidate named entity; identifying a domain of the plurality of domains for processing the textual representation of user speech based at least in part on the lowered saliency score associated with the candidate named entity; and performing, by a virtual assistant on the electronic device, one or more tasks based on the identified domain to present an output. 20. The system of claim 18 , wherein determining possible parts of speech of the candidate named entity comprises determining all possible parts of speech of the candidate named entity. | 0.824144 |
7,756,890 | 17 | 18 | 17. The method of claim 11 , wherein accumulating further includes presenting the related information to an agent associated with the semantic identity, wherein the agent represents a primary identity for a principal and a principal is a resource. | 17. The method of claim 11 , wherein accumulating further includes presenting the related information to an agent associated with the semantic identity, wherein the agent represents a primary identity for a principal and a principal is a resource. 18. The method of claim 17 further comprising, assigning a rank value to portions of the related information, wherein higher rank values are associated with a more desirable portions of the related information than lower rank values, which are associated with less desirable portions of the related information, and wherein the higher and lower rank values may be used to modify the semantic specification. | 0.5 |
7,831,423 | 11 | 12 | 11. A computer-implemented method comprising: (A) identifying a first phrase, the first phrase representing an expanded written form of a concept; (B) receiving an instruction from a user to modify the first phrase; (C) in response to receipt of the instruction, identifying a second phrase representing an abbreviated written form of the concept; and (D) replacing the first phrase with the second phrase; and (E) after (D), replacing the second phrase with the first phrase; wherein the instruction does not include the second phrase. | 11. A computer-implemented method comprising: (A) identifying a first phrase, the first phrase representing an expanded written form of a concept; (B) receiving an instruction from a user to modify the first phrase; (C) in response to receipt of the instruction, identifying a second phrase representing an abbreviated written form of the concept; and (D) replacing the first phrase with the second phrase; and (E) after (D), replacing the second phrase with the first phrase; wherein the instruction does not include the second phrase. 12. The method of claim 11 , wherein the instruction comprises an instruction generated by the user using a single keystroke. | 0.663978 |
9,356,941 | 15 | 16 | 15. The system of claim 14 , wherein the classification module classifies the first web page as suspicious using the classification model by classifying the first web page as suspicious based on at least one of the following: a content feature of the first web page; a uniform resource locator feature of the first web page; a link between the first web page and the plurality of malicious web pages, wherein the link is represented by an edge within the web-page link graph. | 15. The system of claim 14 , wherein the classification module classifies the first web page as suspicious using the classification model by classifying the first web page as suspicious based on at least one of the following: a content feature of the first web page; a uniform resource locator feature of the first web page; a link between the first web page and the plurality of malicious web pages, wherein the link is represented by an edge within the web-page link graph. 16. The system of claim 15 , wherein: the classification module classifies the first web page as suspicious using the classification model by classifying the first web page as suspicious based on the link between the first web page and the plurality of malicious web pages; the classification module classifies the first web page as suspicious based on the link between the first web page and the plurality of malicious web pages by: using the web-page link graph to identify a set of direct links between the first web page and the plurality of malicious web pages; using the web-page link graph to identify a set of indirect links between the first web page and the plurality of malicious web pages; calculating a suspicious link score for the first web page based on the set of direct links and the set of indirect links; classifying the first web page as suspicious based at least in part on the suspicious link score. | 0.5 |
9,002,869 | 10 | 14 | 10. A computer-readable storage device having stored thereon instructions that, when executed by a computer, cause the computer to perform operations comprising: receiving an initial search query including one or more terms; using statistical machine translation to translate the initial search query into a translated search query, the translated search query being different from the initial search query and being in a same natural language as the initial search query; identifying a first term occurring in the initial search query that was replaced by a corresponding second term occurring in the translated search query; determining that one or more context terms occurring adjacent to the first term in the initial search query also occur adjacent to the second term in the translated search query; and in response to determining that one or more context terms occurring adjacent to the first term in the initial search query also occur adjacent to the second term in the translated search query, designating the second term as a synonym of the first term when the first term occurs adjacent to the one or more context terms in search queries, wherein a search engine expands a particular search query to include the second term in response to a determination that the first term occurs adjacent to the one or more context terms in the particular search query. | 10. A computer-readable storage device having stored thereon instructions that, when executed by a computer, cause the computer to perform operations comprising: receiving an initial search query including one or more terms; using statistical machine translation to translate the initial search query into a translated search query, the translated search query being different from the initial search query and being in a same natural language as the initial search query; identifying a first term occurring in the initial search query that was replaced by a corresponding second term occurring in the translated search query; determining that one or more context terms occurring adjacent to the first term in the initial search query also occur adjacent to the second term in the translated search query; and in response to determining that one or more context terms occurring adjacent to the first term in the initial search query also occur adjacent to the second term in the translated search query, designating the second term as a synonym of the first term when the first term occurs adjacent to the one or more context terms in search queries, wherein a search engine expands a particular search query to include the second term in response to a determination that the first term occurs adjacent to the one or more context terms in the particular search query. 14. The computer-readable storage device of claim 10 , wherein the operations further comprise: identifying a search result access log identifying search queries and corresponding snippets, each record in the search result access log identifying a respective stored search query and a corresponding snippet, the snippet of a respective stored search query being a portion of content from a document accessed by a user, the document having been presented to the user as a search result in response to receiving the respective stored search query; and building a translation model trained on the search queries and the corresponding snippets including using the search queries from the search result access log as a source language for the translation model and the corresponding snippets as a target language for the translation model, wherein using statistical machine translation to translate the initial search query into a translated search query comprises providing the initial search query as input to the translation model trained on the search queries and the corresponding snippets and receiving the translated search query as output from the translation model trained on the search queries and the corresponding snippets. | 0.5 |
8,117,239 | 8 | 13 | 8. A method for aggregating property attribute values across two or more schemas associated with two or more data sources, the method comprising: receiving at least a first schema and a second schema that both include a first property, wherein within the first schema the first property is described by a plurality of static attributes and a plurality of contextual attributes associated with a first plurality of contextual attribute values, and wherein within the second schema the first property is describe by a property reference to the first property in the first schema that includes the plurality of contextual attributes associated with a second plurality of contextual attribute values and applies the static attributes from the first schema to a definition of the first property in the second schema, wherein a contextual attribute value for a contextual attribute in the first schema is different than the contextual attribute value for the contextual attribute in the second schema; receiving a request for an aggregated first property description of the first property based on the first schema and the second schema; building, at a computing device, the aggregated first property description from the plurality of static attributes and the plurality of contextual attributes associated with contextual attributes selected from either the first plurality of contextual attribute values or the second plurality of contextual attribute values; and communicating the aggregated first property description. | 8. A method for aggregating property attribute values across two or more schemas associated with two or more data sources, the method comprising: receiving at least a first schema and a second schema that both include a first property, wherein within the first schema the first property is described by a plurality of static attributes and a plurality of contextual attributes associated with a first plurality of contextual attribute values, and wherein within the second schema the first property is describe by a property reference to the first property in the first schema that includes the plurality of contextual attributes associated with a second plurality of contextual attribute values and applies the static attributes from the first schema to a definition of the first property in the second schema, wherein a contextual attribute value for a contextual attribute in the first schema is different than the contextual attribute value for the contextual attribute in the second schema; receiving a request for an aggregated first property description of the first property based on the first schema and the second schema; building, at a computing device, the aggregated first property description from the plurality of static attributes and the plurality of contextual attributes associated with contextual attributes selected from either the first plurality of contextual attribute values or the second plurality of contextual attribute values; and communicating the aggregated first property description. 13. The method of claim 8 , wherein the aggregated first property description is communicated to a search utility. | 0.839437 |
6,069,939 | 1 | 9 | 1. A method for providing a called party with audio prompts in a language selected by a calling party, comprising the steps of determining a geographic location of said called party; selecting a language or dialect previously determined by said calling party from a plurality of languages for delivery of audio prompts to said called party based on a determined geographic location of said called party; and providing said called party with audio prompts in the selected language. | 1. A method for providing a called party with audio prompts in a language selected by a calling party, comprising the steps of determining a geographic location of said called party; selecting a language or dialect previously determined by said calling party from a plurality of languages for delivery of audio prompts to said called party based on a determined geographic location of said called party; and providing said called party with audio prompts in the selected language. 9. The method of claim 1, wherein said selecting language step includes the step of selecting a language that corresponds to a dialed country. | 0.759322 |
8,996,514 | 9 | 12 | 9. A computer-readable storage device including instructions that, when executed by a processor, cause performance of operations that comprise: receiving, by a computing system, a query that was defined by user input at a computing device; identifying, by the computing system, documents that are responsive to the received query, wherein the documents that are responsive to the received query include a particular document; identifying, by the computing system, that the particular document matches another document; identifying, by the computing system, information that reflects a ranking of the another document as a result for one or more queries; determining, by the computing system and in response to having identified the information that reflects the ranking of the another document as the result for the one or more queries, a score to assign to the particular document using the information that reflects the ranking of the another document as the result for the one or more queries, wherein the computing system has determined a score to assign to each of the documents that are responsive to the received query; ranking, by the computing system and in response to having received the query, each of the documents that are responsive to the received query using the scores that have been assigned to the documents that are responsive to the received query, including the determined score that was assigned to the particular document, to generate a ranking of the documents that are responsive to the received query; and providing, by the computing system and in response to having received the query, information for receipt by the computing device so as to cause the computing device to present a display of search results that identify the documents that are responsive to the received query and that are presented in an order that is defined by the generated ranking. | 9. A computer-readable storage device including instructions that, when executed by a processor, cause performance of operations that comprise: receiving, by a computing system, a query that was defined by user input at a computing device; identifying, by the computing system, documents that are responsive to the received query, wherein the documents that are responsive to the received query include a particular document; identifying, by the computing system, that the particular document matches another document; identifying, by the computing system, information that reflects a ranking of the another document as a result for one or more queries; determining, by the computing system and in response to having identified the information that reflects the ranking of the another document as the result for the one or more queries, a score to assign to the particular document using the information that reflects the ranking of the another document as the result for the one or more queries, wherein the computing system has determined a score to assign to each of the documents that are responsive to the received query; ranking, by the computing system and in response to having received the query, each of the documents that are responsive to the received query using the scores that have been assigned to the documents that are responsive to the received query, including the determined score that was assigned to the particular document, to generate a ranking of the documents that are responsive to the received query; and providing, by the computing system and in response to having received the query, information for receipt by the computing device so as to cause the computing device to present a display of search results that identify the documents that are responsive to the received query and that are presented in an order that is defined by the generated ranking. 12. The computer-readable storage device of claim 9 , wherein the operations further comprise: determining that the another document has been created for display on a non-mobile device; and determining that the particular document is a version of the another document that is different than the another document and that has been created for display on a mobile device. | 0.644509 |
9,058,644 | 16 | 17 | 16. The computing device of claim 15 , wherein identifying the first region includes prompting a user of the computing device to select the first region. | 16. The computing device of claim 15 , wherein identifying the first region includes prompting a user of the computing device to select the first region. 17. The computing device of claim 16 , wherein the instructions, when executed by the processor, further enable the computing device to: obtain a second image; identify a second region in the second image based at least in part on previous selections by the at least one of the user or multiple other user on previous images; and process the at least one second region with the visual recognition technique. | 0.5 |
8,626,862 | 28 | 29 | 28. The system of claim 26 wherein the status information comprises an indicator indicating that the first person is currently engaged in conversation with another person. | 28. The system of claim 26 wherein the status information comprises an indicator indicating that the first person is currently engaged in conversation with another person. 29. The system of claim 28 wherein the indicator indicates that the first person is currently engaged in conversation using one of voice conversation mode, voice/video conversation mode, and graphic text-based conversation mode. | 0.5 |
9,946,783 | 8 | 11 | 8. A computer system comprising: one or more memory elements for storing a set of documents that have been classified within a hierarchical taxonomy using a classification algorithm; and one or more processors coupled to the one or more memory elements and including instructions that, when executed, cause the one or more processors to perform operations comprising: identifying, within the set of documents that have been classified within a hierarchical taxonomy using a classification algorithm, documents having a classification confidence level that is below a predetermined confidence level threshold; disassociating the identified documents from their respective classifications based on the classification level being below the predetermined confidence level threshold; obtaining, from a different classifier, a new classification within the hierarchical taxonomy for each of the identified documents; associating each of the newly classified documents with a highest classification confidence level for its respective new classification; including the newly classified documents in a trusted corpus of documents that are used to train the classification algorithm; determining a distribution of classifications of the newly classified documents within the trusted corpus of documents; updating the classification algorithm based on the trusted corpus of documents, such that the classification algorithm is configured to classify documents to promote a classification distribution that is in accordance with the determined distribution of classifications; and applying the updated classification algorithm to at least a portion of the set of documents to obtain new classifications within the taxonomy or new classification confidence levels for the portion of the set of documents, such that the at least a portion of the set of documents are classified in accordance with the classification distribution. | 8. A computer system comprising: one or more memory elements for storing a set of documents that have been classified within a hierarchical taxonomy using a classification algorithm; and one or more processors coupled to the one or more memory elements and including instructions that, when executed, cause the one or more processors to perform operations comprising: identifying, within the set of documents that have been classified within a hierarchical taxonomy using a classification algorithm, documents having a classification confidence level that is below a predetermined confidence level threshold; disassociating the identified documents from their respective classifications based on the classification level being below the predetermined confidence level threshold; obtaining, from a different classifier, a new classification within the hierarchical taxonomy for each of the identified documents; associating each of the newly classified documents with a highest classification confidence level for its respective new classification; including the newly classified documents in a trusted corpus of documents that are used to train the classification algorithm; determining a distribution of classifications of the newly classified documents within the trusted corpus of documents; updating the classification algorithm based on the trusted corpus of documents, such that the classification algorithm is configured to classify documents to promote a classification distribution that is in accordance with the determined distribution of classifications; and applying the updated classification algorithm to at least a portion of the set of documents to obtain new classifications within the taxonomy or new classification confidence levels for the portion of the set of documents, such that the at least a portion of the set of documents are classified in accordance with the classification distribution. 11. The system of claim 8 , wherein updating the classification algorithm includes applying a supervised learning model that analyzes the trusted corpus to identify one or more attributes that are associated with classifications of documents in the trusted corpus. | 0.648 |
7,779,029 | 5 | 6 | 5. The machine-readable medium of claim 2 wherein said object-oriented code for refreshing said database query is defined within a first object-oriented class and said object-oriented code for refreshing said user interface screen is defined within a second object-oriented class. | 5. The machine-readable medium of claim 2 wherein said object-oriented code for refreshing said database query is defined within a first object-oriented class and said object-oriented code for refreshing said user interface screen is defined within a second object-oriented class. 6. The machine-readable medium of claim 5 wherein said instantiation of said object-oriented code for refreshing said user interface screen comprises instantiating an instance of said first object-oriented class and setting data members of said instance based on attributes of the markup language element representing said refreshing of said user interface screen, and wherein said instantiation of said object-oriented code for refreshing said database query comprises instantiating an instance of said second object-oriented class and setting data members of said instance of said second object-oriented class based on attributes of the markup language element representing said refreshing of said database query. | 0.5 |
8,639,522 | 21 | 22 | 21. The computer program product as in claim 20 , wherein determining the likelihood of the provided service co-occurring with the historical service in order to determine the overall inconsistency metric further comprises: determining, by the at least one data processor, for each combination of the provided service and a historical service received by the client, an inconsistency value; and determining, by the at least one data processor, a metric of the inconsistency values. | 21. The computer program product as in claim 20 , wherein determining the likelihood of the provided service co-occurring with the historical service in order to determine the overall inconsistency metric further comprises: determining, by the at least one data processor, for each combination of the provided service and a historical service received by the client, an inconsistency value; and determining, by the at least one data processor, a metric of the inconsistency values. 22. The computer program product of claim 21 wherein services provided to the client by the provider are excluded from the client historical data used to determine the overall inconsistency metric. | 0.5 |
7,747,442 | 12 | 14 | 12. A computer-readable storage medium, including an instruction set stored thereon, which when executed by a processor of a computer causes the computer to: present one or more user interfaces through which to receive input to define and manipulate properties of a graphical listen element, the properties identifying one or more data sources; and build a speech recognition program grammar as a function of one or more graphical listen elements, the grammar including a representation of data retrieved from the one or more data sources, wherein building the grammar includes: for each of the one or more data sources, retrieving the data into a respective local table; for each local table, identifying matches between data in the local table with over-ride entries; and for each identified match with an over-ride entry, delete the matching entry in the local table and insert data from an over-ride configuration; and store, on a data storage device, at least one of the graphical listen element, the manipulated properties of the graphical listen element, and the grammar. | 12. A computer-readable storage medium, including an instruction set stored thereon, which when executed by a processor of a computer causes the computer to: present one or more user interfaces through which to receive input to define and manipulate properties of a graphical listen element, the properties identifying one or more data sources; and build a speech recognition program grammar as a function of one or more graphical listen elements, the grammar including a representation of data retrieved from the one or more data sources, wherein building the grammar includes: for each of the one or more data sources, retrieving the data into a respective local table; for each local table, identifying matches between data in the local table with over-ride entries; and for each identified match with an over-ride entry, delete the matching entry in the local table and insert data from an over-ride configuration; and store, on a data storage device, at least one of the graphical listen element, the manipulated properties of the graphical listen element, and the grammar. 14. The computer-readable medium of claim 12 , wherein the graphical listen element properties allow a representation of one or more words and phrases to be included in the grammar. | 0.666052 |
10,073,913 | 26 | 27 | 26. The system of claim 25 , wherein the server is further configured to determine the intent weight associated with the search query. | 26. The system of claim 25 , wherein the server is further configured to determine the intent weight associated with the search query. 27. The system of claim 26 , wherein in order to determine the intent weight associated with the search query, the server is configured to parse the search query to determine a search intent parameter and a results intent parameter. | 0.5 |
7,657,832 | 10 | 12 | 10. A computer program product tangibly embodied in a machine-readable storage device for correcting an XML electronic document, the XML electronic document having a structure, the product comprising instructions operable to cause one or more data processing apparatus to perform operations comprising: identifying a validation error in the XML electronic document structure, the validation error being an aspect of the XML electronic document structure that fails to conform to rules of an XML document type definition or an XML schema, the rules being associated with the XML electronic document, the validation error being of a particular kind, wherein identifying the validation error comprises building a deterministic finite automaton from a content model defined in a document type definition of the XML electronic document and identifying the validation error using the deterministic finite automaton; selecting a suggestion template from among multiple suggestion templates according to the particular kind of the validation error, and using the selected suggestion template to suggest to a user suggested corrections that are predefined in the template for the particular kind of validation error, the selected suggestion template including logic necessary for modifying the XML electronic document structure in conformance with the rules of the XML document type definition or the XML schema, wherein modifying the XML electronic document structure comprises retagging an element in the XML electronic document structure and moving an element from a current location to a new location in the XML electronic document structure; receiving an input selecting one of the suggested corrections; and using the logic in the selected suggestion template to apply the correction selected by the input to the XML electronic document. | 10. A computer program product tangibly embodied in a machine-readable storage device for correcting an XML electronic document, the XML electronic document having a structure, the product comprising instructions operable to cause one or more data processing apparatus to perform operations comprising: identifying a validation error in the XML electronic document structure, the validation error being an aspect of the XML electronic document structure that fails to conform to rules of an XML document type definition or an XML schema, the rules being associated with the XML electronic document, the validation error being of a particular kind, wherein identifying the validation error comprises building a deterministic finite automaton from a content model defined in a document type definition of the XML electronic document and identifying the validation error using the deterministic finite automaton; selecting a suggestion template from among multiple suggestion templates according to the particular kind of the validation error, and using the selected suggestion template to suggest to a user suggested corrections that are predefined in the template for the particular kind of validation error, the selected suggestion template including logic necessary for modifying the XML electronic document structure in conformance with the rules of the XML document type definition or the XML schema, wherein modifying the XML electronic document structure comprises retagging an element in the XML electronic document structure and moving an element from a current location to a new location in the XML electronic document structure; receiving an input selecting one of the suggested corrections; and using the logic in the selected suggestion template to apply the correction selected by the input to the XML electronic document. 12. The computer program product of claim 10 , wherein: suggesting changes to the user includes suggesting a plurality of changes to the user in an order determined by predefined user preferences, the predefined user preferences including ranking particular changes higher than other changes. | 0.742504 |
9,043,314 | 16 | 17 | 16. The method of claim 1 , further comprising: associating each of the one or more keywords in the search string with each of the one or more websites associated with the category stored in the data store, and raising a third assigned rating for each of the one or more websites upon association with a keyword of the one or more keywords in said search string, wherein the results are also modified based on the third assigned rating. | 16. The method of claim 1 , further comprising: associating each of the one or more keywords in the search string with each of the one or more websites associated with the category stored in the data store, and raising a third assigned rating for each of the one or more websites upon association with a keyword of the one or more keywords in said search string, wherein the results are also modified based on the third assigned rating. 17. The method of claim 16 , further comprising: associating each of the one or more keywords in the search string with the category stored in the data store, and raising a fourth assigned rating for each of the one or more keywords in the search string upon association with the category, wherein the results are also modified based on the the fourth assigned rating. | 0.5 |
9,251,224 | 1 | 9 | 1. A computer-implemented method performed by data processing apparatus comprising one or more computers in data communication, the method comprising: receiving queries, each query submitted for a respective first search operation; for each query: initiating the first search operation and receiving data indicating first resources identified by the first search operation as being responsive the query, each first resource having a corresponding score by which the first resource can be ranked in responsiveness to the query relative to other first resources; determining a search probability ratio for the query, the search probability ratio being a measure of a likelihood of the query being submitted for a second search operation, the second search operation being of search operation type that is different from a search operation type of the first search operation; initiating the second search operation and receiving data indicating second resources identified by the second search operation as being responsive the query, each second resource having a corresponding score by which the second resource can be ranked in responsiveness to the query relative to other second resources; determining, for a second resource identified by the second search operation, a first resource identified by the first search operation that is descriptive of a second resource; determining, based on the search probability ratio, the corresponding score of the first resource, and the corresponding score of the second resource, whether to insert a search result identifying the second resource in a set of search results identifying the first resources; and for each query for which a determination is made to insert a search result identifying the second resource in a set of search results identifying the first resources, inserting the search result identifying the second resource in the set of search results identifying the first resources. | 1. A computer-implemented method performed by data processing apparatus comprising one or more computers in data communication, the method comprising: receiving queries, each query submitted for a respective first search operation; for each query: initiating the first search operation and receiving data indicating first resources identified by the first search operation as being responsive the query, each first resource having a corresponding score by which the first resource can be ranked in responsiveness to the query relative to other first resources; determining a search probability ratio for the query, the search probability ratio being a measure of a likelihood of the query being submitted for a second search operation, the second search operation being of search operation type that is different from a search operation type of the first search operation; initiating the second search operation and receiving data indicating second resources identified by the second search operation as being responsive the query, each second resource having a corresponding score by which the second resource can be ranked in responsiveness to the query relative to other second resources; determining, for a second resource identified by the second search operation, a first resource identified by the first search operation that is descriptive of a second resource; determining, based on the search probability ratio, the corresponding score of the first resource, and the corresponding score of the second resource, whether to insert a search result identifying the second resource in a set of search results identifying the first resources; and for each query for which a determination is made to insert a search result identifying the second resource in a set of search results identifying the first resources, inserting the search result identifying the second resource in the set of search results identifying the first resources. 9. The computer-implemented method of claim 1 , wherein inserting the search result identifying the second resource in the set of search results identifying the first resources comprises replacing a search result identifying a first resource that is descriptive of a second resource with a search result that identities the second resource. | 0.748892 |
9,547,420 | 16 | 17 | 16. A computing device, comprising: a processor; and a memory device including instructions that, when executed by the processor, cause the computing device to: obtain character input entered into an interface of a computing device; analyze the character input to determine a plurality of suggestions for completing words, the plurality of suggestions are based at least in part upon the character input, the suggestions having respective confidence scores, wherein a first suggestion of the plurality of suggestions is designated as one of a correction type, a common base portion type, or a completion type, the common base portion type including at least a root word, the completion type including at least a corresponding completing word; determine a spatial layout of at least a portion of the plurality of suggestions, a location of a suggestion of the portion being determined based, at least in part, upon the respective confidence score of the suggestion, wherein first suggestions that share a same completion type are grouped together in a first group, second suggestions that share a same correction type are grouped together in a second group, and third suggestions that share a same common base portion type are grouped together in a third group; display the at least the portion of the plurality of suggestions arranged according to the spatial layout, wherein the first suggestions that form the first group, the second suggestions that form the second group and the third suggestions that form the third group are displayed proximate to one another in the spatial layout; detect a user selection of a specified selection of the plurality of suggestions displayed according to the spatial layout; and modify the character input to correspond to the specified selection. | 16. A computing device, comprising: a processor; and a memory device including instructions that, when executed by the processor, cause the computing device to: obtain character input entered into an interface of a computing device; analyze the character input to determine a plurality of suggestions for completing words, the plurality of suggestions are based at least in part upon the character input, the suggestions having respective confidence scores, wherein a first suggestion of the plurality of suggestions is designated as one of a correction type, a common base portion type, or a completion type, the common base portion type including at least a root word, the completion type including at least a corresponding completing word; determine a spatial layout of at least a portion of the plurality of suggestions, a location of a suggestion of the portion being determined based, at least in part, upon the respective confidence score of the suggestion, wherein first suggestions that share a same completion type are grouped together in a first group, second suggestions that share a same correction type are grouped together in a second group, and third suggestions that share a same common base portion type are grouped together in a third group; display the at least the portion of the plurality of suggestions arranged according to the spatial layout, wherein the first suggestions that form the first group, the second suggestions that form the second group and the third suggestions that form the third group are displayed proximate to one another in the spatial layout; detect a user selection of a specified selection of the plurality of suggestions displayed according to the spatial layout; and modify the character input to correspond to the specified selection. 17. The computing device of claim 16 , wherein the instructions when executed further cause the computing device to: determine at least one font characteristic for a suggestion of the spatial layout based at least in part upon the respective confidence score of the suggestion, the font characteristic including at least one of font size, font style, font color, font bold level, font italicize level, font animation, and font angle. | 0.5 |
8,380,733 | 17 | 18 | 17. A non-transitory computer readable medium encoded with software comprising executable instructions that when executed are operable to: detect an original search input entered by a user; detect an excluded term included within the original search input; delete the excluded term from the original search input to create a modified search input without the excluded term; match the modified search input without the excluded term against a plurality of stored terms as the original search input is entered by the user; display, in response to there being a match between the modified search input without the excluded term and one or more of the plurality of stored terms, a suggestion of a search term dynamically to replace the original search input as the original search is entered by the user based on the match between the modified search input without the excluded term and the one or more stored terms; add the excluded term from the original search back to the modified input; match the modified search input with the excluded term to the plurality of stored terms to determine if there is a match; and display, in response to there not being a match between the modified search input without the excluded term and one or more of the plurality of stored terms, a suggestion of a search term dynamically to replace the original search input as the original search is entered by the user based on a match between the original search input and one or more of the plurality of stored terms. | 17. A non-transitory computer readable medium encoded with software comprising executable instructions that when executed are operable to: detect an original search input entered by a user; detect an excluded term included within the original search input; delete the excluded term from the original search input to create a modified search input without the excluded term; match the modified search input without the excluded term against a plurality of stored terms as the original search input is entered by the user; display, in response to there being a match between the modified search input without the excluded term and one or more of the plurality of stored terms, a suggestion of a search term dynamically to replace the original search input as the original search is entered by the user based on the match between the modified search input without the excluded term and the one or more stored terms; add the excluded term from the original search back to the modified input; match the modified search input with the excluded term to the plurality of stored terms to determine if there is a match; and display, in response to there not being a match between the modified search input without the excluded term and one or more of the plurality of stored terms, a suggestion of a search term dynamically to replace the original search input as the original search is entered by the user based on a match between the original search input and one or more of the plurality of stored terms. 18. The non-transitory computer readable medium of claim 17 , wherein the executable instructions when executed are further operable to: replace, in response to there not being a match between the modified search input without the excluded term and one or more of the plurality of stored terms, the original search input with the suggestion of the search term. | 0.589977 |
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