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9,477,749 | 33 | 40 | 33. A non-transitory computer readable storage medium comprising instructions that if executed enables a computing system to: access unstructured data from one or more sources of text; process text from the unstructured data to extract features from the unstructured data; receive an instruction to execute a report from a user; receive an instruction to determine the one or more causal factors associated with an observation selected by the user; determine a baseline for comparison with the selected observation, the baseline being determined by the user as either data comprising one or more features in which the observation is not present or the data originating in a particular time period comprising one or more features in which the observation is present; determine the one or more causal factors associated with the selected observation by calculating an impact of one or more of the features of the unstructured data on the observation selected by the user using the baseline for comparison with the observation selected, at least one of the one or more causal factors comprising one or more of the features, and the impact on a measurable characteristic of the observation selected being calculated based on a comparison of one or more of the features of the unstructured data associated with the presence of the observation and features of the unstructured data associated with the baseline, the measurable characteristic being a volume-based metric, a sentiment metric, a satisfaction metric, or another user-defined metric; rank the one or more causal factors based on a measure of statistical association to the selected observation; and present results to the user. | 33. A non-transitory computer readable storage medium comprising instructions that if executed enables a computing system to: access unstructured data from one or more sources of text; process text from the unstructured data to extract features from the unstructured data; receive an instruction to execute a report from a user; receive an instruction to determine the one or more causal factors associated with an observation selected by the user; determine a baseline for comparison with the selected observation, the baseline being determined by the user as either data comprising one or more features in which the observation is not present or the data originating in a particular time period comprising one or more features in which the observation is present; determine the one or more causal factors associated with the selected observation by calculating an impact of one or more of the features of the unstructured data on the observation selected by the user using the baseline for comparison with the observation selected, at least one of the one or more causal factors comprising one or more of the features, and the impact on a measurable characteristic of the observation selected being calculated based on a comparison of one or more of the features of the unstructured data associated with the presence of the observation and features of the unstructured data associated with the baseline, the measurable characteristic being a volume-based metric, a sentiment metric, a satisfaction metric, or another user-defined metric; rank the one or more causal factors based on a measure of statistical association to the selected observation; and present results to the user. 40. The non-transitory computer readable storage medium of claim 33 , further comprising instructions that if executed enable the computing system to: extract metadata from unstructured text documents. | 0.863265 |
8,510,249 | 42 | 52 | 42. The computer-readable recording medium according to claim 41 , wherein the computer is further caused to execute the step of: (c) generating a plurality of the units of analysis from the text information, wherein in the step (b), the density is estimated for each unit of analysis generated in the step (c). | 42. The computer-readable recording medium according to claim 41 , wherein the computer is further caused to execute the step of: (c) generating a plurality of the units of analysis from the text information, wherein in the step (b), the density is estimated for each unit of analysis generated in the step (c). 52. The computer-readable recording medium according to claim 42 , wherein the computer is further caused to execute the steps of: (d) generating training data from training text information including information indicating whether or not each sentence of the training text information is the target information, by generating a plurality of units of training each composed of a plurality of sentences of the training text information, from the training text information in accordance with a setting condition, setting, for each unit of training, a target information density indicating an amount of the target information included in the unit of training, with reference to information indicating whether or not each sentence of the unit of training is the target information, further obtaining, for each unit of training, a feature quantity from information acquired from a word or a clause in each sentence of the unit of training, and generating the target information density and the feature quantity of each unit of training as the training data; and (e) learning a density estimation model usable in the density estimation performed in the step (a), using the training data generated in the step (d), wherein in the step (a), for each unit of analysis, the density is estimated in accordance with the density estimation model acquired in the step (e). | 0.5 |
9,881,009 | 1 | 4 | 1. A computer-implemented method, comprising: under control of one or more processors configured with executable instructions, receiving, from a device of an author and via a content ingestion service associated with a network, an electronic book having first body text and first metadata; normalizing the electronic book by removing illustrations from the electronic book, removing extraneous characters from the electronic book, and converting characters of the electronic book to a single case; determining, in response to the normalizing of the electronic book, whether the first metadata of the electronic book matches metadata of any existing book title sets; based at least partly on a first determination that the first metadata of the electronic book matches second metadata of no more than a single existing book title set that includes at least one book, adding the electronic book to the single existing book title set such that the single existing book title set includes the at least one book and the electronic book; based at least partly on a second determination that the first metadata of the electronic book matches third metadata of multiple existing book title sets, calculating a text matching score corresponding to individual ones of the existing book title sets, the text matching score indicating a comparison of a first frequency of one or more words included in the first body text of the electronic book and a second frequency of the one or more words included in second body text of the corresponding existing book title set; and adding the electronic book to an existing book title set of the multiple existing book title sets based at least partly on the text matching score corresponding to the existing book title set being greater than a specified threshold, the existing book title set including the electronic book and one or more other books. | 1. A computer-implemented method, comprising: under control of one or more processors configured with executable instructions, receiving, from a device of an author and via a content ingestion service associated with a network, an electronic book having first body text and first metadata; normalizing the electronic book by removing illustrations from the electronic book, removing extraneous characters from the electronic book, and converting characters of the electronic book to a single case; determining, in response to the normalizing of the electronic book, whether the first metadata of the electronic book matches metadata of any existing book title sets; based at least partly on a first determination that the first metadata of the electronic book matches second metadata of no more than a single existing book title set that includes at least one book, adding the electronic book to the single existing book title set such that the single existing book title set includes the at least one book and the electronic book; based at least partly on a second determination that the first metadata of the electronic book matches third metadata of multiple existing book title sets, calculating a text matching score corresponding to individual ones of the existing book title sets, the text matching score indicating a comparison of a first frequency of one or more words included in the first body text of the electronic book and a second frequency of the one or more words included in second body text of the corresponding existing book title set; and adding the electronic book to an existing book title set of the multiple existing book title sets based at least partly on the text matching score corresponding to the existing book title set being greater than a specified threshold, the existing book title set including the electronic book and one or more other books. 4. The computer-implemented method of claim 1 , wherein calculating the text matching score comprises evaluating page alignment between the electronic book and the existing book title set. | 0.667845 |
7,551,187 | 1 | 4 | 1. A computer system that facilitates free form digital inking, comprising: a pen-based microprocessor device and an application program, the application program is recorded on a computer-readable medium and capable of execution by a computer, the application program comprising: an input device for activating an inking region within a zoom window; an annotation management component that generates the zoom window comprising the inking region for an underlying digital document; and a navigation component that manually and automatically re-positions and re-sizes the zoom window and the inking region relative to the digital document, the re-position and re-size of the zoom window and the inking region occurs at least as an annotation of the digital document is entered in the inking region during an annotation event based at least in part on an amount of annotation information entered and displayed in the inking region, the size of the zoom window corresponds to the size of the inking region. | 1. A computer system that facilitates free form digital inking, comprising: a pen-based microprocessor device and an application program, the application program is recorded on a computer-readable medium and capable of execution by a computer, the application program comprising: an input device for activating an inking region within a zoom window; an annotation management component that generates the zoom window comprising the inking region for an underlying digital document; and a navigation component that manually and automatically re-positions and re-sizes the zoom window and the inking region relative to the digital document, the re-position and re-size of the zoom window and the inking region occurs at least as an annotation of the digital document is entered in the inking region during an annotation event based at least in part on an amount of annotation information entered and displayed in the inking region, the size of the zoom window corresponds to the size of the inking region. 4. The system of claim 1 , wherein the inking region is generated to cover a subset of the digital document such that the remaining document can be concurrently viewed. | 0.626667 |
8,428,944 | 11 | 14 | 11. A system according to claim 10 wherein: said speech recognition engine comprises an acoustic model with the plurality of adjustable parameters; the difference engine matches the at least one of the plurality of acoustic differences to a matched adjustable parameter of the plurality of adjustable parameters; and the compensation controller adjusts the acoustic model by varying the matched adjustable parameter to reflect the at least one of the plurality of acoustic differences. | 11. A system according to claim 10 wherein: said speech recognition engine comprises an acoustic model with the plurality of adjustable parameters; the difference engine matches the at least one of the plurality of acoustic differences to a matched adjustable parameter of the plurality of adjustable parameters; and the compensation controller adjusts the acoustic model by varying the matched adjustable parameter to reflect the at least one of the plurality of acoustic differences. 14. A speech recognition system according to claim 11 wherein the compensation controller varies the matched adjustable parameter as a function of a magnitude of the corresponding at least one of the plurality of acoustic differences. | 0.74115 |
8,332,373 | 9 | 13 | 9. The method of claim 1 , further comprising representing the predicate expression with an operator-based parse tree structure if the indicator has a first value, and representing the predicate expression with a function-based parse tree structure if the indicator has a second value, the operator-based parse tree structure and function-based parse tree structure being two of the plural types of data structures. | 9. The method of claim 1 , further comprising representing the predicate expression with an operator-based parse tree structure if the indicator has a first value, and representing the predicate expression with a function-based parse tree structure if the indicator has a second value, the operator-based parse tree structure and function-based parse tree structure being two of the plural types of data structures. 13. The method of claim 9 , further comprising storing the indicator in a data dictionary table associated with the user-defined routine. | 0.6575 |
8,529,270 | 1 | 2 | 1. An interactive system for instructing and assessing achievement of preschool students with enablement of instructor assistance utilizing a computer with a display screen, a speaker and manually operated means for indicating and selecting a displayed component on the display screen, comprising: means for generating an animated cartoon with a plurality of displayed components recognizable by a preschool student on a first portion of the display screen along with an accompanying vocal story on the speaker; interactive means for enabling the manually operated means for user selection of one of the plurality of displayed components in the generated cartoon; the cartoon and accompanying vocal story requesting use of the manually operated selecting means to select a displayed component having a predefined aspect representative of an educational goal; means responsive to operation of the manually operated means selecting the displayed component having the predefined aspect for indicating achievement of the educational goal; and means for generating a written instruction on a second portion of the display screen to provide instructions for the instructor in assistance of the preschool student. | 1. An interactive system for instructing and assessing achievement of preschool students with enablement of instructor assistance utilizing a computer with a display screen, a speaker and manually operated means for indicating and selecting a displayed component on the display screen, comprising: means for generating an animated cartoon with a plurality of displayed components recognizable by a preschool student on a first portion of the display screen along with an accompanying vocal story on the speaker; interactive means for enabling the manually operated means for user selection of one of the plurality of displayed components in the generated cartoon; the cartoon and accompanying vocal story requesting use of the manually operated selecting means to select a displayed component having a predefined aspect representative of an educational goal; means responsive to operation of the manually operated means selecting the displayed component having the predefined aspect for indicating achievement of the educational goal; and means for generating a written instruction on a second portion of the display screen to provide instructions for the instructor in assistance of the preschool student. 2. An interactive instructing and assessing system as claimed in claim 1 wherein the plurality of displayed components include cartoon characters. | 0.85041 |
9,069,768 | 1 | 3 | 1. A system for creating subgroups of documents using optical character recognition data, the system comprising: one or more processors; and a non-transitory computer readable medium storing a plurality of instructions, which when executed, cause the one or more processors to: create a matrix for words included in documents, wherein each column-row combination in the matrix indicates whether a corresponding word that is associated with the column-row combination is included in a corresponding document that is associated with the column-row combination; identify distances between pairs of the words in the matrix, wherein each distance is based on a number of the documents that differ in including a corresponding pair of the words; create word clusters, wherein each word cluster comprises pairs of words associated with a corresponding distance less than a distance threshold; create sets of word clusters, wherein a set of word clusters comprises word clusters that are not associated with any of the documents associated with other word clusters in the set of word clusters; and create subgroups of the digitized documents based on a set of word clusters corresponding to a high word score relative to at least one other word score corresponding to at least one other set of word clusters. | 1. A system for creating subgroups of documents using optical character recognition data, the system comprising: one or more processors; and a non-transitory computer readable medium storing a plurality of instructions, which when executed, cause the one or more processors to: create a matrix for words included in documents, wherein each column-row combination in the matrix indicates whether a corresponding word that is associated with the column-row combination is included in a corresponding document that is associated with the column-row combination; identify distances between pairs of the words in the matrix, wherein each distance is based on a number of the documents that differ in including a corresponding pair of the words; create word clusters, wherein each word cluster comprises pairs of words associated with a corresponding distance less than a distance threshold; create sets of word clusters, wherein a set of word clusters comprises word clusters that are not associated with any of the documents associated with other word clusters in the set of word clusters; and create subgroups of the digitized documents based on a set of word clusters corresponding to a high word score relative to at least one other word score corresponding to at least one other set of word clusters. 3. The system of claim 1 , wherein the documents comprise digitized optical character recognition data. | 0.707386 |
8,775,183 | 13 | 14 | 13. An article comprising a storage medium containing instructions that if executed enable a system to: receive a request to recognize speech from an application; recognize the speech to form a recognized word sequence; transform the recognized word sequence according to a user-specified behavior requirement encoded into an input speech recognition grammar specification, wherein the user-specified behavior requirement changes a setting prior to recognizing speech to the input speech recognition grammar to select or de-select a built-in transformation from a set of built-in transformations of a speech recognition system to apply to recognized speech, and wherein the user-specified behavior requirement includes a semantic tag that specifies at least one of: a proper name, a phone number, an address, an email address, an internet protocol address, and a web address; and provide the transformed sequence to the application. | 13. An article comprising a storage medium containing instructions that if executed enable a system to: receive a request to recognize speech from an application; recognize the speech to form a recognized word sequence; transform the recognized word sequence according to a user-specified behavior requirement encoded into an input speech recognition grammar specification, wherein the user-specified behavior requirement changes a setting prior to recognizing speech to the input speech recognition grammar to select or de-select a built-in transformation from a set of built-in transformations of a speech recognition system to apply to recognized speech, and wherein the user-specified behavior requirement includes a semantic tag that specifies at least one of: a proper name, a phone number, an address, an email address, an internet protocol address, and a web address; and provide the transformed sequence to the application. 14. The article of claim 13 , further comprising instructions that if executed enable the system to transform the recognized word sequence according to at least one of the user-specified behavior requirement or a user-specified transformation requirement, wherein the user-specified transformation requirement includes a semantic tag that specifies at least one of: a proper name, a phone number, an address, an email address, an internet protocol address, and a web address. | 0.5 |
8,433,568 | 1 | 2 | 1. A method for measuring speech intelligibility, the method comprising the steps of: inputting a speech waveform; extracting at least one acoustic feature from the waveform; segmenting at least one phoneme from the at least one first acoustic feature; extracting at least one acoustic correlate measure from the at least one phoneme; determining at least one intelligibility measure, wherein the determination is based upon a language; and mapping the at least one acoustic correlate measure to the at least one intelligibility measure, wherein mapping comprises a vector of at least one value that correspond to the at least one intelligibility measure, the at least one value corresponding to a degree to which the at least one intelligibility measure corresponds to the at least one phoneme. | 1. A method for measuring speech intelligibility, the method comprising the steps of: inputting a speech waveform; extracting at least one acoustic feature from the waveform; segmenting at least one phoneme from the at least one first acoustic feature; extracting at least one acoustic correlate measure from the at least one phoneme; determining at least one intelligibility measure, wherein the determination is based upon a language; and mapping the at least one acoustic correlate measure to the at least one intelligibility measure, wherein mapping comprises a vector of at least one value that correspond to the at least one intelligibility measure, the at least one value corresponding to a degree to which the at least one intelligibility measure corresponds to the at least one phoneme. 2. The method of claim 1 , wherein the speech waveform is input from a talker. | 0.695313 |
7,970,698 | 22 | 23 | 22. The non-transitory computer-readable medium of claim 17 , further comprising: program code for applying at least one of the plurality of decision rules to at least a portion of the information associated with the applicant to obtain an outcome associated with the at least one of the plurality of decision rules; program code for generating a test outcome associated with the at least one of the plurality of decision rules; and program code for displaying the test outcome on the user interface. | 22. The non-transitory computer-readable medium of claim 17 , further comprising: program code for applying at least one of the plurality of decision rules to at least a portion of the information associated with the applicant to obtain an outcome associated with the at least one of the plurality of decision rules; program code for generating a test outcome associated with the at least one of the plurality of decision rules; and program code for displaying the test outcome on the user interface. 23. The non-transitory computer-readable medium of claim 22 , wherein program code for generating the test outcome associated with the at least one of the plurality of decision rules further comprises: program code for modifying the at least one of the plurality of decision rules based at least in part on information associated with the outcome. | 0.745974 |
7,693,904 | 9 | 15 | 9. A method of determining a relation between search queries, the method comprising: maintaining a database that associates a search session with at least one search query which has been received from a user terminal during said search session, wherein the database is updated at predetermined time intervals, said database being stored in a memory; determining a total number of search sessions for each user terminal during a first time interval, by referring to said database; determining a first number of search sessions where a first search query is initially received and a second query is subsequently received from said each user terminal during said time interval, by referring to said database; determining a second number of search sessions where a third search query is received from said each user terminal during said time interval, by referring to said database; determining a third number of search sessions where said first search query and said second search query are initially received, and said third search query is subsequently received from said each user terminal during said time interval, by referring to said database; calculating conditional probability from comparing said determined first number of search sessions with said determined third number of search sessions; calculating correlation by using said total number of search sessions, said first number of search sessions, said second number of search sessions, and said third number of search sessions; and determining a relation between said first search query, said second search query and said third search query based, at least in part, upon said calculated conditional probability and said calculated correlations, wherein said steps of calculating conditional probability and calculating correlation are performed by a processor. | 9. A method of determining a relation between search queries, the method comprising: maintaining a database that associates a search session with at least one search query which has been received from a user terminal during said search session, wherein the database is updated at predetermined time intervals, said database being stored in a memory; determining a total number of search sessions for each user terminal during a first time interval, by referring to said database; determining a first number of search sessions where a first search query is initially received and a second query is subsequently received from said each user terminal during said time interval, by referring to said database; determining a second number of search sessions where a third search query is received from said each user terminal during said time interval, by referring to said database; determining a third number of search sessions where said first search query and said second search query are initially received, and said third search query is subsequently received from said each user terminal during said time interval, by referring to said database; calculating conditional probability from comparing said determined first number of search sessions with said determined third number of search sessions; calculating correlation by using said total number of search sessions, said first number of search sessions, said second number of search sessions, and said third number of search sessions; and determining a relation between said first search query, said second search query and said third search query based, at least in part, upon said calculated conditional probability and said calculated correlations, wherein said steps of calculating conditional probability and calculating correlation are performed by a processor. 15. The method of claim 9 , wherein a close relation between said first search query, said second search query and said third search query is determined when the conditional probability information is greater than a predetermined numerical value, and the numerical value changes based on a predetermined function which decreases according to an increase of the first search session number information. | 0.804581 |
9,775,013 | 6 | 9 | 6. An electronic device, comprising: a display; 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: generating a data analysis request using raw data; sending the data analysis request including the raw data to a remotely located server; in response to sending the data analysis request, receiving from the remotely located server a first reply including a plurality of static thumbnail graphical representations of the raw data, wherein each thumbnail graphical representation is associated with a respective type of chart; sending to the remotely located server a request comprising a user selection of one or more of the plurality of static thumbnail graphical representations; in response to sending the request comprising the user selection of the one or more static thumbnail graphical representations, receiving from the server a second reply comprising information to create an editable, graphical representation of the raw data corresponding to the one or more static thumbnail graphical representations; in response to receiving from the server the second reply: determining whether the portable electronic device stores locally in the memory one or more valid graphical display templates corresponding to the information to create the editable, graphical representation for display locally on the display of the portable electronic device; and in accordance with a determination that the portable electronic device stores locally in the memory the one or more valid graphical display templates corresponding to the information to create the editable, graphical representation: displaying the graphical representation of the raw data on the display using the one or more graphical display templates. | 6. An electronic device, comprising: a display; 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: generating a data analysis request using raw data; sending the data analysis request including the raw data to a remotely located server; in response to sending the data analysis request, receiving from the remotely located server a first reply including a plurality of static thumbnail graphical representations of the raw data, wherein each thumbnail graphical representation is associated with a respective type of chart; sending to the remotely located server a request comprising a user selection of one or more of the plurality of static thumbnail graphical representations; in response to sending the request comprising the user selection of the one or more static thumbnail graphical representations, receiving from the server a second reply comprising information to create an editable, graphical representation of the raw data corresponding to the one or more static thumbnail graphical representations; in response to receiving from the server the second reply: determining whether the portable electronic device stores locally in the memory one or more valid graphical display templates corresponding to the information to create the editable, graphical representation for display locally on the display of the portable electronic device; and in accordance with a determination that the portable electronic device stores locally in the memory the one or more valid graphical display templates corresponding to the information to create the editable, graphical representation: displaying the graphical representation of the raw data on the display using the one or more graphical display templates. 9. The device of claim 6 , wherein determining whether the portable electronic device stores locally in the memory one or more valid graphical display templates corresponding to the information to create the editable, graphical representation comprises determining if the one or more graphical display templates stored in the memory have expired. | 0.785626 |
9,582,270 | 1 | 2 | 1. A computer-implemented method for effective feature location in software code comprising: receiving a specification of a software feature implementation to be located in software code, generating a feature behavior model specifying one or more of: an action and/or entity “master” behavior and a action and/or entity “slave” behavior; accessing methods and related artifacts from a source code repository; generating an expressive behavior signature for an accessed method based on any related artifacts information; identifying one or more feature-related code scope methods exhibiting the feature implementation using the expressive behavior signature for the method and the generated feature behavior model associated with the feature description; generating a code behavior model for each one or more feature-related code scope method; determining a similarity between the feature behavior model and the code behavior models; and identifying and ranking a feature location feature-related code locations based on the similarity determining, wherein a hardware processor device performs one or more said receiving, said feature behavior model generating, said accessing, said analyzing, said expressive behavior signature generating, said feature-related code scope identifying, said code behavior model generating determining, and said feature-related code locations identifying and ranking. | 1. A computer-implemented method for effective feature location in software code comprising: receiving a specification of a software feature implementation to be located in software code, generating a feature behavior model specifying one or more of: an action and/or entity “master” behavior and a action and/or entity “slave” behavior; accessing methods and related artifacts from a source code repository; generating an expressive behavior signature for an accessed method based on any related artifacts information; identifying one or more feature-related code scope methods exhibiting the feature implementation using the expressive behavior signature for the method and the generated feature behavior model associated with the feature description; generating a code behavior model for each one or more feature-related code scope method; determining a similarity between the feature behavior model and the code behavior models; and identifying and ranking a feature location feature-related code locations based on the similarity determining, wherein a hardware processor device performs one or more said receiving, said feature behavior model generating, said accessing, said analyzing, said expressive behavior signature generating, said feature-related code scope identifying, said code behavior model generating determining, and said feature-related code locations identifying and ranking. 2. The method of claim 1 , wherein said generating a code behavior model comprises: initiating a static code analysis upon a current subject feature-related code scope method to generate a control flow graph (CFG) information for that method; and integrating said CFG information generated for each method and a signature information of a method's callees in said code behavior model, said generated control flow information resulting in an increased fine-grained code behavior model. | 0.705954 |
9,972,310 | 1 | 4 | 1. A method for training acoustic models in speech recognition systems, wherein the speech recognition system comprises a neural network, the method comprising the steps of: a. extracting acoustic features from a speech signal using the neural network; and b. processing the acoustic features into an acoustic model by the speech recognition system, wherein the neural network comprises at least one of: activation functions with parameters, prealigned feature data, and training, wherein the training is performed using a stochastic gradient descent method on a cost function, and wherein the cost function is a linear discriminant analysis cost function. | 1. A method for training acoustic models in speech recognition systems, wherein the speech recognition system comprises a neural network, the method comprising the steps of: a. extracting acoustic features from a speech signal using the neural network; and b. processing the acoustic features into an acoustic model by the speech recognition system, wherein the neural network comprises at least one of: activation functions with parameters, prealigned feature data, and training, wherein the training is performed using a stochastic gradient descent method on a cost function, and wherein the cost function is a linear discriminant analysis cost function. 4. The method of claim 1 , wherein the processing comprises using at least one of a maximum likelihood method and an expectation maximization method. | 0.5 |
8,508,489 | 17 | 18 | 17. A method comprising: receiving handwritten input entered via pointer interaction with a touch surface and displaying the handwritten input on a graphic surface presented on said touch surface; in response to a stationary pointer contact on the touch surface exceeding a first non-zero threshold duration, updating the graphic surface so as to provide a visual indication of the start of a potential input gesture entry; determining when a gesture has been input via pointer interaction with said touch surface following said updating, said gesture indicating a position in an application; in response to said gesture, performing recognition on the displayed handwritten input to convert the handwritten input into a different form; displaying the recognition result together with a clear result option; entering the converted handwritten input into said application substantially at the position indicated by said gesture and displaying the converted handwritten input on said touch surface when the displayed recognition result is selected; and clearing the recognition result when said clear result option is selected. | 17. A method comprising: receiving handwritten input entered via pointer interaction with a touch surface and displaying the handwritten input on a graphic surface presented on said touch surface; in response to a stationary pointer contact on the touch surface exceeding a first non-zero threshold duration, updating the graphic surface so as to provide a visual indication of the start of a potential input gesture entry; determining when a gesture has been input via pointer interaction with said touch surface following said updating, said gesture indicating a position in an application; in response to said gesture, performing recognition on the displayed handwritten input to convert the handwritten input into a different form; displaying the recognition result together with a clear result option; entering the converted handwritten input into said application substantially at the position indicated by said gesture and displaying the converted handwritten input on said touch surface when the displayed recognition result is selected; and clearing the recognition result when said clear result option is selected. 18. The method of claim 17 wherein said gesture is a stationary pointer contact on said touch surface that exceeds a threshold duration. | 0.575 |
8,265,991 | 3 | 6 | 3. The method of claim 2 further comprising, before executing the downloaded programming instructions: from the user, receiving order information associated with the order; and from the server computer, receiving product information associated with the purchase order, wherein executing the programming instructions to determine the applicability of the discount type comprises applying the downloaded programming instructions to the product and order information. | 3. The method of claim 2 further comprising, before executing the downloaded programming instructions: from the user, receiving order information associated with the order; and from the server computer, receiving product information associated with the purchase order, wherein executing the programming instructions to determine the applicability of the discount type comprises applying the downloaded programming instructions to the product and order information. 6. The method of claim 3 , wherein: the programming instructions comprise a rule engine implemented by rule programming, the rule engine comprising a set of rules and a processing relationship between a plurality of rules in the set of rules; and executing the downloaded programming instructions comprises applying the rule engine to product and order information to determine applicability of the discount type and a discount value when the discount type is applicable to the order. | 0.5 |
7,522,967 | 1 | 20 | 1. An audio processing method, comprising: identifying audio summaries of respective audio pieces, wherein each of the audio summaries comprises digital content summarizing at least a portion of the respective audio piece, and the identifying comprises for each of the audio pieces selecting constituent segments of the audio piece as its respective ones of the audio summaries and ranking its audio summaries into different levels of a respective audio summary hierarchy; determining transition audio segments each comprising a form of audio content that is different from the audio summaries and distinguishes the transition audio segment from the audio summaries; concatenating the transition audio segments and ones of the audio summaries ranked at a selected level of the audio summary hierarchies into a sequence in which at least one of the transition audio segments is between successive ones of the audio summaries; and rendering the sequence. | 1. An audio processing method, comprising: identifying audio summaries of respective audio pieces, wherein each of the audio summaries comprises digital content summarizing at least a portion of the respective audio piece, and the identifying comprises for each of the audio pieces selecting constituent segments of the audio piece as its respective ones of the audio summaries and ranking its audio summaries into different levels of a respective audio summary hierarchy; determining transition audio segments each comprising a form of audio content that is different from the audio summaries and distinguishes the transition audio segment from the audio summaries; concatenating the transition audio segments and ones of the audio summaries ranked at a selected level of the audio summary hierarchies into a sequence in which at least one of the transition audio segments is between successive ones of the audio summaries; and rendering the sequence. 20. The method of claim 1 , further comprising following a pointer from a given audio summary being rendered to a location in an associated audio piece specified by the pointer, and rendering the associated audio piece beginning at the specified location. | 0.729299 |
9,009,220 | 24 | 30 | 24. A method comprising: at a provider entity: storing data on a data storage system on behalf of a client entity, the data being accessible from the data storage system by the client entity; identifying, among the data, electronic communications at least some of which each include data identifying a sender or a receiver, the sender or receiver being an individual associated with the client entity; analyzing the data at discrete intervals, including: identifying one or more words or phrases that occur in one or more of the electronic communications and meet a threshold frequency of occurrence, and comparing the identified words or phrases to one or more words or phrases occurring in electronic communications analyzed at multiple previous discrete intervals; and at times determined by the provider, generating results of the analysis for use by the client entity at times determined based on the results of the analysis and the user's preferences for receiving information, the results indicating a characteristic of at least one of the individuals associated with the client entity, the characteristic being related to at least one of the identified words or phrases. | 24. A method comprising: at a provider entity: storing data on a data storage system on behalf of a client entity, the data being accessible from the data storage system by the client entity; identifying, among the data, electronic communications at least some of which each include data identifying a sender or a receiver, the sender or receiver being an individual associated with the client entity; analyzing the data at discrete intervals, including: identifying one or more words or phrases that occur in one or more of the electronic communications and meet a threshold frequency of occurrence, and comparing the identified words or phrases to one or more words or phrases occurring in electronic communications analyzed at multiple previous discrete intervals; and at times determined by the provider, generating results of the analysis for use by the client entity at times determined based on the results of the analysis and the user's preferences for receiving information, the results indicating a characteristic of at least one of the individuals associated with the client entity, the characteristic being related to at least one of the identified words or phrases. 30. The method of claim 24 comprising: receiving, from the client entity, data of distinct data systems associated with the client entity; processing the data from the distinct data systems for storage on the data storage system; and enabling access by the client entity to the processed data and by an analysis engine associated with the data storage system. | 0.629132 |
10,013,490 | 17 | 18 | 17. The method of claim 14 , further comprising: identifying, via the at least one computing device, an account associated with the client device; and selecting, via the at least one computing device, the at least one of the plurality of application search results based at least in part on determining that the account is configured to purchase the item. | 17. The method of claim 14 , further comprising: identifying, via the at least one computing device, an account associated with the client device; and selecting, via the at least one computing device, the at least one of the plurality of application search results based at least in part on determining that the account is configured to purchase the item. 18. The method of claim 17 , wherein selecting the at least one of the plurality of application search results further comprises ranking, via the at least one computing device, the at least one of the plurality of application search results based at least in part on determining that the account is configured to purchase the item. | 0.5 |
8,108,216 | 2 | 3 | 2. The system according to claim 1 , further comprising: a first storage unit including a plurality of storage mediums with different data acquisition speeds, which store a plurality of speech units, respectively; and a second storage unit configured to store information indicating in which one of said plurality of storage mediums each of the speech units is stored, and wherein the concatenation unit is further configured to acquire the plurality of speech units from the first storage unit in accordance with the information before concatenating the plurality of speech units, and wherein the second calculation unit is configured to calculate the penalty coefficient for each of said plurality of third speech unit strings based on a restriction concerning quickness of data acquisition which is to be satisfied when the speech units included in the first speech unit string are acquired from the first storage unit by the concatenation unit and a statistic determined depending on which one of said plurality of storage mediums each of all speech units included in the third speech unit string is stored in. | 2. The system according to claim 1 , further comprising: a first storage unit including a plurality of storage mediums with different data acquisition speeds, which store a plurality of speech units, respectively; and a second storage unit configured to store information indicating in which one of said plurality of storage mediums each of the speech units is stored, and wherein the concatenation unit is further configured to acquire the plurality of speech units from the first storage unit in accordance with the information before concatenating the plurality of speech units, and wherein the second calculation unit is configured to calculate the penalty coefficient for each of said plurality of third speech unit strings based on a restriction concerning quickness of data acquisition which is to be satisfied when the speech units included in the first speech unit string are acquired from the first storage unit by the concatenation unit and a statistic determined depending on which one of said plurality of storage mediums each of all speech units included in the third speech unit string is stored in. 3. The system according to claim 2 , wherein said plurality of storage mediums include a storage medium with a high data acquisition speed and a storage medium with a low data acquisition speed, and the restriction is an upper limit value of the number of times of acquisition of speech unit data included in the first speech unit string from the storage medium with the low data acquisition speed, and the statistic is a proportion of the number of speech units stored in the storage medium with the low data acquisition speed to the number of speech units included in the third speech unit string. | 0.5 |
7,636,700 | 25 | 28 | 25. A method for object recognition incorporating swarming domain classifiers, the method comprising acts of: initializing, in a processor, an agent swarm for N objects to perform at least one iteration on a domain; evaluating agent classifiers at each agent's location by running the agent swarm to determine a classification value for the domain at each agent's location; computing possibilistic memberships; determining if the number of iterations is less than a predetermined value; if the number of iterations is less than the predetermined value, then updating the agent position and velocity according to a velocity update technique; if the number of iterations is greater than the predetermined value, then updating the agent positions and velocity according to a possibilistic update technique; determining if the number of iterations has reached a predetermined maximum number of iterations; if the number of iterations is greater than or equal to the predetermined maximum number of iterations, then loading a new domain into the swarming domain classifier; if the number of iterations is less than the predetermined number of iterations, then continue running the swarming domain classifier on the domain at the step for evaluating agent classifiers at each location by running the classifier to determine a classification value for the domain at each agent's location; and wherein in the act of computing possibilistic memberships, possibilistic memberships are calculated according to the following: μ ij = η j η j + d ij 2 , where η j is a dynamic elastic constraint around the jth minima, and d ij 2 is the distance of an ith agent to a jth minima, and where initially η j is unbounded and it is slowly decreased to a small region around the local minima. | 25. A method for object recognition incorporating swarming domain classifiers, the method comprising acts of: initializing, in a processor, an agent swarm for N objects to perform at least one iteration on a domain; evaluating agent classifiers at each agent's location by running the agent swarm to determine a classification value for the domain at each agent's location; computing possibilistic memberships; determining if the number of iterations is less than a predetermined value; if the number of iterations is less than the predetermined value, then updating the agent position and velocity according to a velocity update technique; if the number of iterations is greater than the predetermined value, then updating the agent positions and velocity according to a possibilistic update technique; determining if the number of iterations has reached a predetermined maximum number of iterations; if the number of iterations is greater than or equal to the predetermined maximum number of iterations, then loading a new domain into the swarming domain classifier; if the number of iterations is less than the predetermined number of iterations, then continue running the swarming domain classifier on the domain at the step for evaluating agent classifiers at each location by running the classifier to determine a classification value for the domain at each agent's location; and wherein in the act of computing possibilistic memberships, possibilistic memberships are calculated according to the following: μ ij = η j η j + d ij 2 , where η j is a dynamic elastic constraint around the jth minima, and d ij 2 is the distance of an ith agent to a jth minima, and where initially η j is unbounded and it is slowly decreased to a small region around the local minima. 28. A method for object recognition incorporating swarming domain classifiers as set forth in claim 25 , wherein in the act of updating the agent position and velocity according to a velocity update technique, the velocity update technique is calculated according to the following;
v i ( t )= wv i ( t− 1)+ c 1 *r and( )*( p best− x i ( t− 1))+ c 2 *r and( )*( g best− x i ( t− 1)) x i ( t )= x i ( t− 1)+ v i ( t ), where x i (t) and v i (t) are the position and velocity vectors at time t of the ith agent and c 1 and c 2 are parameters that weight the influence of their respective terms in the velocity update technique, where w is a decay constant, and where the rand( ) function generates a random number, and gbest is used to store a best location among all agents, and pbest is an observed best solution that the agent has identified. | 0.508159 |
9,304,786 | 3 | 5 | 3. The information processing apparatus according to claim 1 , wherein the button name is a character string input by the user, as a name of the user-defined button. | 3. The information processing apparatus according to claim 1 , wherein the button name is a character string input by the user, as a name of the user-defined button. 5. The information processing apparatus according to claim 3 , wherein the character string is a name of a shortcut button used to access a specified website. | 0.673554 |
8,270,587 | 8 | 10 | 8. The communication system according to claim 3 , wherein said at least one recorder is arranged to record speech of said at least one participant in the form of a series of speech blocks per participant, and said phone conference system is arranged to send individual speech blocks to said net meeting processor each time the individual speech block is recorded, said net meeting processor being arranged to include one speech block in each voice clip upon receipt of said one speech block. | 8. The communication system according to claim 3 , wherein said at least one recorder is arranged to record speech of said at least one participant in the form of a series of speech blocks per participant, and said phone conference system is arranged to send individual speech blocks to said net meeting processor each time the individual speech block is recorded, said net meeting processor being arranged to include one speech block in each voice clip upon receipt of said one speech block. 10. The communication system according to claim 8 , wherein said net meeting processor is also arranged to register information as to a location of a cursor in said at least one section as a function of time and to use said information to associate said voice clips with locations in said at least one section. | 0.530303 |
9,317,491 | 16 | 17 | 16. A method of adapting a visual layout of an interactive network document, comprising: providing an extracted visual layout of an interactive network document having a plurality of discrete interactive elements and published in a network accessible storage to be available to a plurality of web browsers installed on a plurality of client terminals; automatically setting for said extracted visual layout, a plurality of relative arrangement rules according to said visual layout, each said relative arrangement rule defines a relation between a layout parameter of one of said plurality of discrete interactive elements and a respective layout parameter of another of said plurality of discrete interactive elements; setting a hierarchical order of said plurality of relative arrangement rules; receiving instructions to adapt said visual layout; generating a layout adjusted interactive network document having an adapted version of said interactive network document by applying said instructions and then applying said plurality of relative arrangement rules in said hierarchical order on at least some of said plurality of discrete interactive elements; and replacing said interactive network document with said layout adjusted interactive network document in said network accessible storage such that said layout adjusted interactive network document is available to said plurality of web browsers. | 16. A method of adapting a visual layout of an interactive network document, comprising: providing an extracted visual layout of an interactive network document having a plurality of discrete interactive elements and published in a network accessible storage to be available to a plurality of web browsers installed on a plurality of client terminals; automatically setting for said extracted visual layout, a plurality of relative arrangement rules according to said visual layout, each said relative arrangement rule defines a relation between a layout parameter of one of said plurality of discrete interactive elements and a respective layout parameter of another of said plurality of discrete interactive elements; setting a hierarchical order of said plurality of relative arrangement rules; receiving instructions to adapt said visual layout; generating a layout adjusted interactive network document having an adapted version of said interactive network document by applying said instructions and then applying said plurality of relative arrangement rules in said hierarchical order on at least some of said plurality of discrete interactive elements; and replacing said interactive network document with said layout adjusted interactive network document in said network accessible storage such that said layout adjusted interactive network document is available to said plurality of web browsers. 17. A non-transitory computer readable medium comprising computer executable instructions adapted to perform the method of claim 16 . | 0.5 |
9,571,870 | 10 | 19 | 10. A non-transitory computer-readable storage medium storing one or more instructions which, when executed by one or more processors, cause the one or more processors to perform steps comprising: receiving, by a server computer, a request from a client computer specifying particular content for a particular account, wherein the particular content is associated with an original audio language; in response to receiving the request, selecting, by the server computer, a preferred audio language and a preferred subtitle language for the particular content based on a particular record of a preference database that maps the original audio language and the particular account to the preferred audio language and the preferred subtitle language; wherein the preference database includes a plurality of records for the particular account, wherein each record of the plurality of records maps a different original audio language to a respective preferred audio language and a respective preferred subtitle language; wherein a first record of the plurality of records maps a first original audio language to a first combination of preferred audio language and preferred subtitle language and a second record of the plurality of records maps a second original audio language to a second combination of preferred audio language and preferred subtitle language, wherein the first original audio language is different than the second original audio language and the first combination is different than the second combination; providing, from the server computer to the client computer, asset identifying data for an asset associated with the particular content, the preferred audio language, and the preferred subtitle language; in response to receiving a message at the server computer from the client computer representing input which specifies a new audio language or a new subtitle language, providing different asset identifying data associated with the particular content and one or more of: the new audio language or the new subtitle language; receiving, by the server computer, one or more messages from the client computer that identify a presented audio language and a presented subtitle language that were presented to a particular user of the particular account in relation to the particular content; in response to a determination that one or more of: the presented audio language differs from the preferred audio language or that the presented subtitle language differs from the preferred subtitle language, the server computer updating the particular record in the preference database to specify that one or more of: the preferred audio language is the presented audio language or the preferred subtitle language is the presented subtitle language; receiving, by the server computer, a second request from the client computer specifying second particular content for the particular account, wherein the second particular content is associated with the original audio language; in response to receiving the request, selecting, by the server computer, a second preferred audio language and a second preferred subtitle language for the second particular content based on the particular record of the preference database for the particular account and the original language, wherein one or more of: the second preferred audio language is the presented audio language of the particular content or the second preferred subtitle language is the presented subtitle language for the particular content; providing, from the server computer to the client computer, second asset identifying data for a second asset associated with the second particular content, the second preferred audio language, and the second preferred subtitle language. | 10. A non-transitory computer-readable storage medium storing one or more instructions which, when executed by one or more processors, cause the one or more processors to perform steps comprising: receiving, by a server computer, a request from a client computer specifying particular content for a particular account, wherein the particular content is associated with an original audio language; in response to receiving the request, selecting, by the server computer, a preferred audio language and a preferred subtitle language for the particular content based on a particular record of a preference database that maps the original audio language and the particular account to the preferred audio language and the preferred subtitle language; wherein the preference database includes a plurality of records for the particular account, wherein each record of the plurality of records maps a different original audio language to a respective preferred audio language and a respective preferred subtitle language; wherein a first record of the plurality of records maps a first original audio language to a first combination of preferred audio language and preferred subtitle language and a second record of the plurality of records maps a second original audio language to a second combination of preferred audio language and preferred subtitle language, wherein the first original audio language is different than the second original audio language and the first combination is different than the second combination; providing, from the server computer to the client computer, asset identifying data for an asset associated with the particular content, the preferred audio language, and the preferred subtitle language; in response to receiving a message at the server computer from the client computer representing input which specifies a new audio language or a new subtitle language, providing different asset identifying data associated with the particular content and one or more of: the new audio language or the new subtitle language; receiving, by the server computer, one or more messages from the client computer that identify a presented audio language and a presented subtitle language that were presented to a particular user of the particular account in relation to the particular content; in response to a determination that one or more of: the presented audio language differs from the preferred audio language or that the presented subtitle language differs from the preferred subtitle language, the server computer updating the particular record in the preference database to specify that one or more of: the preferred audio language is the presented audio language or the preferred subtitle language is the presented subtitle language; receiving, by the server computer, a second request from the client computer specifying second particular content for the particular account, wherein the second particular content is associated with the original audio language; in response to receiving the request, selecting, by the server computer, a second preferred audio language and a second preferred subtitle language for the second particular content based on the particular record of the preference database for the particular account and the original language, wherein one or more of: the second preferred audio language is the presented audio language of the particular content or the second preferred subtitle language is the presented subtitle language for the particular content; providing, from the server computer to the client computer, second asset identifying data for a second asset associated with the second particular content, the second preferred audio language, and the second preferred subtitle language. 19. The non-transitory computer-readable storage medium of claim 10 , wherein the preferred subtitle language is no subtitles. | 0.861842 |
9,336,496 | 1 | 9 | 1. A computer-implemented method for generating a reference set via clustering, comprising the steps of: obtaining a collection of unclassified documents; grouping the unclassified documents into clusters; selecting n-documents from each cluster, comprising: building a hierarchical tree of the clusters; and traversing the hierarchical tree to identify the n-documents, wherein one of the n-documents from each cluster is located closest to a center of that cluster; combining the selected n-documents as reference set candidates assigning a classification code to each of the reference set candidates; and grouping two or more of the reference set candidates as a reference set of classified documents, wherein the steps are performed by a suitably programmed computer. | 1. A computer-implemented method for generating a reference set via clustering, comprising the steps of: obtaining a collection of unclassified documents; grouping the unclassified documents into clusters; selecting n-documents from each cluster, comprising: building a hierarchical tree of the clusters; and traversing the hierarchical tree to identify the n-documents, wherein one of the n-documents from each cluster is located closest to a center of that cluster; combining the selected n-documents as reference set candidates assigning a classification code to each of the reference set candidates; and grouping two or more of the reference set candidates as a reference set of classified documents, wherein the steps are performed by a suitably programmed computer. 9. A method according to claim 1 , further comprising: propagating the classification codes of the selected n-documents to a further set of unclassified documents. | 0.816027 |
8,438,008 | 7 | 11 | 7. A system for generating a transliteration font, comprising: a processor; computer readable memory coupled to the processor; a user interface coupled to the processor; software stored in the computer readable memory and executable by the processor, the software having: means for generating a transliteration database including at least first and second data sets, said first data set including graphic representations of characters of an alphabet of a first language and phonetic data representing phonetic pronunciations associated with each of the characters of the alphabet of the first language, said second data set including graphic representations of characters of an alphabet of a second language and phonetic data representing phonetic pronunciations associated with each of the characters of the alphabet of the second language; means for storing the transliteration database in the computer readable memory; means for inputting a word in the first language, the word including at least one of the characters of the alphabet associated with the first language; means for storing the word in the first language in the computer readable memory; means for generating a phonetic representation of the word in the first language, the phonetic representation including the phonetic data representing the phonetic pronunciation of each of the characters of the alphabet of the first language associated with the word; means for comparing the phonetic representation of the word in the first language with corresponding phonetic data of the second language to generate a phonetic equivalent of each of the characters of the word in the alphabet of the second language; means for visually displaying the word in the first language; means for embedding a visual representation of the phonetic equivalent of each of the characters of the word in the second language directly adjacent each respective displayed character in the first language to form a representation of the word in a transliteration font, wherein the visual representation of the phonetic equivalent of each of the characters is embedded within a visual field of each respective displayed character in the first language and within a visual field of the word; means for storing the representation of the word in the transliteration font in the computer readable memory; and means for displaying the word in the transliteration font. | 7. A system for generating a transliteration font, comprising: a processor; computer readable memory coupled to the processor; a user interface coupled to the processor; software stored in the computer readable memory and executable by the processor, the software having: means for generating a transliteration database including at least first and second data sets, said first data set including graphic representations of characters of an alphabet of a first language and phonetic data representing phonetic pronunciations associated with each of the characters of the alphabet of the first language, said second data set including graphic representations of characters of an alphabet of a second language and phonetic data representing phonetic pronunciations associated with each of the characters of the alphabet of the second language; means for storing the transliteration database in the computer readable memory; means for inputting a word in the first language, the word including at least one of the characters of the alphabet associated with the first language; means for storing the word in the first language in the computer readable memory; means for generating a phonetic representation of the word in the first language, the phonetic representation including the phonetic data representing the phonetic pronunciation of each of the characters of the alphabet of the first language associated with the word; means for comparing the phonetic representation of the word in the first language with corresponding phonetic data of the second language to generate a phonetic equivalent of each of the characters of the word in the alphabet of the second language; means for visually displaying the word in the first language; means for embedding a visual representation of the phonetic equivalent of each of the characters of the word in the second language directly adjacent each respective displayed character in the first language to form a representation of the word in a transliteration font, wherein the visual representation of the phonetic equivalent of each of the characters is embedded within a visual field of each respective displayed character in the first language and within a visual field of the word; means for storing the representation of the word in the transliteration font in the computer readable memory; and means for displaying the word in the transliteration font. 11. The system for generating a transliteration font as recited in claim 7 , wherein the first language is Arabic. | 0.897112 |
10,146,746 | 13 | 17 | 13. The method of claim 1 , wherein the changing of the intermediate blank space includes inserting the intermediate blank space into a row of a table to which the separating position belongs, when the separating position belongs to a display region of content of the table. | 13. The method of claim 1 , wherein the changing of the intermediate blank space includes inserting the intermediate blank space into a row of a table to which the separating position belongs, when the separating position belongs to a display region of content of the table. 17. The method of claim 13 , wherein the content of the content layer is arranged in a single line on the content layer based on the content information. | 0.5 |
8,296,152 | 1 | 19 | 1. A method for distributing a topic notification, comprising: receiving, by a processing device, a first audio stream comprising voice signals generated by a first participant in a voice call speaking with a second participant during a duration of the voice call; detecting, by the processing device, at least one term in the voice signals; determining, by the processing device, at least one topic based on the at least one term; processing the first audio stream to identify an emotion of the first participant; accessing user preference data associated with the first participant, wherein the user reference data precludes to sic notification distribution if at least one particular emotion is identified based on the first audio stream; determining that the emotion is not the at least one particular emotion; distributing the topic notification including the at least one topic and an identification of at least one of the first participant and the second participant to a plurality of destinations in response to determining that the emotion is not the at least one particular emotion; and joining a recipient of the topic notification to the voice call in response to the topic notification. | 1. A method for distributing a topic notification, comprising: receiving, by a processing device, a first audio stream comprising voice signals generated by a first participant in a voice call speaking with a second participant during a duration of the voice call; detecting, by the processing device, at least one term in the voice signals; determining, by the processing device, at least one topic based on the at least one term; processing the first audio stream to identify an emotion of the first participant; accessing user preference data associated with the first participant, wherein the user reference data precludes to sic notification distribution if at least one particular emotion is identified based on the first audio stream; determining that the emotion is not the at least one particular emotion; distributing the topic notification including the at least one topic and an identification of at least one of the first participant and the second participant to a plurality of destinations in response to determining that the emotion is not the at least one particular emotion; and joining a recipient of the topic notification to the voice call in response to the topic notification. 19. The method of claim 1 wherein distributing the topic notification including the at least one topic and the identification of the at least one of the first participant and the second participant to the plurality of destinations further comprises distributing the topic notification including the at least one topic, the identification of the at least one of the first participant and the second participant, and an identification of the emotion to the plurality of destinations. | 0.670548 |
7,512,545 | 1 | 6 | 1. A method for developing an automated speech recognition application persona, comprising: identifying personality traits key to customer satisfaction; assigning values to the identified personality traits; defining a plurality of personality profiles based on the assigned values; evaluating measurable customer satisfaction effects associated with each personality profile; rating the personality profiles regarding their ability to represent key personality traits in one or more selected automated systems wherein the rating includes eliciting sample population feedback following sample population utilization of the personality profiles; varying one or more characteristics of the personality profiles; and evaluating the varied personality profile characteristics to identify characteristics most capable of conveying preferred personality traits. | 1. A method for developing an automated speech recognition application persona, comprising: identifying personality traits key to customer satisfaction; assigning values to the identified personality traits; defining a plurality of personality profiles based on the assigned values; evaluating measurable customer satisfaction effects associated with each personality profile; rating the personality profiles regarding their ability to represent key personality traits in one or more selected automated systems wherein the rating includes eliciting sample population feedback following sample population utilization of the personality profiles; varying one or more characteristics of the personality profiles; and evaluating the varied personality profile characteristics to identify characteristics most capable of conveying preferred personality traits. 6. The method of claim 1 , further comprising identifying personality traits key to customer satisfaction using questionnaires with a sample population. | 0.797333 |
8,234,263 | 16 | 19 | 16. The system for building a dynamic classification dictionary of claim 15 , wherein the composite set of taxonomic nouns includes a list of taxonomic nouns and a document and occurrence count. | 16. The system for building a dynamic classification dictionary of claim 15 , wherein the composite set of taxonomic nouns includes a list of taxonomic nouns and a document and occurrence count. 19. The system for building a dynamic classification dictionary of claim 16 , further comprising: a computing device configured to analyze the aggregate set of taxonomic nouns identified for all documents; and a computing device configured to create a term table based upon the analyzed aggregate set of taxonomic nouns. | 0.5 |
9,477,768 | 1 | 8 | 1. A method of disambiguating online social mentions of a real-world entity, the method including: selecting one or more core entity attributes that represent a real-world entity as a first search attribute set for use in searching biographical sources; receiving, responsive to searching the biographical sources based on the first search attribute set, entity reflections that include supplemental entity attributes for the real-world entity; using a combination of the selected core entity attributes and one or more supplemental entity attributes to define a second search attribute set that is narrower than the first search attribute set; receiving, responsive to searching further web sources based on the second search attribute set, more entity reflections that include meta entity attributes for the real-world entity; and updating the combination to include one or more of the meta entity attributes. | 1. A method of disambiguating online social mentions of a real-world entity, the method including: selecting one or more core entity attributes that represent a real-world entity as a first search attribute set for use in searching biographical sources; receiving, responsive to searching the biographical sources based on the first search attribute set, entity reflections that include supplemental entity attributes for the real-world entity; using a combination of the selected core entity attributes and one or more supplemental entity attributes to define a second search attribute set that is narrower than the first search attribute set; receiving, responsive to searching further web sources based on the second search attribute set, more entity reflections that include meta entity attributes for the real-world entity; and updating the combination to include one or more of the meta entity attributes. 8. The method of claim 1 , further including applying one or more probability distribution functions or joint probability distribution functions to estimate resulting cohort size of entity reflections responsive to the first and second search attribute sets. | 0.776817 |
8,275,769 | 16 | 18 | 16. A system according to claim 15 , further comprising: a calculation module to calculate a number of the voting users for each candidate user and to calculate a number of total users comprising the voting users and non-voting users connected to each candidate user. | 16. A system according to claim 15 , further comprising: a calculation module to calculate a number of the voting users for each candidate user and to calculate a number of total users comprising the voting users and non-voting users connected to each candidate user. 18. A system according to claim 16 , wherein the relevancy score is determined according to an equation f u /F u , where f u is the number of voting users connected to the candidate user and F u is the total number of users connected to the candidate user. | 0.501946 |
9,092,424 | 6 | 15 | 6. In a computing environment, a system comprising; at least one processor; a computer readable storage medium communicatively coupled to the at least one processor and including components comprising; a framework configured to process a webpage to understand one or more entities of the webpage, the framework including a text understanding component and a structure understanding component for enabling bidirectional integration of webpage structure understanding and text understanding in an iterative manner until an iteration similarity stop criterion is met, the text understanding component configured to provide text-related data to the structure understanding component for identifying a structure of the webpage, the structure understanding component configured to use the text-related data and visual layout features of the webpage to produce a labeled block, the text understanding component configured to use the labeled block to understand text of the one or more entities. | 6. In a computing environment, a system comprising; at least one processor; a computer readable storage medium communicatively coupled to the at least one processor and including components comprising; a framework configured to process a webpage to understand one or more entities of the webpage, the framework including a text understanding component and a structure understanding component for enabling bidirectional integration of webpage structure understanding and text understanding in an iterative manner until an iteration similarity stop criterion is met, the text understanding component configured to provide text-related data to the structure understanding component for identifying a structure of the webpage, the structure understanding component configured to use the text-related data and visual layout features of the webpage to produce a labeled block, the text understanding component configured to use the labeled block to understand text of the one or more entities. 15. The system of claim 6 wherein the text understanding component is further configured to detect multiple mentions of an entity. | 0.803625 |
8,751,418 | 15 | 21 | 15. A system comprising: a processor; and a non-transitory computer readable storage medium storing processor-executable computer program instructions that when executed, cause a computer processor to perform operations comprising: receiving focus information descriptive of a search engine advertising campaign from an advertising campaign manager, the focus information comprising two or more keyword search strings, each keyword search string paired with at least one bid parameter, a relative importance of each keyword search string characterized by the at least one bid parameter; accessing a respective consumption history of each of a plurality of entities in a storage; identifying, at an audience selection system, a training set of entities from the storage by examining each of the respective consumption histories for one or more proxy events, each proxy event comprising a keyword search matching at least one of the two or more keyword search strings described in the focus information; weighting each proxy event according to the at least one bid parameter paired with each proxy event's keyword search string; creating a weighted training set by weighting each entity in the training set according to the proxy event weights of the one or more proxy events found in each entity's respective consumption history; building a behavioral model based on the weighted training set; receiving a specified entity's consumption history; and assessing the suitability of the specific entity for selection by applying the behavioral model to the specified entity's consumption history. | 15. A system comprising: a processor; and a non-transitory computer readable storage medium storing processor-executable computer program instructions that when executed, cause a computer processor to perform operations comprising: receiving focus information descriptive of a search engine advertising campaign from an advertising campaign manager, the focus information comprising two or more keyword search strings, each keyword search string paired with at least one bid parameter, a relative importance of each keyword search string characterized by the at least one bid parameter; accessing a respective consumption history of each of a plurality of entities in a storage; identifying, at an audience selection system, a training set of entities from the storage by examining each of the respective consumption histories for one or more proxy events, each proxy event comprising a keyword search matching at least one of the two or more keyword search strings described in the focus information; weighting each proxy event according to the at least one bid parameter paired with each proxy event's keyword search string; creating a weighted training set by weighting each entity in the training set according to the proxy event weights of the one or more proxy events found in each entity's respective consumption history; building a behavioral model based on the weighted training set; receiving a specified entity's consumption history; and assessing the suitability of the specific entity for selection by applying the behavioral model to the specified entity's consumption history. 21. The system of claim 15 wherein the operation of assessing comprises: receiving the consumption history of the specified entity wherein the consumption history of the specified entity is not stored in the storage. | 0.584615 |
9,047,275 | 1 | 6 | 1. A computer-implemented method of aligning fragments of a first text in a first language with corresponding fragments of a second text, which is a translation of the first text into a second language, comprising: preliminarily dividing the first and second texts into fragments; generating a hypothesis about correspondence between at least first fragment in the first text and at least second fragment in the second text; determining estimations reflecting correspondence between the first and the second fragments, wherein each estimation is based at least on a ratio between: (a) a number of words in at least one of the first segment or the second segment; and (b) a number of words in the first fragment that have a corresponding translation in the second fragment according to a normalized one-to-one dictionary; determining a degree of correspondence between the first and the second fragments based on the estimations, including adjusting the estimations by using weight coefficients selected on the basis of heuristics or training; and comparing the degree of correspondence to a predetermined threshold. | 1. A computer-implemented method of aligning fragments of a first text in a first language with corresponding fragments of a second text, which is a translation of the first text into a second language, comprising: preliminarily dividing the first and second texts into fragments; generating a hypothesis about correspondence between at least first fragment in the first text and at least second fragment in the second text; determining estimations reflecting correspondence between the first and the second fragments, wherein each estimation is based at least on a ratio between: (a) a number of words in at least one of the first segment or the second segment; and (b) a number of words in the first fragment that have a corresponding translation in the second fragment according to a normalized one-to-one dictionary; determining a degree of correspondence between the first and the second fragments based on the estimations, including adjusting the estimations by using weight coefficients selected on the basis of heuristics or training; and comparing the degree of correspondence to a predetermined threshold. 6. The method of claim 1 further comprising, if the degree of correspondence is sufficiently significant, then confirming the hypothesis and saving the correspondence of the first and the second fragments, otherwise, changing boundaries of at least one fragment so as to select a new hypothesis. | 0.5 |
9,237,291 | 9 | 10 | 9. A television, comprising: a television screen; a local computer readable medium; at least one of an infrared and radio frequency module to receive wirelessly input signals from a remote control of a user; a microprocessor executable application framework to display on a screen of a television, a search panel, the search panel comprising a search term field to receive a search term and at least one previous set of search terms used by the user in a prior search, wherein selection of the at least one previous set of search terms initiates a search of electronic program guide (“EPG”) information using the at least one previous set of search terms as a first selected set of search terms; a microprocessor executable content aggregation service to access, from a network accessible content source EPG information, the EPG information comprising, for each program, airtime, program name, program channel, and program description; receive a selected set of search terms; perform the search using a second selected set of search terms, the second selected set of search terms being received in the search term field or a selected previous set of search terms, receive local search results, from a local database of the television, the local search results responsive to the second selected set of search terms; and receive non-local search results responsive to the second selected set of search terms from multiple external content sources, the multiple external content sources comprising an Internet site and one or both of cable and satellite content sources other than the Internet site; the non-local search results comprising EPG information corresponding to multiple channels and/or programs, wherein performing the search comprises: providing, by the microprocessor executable content aggregation service, the second selected set of search terms to multiple external content sources, wherein the multiple external content sources comprise a Web site other than the EPG content source; and a microprocessor executable content presentation service operable to open a socket to send the second selected set of search terms to the content aggregation service and provide, by the application framework, the local and non-local search results, over the previously opened socket to one or more users, the providing the local and non-local search results comprising displaying, by the application framework, the local and non-local search results on the television screen; wherein the application framework receives, from a remote control of the user, a program selection from the displayed set of local and non-local search results and changes a current channel to a channel broadcasting the program selection, wherein, when the search session is over, the microprocessor executable content presentation service disconnects the socket. | 9. A television, comprising: a television screen; a local computer readable medium; at least one of an infrared and radio frequency module to receive wirelessly input signals from a remote control of a user; a microprocessor executable application framework to display on a screen of a television, a search panel, the search panel comprising a search term field to receive a search term and at least one previous set of search terms used by the user in a prior search, wherein selection of the at least one previous set of search terms initiates a search of electronic program guide (“EPG”) information using the at least one previous set of search terms as a first selected set of search terms; a microprocessor executable content aggregation service to access, from a network accessible content source EPG information, the EPG information comprising, for each program, airtime, program name, program channel, and program description; receive a selected set of search terms; perform the search using a second selected set of search terms, the second selected set of search terms being received in the search term field or a selected previous set of search terms, receive local search results, from a local database of the television, the local search results responsive to the second selected set of search terms; and receive non-local search results responsive to the second selected set of search terms from multiple external content sources, the multiple external content sources comprising an Internet site and one or both of cable and satellite content sources other than the Internet site; the non-local search results comprising EPG information corresponding to multiple channels and/or programs, wherein performing the search comprises: providing, by the microprocessor executable content aggregation service, the second selected set of search terms to multiple external content sources, wherein the multiple external content sources comprise a Web site other than the EPG content source; and a microprocessor executable content presentation service operable to open a socket to send the second selected set of search terms to the content aggregation service and provide, by the application framework, the local and non-local search results, over the previously opened socket to one or more users, the providing the local and non-local search results comprising displaying, by the application framework, the local and non-local search results on the television screen; wherein the application framework receives, from a remote control of the user, a program selection from the displayed set of local and non-local search results and changes a current channel to a channel broadcasting the program selection, wherein, when the search session is over, the microprocessor executable content presentation service disconnects the socket. 10. The television of claim 9 , wherein the multiple external content sources comprise a plurality of an email server, an instant messaging service, a data service other than a Web site, a blogging service, a social media site, and a Web site other than the foregoing multiple external content sources. | 0.585165 |
9,489,417 | 1 | 11 | 1. A method comprising: causing presentation of a message interface that is used, by a user, to report an issue affecting the user to a content submission system, the message interface including a short text field that receives at least one keyword that summarizes the issue being reported and a separate description field for textual input of a description of the issue being reported; receiving a selection that turns on an auto-search feature, the auto-search feature triggering the content submission system to automatically search a content database in response to completion of entry of the at least one keyword in the short text field that summarizes the issue being reported, the search automatically being performed without receiving a selection of a button that triggers the search; detecting completion of entry of the at least one keyword in the short text field; automatically based on the auto-search feature being turned on and without receiving the selection of a button that triggers the search, performing, using a processor of a machine, the search of a content database for previously submitted content comprising one or more issues reported by other users that matches the at least one keyword that summarizes the issue being reported, the previously submitted content being previously submitted messages reporting issues to the content submission system; and based on the search, causing display of a results list in proximity to the short text field on the message interface, the results list comprising a selectable title and a separately selectable link for each result in the results list that corresponds to the previously submitted content that matches the at least one keyword that summarizes the issue being reported. | 1. A method comprising: causing presentation of a message interface that is used, by a user, to report an issue affecting the user to a content submission system, the message interface including a short text field that receives at least one keyword that summarizes the issue being reported and a separate description field for textual input of a description of the issue being reported; receiving a selection that turns on an auto-search feature, the auto-search feature triggering the content submission system to automatically search a content database in response to completion of entry of the at least one keyword in the short text field that summarizes the issue being reported, the search automatically being performed without receiving a selection of a button that triggers the search; detecting completion of entry of the at least one keyword in the short text field; automatically based on the auto-search feature being turned on and without receiving the selection of a button that triggers the search, performing, using a processor of a machine, the search of a content database for previously submitted content comprising one or more issues reported by other users that matches the at least one keyword that summarizes the issue being reported, the previously submitted content being previously submitted messages reporting issues to the content submission system; and based on the search, causing display of a results list in proximity to the short text field on the message interface, the results list comprising a selectable title and a separately selectable link for each result in the results list that corresponds to the previously submitted content that matches the at least one keyword that summarizes the issue being reported. 11. The method of claim 1 , further comprising: receiving a submission of the new message reporting the issue via the message interface; and storing the submitted new message reporting the issue in the content database, the submitted new message reporting the issue now being previously submitted content for a future search. | 0.73229 |
8,954,364 | 9 | 10 | 9. A computer program product for driving a sensor based application, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising: generating a context hierarchy for the sensor based application, wherein the context hierarchy comprises a plurality of contexts, each context being either a static context having no associated sensors from a sensor network or a dynamic context having at least one associated sensor from the sensor network, wherein the plurality of contexts includes at least one static context and at least one dynamic context; discovering a set of sensors from the sensor network using the context hierarchy, wherein each sensor included in the discovered set of sensors is associated with a dynamic context from among the plurality of contexts, wherein the discovered set of sensors includes only sensors from the sensor network that are needed to meet a goal of the sensor based application; reading data values from the discovered set of sensors; applying the data values read from the discovered set of sensors in the sensor based application; setting a priority for the at least one dynamic context of the plurality of contexts, wherein the priority of the at least one dynamic context is set by a superior context within the context hierarchy, and the priority does not exceed a priority of the superior context; and adjusting the priority of the at least one dynamic context based on an amount of use of the at least one associated sensor corresponding to the at least one dynamic context. | 9. A computer program product for driving a sensor based application, the computer program product comprising a non-transitory computer readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to perform a method comprising: generating a context hierarchy for the sensor based application, wherein the context hierarchy comprises a plurality of contexts, each context being either a static context having no associated sensors from a sensor network or a dynamic context having at least one associated sensor from the sensor network, wherein the plurality of contexts includes at least one static context and at least one dynamic context; discovering a set of sensors from the sensor network using the context hierarchy, wherein each sensor included in the discovered set of sensors is associated with a dynamic context from among the plurality of contexts, wherein the discovered set of sensors includes only sensors from the sensor network that are needed to meet a goal of the sensor based application; reading data values from the discovered set of sensors; applying the data values read from the discovered set of sensors in the sensor based application; setting a priority for the at least one dynamic context of the plurality of contexts, wherein the priority of the at least one dynamic context is set by a superior context within the context hierarchy, and the priority does not exceed a priority of the superior context; and adjusting the priority of the at least one dynamic context based on an amount of use of the at least one associated sensor corresponding to the at least one dynamic context. 10. The computer program product of claim 9 , wherein the method further comprises: setting a level of interest for each of the plurality of contexts, wherein the level of interest of at least one of the plurality of contexts is set by the superior context within the context hierarchy, and the level of interest does not exceed a level of interest of the superior context. | 0.54733 |
9,576,473 | 28 | 30 | 28. The method of claim 18 wherein the client device: to access a pairing server when processing the identification data associated with the sandbox reachable service sharing the public address with the client device, wherein the pairing server performs a discovery lookup of any devices that have announced that they share the public address associated with the client device, and wherein the sandbox reachable service announces itself to the pairing server prior to the establishment of the communication session between the sandboxed application and the sandbox reachable service. | 28. The method of claim 18 wherein the client device: to access a pairing server when processing the identification data associated with the sandbox reachable service sharing the public address with the client device, wherein the pairing server performs a discovery lookup of any devices that have announced that they share the public address associated with the client device, and wherein the sandbox reachable service announces itself to the pairing server prior to the establishment of the communication session between the sandboxed application and the sandbox reachable service. 30. The method of claim 28 further comprising: eliminating a communication through a centralized infrastructure when the sandboxed application and the sandbox reachable service communicate in a shared network common to the client device and the networked device when the communication is established, wherein the shared network is at least one of a local area network, a multicast network, an anycast network, and a multilan network; minimizing a latency in the communication session when the sandboxed application and the sandbox reachable service communicate in the shared network common to the client device and the networked device when the communication is established; and improving privacy in the communication session when the sandboxed application and the sandbox reachable service communicate in the shared network common to the client device and the networked device when the communication is established. | 0.5 |
8,914,361 | 21 | 23 | 21. A non-transitory computer-readable medium storing program code operable to cause one or more computers to perform operations comprising: receiving a source web page document; identifying, by a preprocessor based on formatting information of the source web page document, a plurality of regions contained within the source webpage document, that would be displayed to a user visiting said source web page document, wherein the regions contained within the source webpage document contain content between opening and closing HTML or XML tags; determining at least one local concept expressed in each previously identified region, wherein determining the at least one local concept comprises identifying words in the document and aligning the words with concepts, wherein said at least one local concept expressed in the previously identified region is expressed by two or more words in the region; determining a score for a local concept expressed in each previously-identified region, wherein the score is based on a size of, or an importance associated with, the previously-identified region; analyzing the previously determined at least one local concept of each region to identify and eliminate from consideration one or more local concepts that are unrelated to local concepts of other of said previously identified regions by creating a ranked global list of all of said local concepts; analyzing the previously identified regions to identify and eliminate from consideration one or more regions that are unrelated to regions by comparing a ranked list of local concepts for each of said previously identified regions to said global list; determining a source meaning for the source web page document, wherein the source meaning for the source web page document is a weighted vector of said previously determined local concepts expressed in the source web page document that remain after the eliminations; and matching the source web page document with an item selected from a set of items by comparing the previously determined source meaning and a meaning of the item. | 21. A non-transitory computer-readable medium storing program code operable to cause one or more computers to perform operations comprising: receiving a source web page document; identifying, by a preprocessor based on formatting information of the source web page document, a plurality of regions contained within the source webpage document, that would be displayed to a user visiting said source web page document, wherein the regions contained within the source webpage document contain content between opening and closing HTML or XML tags; determining at least one local concept expressed in each previously identified region, wherein determining the at least one local concept comprises identifying words in the document and aligning the words with concepts, wherein said at least one local concept expressed in the previously identified region is expressed by two or more words in the region; determining a score for a local concept expressed in each previously-identified region, wherein the score is based on a size of, or an importance associated with, the previously-identified region; analyzing the previously determined at least one local concept of each region to identify and eliminate from consideration one or more local concepts that are unrelated to local concepts of other of said previously identified regions by creating a ranked global list of all of said local concepts; analyzing the previously identified regions to identify and eliminate from consideration one or more regions that are unrelated to regions by comparing a ranked list of local concepts for each of said previously identified regions to said global list; determining a source meaning for the source web page document, wherein the source meaning for the source web page document is a weighted vector of said previously determined local concepts expressed in the source web page document that remain after the eliminations; and matching the source web page document with an item selected from a set of items by comparing the previously determined source meaning and a meaning of the item. 23. The non-transitory computer-readable medium of claim 21 , wherein: the matched item comprises a second web page; and the associated content comprises an advertisement. | 0.694643 |
8,762,834 | 24 | 25 | 24. A computer program product, tangibly stored on a non transitory machine readable storage device, for displaying, comprising instructions operable to cause a programmable processor to: display a text file in a parent container object; responsive to selection of the parent container object, display a menu from which one of a set of actions may be selected; responsive to selection of one of the set of actions, extract at least a portion of the text file; generate at least a first child container object that includes the portion of the text file extracted; and generate at least a second child container object that includes remaining portion of the text file remaining as a result of the extracting. | 24. A computer program product, tangibly stored on a non transitory machine readable storage device, for displaying, comprising instructions operable to cause a programmable processor to: display a text file in a parent container object; responsive to selection of the parent container object, display a menu from which one of a set of actions may be selected; responsive to selection of one of the set of actions, extract at least a portion of the text file; generate at least a first child container object that includes the portion of the text file extracted; and generate at least a second child container object that includes remaining portion of the text file remaining as a result of the extracting. 25. The computer program product of claim 24 further comprising instructions operable to cause the programmable processor to: responsive to selection of the first or second child container object, display the menu; and responsive to selection of one of the set of actions, generate and display at least one other container object associated with the first or second child container object. | 0.5 |
9,384,732 | 13 | 14 | 13. The computer-readable storage device of claim 12 , wherein the application-specific VCDF includes different listen for elements that each define a different syntax on how to recognize the voice command based on the command portion. | 13. The computer-readable storage device of claim 12 , wherein the application-specific VCDF includes different listen for elements that each define a different syntax on how to recognize the voice command based on the command portion. 14. The computer-readable storage device of claim 13 , wherein the listen for elements for the command comprises a phrase list parameter that represents any one of a list of items that are defined in a phrase list specified within the application-specific VCDF. | 0.721154 |
10,048,945 | 1 | 3 | 1. A method performed by a device having an operating system and a system library for enhancing operable functionality of a software program, comprising: receiving, by the device, a plurality of input source code files from the software program submitted by a developer; identifying, by the device, one or more candidate code snippets from the plurality of input source code files by comparing source code feature vectors for the plurality of input source code files to library function feature vectors for library functions stored in the system library to identify at least a first candidate code snippet which meets at least a first similarity threshold measure for a first library function stored in the system library, and removing one or more code snippets that do not meet a similarity threshold measure for library functions stored in the system library; identifying, by the device, at least a first validated code snippet from the one or more candidate code snippets that matches a first library function stored in the system memory on the basis of at least first and second matching metrics comprising implementing an input/output matching algorithm for selecting a candidate code snippet which generates the same output as the first library function when both are injected with a shared input; and presenting, to the developer, a library function recommendation comprising the first validated code snippet, the first library function, and instructions for replacing the first validated code snippet with the first library function. | 1. A method performed by a device having an operating system and a system library for enhancing operable functionality of a software program, comprising: receiving, by the device, a plurality of input source code files from the software program submitted by a developer; identifying, by the device, one or more candidate code snippets from the plurality of input source code files by comparing source code feature vectors for the plurality of input source code files to library function feature vectors for library functions stored in the system library to identify at least a first candidate code snippet which meets at least a first similarity threshold measure for a first library function stored in the system library, and removing one or more code snippets that do not meet a similarity threshold measure for library functions stored in the system library; identifying, by the device, at least a first validated code snippet from the one or more candidate code snippets that matches a first library function stored in the system memory on the basis of at least first and second matching metrics comprising implementing an input/output matching algorithm for selecting a candidate code snippet which generates the same output as the first library function when both are injected with a shared input; and presenting, to the developer, a library function recommendation comprising the first validated code snippet, the first library function, and instructions for replacing the first validated code snippet with the first library function. 3. The method of claim 1 , where identifying one or more candidate code snippets comprises pruning the plurality of input source code files by performing natural language processing analysis of the plurality of input source code files to keep each candidate code snippet which meets at least a first similarity threshold measure for a first library function stored in the system library. | 0.505115 |
7,720,657 | 10 | 11 | 10. A computer-implemented method for modeling a target system, the method comprising: identifying a first block that represents multiple component models in a block diagram model of a target system; displaying a user interface in response to a user action indicating a selection of the first block, the user interface including a mechanism that provides the user with the multiple component models; and receiving a user selection that selects a first component model from the multiple component models; incorporating the first component model into the model of the target system using the block; saving the model of the target system that includes the first component model in a memory; switching the first block to represent a second component model in response to a user action indicating a selection of the second component model in the user interface; and incorporating the second component model into the model of the target system by one of copying or referring to the second component model in the block, conditionally evaluating at least a part of the component model, or executing a sequence of modifications to the component model. | 10. A computer-implemented method for modeling a target system, the method comprising: identifying a first block that represents multiple component models in a block diagram model of a target system; displaying a user interface in response to a user action indicating a selection of the first block, the user interface including a mechanism that provides the user with the multiple component models; and receiving a user selection that selects a first component model from the multiple component models; incorporating the first component model into the model of the target system using the block; saving the model of the target system that includes the first component model in a memory; switching the first block to represent a second component model in response to a user action indicating a selection of the second component model in the user interface; and incorporating the second component model into the model of the target system by one of copying or referring to the second component model in the block, conditionally evaluating at least a part of the component model, or executing a sequence of modifications to the component model. 11. The method of claim 10 wherein the component models belong to a category of atmosphere models that include at least a non standard day atmosphere model. | 0.642202 |
4,866,778 | 12 | 14 | 12. A speech recognition system as described in claim 1 wherein: said means for receiving an acoustic description of a portion of speech to be recognized includes means for recording an extended acoustic description of a plurality of successive spoken words; said recognition means includes means for making a determination of which one or more words of a recognition vocabulary most probably correspond to each of a plurality of successive segments of said extended acoustic description. | 12. A speech recognition system as described in claim 1 wherein: said means for receiving an acoustic description of a portion of speech to be recognized includes means for recording an extended acoustic description of a plurality of successive spoken words; said recognition means includes means for making a determination of which one or more words of a recognition vocabulary most probably correspond to each of a plurality of successive segments of said extended acoustic description. 14. A speech recognition system as described in claim 12 wherein: said means for recording an extended acoustic description includes means for recording an extended acoustic description of a plurality of continuously spoken words; said recognition means includes means for making a determination of which one or more words from a recognition vocabulary most probably correspond to successive segments of continuous speech recorded in said extended acoustic description. | 0.550766 |
8,200,663 | 33 | 34 | 33. The method of claim 32 , wherein the reviewer is a second searcher associated with one or more items associated with the query. | 33. The method of claim 32 , wherein the reviewer is a second searcher associated with one or more items associated with the query. 34. The method of claim 33 , wherein the one or more items associated with the query are one or more of a category, a keyword, a profile, and a search query. | 0.5 |
8,694,453 | 4 | 6 | 4. A dialogue control system that uses an ontology that systematically expresses domain knowledge representing concepts and relationships between concepts to be used in questions, determines questions for a user and implements the questions, receives user answers to the questions, and controls a dialogue in accordance with the user answers, wherein the domain knowledge includes the concepts and relationships between concepts, and dialogue progress information that specifies movement relationships from concepts employed in questions to concepts to be employed in subsequent questions, and the dialogue control system includes: a dimension-classified ontology storage unit that stores at least one dimension-classified ontology, for each of dimensions for combinations of conditions, the dimension-classified ontologies differing in domain knowledge content; a basic ontology storage unit that stores a basic ontology including domain knowledge content for when there is no condition; a dimension priority storage unit that stores dimension priorities representing priorities of the respective dimensions; a dimension-classified ontology fetcher that, when a concept in the user answers is specified as a condition, fetches from the dimension-classified ontology storage unit one or more dimension-classified ontologies that meet the specified condition; a multidimensional ontology generator that overwrites the content of the fetched dimension-classified ontologies onto the basic ontology according to the dimension priorities of the dimension priority storage unit, in order from the dimension-classified ontology with the lowest dimension priority, and generates a multidimensional ontology to be used with the condition; and a dialogue controller that decides on a concept to be employed in a subsequent question on the basis of the dialogue progress information of the multidimensional ontology generated by the multidimensional ontology generator, and provides the question to the user. | 4. A dialogue control system that uses an ontology that systematically expresses domain knowledge representing concepts and relationships between concepts to be used in questions, determines questions for a user and implements the questions, receives user answers to the questions, and controls a dialogue in accordance with the user answers, wherein the domain knowledge includes the concepts and relationships between concepts, and dialogue progress information that specifies movement relationships from concepts employed in questions to concepts to be employed in subsequent questions, and the dialogue control system includes: a dimension-classified ontology storage unit that stores at least one dimension-classified ontology, for each of dimensions for combinations of conditions, the dimension-classified ontologies differing in domain knowledge content; a basic ontology storage unit that stores a basic ontology including domain knowledge content for when there is no condition; a dimension priority storage unit that stores dimension priorities representing priorities of the respective dimensions; a dimension-classified ontology fetcher that, when a concept in the user answers is specified as a condition, fetches from the dimension-classified ontology storage unit one or more dimension-classified ontologies that meet the specified condition; a multidimensional ontology generator that overwrites the content of the fetched dimension-classified ontologies onto the basic ontology according to the dimension priorities of the dimension priority storage unit, in order from the dimension-classified ontology with the lowest dimension priority, and generates a multidimensional ontology to be used with the condition; and a dialogue controller that decides on a concept to be employed in a subsequent question on the basis of the dialogue progress information of the multidimensional ontology generated by the multidimensional ontology generator, and provides the question to the user. 6. The dialogue control system according to claim 4 , wherein the domain knowledge specifies at least check texts and link texts for relationships between concepts, the multidimensional ontology generator dynamically changes the check texts and link texts by generating multidimensional ontologies with concepts in the user answers as conditions, and the dialogue controller outputs the dynamically changed check texts and link texts to the user. | 0.590826 |
9,779,084 | 1 | 8 | 1. A system adapted to assist instructors with interactions with students, comprising: a network server comprising a processor and a computer readable medium operably coupled thereto, the computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, where the plurality of instructions comprises: instructions, that when executed, receive a communication posted by a student; instructions, that when executed, receive a communication written by an instructor; instructions, that when executed, apply a psychologically-based linguistic analysis to text of the student communication and instructor communication to predict a likelihood of a student outcome with the instructor; instructions, that when executed, monitor the electronic communication between the instructor and the student to measure instructor performance; instructions, that when executed, apply a scoring algorithm to the measured instructor performance and to the analyzed text of the instructor communication to detect keywords and phrases; instructions, that when executed, generate a score for the instructor communication from the application of the scoring algorithm and from comparison of the detected keywords and phrases with a plurality of keywords and phrases stored in a library; and instructions, that when executed, create an evaluation report that provides guidance to the instructor to facilitate a responsive communication with the student based on the score for the instructor communication, wherein the responsive communication is received on a student device using a modality for the responsive communication based on the predicted likelihood of the student outcome. | 1. A system adapted to assist instructors with interactions with students, comprising: a network server comprising a processor and a computer readable medium operably coupled thereto, the computer readable medium comprising a plurality of instructions stored in association therewith that are accessible to, and executable by, the processor, where the plurality of instructions comprises: instructions, that when executed, receive a communication posted by a student; instructions, that when executed, receive a communication written by an instructor; instructions, that when executed, apply a psychologically-based linguistic analysis to text of the student communication and instructor communication to predict a likelihood of a student outcome with the instructor; instructions, that when executed, monitor the electronic communication between the instructor and the student to measure instructor performance; instructions, that when executed, apply a scoring algorithm to the measured instructor performance and to the analyzed text of the instructor communication to detect keywords and phrases; instructions, that when executed, generate a score for the instructor communication from the application of the scoring algorithm and from comparison of the detected keywords and phrases with a plurality of keywords and phrases stored in a library; and instructions, that when executed, create an evaluation report that provides guidance to the instructor to facilitate a responsive communication with the student based on the score for the instructor communication, wherein the responsive communication is received on a student device using a modality for the responsive communication based on the predicted likelihood of the student outcome. 8. The system of claim 1 , further comprising instructions, that when executed, determine a degree of responsiveness, grammar, clarity, and relevance of the instructor communication. | 0.614407 |
9,602,606 | 10 | 18 | 10. A system for recommending a social event to a user, the system comprising: a memory for storing: a user profile including characteristics of the user's interests, a plurality of user profiles, each user profile of the plurality of user profiles including characteristics of interests of a respective friend of the user; and a plurality of social events; and a processor configured to: periodically receive, from a social event database, updated social events; store the updated social events in the memory; receive, over a communications network, from a media guidance application executed by the processor, a user request for a social event recommendation and a first threshold distance, wherein the media guidance application provides an interface enabling the user to request the social event recommendation and select the first threshold distance; select, in response to receiving the user request, a characteristic of the user's interests from the user profile stored in the memory; compare a social event characteristic associated with the social event of the plurality of social events with the selected characteristic of the user's interests; when the social event characteristic of the social event matches the selected characteristic of the user's interests, determine a length of time between a current time and a start time associated with the social event; when the determined length of time is within a time period, determine a static geographic location based on a predetermined address associated with the user; when the determined length of time is outside the time period, determine a dynamic geographic location by determining a current location of the user based on GPS technology; determine a distance between a location of the social event and the determined geographic location; select the social event when the determined distance is less than a first threshold distance; select a subset of the friends of the user, wherein each of the friends in the subset of the friends has a user profile characteristic matching the social event characteristic, and wherein the user profile characteristic of each of the friends in the subset of friends is determined by accessing the plurality of user profiles stored in the memory; and generate for display, in a display screen of the media guidance application, an identifier of the selected social event to the user in a map region and a plurality of identifiers of the selected subset of the friends. | 10. A system for recommending a social event to a user, the system comprising: a memory for storing: a user profile including characteristics of the user's interests, a plurality of user profiles, each user profile of the plurality of user profiles including characteristics of interests of a respective friend of the user; and a plurality of social events; and a processor configured to: periodically receive, from a social event database, updated social events; store the updated social events in the memory; receive, over a communications network, from a media guidance application executed by the processor, a user request for a social event recommendation and a first threshold distance, wherein the media guidance application provides an interface enabling the user to request the social event recommendation and select the first threshold distance; select, in response to receiving the user request, a characteristic of the user's interests from the user profile stored in the memory; compare a social event characteristic associated with the social event of the plurality of social events with the selected characteristic of the user's interests; when the social event characteristic of the social event matches the selected characteristic of the user's interests, determine a length of time between a current time and a start time associated with the social event; when the determined length of time is within a time period, determine a static geographic location based on a predetermined address associated with the user; when the determined length of time is outside the time period, determine a dynamic geographic location by determining a current location of the user based on GPS technology; determine a distance between a location of the social event and the determined geographic location; select the social event when the determined distance is less than a first threshold distance; select a subset of the friends of the user, wherein each of the friends in the subset of the friends has a user profile characteristic matching the social event characteristic, and wherein the user profile characteristic of each of the friends in the subset of friends is determined by accessing the plurality of user profiles stored in the memory; and generate for display, in a display screen of the media guidance application, an identifier of the selected social event to the user in a map region and a plurality of identifiers of the selected subset of the friends. 18. The system of claim 10 , wherein the processor is further configured to receive further updated social events in response to a change in the determined geographic location. | 0.770833 |
9,569,485 | 13 | 16 | 13. A data processing system for optimizing database transactions, the data processing system comprising: a storage device including a storage medium, wherein the storage device stores computer usable program code; and a processor, wherein the processor executes the computer usable program code, and wherein the computer usable program code comprises: computer usable code for receiving a query, the query specifying (i) a set of predicates supplied to the query and (ii) a minimal number of predicates in the set to be satisfied for a data record to be returned in a query result set; computer usable code for forming a bitwise predicate pattern for each of one of the specified predicates, including forming a unique set of bits for each one of the bitwise predicate patterns, each of the sets of bits having the same number of bits and having only one of the bits turned ON, such that each one of the bitwise predicate patterns uniquely represents a respective one of the predicates, and including forming the set of bits for each one of the bitwise predicate patterns such that the bit that is ON in a set of bits indicates which one of the predicates corresponds to which one of the bitwise predicate patterns; computer usable code for generating a logical expression using the sets of bits of the bitwise predicate patterns; computer usable code for performing operations on the logical expression to optimize the query, thereby producing an optimized query; computer usable code for using the optimized query on a repository stored in a computer readable storage medium to find a set of results satisfying the minimal number of predicates; and computer usable code for rendering the set of results satisfying the minimal number of predicates. | 13. A data processing system for optimizing database transactions, the data processing system comprising: a storage device including a storage medium, wherein the storage device stores computer usable program code; and a processor, wherein the processor executes the computer usable program code, and wherein the computer usable program code comprises: computer usable code for receiving a query, the query specifying (i) a set of predicates supplied to the query and (ii) a minimal number of predicates in the set to be satisfied for a data record to be returned in a query result set; computer usable code for forming a bitwise predicate pattern for each of one of the specified predicates, including forming a unique set of bits for each one of the bitwise predicate patterns, each of the sets of bits having the same number of bits and having only one of the bits turned ON, such that each one of the bitwise predicate patterns uniquely represents a respective one of the predicates, and including forming the set of bits for each one of the bitwise predicate patterns such that the bit that is ON in a set of bits indicates which one of the predicates corresponds to which one of the bitwise predicate patterns; computer usable code for generating a logical expression using the sets of bits of the bitwise predicate patterns; computer usable code for performing operations on the logical expression to optimize the query, thereby producing an optimized query; computer usable code for using the optimized query on a repository stored in a computer readable storage medium to find a set of results satisfying the minimal number of predicates; and computer usable code for rendering the set of results satisfying the minimal number of predicates. 16. The data processing system as claimed in claim 13 , wherein the repository comprises a structured data. | 0.877011 |
8,356,051 | 18 | 19 | 18. A non-transitory computer-readable storage medium having executable computer program instructions embodied therein, comprising: instructions for receiving a search query from a user operating a remote client device; instructions for saving the received search query in a storage medium; instructions for transmitting the saved search query to a remote network search service; instructions for receiving a first search result set from the network search service based on the saved search query; instructions for providing at least a portion of the first search result set to the remote client device; instructions for automatically retransmitting the saved search query to the network search service to obtain an updated search result set; instructions for identifying search results of the updated search result set that were not present in the first search result set; instructions for providing at least the identified search results to the remote client device; instructions for determining a count of the search results of the updated search result set that were not present in the first search result set; instructions for computing a search backoff time based at least in part on the count; and instructions for waiting the computed search backoff time before retransmitting the saved search query to the network search service. | 18. A non-transitory computer-readable storage medium having executable computer program instructions embodied therein, comprising: instructions for receiving a search query from a user operating a remote client device; instructions for saving the received search query in a storage medium; instructions for transmitting the saved search query to a remote network search service; instructions for receiving a first search result set from the network search service based on the saved search query; instructions for providing at least a portion of the first search result set to the remote client device; instructions for automatically retransmitting the saved search query to the network search service to obtain an updated search result set; instructions for identifying search results of the updated search result set that were not present in the first search result set; instructions for providing at least the identified search results to the remote client device; instructions for determining a count of the search results of the updated search result set that were not present in the first search result set; instructions for computing a search backoff time based at least in part on the count; and instructions for waiting the computed search backoff time before retransmitting the saved search query to the network search service. 19. The non-transitory computer-readable storage medium of claim 18 , wherein the computed search backoff time becomes less as the determined count becomes greater. | 0.818985 |
9,513,885 | 1 | 12 | 1. A computer-implemented method comprising: receiving one or more base data files at a platform server; transforming the base data files into one or more application data files, the application data files being defined in a declarative application modeling language, the declarative application modeling language comprising named data elements arranged in a hierarchical structure, the names and structure of the named data elements describing an application user interface and behavior, the declarative application modeling language including a structure for managing rules that define in part the behavior of an application, the rules comprising at least a given action and a given action trigger, the given action being automatically performed by the application upon the occurrence of the given action trigger, the given action trigger being dynamically evaluated during execution of the application and based in part on user actions, wherein the base data files are input into one or more data transformations to yield one or more application data files, each application data file describing a different application user interface and behavior corresponding to different web applications; compiling, by execution of a data processor, each application data file into the corresponding different web applications; and causing the web applications to be served to a browser, wherein the web application caches application states using state identifiers. | 1. A computer-implemented method comprising: receiving one or more base data files at a platform server; transforming the base data files into one or more application data files, the application data files being defined in a declarative application modeling language, the declarative application modeling language comprising named data elements arranged in a hierarchical structure, the names and structure of the named data elements describing an application user interface and behavior, the declarative application modeling language including a structure for managing rules that define in part the behavior of an application, the rules comprising at least a given action and a given action trigger, the given action being automatically performed by the application upon the occurrence of the given action trigger, the given action trigger being dynamically evaluated during execution of the application and based in part on user actions, wherein the base data files are input into one or more data transformations to yield one or more application data files, each application data file describing a different application user interface and behavior corresponding to different web applications; compiling, by execution of a data processor, each application data file into the corresponding different web applications; and causing the web applications to be served to a browser, wherein the web application caches application states using state identifiers. 12. The method as claimed in claim 1 wherein the web application uses position-based relationship modeling to control application behavior. | 0.789394 |
8,521,845 | 1 | 2 | 1. A method of resolving a registered multilingual domain name, the method comprising: receiving, at a primary name server, a request to resolve the registered multilingual domain name that is identified by a sequence of numeric values, wherein the request that was received from a Web browser of a user is based on a specified URL that contains the domain name; determining that the primary name server is unable to identify, in a zone data file of the primary name server, an IP address associated with the sequence of numeric values; selecting a default IP address in response to a failure to identify an associated IP address, the default IP address corresponding to a multilingual domain name server that is able to resolve requests for domain names in multiple languages; determining appropriate response information for the multilingual domain name; and providing an indication of the appropriate response information to the Web browser of the user in response to the request. | 1. A method of resolving a registered multilingual domain name, the method comprising: receiving, at a primary name server, a request to resolve the registered multilingual domain name that is identified by a sequence of numeric values, wherein the request that was received from a Web browser of a user is based on a specified URL that contains the domain name; determining that the primary name server is unable to identify, in a zone data file of the primary name server, an IP address associated with the sequence of numeric values; selecting a default IP address in response to a failure to identify an associated IP address, the default IP address corresponding to a multilingual domain name server that is able to resolve requests for domain names in multiple languages; determining appropriate response information for the multilingual domain name; and providing an indication of the appropriate response information to the Web browser of the user in response to the request. 2. The method of claim 1 , wherein the primary name server is capable of resolving domain names in an ASCII-compatible encoding. | 0.803077 |
9,679,252 | 13 | 19 | 13. A method for performing a context classification with adjustable granularity, the method comprising: receiving a request for the context classification and a granularity input associated with the request, wherein the granularity input indicates a granularity level of a context classification output to identify a subset of available states from which the context classification output is selected, with the subset of available states comprising a number of states determined based on the granularity level indicated by the granularity input, and to determine which data features are collected from data sources to select the context classification output, with the determined data features comprising a number of data features determined based on the granularity level indicated by the granularity input such that fewer data features are used for classification when a first granularity level is indicated than when a second granularity level, larger than the first granularity level, is indicated; selecting a configuration parameter, from a plurality of configuration parameters, for the context classification based on the granularity input, the plurality of configuration parameters comprising different values for different granularity levels indicated by the granularity input, wherein a configuration parameter for a granularity input indicating a high granularity level is associated with a high resource usage level and a configuration parameter for a granularity input indicating a low granularity level is associated with a low resource usage level; and performing the context classification according to the granularity input, indicating the granularity level of the context classification output, by classifying data of the data features collected from the data sources using the selected configuration parameter for the context classification. | 13. A method for performing a context classification with adjustable granularity, the method comprising: receiving a request for the context classification and a granularity input associated with the request, wherein the granularity input indicates a granularity level of a context classification output to identify a subset of available states from which the context classification output is selected, with the subset of available states comprising a number of states determined based on the granularity level indicated by the granularity input, and to determine which data features are collected from data sources to select the context classification output, with the determined data features comprising a number of data features determined based on the granularity level indicated by the granularity input such that fewer data features are used for classification when a first granularity level is indicated than when a second granularity level, larger than the first granularity level, is indicated; selecting a configuration parameter, from a plurality of configuration parameters, for the context classification based on the granularity input, the plurality of configuration parameters comprising different values for different granularity levels indicated by the granularity input, wherein a configuration parameter for a granularity input indicating a high granularity level is associated with a high resource usage level and a configuration parameter for a granularity input indicating a low granularity level is associated with a low resource usage level; and performing the context classification according to the granularity input, indicating the granularity level of the context classification output, by classifying data of the data features collected from the data sources using the selected configuration parameter for the context classification. 19. The method of claim 13 wherein the context classification comprises one or more of a motion state classification, a location state classification, or an audio state classification. | 0.746556 |
8,799,186 | 10 | 19 | 10. A method for computationally performing an online choice model, the method comprising: receiving a plurality of attributes from a user wherein each attribute has an associated plurality of attribute levels; generating a survey experimental design and an associated set of treatments, comprising the steps of: determining the signature of the attribute space from the received plurality of attributes and associated attribute levels; selecting one or more experimental designs from a library of experimental designs; for each selected experimental design; performing one or more transformations until the signature of the transformed experimental design matches the signature of the attribute space to obtain one or more matching transformed experimental designs; wherein each transformation preserves the information properties of the untransformed experimental design; selecting a survey experimental design from the one or more matching transformed experimental designs; obtaining a set of treatments from the selected survey experimental design; assembling an online survey, comprising the steps of: creating a plurality of survey templates pages; creating a plurality of treatment representations based on the set of treatments associated with the survey experimental design; assembling the plurality of survey templates pages and plurality of treatment representations to form an online survey; conducting an online survey, the online survey comprising allocating each treatment to one or more respondents; providing a plurality of combinations of treatments to the one or more respondents; receiving the responses of the one or more respondents; generating a model based upon the received responses to obtain a plurality of model parameter estimates and errors from which a utility estimate can be obtained for each attribute level; and providing a model explorer user interface for allowing the user to enter one or more attribute levels and obtain a model prediction of the expected utility; wherein the one or more transformations comprise one or more of the following group of transformations: factorial splitting of a factor F into two sub factors A, B where A×B=F and A or B match at least one unmatched factor in the signature; factorial expansion of a factor F into a new factor A×F where A×F matches at least one unmatched factor in the signature; factor truncation of a factor F into a new factor F−A where F−A matches at least one unmatched factor in the signature; full factorization by generation of a new factor F where F matches at least one unmatched factor in the signature; and deleting a factor F when all the other factors in the signature are matched. | 10. A method for computationally performing an online choice model, the method comprising: receiving a plurality of attributes from a user wherein each attribute has an associated plurality of attribute levels; generating a survey experimental design and an associated set of treatments, comprising the steps of: determining the signature of the attribute space from the received plurality of attributes and associated attribute levels; selecting one or more experimental designs from a library of experimental designs; for each selected experimental design; performing one or more transformations until the signature of the transformed experimental design matches the signature of the attribute space to obtain one or more matching transformed experimental designs; wherein each transformation preserves the information properties of the untransformed experimental design; selecting a survey experimental design from the one or more matching transformed experimental designs; obtaining a set of treatments from the selected survey experimental design; assembling an online survey, comprising the steps of: creating a plurality of survey templates pages; creating a plurality of treatment representations based on the set of treatments associated with the survey experimental design; assembling the plurality of survey templates pages and plurality of treatment representations to form an online survey; conducting an online survey, the online survey comprising allocating each treatment to one or more respondents; providing a plurality of combinations of treatments to the one or more respondents; receiving the responses of the one or more respondents; generating a model based upon the received responses to obtain a plurality of model parameter estimates and errors from which a utility estimate can be obtained for each attribute level; and providing a model explorer user interface for allowing the user to enter one or more attribute levels and obtain a model prediction of the expected utility; wherein the one or more transformations comprise one or more of the following group of transformations: factorial splitting of a factor F into two sub factors A, B where A×B=F and A or B match at least one unmatched factor in the signature; factorial expansion of a factor F into a new factor A×F where A×F matches at least one unmatched factor in the signature; factor truncation of a factor F into a new factor F−A where F−A matches at least one unmatched factor in the signature; full factorization by generation of a new factor F where F matches at least one unmatched factor in the signature; and deleting a factor F when all the other factors in the signature are matched. 19. The method as claimed in claim 10 , wherein the step of receiving a plurality of attributes from a user further comprises: providing an attribute input user interface for receiving a plurality of attributes from a user for use in performing the online choice model, comprising: one or more attribute zones wherein each attribute zone receives an attribute and a plurality of attribute levels associated with the attribute from the user; and providing a model explorer user interface further comprises: an attribute level selection zone for each attribute in the choice model; wherein each attribute level selection zone allows a user to select one of the associated levels; a prediction output zone which displays an estimate of the predicted response and variability estimate from the online choice model for the current attribute levels selected in the attribute level selection zone. | 0.595455 |
9,620,128 | 56 | 57 | 56. The computationally-implemented method of claim 33 , wherein said facilitating acquisition of adaptation result data that is based on at least one aspect of the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data comprises: facilitating the acquisition of the adaptation result data that is based on at least one aspect of the speech-facilitated transaction, wherein the adaptation result data includes a numeric score that is a computer-generated estimate of a success of the speech-facilitated transaction based on an objective aspect of the speech-facilitated transaction. | 56. The computationally-implemented method of claim 33 , wherein said facilitating acquisition of adaptation result data that is based on at least one aspect of the speech-facilitated transaction and configured to be used in determining whether to modify the adaptation data comprises: facilitating the acquisition of the adaptation result data that is based on at least one aspect of the speech-facilitated transaction, wherein the adaptation result data includes a numeric score that is a computer-generated estimate of a success of the speech-facilitated transaction based on an objective aspect of the speech-facilitated transaction. 57. The computationally-implemented method of claim 56 , wherein said facilitating the acquisition of the adaptation result data that is based on at least one aspect of the speech-facilitated transaction, wherein the adaptation result data includes a numeric score that is a computer-generated estimate of a success of the speech-facilitated transaction based on an objective aspect of the speech-facilitated transaction comprises: facilitating the acquisition of the adaptation result data that is based on at least one aspect of the speech-facilitated transaction, wherein the adaptation result data includes a numeric score that is a computer-generated estimate of a success of the speech-facilitated transaction based on an observed error rate in speech interpretation. | 0.5 |
7,580,926 | 30 | 31 | 30. The method of claim 26 , wherein generating the target vector representing the target comprises: communicating the target as a query to a search engine; accessing one or more original search results returned by the search engine in response to the query; and calculating a value for each of the tokens based at least in part on a first number of appearances of the token in the documents and a second number of appearances of the token in the original search results, wherein the target vector comprises the values calculated for the tokens ordered according to the token order. | 30. The method of claim 26 , wherein generating the target vector representing the target comprises: communicating the target as a query to a search engine; accessing one or more original search results returned by the search engine in response to the query; and calculating a value for each of the tokens based at least in part on a first number of appearances of the token in the documents and a second number of appearances of the token in the original search results, wherein the target vector comprises the values calculated for the tokens ordered according to the token order. 31. The method of claim 30 , wherein mapping the target onto the categories to generate the target categorization vector comprises: determining a category order among the categories; and for each of the categories, calculating a distance between the target vector representing the target and the category signature vector representing the category, wherein the target categorization vector comprises the distances calculated for the categories ordered according to the category order. | 0.5 |
7,793,326 | 44 | 45 | 44. The apparatus of claim 42 , wherein the search request qualification comprises: a search request initiation time; a list of search request content types; and a search request time limit. | 44. The apparatus of claim 42 , wherein the search request qualification comprises: a search request initiation time; a list of search request content types; and a search request time limit. 45. The apparatus of claim 44 , wherein the list of search request content types allows the user to specify one or more of video, audio, software, text, electronic books, and Websites, wherein the search engine server is configured to return search results based on the list of search result content types. | 0.5 |
8,781,813 | 2 | 3 | 2. The article of manufacture of claim 1 , wherein the operations further comprise assigning parameters to the intent categories that control how the associated intent responses are displayed. | 2. The article of manufacture of claim 1 , wherein the operations further comprise assigning parameters to the intent categories that control how the associated intent responses are displayed. 3. The article of manufacture of claim 2 , wherein the operations further comprise associating user parameters with the intent categories that cause a search engine to display different information associated with a user submitting the question or associated with a query history associated with the user submitting the question. | 0.5 |
10,013,766 | 13 | 14 | 13. The computer-implemented method of claim 7 , wherein determining an intent of the user to obtain additional information about the target object comprises determining an intent of the user to obtain additional information about the target object at a future time. | 13. The computer-implemented method of claim 7 , wherein determining an intent of the user to obtain additional information about the target object comprises determining an intent of the user to obtain additional information about the target object at a future time. 14. The computer-implemented method of claim 13 , further comprising creating a timeline that includes the image of the target object. | 0.5 |
6,097,498 | 1 | 5 | 1. A thin layer protocol for printer management, comprising: a native language printer control stream; the printer control stream defining an object-container for recoverable transfer of foreign language objects within the control stream; a parsing engine receiving the control stream; the parsing engine responsive to the object-container for appropriately handling the foreign language objects outside native stream handling; and the thin layer including a first command for creating an instance of the object-container, a second command for building an object for insertion into the object-container, and a third command for terminating the object-container. | 1. A thin layer protocol for printer management, comprising: a native language printer control stream; the printer control stream defining an object-container for recoverable transfer of foreign language objects within the control stream; a parsing engine receiving the control stream; the parsing engine responsive to the object-container for appropriately handling the foreign language objects outside native stream handling; and the thin layer including a first command for creating an instance of the object-container, a second command for building an object for insertion into the object-container, and a third command for terminating the object-container. 5. The thin layer protocol of claim 1, wherein the foreign language object is partitioned, the object-container including a sequence of the partitions, and each partition is preceded by an instance of the second command. | 0.817276 |
8,843,364 | 1 | 3 | 1. A non-transitory computer-readable storage medium storing program instructions, the program instructions being computer-executable to implement: for a first source, generating a model for each word of a plurality of words, each model includes including: a plurality of dictionaries, each of the plurality of dictionaries including one or more spectral components; and probabilities of transition between the plurality of dictionaries; and constraining the models according to high level information that defines valid transitions, the constrained models being usable to perform source separation on a sound mixture that includes multiple sources. | 1. A non-transitory computer-readable storage medium storing program instructions, the program instructions being computer-executable to implement: for a first source, generating a model for each word of a plurality of words, each model includes including: a plurality of dictionaries, each of the plurality of dictionaries including one or more spectral components; and probabilities of transition between the plurality of dictionaries; and constraining the models according to high level information that defines valid transitions, the constrained models being usable to perform source separation on a sound mixture that includes multiple sources. 3. The non-transitory computer-readable storage medium of claim 1 , wherein said generating the model for each word includes performing a non-negative hidden Markov technique. | 0.764785 |
8,781,204 | 31 | 32 | 31. A digital signal processing unit for processing image data of a sample image of at least one region of interest of the surface of a candidate document to be authenticated according to the method of claim 8 , said digital signal processing unit being programmed for performing said digital processing of the sample image. | 31. A digital signal processing unit for processing image data of a sample image of at least one region of interest of the surface of a candidate document to be authenticated according to the method of claim 8 , said digital signal processing unit being programmed for performing said digital processing of the sample image. 32. The digital signal processing unit of claim 31 , implemented as an FPGA (Field-Programmable-Gate-Array) unit. | 0.5 |
8,527,524 | 13 | 14 | 13. The method of claim 8 , where the generated score is a first score, the method further comprising: generating a second score, for the document, that is based on a relevance of the document to a search query; and combining the first and second scores to generate an overall score, where ranking the document includes ranking the document with regard to the at least one other document based on the overall score. | 13. The method of claim 8 , where the generated score is a first score, the method further comprising: generating a second score, for the document, that is based on a relevance of the document to a search query; and combining the first and second scores to generate an overall score, where ranking the document includes ranking the document with regard to the at least one other document based on the overall score. 14. The method of claim 13 , where combining the first and second scores includes: adjusting the second score by an amount that is based on the first score. | 0.5 |
9,201,664 | 1 | 5 | 1. A method for users to give commands directly in computer software to be used in computers and other programmable devices to render them easier to use, the method comprising: receiving a command in text form from a user input interface; searching first for matches the command words and phrases in the command database, which contains command words and phrases in the software as well as synonyms and synonymous phrases to the command words and phrases; determining if a match for the command is found and the matched command is executed; if no match is found, then searching for matches the recorded previous user command inputs in the user command dictionary or database, if a match with previous user command inputs is found, for cases of only one previously executed command corresponding to the matched user command input, the previously executed command is executed, for cases of multiple previously executed commands corresponding to the matched user command input, the previously executed commands are presented with a dynamical user interface for the user to select and execute; wherein the dynamical user interface associates said matched commands with user interface elements through command names or command identifiers dynamically by passing the command name strings and command identifiers to the constructor of the dynamical user interface to replace the displaying names and the command identifiers of the user interface elements; if no match with previous user command inputs is found, finally searching for matches the synonyms and synonymous phrases in the command database, if one or more matches are found, the command or commands corresponding to the match or matches are presented with a dynamical user interface for the user to select and execute, the selection by the user is recorded in the user command database or dictionary; and if a match is still not found, a message stating that the input command cannot be found in the software is displayed to the user. | 1. A method for users to give commands directly in computer software to be used in computers and other programmable devices to render them easier to use, the method comprising: receiving a command in text form from a user input interface; searching first for matches the command words and phrases in the command database, which contains command words and phrases in the software as well as synonyms and synonymous phrases to the command words and phrases; determining if a match for the command is found and the matched command is executed; if no match is found, then searching for matches the recorded previous user command inputs in the user command dictionary or database, if a match with previous user command inputs is found, for cases of only one previously executed command corresponding to the matched user command input, the previously executed command is executed, for cases of multiple previously executed commands corresponding to the matched user command input, the previously executed commands are presented with a dynamical user interface for the user to select and execute; wherein the dynamical user interface associates said matched commands with user interface elements through command names or command identifiers dynamically by passing the command name strings and command identifiers to the constructor of the dynamical user interface to replace the displaying names and the command identifiers of the user interface elements; if no match with previous user command inputs is found, finally searching for matches the synonyms and synonymous phrases in the command database, if one or more matches are found, the command or commands corresponding to the match or matches are presented with a dynamical user interface for the user to select and execute, the selection by the user is recorded in the user command database or dictionary; and if a match is still not found, a message stating that the input command cannot be found in the software is displayed to the user. 5. The method of claim 1 , wherein the dynamical user interface includes a dynamical dialog box which associates said matched commands or command synonyms as string array and their corresponding command identifiers as an integer array with command buttons for the matched commands or matched command synonyms for users to select and execute. | 0.747781 |
9,251,524 | 1 | 20 | 1. A method performed by a document server for updating and/or creating a user profile associated with a user of a client device, wherein the document server comprises a recommender system, the method comprising: (i) transmitting, from the document server to the user, a document containing a set of terms, including a first term and a second term, wherein a document profile corresponding to the document associates the first term with a first term value (vd1) and associates the second term with a second term value (vd2): (ii) after step (i), receiving, at the document server, information identifying a set of two or more actions the user of the client device took with respect to the document, wherein the set of user actions is mapped to an action value (iii) in response to receiving the information, determining, for each term included in the set of terms, a value (v) to associate with the term and associating the determined value (v) with the term, thereby establishing a set of term/value pairs, where each said pair consists of one of said terms and its associated value (v), wherein said determining step comprising determining a first value (v1) for said first term of the document, and determining the first value (v1) for the first term of the document comprises obtaining the action value (a) mapped to the set of actions the user took with respect to the document and then calculating the first value (v1) using the obtained action value (a) and the first term value (vd1); and (iv) storing the set of term/value pairs in the user profile. | 1. A method performed by a document server for updating and/or creating a user profile associated with a user of a client device, wherein the document server comprises a recommender system, the method comprising: (i) transmitting, from the document server to the user, a document containing a set of terms, including a first term and a second term, wherein a document profile corresponding to the document associates the first term with a first term value (vd1) and associates the second term with a second term value (vd2): (ii) after step (i), receiving, at the document server, information identifying a set of two or more actions the user of the client device took with respect to the document, wherein the set of user actions is mapped to an action value (iii) in response to receiving the information, determining, for each term included in the set of terms, a value (v) to associate with the term and associating the determined value (v) with the term, thereby establishing a set of term/value pairs, where each said pair consists of one of said terms and its associated value (v), wherein said determining step comprising determining a first value (v1) for said first term of the document, and determining the first value (v1) for the first term of the document comprises obtaining the action value (a) mapped to the set of actions the user took with respect to the document and then calculating the first value (v1) using the obtained action value (a) and the first term value (vd1); and (iv) storing the set of term/value pairs in the user profile. 20. The method of claim 1 , wherein the method further comprises performing the following steps prior to transmitting the document to the user: obtaining a reduced user vector based on the user profile; obtaining the document profile associated with the document; comparing the reduced user vector with the document vector to produce a similarity value; and determining that a reference to the document should be transmitted to the user based on the similarity value. | 0.5 |
7,657,515 | 19 | 20 | 19. The system of claim 12 , wherein the first and second lists of query terms are represented in said computing system by an AND-OR_N tree that is processed by the software search component. | 19. The system of claim 12 , wherein the first and second lists of query terms are represented in said computing system by an AND-OR_N tree that is processed by the software search component. 20. The system of claim 19 , wherein the AND-OR_N tree is traversed using an OR_N logical operation. | 0.5 |
8,484,014 | 11 | 12 | 11. A computing device for identifying sentences having words of a designated part of speech, comprising: a component that inputs from a user a query having a word and a part of speech, the part of speech representing a wildcard for any word that is that part of speech; a component that identifies sentences that have the word of the query collocated with any word used as the part of speech of the query, the sentences being identified based on mappings from part of speech and word pairs to sentences, the mappings having been generated by a component that: identifies collocated words of sentences; and for each identified pair of collocated words of a sentence, identifies a part of speech of each word of the pair; generates a first part of speech and word pair that includes the identified part of speech of the first word and the second word and a second part of speech and word pair that includes the first word and the identified part of speech of the second word; and generates a mapping from the first part of speech and word pair and the second part of speech and word pair to the sentence; and a component that displays to the user the identified sentences. | 11. A computing device for identifying sentences having words of a designated part of speech, comprising: a component that inputs from a user a query having a word and a part of speech, the part of speech representing a wildcard for any word that is that part of speech; a component that identifies sentences that have the word of the query collocated with any word used as the part of speech of the query, the sentences being identified based on mappings from part of speech and word pairs to sentences, the mappings having been generated by a component that: identifies collocated words of sentences; and for each identified pair of collocated words of a sentence, identifies a part of speech of each word of the pair; generates a first part of speech and word pair that includes the identified part of speech of the first word and the second word and a second part of speech and word pair that includes the first word and the identified part of speech of the second word; and generates a mapping from the first part of speech and word pair and the second part of speech and word pair to the sentence; and a component that displays to the user the identified sentences. 12. The computing of claim 11 wherein the word of the query and the word used as the part of speech are different words. | 0.62963 |
8,316,041 | 1 | 4 | 1. A computer-implemented method comprising: receiving, at a computer device, a collection of text-based strings associated with a document; determining, via the computer device, a set of lexical identifiers for the collection of text-based strings, the set of lexical identifiers comprising one or more lexical identifiers assigned to uniquely represent one or more of the text-based strings of the collection, wherein the one or more lexical identifiers are assigned using a map, wherein, if wholly represented in the map, a text-based string of the collection is represented by a lexical identifier, and, if not wholly represented in the map, the text-based string of the collection is represented using multiple lexical identifiers from the map, wherein the map comprises lexical identifier values such that any text-based string can be represented using either a single lexical identifier or a new lexical identifier created using multiple lexical values of the map. | 1. A computer-implemented method comprising: receiving, at a computer device, a collection of text-based strings associated with a document; determining, via the computer device, a set of lexical identifiers for the collection of text-based strings, the set of lexical identifiers comprising one or more lexical identifiers assigned to uniquely represent one or more of the text-based strings of the collection, wherein the one or more lexical identifiers are assigned using a map, wherein, if wholly represented in the map, a text-based string of the collection is represented by a lexical identifier, and, if not wholly represented in the map, the text-based string of the collection is represented using multiple lexical identifiers from the map, wherein the map comprises lexical identifier values such that any text-based string can be represented using either a single lexical identifier or a new lexical identifier created using multiple lexical values of the map. 4. The method as in claim 1 further comprising processing of the set of lexical identifiers associated with the text-based strings, the processing comprising: for each of multiple lexical identifiers in the set, repeating steps of: selecting a lexical identifier found in the set; and counting a number of occurrences of the selected lexical identifier to identify a number of times a text-based string corresponding to the selected lexical identifier appears in the document. | 0.647407 |
7,996,403 | 1 | 4 | 1. A method for performing a search request for a name among a database including a plurality of names, the method comprising: receiving the search request for the name; evaluating the name to assign a first cultural classification as a preliminary cultural classification to the name, wherein the first cultural classification is selected from a plurality of cultural classifications, each encompassing a respective plurality of cultural sub-classifications; determining a frequency distribution of the name for at least one country associated with at least one of the plurality of cultural sub-classifications encompassed by the preliminary cultural classification; by operation of one or more computer processors, evaluating the preliminary cultural classification associated with the name to assign a final cultural classification to the name, based on the determined frequency distribution of the name for the at least one country, wherein evaluating the preliminary cultural classification comprises: upon determining that only one cultural sub-classification of the plurality of cultural sub-classifications of the preliminary cultural classification is statistically significant, refining the preliminary cultural classification by assigning the one cultural sub-classification to the name as the final cultural classification to the name; upon determining that more than one cultural sub-classification of the plurality of cultural sub-classifications of the preliminary cultural classification is statistically significant, corroborating the preliminary cultural classification by assigning the preliminary cultural classification as the final cultural classification for the name; and upon determining that none of the plurality of cultural sub-classifications of the preliminary cultural classification are statistically significant and that more than one cultural sub-classification of a second cultural classification is statistically significant, overriding the preliminary cultural classification by assigning the second cultural classification to the name as the final cultural classification for the name; and completing the search request by searching for the name among the plurality of names within the database based on the final cultural classification assigned to the name. | 1. A method for performing a search request for a name among a database including a plurality of names, the method comprising: receiving the search request for the name; evaluating the name to assign a first cultural classification as a preliminary cultural classification to the name, wherein the first cultural classification is selected from a plurality of cultural classifications, each encompassing a respective plurality of cultural sub-classifications; determining a frequency distribution of the name for at least one country associated with at least one of the plurality of cultural sub-classifications encompassed by the preliminary cultural classification; by operation of one or more computer processors, evaluating the preliminary cultural classification associated with the name to assign a final cultural classification to the name, based on the determined frequency distribution of the name for the at least one country, wherein evaluating the preliminary cultural classification comprises: upon determining that only one cultural sub-classification of the plurality of cultural sub-classifications of the preliminary cultural classification is statistically significant, refining the preliminary cultural classification by assigning the one cultural sub-classification to the name as the final cultural classification to the name; upon determining that more than one cultural sub-classification of the plurality of cultural sub-classifications of the preliminary cultural classification is statistically significant, corroborating the preliminary cultural classification by assigning the preliminary cultural classification as the final cultural classification for the name; and upon determining that none of the plurality of cultural sub-classifications of the preliminary cultural classification are statistically significant and that more than one cultural sub-classification of a second cultural classification is statistically significant, overriding the preliminary cultural classification by assigning the second cultural classification to the name as the final cultural classification for the name; and completing the search request by searching for the name among the plurality of names within the database based on the final cultural classification assigned to the name. 4. The method of claim 1 , wherein the search request for a name is a search request for a personal name. | 0.902597 |
8,886,636 | 13 | 16 | 13. A server for determining a type of landing page to which to transfer web searchers that enter a particular query, each query related to a landing page that links from an advertisement, the server comprising: a landing page classifier to extract content of each of a plurality of landing pages to be classified, the content comprising words of the landing page; extract text from the content; establish a feature space based on the extracted text, representing the extracted landing page; reduce the feature space by applying a supervised attribute selection technique; and conduct classification training with a computer under a machine learning model using a learning algorithm; and classify a target landing page as one of a plurality of landing page classes; a query classifier coupled with the landing page classifier to determine characteristics of one or more query such that the one or more query is associated with the target landing page based on the class of the landing page being related to the characteristics of the one or more query; and a processor coupled with the landing page and query classifiers to choose whether to retain or to change classification of the target landing page associated with the one or more query based on relative average conversion rates of advertisements on a plurality of previously-classified landing pages when associated with the characteristics of the one or more query, wherein the previously-classified landing pages are different than the landing page, and wherein relative average conversion rates comprise average conversion rates that result for respective classified type of landing page over a period of time. | 13. A server for determining a type of landing page to which to transfer web searchers that enter a particular query, each query related to a landing page that links from an advertisement, the server comprising: a landing page classifier to extract content of each of a plurality of landing pages to be classified, the content comprising words of the landing page; extract text from the content; establish a feature space based on the extracted text, representing the extracted landing page; reduce the feature space by applying a supervised attribute selection technique; and conduct classification training with a computer under a machine learning model using a learning algorithm; and classify a target landing page as one of a plurality of landing page classes; a query classifier coupled with the landing page classifier to determine characteristics of one or more query such that the one or more query is associated with the target landing page based on the class of the landing page being related to the characteristics of the one or more query; and a processor coupled with the landing page and query classifiers to choose whether to retain or to change classification of the target landing page associated with the one or more query based on relative average conversion rates of advertisements on a plurality of previously-classified landing pages when associated with the characteristics of the one or more query, wherein the previously-classified landing pages are different than the landing page, and wherein relative average conversion rates comprise average conversion rates that result for respective classified type of landing page over a period of time. 16. The server of claim 13 , wherein the classifier comprises a web crawler to extract hypertext markup language (HTML) content and a page rendering program to extract text from the HTML content of each landing page to be classified, wherein the machine learning model comprises a support vector machine model, and wherein the learning algorithm comprises a sequential minimal optimization (SMO) algorithm of the support vector machine model. | 0.5 |
7,693,720 | 8 | 10 | 8. The mobile system according to claim 6 , wherein at least one of the one or more devices is connected to the vehicle. | 8. The mobile system according to claim 6 , wherein at least one of the one or more devices is connected to the vehicle. 10. The mobile system according to claim 8 , wherein the at least one device connected to the vehicle includes at least one of a navigation system, a monitoring system, a security system, a control system, or a media system connected to the vehicle. | 0.503984 |
8,571,873 | 7 | 10 | 7. The computer program product of claim 6 , further comprising computer readable program code configured to detect syllable repetition via: aligning syllables; and comparing aligned syllables to detect repeated syllables. | 7. The computer program product of claim 6 , further comprising computer readable program code configured to detect syllable repetition via: aligning syllables; and comparing aligned syllables to detect repeated syllables. 10. The computer program product of claim 7 , wherein comparing aligned syllables further comprises comparing at least two adjacent syllables using syllable level features capturing dynamic variations over syllable duration in at least one of periodicity, frequency content, and energy. | 0.548896 |
9,591,065 | 25 | 32 | 25. A system comprising: a processing device comprising computer memory storing a script containing simple object access protocol (SOAP) commands; and a device associated with an apparatus, the device for executing instructions stored in computer memory to perform operations comprising: receiving the script from the processing device, the script defining one or more variables that are used in execution of the script, at least some of the SOAP commands in the script including corresponding arguments; interpreting the script to execute functions contained in the script; parsing the SOAP commands from the script during execution of the functions; executing the SOAP commands; wherein the apparatus is configured by execution of the SOAP commands and the functions; and wherein the execution of the SOAP commands and the functions comprises passing a variable in the script as an argument to a first SOAP command, returning an output of the first SOAP command to the script, and executing a second SOAP command based on the output. | 25. A system comprising: a processing device comprising computer memory storing a script containing simple object access protocol (SOAP) commands; and a device associated with an apparatus, the device for executing instructions stored in computer memory to perform operations comprising: receiving the script from the processing device, the script defining one or more variables that are used in execution of the script, at least some of the SOAP commands in the script including corresponding arguments; interpreting the script to execute functions contained in the script; parsing the SOAP commands from the script during execution of the functions; executing the SOAP commands; wherein the apparatus is configured by execution of the SOAP commands and the functions; and wherein the execution of the SOAP commands and the functions comprises passing a variable in the script as an argument to a first SOAP command, returning an output of the first SOAP command to the script, and executing a second SOAP command based on the output. 32. The system of claim 25 , wherein the functions comprise a control statement that affects a sequence of execution of the SOAP commands. | 0.759582 |
7,610,290 | 8 | 11 | 8. The method of claim 1 , wherein the parse tree is circulated to each of the selected search providers in a serial fashion in order to complete an aggregate search request involving mutually exclusive content associated with different respective search providers. | 8. The method of claim 1 , wherein the parse tree is circulated to each of the selected search providers in a serial fashion in order to complete an aggregate search request involving mutually exclusive content associated with different respective search providers. 11. The method of claim 8 , further comprising retiring search results, wherein the search results are returned as extensible markup language (“XML”) content. | 0.579787 |
7,870,295 | 3 | 8 | 3. A parser program stored on a non-transitory computer readable medium comprising program code for execution on a computer for processing a bit stream which may contain a plurality of data formats, the parser program including a set of selectable parsers, each adapted for analyzing a specific set of one or more data formats, wherein the parser program includes: instructions for selecting, by a parser selector, a first parser to parse a first component of a bit stream; instructions for parsing, by the first parser, the first component of the bit stream; instructions for identifying, by the first parser, the data format of a second component of the bit stream; and instructions for selecting, by the first parser, a second parser in the set of parsers based on the data format of the second component and for invoking the second parser to parse the second component, wherein said instructions for invoking the second parser includes instructions for inputting the second component to the second parser. | 3. A parser program stored on a non-transitory computer readable medium comprising program code for execution on a computer for processing a bit stream which may contain a plurality of data formats, the parser program including a set of selectable parsers, each adapted for analyzing a specific set of one or more data formats, wherein the parser program includes: instructions for selecting, by a parser selector, a first parser to parse a first component of a bit stream; instructions for parsing, by the first parser, the first component of the bit stream; instructions for identifying, by the first parser, the data format of a second component of the bit stream; and instructions for selecting, by the first parser, a second parser in the set of parsers based on the data format of the second component and for invoking the second parser to parse the second component, wherein said instructions for invoking the second parser includes instructions for inputting the second component to the second parser. 8. The parser program according to claim 3 , further comprising: instructions for identifying, by the second parser, a data format of a third component of the bit stream; and instructions for selecting, by the second parser, a third parser in the set of parsers based on the identified data format of the third component and for invoking the third parser to parse the third component. | 0.5 |
9,626,768 | 2 | 3 | 2. The computer-implemented method of claim 1 , wherein individual models of the plurality of models are generated by applying one or more signals to the image to define the at least one salient region or the at least one invariant region of the image, and wherein the computer-implemented method further comprises: determining a signal score for individual models of the plurality of models; filtering individual models based on the signal score to determine selected models; and displaying a transformation of the selected models, wherein an order of the display of the selected models is based on the signal score. | 2. The computer-implemented method of claim 1 , wherein individual models of the plurality of models are generated by applying one or more signals to the image to define the at least one salient region or the at least one invariant region of the image, and wherein the computer-implemented method further comprises: determining a signal score for individual models of the plurality of models; filtering individual models based on the signal score to determine selected models; and displaying a transformation of the selected models, wherein an order of the display of the selected models is based on the signal score. 3. The computer-implemented method of claim 2 , wherein the signal score is based on a success rating for the plurality of signals that are applied to the image. | 0.5 |
9,967,217 | 1 | 8 | 1. A method for displaying instant messaging messages, comprising: detecting that an instant messaging message to be displayed includes a hyperlink; when the instant messaging message includes the hyperlink, verifying whether the hyperlink matches a predetermined rule based on uniform resource locators (URLs) of a type of service, wherein the predetermined rule comprises assigning each service with an identification (ID) and adding a flag for each type of service; when the hyperlink matches the predetermined rule, pulling out a predetermined type of information of a webpage corresponding to the hyperlink, wherein the predetermined type is identified according to the type of service; inserting a control in a chat window; filling the pulled-out information of the webpage in the inserted control; and displaying, in the chat window, the instant messaging message as well as the control filled with the information of the webpage corresponding to the hyperlink. | 1. A method for displaying instant messaging messages, comprising: detecting that an instant messaging message to be displayed includes a hyperlink; when the instant messaging message includes the hyperlink, verifying whether the hyperlink matches a predetermined rule based on uniform resource locators (URLs) of a type of service, wherein the predetermined rule comprises assigning each service with an identification (ID) and adding a flag for each type of service; when the hyperlink matches the predetermined rule, pulling out a predetermined type of information of a webpage corresponding to the hyperlink, wherein the predetermined type is identified according to the type of service; inserting a control in a chat window; filling the pulled-out information of the webpage in the inserted control; and displaying, in the chat window, the instant messaging message as well as the control filled with the information of the webpage corresponding to the hyperlink. 8. The method according to claim 1 , wherein, after pulling out the information of the webpage corresponding to the hyperlink, the method further comprises: storing the hyperlink and the information of the webpage corresponding to the hyperlink; and when a subsequent instant messaging message to be displayed comprises the hyperlink, displaying the subsequent instant messaging message together with the stored information of the webpage corresponding to the hyperlink. | 0.5 |
9,002,821 | 8 | 10 | 8. A computer-implemented method performed by data processing apparatus comprising one or more computers in data communication, the method comprising: receiving first search results responsive to a search query, each of the search results referencing a resource that can be rendered in a browser application on a user device and including a link to the resource, the first search results generated in response to a search of a first index of resources that can be rendered in the browser application; receiving at least one second search result responsive to the query, the second search result specifying a native application operating independent of a browser application that can operate on the user device, the second search result generated in response to a search of a second index of application pages that can be display on a user device within the native application, wherein the second index includes a combination of a uniform resource identifiers (URI) of the application pages and a unique application identifier that identifies the native application; and providing the first search results and the second search result for display on a user device. | 8. A computer-implemented method performed by data processing apparatus comprising one or more computers in data communication, the method comprising: receiving first search results responsive to a search query, each of the search results referencing a resource that can be rendered in a browser application on a user device and including a link to the resource, the first search results generated in response to a search of a first index of resources that can be rendered in the browser application; receiving at least one second search result responsive to the query, the second search result specifying a native application operating independent of a browser application that can operate on the user device, the second search result generated in response to a search of a second index of application pages that can be display on a user device within the native application, wherein the second index includes a combination of a uniform resource identifiers (URI) of the application pages and a unique application identifier that identifies the native application; and providing the first search results and the second search result for display on a user device. 10. The computer-implemented method of claim 8 , wherein the second search result includes text of an application page, the text being responsive to the search query and describing content that is relevant to the search query. | 0.723039 |
9,690,982 | 10 | 11 | 10. A system for using self-referential movement data compressed by principal joint variable analysis to identify a movement of a human object or a non human object relating to betting or game activity, the system comprising: a classifier configured to receive a stream of reference frames from a detector unit, the stream of reference frames comprising a set of self-referential movement data points provided in three dimensions, each self-referential movement data point identifying locations or positions of one or more parts of a body of the human object or the non human object with respect to a reference point on the body of the human object or the non human object with respect to a particular dimension of the three dimensions; the classifier configured to determine that a subset of the set of self-referential movement data points is sufficient to recognize a reference movement relating to betting or game activity; the classifier configured to generate a feature matrix, each row of the feature matrix (i) representative of a particular location or position of the one or more parts of the body, and (ii) having at least three cells, each cell storing a self-referential movement data point of the set of self-referential movement data points corresponding to the particular location or position of the one or more parts of the body in one of the three dimensions; the classifier configured to transform the feature matrix into a compressed feature matrix using a principal joint variable analysis function at a pre-defined variance threshold, collapsing the feature matrix by reducing the three-dimensional data set into a two-dimensional data set or a single-dimensional data set, the compressed feature matrix maintaining only the rows of the feature matrix having a corresponding variance greater than the pre-defined variance threshold; a data storage configured to store the compressed feature matrix representative of the reference movement; and a recognizer configured to receive a new stream of frames including new self-referential movement data points, each new self-referential movement data point identifying a location of a part of a body of a new human object or the new non human object with respect to the reference point on the body of the new human object or the new non human object and recognizing that the movement of the new human object or the new non human object corresponds to the reference movement when the new self-referential movement data points corresponding to the compressed feature matrix only vary from the data set of the compressed feature matrix within a pre-defined recognition threshold. | 10. A system for using self-referential movement data compressed by principal joint variable analysis to identify a movement of a human object or a non human object relating to betting or game activity, the system comprising: a classifier configured to receive a stream of reference frames from a detector unit, the stream of reference frames comprising a set of self-referential movement data points provided in three dimensions, each self-referential movement data point identifying locations or positions of one or more parts of a body of the human object or the non human object with respect to a reference point on the body of the human object or the non human object with respect to a particular dimension of the three dimensions; the classifier configured to determine that a subset of the set of self-referential movement data points is sufficient to recognize a reference movement relating to betting or game activity; the classifier configured to generate a feature matrix, each row of the feature matrix (i) representative of a particular location or position of the one or more parts of the body, and (ii) having at least three cells, each cell storing a self-referential movement data point of the set of self-referential movement data points corresponding to the particular location or position of the one or more parts of the body in one of the three dimensions; the classifier configured to transform the feature matrix into a compressed feature matrix using a principal joint variable analysis function at a pre-defined variance threshold, collapsing the feature matrix by reducing the three-dimensional data set into a two-dimensional data set or a single-dimensional data set, the compressed feature matrix maintaining only the rows of the feature matrix having a corresponding variance greater than the pre-defined variance threshold; a data storage configured to store the compressed feature matrix representative of the reference movement; and a recognizer configured to receive a new stream of frames including new self-referential movement data points, each new self-referential movement data point identifying a location of a part of a body of a new human object or the new non human object with respect to the reference point on the body of the new human object or the new non human object and recognizing that the movement of the new human object or the new non human object corresponds to the reference movement when the new self-referential movement data points corresponding to the compressed feature matrix only vary from the data set of the compressed feature matrix within a pre-defined recognition threshold. 11. The system of claim 10 , wherein the recognizer further identifies, within a first threshold of accuracy, that at least a first self-referential new movement data point matches at least one self-referential movement data point of the compressed feature matrix. | 0.767606 |
8,341,665 | 26 | 28 | 26. A wireless communication terminal, comprising: a communication session interface configured to conduct at least one of audio and video media communication sessions with remote terminals, over a wireless link; a display; an earphone interface; and a processor configured to display advertisements on the terminal responsive to whether an earphone is coupled to the earphone interface. | 26. A wireless communication terminal, comprising: a communication session interface configured to conduct at least one of audio and video media communication sessions with remote terminals, over a wireless link; a display; an earphone interface; and a processor configured to display advertisements on the terminal responsive to whether an earphone is coupled to the earphone interface. 28. A terminal according to claim 26 , wherein the processor is configured to track the amount of time that advertisements were displayed while an earphone was coupled to the earphone interface. | 0.5 |
10,127,022 | 1 | 21 | 1. A method comprising: providing a development environment for a dataflow programming language allowing specifying of at least one matcher state machine that can perform pattern matching in a received input stream and generate output data, wherein the development environment comprises a plurality of tools to perform at least one of the following: identifying a plurality of potential data streams; identifying a set of reactive functions and parameters corresponding to patterns of data in the streams; identifying a set of handling functions and parameters for transforming data matching declared patterns; identifying a set of timed events against which patterns of data flow are compared; creating a dataflow program from expressed intent which describes the identified streams, reactions, functions, and timed events; providing the dataflow program as input to a two-phase translation tool comprising a first-phase translation tool incorporating a matcher generator for translating program statements to corresponding matchers, data flow topologies, functions, and related symbolic components, and a second-phase translation tool for generating optimized platform-specific hardware instructions corresponding to the translated statements for execution on a hardware platform; and receiving the output of each phase of the translation tool. | 1. A method comprising: providing a development environment for a dataflow programming language allowing specifying of at least one matcher state machine that can perform pattern matching in a received input stream and generate output data, wherein the development environment comprises a plurality of tools to perform at least one of the following: identifying a plurality of potential data streams; identifying a set of reactive functions and parameters corresponding to patterns of data in the streams; identifying a set of handling functions and parameters for transforming data matching declared patterns; identifying a set of timed events against which patterns of data flow are compared; creating a dataflow program from expressed intent which describes the identified streams, reactions, functions, and timed events; providing the dataflow program as input to a two-phase translation tool comprising a first-phase translation tool incorporating a matcher generator for translating program statements to corresponding matchers, data flow topologies, functions, and related symbolic components, and a second-phase translation tool for generating optimized platform-specific hardware instructions corresponding to the translated statements for execution on a hardware platform; and receiving the output of each phase of the translation tool. 21. The method of claim 1 wherein the timed events comprise intervals of time in which data are to be collected. | 0.916418 |
9,959,318 | 1 | 5 | 1. A method comprising, by a computing system: receiving, from a client system of a first user of an online social network, an indication of the first user accessing a query field associated with a currently accessed page of the online social network, the online social network being associated with a plurality of entities, wherein the currently accessed page is a unique profile page of a particular entity of the plurality of entities; identifying the particular entity of the plurality of entities corresponding to the profile page generating one or more structured queries based on the particular entity corresponding to the profile page, each structured query comprising a reference to the particular entity corresponding to the profile page and one or more additional query tokens; and sending, to the client system of the first user, responsive to the user accessing the query field, instructions for displaying one or more suggested queries on the page, wherein the one or more suggested queries correspond to one or more of the structured queries, respectively, and wherein each suggested query that is displayed is selectable by the first user to retrieve search results corresponding to the selected query. | 1. A method comprising, by a computing system: receiving, from a client system of a first user of an online social network, an indication of the first user accessing a query field associated with a currently accessed page of the online social network, the online social network being associated with a plurality of entities, wherein the currently accessed page is a unique profile page of a particular entity of the plurality of entities; identifying the particular entity of the plurality of entities corresponding to the profile page generating one or more structured queries based on the particular entity corresponding to the profile page, each structured query comprising a reference to the particular entity corresponding to the profile page and one or more additional query tokens; and sending, to the client system of the first user, responsive to the user accessing the query field, instructions for displaying one or more suggested queries on the page, wherein the one or more suggested queries correspond to one or more of the structured queries, respectively, and wherein each suggested query that is displayed is selectable by the first user to retrieve search results corresponding to the selected query. 5. The method of claim 1 , wherein the profile page is a profile page of the online social network corresponding to a concept or a user of the online social network. | 0.797794 |
8,527,446 | 11 | 15 | 11. A computer-implemented method comprising: selecting one or more business terms, wherein each of the one or more selected business terms corresponds to one or more standardized business definitions; identifying one or more data structures utilized by a first enforcement system that are equivalent to the one or more selected business terms; identifying one of the one or more native rules utilized by the first enforcement system that includes at least one of the one or more equivalent data structures, the identified native rule written in a first enforcement system-specific format; and creating a mapping entry that maps the identified native rule to a selected one of the canonical rules, wherein the selected canonical rule includes one or more of the one more selected business terms, and wherein the selected canonical rule is written in a canonical format that is independent from the first enforcement system-specific format. | 11. A computer-implemented method comprising: selecting one or more business terms, wherein each of the one or more selected business terms corresponds to one or more standardized business definitions; identifying one or more data structures utilized by a first enforcement system that are equivalent to the one or more selected business terms; identifying one of the one or more native rules utilized by the first enforcement system that includes at least one of the one or more equivalent data structures, the identified native rule written in a first enforcement system-specific format; and creating a mapping entry that maps the identified native rule to a selected one of the canonical rules, wherein the selected canonical rule includes one or more of the one more selected business terms, and wherein the selected canonical rule is written in a canonical format that is independent from the first enforcement system-specific format. 15. The method of claim 11 further comprising: retrieving usage information corresponding to a second native rule included in the plurality of rules; analyzing the usage information; in response to analyzing the usage information, determining to map the second native rule to the selected one of the canonical rules; and adjusting the created mapping entry by mapping the subsequent native rule to the selected one of the canonical rules. | 0.803235 |
9,262,541 | 1 | 4 | 1. A method performed by data processing apparatus, the method comprising: receiving data specifying a search query, and a location of a user device from which the search query was received; receiving data specifying a set of documents determined to be relevant to the search query, the data specifying, for each of the documents, a respective search score indicative of the relevance of the document to the query and a ranking of the documents according to a first order based on the search scores, and wherein a proper subset of the documents are local documents, wherein each of the local documents is a document that is specified as having local significance to a geographic location of a user device; determining that a first local document in the proper subset of the local documents is eligible for a demotion operation that adjusts the first local document's respective search score to demote the rank of the first local document in the first order, the determination based at least in part on a proximity measure based on the geographic location of the user device and a geographic location specified for the first local document, and in response to the determination: for each second local document in the proper subset of local documents, determining a proximity measure that is based on the geographic location of the user device and the geographic location specified for the second local document; and adjusting the search score of the first local document to demote the first local document's ranking the first order when at least one of the proximity measures indicates a respective second local document has a specified geographic location that is within a threshold distance of the geographic location of the user device. | 1. A method performed by data processing apparatus, the method comprising: receiving data specifying a search query, and a location of a user device from which the search query was received; receiving data specifying a set of documents determined to be relevant to the search query, the data specifying, for each of the documents, a respective search score indicative of the relevance of the document to the query and a ranking of the documents according to a first order based on the search scores, and wherein a proper subset of the documents are local documents, wherein each of the local documents is a document that is specified as having local significance to a geographic location of a user device; determining that a first local document in the proper subset of the local documents is eligible for a demotion operation that adjusts the first local document's respective search score to demote the rank of the first local document in the first order, the determination based at least in part on a proximity measure based on the geographic location of the user device and a geographic location specified for the first local document, and in response to the determination: for each second local document in the proper subset of local documents, determining a proximity measure that is based on the geographic location of the user device and the geographic location specified for the second local document; and adjusting the search score of the first local document to demote the first local document's ranking the first order when at least one of the proximity measures indicates a respective second local document has a specified geographic location that is within a threshold distance of the geographic location of the user device. 4. The method of claim 1 , wherein the determination based at least in part on the proximity measure based on the geographic location of the user device and a geographic location specified for the first local document comprises determining that the proximity measure indicates a distance between the geographic location of the user device and a geographic location specified for the first local document exceeds a maximum distance. | 0.632879 |
8,633,838 | 26 | 33 | 26. A computer-implemented method of compressing data, comprising carrying out steps of the computer-implemented method by a computer system with at least a processor and a memory, the computer-implemented steps of the method including: a) receiving a current instance of data in memory comprising an input buffer; b) performing by the processor a repeat pattern replacement (RPR) compression on at least a portion of the current instance of data to store a corresponding RPR processed range at a next available position in a reference log, wherein the RPR compression processing substitutes an RPR item for a consecutive range of symbols, wherein the value of the RPR item is independent of the location of the consecutive range of symbols; and c) performing by the processor a dedupe compression on each RPR processed portion to store a corresponding dedupe processed range at a next available position in a temporary buffer, wherein a dedupe item is substituted for a selected range of consecutive symbols of the RPR processed range if the selected range is verified as recurring, wherein the dedupe item identifies an offset to the location of the prior occurrence of the selected range in a same RPR processed range or a prior RPR processed range from one of the current instance and a prior instance of data in the input buffer; d) making the reference log available for communication to a target computer. | 26. A computer-implemented method of compressing data, comprising carrying out steps of the computer-implemented method by a computer system with at least a processor and a memory, the computer-implemented steps of the method including: a) receiving a current instance of data in memory comprising an input buffer; b) performing by the processor a repeat pattern replacement (RPR) compression on at least a portion of the current instance of data to store a corresponding RPR processed range at a next available position in a reference log, wherein the RPR compression processing substitutes an RPR item for a consecutive range of symbols, wherein the value of the RPR item is independent of the location of the consecutive range of symbols; and c) performing by the processor a dedupe compression on each RPR processed portion to store a corresponding dedupe processed range at a next available position in a temporary buffer, wherein a dedupe item is substituted for a selected range of consecutive symbols of the RPR processed range if the selected range is verified as recurring, wherein the dedupe item identifies an offset to the location of the prior occurrence of the selected range in a same RPR processed range or a prior RPR processed range from one of the current instance and a prior instance of data in the input buffer; d) making the reference log available for communication to a target computer. 33. The computer-implemented method of claim 26 wherein the RPR compression processing replaces any occurrences of a predefined list of symbol patterns with an RPR item. | 0.86371 |
9,047,916 | 3 | 5 | 3. The non-transitory computer-readable recording medium according to claim 2 , wherein the measuring includes measuring appearance frequency with which the word associated with the category appears in the music, and the associating includes associating the category with the appearance frequency. | 3. The non-transitory computer-readable recording medium according to claim 2 , wherein the measuring includes measuring appearance frequency with which the word associated with the category appears in the music, and the associating includes associating the category with the appearance frequency. 5. The non-transitory computer-readable recording medium according to claim 3 , wherein the associating includes calculating, with respect to the category, relative incidence by dividing a value, obtained by adding the appearance frequency to the appearance time, by a value, obtained by adding the total number of words contained in the character information to the total time of the music, and includes associating the category with the relative incidence. | 0.5 |
8,832,200 | 8 | 14 | 8. A computer program product for processing external events in a persistent human-to-human conservational space, the computer program product comprising: a machine readable storage device having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code for persisting a human-to-human conversational space; computer readable program code for posting turns in said persistent human-to-human conversational space; computer readable program code for receiving different notifications of external events, the different notifications of external events indicate events occurring externally to said persistent human-to-human conversational space, the external events including a creation of a timestamp for a file, a creation of a timestamp for a different human-to-human conversational space, a creation of meta-data for a file, a creation of meta-data for a message, and a creation of meta-data for a different human-to-human conversational space; computer readable program code for converting said notifications of external events into respectively different textual descriptions of the different notifications of external events responsive to receiving said notifications of external events; and, computer readable program code for further posting the converted different textual descriptions of the different notifications of external events in said persistent human-to-human conversational space. | 8. A computer program product for processing external events in a persistent human-to-human conservational space, the computer program product comprising: a machine readable storage device having computer readable program code embodied therewith, the computer readable program code comprising: computer readable program code for persisting a human-to-human conversational space; computer readable program code for posting turns in said persistent human-to-human conversational space; computer readable program code for receiving different notifications of external events, the different notifications of external events indicate events occurring externally to said persistent human-to-human conversational space, the external events including a creation of a timestamp for a file, a creation of a timestamp for a different human-to-human conversational space, a creation of meta-data for a file, a creation of meta-data for a message, and a creation of meta-data for a different human-to-human conversational space; computer readable program code for converting said notifications of external events into respectively different textual descriptions of the different notifications of external events responsive to receiving said notifications of external events; and, computer readable program code for further posting the converted different textual descriptions of the different notifications of external events in said persistent human-to-human conversational space. 14. The computer program product of claim 8 , wherein the external events further include a creation of a timestamp for a message, a collaborator entering a collaboration session managed using a collaborative tool, and a collaborator leaving a collaboration session managed using a collaborative tool. | 0.600796 |
6,167,328 | 7 | 8 | 7. The robot language processing apparatus according to claim 4, wherein, an operation interval is recognized on the basis of operation start and end commands in said intermediate code, and one of the displayed lines which corresponds to said operation interval is displayed in a different color or type. | 7. The robot language processing apparatus according to claim 4, wherein, an operation interval is recognized on the basis of operation start and end commands in said intermediate code, and one of the displayed lines which corresponds to said operation interval is displayed in a different color or type. 8. The robot language processing apparatus according to claim 7, wherein, when a line in a start interval and a line in an end interval among the displayed lines are designated by said pointing means, said language processing means establishes an effective interval for an operating command based on the designated lines, and inserting the operating command into said intermediate code in said storage means. | 0.5 |
9,230,040 | 1 | 5 | 1. A method of applying, on a device having a processor, queries to a document set comprising at least one document, respective documents comprising at least one node located at a node path from a root node of the document and having a node identifier and a node value, the method comprising: executing on the processor instructions configured to, upon receiving a query specifying a query node path comprising at least one pair of a query node identifier and a query node value for the node having the query node identifier: identify at least one matching document having at least one matching node comprising, for respective pairs of query node identifiers and query node values, at least one path node in the node path of the matching node that matches the query node identifier and a node value of the path node that matches the query node value; and present at least a portion of the at least one matching document in response to the query. | 1. A method of applying, on a device having a processor, queries to a document set comprising at least one document, respective documents comprising at least one node located at a node path from a root node of the document and having a node identifier and a node value, the method comprising: executing on the processor instructions configured to, upon receiving a query specifying a query node path comprising at least one pair of a query node identifier and a query node value for the node having the query node identifier: identify at least one matching document having at least one matching node comprising, for respective pairs of query node identifiers and query node values, at least one path node in the node path of the matching node that matches the query node identifier and a node value of the path node that matches the query node value; and present at least a portion of the at least one matching document in response to the query. 5. The method of claim 1 : the query node path specifying a query node value range; and identifying the matching documents comprising: identifying at least one matching document having at least one matching node comprising, for respective query node values of the query, at least one path node in the node path of the matching node that matches the query node identifier and a node value within the query node value range. | 0.667717 |
8,468,160 | 13 | 14 | 13. A method of semantic-aware record matching, comprising: receiving a source string record and a target string record; tokenizing the source string record into substrings of variable length to form a first set of tokens with each token of the first set of tokens having a weight, the weight of each token associated with the tokens commonality in the source string record specification; tokenizing the target string record into substrings of variable length to form a second set of tokens with each token of the second set of tokens having a weight, the weight of each token associated with the tokens commonality in the target string record specification; receiving semantic knowledge referring to the tokens of the source string record and target string record; calculating a similarity score for each pairing of the tokens of the first set and the tokens of the second set based on the semantic knowledge and the weight assigned to each of the tokens; calculating an overall similarity score to the source string record and the target string record based on the similarity scores; and matching the source string record and the target string record based on the overall similarity score. | 13. A method of semantic-aware record matching, comprising: receiving a source string record and a target string record; tokenizing the source string record into substrings of variable length to form a first set of tokens with each token of the first set of tokens having a weight, the weight of each token associated with the tokens commonality in the source string record specification; tokenizing the target string record into substrings of variable length to form a second set of tokens with each token of the second set of tokens having a weight, the weight of each token associated with the tokens commonality in the target string record specification; receiving semantic knowledge referring to the tokens of the source string record and target string record; calculating a similarity score for each pairing of the tokens of the first set and the tokens of the second set based on the semantic knowledge and the weight assigned to each of the tokens; calculating an overall similarity score to the source string record and the target string record based on the similarity scores; and matching the source string record and the target string record based on the overall similarity score. 14. The method of claim 13 , wherein token weights reflect importance of each token. | 0.543478 |
9,159,074 | 8 | 12 | 8. A system comprising: a client device configured to display content and comments within a browser and receive and provide instructions over a network; and a network device configured to communicate with the client device over the network and further perform actions, including: receiving the content and a plurality of target object lists from a content author, wherein each target object list identifies a unique subset of content as target objects within the received content and each unique subset differs by at least one target object; receiving a request from the client device for the received content; determining whether a user at the client device is validated by an online social network as having a relationship status with the content author; associating at least one of the plurality of target object lists with the validated user of the client device based in part on the subject matter of the target objects, wherein the associating of the at least one target object list with the validated user of the client device is based on a social network relationship definable by the content author and identified with the client device, and wherein the associating of the at least one target object list with the validated user of the client device is performed by a third party; configuring the target objects in each associated target object list within the received content as available for associating comments; transmitting the received content to the client device over the network, wherein the configured target objects are identifiable within the received content; receiving a comment about one of the identifiable target objects within the received content; in response to detecting a selection of the identifiable target object at the client device, selectively enabling display of the received comment at the client device; receiving another input from the client device; and providing an expanded view of the comment with at least one other comment, and information about users having entered the comments. | 8. A system comprising: a client device configured to display content and comments within a browser and receive and provide instructions over a network; and a network device configured to communicate with the client device over the network and further perform actions, including: receiving the content and a plurality of target object lists from a content author, wherein each target object list identifies a unique subset of content as target objects within the received content and each unique subset differs by at least one target object; receiving a request from the client device for the received content; determining whether a user at the client device is validated by an online social network as having a relationship status with the content author; associating at least one of the plurality of target object lists with the validated user of the client device based in part on the subject matter of the target objects, wherein the associating of the at least one target object list with the validated user of the client device is based on a social network relationship definable by the content author and identified with the client device, and wherein the associating of the at least one target object list with the validated user of the client device is performed by a third party; configuring the target objects in each associated target object list within the received content as available for associating comments; transmitting the received content to the client device over the network, wherein the configured target objects are identifiable within the received content; receiving a comment about one of the identifiable target objects within the received content; in response to detecting a selection of the identifiable target object at the client device, selectively enabling display of the received comment at the client device; receiving another input from the client device; and providing an expanded view of the comment with at least one other comment, and information about users having entered the comments. 12. The system of claim 8 , wherein the network device is operative to perform further actions, including: in response to the selection of the identifiable target object at the client device, enabling the validated user of the client device to enter another comment related to the selected target object, wherein the entered comment is selectively displayable at another client device. | 0.5 |
7,768,513 | 1 | 7 | 1. A method of rendering text on a display screen of a computer device, the computer device including a memory storing an image file, the image file defining an image containing a plurality of glyphs, the plurality of glyphs being arranged horizontally in the image, the memory having stored thereon data regarding the order of said glyphs and width data regarding the width of each of said glyphs, the method comprising the steps of: defining a portion of said image containing one of said plurality of glyphs and excluding at least one other of said plurality of glyphs, including determining the location of said one of said plurality of glyphs within said image and the size of the portion based upon said data regarding the order and said width data; and rendering said portion on the display screen, wherein said plurality of glyphs represent a font in which said width data is not identical for each of said plurality of glyphs, and wherein said width data includes: a single stored standard width for said plurality of glyphs; and the respective stored width of each glyph of said plurality of glyphs that deviates from the standard width, and wherein at least one glyph in the image file has the standard width. | 1. A method of rendering text on a display screen of a computer device, the computer device including a memory storing an image file, the image file defining an image containing a plurality of glyphs, the plurality of glyphs being arranged horizontally in the image, the memory having stored thereon data regarding the order of said glyphs and width data regarding the width of each of said glyphs, the method comprising the steps of: defining a portion of said image containing one of said plurality of glyphs and excluding at least one other of said plurality of glyphs, including determining the location of said one of said plurality of glyphs within said image and the size of the portion based upon said data regarding the order and said width data; and rendering said portion on the display screen, wherein said plurality of glyphs represent a font in which said width data is not identical for each of said plurality of glyphs, and wherein said width data includes: a single stored standard width for said plurality of glyphs; and the respective stored width of each glyph of said plurality of glyphs that deviates from the standard width, and wherein at least one glyph in the image file has the standard width. 7. The method of claim 1 , wherein the image of said image file is in PNG format. | 0.815068 |
9,245,024 | 13 | 14 | 13. The system of claim 10 , wherein when extracting the contextual information, the processor extracts keywords and phrases provided in a comment associated with the first video. | 13. The system of claim 10 , wherein when extracting the contextual information, the processor extracts keywords and phrases provided in a comment associated with the first video. 14. The system of claim 13 , wherein the one or more second resources are blog sites, and wherein the comment is provided as a blog post at a blog site. | 0.5 |
10,097,482 | 4 | 5 | 4. The method of claim 1 , wherein: the first plurality of input options and the second plurality of input options include a same option associated with switching between user input formats. | 4. The method of claim 1 , wherein: the first plurality of input options and the second plurality of input options include a same option associated with switching between user input formats. 5. The method of claim 4 , wherein: the user input formats comprise a verbal input format and a written input format. | 0.5 |
9,871,714 | 2 | 9 | 2. The method of claim 1 , the analysis of the first node corresponding to the first user and the plurality of user nodes corresponding to the plurality of second users, respectively, comprises: identifying at least one candidate user node of the plurality of second nodes that each correspond to a concept or a second user; comparing at least one first user attribute of the first node to at least one second user attribute of the at least one candidate user node; and including, in the plurality of user nodes corresponding to the plurality of second users, the at least one candidate user node when the at least one first user attribute matches the at least one second user attribute. | 2. The method of claim 1 , the analysis of the first node corresponding to the first user and the plurality of user nodes corresponding to the plurality of second users, respectively, comprises: identifying at least one candidate user node of the plurality of second nodes that each correspond to a concept or a second user; comparing at least one first user attribute of the first node to at least one second user attribute of the at least one candidate user node; and including, in the plurality of user nodes corresponding to the plurality of second users, the at least one candidate user node when the at least one first user attribute matches the at least one second user attribute. 9. The method of claim 2 , wherein the implicit bias of the first user comprises a node-based user bias that includes at least one biasing user attribute of a biasing user node, and at least one biasing-edge type, and wherein the analysis of the first node corresponding to the first user and the plurality of user nodes corresponding to the plurality of second users, respectively, further comprises: when the at least one first user attribute matches the at least one second user attribute: identifying the at least one biasing user attribute based on the first user attribute that matches the at least one second user attribute, and identifying the at least one biasing-edge type based on at least one edge that connects the at least one candidate user node to at least one biased node of the social graph. | 0.513237 |
8,606,786 | 1 | 2 | 1. A method comprising the following computer-executable acts: accessing a data repository in a computing device, wherein the data repository comprises a plurality of queries issued by users of a search engine and sets of search results selected by issuers of respective queries in the plurality of queries; determining, for each query in the plurality of queries, a click distribution over a respective set of search results for a respective query; determining measures of similarity between queries in the plurality of queries based at least in part upon click distributions over the sets of search results for each of the respective queries, wherein a measure of similarity between a first query and a second query is a cosine similarity of click distributions over respective sets of search results for the first query and the second query, the measure of similarity computed as a function of: a first probability that a first searcher that issued the first query will select a first search result; and a second probability that a second searcher that issued the second query will select the first search result, wherein the first probability and the second probability are computed based at least in part upon the click distributions over the sets of search results for each of the respective queries; from amongst unclustered queries in the plurality of queries, selecting a query that is most often submitted to the search engine as a seed query; executing a clustering algorithm over the unclustered queries in the plurality of queries utilizing the seed query, wherein queries from the unclustered queries are placed into a cluster with the seed query if measures of similarity between the seed query and respective unclustered queries are above a threshold; labeling queries in the cluster as being similar queries; and repeating acts of selecting, executing, and labeling until there are no unclustered queries. | 1. A method comprising the following computer-executable acts: accessing a data repository in a computing device, wherein the data repository comprises a plurality of queries issued by users of a search engine and sets of search results selected by issuers of respective queries in the plurality of queries; determining, for each query in the plurality of queries, a click distribution over a respective set of search results for a respective query; determining measures of similarity between queries in the plurality of queries based at least in part upon click distributions over the sets of search results for each of the respective queries, wherein a measure of similarity between a first query and a second query is a cosine similarity of click distributions over respective sets of search results for the first query and the second query, the measure of similarity computed as a function of: a first probability that a first searcher that issued the first query will select a first search result; and a second probability that a second searcher that issued the second query will select the first search result, wherein the first probability and the second probability are computed based at least in part upon the click distributions over the sets of search results for each of the respective queries; from amongst unclustered queries in the plurality of queries, selecting a query that is most often submitted to the search engine as a seed query; executing a clustering algorithm over the unclustered queries in the plurality of queries utilizing the seed query, wherein queries from the unclustered queries are placed into a cluster with the seed query if measures of similarity between the seed query and respective unclustered queries are above a threshold; labeling queries in the cluster as being similar queries; and repeating acts of selecting, executing, and labeling until there are no unclustered queries. 2. The method of claim 1 , wherein the cosine similarity of click distributions is computed by way of the following algorithm: cosine similarity = ∑ i P ( U i ❘ Q A ) P ( U i | Q B ) ∑ i P ( U i ❘ Q A ) 2 ∑ i P ( U i | Q B ) 2 , where U i represents an ith search result, Q A represents the first query, Q B represents the second query, P(U i |Q A ) represents a probability that the search result U i was selected by the first searcher, and P(U i |Q B ) represents the probability that the search result U i was selected by the second searcher. | 0.576233 |
8,140,410 | 1 | 4 | 1. A method, comprising: generating an element mapping in a computer readable storage device for each of a plurality of data mapping user elements and attributes to data pool elements and attributes, wherein data pools maintain product information; generating a message mapping for each of the plurality of data pools mapping user messages and their parameters to data pool messages and their parameters; and maintaining for each of the plurality of data pools code enabled to cause operations comprising receiving a first document including user elements and messages and mapping the user elements and messages in the first document to a second document including data pool elements and attributes corresponding to the user elements and messages in the first document, wherein the first document includes one user message from one retailer requesting product information in one specified data pool; accessing the code for the specified data pool and the message mapping to map the user message and parameters to at least one mapped specified data pool message and parameters to request the product information in the specified data pool; adding the at least one mapped data pool message and parameters to the second document; and transmitting the second document to the specified data pool. | 1. A method, comprising: generating an element mapping in a computer readable storage device for each of a plurality of data mapping user elements and attributes to data pool elements and attributes, wherein data pools maintain product information; generating a message mapping for each of the plurality of data pools mapping user messages and their parameters to data pool messages and their parameters; and maintaining for each of the plurality of data pools code enabled to cause operations comprising receiving a first document including user elements and messages and mapping the user elements and messages in the first document to a second document including data pool elements and attributes corresponding to the user elements and messages in the first document, wherein the first document includes one user message from one retailer requesting product information in one specified data pool; accessing the code for the specified data pool and the message mapping to map the user message and parameters to at least one mapped specified data pool message and parameters to request the product information in the specified data pool; adding the at least one mapped data pool message and parameters to the second document; and transmitting the second document to the specified data pool. 4. The method of claim 1 , wherein the first document is directed to one specified data pool, further comprising: maintaining a message archive for each data pool including messages received from suppliers and retailers directed to each data pool and messages received from the data pool directed to the suppliers or retailers. | 0.73756 |
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